ALBERT

Beschreibung: Entanglement is a key feature of many-body quantum systems. Measuring the entropy of different partitions of a quantum system provides a way to probe its entanglement structure. Here, we present and experimentally demonstrate a protocol for measuring the second-order Rényi entropy based on statistical correlations between randomized measurements. Our experiments, carried out with a trapped-ion quantum simulator with partition sizes of up to 10 qubits, prove the overall coherent character of the system dynamics and reveal the growth of entanglement between its parts, in both the absence and presence of disorder. Our protocol represents a universal tool for probing and characterizing engineered quantum systems in the laboratory, which is applicable to arbitrary quantum states of up to several tens of qubits.

Beschreibung: When preserving perishable goods, maintaining a constant temperature over the cold supply chain is essential. Therefore, refrigerated vehicles are an important part of the cold supply chain system. However, many traditional refrigerated cargo systems are not designed to support the homogeneity of the temperature inside cargo trailers. Indeed, refrigerating equipment is usually placed on one side of transportation systems as this is considered to be more practical. Such a configuration thus leads to significant temperature differences in the two distinct parts of a refrigerated cargo trailer, which might affect the quality, safety, and shelf life of perishable foods. This research aims to improve the temperature distribution of refrigerated trailers. In this study, it is highlighted that in the most commonly used traditional refrigerated trailer models, lower air velocity and higher product temperature are observed at the rear. There is also a partial product chilling risk at the front of the refrigerated trailer. This study investigates and reports significant differences among the three airflow design models of refrigerated cargo systems by applying turbulence flow, heat, and mass transfer models. The analyses of these three models reveal that significant improvement could be achieved by applying the proper arrangements of inlets on the ceiling of the trailer body.

Beschreibung: Professional truck drivers are prone to both physical and psychological stress. Such stress can lead to burnout. Drawing on Job Demands Resources literature and stress research, we investigate the relationship between job related role stressors and three components of burnout, among professional truck drivers who are based in the Netherlands. They were surveyed with a time-lagged design (interval of two months). In the first wave, the different potential causes of burnout were measured (role conflict, role ambiguity, quality of sleep, and the perceived emotional intelligence of the dispatcher). In the second wave, the three elements of burnout were measured: emotional exhaustion, depersonalization, and low personal accomplishment. The results of our study indicate that role conflict relates positively to all three components of a burnout. The emotional intelligence of the dispatcher—as perceived by the truck drivers—was negatively related with the three components of a burnout. Finally, the quality of sleep had an impact on depersonalization and emotional exhaustion. Theoretically, several job specific role stressors are confirmed to play a role in truck driver burnout. However, the top three role stressors all appeared to be related to the trucking industry, instead of a particular employer, and they may therefore require national policy measures.

Beschreibung: Accurate travel time prediction is of high value for freight transports, as it allows supply chain participants to increase their logistics quality and efficiency. It requires both sufficient input data, which can be generated, e.g., by mobile sensors, and adequate prediction methods. Machine Learning (ML) algorithms are well suited to solve non-linear and complex relationships in the collected tracking data. Despite that, only a minority of recent publications use ML for travel time prediction in multimodal transports. We apply the ML algorithms extremely randomized trees (ExtraTrees), adaptive boosting (AdaBoost), and support vector regression (SVR) to this problem because of their ability to deal with low data volumes and their low processing times. Using different combinations of features derived from the data, we have built several models for travel time prediction. Tracking data from a real-world multimodal container transport relation from Germany to the USA are used for evaluation of the established models. We show that SVR provides the best prediction accuracy, with a mean absolute error of 17 h for a transport time of up to 30 days. We also show that our model performs better than average-based approaches.

Beschreibung: Economic potential of feedstock generated low-valued forest residue can be enhanced by emerging biomass conversion technologies (BCT), such as torrefaction, briquetting, and gasification. However, for implementing these emerging processes within the woods, several hurdles are to be overcome, among which a balanced supply chain is pivotal. Centralized biomass recovery operation (CBRO) could be an economically viable solution in accessing harvesting sites and allows integration of BCT into forest management. The goal of this study was to examine the logistic effects of integrating a BCT into a CBRO, under different in-wood scenarios based on variations in travel time between the facility locations, amount of raw materials handled, intermediate storage capacity, and duration (number of days) of annual operations. Specific objectives included analyzing the effects of forest residue recoverability (BDMT, bone dry metric ton/ha), total transportation time from the harvest unit to the market, and the annual number of in-woods production sites on the overall efficiency of the BCT operations. Concurrently, this study examined the forest managerial impacts due to such an integration. Location-allocation tool (maximize market share problem type) within the ArcGIS Network Analyst platform was utilized to model the scenarios and generate one-way travel times from the harvest site to final markets. Results from geospatial analysis showed that there were 89–159 and 64–136 suitable locations for the BCT for logistics model (LM) I and II, respectively. Total one-way travel time for all the models ranged between 1.0–1.7 h. Additionally, the annual numbers of BCT sites was inversely proportional to the total one-way travel time (i.e., harvest unit to market). Arranging CBRO and BCT operations to occur at the same in-woods site returned shorter total and average travel times than arranging the two activities at separate in-woods sites. The model developed for this study can be used by forest managers and entrepreneurs to identify sites for placing BCTs in the forest that minimizes transportation times.

Beschreibung: This article presents the results of theoretical and empirical studies on the search for new logistics development paradigms needed to meet the challenges of the twenty-first century global economy. The author reviews the major factors determining the effectiveness of international processes and operations, including logistics success potentials in supply chains. Furthermore, the article proposes methods for measuring logistics performance, specifically the logit model and the model of fuzzy logic, which could be used to assess whether a firm’s planned investments in logistics infrastructure will end in success or failure. The article also evaluates the impact of logistics on the development of international trade in the practice of Polish firms. The studies cover a period before Poland’s accession to the European Union (EU) (2000 to 2004), and after the accession, from 2005 to 2016, and are supplemented with a forecast for logistics development in Polish firms until 2020.

Beschreibung: The Internet of Things (IoT) is an emerging paradigm branded by heterogeneous technologies composed of smart ubiquitous objects that are seamlessly connected to the Internet. These objects are deployed as Low power and Lossy Networks (LLN) to provide innovative services in various application domains such as smart cities, smart health, and smart communities. The LLN is a form of a network where the interconnected devices are highly resource-constrained (i.e., power, memory, and processing) and characterized by high loss rates, low data rates, and instability in the communication links. Additionally, IoT devices produce a massive amount of confidential and security-sensitive data. Various cryptographic-based techniques exist that can effectively cope with security attacks but are not suitable for IoT as they incur high consumption of resources (i.e., memory, storage and processing). One way to address this problem is by offloading the additional security-related operations to a more resourceful entity such as a fog-based node. Generally, fog computing enables security and analysis of latency-sensitive data directly at the network’s edge. This paper proposes a novel Fog Security Service (FSS) to provide end-to-end security at the fog layer for IoT devices using two well-established cryptographic schemes, identity-based encryption, and identity-based signature. The FSS provides security services such as authentication, confidentiality, and non-repudiation. The proposed architecture would be implemented and evaluated in an OPNET simulator using a single network topology with different traffic loads. The FSS performed better when compared with the APaaS and the legacy method.

Beschreibung: Counterfeiting has always been a concern, costing a significant amount of money and causing losses in international trading markets. Radio frequency identification (RFID) tag Anti-counterfeiting is a conceptual solution that has received attention in the past few years. In this article, we present a survey study on the research topic of anti-counterfeiting products using RFID tags on merchandise. As this issue evolved in industry, there were several techniques used to address the problem; each technique uses a different concept and mechanism in resolving the issue. Each technique also has different pros and cons which we will address at the end of this paper with our findings. As we explore RFID technology and its implementation, we will discuss previous research before proceeding to the core of the topic of RFID Anti-counterfeiting based on the methods used. We compare the different techniques used at the end of the paper.

Beschreibung: Thanks to their arising abilities to influence the human lifestyle, along with reducing the healthcare systems’ cost, wireless body area networks (WBANs) still form a strongly growing research field. Recent advances focus on the opportunities of coexistence and communication between a group of WBANs, that will forward the sensing data, using persons as network relays, until reaching a remote analysis server or cloud servers via the Internet, forming thus a body-to-body network (BBN). Such new-style networks support a range of innovative and promising applications, including ubiquitous healthcare (U-health), interactive games, and military, to cite a few. In this paper, we first present the evolution of the single WBAN concept to the cooperative network of multiple WBANs, giving rise to the BBN concept. A synopsis of the WBAN and BBN respective standards and applications is given, and the emerging BBN challenges are highlighted. Then, we present and discuss the existing WBAN proposals, especially the candidate WBAN protocols that could be adapted and used in BBNs, focusing on four intrinsically related axes of great importance for BBN design: energy efficiency, mobility prediction, quality of service (QoS) and security. Further BBN open issues are also investigated, namely, the wireless propagation between humans carrying wearable devices, the interference, storage and privacy issues as well as the heterogeneity of BBN devices and traffic.

Beschreibung: A service function chain (SFC) is an ordered virtual network function (VNF) chain for processing traffic flows to deliver end-to-end network services in a virtual networking environment. A challenging problem for an SFC in this context is to determine where to deploy VNFs and how to route traffic between VNFs of an SFC on a substrate network. In this paper, we formulate an SFC placement problem as an integer linear programing (ILP) model, and propose an availability-enhanced VNF placing scheme based on the layered graphs approach. To improve the availability of SFC deployment, our scheme distributes VNFs of an SFC to multiple substrate nodes to avoid a single point of failure. We conduct numerical analysis and computer simulation to validate the feasibility of our SFC scheme. The results show that the proposed scheme outperforms well in different network scenarios in terms of end-to-end delay of the SFC and computation time cost.

Beschreibung: The tremendous increase in the urban population highlights the need for more efficient transport systems and techniques to alleviate the increasing number of the resulting traffic-associated problems. Modeling and predicting road traffic flow are a critical part of intelligent transport systems (ITSs). Therefore, their accuracy and efficiency have a direct impact on the overall functioning. In this scope, a new approach for predicting the road traffic flow is proposed that combines the Petri nets model with a dynamic estimation of intersection turning movement counts to ensure a more accurate assessment of its performance. Thus, this manuscript extends our work by introducing a new feature, namely turning movement counts, to attain a better prediction of road traffic flow. A simulation study is conducted to get a better understanding of how predictive models perform in the context of estimating turning movements.

Beschreibung: Continuous monitoring of breathing activity plays a major role in detecting and classifying a breathing abnormality. This work aims to facilitate detection of abnormal breathing syndromes, including tachypnea, bradypnea, central apnea, and irregular breathing by tracking of thorax movement resulting from respiratory rhythms based on ultrasonic radar detection. This paper proposes a non-contact, non-invasive, low cost, low power consumption, portable, and precise system for simultaneous monitoring of normal and abnormal breathing activity in real-time using an ultrasonic PING sensor and microcontroller PIC18F452. Moreover, the obtained abnormal breathing syndrome is reported to the concerned physician’s mobile telephone through a global system for mobile communication (GSM) modem to handle the case depending on the patient’s emergency condition. In addition, the power consumption of the proposed monitoring system is reduced via a duty cycle using an energy-efficient sleep/wake scheme. Experiments were conducted on 12 participants without any physical contact at different distances of 0.5, 1, 2, and 3 m and the breathing rates measured with the proposed system were then compared with those measured by a piezo respiratory belt transducer. The experimental results illustrate the feasibility of the proposed system to extract breathing rate and detect the related abnormal breathing syndromes with a high degree of agreement, strong correlation coefficient, and low error ratio. The results also showed that the total current consumption of the proposed monitoring system based on the sleep/wake scheme was 6.936 mA compared to 321.75 mA when the traditional operation was used instead. Consequently, this led to a 97.8% of power savings and extended the battery life time from 8 h to approximately 370 h. The proposed monitoring system could be used in both clinical and home settings.

Beschreibung: Mobile health research field aims to provide access to healthcare anytime and anywhere through mobile computing technologies while using a cost-effective approach. Mobile health is closely related to ambient assisted living as both research fields address independence in elderly adults. Aging has become a relevant challenge, as it is anticipated that 20% of world population will be aged 60 years and older in 2050. Most people spend more than 90% of their time indoors, therefore the indoor environmental quality has a relevant impact on occupant’s health and well-being. We intended to provide real-time indoor quality monitoring for enhanced living environments and occupational health. This paper presents the AirPlus real-time indoor environmental quality monitoring system, which incorporates several advantages when compared to other systems, such as scalability, flexibility, modularity, easy installation, and configuration, as well as mobile computing software for data consulting and notifications. The results that were obtained are promising and present a significant contribution to the monitoring solutions available in the literature. AirPlus provides a rich dataset to plan interventions for enhanced indoor quality, but also to support clinical diagnostics and correlate occupant’s health problems with their living environment conditions.

Beschreibung: The increasing demand for location-dependent services in wireless sensor networks (WSNs) calls for solutions capable of handling the diversified demands and the unique challenges presented in WSNs. In most applications, nodes need to determine their locations in a reliable manner while operating under stringent constraints in computation, communication, and energy resources. This paper offers a novel solution to bridge the gap between the high accuracy demand and low resources available for range-based localization. We propose KickLoc, a fully distributed scheme, which considers the uncertainty of the distance measurements to minimize localization errors introduced from the range measurement, and leverages information from all neighboring nodes for better position estimations. Our work is evaluated via extensive simulations, with comparisons to other well-known localization schemes, and the Cramér-Rao lower bound (CRLB). In addition, we implement and evaluate the proposed system on sensor platforms with different range measurement mechanisms. The results show that this localization solution outperforms existing methods in various scenarios, while remains lightweight and suitable for small, low resources WSNs.

Beschreibung: The term smart grid (SG) has been used by many government bodies and researchers to refer to the new trend in the power industry of modernizing and automating the existing power system. SGs must utilize assets optimally by making use of the information, like equipment capacity, voltage drop, radial network structure, minimizing investment and operating costs, minimizing energy loss and reliability indices, and so on. One way to achieve this is to re-route or reconfigure distribution systems (DSs). Distribution systems are reconfigured to choose a switching combination of branches of the system that optimize certain performance parameters of the power supply, while satisfying some specified constraints. In this paper, a blended biased and unbiased weightage (BBUW) multiple attribute decision-making (MADM) method is proposed for finding the compromised best configuration and compared it with other decision-making methods, such as the weighted sum method (WSM), weighted product method (WPM), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The BBUW method is implemented for two distribution systems, and the result obtained shows a good co-relationship between BBUW and other decision-making methods. Further weights obtained from the BBUW method are used for the WSM, WPM and TOPSIS methods for decision making. Examples of the distribution system are worked out in this paper to demonstrate the validity and effectiveness of the method.

Beschreibung: This study investigated the relationship between open innovation and the radicalness of innovation. The balance between radical and incremental innovation is an essential part of the ambidextrous use of explorative and exploitative strategies, and this study assumed that open innovation is usually interlinked with explorative strategies and is thus related to radical innovation performance. Accordingly, following an empirical investigation, we demonstrate that the balance of open innovation firms is slightly skewed toward explorative radical innovation. Using the Korean version of the community innovation survey, we show that the relative radicalness that is projected on innovation output exhibits an inverted-U curve. Furthermore, the curve shifts based on the level of inbound open innovation. Our results suggest that there is an ambidextrous balance between radical and incremental innovation while implementing open innovation. In addition, the research results imply that firms placing greater weight on explorative radical innovations need to consider in-depth open innovation strategies.

Beschreibung: This study aims to identify, from among business strategies presented in Miles and Snow (1978, 2003), those that increase the future performance or growth sustainability of unlisted small and medium-sized enterprises (SMEs) in Korea. (This study applied the scope of SMEs based on Article 2 of the Enforcement Decree of the Tax Exemption Restriction Act in Korea. The Korean tax law sets the scope of SMEs based on independence criteria set by the scale of sales, assets, and affiliation, and subordination. For example, the size standard of a manufacturing industry can be regarded as a small business if the average sales amount is less than 150 billion won or the total amount of assets is less than 500 billion won for three years.) In addition, it analyzes measured variables of business strategy for factors influencing unlisted SMEs’ future performance and growth potential. The objective is to determine a business strategy for unlisted SMEs, which are small, financially challenged, and have shorter lifespans and faster growth rates. The results highlight that investment in research and development (R&D) for new products influences both future performance and growth sustainability. R&D is an important intangible resource of the firm, which increases future risk due to high future uncertainty, but it is also an important factor to increase future performance or value based on resource-based theory. In the accounting field, research and development expenditure also provided evidence of future excess return or performance. This study is meaningful because it identifies the role of research and development in increasing future growth sustainability in SMEs, thus emphasizing change and innovation.

Beschreibung: Commercialization strategy is an all-encompassing plan that organizes technology transfer office goals to commercialize a university’s technologies. Measurement strategy requires feasible variables that make up those goals. This strategy also ensures that all variables that are important in measuring contribute to the larger goals. A useful way to assess and explain the effectiveness of the technology transfer office (TTO) of universities is to model this within a production function/frontier framework. Such a production function is typically estimated econometrically. This study presents evidence on the relative efficiency of research commercialization in the university through the data envelopment analysis (DEA) model. The implication of the DEA efficiency result is to derive the efficiency level of the TTO’s strategy from the observed performance. It also helps in identifying the benchmarking of other TTOs, which would be valuable information for improving their new technology commercialization strategy. In detail, a benchmark is provided to improve the weakness of strategy and resource allocation of a poorly performing TTO. The proposed matrix of indicators is an exploit of how performance could be measured within the decision-making units that have been chosen. By introducing the measure to commercialization strategy framework the development of technology transfer offices policies are considered.

Beschreibung: This research aims to forecast future economic and environmental growth for the next 16 years (2020–2035) according to the government’s strategic framework by applying the second order autoregressive-structural equation model (second order autoregressive-SEM). The model is validated by various measures, fits with the best model standards, meets all criteria of the goodness of fit, and is absent from any issues of heteroskedasticity, multicollinearity, autocorrelation, and non-normality. The proposed model is very distinct from other alternatives in that it produces the optimal outcome. Its mean absolute percentage error (MAPE) is 1.02% while the root mean square error (RMSE) is 1.51%. A comparison of the above results is carried out to compare the same values from other models, namely the regression linear model (ML model), back propagation neural network (BP model), artificial neural natural model (ANN model), gray model, and the autoregressive integrated moving average model (ARIMA model). The second order autoregressive-SEM is a model that is appropriate for long-term forecasting (2020–2035), and accounts for the specifics of the Thai government strategy set under the Industry 4.0 policy framework. The results of the long-term analysis indicate that the current political policy will result in continuous economic growth, where the gross national product (GNP) growth rate will climb up to 6.45% per annum by 2035, while the environment is being negatively affected. The study predicts that CO2 emissions will rise up to 97.52 Mt CO2 Eq. (2035). The forecasting model also reflects that the economy factor has an adjustment ability to equilibrium stronger than that of the environment factor; further, it shows that the relationship between the factors is causal. In addition, the political policy , economy , and environment factors are found to have both direct and indirect effects. As to the results, this study illustrates that the Industry 4.0 policy is still inefficient, as the carbon dioxide emissions are projected to be higher than the threshold for environment hazards and disasters which set to the limit of 80 Mt CO2 Eq. by 2035. The effect of such policy will put the environment at risk, and the government must take immediate action to respond to this urgency. Thus, the second order autoregressive-SEM model remains a significant model embedded with the adjustment ability to equilibrium and the applicability for various contexts in different sectors. This introduced model is a vital tool for assisting the national government to create policy that is effective and sustainable, and lead to positive development of the nation. This second order autoregressive-SEM model can be used as a resource for the management of both public policy and private enterprise.

Beschreibung: Today’s dynamic and complex environment means that companies are trying to develop entrepreneurial thinking as a competitive advantage. Universities around the world are simultaneously increasing entrepreneurial training across a broad array of majors. However, the entrepreneurial training is not heavily connected to industry needs. This paper focuses on how industry and universities can cooperate to prepare students for corporate entrepreneurial thinking. The research is based on extensive literature, reports, and in-depth interviews with 28 people from various parts of the RTP (Research Triangle Park), including companies, government agencies, and numerous programs at multiple universities. The major finding from this study is that the strength of entrepreneurial education in the regional innovation system reinforces the companies’ open innovation capacity and their performance. To be successful at launching campus-wide entrepreneurship education to increase understanding of corporate entrepreneurship, Corporate Entrepreneurship Education (CEE) must include (1) entrepreneurial leadership; (2) faculty champions; (3) student-focused policies; (4) engagement with the community; and (5) a decentralized, autonomous structure of entrepreneurship programs.

Beschreibung: This paper extends resource dependence logic by investigating the antecedents of technological diversification and further identifies its boundary condition. We argue that this resource dependence logic is bound by state ownership through coalitions with firms, a less discussed component of interdependence. The empirical results, based on a panel data analysis of Chinese listed firms, suggest that environmental dynamism positively relates to technological diversification, while environmental munificence negatively relates to technological diversification. These relationships changed when state ownership is considered. The theoretical implications for resource dependence theory and diversification research are discussed.

Beschreibung: Industry 4.0, started in Germany in 2011, was fervently promoted by various advanced countries and followed by the introduction of “smart manufacturing”. As an innovative strategy of the manufacturing industry “smart manufacturing” has attracted considerable attention in the field of academics and practice. However, the issues of huge investment and differentiation of individual enterprises have created a big gap between policy promotion and production at the site of actual industrial manufacturing and resulted in limited progress in smart manufacturing. In view of the situation, the authors have previously developed in relation to the practice of individual companies in the industry a practical structure of “Lean Smart Manufacturing: a conceptual framework and solution based co-creative platform” combining Lean Production with smart manufacturing to achieve customer value. In addition to filling the gap between government policy and industry in Industry 4.0, the practical structure suggests the possibility of balancing differentiation and open innovation. Taiwan’s bicycle industry is one of Taiwan's most internationally competitive industries. GIANT, the leading manufacturer of bicycles in Taiwan, has been actively promoting TPS since 2000. With the development of Industry 4.0, GIANT has been working on the application of Industry 4.0 related technologies in order to further enhance customer value. In the application of the practical structure of “Lean Smart Manufacturing”, there are few cases of corporate practice. This study focuses on the A-Team which is constructed by the bicycle industry in Taiwan and GIANT for empirical research, to see how GIANT implement the “Lean Smart Manufacturing” and construct the co-creative platform, to balance differentiation and open innovation, then strengthen its competitiveness. The research results show that although this case is still in the development stage, it has the basic form of “Lean Smart Manufacturing: a conceptual framework and solution based co-creative platform”. This case, as we advocate the use of differentiated advantages of “Lean Smart Manufacturing”, pragmatically from the establishment of the smart factory platform on the physical system, gradually extended to the strategic co-creative platform of the cyber system.

Beschreibung: The purpose of this study is to reveal the effect of personal value as a part of creating shared value (CSV). We extracted factors of personal value through a literature review. Personal value consists of social commitment, self-actualization, goal setting, and solidarity. Self-actualization is the universal motivation of the individual, goal setting is the basis for the occurrence of action, and solidarity is the relationship factor that defends competition and personalization. This study was conducted on three hypotheses. Hypothesis 1 is that self-actualization will have an effect on CSV. Hypothesis 2 is that goal setting will have an effect on CSV. Hypothesis 3 is that solidarity will have an effect on CSV. The proxy of CSV is social commitment. We examine the effects of these personal values on CSV by surveying 557 university students. This study applied the regression model to test the hypotheses. The empirical results are as follows. CSV increases when we are more self-actualized. Goal setting positively affects CSV. CSV goes up as we have many relationships with organizations and are more cooperative in work. This study suggests the important elements of personal values in a university setting for CSV, and enables setting the direction of the education by setting the index of the attitude to increase the value of the individual in CSV.

Beschreibung: This study aims to develop a Modular Object-Oriented Dynamic Learning Environment (Moodle)-based online learning system and derive a class model to enhance learners’ creative collaboration capabilities. The research method for this is first to analyze the functional elements of the online learning system to enhance creative collaboration among the functions of the Moodle online learning system. Second, a class model is derived to enhance creative collaboration by applying the constructivist teaching–learning principle. Third, we conduct a verification of the effectiveness of the Moodle-based class model that was developed to enhance creative collaboration. The results of the study show that, among the functions of the Moodle online learning system, forms, real-time conferencing, reciprocal evaluation, Wiki, and blogs have the ability to enhance creative collaboration. Second, the class model for promoting creative collaboration based on a mood-based online learning system consists of self-reflections, learner-driven learning, professional learning, practical task, and the role of the processor. Third, after verifying the application effect of the Moodle-based class model for university students, a significant effect is found in the creative collaboration of university students. The results of this study suggest that: First, the Moodle online learning system should be utilized to provide learners with a variety of online learning opportunities to promote creative collaboration. Second, the teaching–learning operation manual needs to be developed later in order for the class model to be effectively implemented at the classroom site to promote creative collaboration based on the Moodle online learning system.

Beschreibung: Given the dearth of studies in developing and Asian countries’ context, the present study attempts to excavate the predictors of enterprise resource planning (ERP) adoption and implementation. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model and open innovation literature, an extended model is proposed encompassing mediator and moderator variables. The study follows the deducting reasoning approach with the positivism paradigm. Out of 235 responses, the study used 225 replies collected through a self-administered sampling, and the data were analyzed by using PLS-based structural equation modeling. The study revealed that the hypothesized direct influences are significant except the influence of facilitating conditions on actual use. Likewise, the intention to use mediates the impact of facilitating conditions on the actual use of ERP. However, there is no moderating effect of education and firms’ size among the hypothesized influence. The study contributes to advance the previous findings by using an extended UTAUT model and validates results with the rest of the world.

Beschreibung: The purpose of this study is to explore the relationships between three intangible resources and the innovation performance of Chinese high-tech firms, and the moderating effect of internationalization on these relationships. We implement a hierarchical multiple regression analysis using data for 274 Chinese high-tech firms. The results show that all three intangible resources, measured by top management team diversity, research and development intensity, and government subsidies, positively influence Chinese high-tech firm innovation performance. We find the relationships between these intangible resources and the innovation performance of Chinese high-tech firms are significantly positively moderated by internationalization. These findings have important implications, as follows. First, they provide evidence of the strategic value of intangible resources and their effects on innovation performance. Second, our results show that increasing internationalization alone does not guarantee performance improvement. Firms should consider their internal and external environments and the complex relationships among factors when they make decisions about internationalization investments. Prior research does not provide an explanation for how internationalization affects performance, because it primarily focuses on the direct relationship between internationalization and performance. This study overcomes this limitation by examining the indirect effect of internationalization on performance.

Beschreibung: In Korean society, where aging is rapidly progressing, the happiness of the elderly is no longer an economic issue. An esthetics program has the effect of improving depression or low self-esteem to increase psychological and physical satisfaction, which is a good way to raise the happiness index of the elderly. However, there is a lack of esthetics education or esthetics programs in Korea to train estheticians to serve elderly people. This study confirmed the possibility of open innovation through esthetics education to increase the happiness index of the elderly. As a research method, a self-administered questionnaire was used to survey 572 estheticians and analyzed statistically. In this study, Korean estheticians were very positive about the need for the development of professional care programs for the elderly, and it was found that they are willing to care for the elderly. Developing a variety of esthetic programs through the training of professional manpower for the elderly in the future will contribute to enhancing the happiness index of elderly Korean people.

Beschreibung: This paper considers a carbon emission cap and trade market, where the carbon emission cap for each entity (either government or firm) is allocated first and then the carbon trading price is decided interdependently in the carbon trading market among the non-cooperative entities which make their production decision. We assume that there are n entities emitting carbon during the production process. After allocating the carbon (emission) cap for each participating entity in the carbon cap and trade market, each participant makes a production decision using the Newsvendor model given carbon trading price determined in the carbon trading market and trades some amount of its carbon emission, if its carbon emission is below or above its own carbon cap. Here, the carbon trading price depends on how carbon caps over the entities are allocated, since the carbon trading price is determined through the carbon (emission) trading market, which considers total amount of carbon emission being equal to total carbon caps over entities and some fraction of total carbon emission should be from each entity participating in the carbon cap and trade market. Thus, we can see the interdependency among the production decision, carbon cap and carbon trading price. We model this as a non-cooperative Stackelberg game in which carbon cap for each entity is allocated in the first stage and each entity’s production quantity is decided in the second stage considering the carbon trading price determined in the carbon trading market. First, we show the monotonic property of the carbon trading price and each entity’s production over the carbon cap allocation. In addition, we show that there exists an optimality condition for the carbon cap allocation. Using this optimality condition, we provide various results for carbon cap and trade market.

Beschreibung: Integrating the relational approach and social exchange theory, the authors conceptualize the quality of leader‒member and team member exchanges as mediators for understanding the role of transformational leadership in employee proactive behaviors (e.g., voice, taking charge, and innovative behaviors). The results based on data collected from 352 full-time employees working in pharmaceutical companies in Vietnam largely support the proposed theoretical framework and shed light on the mechanism through which leadership style influences employee proactivity in a manufacturing context. Using the results, the authors discuss research limitation and, managerial implications, and suggest future research directions for the relationship between leadership style and employee proactive behavior.

Beschreibung: This study investigates whether higher start-up intention leads to innovative behavior and whether innovative behavior is increased by the medium of entrepreneurship. This study tested the hypotheses by conducting a survey on students participating in entrepreneurship club activities in university. The results showed that start-up intention affects innovative behavior and has a significant effect on the sub-factors of entrepreneurship, such as innovation, risk taking, and proactiveness. The result of an analysis of the mediating effect of entrepreneurship on innovative behavior showed that all sub-factors performed a partially mediating role. It can therefore be said that higher start-up intention leads to more innovative behavior and that entrepreneurship serves as an important link in this relationship. These results show that increasing start-up intention may lead to innovative behavior and imply that this has educational relevance in cultivating entrepreneurship. However, this study is limited in terms of the generalizability of the results, as the subjects are university students participating in entrepreneurship club activities in Korea. Therefore, more significant outcomes can be obtained in further research by targeting a broader scope of subjects.

Beschreibung: The pharmaceutical industry is a high-technology industry that requires a combination of in-depth knowledge from various fields. It is characterized by high cost, high risk and a long-term perspective due to the high level of regulation. In addition, it is known that research and development (R&D) productivity is deteriorating in the industry. Under these conditions, the importance of open innovation strategies has been emphasized. Under an open innovation system, it is essential for firms to develop several dynamic capabilities to effectively manage their resources both internally and externally. Using a systematic framework of dynamic capabilities suggested by previous studies, this study focuses on the determinants affecting firms’ desorptive capacities, which are measured as the number of out-licensing deals, as an indicator for the performance of their outbound innovation. For the analysis, negative binomial regression is employed and inventive capacity and connective capacity are selected as the determinants of the licensors’ desorptive capacity. The results of regression analysis reveal that inventive capacity does not have a significant effect on desorptive capacity and that only connective capacity has a significant positive effect on desorptive capacity.

Beschreibung: This study presents the Location Routing Problem (LRP) for which we have created a model for the integration of locating facilities and vehicle routing decisions to solve the problem. The case study is the Palm Oil Collection Center, which is also important for the supply chain system. A mathematical model was made to minimize the total cost of a facility-opening cost, fixed cost of vehicle uses and fuel consumption cost. The fuel consumption cost relies on the distance and road conditions, in case of poor physical condition of a road, and its width, which can be affected the speed of the vehicle as well as the used fuel. Thus, we propose an Adaptive Large Neighborhood Search (ALNS) based on heuristic for solving the LRP. The ALNS method was tested with three datasets of samples divided into small, medium and large problems. Then, the results were compared with the results from the exact method by the Lingo program. The computational study indicated that the ALNS algorithm was competitive to the results of the Lingo for all instance sizes. Moreover, the ALNS was more effective than the exact method; approximately 99% in terms of processing time. We extended this approach to solve the case study, which was considered to be the largest problem, and the ALNS algorithm was efficient with acceptable solutions and short processing time. Therefore, the proposed method provided an effective solution to manage location routing decision of the palm oil collection center.

Beschreibung: The article deals with the issue of knowledge spillovers in the European regions. For this purpose, a standard Knowledge Production Function (KPF) approach was extended by the application of spatial econometrics methods. Our analysis started from the construction of the alternative structures of the spatial weight matrices. These matrices were based on technological and institutional proximities, which represent compelling alternatives to geographic proximity regarded as a kind of all-encompassing connectivity measure. The next step in our analysis was the modeling of regional knowledge generation processes. We treated R&D expenditures and human resources in science and technology as the input measures and patent applications to the European Patent Office as the output measure in our basic and extended models. The results show that the scope and direction of knowledge spillovers are sensitive to the type of knowledge (tacit vs. codified) and proximity dimension engaged. These findings contribute to the current debate in the geography of innovation and economics of knowledge literature.

Beschreibung: The aim of the paper is to provide an analysis of news and financial data using their network representation. The formation of network structures from data sources is carried out using two different approaches: by building the so-called market graph in which nodes represent financial assets (e.g., stocks) and the edges between nodes stand for the correlation between the corresponding assets, by constructing a company co-mention network in which any two companies are connected by an edge if a news item mentioning both companies has been published in a certain period of time. Topological changes of the networks over the period 2005–2010 are investigated using the sliding window of six-month duration. We study the stability of the market graph and the company co-mention network over time and establish which of the two networks was more stable during the period. In addition, we examine the impact of the crisis of 2008 on the stability of the market graph as well as the company co-mention network. The networks that are considered in this paper and that are the objects of our study (the market graph and the company co-mention network) have a non-changing set of nodes (companies), and can change over time by adding/removing links between these nodes. Different graph similarity measures are used to evaluate these changes. If a network is stable over time, a measure of similarity between two graphs constructed for two different time windows should be close to zero. If there was a sharp change between the graphs constructed for two adjacent periods, then this should lead to a sharp increase in the value of the similarity measure between these two graphs. This paper uses the graph similarity measures which were proposed relatively recently. In addition, to estimate how the networks evolve over time we exploit QAP (Quadratic Assignment Procedure). While there is a sufficient amount of works studying the dynamics of graphs (including the use of graph similarity metrics), in this paper the company co-mention network dynamics is examined both individually and in comparison with the dynamics of market graphs for the first time.

Beschreibung: This article proposes a methodology to resolve the advertising method selection problem (AdSP). The use of different advertising methods for the same product can generate different responses in terms of the product’s sales volume. Companies selling products have limited resources for advertising, with challenges such as budget and time constraints. It is necessary that the correct advertising method is selected in order to increase the maximum profit, given these limited resources. In the present study, a mathematical model was developed to represent the AdSP, and optimization software (OS) was utilized to optimally resolve it. However, a larger problem can prevent OS from optimally resolving the problem within a reasonable timeframe. To overcome this challenge, the authors developed a metaheuristic called the improved differential evolution algorithm (IDE), which combines three metaheuristics: (1) The differential evolution algorithm (DE); (2) the iterated local search (ILS); and (3) the adaptive large neighborhood search (ALNS). The performance of IDE reflects the best elements of these three methods. The computational results show that IDE can generate solutions that are similar to the optimal solutions obtained by OS while using 69.25% less computational time than OS. IDE improved the efficiency compared with the three original component methods. Moreover, IDE also found better solutions than those found by the original DE, ILS, and ALNS.

Beschreibung: Recently, a lot of small- and mid-sized companies have emerged through continuous technological development and start-up successes despite insufficient scales and resources compared to medium companies or conglomerates in fierce market competition. Technological development capability, which is required to acquire, select, or utilize source technology for company competitiveness, becomes the competitive edge and key capability to gain distinctiveness. Accordingly, the objective of this research was to investigate the influential factors on performance by suggesting technological development results and technology commercialization as the outcome of technological development capability and to identify the capability required for successful technological development performance and technology commercialization for companies through previous academic research. Moreover, the study aimed to investigate performance differences according to technology business groups by dividing the groups into high-technology companies, medium-technology companies, and low-technology companies. As a result of the analysis, among the indicators constituting technological development capability, manpower in technological development and technological development-specialized research centers had a positive influence on the product competitiveness of technological development performance. Also, technological development expenses and technology skill levels were verified to have positive impacts on the technology competitiveness of technological development performance. As for technology commercialization performance, the more manpower that is in research and development, the higher the sales amounts by technological development; also, the higher the technology skill levels, the higher the export amounts by technological development. Moreover, technology business groups had differences in performance. This research has significance in focusing on the influence of the technological development capability of companies on technological development performance and technology commercialization performance. Future research is expected to draw new variations different from the analysis results from existing studies by setting variations, investigating complementary relationships among variations in detail, and utilizing statistical techniques that can control mutual relationships among variations.

Beschreibung: The main purpose of this study was to find out the perceived impacts on the garment and textile industry of Vietnam from the Belt and Road Initiative (the BRI), a global-scale developmental and trade facilitation policy of China. The research applied both desk review and in-depth interviews with 54 leaders and high-ranked officials from public and private sectors in 2017 to identify potential impacts of the BRI on the Vietnam textile and garment industry. In addition, perceived challenges and opportunities of the BRI were also examined. Respondents from both sectors agreed that the initiative could foster textile export and the development of infrastructure. Apart from that, the main challenge is recognized as the poor competitiveness of Vietnamese textile firms on the international commercial playground. Solution insights that were offered through interviews suggested that the competence of domestic apparel brands and establishment of ODM (Original Design Manufacturing) and OBM (Own Brand Manufacturing) business models in Vietnamese textile producers may play the key roles in coping with the new challenges and in grasping opportunities that the initiative has to offer. From the perspective of the state, an improved public administration system is perceived as the key element in supporting the enterprises for upcoming challenges.

Beschreibung: In recent years, the construction industry faced major challenges in ensuring a balance between environmental, economic, and social aspects. There are a lot of different studies on different aspects of the construction industry. Most of the available studies look at the construction supervision process mainly from the constructor’s point of view. However, there is little research on the market surveillance and supervision process performed by the government and its role in ensuring sustainability in a particular area. The aim of this study was to identify the main activities within the construction supervision process to achieve the sustainability of construction. The theoretical framework of the concept of sustainability in construction and in the activities of the supervision process was analyzed on the basis of a literature survey. The research revealed a connection between sustainability elements and the construction supervision activities. The results of the survey identified the most important factors that influence, negatively as well as positively, the achievements of sustainability in the supervision process. The research results are significant in order to create a construction supervision process which would not only ensure the compliance with the set requirements but also help achieve sustainability in the particular area. Research Limitations/Implications: Research is focused on the supervision process of public building construction in Latvia.

Beschreibung: Accounting education focuses on delivering knowledge to students. Most student are passive, behaving as bystanders or listeners in lecturer-oriented learning. However, student-centered learning requires active and positive engagement from students to generate effective learning. Board games represent a key driving tool in inducing student participation and interest in active learning. This study investigates whether the active participation of students in class activities has positive effects on accounting education. Specifically, it tests whether active student involvement in board game activities in introductory accounting courses contributes to effective learning. There were a few key findings. Firstly, the more actively that students participate in the game, the higher their favorable changes are in terms of perception of accounting. Secondly, the higher their positive perceptions are, the higher the effects of accounting education are. These results imply that the active involvement of learners is a precondition for the effect of accounting education activities, and that positive perception is a mediator for learning effects.

Beschreibung: In Korea, cooperation between university and company is mainly encouraged by government policy as the Triple Helix’s statist model. Since 2003, the government started a variety of university financial support program, and in 2014, it reached to the point that 31 ministries conducted 408 programs in total. Most projects focused on training human resources and supporting Research and development, which is considered as the core function of universities, but some of the projects are designed to support the industry–academia cooperation. For instance, the Ministry of Education ran ‘Leaders in University and Industry Cooperation (LINC)’ program. LINC is a follow-up project of Human Resources Development for the Leading Industries, Industry–Academia Cooperation-oriented University, and Focal Point Research program. Accordingly, it aimed to create university–industry cooperative models, and nurture talents based on regional economy’s demand. The program provided approximately $230M per year for over 50 universities across the country. It was one of the highly influential grant programs considering the fact that there are about 200 universities nationwide and an annual budget of university is $900 billion on average. In this context, this study is to assess the influence of resources of universities capacity on the achievement of university–industry cooperation and explore whether a government-initiated policy has a significant effect using data from government information disclosure system on education.

Beschreibung: Automotive manufacturers are competing to be the first to introduce customer-ready autonomous vehicles. Some manufacturers are claiming to launch their first self-driving cars as early as 2020. Which all sounds very good and futuristic; however, the question arises, are customers even ready to adopt this new technological advancement? Therefore, this pilot study is aimed at finding out the answer to this question in the Austrian market. This study discovers the standpoint of Austrian consumers concerning the acceptance of self-driving cars for daily usage and gives an overview of the current point of view regarding autonomous vehicles (AVs). The data for this study was collected using an online, user-friendly, Likert scale survey. The collected data were processed and analyzed for empirical significance in SPSS using Spearman’s rank correlation and the Mann–Whitney U test supported by descriptive analysis. The results of the study indicate that Austrian consumers are well aware of autonomous vehicles and their technology. However, they have specific concerns about reliability, cybersecurity, and futuristic car-sharing models. Therefore, these concerns about AVs should be addressed by auto manufactures in order to gain consumers’ trust and sell them a new form of mobility.

Beschreibung: Rigorous peer-review is the corner-stone of high-quality academic publishing [...]

Beschreibung: A large body of literature has studied supply chain integration (SCI) at the macro (firm or dyad) level. However, the micro-foundations of SCI that highlight the range of different activities and choices firms have in implementing integration have not been studied. This paper identifies and analyzes integrative activities or practices that form the micro-units of firm-level SCI. Qualitative analysis yields nine elements of integration that emerge from the large number of integrative practices. In doing so, the paper maps out the structure of the broad SCI construct and discusses the theoretical repercussions of this new approach. New theoretical insights and research directions are identified based on this new micro-level activity-based view of SCI. This paper shifts the focus from where integration is done (customer vs. supplier integration) to what integration entails. SCI has become a very broad construct over time. This paper is a significant and systematic step in unraveling the structure of this broad conceptual domain. It improves nascent ideas about the multiple dimensions of integration by identifying elements based on a comprehensive list of different integrative activities that firms undertake.

Beschreibung: Integrating triple bottom line (TBL) goals into supply chains (SCs) is a challenging task which necessitates the careful coordination of numerous stakeholders’ individual interests. Recent technological advancements can impact TBL sustainability by changing the design, structure, and management of modern SCs. Blockchain technology enables immutable data records and facilitates a shared data view along the supply chain. The Physical Internet (PI) is an overarching framework that can be applied to create a layered and comprehensive view of the SC. In this conceptual paper, I define and combine these technologies and derive several high-level research areas and research questions (RQ) to investigate adoption and management as well as structural SC issues. I suggest a theory-based research agenda for the years to come that exploits the strengths of rigorous academic research, while remaining relevant for industry. Furthermore, I suggest various well-established theories to tackle the respective research questions and provide specific directions for future research.

Beschreibung: Additive Manufacturing (AM) is a digital manufacturing technology that enables companies to rethink their supply chain (SC) design. By means of literature synthesis, we build new knowledge about the mechanisms AM induces to improve SC design and performance, as well as the disruptive changes AM can cause. We investigate opportunities to optimize SC design for manufacturing purposes by exploiting the characteristics of AM, e.g., its freedom in terms of shape design and complexity and the absence of a need for object-specific tools. We study the roles of demand, assortment, IT systems, sourcing, manufacturing, knowledge, warehousing, and transportation, and explore the effects and tradeoffs on various SC performance outcomes, including cost, assets, and responsiveness. The contribution of this article is twofold. First, through literature synthesis, we construct six AM SC mechanisms that can be used in SC design to achieve desired SC outcomes for AM production applications in certain (business) contexts. Second, we identify the disruptive ‘game-changing’ effects of AM for SC stakeholders. This knowledge can be used by other researchers to develop further research. Moreover, general and logistics managers can use the results to fully exploit the potential of AM for designing much improved supply chains. Innovators and policy makers can use the results to understand the potential game-changing consequences of AM.

Beschreibung: In a distributed system, a common time reference allows each component to associate the same timestamp to events that occur simultaneously. It is a design option with benefits and drawbacks since it simplifies and makes more efficient a number of functions, but requires additional resources and control to keep component clocks synchronized. In this paper, we quantify how much power is spent to implement such a function, which helps to solve the dilemma in a system of low-power sensors. To find widely applicable results, the formal model used in our investigation is agnostic of the communication pattern that components use to synchronize their clocks, and focuses on the scheduling of clock synchronization operations needed to correct clock drift. This model helps us to discover that the dynamic calibration of clock drift significantly reduces power consumption. We derive an optimal algorithm to keep a software defined clock (SDCk) synchronized with the reference, and we find that its effectiveness is strongly influenced by hardware clock quality. To demonstrate the soundness of formal statements, we introduce a proof of concept. For its implementation, we privilege low-cost components and standard protocols, and we use it to find that the power needed to keep a clock within 200 ms from UTC (Universal Time Coordinate) as on the order of 10−5 W . The prototype is fully documented and reproducible.

Beschreibung: Information fusion has been a topic of immense interest owing to its applicability in various applications. This brings to the fore the need for a flexible and accurate fusion algorithm that can be versatile. The Brooks–Iyengar algorithm is one such fusion algorithm. It has since its inception found numerous applications that deal with the fusion of data from multiple sources. The uniqueness of the Brooks–Iyengar algorithm is the ease with which the data from multiple sensors in a local system can be fused and also reach consensus in a distributed system with the added capability of fault tolerance. Blockchain has found its use as a distributed ledger and has successfully supported and fueled many crypto-currencies over the years. Information fusion with regards to Blockchains is a topic of great research interest in the past couple of years. Since blockchain has no official node, the introduction of a decentralized network and a consensus algorithm is required in making the interactions and exchanges between multiple suppliers easier and thus leads to business being carried out without any hassles. In this paper, we attempt to understand and describe the deployment of multiple sensors to measure various aspects of the physical world. We discuss a novel technique of employing the Brooks–Iyengar algorithm in the design of the system that would decentralize the data source from the corresponding measurements and thus ensure the integrity of the transactions in the Blockchain. Finally, a theoretical analysis of the performance of the algorithm when used in a blockchain based decentralized environment is also discussed.

Beschreibung: Security of IoT devices is getting a lot of attention from researchers as they are becoming prevalent everywhere. However, implementation of hardware security in these devices has been overlooked, and many researches have mainly focused on software, network, and cloud security. A deeper understanding of hardware Trojans (HTs) and protection against them is of utmost importance right now as they are the prime threat to the hardware. This paper emphasizes the need for a secure hardware-level foundation for security of these devices, as depending on software security alone is not adequate enough. These devices must be protected against sophisticated attacks, especially if the groundwork for the attacks is already laid in devices during design or manufacturing process, such as with HTs. This paper will discuss the stealthy nature of these HT, highlight HT taxonomy and insertion methods, and provide countermeasures.

Beschreibung: Connected cars and vehicle-to-everything (V2X) communication scenarios are attracting more researchers. There will be numerous possibilities offered by V2X in the future. For instance, in the case of vehicles that move in a column, they could react to the braking of those in front of it through the rapid information exchanges, and most chain collisions could be avoided. V2X will be desiderated for routes optimizations, travel time reductions, and accident rate decrease in cases such as communication with infrastructures, traffic information exchanges, functioning of traffic lights, possible situations of danger, and the presence of construction sites or traffic jams. Furthermore, there could be massive conversations between smartphones and vehicles performing real-time dialogues. It is relatively reasonable to expect a connection system in which a pedestrian can report its position to all surrounding vehicles. Regarding this, it is compelling to perceive the positive effects of the driver being aware of the presence of pedestrians when vehicles are moving on the roads. This paper introduces the concepts for the development of a solution based on V2X communications aimed at vehicle and pedestrian safety. A potential system architecture for the development of a real system, concerning the safety of vehicles and pedestrians, is suggested to draft some guidelines that could be followed in new applications.

Beschreibung: The Quantum Double Delta Swarm (QDDS) Algorithm is a networked, fully-connected novel metaheuristic optimization algorithm inspired by the convergence mechanism to the center of potential generated within a single well of a spatially colocated double–delta well setup. It mimics the wave nature of candidate positions in solution spaces and draws upon quantum mechanical interpretations much like other quantum-inspired computational intelligence paradigms. In this work, we introduce a Chebyshev map driven chaotic perturbation in the optimization phase of the algorithm to diversify weights placed on contemporary and historical, socially-optimal agents’ solutions. We follow this up with a characterization of solution quality on a suite of 23 single–objective functions and carry out a comparative analysis with eight other related nature–inspired approaches. By comparing solution quality and successful runs over dynamic solution ranges, insights about the nature of convergence are obtained. A two-tailed t-test establishes the statistical significance of the solution data whereas Cohen’s d and Hedge’s g values provide a measure of effect sizes. We trace the trajectory of the fittest pseudo-agent over all iterations to comment on the dynamics of the system and prove that the proposed algorithm is theoretically globally convergent under the assumptions adopted for proofs of other closely-related random search algorithms.

Beschreibung: Rigorous peer-review is the corner-stone of high-quality academic publishing [...]

Beschreibung: Sensors and intelligent applications enabling smart vehicular traffic create an opportunity for improving the welfare of people, from the viewpoints of efficiency, sustainability, and social inclusivity. Like the opportunities, challenges of such an endeavour are multifaceted, including the scalable collection and processing of the hefty data volumes generated by sensors, and the coordinated operation between selfish agents. The purpose of this work is to survey recent literature with an emphasis on applications and a multidisciplinary eye, with the aim of stimulating discussion and reflection in the scientific communities. The principal application areas of smart traffic and smart mobility are discussed, synthesizing different perspectives. Many intriguing areas for future research exist besides those relative to connectivity, data fusion, and privacy. Some research challenges pertinent to sustainability, insurance, simulation and the handling of ambiguous information are highlighted.

Beschreibung: Enabling haptic communication as well as voice and data over the future 5G cellular system has become a demand. Tactile Internet is one of the main use cases of the 5G system that will allow the transfer of haptic communications in real time. Latency, availability, reliability, and security are the main design challenges of the tactile Internet system and haptic based bilateral teleoperation systems. An end-to-end latency of 1 ms remains the main challenge toward tactile Internet system realization, not only for the processing and coding delays but mainly for the limitations of light. In this work, we analyze the key solutions to overcome the light limitations and enable the tactile Internet over any distances with the required latency. Building a virtual model or model mediated for the remote environment at the edge cloud unit near to the end user is the main solution. By means of AI, the virtual model can predict the behavior of the remote environment and thus, the end user can interact with the virtual environment with a high system experience. This literature review covers the existing work of the model mediated bilateral teleoperated systems and discusses its availability for the tactile Internet system. Furthermore, the security issues of tactile Internet system and the effect of model mediated system on the required security level of tactile Internet applications are discussed. Finally, a structure for the tactile Internet system, with the deployment of model mediation, is suggested.

Beschreibung: To provide accurate activity recognition within a smart environment, visible spectrum cameras can be used as data capture devices in solution applications. Privacy, however, is a significant concern with regards to monitoring in a smart environment, particularly with visible spectrum cameras. Their use, therefore, may not be ideal. The need for accurate activity recognition is still required and so an unobtrusive approach is addressed in this research highlighting the use of a thermopile infrared sensor as the sole means of data collection. Image frames of the monitored scene are acquired from a thermopile infrared sensor that only highlights sources of heat, for example, a person. The recorded frames feature no discernable characteristics of people; hence privacy concerns can successfully be alleviated. To demonstrate how thermopile infrared sensors can be used for this task, an experiment was conducted to capture almost 600 thermal frames of a person performing four single component activities. The person’s position within a room, along with the action being performed, is used to appropriately predict the activity. The results demonstrated that high accuracy levels, 91.47%, for activity recognition can be obtained using only thermopile infrared sensors.

Beschreibung: Intrusion Detection Systems (IDS) are used to prevent attacks by detecting potential harmful intrusion attempts. Currently, there are a set of available Open Source IDS with different characteristics. The Open Source Host-based Intrusion Detection System (OSSEC) supports multiple features and its implementation consists of Agents that collect and send event logs to a Manager that analyzes and tests them against specific rules. In the Manager, if certain events match a specific rule, predefined actions are triggered in the Agents such as to block or unblock a particular IP address. However, once an action is triggered, the systems administrator is not able to centrally check and obtain detailed information of the past event logs. In addition, OSSEC may assume false positive or negative detections and their triggered actions: previously harmless but blocked IP addresses by OSSEC have to be unblocked in order to reestablish normal operation or potential harmful IP addresses not previously blocked by OSSEC should be blocked in order to increase protection levels. These operations to override OSSEC actions must be manually performed in every Agent, thus requiring time and human resources. Both these limitations have a higher impact on large scale OSSEC deployments assuming tens or hundreds of Agents. This paper proposes an extension to OSSEC that improves the administrator analysis capability by maintaining, organizing and presenting Agent logs in a central point, and it allows for blocking or unblocking IP addresses in order to override actions triggered by false detections. The proposed extension aims to increase efficiency of time and human resources management, mainly considering large scale OSSEC deployments.

Beschreibung: One of the most common forgotten things of adults is that they go to the shops and completely forget what they went for. The solution to this problem is to carry a shopping list. In this project, a novel Internet of Things (IoT)-connected smart canister system is developed, which automatically senses the item quantity in the canisters using proximity sensor, sends the data to a hub using Bluetooth Low Energy, and then the hub sends a cloud message to the consumer’s smartphone app using the Internet. The hub and the smartphone app display the item quantities and automatically add the items that are about to finish to a digital shopping list. The automatic generation of the shopping list removes the burden of manually checking each item before going to the shops and gives peace of mind to the consumers. A prototype of the proposed system with three canister devices, one hub, and the smartphone app is developed and tested successfully. The canister device consumes ultra-low power and has a battery life of more than a year.

Beschreibung: Monitoring and interpreting structural response using structural-identification methodologies improves understanding of civil-infrastructure behavior. New sensing devices and inexpensive computation has made model-based data interpretation feasible in engineering practice. Many data-interpretation methodologies, such as Bayesian model updating and residual minimization, involve strong assumptions regarding uncertainty conditions. While much research has been conducted on the scientific development of these methodologies and some research has evaluated the applicability of underlying assumptions, little research is available on the suitability of these methodologies to satisfy practical engineering challenges. For use in practice, data-interpretation methodologies need to be able, for example, to respond to changes in a transparent manner and provide accurate model updating at minimal additional cost. This facilitates incremental and iterative increases in understanding of structural behavior as more information becomes available. In this paper, three data-interpretation methodologies, Bayesian model updating, residual minimization and error-domain model falsification, are compared based on their ability to provide robust, accurate, engineer-friendly and computationally inexpensive model updating. Comparisons are made using two full-scale case studies for which multiple scenarios are considered, including incremental acquisition of information through measurements. Evaluation of these scenarios suggests that, compared with other data-interpretation methodologies, error-domain model falsification is able to incorporate, iteratively and transparently, incremental information gain to provide accurate model updating at low additional computational cost.

Beschreibung: The use of Internet of Things (IoT) with medical devices within a connected health environment promotes the quick flow of information and enables easy access to it [...]

Beschreibung: The rabid growth of today’s technological world has led us to connecting every electronic device worldwide together, which guides us towards the Internet of Things (IoT). Gathering the produced information based on a very tiny sensing devices under the umbrella of Wireless Sensor Networks (WSNs). The nature of these networks suffers from missing sharing among them in both hardware and software, which causes redundancy and more budget to be used. Thus, the appearance of Shared Sensor Networks (SSNs) provides a real modern revolution in it. Where it targets making a real change in its nature from domain specific networks to concurrent running domain networks. That happens by merging it with the technology of virtualization that enables the sharing feature over different levels of its hardware and software to provide the optimal utilization of the deployed infrastructure with a reduced cost. This article is concerned with surveying the idea of SSNs, the difference between it and the traditional WSNs, the requirements for its construction, challenges facing it, and the opportunities that are provided by it, then describing our proposed architectures. As a result of using virtualization technology as a basic block in building SSNs, using different types of virtualization will produce different types of SSNs that will give different usages to it. This article proposes a novel approach of taxonomy for SSNs that is based on the used virtualization techniques, and it describes the needs and usages of each one. It presents a wide array of previously proposed solutions comparing them to each other and a brief description of the issues addressed by each category of that taxonomy. Additionally, the shared sensor architecture and shared network architecture were depicted. Finally, some of its applications in some daily life fields are listed.

Beschreibung: Various technologies and standards for the Internet of Things (IoT) have defined the way devices should interact with each other to provide an intelligent IoT service to users in an efficient manner. Although the usability of system interface between the platform and users is one of the key factors for the success of IoT ecosystems, the manner in which IoT platforms should interact with users has not been well studied. Current IoT platforms provide a simple list-based interface to manage devices, which result in the degradation of their usability as the number of devices increases. In this paper, we propose an interactive web-based IoT management system where deep object detection techniques are adopted to facilitate user’s device selection and management. The proposed system automatically recognizes the device type from video streams and accordingly generates smart controllers. The users can choose a device by touching an object in the video stream and use a smart controller to control the selected device. Finally, we show the feasibility of the proposed system through the implementation of a prototype which demonstrates a set of user scenarios.

Beschreibung: This study provides a mathematical model and theoretical analysis of an interference cancellation system combining an orthogonal matched filter (OMF) and adaptive array antenna that is called the extended OMF (EOMF). In recent years, an increase in the number of applications of mobile ad hoc networks (MANETs) is expected. To realize a highly reliable MANET, it is essential to introduce a method for cancelling the interference from other nodes. This research focuses on a scheme based on Code Division Multiple Access (CDMA) that enables simultaneous multiple access and low latency communication. However, there are problems with deteriorating performance due to the near–far problem and the increase in the amount of interference as the number of users increases. Additionally, another problem is that the spreading sequence of each user is unknown in a MANET. The OMF is expected to be a solution to these problems. The OMF performs interference cancellation by generating and subtracting a replica of the interference signal that is contained in the received signal. However, the OMF may generate an incorrect replica in the near–far problem. The EOMF compensates for the OMF’s weakness by combining the OMF with an adaptive array antenna. In this research, optimal parameters are derived from mathematical modelling and theoretical analysis of the EOMF. Specifically, the optimal weight vector and the minimum mean squared error that allow the adaptive algorithm to converge are derived and obtained from the numerical results.

Beschreibung: This paper presents a framework to accurately and non-intrusively detect the number of people in an environment and track their positions. Different from most of the previous studies, our system setup uses only ambient thermal sensors with low-resolution, using no multimedia resources or wearable sensors. This preserves user privacy in the environment, and requires no active participation by the users, causing no discomfort. We first develop multiple methods to estimate the number of people in the environment. Our experiments demonstrate that algorithm selection is very important, but with careful selection, we can obtain up to 100% accuracy when detecting user presence. In addition, we prove that sensor placement plays a crucial role in the system performance, where placing the sensor on the room ceiling yields to the best results. After accurately finding the number of people in the environment, we perform position tracking on the collected ambient data, which are thermal images of the space where there are multiple people. We consider position tracking as static activity detection, where the user’s position does not change while performing activities, such as sitting, standing, etc. We perform efficient pre-processing on the data, including normalization and resizing, and then feed the data into well-known machine learning methods. We tested the efficiency of our framework (including the hardware and software setup) by detecting four static activities. Our results show that we can achieved up to 97.5% accuracy when detecting these static activities, with up to 100% class-wise precision and recall rates. Our framework can be very beneficial to several applications such as health-care, surveillance, and home automation, without causing any discomfort or privacy issues for the users.

Beschreibung: Nowadays, the penetration of sensors and actuators in different application fields is revolutionizing all aspects of our daily life. One of the major sectors that is taking advantage of such cutting-edge cheap smart devices is healthcare. In this context, Remote Patient Monitoring (RPM) at home represents a tempting opportunity for hospitals to reduce clinical costs and to improve the quality of life of both patients and their families. It allows patients to be monitored remotely by means networks of Internet of Things (IoT) medical devices equipped with sensors and actuators that collect healthcare data from patients and send them to a Cloud-based Hospital Information System (HIS) for processing. Up to now, many different proprietary software systems have been developed as stand-along expensive solutions, presenting interoperability, extensibility, and scalability issues. In recent years, the European Commission (EC) has promoted the wide adoption of FIWARE technology, launching 16 Industrial Accelerators focusing on different application fields. One of these, i.e., FICHe, is specialized in healthcare, providing the guidelines on how to develop eHealth systems. This paper focuses on how to compose new cutting-edge IoT and Cloud-based Cyber Physical Health Sytem (CPHS) services and applications interconnected with remote medical sensors and actuators using FIWARE technology in the context envisioned by FICHe. In particular, we discuss the design and development of an RPM system implemented through the collaboration between the Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) “Bonino Pulejo” (i.e., a clinical and research healthcare centre specialized in the treatment of neuro lesions), University of Messina, IBM Research, Telefónica, and the University of the Western Cape in South Africa. The description of our best practice provides a model and guidelines for the development of lightweight and low cost RPM services for rural and isolated areas, with the expectation of expanding healthcare to the developing world and in general allows us to outline how to deal with the real adoption of the FIWARE technology in an e-health project.

Beschreibung: The paper addresses the problem of localization based on hybrid received signal strength (RSS) and time of arrival (TOA) measurements, in the presence of synchronization errors among all the nodes in a wireless network, and assuming all parameters are unknown. In most existing schemes, in fact, knowledge of the model parameters is postulated to reduce the high dimensionality of the cost functions involved in the position estimation process. However, such parameters depend on the operational wireless context, and change over time due to the presence of dynamic obstacles and other modification of the environment. Therefore, they should be adaptively estimated “on the field”, with a procedure that must be as simple as possible in order to suit multiple real-time re-calibrations, even in low-cost applications, without requiring human intervention. Unfortunately, the joint maximum likelihood (ML) position estimator for this problem does not admit a closed-form solution, and numerical optimization is practically unfeasible due to the large number of nuisance parameters. To circumvent such issues, a novel two-step algorithm with reduced complexity is proposed: A first calibration phase exploits nodes in known positions to estimate the unknown RSS and TOA model parameters; then, in a second localization step, an hybrid TOA/RSS range estimator is combined with an iterative least-squares procedure to finally estimate the unknown target position. The results show that the proposed hybrid TOA/RSS localization approach outperformed state-of-the-art competitors and, remarkably, achieved almost the same accuracy of the joint ML benchmark but with a significantly lower computational cost.

Beschreibung: In energy detection for cognitive radio spectrum sensing, the noise variance is usually assumed given, by which a threshold is set to guarantee a desired constant false alarm rate (CFAR) or a constant detection rate (CDR). However, in practical situations, the exact information of noise variance is generally unavailable to a certain extent due to the fact that the total noise consists of time-varying thermal noise, receiver noise, and environmental noise, etc. Hence, setting the thresholds by using an estimated noise variance may result in different false alarm probabilities from the desired ones. In this paper, we analyze the basic statistical properties of the false alarm probability by using estimated noise variance, and propose a method to obtain more suitable CFAR thresholds for energy detection. Specifically, we first come up with explicit descriptions on the expectations of the resultant probability, and then analyze the upper bounds of their variance. Based on these theoretical preparations, a new method for precisely obtaining the CFAR thresholds is proposed in order to assure that the expected false alarm probability can be as close to the predetermined as possible. All analytical results derived in this paper are testified by corresponding numerical experiments.

Beschreibung: Historically, universities and institutions of higher learning have gone through three academic revolutions, namely, teaching, research, and innovation. Universities and Higher Educational Institutions (HEIs) in the last two decades have come to occupy an important part in the national innovation systems (NIS), which is a complex of ‘all important economic, social, political, organizational, institutional and other factors that influence the development, diffusion and use of innovations’. From a broader perspective, universities, together with public Research and Development (R&D) labs and science agencies, public policies (on industry, research, innovation and higher education, etc.) and business enterprises are now considered as important actors in the NIS of Asia-Pacific economies. The rise of Asia in the global knowledge-based economy from mid-1990s is closely associated with the rise of knowledge institutions of higher learning and scientific research output. Every Asia-Pacific country embraced and introduced policies relating to innovation in varying forms. Consultancy and collaborative links with industry being traditional forms of engagement, new policy and institutional measures in technology transfer and innovation to engage with society and business enterprises are gaining prominence. Policies for incubation, start-ups, and spin-offs, technology transfer offices (TTOs), and science and technology parks have gained tremendous prominence in leading Asia-Pacific universities. Different national innovation systems in the Asia-Pacific region have given rise to varying roles of universities. Whilst universities in Southeast Asian countries and India continue to play a traditional role of teaching and generating human capital, there are countries such as Singapore, China, Taiwan, and Japan, wherein universities are being transformed as entrepreneurial universities. Science and innovation policies in these countries have orchestrated the goal direction of universities as frontiers of innovation. Universities in Australia and New Zealand have so far been quite successful in marketing higher education to neighboring Asian countries. They have in recent years begun to embark on innovation and commercialization of research. The paper focuses on South East Asia and draws some comparison with more dynamic university ecosystems in East Asia. In doing so, the paper brings into focus the emerging innovation landscapes across the region.

Beschreibung: Nowadays, new energy vehicles play an important role in the transformation and upgrade of China’s energy security, energy conservation and other industries. At present, there are 26 pilot cities for the demonstration of new energy vehicles in China; however, the operation effect and experience of the pilot cities have been summarized less. This paper takes Shenzhen’s new energy vehicle industry policy as the object of research, in order to explore the impact of demand innovation on the development of new energy vehicles. This paper summarizes the three stages of Shenzhen’s new energy vehicle industry promotion, and further analyzes the policy and market environments of each stage by using the demand-side innovation policy theory. By reflecting on the concept of policy design, this paper proposes that decision makers need to cultivate open innovative thinking, and transform their production-oriented policy design into a demand-oriented policy design. This conclusion is helpful for pilot cities in order to adjust their policies over time according to the different stages of industrial development, and further improve the innovation and competitiveness of China’s new energy vehicle industry.

Beschreibung: This conceptual paper examines the still under-researched phenomena associated with internationalization within the context of entrepreneurial ecosystems. Drawing on multiple literature streams, I develop TCKF-Connect, a cross-disciplinary conceptual framework to investigate how entrepreneurial ecosystems become globally connected, and how, in turn, an ecosystem’s global connectedness can drive and sustain the internationalization processes of innovative start-ups. I propose a distinction between entrepreneurial ecosystems’ connectivity and ecosystems’ connectedness, where the former is purported as a necessary but not sufficient condition to achieve the latter. The framework developed revolves around the role played by a specific “vehicle” of connectivity across entrepreneurial ecosystems, i.e., temporary clusters, as conceptualized by Maskell, Bathelt and Malmberg and focuses on the role of knowledge flows within temporary clusters and across the entrepreneurial ecosystems where the temporary clusters are nested. The cross-disciplinary conceptual framework developed contributes to both research and policy debates by underpinning the investigation of research questions to further our understanding of the interplay between internationalization of entrepreneurial ecosystems and internationalization of the start-ups nested within them. The article proposes a research agenda emanating from the application of the cross-disciplinary conceptual framework developed and suggests a methodology for the empirical investigation.

Beschreibung: The study aims to identify motivational factors that lead to collective intelligence and understand how these factors relate to each other and to innovation in enterprises. The study used the convenience sampling of corporate employees who use collective intelligence from corporate panel members (n = 1500). Collective intelligence was found to affect work process, operations, and service innovation. When corporate employees work in an environment where collective intelligence (CI) is highly developed, work procedures or efficiency may differ depending on the onset of CI. This raises the importance of CI within an organization and implies the importance of finding means to vitalize CI. This study provides significant implications for corporations utilizing collective intelligence services, such as online communities. Firstly, such corporations vitalize their services by raising the quality of information and knowledge shared in their workplaces; and secondly, contribution motivations that consider the characteristics of knowledge and information contributors require further development.

Beschreibung: The financial valuation of a drug that is still under development is required for various purposes. The risk-adjusted net present value (r-NPV) method, which recently emerged in the biotech industry, uses the development attrition rate as a discount factor to reflect risk during each development phase. The r-NPV method was developed to overcome the disadvantages of the prevailing discounted cash flow and real options methods and considers drug type, as well as the stage of development in its approach. Using this method, the current study examines technology values in the biopharmaceutical industry and matches the clinical development periods and success rates of these new drugs by analyzing datasets from ClinicalTrials.gov and MedTrack DB. It thus provides support for an empirical valuation model for experts in the field. Notably, there is limited research on the attrition rate and development period of new substance drugs and the research results are not consistently presented. In addition to new substance drugs, further research is necessary to deepen understanding of the attrition rate and development period of biologically-based drugs because of their inherent physical and developmental differences. Similarly, research on performance specifics within drug class models would enable refinement of the model.

Beschreibung: This research aimed to present a solution to the problem of production scheduling and assignment in broiler farms, which thus enabled the farms to achieve maximum profit. In the operation of farms, there are many factors that affect profits, such as the number of broilers being consistent with the demand of production plants, including profits from the sales and transportation costs. Therefore, we formulated a mathematical model and tested it while using three problem groups through the Lingo v.11 program. The results indicated that this mathematical model could find a suitable solution. However, finding the best solution had time constraints, which resulted in various other problems that prevented a search for an optimal solution due to time consumption exceeding 72 h. We developed an algorithm using the Adaptive Large Neighborhood Search (ALNS) method in order to find another possible solution using a shorter time period, which consisted of ALNS1, ALNS2, and ALNS3. These algorithms are based on a combination of the method of destruction solutions and methods accepting different solutions. We aimed to effectively solve the problems and ensure that they are appropriate for the case study, a broiler farm in Buriram. When comparing the algorithm efficiency with the Lingo v.11 program, it was found that the ALNS1 algorithm was the most suitable for finding the optimal solution in the shortest time, which resulted in a 5.74% increase in operating profits.

Beschreibung: Logging and tracking raw materials, workpieces and engineered products for seamless and quick pulls is a complex task in the construction and shipbuilding industries due to lack of structured storage solutions. Additional uncertainty is introduced if workpieces are stacked and moved by multiple stakeholders without maintaining an active and up-to-date log of such movements. While there are frameworks proposed to improve workpiece pull times using a variety of tracking modes based on deterministic approaches, there is little discussion of cases wherein direct observations are sparse due to occlusions from stacking and interferences. Our work addresses this problem by: logging visible part locations and timestamps, through a network of custom designed observation devices; and building a graph-based model to identify events that highlight part interactions and estimate stack formation to search for parts that are not directly observable. By augmenting the site workers and equipment with our wearable devices, we avoid adding additional cognitive effort for the workers. Native building blocks of the graph-based model were evaluated through simulations. Experiments were also conducted in an active shipyard to validate our proposed system.

Beschreibung: The incorporation of sustainable aspects in the supply chain management (SCM) has become an important topic for researchers and professionals; however, it is a field that yet lacks a systemic understanding. The objective of this article is to conduct an analysis on the international literature about the SCM sustainability topic, by employing a systematic review protocol, covering the period from 2011 to 2016. The content analysis technique was performed, following the procedures of categorical thematic analysis proposed by Bardin (1977), which considers the creation of categories a posteriori, based in the direction senses related to the content analyzed. Besides to present the main characteristics of the articles related to distribution of publications per year, most studied sectors, main methods and approaches used main countries and journals of publications, we categorize the results at the systemic approach level of the sustainable development dimensions. We found that some dimensions are prominent when compared with the others: For example: the environmental one, on the other hand, the social one is approached few times in the papers considered in our analysis. These results also indicate that this type of discussion needs to be extended to other sectors that have not yet been explored. The contribution of this paper lies on the synthetization of the state-of-the-art related to sustainable SCM in the period considered, highlighting the environmental, social and economic dimensions, in order to identify a research agenda. By identifying possible research gaps, the results of this research contribute to guide future investigations on sustainable SCM, aiding researchers and practitioners in this field.

Beschreibung: Blockchains are attracting the attention of stakeholders in many industrial domains, including the logistics and supply chain industries. Blockchain technology can effectively contribute in recording every single asset throughout its flow on the supply chain, contribute in tracking orders, receipts, and payments, while track digital assets such as warranties and licenses in a unified and transparent way. The paper provides, through its methodology, a detailed analysis of the blockchain fit in the supply chain industry. It defines the specific elements of blockchain that affect supply chain such as scalability, performance, consensus mechanism, privacy considerations, location proof and cost, and details on the impact that blockchains will have in disrupting the supply chain industry. Discussing the tradeoff between consensus cost, throughput and validation time it proceeds with a suggested high-level architectural approach, and concludes as a result with a discussion on changes needed and challenges faced for an in-vivo deployment of blockchains in the supply chain industry. While the technological features of modern blockchains can effectively facilitate supply chain uses cases, the various challenges that still remain, bring in front of us a wide set of needed changes and further research efforts for achieving a global, production level blockchain for the supply chain industry.

Beschreibung: Dairy farming is a subsidiary profession of agriculture in India where dairy cooperatives are an important part of rural development. The current study explores the critical factors in the dairy supply chain, and provides an initial decision framework for its implications. The necessary data were collected from dairy producer members including dairy farmers, executives, and key informants of processing units, to summarize the strengths, weaknesses, opportunities, threats (SWOT) of the milk processing system in India. This includes identifying the objectives of the dairy industry, along with the internal and external critical factors (CFs). SWOT exploration does not offer any investigative basis for evaluating the priorities of CFs, therefore the analytic hierarchy process is applied to define the priorities of identified CFs. The CFs have also been ordered according to relative importance. The findings of this study depict that the SWOT based methodology offers vital sensitivity in assessing the supply chain strategies for the dairy industry.

Beschreibung: As Internet of Things (IoT) involvement increases in our daily lives, several security and privacy concerns like linkability, unauthorized conversations, and side-channel attacks are raised. If they are left untouched, such issues may threaten the existence of IoT. They derive from two main reasons. One is that IoT objects are equipped with limited capabilities in terms of computation power, memory, and bandwidth which hamper the direct implementation of traditional Internet security techniques. The other reason is the absence of widely-accepted IoT security and privacy guidelines and their appropriate implementation techniques. Such guidelines and techniques would greatly assist IoT stakeholders like developers and manufacturers, paving the road for building secure IoT systems from the start and, thus, reinforcing IoT security and privacy by design. In order to contribute to such objective, we first briefly discuss the primary IoT security goals and recognize IoT stakeholders. Second, we propose a comprehensive list of IoT security and privacy guidelines for the edge nodes and communication levels of IoT reference architecture. Furthermore, we point out the IoT stakeholders such as customers and manufacturers who will benefit most from these guidelines. Moreover, we identify a set of implementation techniques by which such guidelines can be accomplished, and possible attacks against previously-mentioned levels can be alleviated. Third, we discuss the challenges of IoT security and privacy guidelines, and we briefly discuss digital rights management in IoT. Finally, through this survey, we suggest several open issues that require further investigation in the future. To the best of the authors’ knowledge, this work is the first survey that covers the above-mentioned objectives.

Beschreibung: Thanks to IEEE 802.15.4 defining the operation of low-rate wireless personal area networks (LR-WPANs), the door is open for localizing sensor nodes using tiny, low power digital radios such as Zigbee. In this paper, we propose a three-dimensional (3D) localization scheme based on well-known loop invariant for division algorithm. Parametric points are proposed by using the reference anchor points bounded in an outer region named as Parametric Loop Division (PLD) algorithm. Similar to other range-based localization methods, PLD is often influenced by measurement noise which greatly degrades the performance of PLD algorithm. We propose to adopt extended Kalman filtering (EKF) to refine node coordinates to mitigate the measurement noise. We provide an analytical framework for the proposed scheme and find the lower bound for its localization accuracy. Simulation results show that compared with the existing PLD algorithm, our technique always achieves better positioning accuracy regardless of network topology, communication radius, noise statistics, and the node degree of the network. The proposed scheme PLD-EKF provides an average localization accuracy of 0.42 m with a standard deviation of 0.26 m.

Beschreibung: Advances in the Internet of Things (IoT) are helping to make water management smarter and optimizing consumption in the smart agriculture industry. This article proposes a new topology of sensor nodes based on the use of inexpensive and highly efficient components, such as water level, soil moisture, temperature, humidity, and rain sensors. Additionally, to guarantee good performance of the system, the used transmission module is based on LoRa LPWAN technology. The design of the main circuit board of the system is optimized by combining two layers and implementing software optimization. The overall sensor network is developed and tested in the research lab, and real farms can be controlled by users manually or automatically using the mobile application. Experimental results are produced by testing sensor and communication link effectiveness, and are subsequently validated in the field through a one-week measurement campaign.

Beschreibung: In the Internet of Things (IoT), a huge number of sensors, actuators and other equipment for data acquisition and processing will be interconnected by means of an omnipresent communication network able to efficiently support heterogeneous transmission technologies and applications. On the one hand, advanced optical communication systems, which already play a significant role in modern networks, are currently evolving to meet very high requirements of modern applications. On the other hand, there are already many ways to utilize optical components and effects for building precise, efficient, and reliable sensors. Thus, optical technologies have the potential to greatly help in realizing future smart infrastructures and systems. This paper gives an overview of currently available and emerging optical technologies for sensing and communication applications and reviews their possible application in the context of the IoT for realizing smart systems and infrastructures.