ALBERT

Beschreibung: The influence of size effect on the hydromechanical behavior of rock mass has long been recognized. As a result, analysis of the rock mass size effect has been developed. However, when conducting size effect studies, the representativeness of the sample is less considered. Therefore, combining the existing statistical methods and sampling methods, a comprehensive representative sampling method for rock mass is present. In this method, a large number of sample statistics of different sizes are provided in the progressive coverage method; then, the plane density of the track length is defined as the value of stratification to perform stratified sampling for representative samples. Furthermore, it is applied to a joint network model generated in accordance with the actual situation and compared with those of other methods. The sampling results show that the proposed method can provide a certain reference value for studying the scale-dependent behavior of rock mass mechanical parameters.

Beschreibung: The Linxing area is located in the north of the eastern margin of the Ordos Basin, which has great resource potential for tight gas. In this paper, fluid inclusion analysis and basin modeling are the main means to clarify the gas accumulation mechanism of the Upper Paleozoic in the Linxing area. Petrographic analysis shows that fluid inclusions can be classified into 5 types: aqueous inclusions, hydrocarbon-bearing aqueous inclusions, hydrocarbon inclusions, crystal-bearing aqueous inclusions, and aqueous-carbonic inclusions. According to the statistical analysis of homogenization temperature and salinity of fluid inclusions, combined with the burial-thermal evolution, the study area was divided into 3 areas: the inner-magma baking area, the middle-anomal thermal area, and the outer-normal thermal area. The gas accumulation characteristics are differences among the 3 areas, the closer to Zijinshan magmatic pluton, the earlier gas accumulation period; and the vertical gas accumulation in the inner-magma baking area and the middle-anomal thermal area was not a slow and gradual process from bottom to top. The period from the Middle Jurassic to the Early Cretaceous is the key period for rapid pressure accumulation in the Upper Paleozoic reservoirs, which is consistent with the period of natural gas accumulation. The area near the Zijinshan magmatic pluton was the high fluid potential area during the gas accumulation period, which indicates that natural gas and other fluids migrated from Zijinshan magmatic pluton to the surrounding area. It is concluded that in the Linxing area, the Zijinshan magmatic pluton had a significant impact on natural gas accumulation, and the natural gas accumulation model under the control of magmatic thermal-tectonic effect was proposed.

Beschreibung: With the increasingly close relations between cities in China, it is of great significance to explore the regular characteristics of the intercity connection. Through Tencent’s population migration heat and Baidu map big data, this paper analyzes the regular characteristics of the relations between complex cities based on such index as the rich node propensity index, preference level index, and relative heat index and also investigates the influence of geographical proximity factors on the external relations of different cities. The research has the following results. Firstly, the relations between cities have obvious club characteristics. The rich nodes tend to connect with the rich nodes, while the nonrich nodes tend to connect with the nonrich nodes. Secondly, the connection between cities has the effect of hierarchical proximity, and cities mainly establish spatial connections with cities of the same level and adjacent level. Thirdly, the relations between cities also have the effect of geographical proximity, and the degree of influence of geographical proximity in low-level cities is greater than that in high-level cities. Fourthly, the external connection mode of high-level cities is to establish close contact with high-level cities adjacent to the level, with strong attraction to low-level cities adjacent to the location at the same time. The low-level cities are closely related to the high-level cities adjacent to the location and other cities of geographical proximity or adjacent level. This study helps to further understand the complex characteristics and laws of intercity connections and urban networks.

Beschreibung: The seepage of gas-liquid two-phase flow in fracture is a commonly found phenomenon in nature. To reveal the underlying mechanism and the critical condition of the chaos occurrence, a stochastic gas-liquid two-phase flow seepage model is established, and then investigated through a numerical simulation and a horizontal Hele-Shaw experiment. The numerical simulation and laboratory experiment results show that the seepage chaos of gas-liquid two-phase flow takes place when the relative saturation is in the range of gas relative saturation 44%-70%, and the occurrence probability can be expressed in polynomials. The chaos probability exceeds 80% when the relative saturation of gas is 47%-65%, and the chaos probability is 100% when the relative gas saturation is 57%-60%. It is found that the stochastic variation of gas connection cluster and the compressibility of gas lead to a remarkable change of pressure gradient of the gas-liquid flow both in magnitude and direction. Therefore, the turbulent flow is formed, the kinetic energy of fluid transport decreases gradually, and the flow is stopped at last.

Beschreibung: An effective porosity is defined as the ratio of volume of interconnected pore space to total volume of a porous sample. It controls the magnitude of fluid flow and is a key parameter in the assessment of recoverable resources. However, its accurate measurement in tight formations is challenging, due to their complex pore structure and lithofacies heterogeneity. In this study, porosities of sixteen lacustrine shale samples from the second Member of the Kongdian Formation (Ek2) in the Cangdong Sag, Bohai Bay Basin were measured and compared using multiple methods and sample sizes to compare and contrast the effective porosity results. The methods included helium pycnometry (HP; cubes of 1 cm3 and grains at 500-841 μm), water immersion porosimetry (WIP; cubes), mercury intrusion porosimetry (MIP; cubes), and nuclear magnetic resonance (NMR; cubes). Finally, samples were completely sealed using paraffin for bulk density measurements to evaluate the extent of potential clay swelling in shale samples involving probing fluids. Results from the HP, WIP, and MIP methods for skeletal density, bulk density, and effective porosity with cubic samples were compared. While very similar skeletal densities were found for all three methods, a lower bulk density, and therefore lower porosity, from the MIP approach can be attributed to the experimental conditions (e.g., vacuum efficiency, applied pressure, wettability of water/helium vs. mercury) and the probable presence of pores with diameters larger than 50 μm not measurable by MIP. Furthermore, the HP porosity of granular samples with 500-841 μm grain sizes can be regarded as approaching the total porosity. The complicated relationship between WIP and NMR porosities may result from the heat-induced volatilization of moisture in pores during NMR tests, and countercurrent imbibition of water replacing the residual hydrocarbons during the saturation process for sample preparation in both tests. The swelling behavior of the lacustrine Ek2 shale with water is not significant because of the low content of expansive clay minerals. In summary, the WIP and HP methods are recommended for effective porosity measurement, whereas the NMR and MIP methods are invaluable for the measurement of pore-size distribution, with additional information on the effective porosity.

Beschreibung: The lower Silurian Longmaxi Formation hosts a highly productive shale gas play in the Zhaotong region of southern China. According to core observation, X-ray diffraction analyses, and scanning electron microscopy (SEM) observations, the shale comprises primarily quartz, carbonate minerals, and clay minerals, with minor amounts of plagioclase, K-feldspar, and pyrite. The clay mineral content ranges from 15.0% to 46.1%, with an average of 29.3% in the Zhaotong region. Organic geochemical analyses show that the Longmaxi Formation has good potential for shale gas resources by calculating total organic carbon, vitrinite reflectance, and gas content. Scanning electron microscope images demonstrate that reservoir pore types in the Longmaxi shale include organic pores, interparticle pores, intercrystalline pores, intraparticle pores, and fractures. Reservoir distribution is controlled by lithofacies, mineral composition, and geochemical factors. In addition, we investigated the relationships between reservoir parameters and production from 15 individual wells in the Zhaotong region by correlation coefficients. As a result, the brittleness index, total organic carbon (TOC), porosity, and gas content were used to define high-quality reservoirs in the Longmaxi shale. Based on these criteria, we mapped the thickness and distribution of high-quality reservoirs in the Longmaxi Formation and selected highlighted several key sites for future exploration and development.

Beschreibung: When mine water inrush accidents occur, timely and accurately identifying the water inrush source plays an important role in determining the cause of water inrush and making a solution to a disaster. According to the differences of water chemical composition in each water sources of mine, eight kinds of indicators of water chemical composition were selected as sample variables for water inrush source identification. On this basis, an identification model of water inrush source was established by using principal component analysis (PCA) and Fisher discriminant analysis (FDA) combined. The model was used to identify the water inrush source of 14 groups of training samples and 12 groups of samples to be judged in different water sources of the Xiandewang coal mine, and it was compared with the results of the conventional identification model which used the FDA method. Results of this study showed that having processed data by using the PCA method can effectively eliminate the effects of information superposition between sample indicators, and the identification accuracy of mine water inrush source was significantly increased. Related study in this paper can provide some basis and reference for the study of mine water inrush source identification technology.

Beschreibung: The abundance of organic matter in shales, which has a direct effect on the hydrocarbon generation potential of shales, is an important organic geochemical parameter for evaluating shale gas reservoirs. The total organic carbon content (TOC content) in shale is controlled by the abundance of original sedimentary organic matter. Therefore, it is very important to study the mechanism of organic matter enrichment in shale. In this paper, the Lower Cambrian marine shales from the Lower Yangtze region are selected as the research subject, most of which originate from a typical area well called Well JXY1. The degree of pyritization (DOP) is used to characterize the redox environment of the water body, while the P/Al ratio is used to analyze the biological productivity of paleoseawater. The paleosalinity of seawater is calculated via carbon and oxygen isotope analysis. In addition, the early Cambrian hydrothermal activities were studied by using core description; Si, Al, Fe, and Mn elemental analysis; and oxygen isotope calculations. The results show that during the early Cambrian Wangyinpu sedimentary period, the seawater was an anaerobic water body with H2S, and the oxygen concentration was approximately 0 mL/L. In the middle stages of the Wangyinpu sedimentary period, the water body had the strongest reducibility and the highest biological productivity. Moreover, the paleoocean in this period between the Yangtze plate and the Cathaysian plate was greatly affected by hydrothermal activities, with temperatures ranging from 90°C to 120°C. Active hydrothermal activities promoted high biological productivity and an anaerobic environment, both of which were conducive to the preservation and enrichment of organic matter, resulting in extremely high TOC content in the Wangyinpu shales (from 6.5% to approximately 16%).

Beschreibung: Electroencephalography-(EEG-) based control is a noninvasive technique which employs brain signals to control electrical devices/circuits. Currently, the brain-computer interface (BCI) systems provide two types of signals, raw signals and logic state signals. The latter signals are used to turn on/off the devices. In this paper, the capabilities of BCI systems are explored, and a survey is conducted how to extend and enhance the reliability and accuracy of the BCI systems. A structured overview was provided which consists of the data acquisition, feature extraction, and classification algorithm methods used by different researchers in the past few years. Some classification algorithms for EEG-based BCI systems are adaptive classifiers, tensor classifiers, transfer learning approach, and deep learning, as well as some miscellaneous techniques. Based on our assessment, we generally concluded that, through adaptive classifiers, accurate results are acquired as compared to the static classification techniques. Deep learning techniques were developed to achieve the desired objectives and their real-time implementation as compared to other algorithms.

Beschreibung: As the externalized carrier of intrinsic value, value decision-making is an important factor affecting the social value system. As an old Chinese saying goes, “A friend in need is a friend indeed,” crisis environment provides the background for the conflicts of multiple values, while individual social value orientation (SVO) determines the ranking of the value states. This paper defined the SVO types by means of Slider Measure method on the basis of environment description, constructed a decision-making game model in accordance with SVO differences, and finally analysed the mechanism of people’s decision-making. Taking the epidemic situation as the background, this paper conducted an empirical analysis with the sample of college students. The results showed that the most SVO types of college students were prosocial orientation, followed by individualistic orientation, altruistic orientation, and competitive orientation. In the crisis environment, individual SVO type and decision-making constituted a mapping relationship. There was an equilibrium point in the decision of prosocial orientation, and the dominant decision of altruistic orientation or individualistic orientation is relatively stable.

Beschreibung: High heterogeneity and nonuniformly distributed multiscale pore systems are two characteristics of the unconventional reservoirs, which lead to very complex transport mechanisms. Limited by inadequate computational capability and imaging field of view, flow simulation cannot be directly performed on complex pore structures. The traditional methods usually coarsen the grid to reduce the computational load but will lead to the missing microstructure information and inaccurate simulation results. To develop a better understanding of flow properties in unconventional reservoirs, this study proposed a new upscaling method integrated gray lattice Boltzmann method (GLBM) and pore network model (PNM), accounting for the fluid flow in heterogeneous porous media. This method can reasonably reduce the computational loads while preserving certain micropore characteristics. Verifications are conducted by comparing the simulation and experimental results on tight sandstones, and good agreements are achieved. The proposed method is proven to be capable of estimating bulk properties in highly heterogenous unconventional reservoirs. This method could contribute to the development of multiscale pore structure characterizations and enhance the understandings of fluid flow mechanisms in unconventional reservoirs.

Beschreibung: To solve the problems of current short-term forecasting methods for metro passenger flow, such as unclear influencing factors, low accuracy, and high time-space complexity, a method for metro passenger flow based on ST-LightGBM after considering transfer passenger flow is proposed. Firstly, using historical data as the training set to transform the problem into a data-driven multi-input single-output regression prediction problem, the problem of the short-term prediction of metro passenger flow is formalized and the difficulties of the problem are identified. Secondly, we extract the candidate temporal and spatial features that may affect passenger flow at a metro station from passenger travel data based on the spatial transfer and spatial similarity of passenger flow. Thirdly, we use a maximal information coefficient (MIC) feature selection algorithm to select the significant impact features as the input. Finally, a short-term forecasting model for metro passenger flow based on the light gradient boosting machine (LightGBM) model is established. Taking transfer passenger flow into account, this method has a low space-time cost and high accuracy. The experimental results on the dataset of Lianban metro station in Xiamen city show that the proposed method obtains higher prediction accuracy than SARIMA, SVR, and BP network.

Beschreibung: People are the most important factors of economy and the primary carriers of social culture. Cross-border migration brings economic and cultural impacts to the origin and destination and is also a key to reflect the international relations of related countries. In fact, the migration relationships of countries are complex and multilateral, but most traditional migration models are bilateral. Network theories could provide a better description of global migration to show the structure and statistical characteristics more clearly. Based on the estimated migration data and disparity filter algorithm, the networks describing the global multilateral migration relationships have been extracted among 200 countries over fifty years. The results show that the global migration networks during 1960–2015 exhibit a clustering and disassortative feature, implying globalized and multipolarized changes of migration during these years. The networks were embed into a Poincaré disk, yielding a typical and hierarchical “core-periphery” structure, which is associated with angular density distribution, and has been used to describe the “multicentering” trend since 1990s. Analysis on correlation and evolution of communities indicates the stability of most communities, yet some structural changes still exist since 1990s, which reflect that the important historical events are contributable to regional and even global migration patterns.

Beschreibung: Most of the existing knowledge graph embedding models are supervised methods and largely relying on the quality and quantity of obtainable labelled training data. The cost of obtaining high quality triples is high and the data sources are facing a serious problem of data sparsity, which may result in insufficient training of long-tail entities. However, unstructured text encoding entities and relational knowledge can be obtained anywhere in large quantities. Word vectors of entity names estimated from the unlabelled raw text using natural language model encode syntax and semantic properties of entities. Yet since these feature vectors are estimated through minimizing prediction error on unsupervised entity names, they may not be the best for knowledge graphs. We propose a two-phase approach to adapt unsupervised entity name embeddings to a knowledge graph subspace and jointly learn the adaptive matrix and knowledge representation. Experiments on Freebase show that our method can rely less on the labelled data and outperforms the baselines when the labelled data is relatively less. Especially, it is applicable to zero-shot scenario.

Beschreibung: Portfolio investment is adopted by the venture capital to diversify those risks involved in project selection, investing or operating so that the venture capitalist can expect a relatively stable income and lower financing risks. Based on the design of portfolio investment contract with unlimited funds developed by Kanniainen and Keuschnigg, and Inderst et al., this article makes a modification and presents a model given the limitation of funds available for the venture capitalist. It is demonstrated that the marginal benefit of efforts paid by the entrepreneurs exceeds the marginal cost, given the limitation of funds available, which will conduce to a high-level engagement of the entrepreneurs. Thus, by adopting the design of renegotiation contract, the venture capitalist can manage to stimulate the entrepreneurs to make efforts, which is to result in moral hazard reduction.

Beschreibung: Huge data on the web come from discussion forums, which contain millions of threads. Discussion threads are a valuable source of knowledge for Internet users, as they have information about numerous topics. The discussion thread related to single topic comprises a huge number of reply posts, which makes it hard for the forum users to scan all the replies and determine the most relevant replies in the thread. At the same time, it is also hard for the forum users to manually summarize the bulk of reply posts in order to get the gist of discussion thread. Thus, automatically extracting the most relevant replies from discussion thread and combining them to form a summary are a challenging task. With this motivation behind, this study has proposed a sentence embedding based clustering approach for discussion thread summarization. The proposed approach works in the following fashion: At first, word2vec model is employed to represent reply sentences in the discussion thread through sentence embeddings/sentence vectors. Next, K-medoid clustering algorithm is applied to group semantically similar reply sentences in order to reduce the overlapping reply sentences. Finally, different quality text features are utilized to rank the reply sentences in different clusters, and then the high-ranked reply sentences are picked out from all clusters to form the thread summary. Two standard forum datasets are used to assess the effectiveness of the suggested approach. Empirical results confirm that the proposed sentence based clustering approach performed superior in comparison to other summarization methods in the context of mean precision, recall, and F-measure.

Beschreibung: Low-permeability reservoirs have tiny pores with winding and complicated pore throats. The oil recovery efficiency of low-permeability reservoirs can be enhanced through the displacement of reservoir oil through imbibition. In the present study, experiments were conducted to investigate variations in the imbibition height of hydrophilic and weakly-hydrophilic rock samples under different interfacial tensions. An imbibition model considering imbibition resistance and bending of pore throats was established based on fractal theory. According to the experimental results, variations in the imbibition height of low-permeability rock samples with time can be divided into three stages. In the first stage, the capillary force plays a dominant role, while the viscous force and gravity have very slight effects. The imbibition height first increases rapidly and then levels off to a constant rate. With the increase in interfacial tension, the imbibition rate in the first stage increases, the ultimate imbibition height increases initially and then decreases, and the contribution of the imbibition height in the first stage to the ultimate imbibition height becomes greater. There is an optimal interfacial tension that causes the ultimate imbibition height to reach its maximum. The calculated results obtained from the proposed imbibition model are consistent with the experimental results, indicating that the model can accurately reflect the change in the imbibition height in low-permeability reservoirs in the first stage.

Beschreibung: The Otago Schist in the South Island of New Zealand represents an exhumed Mesozoic accretionary prism. Two coastal areas (Akatore Creek and Bruce Rocks) south of Dunedin preserve structural and geochemical evidence for the development of postmetamorphic hydrothermal systems that involved widespread fluid-rock reaction at shallow crustal depths. The Jurassic to Triassic pumpellyite-actinolite (Akatore Creek) to upper greenschist facies (Bruce Rocks) metamorphic fabrics were crosscut by sets of regionally extensive Cretaceous exhumation joints. Many of the joints were subsequently reactivated to form networks of small-displacement (

Beschreibung: This paper considers the two-player location game in a closed-loop market with quantity competition. Based on the Cournot and Hotelling models, a circle model is established for a closed-loop market in which two players (firms) play a location game under quantity competition. Using a two-stage (location-then-quantity) pattern and backward induction method, the existence of subgame-perfect Nash equilibria is proved for the location game in the circle model with a minimum distance transportation cost function. In addition, sales strategies are proposed for the two players for every local market on the circle when the players are in the equilibrium positions. Finally, an algorithm for simulating the competitive dynamics of the closed-loop market is designed, and two numerical simulations are provided to substantiate the effectiveness of the obtained results.

Beschreibung: Widely distributed in North China, Ordovician karst is characterized by having high thickness, nonuniform aquosity, and significant water pressure-bearing properties. Deep mining in North China is threatened by associated water hazards; hence, research on the hydrogeological characteristics of deep Ordovician karst is needed. In this study, the Weibei coalfield in Shaanxi Province, China, was selected as the study area, especially mines in the Hancheng and Chenghe mining areas. In situ experiments, including water pumping, water drainage, water injecting and water pressure, and laboratory experiments, were conducted to study the hydrogeological characteristics of the Ordovician karst top in the study area. A comprehensive analysis was conducted on controlling factors for the development of the Ordovician karst top in the study area, and a method for evaluating the water inrush risk in coal mining areas based on karst hydrogeological characteristics was proposed. The research results indicated that the Ordovician karst top in the study area was characterized by heterogeneity, vertical zonation, and partially filled properties, which were mainly controlled by two factors: sedimentation and tectonism. The hydrogeological conditions of the Ordovician karst could be divided into three types: nonfilled and nonsignificant tectonism, filled and nonsignificant tectonism, and significant tectonism. Among them, the filled and nonsignificant tectonism type Ordovician karst top type had a filling thickness of 20 m. Based on karst hydrogeological characteristics, the methods were proposed to evaluate the water inrush risk in the coal mining floor. The practical tests verified the methods.

Beschreibung: It is critical to select an optimized sand control method for an interbedded sandstone and mudstone reservoir (ISMR) due to its serious sand production hazards. However, currently, most general sand control methods cannot meet the requirements of sand control in interbedded sandstone and mudstone reservoirs (e.g., Bohai Bay oil and gas fields from China). Ensuring efficiency of sand control and increasing the oil and gas production rate in this interbedded sandstone and mudstone become more and more important. In this paper, a “multilayer rotatable sand control experimental device” for the interbedded sandstone and mudstone reservoir was developed. A series of sand control experimental studies were conducted by using the proposed device. The net-to-gross ratio (NTG) and well inclinations are two major factors considered in the experimental analysis. In addition, a sensitivity analysis regarding formation particle size distribution (PSD), clay content, and mineral compositions is performed in the experiment under a moderate sand control mode. With systematic experimental test results in this work, combined with numerous existing sand control models, a set of optimum sand control design and the associated optimization template for ISMR were developed, which have been successfully applied in Bohai Bay. Field application results show that NTG and well inclination are two critical parameters in the design of sand control in ISMR. The optimal indexes of a sand control mode are determined as NTG of 0.4 and well inclination of 45°. The introduction of these two key factors in sand control design broadens the application range of moderate sand production.

Beschreibung: The scale dependence of surface roughness is critical in characterising the hydromechanical properties of field-scale rock joints but is still not well understood, particularly when different orders of roughness are considered. We experimentally reveal the scale dependence of two-order roughness, i.e., waviness and unevenness through fractal parameters using the triangular prism surface area method (TPM). The surfaces of three natural joints of granite with the same dimension of 1000 mm×1000 mm are digitised using a 3D laser scanner at three different measurement resolutions. Waviness and unevenness are quantitatively separated by considering the area variation of joint surface as grid size changes. The corresponding fractal dimensions of waviness and unevenness in sampling window sizes ranging from 100 mm×100 mm to 1000 mm×1000 mm at an interval of 100 mm×100 mm are determined. We find that both the fractal dimensions of waviness and unevenness vary as the window size increases. No obvious stationarity threshold has been found for the three rock joint samples, indicating the surface roughness of natural rock joints should be quantified at the scale of the rock mass in the field.

Beschreibung: A novel posture motion-based spatiotemporal fused graph convolutional network (PM-STGCN) is presented for skeleton-based action recognition. Existing methods on skeleton-based action recognition focus on independently calculating the joint information in single frame and motion information of joints between adjacent frames from the human body skeleton structure and then combine the classification results. However, that does not take into consideration of the complicated temporal and spatial relationship of the human body action sequence, so they are not very efficient in distinguishing similar actions. In this work, we enhance the ability of distinguishing similar actions by focusing on spatiotemporal fusion and adaptive feature extraction for high discrimination information. Firstly, the local posture motion-based attention (LPM-TAM) module is proposed for the purpose of suppressing the skeleton sequence data with a low amount of motion in the temporal domain, and the representation of motion posture features is concentrated. Besides, the local posture motion-based channel attention module (LPM-CAM) is introduced to make use of the strongly discriminative representation between different action classes of similarity. Finally, the posture motion-based spatiotemporal fusion (PM-STF) module is constructed which fuses the spatiotemporal skeleton data by filtering out the low-information sequence and enhances the posture motion features adaptively with high discrimination. Extensive experiments have been conducted, and the results demonstrate that the proposed model is superior to the commonly used action recognition methods. The designed human-robot interaction system based on action recognition has competitive performance compared with the speech interaction system.

Beschreibung: Karst collapse pillars (KCPs) frequently cause severe groundwater inrush disasters in coal mining above a confined aquifer. An accurate understanding of the damage and fracture evolution, permeability enhancement, and seepage changes in KCPs under the combined action of mining-induced stress and confined hydraulic pressure is of great significance for the early prediction and prevention of groundwater inrush from KCPs in coal seam floors. In this study, a micromechanics-based coupled stress-seepage-damage (SSD) modeling approach, in which the macroscopic mechanical and hydraulic properties of the rock are explicitly related to the microcrack kinetics, is proposed to simulate the fracture evolution and the associated groundwater flow in KCPs. An in situ high-precision microseismic monitoring technology is used to verify the micromechanical modeling results, which indicate that the numerical model successfully reproduces the damage and fracture evolution in a coal seam floor with a KCP during the mining process. The presented model also provides a visual representation of the complex process of KCP activation and groundwater inrush channel formation. A numerical study shows that the damage and activation of a KCP start from the edge of the KCP, gradually develop toward the interior of the KCP, and eventually connect with the damage fracture zone of the floor, forming a primary water-conducting channel in the KCP, causing the confined groundwater to flow into the working face. Groundwater inrush from a KCP is a gradual process instead of a mutation process. A reduction in the distance between the working face and a KCP and increases in the confined hydraulic pressure and the initial water-conducting height of the KCP can significantly increase the risk of groundwater inrush from the KCP.

Beschreibung: In this paper, a delayed control strategy for a class of nonlinear underactuated fourth-order systems is developed. The proposal is based on the implementation of the tangent linearization technique, differential flatness, and a study of the σ-stabilization of the characteristic equation of the closed-loop system. The tangent linearization technique allows obtaining a local controllability property for the analyzed class of systems. Also, it can reduce the complexity of the global control design, through the use of a cascade connection of two second-order controllers instead of designing a global controller of the fourth-order system. The stabilizing behavior of the delayed controller design is supported by the σ-stability criterion, which provides the controller parameter selection to reach the maximum exponential decay rate on the system response. To illustrate the efficiency of the theoretical results, the proposal is experimentally assessed in two cases of study: a flexible joint system and a pendubot.

Beschreibung: Recently, knowledge graph embedding methods have attracted numerous researchers’ interest due to their outstanding effectiveness and robustness in knowledge representation. However, there are still some limitations in the existing methods. On the one hand, translation-based representation models focus on conceiving translation principles to represent knowledge from a global perspective, while they fail to learn various types of relational facts discriminatively. It is prone to make the entity congestion of complex relational facts in the embedding space reducing the precision of representation vectors associating with entities. On the other hand, parallel subgraphs extracted from the original graph are used to learn local relational facts discriminatively. However, it probably causes the relational fact damage of the original knowledge graph to some degree during the subgraph extraction. Thus, previous methods are unable to learn local and global knowledge representation uniformly. To that end, we propose a multiview translation learning model, named MvTransE, which learns relational facts from global-view and local-view perspectives, respectively. Specifically, we first construct multiple parallel subgraphs from an original knowledge graph by considering entity semantic and structural features simultaneously. Then, we embed the original graph and construct subgraphs into the corresponding global and local feature spaces. Finally, we propose a multiview fusion strategy to integrate multiview representations of relational facts. Extensive experiments on four public datasets demonstrate the superiority of our model in knowledge graph representation tasks compared to state-of-the-art methods.

Beschreibung: A multimode resource-constrained project scheduling problem (MRCPSP) may have multifeasible solutions, due to its nature of targeting multiobjectives. Given the NP-hard MRCPSP and intricate multiobjective algorithms, finding the optimized result among those solutions seems impossible. This paper adopts data envelopment analysis (DEA) to evaluate a series of solutions of an MRCPSP and to find an appropriate choice in an objective way. Our approach is applied to a typical MRCPSP in practice, and the results validate that DEA is an effective and objective method for MRCPSP solution selection.

Beschreibung: Based on the oligopoly game theory and the intellectual property rights protection policy, we investigate the complex dynamical behaviors of a mixed duopoly game with quadratic cost. In the new system, a few parameters are improved by considering intellectual property rights protection and the stability conditions of the Nash equilibrium point are discussed in detail. A set of the two-dimensional bifurcation diagrams is demonstrated by using numerical modeling, and these diagrams show abundant complex dynamical behaviors, such as coexistence of attractors, different bifurcation, and fractal structures. These dynamical properties can present the long-run effects of strengthening intellectual property protection.

Beschreibung: Implementing artificial neural networks is commonly achieved via high-level programming languages such as Python and easy-to-use deep learning libraries such as Keras. These software libraries come preloaded with a variety of network architectures, provide autodifferentiation, and support GPUs for fast and efficient computation. As a result, a deep learning practitioner will favor training a neural network model in Python, where these tools are readily available. However, many large-scale scientific computation projects are written in Fortran, making it difficult to integrate with modern deep learning methods. To alleviate this problem, we introduce a software library, the Fortran-Keras Bridge (FKB). This two-way bridge connects environments where deep learning resources are plentiful with those where they are scarce. The paper describes several unique features offered by FKB, such as customizable layers, loss functions, and network ensembles. The paper concludes with a case study that applies FKB to address open questions about the robustness of an experimental approach to global climate simulation, in which subgrid physics are outsourced to deep neural network emulators. In this context, FKB enables a hyperparameter search of one hundred plus candidate models of subgrid cloud and radiation physics, initially implemented in Keras, to be transferred and used in Fortran. Such a process allows the model’s emergent behavior to be assessed, i.e., when fit imperfections are coupled to explicit planetary-scale fluid dynamics. The results reveal a previously unrecognized strong relationship between offline validation error and online performance, in which the choice of the optimizer proves unexpectedly critical. This in turn reveals many new neural network architectures that produce considerable improvements in climate model stability including some with reduced error, for an especially challenging training dataset.

Beschreibung: Social networks are a complex system that members communicate, create new connections or destroy existing connections, and further deliver major impacts on each member’s life. Given the spread of the Internet and increased academic pressure, sedentary and prescreen behaviors are very common among adolescents; meanwhile, sports behaviors are gradually decreasing. This situation has had an adverse effect on health. This paper used a questionnaire survey to investigate the influence of social networks on adolescent sports behavior, including the intermediary role of social efficacy and moderating effect of self-presentation. The questionnaire survey was conducted on 568 students from 6 high schools in Shaanxi, Henan, and Shandong Provinces. After this, factor analysis and weighted least squares method were used for the empirical test. Based on theoretical and empirical analysis, this paper found the following: (1) Social networks of adolescents have obvious positive predictive effects on their sports behavior. A single online social network and an offline social network, instrumental network, emotional network, and mixed network have obvious positive predictive effects on adolescent sports behaviors. However, under the influence of multiple types of social networks, an offline social network has a negative predictive effect, while a mixed network has effects that are not as obvious. (2) Social efficacy plays an intermediary role in the relationship between social network and adolescent sports behavior. (3) The moderating effect of self-presentation is not significant.

Beschreibung: Height measurement for moving pedestrians is quite significant in many scenarios, such as pedestrian positioning, criminal suspect tracking, and virtual reality. Although some existing height measurement methods can detect the height of the static people, it is hard to measure height accurately for moving pedestrians. Considering the height fluctuations in dynamic situation, this paper proposes a real-time height measurement based on the Time-of-Flight (TOF) camera. Depth images in a continuous sequence are addressed to obtain the real-time height of the pedestrian with moving. Firstly, a normalization equation is presented to convert the depth image into the grey image for a lower time cost and better performance. Secondly, a difference-particle swarm optimization (D-PSO) algorithm is proposed to remove the complex background and reduce the noises. Thirdly, a segmentation algorithm based on the maximally stable extremal regions (MSERs) is introduced to extract the pedestrian head region. Then, a novel multilayer iterative average algorithm (MLIA) is developed for obtaining the height of dynamic pedestrians. Finally, Kalman filtering is used to improve the measurement accuracy by combining the current measurement and the height at the last moment. In addition, the VICON system is adopted as the ground truth to verify the proposed method, and the result shows that our method can accurately measure the real-time height of moving pedestrians.

Beschreibung: Since China’s first stock index futures, China Securities Index 300 (CSI300) stock index futures were published in 2010, and China’s stock index futures market is now in a period of rapid development and play a key role in price discovery. During 2014 to 2015, China’s stock index futures market fluctuated abnormally, and the overuse of high-frequency trading (HFT) strategies in the stock index futures market was blamed as the main reason of the abnormal volatility. To lower down market fluctuation, the regulatory institute then announced a series of trade restriction policy to prevent the overuse of HFT behaviour. However, until now, the impact of such trade restriction policy for HFT remains uncertain. To tackle this issue, based on minute-level HFT data from the CSI 300 index futures market, this paper aims to investigate the relationship between HFT and the exogenous liquidity risk and how HFT affects China’s stock index futures market on its liquidity using the liquidity-adjusted value at risk (LVaR) model. The findings indicate that HFT improves the return of the liquidity provider and reduces the exogenous liquidity risk significantly.

Beschreibung: Community is the core spatial unit for evaluating sustainable development. However, single data and method seem inadequate for conducting a scientific, effective, and innovative sustainable evaluation of complex community units. In this study, we perform a sustainable-oriented land use scheme using multisource remote sensing, machine learning, and object-based postclassification refinement. Furthermore, we assess the sustainability of the traffic community by data-driven and combined housing, ecosystem services, and landscape configuration. The results indicated that (1) the relationship between housing, ecosystem services, and landscape pattern has obvious synergistic effects, although with dissimilar importance in different sustainability levels. High sustainability level is intensely coordinated with landscape configuration, medium sustainability level is more affected by ecosystem services, and low sustainability level is more related to housing. (2) Community sustainability presents a significant spatial distribution. The communities of high sustainability level are mainly located in both sides of the Pearl River and emerging urban areas, while those of medium sustainability level are distributed sporadically in the study area and those of low sustainability level are concentrated in old towns. (3) Community transformation cannot be accomplished at one step. Along with the continuous optimization of landscape configuration, the priority should be given to housing reconstruction and improvement of ecosystem services further. We provide scientific and effective data-based evidence for urban decision-makers by integrating the advantages of the Earth Observation System and multifactor analysis.

Beschreibung: Practically, supply disruption may lead production process to entirely halt (completely disrupted) or the output to differ in the order size (partially disrupted), which makes it more difficult for the retailer to satisfy stochastic market demand. Under the circumstance, the retailer is likely to procure products from two suppliers to effectively alleviate the demand-supply mismatches. Thus, under supply disruption and stochastic demand, this paper develops both backup sourcing and simultaneous sourcing (SS) strategies to analyze the retailer’s performance, where backup sourcing includes wholesale price priority (WPP) and supply reliability priority (SRP). Specifically, (1) under WPP, when the selling price is relatively lower (higher), the retailer is suggested to activate the reliable backup supplier after the realization of supply disruption (demand uncertainty). (2) Under SRP, two scenarios including minor disruption and major disruption can be identified, where the retailer’s order quantity from the reliable (unreliable) supplier under minor disruption scenario is more (less) than that under major. (3) Finally, this paper systematically compares the retailer’s preferences among WPP, SRP, and SS via theoretical results and numerical examples. That is, when the unreliable supplier is more likely to work normally or shortage cost (selling price) is relatively lower, the retailer prefers SPR regarding the unreliable supplier as backup sourcing due to its lower wholesale price and acceptable supply disruption. Otherwise, the retailer is inclined to WPP regarding the reliable supplier as backup sourcing for ensuring all market demand to be satisfied. In addition, unless the emergency prices of two suppliers are extremely higher, backup sourcing strategies could perform better than simultaneous sourcing strategy.

Beschreibung: This study investigates a multidepot heterogeneous vehicle routing problem for a variety of hazardous materials with risk analysis, which is a practical problem in the actual industrial field. The objective of the problem is to design a series of routes that minimize the total cost composed of transportation cost, risk cost, and overtime work cost. Comprehensive consideration of factors such as transportation costs, multiple depots, heterogeneous vehicles, risks, and multiple accident scenarios is involved in our study. The problem is defined as a mixed integer programming model. A bidirectional tuning heuristic algorithm and particle swarm optimization algorithm are developed to solve the problem of different scales of instances. Computational results are competitive such that our algorithm can obtain effective results in small-scale instances and show great efficiency in large-scale instances with 70 customers, 30 vehicles, and 3 types of hazardous materials.

Beschreibung: Single image super-resolution (SISR) is a traditional image restoration problem. Given an image with low resolution (LR), the task of SISR is to find the homologous high-resolution (HR) image. As an ill-posed problem, there are works for SISR problem from different points of view. Recently, deep learning has shown its amazing performance in different image processing tasks. There are works for image super-resolution based on convolutional neural network (CNN). In this paper, we propose an adaptive residual channel attention network for image super-resolution. We first analyze the limitation of residual connection structure and propose an adaptive design for suitable feature fusion. Besides the adaptive connection, channel attention is proposed to adjust the importance distribution among different channels. A novel adaptive residual channel attention block (ARCB) is proposed in this paper with channel attention and adaptive connection. Then, a simple but effective upscale block design is proposed for different scales. We build our adaptive residual channel attention network (ARCN) with proposed ARCBs and upscale block. Experimental results show that our network could not only achieve better PSNR/SSIM performances on several testing benchmarks but also recover structural textures more effectively.

Beschreibung: A floor aquifuge usually bends and fails when mining above a confined aquifer, which may lead to water inrush disaster. The floor aquifuge was simplified as a thin disc model in this paper, and a series of coupled bending-seepage tests of sandstone were carried out by a patent test system. The variation characteristics of load-displacement, load-time, and permeability-time were analyzed. The deflection and stress in the thin disc rock samples were deduced; the initiation and propagation of cracks were analyzed. The failure behavior of the thin disc rock samples was described. It shows the following: (1) The bending failure behavior relates to the stress distribution and crack evolution inside the thin disc. (2) The main cause of crack initiation is a tension-shear failure. (3) The 5 mm thickness thin discs form petal-shaped cracks, due to tensile stress, while petal-shaped cracks only appear at the cap block of the 10 mm discs, which are sheared into two pieces along the conical surface with an inclination about 45°. (4) Water inrush occurs after bending failure in the floor aquifuge, and it is an opportune moment to grout along the crack propagation trend lines to prevent the water inrush disasters.

Beschreibung: Evapotranspiration (ET) is an essential component of watershed hydrological cycle. Spatial-temporal variations analyses of evapotranspiration and potential evapotranspiration (PET) have remarkable theoretical and practical significances for understanding the interaction between climate changes and hydrological cycle and optimal allocation of water resources under global warming background. The MODIS-estimated ET agreed well with basin evapotranspiration from water balance principle methods in the study. The spatiotemporal variations results based on MOD16 ET data showed the following: (1) multiyear mean ET and PET were 464.2 mm and 1192.2 mm, and annual ET showed an upward trend at a rate of 3.48 mm/a, while PET decreased significantly at a rate of −8.18 mm/a. The annual ET trend showed a complemental relationship with PET; (2) at the seasonal scale, ET was highest in summer and least in winter, while PET was higher in spring and summer. The change of ET and PET in spring and summer had a great contribution to the annual variations; (3) ET and PET in the northern part were significantly stronger than those in the western and southern parts; (4) ET in cropland increased significantly, while PET decreased obviously in grass and forest; (5) changes of ET and PET were closely related to climatic factors. The rise in temperature caused the increase in ET and the decrease of wind speed contributed more to the decrease in PET. The results can provide a scientific basis for water resources planning and management.

Beschreibung: With the gestation and development of new technologies, new products, new formats, and new models, venture capital investment, as one of the most important forms of open innovation in large companies, plays an increasingly important role in the innovation of mature large companies and entrepreneurial enterprises. To deal with the complex and dynamic environment, the niche of Corporate Venture Capital (CVC) ecological community is investigated from the perspective of the innovation ecosystem. By analyzing the innovation of CVC ecological community with the use of the logistic expansion model, this paper analyzes the stability of evolution game through the replicator dynamic equation and discusses ten parameters of niche state. In the end, we conclude that there are four optimization strategies in the coevolution of major corporations and entrepreneurial firms, namely, niche separation, niche expansion, niche K-R, and niche alliance.

Beschreibung: Multiobject detection tasks in complex scenes have become an important research topic, which is the basis of other computer vision tasks. Considering the defects of the traditional single shot multibox detector (SSD) algorithm, such as poor small object detection effect, reliance on manual setting for default box generation, and insufficient semantic information of the low detection layer, the detection effect in complex scenes was not ideal. Aiming at the shortcomings of the SSD algorithm, an improved algorithm based on the adaptive default box mechanism (ADB) is proposed. The algorithm introduces the adaptive default box mechanism, which can improve the imbalance of positive and negative samples and avoid manually set default box super parameters. Experimental results show that, compared with the traditional SSD algorithm, the improved algorithm has a better detection effect and higher accuracy in complex scenes.

Beschreibung: The nonlinear resonant responses, mode interactions, and multitime periodic and chaotic oscillations of the cantilevered pipe conveying pulsating fluid are studied under the harmonic external force in this research. According to the nonlinear dynamic model of the cantilevered beam derived using Hamilton’s principle under the uniformly distributed external harmonic excitation, we combine Galerkin technique and the method of multiple scales together to obtain the average equation of the cantilevered pipe conveying pulsating fluid under 1 : 3 internal resonance and principal parametric resonance. Based on the average equation in the polar form, several amplitude-frequency response curves are obtained corresponding to the certain parameters. It is found that there exist the hardening-spring type behaviors and jumping phenomena in the cantilevered pipe conveying pulsating fluid. The nonlinear oscillations of the cantilevered pipe conveying pulsating fluid can be excited more easily with the increase of the flow velocity, external excitation, and coupling degree of two order modes. Numerical simulations are performed to study the chaos of the cantilevered pipe conveying pulsating fluid with the external harmonic excitation. The simulation results exhibit the existence of the period, multiperiod, and chaotic responses with the variations of the fluid velocity or excitation. It is found that, in the cantilevered pipe conveying pulsating fluid, there are the multitime nonlinear vibrations around the left-mode and the right-mode positions, respectively. We also observe that there exist alternately the periodic and chaotic vibrations of the cantilevered pipe conveying pulsating fluid in the certain range.

Beschreibung: Ventilator is important equipment for mines as it safeguards the lives under the shaft and ensures other equipment’s proper functioning by providing fresh air. Therefore, how to effectively control the ventilator system becomes more significant. In order to acquire the commonly used model and control strategy for ventilator systems, a new universal ventilator model is established based on the blast capacity differential pressure in the ventilating duct and the ventilator motor model. Then, an adaptive Chebyshev neural network (ACNN) controller is proposed to effectively control the ventilator system where the unknown load torque and the unknown disturbance caused by the complex environment under the shaft are approximated by the Chebyshev neural network (CNN). Afterwards, an appropriate Lyapunov function candidate is designed to guarantee the stability of the proposed controller and the closed-loop ventilator system. Finally, the ACNN controller has been demonstrated to be effective in terms of validity and precision for the new proposed ventilator model through the simulations.

Beschreibung: Nonlinear evolution equations widely describe phenomena in various fields of science, such as plasma, nuclear physics, chemical reactions, optics, shallow water waves, fluid dynamics, signal processing, and image processing. In the present work, the derivation and analysis of Lie symmetries are presented for the time-fractional Benjamin–Bona–Mahony equation (FBBM) with the Riemann–Liouville derivatives. The time FBBM equation is reduced to a nonlinear fractional ordinary differential equation (NLFODE) using its Lie symmetries. These symmetries are derivations using the prolongation theorem. Applying the subequation method, we then use the integrating factor property to solve the NLFODE to obtain a few travelling wave solutions to the time FBBM.

Beschreibung: The Cloud Computing paradigm is focused on the provisioning of reliable and scalable virtual infrastructures that deliver execution and storage services. This paradigm is particularly suitable to solve resource-greedy scientific computing applications such as parameter sweep experiments (PSEs). Through the implementation of autoscalers, the virtual infrastructure can be scaled up and down by acquiring or terminating instances of virtual machines (VMs) at the time that application tasks are being scheduled. In this paper, we extend an existing study centered in a state-of-the-art autoscaler called multiobjective evolutionary autoscaler (MOEA). MOEA uses a multiobjective optimization algorithm to determine the set of possible virtual infrastructure settings. In this context, the performance of MOEA is greatly influenced by the underlying optimization algorithm used and its tuning. Therefore, we analyze two well-known multiobjective evolutionary algorithms (NSGA-II and NSGA-III) and how they impact on the performance of the MOEA autoscaler. Simulated experiments with three real-world PSEs show that MOEA gets significantly improved when using NSGA-III instead of NSGA-II due to the former provides a better exploitation versus exploration trade-off.

Beschreibung: There is a large amount of information and maintenance data in the aviation industry that could be used to obtain meaningful results in forecasting future actions. This study aims to introduce machine learning models based on feature selection and data elimination to predict failures of aircraft systems. Maintenance and failure data for aircraft equipment across a period of two years were collected, and nine input and one output variables were meticulously identified. A hybrid data preparation model is proposed to improve the success of failure count prediction in two stages. In the first stage, ReliefF, a feature selection method for attribute evaluation, is used to find the most effective and ineffective parameters. In the second stage, a K-means algorithm is modified to eliminate noisy or inconsistent data. Performance of the hybrid data preparation model on the maintenance dataset of the equipment is evaluated by Multilayer Perceptron (MLP) as Artificial Neural network (ANN), Support Vector Regression (SVR), and Linear Regression (LR) as machine learning algorithms. Moreover, performance criteria such as the Correlation Coefficient (CC), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) are used to evaluate the models. The results indicate that the hybrid data preparation model is successful in predicting the failure count of the equipment.

Beschreibung: The optical images collected by remotely operated vehicles (ROV) contain a lot of information about underwater (such as distributions of underwater creatures and minerals), which plays an important role in ocean exploration. However, due to the absorption and scattering characteristics of the water medium, some of the images suffer from serious color distortion. These distorted color images usually need to be enhanced so that we can analyze them further. However, at present, no image enhancement algorithm performs well in any scene. Therefore, in order to monitor image quality in the display module of ROV, a no-reference image quality predictor (NIPQ) is proposed in this paper. A unique property that differentiates the proposed NIPQ metric from existing works is the consideration of the viewing behavior of the human visual system and imaging characteristics of the underwater image in different water types. The experimental results based on the underwater optical image quality database (UOQ) show that the proposed metric can provide an accurate prediction for the quality of the enhanced image.

Beschreibung: Identification of community structures and the underlying semantic characteristics of communities are essential tasks in complex network analysis. However, most methods proposed so far are typically only applicable to assortative community structures, that is, more links within communities and fewer links between different communities, which ignore the rich diversity of community regularities in real networks. In addition, the node attributes that provide rich semantics information of communities and networks can facilitate in-depth community detection of structural information. In this paper, we propose a novel unified Bayesian generative model to detect generalized communities and provide semantic descriptions simultaneously by combining network topology and node attributes. The proposed model is composed of two closely correlated parts by a transition matrix; we first apply the concept of a mixture model to describe network regularities and then adjust the classic Latent Dirichlet Allocation (LDA) topic model to identify community semantically. Thus, the model can detect broad types of network structure regularities, including assortative structures, disassortative structures, and mixture structures and provide multiple semantic descriptions for the communities. To optimize the objective function of the model, we use an effective Gibbs sampling algorithm. Experiments on a number of synthetic and real networks show that our model has superior performance compared with some baselines on community detection.

Beschreibung: This work investigates a decentralized state feedback scheme of neural network control for an interconnected system. The completely unknown associated terms are estimated directly by the neural structure. A modified approach is proposed to deal with the state feedback format. By combining the Lyapunov function and backstepping technology together, an adaptive decentralized controller is established, and we can construct the boundedness of all signals in the closed-loop structure through the controller, which can drive the formation of a given reference signal. In the end, the effectiveness of the presented strategy is referred to a simulation example.

Beschreibung: A novel four-dimensional energy, economic, and environmental (3E) under energy reduction constraints chaotic system is proposed. The acquisition of environmental quality data is the key to this paper. During the course of the study, we used Bayesian estimation algorithm to calibrate the environmental quality. Based on the official data, the Levenberg–Marquardt backpropagation neural network method was optimized by genetic algorithm to effectively identify the parameters in the 3E system. The research results show that although increasing energy reduction inputs can improve environmental quality, the effect on energy intensity and overall stability of the system is not obvious. When polluting input in the ecological environment system affects its maximum capacity, the environmental system collapses (i.e., the ecological system can no longer purify the environment through the self-circulation process and will eventually die out). Therefore, it is necessary to correctly grasp the ecological environment protection and the relationship between economic developments and explore synergies to promote ecological priorities and green development new ideas.

Beschreibung: Recently, the use of NoSQL databases has grown to manage unstructured data for applications to ensure performance and scalability. However, many organizations prefer to transfer data from an operational NoSQL database to a SQL-based relational database for using existing tools for business intelligence, analytics, decision making, and reporting. The existing methods of NoSQL to relational database transformation require manual schema mapping, which requires domain expertise and consumes noticeable time. Therefore, an efficient and automatic method is needed to transform an unstructured NoSQL database into a structured database. In this paper, we proposed and evaluated an efficient method to transform a NoSQL database into a relational database automatically. In our experimental evaluation, we used MongoDB as a NoSQL database, and MySQL and PostgreSQL as relational databases to perform transformation tasks for different dataset sizes. We observed excellent performance, compared to the existing state-of-the-art methods, in transforming data from a NoSQL database into a relational database.

Beschreibung: In the development of technology for smart cities, the installation and deployment of electronic motor vehicle registration identification have attracted great attention in terms of smart transportation in recent years. Vehicle velocity measurement is one of the fundamental data collection efforts for motor vehicles. The velocity detection using electronic registration identification of motor vehicles is constrained by the detection algorithm, the material of the automobile windshield, the placement of the decals, the installation method of the signal reader, and the angle of the antenna. The software and hardware for electronic motor vehicle registration identification produced in the standard manner cannot meet the accuracy of velocity detection for all scenarios. Based on the actual application requirements, we propose a calibration method for the numerical output of the automobile velocity detector based on edge computing of the optimized multiple reader/writer velocity values and based on a particle swarm-optimized radial basis function (RBF) neural network. The proposed method was tested on a two-way eight-lane road, and the test results showed that it can effectively improve the accuracy of velocity detection using electronic registration identification of motor vehicles. Compared with the actual velocity, 87.12% of all the data samples had an error less than 5%, and 91.76% of the data samples for vehicles in the center lane had an error less than 5%. By calibrating the electronic vehicle velocity based on the registration identification, the accuracy of velocity detection in different application environments can be improved. Moreover, the method can establish an accurate foundation for application in traffic flow management, environmental protection, traffic congestion fee collection, and special vehicle traffic management.

Beschreibung: In this work, we solve the uncertain unmanned aerial vehicle smooth landing problem over a moving platform, assuming that the aircraft position relative to the platform and its acceleration is always measurable. The landing task is carried out by an output-feedback robust controller, together with a repulsive force. The robust controller controls the nominal model, accomplishes the needed tracking trajectory, and counteracts the unknown uncertainties. To assure that the aircraft is always above the platform, we include a repulsive force that only works in a small vicinity of the platform. To estimate the relative aircraft velocity and platform acceleration, we use a supertwisting-based observer, assuring finite-time convergence of these signals. This fact allowed us to design the feedback state stabilizer independently of the observer design (in accordance with the separation principle). We confirmed the effectiveness of our control approach by convincing numerical simulations.

Beschreibung: As a green and renewable energy source, photovoltaic power is of great significance for the sustainable development of energy and has been increasingly exploited. The photovoltaic controller is the key component of a photovoltaic power generation system, and its central technology is the maximum power point tracking technology. In this paper, a mathematical model of photovoltaic cells is firstly established, the output characteristics of photovoltaic cells are analyzed, the main factors that affect the output efficiency of photovoltaic cells are obtained, and it is proved that the most important factor that affects the output power is the light intensity. Therefore, in the design, the maximum power point of the photovoltaic cell is tracked by the control algorithm and can maximize the use of photovoltaic output power fast charging. The key to the design of a photovoltaic controller is the design of control algorithm. So, an improved fuzzy control algorithm is proposed to overcome the shortcomings of the traditional maximum power point tracking (MPPT) algorithm. The algorithm can consider tracking both speed and convergence, but the algorithm requires high input and output fuzzy domain parameters, and although the tracking speed is fast, the stability of convergence is poor. For the limitation of fuzzy control algorithm, considering the property of the Versoria function, an MPPT design method for an intelligent controller based on the Versoria variable step algorithm is further proposed. According to the output characteristics of photovoltaic cells, three parameters, α, β, and γ, are set to solve the tracking speed and tracking stability. In order to reduce the static error, a genetic factor is proposed to sum up the historical error to effectively improve the tracking stability. The simulation results show that the algorithm can track the maximum power point quickly and has good tracking speed and stability. This algorithm can be used in engineering practice effectively.

Beschreibung: Knowledge graph is a kind of semantic network for information retrieval. How to construct a knowledge graph that can serve the power system based on the behavior data of dispatchers is a hot research topic in the area of electric power artificial intelligence. In this paper, we propose a method to construct the dispatch knowledge graph for the power grid. By leveraging on dispatch data from the power domain, this method first extracts entities and then identifies dispatching behavior relationship patterns. More specifically, the method includes three steps. First, we construct a corpus of power dispatching behaviors by semi-automated labeling. And then, we propose a model, called the BiLSTM-CRF model, to extract entities and identify the dispatching behavior relationship patterns. Finally, we construct a knowledge graph of power dispatching data. The knowledge graph provides an underlying knowledge model for automated power dispatching and related services and helps dispatchers perform better power dispatch knowledge retrieval and other operations during the dispatch process.

Beschreibung: With the advancement in ICT, web search engines have become a preferred source to find health-related information published over the Internet. Google alone receives more than one billion health-related queries on a daily basis. However, in order to provide the results most relevant to the user, WSEs maintain the users’ profiles. These profiles may contain private and sensitive information such as the user’s health condition, disease status, and others. Health-related queries contain privacy-sensitive information that may infringe user’s privacy, as the identity of a user is exposed and may be misused by the WSE and third parties. This raises serious concerns since the identity of a user is exposed and may be misused by third parties. One well-known solution to preserve privacy involves issuing the queries via peer-to-peer private information retrieval protocol, such as useless user profile (UUP), thereby hiding the user’s identity from the WSE. This paper investigates the level of protection offered by UUP. For this purpose, we present QuPiD (query profile distance) attack: a machine learning-based attack that evaluates the effectiveness of UUP in privacy protection. QuPiD attack determines the distance between the user’s profile (web search history) and upcoming query using our proposed novel feature vector. The experiments were conducted using ten classification algorithms belonging to the tree-based, rule-based, lazy learner, metaheuristic, and Bayesian families for the sake of comparison. Furthermore, two subsets of an America Online dataset (noisy and clean datasets) were used for experimentation. The results show that the proposed QuPiD attack associates more than 70% queries to the correct user with a precision of over 72% for the clean dataset, while for the noisy dataset, the proposed QuPiD attack associates more than 40% queries to the correct user with 70% precision.

Beschreibung: This paper presents a multi-innovation stochastic gradient parameter estimation algorithm for dual-rate sampled state-space systems with d-step time delay by the multi-innovation identification theory. Considering the stochastic disturbance in industrial process and using the gradient search, a multi-innovation stochastic gradient algorithm is proposed through expanding the scalar innovation into an innovation vector in order to obtain more accurate parameter estimates. The difficulty of identification is that the information vector in the identification model contains the unknown states. The proposed algorithm uses the state estimates of the observer instead of the state variables to realize the parameter estimation. The simulation results indicate that the proposed algorithm works well.

Beschreibung: The Longmendian Ag–Pb–Zn deposit is located in the southern margin of the North China Craton, and the mineralization occurs mainly in quartz veins, altered gneissic wallrocks, and minor fault breccias in the Taihua Group. Based on vein crosscutting relations, mineral assemblages, and paragenesis, the mineralization can be divided into three stages: (1) quartz–pyrite, (2) quartz–polymetallic sulfides, and (3) quartz–carbonate–polymetallic sulfides. Wallrock alteration can be divided into three zones, i.e., chlorite–sericite, quartz–carbonate–sericite, and silicate. Fluid inclusions in all Stage 1 to 3 quartz are dominated by vapor-liquid two-phase aqueous type (W-type). Petrographic and microthermometric analyses of the fluid inclusions indicate that the homogenization temperatures of Stages 1, 2, and 3 are 198–332°C, 132–260°C, and 97–166°C, with salinities of 4.0–13.3, 1.1–13.1, and 1.9–7.6 wt% NaCleqv, respectively. The vapor comprises primarily H2O, with some CO2, H2, CO, N2, and CH4. The liquid phase contains Ca2+, Na+, K+, SO42−, Cl−, and F−. The sulfides have δ34S=–1.42 to +2.35‰ and 208Pb/204Pb=37.771 to 38.795, 207Pb/204Pb=15.388 to 15.686, and 206Pb/204Pb=17.660 to 18.101. The H–C–O–S–Pb isotope compositions indicate that the ore-forming materials may have been derived from the Taihua Group and the granitic magma. The fluid boiling and cooling and mixing with meteoric water may have been critical for the Ag–Pb–Zn ore precipitation. Geological and geochemical characteristics of the Longmendian deposit indicate that the deposit is best classified as medium- to low-temperature intermediate-sulfidation (LS/IS) epithermal-type, related to Cretaceous crustal-extension-related granitic magmatism.

Beschreibung: In the present paper, sufficient conditions ensuring the complete controllability for a class of semilinear fractional nonlocal evolution systems with finite delay in Banach spaces are derived. The new results are obtained under a weaker definition of complete controllability we introduced, and then the Lipschitz continuity and other growth conditions for the nonlinearity and nonlocal item are not required in comparison with the existing literatures. In addition, an appropriate complete space and a corresponding time delay item are introduced to conquer the difficulties caused by time delay. Our main tools are properties of resolvent operators, theory of measure of noncompactness, and Mönch fixed point theorem.

Beschreibung: Hydraulic properties of hydrate-bearing sediments are largely affected by the maximum size of pores occupied by fluids. However, effects of host particle properties on the maximum size of fluid-occupied pores within hydrate-bearing sediments remain elusive, and differences in the maximum equivalent, incircle, and hydraulic diameters of fluid-occupied pores evolving with hydrate saturation have not been well understood. In this study, numerical simulations of grain-coating and pore-filling hydrate nucleation and growth within different artificial porous media are performed to quantify the maximum equivalent, incircle, and hydraulic diameters of fluid-occupied pores during hydrate formation, and how maximum diameters of fluid-occupied pores change with hydrate saturation is analyzed. Then, theoretical models of geometry factors for incircle and hydraulic diameters are proposed based on fractal theory, and variations of fluid-occupied pore shapes during hydrate formation are discussed. Results show that host particle properties have obvious effects on the intrinsic maximum diameters of fluid-occupied pores and introduce discrepancies in evolutions of the maximum pore diameters during hydrate formation. Pore-filling hydrates reduce the maximum incircle and hydraulic diameters of fluid-occupied pores much more significantly than grain-coating hydrates; however, hydrate pore habits have minor effects on the maximum equivalent diameter reduction. Shapes of fluid-occupied pores change little due to the presence of grain-coating hydrates, but pore-filling hydrates lead to much fibrous shapes of fluid-occupied pores.

Beschreibung: Solution multiplicity of natural ventilation in buildings is of much importance for personnel safety and ventilation design. In this paper, a new mathematical model of buoyancy pressure ventilation for two vertically connected open cavities is presented. Compared with the previous published papers studying two vertically connected open cavities with equal heights and hot source E2 

Beschreibung: Considering the multienergy structure of the electricity market and supply-side competition reform in China, a dual-channel and multiproduct supply chain model is constructed. There are three players in the game model: new energy company and traditional energy company provide energy for the market and the State Grid at the same time. The State Grid is a retailer who buys electricity from two companies and supplies to the market after converting and transmitting the power. Three companies can invest in grid management for saving energy and reducing losses. The energy loss rate is an exponential function of line loss investment. Through the bifurcation graph, Lyapunov exponent, and the basin of parameter, the complex characteristics of the investment market are analyzed. It is interesting to find the Grazing–Hopf bifurcation which usually occurs in nonlinear circuits. The mixed expectation of bounded rationality and the naive expectation is conducive to suppressing the bifurcation and chaos of the market. When external shocks occur, the control model has good robustness.

Beschreibung: With the energy consumption increasing, the coal supply in China has been becoming tight, which has made it difficult for thermal power generation in Yunnan Province. Making full use of local inferior coal and biomass resources in Yunnan can remedy the lack of fuel in power plants. In this paper, an oxygen-rich atmosphere thermogravimetric experiment was performed for a blended sample of Xiaolongtan lignite, Yiliang tobacco rod, and Fuyuan bituminous coal. The combustion characteristics of the mixed fuel under several key operating parameters (i.e., mass ratios, oxygen concentration, and heating rates) were studied. The response surface methodology was used to determine the optimal blending ratio of the three fuels. The results show that the ignition and burnout temperature of coal decrease and the combustion time diminishes with the enrichment of oxygen. The optimal oxygen concentration in the practical application is around 30%. The activation energy and preexponential factor increase with the enlargement of oxygen concentration. Such complex evaluation and optimization approach ensure the stable operation of thermal power plant production.

Beschreibung: Although tectonic plates are usually considered as rigid blocks, intraplate deformation such as lithospheric buckling or diffuse brittle deformation has been recognized for a long time. However, the origin of these deformations remains puzzling. Indeed, whereas the chronology of deformation at plate boundaries can be constrained by numerous methods (syntectonic sedimentary record, thermochronology, etc.), dating of brittle structures (faults, veins, and joints) in the far-field domains remains challenging, preventing a global interpretation of the system as a whole. In this contribution, we have combined a tectonic study with a synkinematical geochronological study of fault-related calcites of the Grands Causses intraplate domain, north of the Pyrenean orogeny. We show that these faults record a much longer history of deformation than previously thought. The Mesozoic extension, usually attributed to an early Jurassic Tethysian rifting event, probably lasted until the Barremian-Aptian epoch, in response to the Pyrenean basin’s opening. The so-called “Pyrenean deformation” of the Grands Causses domain, usually associated with the paroxysm of deformation in the belt during the late Eocene, began much earlier, around 100 Ma, and lasted for more than 60-70 Ma. This study demonstrates the high sensitivity of an intraplate domain (Grands Causses area) to record extensional or compressional deformations occurring at the edge of neighbouring plates.

Beschreibung: This paper mainly investigates the projection synchronization of complex chaotic systems with both uncertainty and disturbance. Using the linear feedback method and the uncertainty and disturbance estimation- (UDE-) based control method, the projection synchronization of such systems is realized by two steps. In the first step, a linear feedback controller is designed to control the nominal complex chaotic systems to achieve projection synchronization. An UDE-based controller is proposed to estimate the whole of uncertainty and disturbance in the second step. Finally, numerical simulations verify the feasibility and effectiveness of the control method.

Beschreibung: A signal denoising method using improved wavelet threshold function is presented for microchip electrophoresis based on capacitively coupled contactless conductivity detection (ME-C4D) device. The evaluation results of denoising effect for the ME-C4D simulation signal show that using Daubechies 5 (db5) wavelet at a decomposition level 4 can produce the best performance. Furthermore, the denoising effect is compared with, as well as proved to be superior to, the existing techniques, such as Savitzky–Golay, Fast Fourier Transform, and soft threshold method. This method has been successfully applied to the self-developed ME-C4D equipment. After executing this method, the noise is cleanly removed, and the signal peak shape and peak area are well maintained.

Beschreibung: Deep geothermal resources are becoming an increasingly important energy source worldwide. To achieve the optimal efficiency of this resource, the heat transfer characteristics between flowing water and rock need to be further studied. Using the stereotopometric scanning system 3D CaMega, the fracture geometry data of five cuboid granite rocks were obtained to determine the effects of fracture roughness on the heat transferability of rock. A 3-D model was built based upon the scanned geometry data to assess the effects of rock temperature, water velocity, and roughness, and aperture size of fracture surface on the heat transfer coefficient. The simulation tests show that water velocity has the most noticeable effect, followed by aperture size and rock roughness. On the other hand, the initial rock temperature has the least influence. A new heat transfer coefficient was proposed considering aperture size, water flow velocity, and rock fracture roughness. The calculated values of Reynolds, Prandtl, and Nusselt numbers obtained using this coefficient are in good agreement with the numerical simulation results. This study provides a reference for enhancing the heat transfer coefficient to benefit the exploitation of heat energy of hot dry rock.

Beschreibung: Spiking neural P systems are a class of computation models inspired by the biological neural systems, where spikes and spiking rules are in neurons. In this work, we propose a variant of spiking neural P systems, called spiking neural P systems with polarizations and rules on synapses (PSNRS P systems), where spiking rules are placed on synapses and neurons are associated with polarizations used to control the application of such spiking rules. The computation power of PSNRS P systems is investigated. It is proven that PSNRS P systems are Turing universal, both as number generating and accepting devices. Furthermore, a universal PSNRS P system with 151 neurons for computing any Turing computable functions is given. Compared with the case of SN P systems with polarizations but without spiking rules in neurons, less number of neurons are used to construct a universal PSNRS P system.

Beschreibung: A pore-scale model has been developed to study the gas flow through multiscale porous media based on a two-dimensional self-similar Sierpinski carpet. The permeability tensor with slippage effect is proposed, and the effects of complex configurations on gas permeability have been discussed. The present fractal model has been validated by comparison with theoretical models and available experimental data. The numerical results show that the flow field and permeability of the anisotropic Sierpinski model are different from that of the isotropic model, and the anisotropy of porous media can enhance gas permeability. The gas permeability of porous media increases with the increment of porosity, while it decreases with increased pore fractal dimension under fixed porosity. Furthermore, the gas slippage effect strengthens as the pore fractal dimension decreases. However, the relationship between the gas slippage effect and porosity is a nonmonotonic decreasing function because reduced pore size and enhanced flow resistance may be simultaneously involved with decreasing porosity. The proposed pore-scale fractal model can present insights on characterizing complex and multiscale structures of porous media and understanding gas flow mechanisms. The numerical results may provide useful guidelines for the applications of porous materials in oil and gas engineering, hydraulic engineering, chemical engineering, thermal power engineering, food engineering, etc.

Beschreibung: Carboniferous–Permian coal seams in the Datong coalfield are intruded by Mesozoic magmatic dikes and sills. Our observations indicate that these dikes and sills have been seriously altered and have lost their original characteristics. Although this phenomenon has been mentioned in some studies, there is a lack of detailed research on the alteration mechanism. To fill this research gap, six dike samples were collected in this study to analyze their alteration characteristics and mechanisms. Petrographic analysis, scanning electron microscopy, and X-ray diffraction were used to determine the mineralogy of the altered igneous samples. The results suggest that the mineral alteration is associated with severe carbonation and clavization. The carbonation of mafic minerals is due to the release of CO2 generated from the coking of high volatile bituminous coals that may have occurred during the intrusive event. However, labradorite did not react with CO2. The water activity in the coal seam was enhanced by the dikes, and mafic minerals were converted into mixtures of chlorite and smectite group minerals. The water activity is especially high at the edges of the dike. Albite and clay minerals were formed due to the albitization of labradorite. Based on these effects, the dike can be divided into weak alteration, carbonation, and clavization bands. The alteration processes in the coal seam are described in detail in this work, and potential formation mechanisms are suggested.

Beschreibung: Considering the complex problem of competition and cooperation among enterprises in the process of product selling and recycling, different coopetition game models of closed-loop supply chain with the fairness preference of a manufacturer and retailers are constructed according to the actual investigation. Then, this study primarily used fairness preference theory and game theory to analyze the impact of fairness preference on the pricing decision, recycling and remanufacturing strategy, and coopetition model selection. The results show that (1) enterprises’ fairness preference would increase the wholesale price and retail price, and the stronger the degree of fairness preference is, the more obvious the trend is; (2) enterprises’ fairness preference is not conducive to recycling and remanufacturing, and the higher level of fairness preference is associated with the lower recycling rate of waste products; (3) enterprises’ fairness preference would not affect the model selection but would benefit the overall profit.

Beschreibung: Aiming at the problems of low contrast and low definition of fog degraded image, this paper proposes an image defogging algorithm based on sparse representation. Firstly, the algorithm transforms image from RGB space to HSI space and uses two-level wavelet transform extract features of image brightness components. Then, it uses the K-SVD algorithm training dictionary and learns the sparse features of the fog-free image to reconstructed I-components of the fog image. Using the nonlinear stretching approach for saturation component improves the brightness of the image. Finally, convert from HSI space to RGB color space to get the defog image. Experimental results show that the algorithm can effectively improve the contrast and visual effect of the image. Compared with several common defog algorithms, the percentage of image saturation pixels is better than the comparison algorithm.

Beschreibung: Hyaloclastites commonly form high-quality reservoir rocks in volcanic geothermal provinces. Here, we investigated the effects of confinement due to burial following prolonged accumulation of eruptive products on the physical and mechanical evolution of surficial and subsurface (depths of 70 m, 556 m, and 732 m) hyaloclastites from Krafla volcano, Iceland. Upon loading in a hydrostatic cell, the porosity and permeability of the surficial hyaloclastite decreased linearly with mean effective stress, as pores and cracks closed due to elastic (recoverable) compaction up to 22-24 MPa (equivalent to ~1.3 km depth in the reservoir). Beyond this mean effective stress, denoted as P∗, we observed accelerated porosity and permeability reduction with increasing confinement, as the rock underwent permanent inelastic compaction. In comparison, the porosity and permeability of the subsurface core samples were less sensitive to mean effective stress, decreasing linearly with increasing confinement as the samples compacted elastically within the conditions tested (to 40 MPa). Although the surficial material underwent permanent, destructive compaction, it maintained higher porosity and permeability than the subsurface hyaloclastites throughout the experiments. We constrained the evolution of yield curves of the hyaloclastites, subjected to different effective mean stresses in a triaxial press. Surficial hyaloclastites underwent a brittle-ductile transition at an effective mean stress of ~10.5 MPa, and peak strength (differential stress) reached 13 MPa. When loaded to effective mean stresses of 33 and 40 MPa, the rocks compacted, producing new yield curves with a brittle-ductile transition at ~12.5 and ~19 MPa, respectively, but showed limited strength increase. In comparison, the subsurface samples were found to be much stronger, displaying higher strengths and brittle-ductile transitions at higher effective mean stresses (i.e., 37.5 MPa for 70 m sample, 〉75 MPa for 556 m, and 68.5 MPa for 732 m) that correspond to their lower porosities and permeabilities. Thus, we conclude that compaction upon burial alone is insufficient to explain the physical and mechanical properties of the subsurface hyaloclastites present in the reservoir at Krafla volcano. Mineralogical alteration, quantified using SEM-EDS, is invoked to explain the further reduction of porosity and increase in strength of the hyaloclastite in the active geothermal system at Krafla.

Beschreibung: Power efficiency of two-stroke spark-ignition engine is generally low because improper amount of fuel injection leads to a lot of unburned fuel loss during the engine working process. However, parameters of the fuel injection system are hard to confirm by aviation experiments due to expensive test costs. This paper proposes a method of calibrating injection parameters of two-stroke spark-ignition engine based on thermodynamic simulation and parameter optimum algorithm. Firstly, the one-dimensional thermodynamic model is built according to the internal structure and thermodynamic process of the engine; then, the model parameters are corrected according to the operating principle of the injector; after experimental verification of the model, considering both the engine power sufficiency and fuel economy, Analytic Hierarchy Process method is applied to look for the optimal injection amount and fuel injection advance angle at different engine working speeds; finally, an aeroengine experiment station with an electronic fuel injector system is built. Through simulation and experiment studies, it can be seen that when the engine speed changes from 3000 to 3500 RPM, the oil consumption rate of the optimal results is higher than that of the previous ones; when the aeroengine speed is higher than 4000 RPM, the oil consumption rate results of the optimal method are 10% to 27% higher than the original results. This paper can be a reference in the optimization of UAV aircraft engine.

Beschreibung: The conjugate gradient projection method is one of the most effective methods for solving large-scale monotone nonlinear equations with convex constraints. In this paper, a new conjugate parameter is designed to generate the search direction, and an adaptive line search strategy is improved to yield the step size, and then, a new conjugate gradient projection method is proposed for large-scale monotone nonlinear equations with convex constraints. Under mild conditions, the proposed method is proved to be globally convergent. A large number of numerical experiments for the presented method and its comparisons are executed, which indicates that the presented method is very promising. Finally, the proposed method is applied to deal with the recovery of sparse signals.

Beschreibung: This paper establishes a two-echelon supply chain consisting of one manufacturer and one retailer. We consider the retailer buys a product from the manufacturer and sells it to consumers through a store channel and an online channel. The retailer needs to bear a fixed investment cost to running its store/online channel. We discuss the impact of the fixed investment cost, the operating cost for the product, and substitutive factor between the two channels on the optimal strategy for the retailer using complex network theory. The result shows that the ratio of net surplus and the ratio of the operating cost between the two channels play a significant role in the retailer’s optimal decisions. Moreover, finance constraint and the fixed investment cost are also two vital factors for the retailer to channel selection strategy. Numerical experiment shows the effectiveness of the conclusion, and some meaningful insights are generated.

Beschreibung: With the background of aging, ensuring the deep integration of pension and medical services and effectively integrating pension resources and medical resources are hot issues that must be addressed in the current mode of integrating health and care services for older people. Thus, we use game theory to construct the utility model of resource allocation between pension and medical institutions. We apply this model to explore how pension institutions and medical institutions invest resources into the integration of health and care services, analysis of influencing factors, and conducting incentive mechanism research by using MATLAB 2016b software. Through theoretical deduction and experimental analysis, the following conclusions are drawn. First, the income distribution coefficient of pension institutions is positively correlated with the level of labor input, and its growth rate has a marginal diminishing effect on the level of labor. Second, in early investment, the income distribution coefficient of pension institutions is positively correlated with fixed asset investment regardless of the different effort coefficients between medical institutions and pension institutions. With a high income distribution coefficient, pension institutions are negatively correlated and marginally decrease. Third, in early investment, the income distribution coefficient of pension institutions is positively correlated with medical institutions’ labor input level. When the income distribution coefficient of pension institutions reaches a certain value, it is negatively correlated with the labor input level of medical institutions, thereby showing a marginal diminishing effect.

Beschreibung: Wind farm siting relies on in situ measurements and statistical analysis of the wind distribution. The current statistical methods include distribution functions. The one that is known to provide the best fit to the nature of the wind is the Weibull distribution function. It is relatively straightforward to parameterize wind resources with the Weibull function if the distribution fits what the function represents but the estimation process gets complicated if the distribution of the wind is diverse in terms of speed and direction. In this study, data from a 101 m meteorological mast were used to test several estimation methods. The available data display seasonal variations, with low wind speeds in different seasons and effects of a moderately complex surrounding. The results show that the maximum likelihood method is much more successful than industry standard WAsP method when the diverse winds with high percentile of low wind speed occur.

Beschreibung: Transportation is an example of a typical, open, fluid complex network system. Expressways are one form of complex transportation networks, and expressway service areas serve as infrastructure nodes in the expressway transportation network; hence, their construction has a significant impact on tourism development and utilization. Domestic and foreign studies on complex transportation networks have mostly been conducted from the perspective of railways, air transport, and urban transportation but seldom on expressway transportation networks. This study employed complex network theory, social network analysis, kernel density analysis, and bivariate autocorrelation to characterize the spatial structure of expressway transport networks in terms of geographical centrality. By innovating the coupling of geographical centrality and passenger flow centrality in clustering, the study also quantitatively analyzed the differences between the geographical advantage and actual passenger flow advantage of China’s Guizhou expressway transportation network to analyze the tourism utilization potential of expressway service areas. We found that (1) the geographical centrality of the Guizhou expressway transportation network ranged from −1.28 to 3.33, and its distribution shows a single-core, polyconcentric dispersed spatial structure; (2) the passenger-car flow rate ranged from 15,000 to 3.66 million, and its distribution showed a dual-core, polycentric dispersed structure that is weakly concentric; and (3) there was a positive correlation of 0.22 between the geographical centrality and passenger flow of the Guizhou expressway transportation network, which showed seven cluster types—“high-high,” “moderately high-high,” “low-high,” “moderately low-high,” “high-low,” “moderately high-low,” and “low-low”—for which seven corresponding models of tourism development were proposed. This study broadens the practical application of traffic network complexity research and provides a scientific basis for upgrading and transforming the Guizhou expressway transportation network as well as for developing composite tourism uses for expressway service areas.

Beschreibung: For face recognition systems, liveness detection can effectively avoid illegal fraud and improve the safety of face recognition systems. Common face attacks include photo printing and video replay attacks. This paper studied the differences between photos, videos, and real faces in static texture and motion information and proposed a living detection structure based on feature fusion and attention mechanism, Dynamic and Texture Fusion Attention Network (DTFA-Net). We proposed a dynamic information fusion structure of an interchannel attention block to fuse the magnitude and direction of optical flow to extract facial motion features. In addition, for the face detection failure of HOG algorithm under complex illumination, we proposed an improved Gamma image preprocessing algorithm, which effectively improved the face detection ability. We conducted experiments on the CASIA-MFSD and Replay Attack Databases. According to experiments, the DTFA-Net proposed in this paper achieved 6.9% EER on CASIA and 2.2% HTER on Replay Attack that was comparable to other methods.

Beschreibung: In this paper, three types of fractional order partial differential equations, including the fractional Cauchy–Riemann equation, fractional acoustic wave equation, and two-dimensional space partial differential equation with time-fractional-order, are considered, and these models are obtained from the standard equations by replacing an integer-order derivative with a fractional-order derivative in Caputo sense. Firstly, we discuss the fractional integral and differential properties of several functions which are derived from the Mittag-Leffler function. Secondly, by using the homotopy analysis method, the exact solutions for fractional order models mentioned above with suitable initial boundary conditions are obtained. Finally, we draw the computer graphics of the exact solutions, the approximate solutions (truncation of finite terms), and absolute errors in the limited area, which show that the effectiveness of the homotopy analysis method for solving fractional order partial differential equations.

Beschreibung: Fault identification under variable operating conditions is a task of great importance and challenge for equipment health management. However, when dealing with this kind of issue, traditional fault diagnosis methods based on the assumption of the distribution coherence of the training and testing set are no longer applicable. In this paper, a novel state identification method integrated by time-frequency decomposition, multi-information entropies, and joint distribution adaptation is proposed for rolling element bearings. At first, fast ensemble empirical mode decomposition was employed to decompose the vibration signals into a collection of intrinsic mode functions, aiming at obtaining the multiscale description of the original signals. Then, hybrid entropy features that can characterize the dynamic and complexity of time series in the local space, global space, and frequency domain were extracted from each intrinsic mode function. As for the training and testing set under different load conditions, all data was mapped into a reproducing space by joint distribution adaptation to reduce the distribution discrepancies between datasets, where the pseudolabels of the testing set and the final diagnostic results were obtained by the k-nearest neighbor algorithm. Finally, five cases with the training and testing set under variable load conditions were used to demonstrate the performance of the proposed method, and comparisons with some other diagnosis models combined with the same features and other dimensionality reduction methods were also discussed. The analysis results show that the proposed method can effectively recognize the multifaults of rolling element bearings under variable load conditions with higher accuracies and has sound practicability.

Beschreibung: Urban bus networks play an important role, when the capacity of urban public services is evaluated. With recent advancements in Internet and Communication Technologies, there is an emerging interest in building an urban bus network model through open big data. This has rarely been investigated and exposes several challenges in the provision of transportation services in urban planning. On the one hand, it is necessary to combine bus stations based on spatial distance constraints due to their ambiguous definition in open big data; on the other hand, it is difficult and time-consuming to relocate and build new stations, but the optimization of bus lines is relatively easy to implement. This study aimed to develop an explicit methodological framework for building and analyzing two different types of urban bus network model using open big data. Thereafter, the framework was applied in two case studies in China, within a county-level administration and in a region including three county-level administrations. The key result shows that there was a shortage of urban bus services across these different administrations. This paper contributes to the body of research methodologies into public transport networks and to understanding the sharing of urban public services across administrations, improving the management of urban bus networks, and highlighting the importance of examining the characteristics of urban bus network in county-level administrations rather than just in large cities in China.

Beschreibung: High-quality development is an innovative way to promote the sustainable development of the marine economy. This study uses China’s coastal areas as an example, constructing a research framework for the high-quality development of the country’s marine economy. The temporal and spatial variation in the high-quality development of China’s marine economy from 2006 to 2016 is explored utilizing the nuclear density estimation, entropy, and mean standard deviation classification methods. The results show the following: (1) the policy orientation of China’s high-quality marine economic development is obvious, and the focus of policy has changed from the pursuit of growth speed to growth quality; (2) a spatiotemporal differentiation is evident, with the coastal areas of the Yangtze River Delta continuing to be the hotspots of high-quality development. The Bohai rim and Pan Pearl River Delta areas feature a mixture of cold and hot spots, with multipolar spatial differentiation; (3) in terms of development stage, Guangdong, Shanghai, Shandong, Zhejiang, and Tianjin are at advanced levels. The intermediate-level areas consist of Fujian, Jiangsu, Hainan, and Liaoning, while Hebei and Guangxi are the primary-level areas.

Beschreibung: Single-rod electrohydraulic system is widely applied in industrial production due to high power-to-weight ratio, but it generally has a low energy efficiency and has many system states which need to be measured. Therefore, an output feedback controller with energy saving is proposed in this paper. The designed controller only needs a displacement sensor to detect the position of the single-rod cylinder; the other states of the system are estimated by extended state observer (ESO). Besides, a nonlinear disturbance observer (NDO) is introduced to estimate the external mismatched disturbance. The output feedback controller based on extended state observer and nonlinear disturbance observer has a better tracking performance compared with other controllers. In addition, a proportional relief valve (PRV) is introduced to control the supply pressure of the system. The variable supply pressure reduces the energy of throttling loss and overflow loss, which achieves energy saving of about 54% according to the simulation results. Meanwhile, the tracking error of the energy saving controller is stable at 0.1 mm. In a word, the proposed controller not only achieves energy saving but also has a satisfactory trajectory tracking performance.

Beschreibung: In order to realize the unsupervised extraction and identification of fault features in power electronic circuits, we proposed a fault diagnosis method based on sparse autoencoder (SAE) and broad learning system (BLS). Firstly, the feature is extracted by the sparse autoencoder, and the fault samples and feature vectors are combined as the input of the broad learning system. The broad learning system is trained based on the error precision step update method, and the system is used to the fault type identification. The simulation results of the thyristor fault diagnosis of the three-phase bridge rectifier circuit show that the method is effective and has better performance than other traditional methods.

Beschreibung: In this paper, a direction of arrival (DOA) estimator is proposed to improve the cyber-physical interactions, which is based on the second-order statistics without a priori knowledge of the source number. The impact of noise will firstly be eliminated. Then the relationship between the processed covariance matrix and the steering matrix is studied. By applying the elementary column transformation, an oblique projector will be designed without the source number. At last, a rooting method will be adopted to estimate the DOAs with the constructed projector. Simulation results show that the proposed method performs as well as other methods, which requires that the source number must be known.

Beschreibung: In this paper, an ecological model described by a couple of state-dependent impulsive equations is studied analytically and numerically. The theoretical analysis suggests that there exists a semitrivial periodic solution under some conditions and it is globally orbitally asymptotically stable. Furthermore, using the successor function, we study the existence, uniqueness, and stability of order-1 periodic solution, and the boundedness of solution is also presented. The relationship between order-k successor function and order-k periodic solution is discussed as well, thereby giving the existence condition of an order-3 periodic solution. In addition, a series of numerical simulations are carried out, which not only support the theoretical results but also show the complex dynamics in the model further, for example, the coexistence of multiple periodic solutions, chaos, and period-doubling bifurcation.

Beschreibung: Exploring and investigating new chaotic systems is a popular topic in nonlinear science. Although numerous chaotic systems have been introduced in the literature, few of them focus on torus-chaotic system. The aim of our short work is to widen the current knowledge of torus chaos. In this paper, a new torus-chaotic system is proposed, which has one positive Lyapunov exponent, two zero Lyapunov exponents, and two negative Lyapunov exponents. The dynamic behavior is investigated by Lyapunov exponents, bifurcations, and stability. The analysis shows that this system has an interesting route leading to chaos. Furthermore, the pseudorandom properties of output sequence are well studied and a random number generator algorithm is proposed, which has the potential of being used in several cyber security systems such as the verification code, secure QR code, and some secure communication protocols.

Beschreibung: As a sportification form of human-computer interaction, eSports is facing great gender stereotype threat and causing female players’ withdraw. This study aims to investigate the relationship between gender-swapping and females’ continuous participation intention in eSports, the mediating effect of self-efficacy, and the moderating effect of discrimination. The results demonstrate (1) that the effect of gender-swapping on continuous participation intention in eSports was not significant, while gender-swapping had a significant association with self-efficacy, and self-efficacy had a significant association with continuous participation intention in eSports; (2) that gender-swapping had an indirect effect (via self-efficacy) on continuous participation intention in eSports; and (3) that discrimination moderated the effect of self-efficacy on continuous participation intention. Female players who had experienced discrimination displayed higher continuous participation intention in the context of self-efficacy enhanced by gender-swapping.

Beschreibung: Coalbed methane (CBM) plays an important role in securing world energy supply and transiting electricity generation from fossil fuel to renewables. CBM reservoirs are generally very tight and require effective stimulation to achieve economic extraction. In recent years, an increasing number of coal seam stimulation techniques were developed, but selecting the most suitable stimulation technique for a particular CBM reservoir condition is becoming increasingly challenging. Therefore, it is deemed very important to compare the effectiveness of different stimulation techniques in a meaningful way to guide future research directions in this area. In this paper, the stimulation techniques were firstly classified into different categories according to the stimulation mechanisms. Then, the associated principles, the history of advances, and challenges of different stimulation techniques were comprehensively reviewed. Two indexes were proposed to compare the stimulation effectiveness at the laboratory and field scales, respectively. Finally, the comparison and evaluation of each stimulation technique in respect to the stimulation effectiveness, influence range, duration, and environment were conducted in detail; the cryogenic liquid nitrogen stimulation technique receives the highest total score among the discussed laboratory-scale stimulation techniques. Hydraulic fracturing and gas injection stimulation techniques gain the highest total score among key field-scale stimulation techniques. Considering the time required for each stimulation method to take effect, high-voltage electric fracturing may have a greater potential in the future. This work is expected to help better select the optimal stimulation technique for reservoir specific conditions.

Beschreibung: In this paper, with the aid of symbolic computation, several kinds of exact solutions including periodic waves, cross-kink waves, and breather are proposed by using a trilinear form for the (2 + 1)-dimensional Sharmo–Tasso–Olver equation. Then, by combing the different forms, the interactions between a lump and one-kink soliton and between a lump and periodic waves are generated. Moreover, the dynamic characteristics of interaction solutions are analyzed graphically by selecting suitable parameters with the help of Maple.