ALBERT

Description: We examine a distributed detection problem in a wireless sensor network, where sensor nodes collaborate to detect a Gaussian signal with an unknown change of power, i.e., a scale parameter. Due to power/bandwidth constraints, we consider the case where each sensor quantizes its observation into a binary digit. The binary data are then transmitted through error-prone wireless links to a fusion center, where a generalized likelihood ratio test (GLRT) detector is employed to perform a global decision. We study the design of a binary quantizer based on an asymptotic analysis of the GLRT. Interestingly, the quantization threshold of the quantizer is independent of the unknown scale parameter. Numerical results are included to illustrate the performance of the proposed quantizer and GLRT in binary symmetric channels (BSCs).

Description: Genome memory is an important aspect of electronic cells. Here, a novel genome memory structure called partial-DNA cyclic memory is proposed, in which cells only store a portion of the system’s entire DNA. The stored gene number is independent of the scale of embryonic array and of the target circuit, and can be set according to actual demand in the design process. Genes can be transferred in the cell and the embryonics array through intracellular and intercellular gene cyclic and non-cyclic shifts, and based on this process the embryonic array’s functional differentiation and self-repair can be achieved. In particular, lost genes caused by faulty cells can be recovered through gene updating based on the remaining normal neighbor cells during the self-repair process. A reliability model of the proposed memory structure is built considering the gene updating method, and depending on the implementations of the memory, the hardware overhead is modeled. Based on the reliability model and hardware overhead model, we can find that the memory can achieve high reliability with relatively few gene backups and with low hardware overhead. Theoretical analysis and a simulation experiment show that the new genome memory structure not only achieves functional differentiation and self-repair of the embryonics array, but also ensures system reliability while reducing hardware overhead. This has significant value in engineering applications, allowing the proposed genome memory structure to be used to design larger scale self-repair chips.

Description: As internet technologies make their way into developing areas, so too does the possibility of education and training being delivered to the people living in those previously unserved areas. The growing catalogue of free, high quality courseware, when combined with the newly acquired means of delivery, creates the potential for millions of people in the developing world to acquire a good education. Yet a good education obviously requires more than simply delivering information; students must also receive high quality feedback on their assessments. They must be told how their performance compares with the ideal, and be shown how to close the gap between the two. However, delivering high quality feedback is labor-intensive, and therefore expensive, and has long been recognized as a problematic issue by educators. This paper outlines a case study that uses a Learning Management System (LMS) to efficiently deliver detailed feedback that is informed by the principles of best practice. We make the case that the efficiencies of this method allow for large-scale courses with thousands of enrolments that are accessible to developing and developed areas alike. We explore the question; is computer-mediated feedback delivery efficient and effective and might it be applied to large-scale courses at low-cost?

Description: In the classic k -center problem, we are given a metric graph, and the objective is to select k nodes as centers such that the maximum distance from any vertex to its closest center is minimized. In this paper, we consider two important generalizations of k -center, the matroid center problem and the knapsack center problem. Both problems are motivated by recent content distribution network applications. Our contributions can be summarized as follows: (1) We consider the matroid center problem in which the centers are required to form an independent set of a given matroid. We show this problem is NP-hard even on a line. We present a 3-approximation algorithm for the problem on general metrics. We also consider the outlier version of the problem where a given number of vertices can be excluded as outliers from the solution. We present a 7-approximation for the outlier version. (2) We consider the (multi-)knapsack center problem in which the centers are required to satisfy one (or more) knapsack constraint(s). It is known that the knapsack center problem with a single knapsack constraint admits a 3-approximation. However, when there are at least two knapsack constraints, we show this problem is not approximable at all. To complement the hardness result, we present a polynomial time algorithm that gives a 3-approximate solution such that one knapsack constraint is satisfied and the others may be violated by at most a factor of \(1+\epsilon \) . We also obtain a 3-approximation for the outlier version that may violate the knapsack constraint by \(1+\epsilon \) .

Description: We design a succinct data structure for representing a poset that, given two elements, can report whether one precedes the other in constant time. This is equivalent to succinctly representing the transitive closure graph of the poset, and we note that the same method can also be used to succinctly represent the transitive reduction graph. For an n element poset, the data structure occupies \(n^2/4 + o(n^2)\) bits in the worst case. Furthermore, a slight extension to this data structure yields a succinct oracle for reachability in arbitrary directed graphs. Thus, using no more than a quarter of the space required to represent an arbitrary directed graph, reachability queries can be supported in constant time. We also consider the operation of listing all the successors or predecessors of a given element, and show how to do this in constant time per element reported using a slightly modified version of our succinct data structure.

Description: More and more hybrid electric vehicles are driven since they offer such advantages as energy savings and better active safety performance. Hybrid vehicles have two or more power driving systems and frequently switch working condition, so controlling stability is very important. In this work, a two-stage Kalman algorithm method is used to fuse data in hybrid vehicle stability testing. First, the RT3102 navigation system and Dewetron system are introduced. Second, a modeling of data fusion is proposed based on the Kalman filter. Then, this modeling is simulated and tested on a sample vehicle, using Carsim and Simulink software to test the results. The results showed the merits of this modeling.

Description: We consider a graph observability problem: how many edge colors are needed for an unlabeled graph so that an agent, walking from node to node, can uniquely determine its location from just the observed color sequence of the walk? Specifically, let G ( n ,  d ) be an edge-colored subgraph of d -dimensional (directed or undirected) lattice of size \(n^d = n \times n \times \cdots \times n\) . We say that G ( n ,  d ) is t -observable if an agent can uniquely determine its current position in the graph from the color sequence of any t -dimensional walk, where the dimension is the number of different directions spanned by the edges of the walk. A walk in an undirected lattice G ( n ,  d ) has dimension between 1 and d , but a directed walk can have dimension between 1 and 2 d because of two different orientations for each axis. We derive bounds on the number of colors needed for t -observability. Our main result is that \(\varTheta (n^{d/t})\) colors are both necessary and sufficient for t -observability of G ( n ,  d ), where d is considered a constant. This shows an interesting dependence of graph observability on the ratio between the dimension of the lattice and that of the walk. In particular, the number of colors for full-dimensional walks is \(\varTheta (n^{1/2})\) in the directed case, and \(\varTheta (n)\) in the undirected case, independent of the lattice dimension. All of our results extend easily to non-square lattices: given a lattice graph of size \(N = n_1 \times n_2 \times \cdots \times n_d\) , the number of colors for t -observability is \(\varTheta (\root t \of {N})\) .

Description: This paper describes the design of multirate filters used for the sample rate reduction of digital signals and their implementation on mixed-signal integrated circuits. Reaching target specifications of power, speed and silicon area as well as realizing multi-mode operation presents challenges. Possible solutions are discussed particularly for those filter stages which operate at the high sample rates and are illustrated in examples.

Description: A fault-injection tool can be very interesting in context to safety-critical applications, e.g., to test fault-detection and avoidance mechanisms or simply to stress an application and analyze its behavior when faults occur. In this work, a fault-injection tool is presented which can be used to instrument an FPGA design with fault-injection logic on netlist level during the implementation phase and to inject faults during runtime afterwards. The proposed approach can be smoothly integrated into an industrial FPGA tool flow, supports devices from multiple FPGA vendors and is highly configurable in order to fit to the number of available FPGA logic resources. Differences to related approaches which are applied on either HDL- and netlist-level as well as on the FPGA configuration bitstream are described. Finally, some results are presented to prove the applicability of the proposed solution.

Description: Line-of-sight (LOS) communication links have an ever increasing demand for high throughput IP-based data transmission. Such LOS systems are of particular interest for bi-directional communications from an aircraft to a ground station. A key requirement for the operation in various countries is carrier frequency agility because of the regulatory issues. That is why the LOS link developed by JOANNEUM RESEARCH DIGITAL supports adjustable carrier frequencies in the range from 2 GHz to 6 GHz. The used TDD (Time Division Duplex) medium access has the advantage that only one frequency for up- and downlink is required. A further advantage is configurable allocation of the available carrier bandwidth between the downlink to the ground and uplink to the aircraft. The maximum throughput in the downlink is 8 Mbit/s. The system is based on a software defined radio (SDR) approach which leads to high flexibility because of fast development and testing of signal processing algorithms. This fact allows cost effective adaption of the system to different user requirements. The paper is organized in the following way. Section 1 provides a system overview. In Section 2 the modem design parameters are discussed in detail, followed by Section 3 and 4 which present the signal processing algorithms implemented and the RF front end. Finally, Section 5 shows the signal characteristic of a test flight with a DA42 aircraft.

Description: In this paper, a comprehensive comparison analysis in terms of outage probability and average symbol error ratio (SER) is presented for cooperative cognitive multiple-input and multiple-output (CC-MIMO) multiuser systems with amplify-and-forward (AF) protocol. Specially, we consider two scenarios where the CC-MIMO multiuser systems have the perfect and imperfect channel state information (CSI). The CC-MIMO multiuser systems consist of one multi-antenna source, one single-antenna relay, and multiple multi-antenna destinations. At the secondary source and destinations, the maximal ratio transmission (MRT) and maximal ratio combining (MRC) are employed, respectively. For such CC-MIMO multiuser systems, we first obtain the exact closed-form expressions of outage probability under the two cases where the CC-MIMO multiuser systems have the perfect and imperfect CSI. Then, to reduce the implementation complexity, the tight lower bounds of outage probability and average SER are derived. Finally, to obtain insight, by using the high signal-to-noise ratio (SNR) approximation, the asymptotic estimations of outage probability are achieved. The numerical results show that the derivations are agreed with the simulations, which validate our derivations. At the same time, the results show that, for the systems without perfect CSI, the achievable diversity order reduces to one, regardless of the number of antennas at the cognitive source and destinations as well as the number of the cognitive destinations. Nevertheless, these key parameters affect the coding gain of the CC-MIMO multiuser systems. When the systems have the perfect CSI (or without feedback delay), the achievable diversity gain is determined by the minimum between the number of source’s antennas and the product of the number of destinations and the number of destination’s antennas. For the effect of PU’s parameters, our results indicate that primary systems only affect the coding gain but not the diversity gain.

Description: We revisit the matrix problems sparse null space and matrix sparsification , and show that they are equivalent. We then proceed to seek algorithms for these problems: we prove the hardness of approximation of these problems, and also give a powerful tool to extend algorithms and heuristics for sparse approximation theory to these problems.

Description: We introduce Planar Disjoint Paths Completion , a completion counterpart of the Disjoint Paths problem, and study its parameterized complexity. The problem can be stated as follows: given a, not necessarily connected, plane graph G ,  k pairs of terminals, and a face F of G ,  find a minimum-size set of edges, if one exists, to be added inside F so that the embedding remains planar and the pairs become connected by k disjoint paths in the augmented network. Our results are twofold: first, we give an upper bound on the number of necessary additional edges when a solution exists. This bound is a function of k , independent of the size of G . Second, we show that the problem is fixed-parameter tractable, in particular, it can be solved in time \(f(k)\cdot n^{2}\) .

Description: Currently deep learning has made great breakthroughs in visual and speech processing, mainly because it draws lessons from the hierarchical mode that brain deals with images and speech. In the field of NLP, a topic model is one of the important ways for modeling documents. Topic models are built on a generative model that clearly does not match the way humans write. In this paper, we propose Event Model, which is unsupervised and based on the language processing mechanism of neurolinguistics, to model documents. In Event Model, documents are descriptions of concrete or abstract events seen, heard, or sensed by people and words are objects in the events. Event Model has two stages: word learning and dimensionality reduction. Word learning is to learn semantics of words based on deep learning. Dimensionality reduction is the process that representing a document as a low dimensional vector by a linear mode that is completely different from topic models. Event Model achieves state-of-the-art results on document retrieval tasks.

Description: Data depth is a statistical method which models data distribution in terms of center-outward ranking rather than density or linear ranking. While there are a lot of academic interests, its applications are hampered by the lack of a method which is both robust and efficient. This paper introduces Half-Space Mass which is a significantly improved version of half-space data depth. Half-Space Mass is the only data depth method which is both robust and efficient, as far as we know. We also reveal four theoretical properties of Half-Space Mass : (i) its resultant mass distribution is concave regardless of the underlying density distribution, (ii) its maximum point is unique which can be considered as median, (iii) the median is maximally robust, and (iv) its estimation extends to a higher dimensional space in which the convex hull of the dataset occupies zero volume. We demonstrate the power of Half-Space Mass through its applications in two tasks. In anomaly detection, being a maximally robust location estimator leads directly to a robust anomaly detector that yields a better detection accuracy than half-space depth; and it runs orders of magnitude faster than \(L_2\) depth, an existing maximally robust location estimator. In clustering, the Half-Space Mass version of K-means overcomes three weaknesses of K-means.

Description: One of the greatest concerns related to the popularity of GPS-enabled devices and applications is the increasing availability of the personal location information generated by them and shared with application and service providers. Moreover, people tend to have regular routines and be characterized by a set of “significant places”, thus making it possible to identify a user from his/her mobility data.In this paper we present a series of techniques for identifying individuals from their GPS movements. More specifically, we study the uniqueness of GPS information for three popular datasets, and we provide a detailed analysis of the discriminatory power of speed, direction and distance of travel. Most importantly, we present a simple yet effective technique for the identification of users from location information that are not included in the original dataset used for training, thus raising important privacy concerns for the management of location datasets.

Description: The identification of distinct seismic regions and features’ extraction of theirs could provide valuable information towards the better understanding of the underlying physics, the generation mechanism and the behavior of the seismic phenomenon. This research paper works towards that direction and unveils the potential presence of a distinct seismic region located in between the Ionean sea and the Cretan see, extending south-east of Peloponnesus, Greece. This observation has emerged as a result of the development and application of a spatio temporal clustering algorithm based on expert knowledge upon seismic data provided by the Geodynamics Institute of Athens, and is further supported by geological observations, which have unveiled the presence of two parallel groups of underground faults beneath the newly discovered potential distinct seismic region. The overall spatio temporal clustering results throughout the Greek vicinity are also in accordance with empirical observations reported in the literature and coincide with cartographic groups of underground faults of Greece.

Description: In a virtualized environment, different virtual networks can operate over the same physical infrastructure. Each virtual network has its own protocols and share the available resources, thus highlighting the need of resource isolation mechanisms.Investigating the isolation mechanisms provided by FlowVisor, we have discovered vulnerabilities previously unknown regarding addressing space isolation. We show that, in the presence of a malicious controller, FlowVisor’s isolation can be broken allowing different attacks. This paper addresses these vulnerabilities by proposing an Action Slicing mechanism, that allows FlowVisor to limit which actions can be used by each virtual network controller, thus extending the virtual network definition. Our experimental results show that using the proposed Action Slicing mechanism can effectively neutralize the discovered vulnerabilities.

Description: Uniaxial compressive strength (UCS) of rock is crucial for any type of projects constructed in/on rock mass. The test that is conducted to measure the UCS of rock is expensive, time consuming and having sample restriction. For this reason, the UCS of rock may be estimated using simple rock tests such as point load index ( I s(50) ), Schmidt hammer ( R n ) and p-wave velocity ( V p ) tests. To estimate the UCS of granitic rock as a function of relevant rock properties like R n , p-wave and I s(50) , the rock cores were collected from the face of the Pahang–Selangor fresh water tunnel in Malaysia. Afterwards, 124 samples are prepared and tested in accordance with relevant standards and the dataset is obtained. Further an established dataset is used for estimating the UCS of rock via three-nonlinear prediction tools, namely non-linear multiple regression (NLMR), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). After conducting the mentioned models, considering several performance indices including coefficient of determination ( R 2 ), variance account for and root mean squared error and also using simple ranking procedure, the models were examined and the best prediction model was selected. It is concluded that the R 2 equal to 0.951 for testing dataset suggests the superiority of the ANFIS model, while these values are 0.651 and 0.886 for NLMR and ANN techniques, respectively. The results pointed out that the ANFIS model can be used for predicting UCS of rocks with higher capacity in comparison with others. However, the developed model may be useful at a preliminary stage of design; it should be used with caution and only for the specified rock types.

Description: The paper explores use of psychometric analysis based on latent trait theory to study quality of information propagation in online social networks. The collective intelligence of users of the network could be used to determine credibility of information. We use the latent trait of ability of users to distinguish between true information and misinformation as a measure of social computing in the network. Using repropagation features available in these networks as an affirmation of credibility of information, we build a dichotomous item response matrix which is evaluated using different models in latent trait theory. This enables us to detect presence of misinformation and also evaluate trust of users in the sources of information. Trust between users and sources of information is further used to construct a polytomous matrix. The matrices are evaluated using polytomous latent theory models to evaluate the types of trust and segregate possible collusion of users to spread misinformation. We show experimental results of psychometric analysis carried out in data sets obtained from ‘Twitter’ to support our claim.

Description: Without baseline information prior to damage, the damage should be detected by only measured data. Most non-baseline damage detection methods can be sensitive to the external noise and have difficulty in detecting damage when the sensor is not close to it. The purpose of this study is to propose a non-baseline damage detection method using only a few measurements and being less sensitive to the noise. A set of pseudo-reference data to be established at measurement instant is compared with another set of measurement data on the structure with the additional damage at a known location. The damage is found at the location to represent the abrupt change of the difference in the two response data sets. Compared to the global-deviation method, this method has merits to reduce the noise effect and to be able to detect damage by a few sensors. The experimental work also investigates the sensitivity of accelerometer and strain gage in detecting damage. The proposed method is verified in a numerical application and an experiment.

Description: We prove that in a graph with n vertices, induced chordal and interval subgraphs with the maximum number of vertices can be found in time \(\mathcal {O}(2^{\lambda n})\) for some \(\lambda 〈1\) . These are the first algorithms breaking the trivial \(2^n n^{\mathcal {O}(1)}\) bound of the brute-force search for these problems.

Description: Community detection in a complex network is an important problem of much interest in recent years. In general, a community detection algorithm chooses an objective function and captures the communities of the network by optimizing the objective function, and then, one uses various heuristics to solve the optimization problem to extract the interesting communities for the user. In this article, we demonstrate the procedure to transform a graph into points of a metric space and develop the methods of community detection with the help of a metric defined for a pair of points. We have also studied and analyzed the community structure of the network therein. The results obtained with our approach are very competitive with most of the well-known algorithms in the literature, and this is justified over the large collection of datasets. On the other hand, it can be observed that time taken by our algorithm is quite less compared to other methods and justifies the theoretical findings.

Description: A fundamental problem in data mining is to effectively build robust classifiers in the presence of skewed data distributions. Class imbalance classifiers are trained specifically for skewed distribution datasets. Existing methods assume an ample supply of training examples as a fundamental prerequisite for constructing an effective classifier. However, when sufficient data are not readily available, the development of a representative classification algorithm becomes even more difficult due to the unequal distribution between classes. We provide a unified framework that will potentially take advantage of auxiliary data using a transfer learning mechanism and simultaneously build a robust classifier to tackle this imbalance issue in the presence of few training samples in a particular target domain of interest. Transfer learning methods use auxiliary data to augment learning when training examples are not sufficient and in this paper we will develop a method that is optimized to simultaneously augment the training data and induce balance into skewed datasets. We propose a novel boosting-based instance transfer classifier with a label-dependent update mechanism that simultaneously compensates for class imbalance and incorporates samples from an auxiliary domain to improve classification. We provide theoretical and empirical validation of our method and apply to healthcare and text classification applications.

Description: We investigate the effect of limiting the number of reserve prices on the revenue in a probabilistic single item auction. In the model considered, bidders compete for an impression drawn from a known distribution of possible types. The auction mechanism sets up to \(\ell \) reserve prices, and each impression type is assigned the highest reserve price lower than the valuation of some bidder for it. The bidder proposing the highest bid for an arriving impression gets it provided his bid is at least the corresponding reserve price, and pays the maximum between the reserve price and the second highest bid. Since the number of impression types may be huge, we consider the revenue \(R_{\ell }\) that can be ensured using only \(\ell \) reserve prices. Our main results are tight lower bounds on \(R_{\ell }\) for the cases where the impressions are drawn from the uniform or a general probability distribution.

Description: Palmprint is a widely used biometric trait deployed in various access-control applications due to its convenience in use, reliability, and low cost. In this paper, we propose a novel scheme for palmprint recognition using a sparse representation of features obtained from Bank of Binarized Statistical Image Features (B-BSIF). The palmprint image is characterized by a rich set of features including principal lines, ridges, and wrinkles. Thus, the use of an appropriate texture descriptor scheme is expected to capture this information accurately. To this extent, we explore the idea of B-BSIF that comprises of 56 different BSIF filters whose responses on the given palmprint image is processed independently and classified using sparse representation classifier (SRC). Extensive experiments are carried out on three different large-scale publicly available palmprint databases. We then present an extensive analysis by comparing the proposed scheme with seven different contemporary state-of-the-art schemes that reveals the efficacy of the proposed scheme for robust palmprint recognition.

Description: A three-step iterative method with fifth-order convergence as a new modification of Newton’s method was presented. This method is for finding multiple roots of nonlinear equation with unknown multiplicity m whose multiplicity m is the highest multiplicity. Its order of convergence is analyzed and proved. Results for some numerical examples show the efficiency of the new method.

Description: To reduce the energy cost of underwater acoustic sensor networks (UWSNs), the duty cycle (i.e., periodic wake-up and sleep) concept has been used in several medium access control (MAC) protocols. Although these protocols are energy efficient, they sacrifice bandwidth utilization, which leads to lower transmission rate. In order to solve this problem, asynchronous duty cycle with network-coding Asynchronous Duty Cycle with Network-Coding MAC (ADCNC-MAC) is proposed. It contains initialization of the MAC protocol phase and data transmission phase. In the first phase, we use an asynchronous duty cycle to find a rendezvous time for exchanging data. A strategy to select network coder nodes is presented to confirm the number of network coder nodes and distribution in the network coder layer. In the data transmission phase, the network coder nodes transmit using the proposed network-coding-based algorithm and a higher volume of packet will be transmitted to the Sink with the same number of transmissions. Simulation results show that ADCNC-MAC achieves higher power efficiency, improves packet delivery ratio (PDR), and network throughput.

Description: Online trading interfaces are important instruments for retail investors. For sound reasons, regulators obligate online brokers to inform customers about certain trade related risks. Research has shown that different behavioral biases can decrease traders’ performance and hence lead to pecuniary losses. The disposition to hold losing stocks too long and sell winning stocks too early (‘disposition effect’) is such a deviation from rational behavior. The disposition effect is analyzed for the prediction market ‘Kurspiloten’ which predicts selected stock prices and counts nearly 2000 active traders and more than 200,000 orders. We show that the disposition effect can be aggravated by visual feedback on a trader’s performance via colored trend direction arrows and percentages. However, we find no evidence that such an interface modification leads to higher activity. Furthermore, we can not confirm that creating awareness of the disposition effect with textual information is suited to decreasing its strength.

Description: Most of the users of a BitTorrent community participate in multiple swarms, usually simultaneously as uploader and downloader. Thus the inter-swarm aspect of the bandwidth resource allocation has high relevance in the algorithm design of deployed BitTorrent clients. This inter-swarm connections among the users of a BitTorrent community can be represented by a flow network of special structure. Using this representation it has been demonstrated that de facto solutions to the resource allocation in BitTorrent communities are suboptimal. In this paper we investigate this conclusion in more details using graph measures and optimization techniques. We find that BitTorrent communities are sensitive for removal of highly contributing users, that the inter-swarm connectivity can lead to different performance results, and that torrent selection mechanisms can hardly improve the average download performance of users. Regarding the theoretical optimum of the discussed problem we show that it does not necessary comply with the BitTorrent protocol.

Description: Diese Arbeit gibt einen Einblick in die Entwurfsmethodik der Digitalteile für Mixed-Signal-Designs des österreichischen Halbleiterherstellers ams. Der Beitrag liefert zudem auch einen Überblick über die Entwicklung von Chips von ams für Audio- und Media-Player aus historischer Perspektive.

Description: Research on land use cover change (LUCC) has reached a mature stage and has formed a relatively complete scientific system. However, most studies analyzed the LUCC process from the view of land use types ignoring the integrality and systematicness of the land use system, which brought certain constraints to understanding the complexity and systematicness of land use process scientifically. Using the Modern Yellow River Delta (MYRD) of China as the study area, this research introduced the complex network analysis method to the study of the LUCC process by using 9 periods of land use data between 1976 and 2014 to build 8 stages of complex networks. The values of node degree, betweenness, changing proportions, and average shortest path in the networks were calculated to identify the key land use types, changing models of land use types, and the stability of land use system. Additionally, main parts of complex networks of the period from 1976 to 1995 and the period from 1995 to 2014 were selected to evaluate the changing characteristics of the LUCC process. The results indicated the area and proportion of natural wetland kept reducing, but the area and proportion of artificial wetland or non-wetland continued rising. The bare land, reed, bush, and cultivated land were the key land use types of the LUCC process. In the past 38 years, beach, bare land, reed and bush had been the output types, and the building land and salt pan had been the input types. The LUCC process has been a transfer process of natural wetland to artificial wetland and non-wetland in the past 38 years, which could be divided into land accretion process (1976 to 1995) and construction process (1995 to 2014). The land ecosystem was unstable for the period from 1990 to 2006.

Description: Modern application-specific integrated circuits (ASICs) contain complete systems on a single die, composed of many processing elements that communicate over a dedicated router-based on-chip network. As systems-on-chip comprise billions of transistors with feature sizes in the range of 10 nm, reliable operation cannot be established without carefully engineered support at all levels, from technology to the circuit- and the system-layer. This article surveys contributions of research groups at TU Wien to this field. At lower levels of abstraction, they range from the generation of fault models for simulation that closely match reality and are at the same time efficient to use, to circuit-level radiation-tolerance techniques. At the level of on-chip networks, novel fault-tolerant routing algorithms are being developed together with architectural techniques to isolate faulty parts while keeping the healthy parts connected and active. The article will briefly portray the associated research activities and summarize their most relevant results.

Description: The Internet is composed of routing devices connected between them and organized into independent administrative entities: the Autonomous Systems. The existence of different types of Autonomous Systems (like large connectivity providers, Internet Service Providers or universities) together with geographical and economical constraints, turns the Internet into a complex modular and hierarchical network. This organization is reflected in many properties of the Internet topology, like its high degree of clustering and its robustness.In this work we study the modular structure of the Internet router-level graph in order to assess to what extent the Autonomous Systems satisfy some of the known notions of community structure. We observe that most of the classical community detection methods fail to detect the Autonomous Systems as communities, mainly because the modular structure of the Internet (as that of many complex networks) is much richer than what can be captured by optimizing a global functional: Autonomous Systems have largely variable sizes, structures and functions. Classical methods are severely affected by resolution limits and by the heterogeneity of the communities; even when using multiresolution methods, there is no single resolution at which most of the communities can be captured.However, we show that multiresolution methods do find the community structure of the Autonomous Systems, but each of them has to be observed at the correct resolution level. Then we develop a low-complexity multiresolution modularity optimization algorithm that finds communities at different resolution levels in a continuous scale, in one single run. Using this method, we show that with a scarce knowledge of the node affiliations, multiresolution methods can be adjusted to retrieve the Autonomous Systems, significantly improving the results of classical single-resolution methods. Finally, in the light of our results, we discuss recent work concerning the use of a priori information to find community structure in complex networks.

Description: In this paper, experimental results of using hot wire anemometer and smoke visualization are presented. The results obtained on the hot wire anemometer for critical Reynolds number and transitional Reynolds number are compared with previous results. Excellent agreement is found for the transitional Reynolds number. The results for the transitional Reynolds number are also compared with previous linear stability results. The results of the smoke visualization clearly show the crossflow vortices which arise in the transition process from a laminar to a turbulent flow. A non-zero angle of attack is also considered. We compare our results with linear stability theory put forward by Garrett and Peake (Eur J Mech B Fluid 26:344–353, 2007 ). Also the visualization and hot wire anemometer results have been compared graphically. The goal of this paper is to check reliability of using hot wire anemometer and smoke visualization in transition problems and check reliability of linear stability theory for this case and compare our results with some trusty experimental works. Graphical Abstract

Description: The orbital debris problem presents an opportunity for international cooperation toward the mutually beneficial goals of orbital debris prevention, mitigation, remediation, and improved space situational awareness (SSA). Achieving these goals requires sharing orbital debris and other SSA data. Toward this, I present an ontological architecture for the orbital debris and related domains, taking steps in the creation of an orbital debris ontology. The purpose of the ontology is to capture general scientific domain knowledge; formally represent the entities within the domain; form, structure, and standardize (where needed) orbital and SSA terminology; and foster semantic interoperability and data-exchange. In doing so I hope to offer a scientifically accurate ontological representation of the orbital domain; contribute to research in astroinformatics, space ontology, and space data management; and improve spaceflight safety by providing a means to capture and communicate informaiton associated with space debris.

Description: The possibility of having information access anytime and anywhere has caused a huge increase of the popularity of wireless networks. Requirements of users and owners have been ever-increasing. However, concerns about the potential health impact of exposure to radio frequency (RF) sources have arisen and are getting accounted for in wireless network planning. In addition to adequate coverage and reduced human exposure, the installation cost of the wireless network is also an important criterion in the planning process. In this paper, a hybrid algorithm is used to optimize indoor wireless network planning while satisfying three demands: maximum coverage, minimal full installation cost (cabling, cable gutters, drilling holes, labor, etc.), and minimal human exposure. For the first time, wireless indoor networks are being optimized based on these advanced and realistic conditions. The algorithm is investigated for three scenarios and for different configurations. The impact of different exposure requirements and cost scenarios is assessed.

Description: Physical transceiver implementations for wireless communication systems usually suffer from transmit-radio frequency (Tx-RF) and receiver-RF (Rx-RF) impairments. In this paper, we aim to design efficient coordinated beamforming for multicell multiuser multi-antenna systems by fully taking into account the residual transceiver impairments. Our design objectives include both spectral efficiency and energy efficiency. In particular, we first derive the closed-form expression of the mean square error (MSE) which includes the impact of transceiver impairments. Based on that, we propose an alternating optimization algorithm to solve the coordinated multicell beamforming problems with the goal of minimizing the worst user MSE, and the sum MSE. Then, by exploiting the relationship between the minimum mean square error (MMSE) and the achievable rate, we develop a new algorithm to address the sum rate maximization problem. This approach is further generalized to solve the more intractable energy efficiency optimization problem. We prove that all the proposed iterative algorithms guarantee to converge to a stationary point. Numerical results show that our proposed schemes achieve a better performance than conventional coordinated beamforming algorithms that were designed ignoring the transceiver impairments.

Description: The new dual-pivot Quicksort by Vladimir Yaroslavskiy—used in Oracle’s Java runtime library since version 7—features intriguing asymmetries. They make a basic variant of this algorithm use less comparisons than classic single-pivot Quicksort. In this paper, we extend the analysis to the case where the two pivots are chosen as fixed order statistics of a random sample. Surprisingly, dual-pivot Quicksort then needs more comparisons than a corresponding version of classic Quicksort, so it is clear that counting comparisons is not sufficient to explain the running time advantages observed for Yaroslavskiy’s algorithm in practice. Consequently, we take a more holistic approach and give also the precise leading term of the average number of swaps, the number of executed Java Bytecode instructions and the number of scanned elements, a new simple cost measure that approximates I/O costs in the memory hierarchy. We determine optimal order statistics for each of the cost measures. It turns out that the asymmetries in Yaroslavskiy’s algorithm render pivots with a systematic skew more efficient than the symmetric choice. Moreover, we finally have a convincing explanation for the success of Yaroslavskiy’s algorithm in practice: compared with corresponding versions of classic single-pivot Quicksort, dual-pivot Quicksort needs significantly less I/Os, both with and without pivot sampling.

Description: In the era of big data, scientific research is entering a key stage of scientific development under the guidance of a new paradigm, “e-Science”, and the core characteristics of which are collaboration and sharing. In the past decade, e-Science has rapidly developed around the world. There are now e-Science strategic plans, projects and extensive research activities on the national and international scales that encompass particle physics, astronomy, earth science, ecology, marine science, medicine, life sciences and other disciplines. However, there is no uniform and clear understanding of the essence, characteristics, infrastructure and application of e-Geoscience. This paper first discusses and analyzes the development of e-Science in a global context and then explores its development in China. Next, the development of e-Geoscience is discussed, particularly regarding the details of its design and implementation in China, including a conceptual model, a mode of application, a logical hierarchy, and functional and technical systems. Finally, the paper introduces a typical application, called the Northeast Asia Joint Scientific Exploration and Cooperative Research Platform (NAJSECRP), which is operating in research institutions in China, Russia and Mongolia. This platform can not only provide geodata and bibliographies and promote resource sharing but also provides a collaborative research platform for scientific exploration. In practice, this platform has been shown to save costs and improve the efficiency of transnational, interdisciplinary scientific exploration and cooperative research.

Description: In this paper, we consider the Unsplittable (hard) Capacitated Facility Location Problem (UCFLP) with uniform capacities and present new approximation algorithms for it. This problem is a generalization of the classical facility location problem where each facility can serve at most u units of demand and each client must be served by exactly one facility. This problem is motivated by its applications in many practical problems including supply chain problems of indivisible goods (Verter in Foundations of location analysis, chapter 2. International series in operations research and management science. Springer, Berlin, 2011 ) and the assignment problem in the content distribution networks (Bateni and Hajiaghayi in Proceedings of the nineteenth annual ACM-SIAM symposium on discrete algorithms, pp 805–814, 2009 ). While there are several approximation algorithms for the soft capacitated version of this problem (in which one can open multiple copies of each facility) or the splittable version (in which the demand of each client can be divided to be served by multiple open facilities), there are very few results for the UCFLP. It is known that it is NP-hard to approximate this problem within any factor without violating the capacities. So we consider bicriteria \((\alpha ,\beta )\) -approximations where the algorithm returns a solution whose cost is within factor \(\alpha \) of the optimum and violates the capacity constraints within factor \(\beta \) . Shmoys et al. (Proceedings of the twenty-ninth annual ACM symposium on theory of computing, pp 265–274, 1997 ) were the first to consider this problem and gave a (9, 4)-approximation. Later results imply ( O (1), 2)-approximations, however, no constant factor approximation is known with capacity violation of less than 2. We present a framework for designing bicriteria approximation algorithms for this problem and show two new approximation algorithms with factors (9, 3 / 2) and (29.315, 4 / 3). These are the first algorithms with constant approximation in which the violation of capacities is below 2. The heart of our algorithm is a reduction from the UCFLP to a restricted version of the problem. One feature of this reduction is that any \((O(1),1+{\epsilon })\) -approximation for the restricted version implies an \((O(1),1+{\epsilon })\) -approximation for the UCFLP and we believe our techniques might be useful towards finding such approximations or perhaps \((f({\epsilon }),1+{\epsilon })\) -approximation for the UCFLP for some function f . In addition, we present a quasi-polynomial time \((1+\epsilon ,1+\epsilon )\) -approximation for the (uniform) UCFLP in Euclidean metrics, for any constant \({\epsilon }〉0\) .

Description: Designing robust mission-critical systems demands bringing together fault tolerance and security. The emergence of Advanced Persistent Threats (APT) has further added to the challenge of meeting mission assurance goals. Despite the advances in mission survivability, the existing solutions remain ineffective against APTs. In this paper, we propose a novel survivability architecture against APTs in a distributed environment. It involves tamper-resistant and surreptitious detection and node-to-node verification of suspicious events. The solution aims to identify Attacker Intent, Objectives and Strategies (AIOS) and to design targeted recoveries that promote survivability. Its security strength has been theoretically analyzed, while the performance and scalability aspects are measured via simulation. Our simulations demonstrate high scalability with respect to network size and application runtime and the time overhead for long running applications can be easily kept under 1 % of original runtime by carefully adjusting the security strength.

Description: Archetypal analysis represents a set of observations as convex combinations of pure patterns, or archetypes. The original geometric formulation of finding archetypes by approximating the convex hull of the observations assumes them to be real–valued. This, unfortunately, is not compatible with many practical situations. In this paper we revisit archetypal analysis from the basic principles, and propose a probabilistic framework that accommodates other observation types such as integers, binary, and probability vectors. We corroborate the proposed methodology with convincing real-world applications on finding archetypal soccer players based on performance data, archetypal winter tourists based on binary survey data, archetypal disaster-affected countries based on disaster count data, and document archetypes based on term-frequency data. We also present an appropriate visualization tool to summarize archetypal analysis solution better.

Description: In 1990s, burglars used to break into house, while the residents were viewing some interesting television shows. This type of attacks happened mainly in the physical world and it was expected that cyber world is free from such crimes. Unfortunately, this is not true. A skilled hacker could compromise a system, while the user is viewing (an interesting) video file. Quite often computer users, use their machines for viewing (interesting) videos. Such users may be naive users or could even be those who work on mission critical systems, like banking, defence, nuclear power-plant, space agencies etc. So playing a video file can lead to high security risk. In this paper, we have analysed video files, for detecting multistage attacks. We found that some video files contain malicious link through which an exploit gets downloaded into the host machine. The contribution of this paper is the discovery of novel attacks that are hidden (by perpetrator) in innocuous video files with the objective of staging a targeted attack in multiple stages. Finally, we propose a new method for detection of such attacks (carried through video files) using API calls.

Description: Business process standardization is the activity of unifying different variants of a family of business processes. While the positive effects of business process standardization are well-described, it is often undesirable to fully unify different variants due to cultural, legal, or operational reasons. Consequently, a decision has to be made about the extent to which a family of business processes should be standardized. However, little is known about the factors that drive that decision. This paper fills that gap, by presenting factors that drive the extent to which business processes can be standardized, performance properties that are influenced by business process standardization, and relations between these concepts.

Description: Community search is the problem of finding a good community for a given set of query vertices. One of the most studied formulations of community search asks for a connected subgraph that contains all query vertices and maximizes the minimum degree. All existing approaches to min-degree-based community search suffer from limitations concerning efficiency, as they need to visit (large part of) the whole input graph, as well as accuracy, as they output communities quite large and not really cohesive. Moreover, some existing methods lack generality: they handle only single-vertex queries, find communities that are not optimal in terms of minimum degree, and/or require input parameters. In this work we advance the state of the art on community search by proposing a novel method that overcomes all these limitations: it is in general more efficient and effective—one/two orders of magnitude on average, it can handle multiple query vertices, it yields optimal communities, and it is parameter-free. These properties are confirmed by an extensive experimental analysis performed on various real-world graphs.

Description: With the rapid development of geospatial service and sensor technologies, large volumes of geospatial data have been collected using various sensor networks, and accessible on the Web. Traditional geospatial data processing could be task-oriented, since a geoprocessing task can be described by a set of action steps, implemented as a workflow, and executed using distributed geoprocessing services. Tasks facilitate the expression of user requirements and capture the problem solving knowledge of users. In this paper, the task-oriented approach is extended to the OGC Sensor Web environment. It highlights how the event-driven technologies adopted by the Sensor Web can be leveraged with geoprocessing workflows to support environment monitoring tasks. The proposal of a Task Model Language (TaskML) and task trigger mechanism allows environmental events to be plugged into an existing model builder, GeoJModelBuilder. Tasks can be created in a stepwise manner, and their execution priority can be updated automatically using triggers. Compared to the traditional “reactive” task enactment mode, the trigger-augmented task can support “active” environmental monitoring. Use cases on PM2.5/PM10 monitoring demonstrate the applicability of the approach.

Description: In this paper, we present three improvements to a three-point third order variant of Newton’s method derived from the Simpson rule. The first one is a fifth order method using the same number of functional evaluations as the third order method, the second one is a four-point 10th order method and the last one is a five-point 20th order method. In terms of computational point of view, our methods require four evaluations (one function and three first derivatives) to get fifth order, five evaluations (two functions and three derivatives) to get 10th order and six evaluations (three functions and three derivatives) to get 20th order. Hence, these methods have efficiency indexes of 1.495, 1.585 and 1.648, respectively which are better than the efficiency index of 1.316 of the third order method. We test the methods through some numerical experiments which show that the 20th order method is very efficient.

Description: Robust small target detection of low signal-to-noise ratio (SNR) is very important in infrared search and track applications for self-defense or attacks. Due to the complex background, current algorithms have some unsolved issues with false alarm rate. In order to reduce the false alarm rate, an infrared small target detection algorithm based on saliency detection and support vector machine was proposed. Firstly, we detect salient regions that may contain targets with phase spectrum Fourier transform (PFT) approach. Then, target recognition was performed in the salient regions. Experimental results show the proposed algorithm has ideal robustness and efficiency for real infrared small target detection applications.

Description: In dynamic propagation environments, beamforming algorithms may suffer from strong interference, steering vector mismatches, a low convergence speed and a high computational complexity. Reduced-rank signal processing techniques provide a way to address the problems mentioned above. This paper presents a low-complexity robust data-dependent dimensionality reduction based on an iterative optimization with steering vector perturbation (IOVP) algorithm for reduced-rank beamforming and steering vector estimation. The proposed robust optimization procedure jointly adjusts the parameters of a rank reduction matrix and an adaptive beamformer. The optimized rank reduction matrix projects the received signal vector onto a subspace with lower dimension. The beamformer/steering vector optimization is then performed in a reduced dimension subspace. We devise efficient stochastic gradient and recursive least-squares algorithms for implementing the proposed robust IOVP design. The proposed robust IOVP beamforming algorithms result in a faster convergence speed and an improved performance. Simulation results show that the proposed IOVP algorithms outperform some existing full-rank and reduced-rank algorithms with a comparable complexity.

Description: Recently, wireless sensor networks (WSNs) have drawn great interest due to their outstanding monitoring and management potential in medical, environmental and industrial applications. Most of the applications that employ WSNs demand all of the sensor nodes to run on a common time scale, a requirement that highlights the importance of clock synchronization. The clock synchronization problem in WSNs is inherently related to parameter estimation. The accuracy of clock synchronization algorithms depends essentially on the statistical properties of the parameter estimation algorithms. Recently, studies dedicated to the estimation of synchronization parameters, such as clock offset and skew, have begun to emerge in the literature. The aim of this article is to provide an overview of the state-of-the-art clock synchronization algorithms for WSNs from a statistical signal processing point of view. This article focuses on describing the key features of the class of clock synchronization algorithms that exploit the traditional two-way message (signal) exchange mechanism. Upon introducing the two-way message exchange mechanism, the main clock offset estimation algorithms for pairwise synchronization of sensor nodes are first reviewed, and their performance is compared. The class of fully-distributed clock offset estimation algorithms for network-wide synchronization is then surveyed. The paper concludes with a list of open research problems pertaining to clock synchronization of WSNs.

Description: This paper proposes a discussion concerning the use of social media-related geographic information in the context of the strategic environmental assessment (SEA) of Sardinian Municipal masterplans (MMPs). We show that this kind of information improves, substantially, the SEA process since it provides planners, evaluators, and the local communities with information retrieved from social media that would have not been available otherwise. This information integrates authoritative data collection, which comes from official sources, and enlightens tastes and preferences of the users of services and infrastructure, and their expectations concerning their spatial organization. A methodological approach related to the collection of social media-related geographic information is implemented and discussed with reference to the urban context of the city of Cagliari (Sardinia, Italy). The results are very effective in terms of provision of information, which may possibly increase the spatial knowledge available for planning policy definition and implementation. In this perspective, this kind of information discloses opportunities for building analytical scenarios related to urban and regional planning and it offers useful suggestions for sustainable development based on tourism strategies.

Description: Network coding is an emerging technique known to improve the network performance in many aspects. In Vehicular Ad-hoc Networks (VANET), the bandwidth is considered to be one of the most important network resources. In this paper, we propose a network coding technique to improve the bandwidth utilization for non-safety applications in VANET. In a scenario where there are two sources broadcasting the data into the same area at the same time, the relay will use the network coding technique to decrease the number of rebroadcasting events and the consumption of the bandwidth, However, a fundamental problem for the relay when it receives a packet, is whether to wait for a coding opportunity and save the bandwidth or send the packet directly and reduce the delay. In order to address such tradeoff, we introduce two versions of our protocol, namely buffer size control scheme (BSCS) and time control scheme (TCS); by both versions we aim to control the delay that is experienced by the packet at each hop, while achieving better bandwidth utilization.Up to 38 % improvement in the bandwidth utilization has been recorded, and both schemes have shown a considerable amount of control on the imposed delay.

Description: Peer-to-peer (P2P) systems have been widely researched over the past decade, leading to highly scalable implementations for a wide range of distributed services and applications. A P2P system assigns symmetric roles to machines, which can act both as client and server. This alleviates the need for any central component to maintain a global knowledge of the system. Instead, each peer takes individual decisions based on a local knowledge of the rest of the system, providing scalability by design.While P2P systems have been successfully applied to a wide range of distributed applications (multicast, routing, storage, pub-sub, video streaming), with some highly visible successes (Skype, Bitcoin), they tend to have fallen out of fashion in favor of a much more cloud-centric vision of the current Internet. We think this is paradoxical, as cloud-based systems are themselves large-scale, highly distributed infrastructures. They reside within massive, densely interconnected datacenters, and must execute efficiently on an increasing number of machines, while dealing with growing volumes of data. Today even more than a decade ago, large-scale systems require scalable designs to deliver efficient services.In this paper we argue that the local nature of P2P systems is key for scalability regardless whether a system is eventually deployed on a single multi-core machine, distributed within a data center, or fully decentralized across multiple autonomous hosts. Our claim is backed by the observation that some of the most scalable services in use today have been heavily influenced by abstractions and rationales introduced in the context of P2P systems. Looking to the future, we argue that future large-scale systems could greatly benefit from fully decentralized strategies inspired from P2P systems. We illustrate the P2P legacy through several examples related to Cloud Computing and Big Data, and provide general guidelines to design large-scale systems according to a P2P philosophy.

Description: An iterative back projection method (i-BP) has been developed to improve the resolution of reconstructed images produced by electrical resistance tomography (ERT). This solution is based on an iterative calculation of the electrical fields and it is possible to reconstruct clearer images than those reconstructed by the conventional back projection method without divergence. However, it does take several minutes to finish the iteration process, and therefore this solution can be applied to flow fields that require high spatial resolution rather than short processing times, such as the accumulation of noble metals in glass melters. Numerical simulations and experiments using a simple model are performed in this study. The numerical simulations show that clear images are reconstructed both near the wall and at the center by i-BP. The conductivity correlation coefficient between the genuine distribution and the reconstructed image is improved from 0.4 to 0.9. The validity of the i-BP method is also confirmed by the experimental results. As a result, it is confirmed that ERT and i-BP are capable of reconstructing acceptable images and have potential for use in the visualization of the accumulation of noble metals in a glass melter. Graphical Abstract

Description: Long-Term Evolution (LTE) was implemented to fulfill and satisfy users’ needs as well as their demands for an improvised, fast and efficient Quality of service (QoS). A minimal aggregate of waiting time in return would give users a better Quality of experience (QoE). Real-time service packet scheduling is an important process in allocating resources to users. An efficient packet scheduling scheme will be able to cater fairly and efficiently to its users in the LTE network. Hence, studies are performed focusing on real-time traffic which includes video as well as Voice over Internet Protocol (VoIP) transmissions. In this work, the existing exponential rule (EXP rule) is utilized to benchmark our proposed packet scheduling techniques so that we are able to further evaluate the scheduling performance. In response to the increasing likelihood of losing packets in the EXP rule’s algorithm and maximizing the throughput rate, several schemes have been experimented with. The proposed schemes include 1) simplified EXP rule (sEXP Rule), 2) modified EXP rule (mEXP Rule), 3) EXP rule with maximum throughput (MT) (EXP_MT Rule), and 4) enhanced EXP rule with MT (E2M). By adding MT as a weight to the EXP rule, the throughput is maximized, thus providing higher throughput rates for real-time and non-real-time traffic. The simulation results show that the sEXP rule has a better performance in throughput, packet loss rate (PLR), and spectral efficiency for video traffic. Aside from this, our proposed E2M rule performs better than the benchmark EXP rule and outperforms the other proposed schemes, as well. It is observed that the E2M rule has better QoS support for real-time transmission in terms of delay, packet loss, throughput and spectral efficiency, within the LTE network. Hence, our proposed E2M rule is an enhancement of the benchmark EXP rule, which is commonly used in LTE packet scheduling.

Description: A commonly studied means of parameterizing graph problems is the deletion distance from triviality (Guo et al., Parameterized and exact computation, Springer, Berlin, pp. 162–173, 2004 ), which counts vertices that need to be deleted from a graph to place it in some class for which efficient algorithms are known. In the context of graph isomorphism, we define triviality to mean a graph with maximum degree bounded by a constant, as such graph classes admit polynomial-time isomorphism tests. We generalise deletion distance to a measure we call elimination distance to triviality, based on elimination trees or tree-depth decompositions. We establish that graph canonisation, and thus graph isomorphism, is \(\mathsf {FPT}\) when parameterized by elimination distance to bounded degree, extending results of Bouland et al. (Parameterized and exact computation, Springer, Berlin, pp. 218–230, 2012 ).

Description: Recent advances in drift analysis have given us better and better tools for understanding random processes, including the run time of randomized search heuristics. In the setting of multiplicative drift we do not only have excellent bounds on the expected run time, but also more general results showing the strong concentration of the run time. In this paper we investigate the setting of additive drift under the assumption of strong concentration of the “step size” of the process. Under sufficiently strong drift towards the goal we show a strong concentration of the hitting time. In contrast to this, we show that in the presence of small drift a Gambler’s-Ruin-like behavior of the process overrides the influence of the drift, leading to a maximal movement of about \(\sqrt{t}\) steps within t iterations. Finally, in the presence of sufficiently strong negative drift the hitting time is superpolynomial with high probability; this corresponds to the well-known Negative Drift Theorem.

Description: A trie is one of the data structures for keyword search algorithms and is utilized in natural language processing, reserved words search for compilers and so on. The double-array and LOUDS are efficient representation methods for the trie. The double-array provides fast traversal at time complexity of O (1), but the space usage of the double-array is larger than that of LOUDS. LOUDS is a succinct data structure with bit-string, and its space usage is extremely compact. However, its traversal speed is not so fast. This paper presents a new compression method of the double-array with keeping the retrieval speed. Our new method compresses the double-array by dividing the double-array into blocks and by using linear functions. Experimental results for varied keywords show that our new method reduced space usage of the double-array up to about 44 %, and the retrieval speed of the new method was 9–14 times faster than that of LOUDS. Moreover, the results show that the construction speed of the new method was faster than that of the conventional method for a large keyword set.

Description: Brazil is an emerging economy with many IT initiatives from public and private sectors. To evaluate the progress of such initiatives, we study the geographical distribution of software developers in Brazil, in particular which of the Brazilian states succeed the most in attracting and nurturing them. We compare the prestige of developers with socio-economic data and find that (i) prestigious developers tend to be located in the most economically developed regions of Brazil, (ii) they are likely to follow others in the same state they are located in, (iii) they are likely to follow other prestigious developers, and (iv) they tend to follow more people. We discuss the implications of those findings for the development of the Brazilian software industry.

Description: The structure of scientific collaboration networks provides insight on the relationships between people and disciplines. In this paper, we study a bipartite graph connecting authors to publications and extract from it clusters of authors and articles, interpreting the author clusters as research groups and the article clusters as research topics. Visualisations are proposed to ease the interpretation of such clusters in terms of discovering leaders, the activity level, and other semantic aspects. We discuss the process of obtaining and preprocessing the information from scientific publications, the formulation and implementation of the clustering algorithm, and the creation of the visualisations. Experiments on a test data set are presented, using an initial prototype implementation of the proposed modules.

Description: Although Internet service providers (ISPs) are technically capable as well as legally allowed to offer non-neutral Internet access services, where the data flows of customers who pay a premium are prioritized over others, such an access service is currently not offered by ISPs. We argue that ISPs are hesitant to tap the price discrimination potential of prioritized Internet access services, because in the context of the ongoing public debate on net neutrality (NN), their customers would consider such differentiation unjust. In a representative survey among German Internet access customers, we find that the customers’ perceptions of justice as well as the framing of the mechanism by which prioritized Internet access is provided are indeed decisive for whether customers would prefer this access regime over NN. In particular, we find that perceptions of distributive and procedural justice influence customers’ choice for non-neutral Internet access. Moreover, customers are more likely to accept a regime that offers an absolute rather than a relative prioritization of data flows.

Description: The instability analysis of the liquid jet issuing into ambient air was conducted with an emphasis placed upon the evolution of surface waves of the jet. An experiment was designed to visualize the microscopic morphology on the surface of a liquid jet. A spectral method was proposed to measure wavelength from the obtained jet images. We also discuss key setup parameters that significantly affect the resolution of desired jet features and the accuracy of the spectral measurement. The results show that the liquid jet near the nozzle exit can be divided into a laminar section, a transition section, an instability section, and a turbulence section. Surface wave scales range from 0.06 to 0.11 times of the nozzle diameter with the atomization breakup regime. For the atomization breakup regime, the growth ratio of the surface waves of the instability section is 0.06 which is 1.5 times the value of the second wind-introduced breakup regime and 3 times the value of the first wind-introduced breakup regime. Graphical abstract

Description: In delay tolerant networks (DTNs), the network may not be fully connected at any instant of time, but connections occurring between nodes at different times make the network connected through the entire time continuum. In such a case, traditional routing methods fail to operate because there are no contemporaneous end-to-end paths between sources and destinations. This study examines the routing in DTNs where connections arise in a periodic nature. We analyze various levels of periodicity in order to meet the requirements of different network models. We propose different routing algorithms for different kinds of periodic connections. Our proposed routing methods guarantee the earliest delivery time and minimum hop-count, simultaneously. We evaluate our routing schemes via extensive simulation experiments and compare them to some other popular routing approaches proposed for DTNs. Our evaluations show the feasibility and effectiveness of our schemes as viable routing methods for delay tolerant networks.

Description: In recent years rising complexity, shrinking silicon feature sizes, and reduced design cycles have posed new challenges on the verification of modern system-on-chip solutions. To tackle the issues caused by the rising complexity various design and verification languages, as well as methodologies and tools have been introduced. Likewise, new and better physical process models allow for improved simulation of both analog and digital designs. Finally, strict management plans are used to cope with the shrinking design and verification cycles. Despite all these efforts, however, many problems exist in industrial state-of-the-art processes and tools. This article gives some insights and presents some lessons learned from the design and verification of a recent automotive microcontroller, a complex system-on-chip solution. Based on these findings, a new verification flow is proposed that closes an identified gap between pre-silicon and post-silicon verification.

Description: Measurements of turbulent swirling flow by means of hot-wire anemometry and stereoscopic particle image velocimetry were performed, 0.67 pipe diameters downstream a 90° pipe bend. The flow for a wide range of swirl numbers up to \(S=1.2\) , based on the angular velocity of the pipe wall and bulk velocity, was investigated and compared to the non-swirling case. The limitations and advantages of using a single hot-wire probe in a highly complex flow field are investigated and discussed. The present paper makes available a unique database for a kind of flow that has been neglected in literature and which is believed to be useful for validation purposes for the computational fluid dynamics community. Graphical abstract

Description: To monitor multiple environmental factors of henhouses in modern chicken farms, a henhouse online monitoring system based on wireless sensor network was developed using wireless sensor technology and computer network technology. Sensor data compensation and correction were designed to be achieved using software and data fitting methods, data reliable transmission achieved using a data loss recovery strategy, and data missing during monitoring addressed using a self-decision and online filling method. Operation test of the system showed that: The system was economic and reliable; it enabled wireless monitoring and Web display of the environmental factors of a henhouse; and the root mean square errors (RMSEs) between the estimated values from the self-decision and on-line filling method and experimental values of the four environmental factors were 0.1698, 3.0859, 77 and 0.094, respectively, indicative of high estimation accuracy. The system can provide support for modern management of henhouses and can be transplanted to related monitoring scenarios in the agricultural field.

Description: Due to rapid developments in mobile technology as well as various multimedia features like messaging, browsing, and streaming, user-created mobile contents are increasing, both in terms of quantity and quality, and at the same time are shared in real time. To get into step with such movements, new content-centric networking (CCN) has appeared. However, CCN has not taken the effect of consumer device movements into consideration. So, this paper proposes a partial path extension scheme to provide lower communication overhead, shorter download time, and lower network resource consumption in mobile consumer environments.

Description: Binets and trinets are phylogenetic networks with two and three leaves, respectively. Here we consider the problem of deciding if there exists a binary level-1 phylogenetic network displaying a given set  \(\mathbb {T}\) of binary binets or trinets over a taxon set  X , and constructing such a network whenever it exists. We show that this is NP-hard for trinets but polynomial-time solvable for binets. Moreover, we show that the problem is still polynomial-time solvable for inputs consisting of binets and trinets as long as the cycles in the trinets have size three. Finally, we present an  \(O(3^{|X|} poly(|X|))\) time algorithm for general sets of binets and trinets. The latter two algorithms generalise to instances containing level-1 networks with arbitrarily many leaves, and thus provide some of the first supernetwork algorithms for computing networks from a set of rooted phylogenetic networks.

Description: This study investigates the antecedents of HIPI (Healthcare Information Protection Intention) of HIS (Healthcare Information Systems) users by introducing a model which incorporates constructs from GDT (General Deterrence Theory) and PMT (Protection Motivation Theory). The results show that (1) a clear awareness of the consequences of security threats increases HIS users’ understanding on the severity of healthcare information leakage, and thus may decreases abuse of HIS by users; (2) user satisfaction with the security system may make them have self-efficacy that they can handle the medical information leakage issue by themselves; and (3) although HIS users are realizing the consequences of healthcare information leakage, they think that they are unlikely to encounter such situations. The results imply that in order to increase HIPI of HIS users, ongoing security education is needed and motivating users to protect healthcare information through their satisfaction with the security system is important.

Description: Smart grid technologies are bringing innovations in electrical power industries, affecting all parts of the electricity supply chain, and leading to changes in market structure, business models and services. In this paper we introduce a model of business intelligence for a smart grid supply chain. The model is developed in order to provide electricity markets with the necessary data flows and information important for the decision making process. The proposed model offers a way to efficiently leverage the new metering architecture and the new capabilities of the grid to reap immediate business value from the huge amounts of disparate data in emerging smart grids. The model was evaluated for the Serbian electricity market in the electric power transmission company Public Enterprise “Elektromreža Srbije”. The results show that business intelligence solutions can contribute to a more effective management of smart grids, in order to ensure that companies achieve sustainability in the increasingly competitive electricity markets, while still providing the high quality services to end users.

Description: In this paper we investigate some parallel variants of Broyden’s method and, for the basic variant, we present its convergence properties. The main result is that the behavior of the considered parallel Broyden’s variants is comparable with the classical parallel Newton method, and significantly better than the parallel Cimmino method, both for linear and nonlinear cases. The considered variants are also compared with two more recently proposed parallel Broyden’s method. Some numerical experiments are presented to illustrate the advantages and limits of the proposed algorithms.