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The article discusses an award given by the journal for the best paper on the subject of Information Technology in 2012, on the subject of governance of global Information Technology (IT) projects from a dynamic control perspective. The winning article presents an analysis of how Customer Relationship Management (CRM) can be made dynamic through the use of mobile telephones.

This paper introduces the ExaPRR Framework, which is capable of managing and controlling dynamic and interactive events in addition to activities related to distributed Published Resources Repository, managing and controlling dynamic and interactive events of the said resource discovery (RD) by redefining the concept of request and response based on wave model. For this purpose, while analyzing the function of the Distributed Published Resource Repository RD and defining the concept of the next element participating in the global activity in this RD, it redefines the concept of request in the Distributed Exascale systems. This framework uses the concept of revising the state of implementation of dynamic and interactive events in the system and redefining the concept of request at every moment of the process of implementation of resource discovery activities based on system status, demanding requests, and dynamic and interactive event, manages the resource's discovery activities. [ABSTRACT FROM AUTHOR]

Studies are actively ongoing for better understanding and strengthening the capabilities of researchers. To do so requires an accurate diagnosis and analysis of such researchers. Therefore, data of each researcher must be collected and be identified in a big-data environment. Consequently, researcher-name identification has emerged as an important issue. This paper proposes a framework for collecting, refining, identifying, and publicly offering researcher data. For identifying authors' name, the proposed framework extracts timeline based patterns that make help to identify the same name authors with their representative attributes such as emails and affiliations. The results of the proposed framework based on timeline patterns, show a 69.5 % average author-identification rate given a group of otherwise unidentified authors. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented in which the editors discuss an article on support tools for users of digital library, changes in web sites, and use of diffusion theory on the integration of online information in curriculum.

This paper includes country level virtual water data in an Environmental Kuznets Curve (EKC) for water pollution. Virtual water accounts for the total amount of water required to produce a good in all stages of production. This paper constructs a water independence index, defined as the water required in domestic production divided by the amount of water required for all imported goods. Results suggest an increase in trade openness and importing water intensive goods may lower water pollution levels. [ABSTRACT FROM AUTHOR]

This special issue of the International Journal of Digital Libraries evolved from the 13th Networked Knowledge Organization Systems (NKOSs) workshop held at the joint Digital Libraries conference 2014 in London. The focus of the workshop was 'Mapping between Linked Data vocabularies of KOS' and 'Meaningful Concept Display and Meaningful Visualization of KOS'. The issue presents six papers on the general theme on both conceptual aspects and technical implementation of NKOS. We dedicate this special issue to our long-term colleague and friend Johan De Smedt who died in June 2015 while we were editing the special issue. [ABSTRACT FROM AUTHOR]

This commentary discusses the consequences the shift from a paper-based world to a screen-centric world has for writers, teachers, and therapists. Whereas the case study was once composed for and stored on paper and its circulation thus restricted, now digital composing transforms the potential for the case study to circulate widely and freely via the World Wide Web. Moving the case study from paper to screen is not a question of reformatting; rather, it requires becoming literate in a new medium, one that offers the potential for ongoing collaborative revision and the development of participatory forms of knowledge production. [ABSTRACT FROM AUTHOR]

WeChat, both a location-based social network (LBSN) and an online social network (OSN), is an immensely popular application in China. In this paper we specifically focus on a popular WeChat sub-service, namely, the People Nearby service, which is exemplary of a find-and-flirt service, similar to those on Momo and Tinder. Specifically, the People Nearby service reads in the current geographic location of the device to locate a list of other people using WeChat who are in the same vicinity. The user can then request to establish a WeChat friendship relation with any of the users on the list. In this paper, we explore: (i) if one gender tends to use the People Nearby service more than another; (ii) if users of People Nearby are more anonymous than ordinary WeChat users; (iii) if ordinary WeChat users are more anonymous than Twitter users. We also take an in-depth examination of the user anonymity and demographics in a combined fashion and examine: (iv) if ordinary WeChat females are more anonymous than ordinary males; (v) if People Nearby females are more anonymous than People Nearby males. By answering these questions, we will gain significant insights into modern online dating and friendship creation, insights that should be able to inform sociologists as well as designers of future find-and-flirt services. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of clustering and re-ranking web image search results so as to improve diversity at high ranks. We propose a novel ranking framework, namely cluster-constrained conditional Markov random walk (CCCMRW), which has two key steps: first, cluster images into topics, and then perform Markov random walk in an image graph conditioned on constraints of image cluster information. In order to cluster the retrieval results of web images, a novel graph clustering model is proposed in this paper. We explore the surrounding text to mine the correlations between words and images and therefore the correlations are used to improve clustering results. Two kinds of correlations, namely word to image and word to word correlations, are mainly considered. As a standard text process technique, tf-idf method cannot measure the correlation of word to image directly. Therefore, we propose to combine tf-idf method with a novel feature of word, namely visibility, to infer the word-to-image correlation. By latent Dirichlet allocation model, we define a topic relevance function to compute the weights of word-to-word correlations. Taking word to image correlations as heterogeneous links and word-to-word correlations as homogeneous links, graph clustering algorithms, such as complex graph clustering and spectral co-clustering, are respectively used to cluster images into topics in this paper. In order to perform CCCMRW, a two-layer image graph is constructed with image cluster nodes as upper layer added to a base image graph. Conditioned on the image cluster information from upper layer, Markov random walk is constrained to incline to walk across different image clusters, so as to give high rank scores to images of different topics and therefore gain the diversity. Encouraging clustering and re-ranking outputs on Google image search results are reported in this paper. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editors discuss various reports within the issue on topics including wireless and mobile networks, the use of traffic engineering techniques in the Internet, and identity and privacy management in mobile networks.

The article discusses research articles on peer-to-peer (P2P) as an infrastructure service. Topics discussed include traffic management and content sharing in P2P systems, allocation of network resources based on P2P traffic planning, distributed P2P caching infrastructure, social cooperation in P2P services, and using advertisements as incentives in P2P media streaming systems.

This paper looks at a project that served to make Executive Fire Officer Applied Research Project papers as well as fire and emergency services-related periodical literature discoverable in the WorldCat search engine, the world's largest database of library materials. It examines why these resources are important to the fire community and explains the desirability of making them more readily visible to a wider audience. Integrating citations to the EFOP papers and periodical literature into WorldCat also led to other new developments at the US Fire Administration's library such as the implementation of the WorldCat Local search which affords users a wide variety of highly important research tools and enhancements including a more seamless and immediate means to search across the fire and emergency services domain of periodical literature and more. [ABSTRACT FROM AUTHOR]

Key Derivation is an important part of numerous security standards, the importance of using it was discussed throughout the literature and industry standards. On the other hand, web service security is an area that has not seen substantial research and application for Key Derivation techniques. After studying the Key Derivation techniques which are applied in Web Service Security, we find the applied algorithms and current implementations to be very limited in regard to performance and their work-flow. These limitations introduce performance bottlenecks that can limit their applicability to low power machines and mobile systems or lead to designers compromising on security to meet the quality of service desired. Moreover, this issue becomes more relevant when applied to a high performance and demanding systems such as real-time business process monitoring and messaging systems. This paper explores how Key Derivation is implemented in web services and WS-Security engines, their limitations, the performance overhead it produces and proposes an enhanced Key Derivation work-flow that takes into consideration both security and performance and allows for fine tuning them. The performance of the proposal is tested using a series of benchmarks and the security properties are verified using a well-known validation tool. [ABSTRACT FROM AUTHOR]

The article focuses on broken hyperlink references in research papers (reference rot) and methods to combat this problem. It states online archiving services like the Internet Archive and Harvard Law School Library's web-archiving service Perma allow researchers to store permanent copies of webpages as they viewed it when preparing manuscripts. It talks about the web archive project Memento which provides users access to all saved version of the web page and allow access to web-at-large links.

The article discusses some of the useful recommendations services for the researchers which would help them in locating the recent research papers and articles. Topics include options such as Google Scholar, Twitter, and Sparrho and experiences of academic researchers such as Casey Bergman, Ross Mounce, and Cassie Ettinger. Also discussed is search with keywords and filters for the scientists along with features of search engines such as PubChase and Scizzle.

For the internet of things (IoT) to fully emerge, it is necessary to design a suitable system architecture and specific protocols for this environment. The former to provide horizontal solutions, breaking away the current paradigm of silos solutions, and thus, allowing the creation of open and interoperable systems; while the latter will offer efficient and scalable communications. This paper presents the latest standards and ongoing efforts to develop specific protocols for IoT. Furthermore, this paper presents a new system, with the most recent standards for IoT. Its design, implementation and evaluation will be also described. The proposed system is based on the latest ETSI M2M specification (ETSI TC M2M in ETSI TS 103 093 V2.1.1. , 2013b) and the MQTT protocol (IBM, Eurotech in MQTT V3.1 Protocol Specification pp 1-42, , 2010). With this solution it is possible to show how we can create new applications to run over it and the importance of designing specifically tailored for IoT communication protocols in order to support real-time applications. [ABSTRACT FROM AUTHOR]

This paper focuses on the uplink channel accessing problem of multiple user multiple input multiple output (MU-MIMO) wireless local access networks (WLANs). The existing channel accessing mechanisms of MU-MIMO WLANs have poor performance in busy network environment due to heavy collisions, thus a novel channel accessing mechanism that based on request to send/clear to send (RTS/CTS) frames is proposed in this paper. Moreover, saturation throughput and average delay of MU-MIMO WLANs are also obtained through analytic model. Simulation results validate the accuracy of the proposed analytic model. And comparisons between the proposed RTS/CTS channel accessing mechanism and an existing channel accessing mechanism prove that the proposed mechanism performs much better especially in heavy network environment. [ABSTRACT FROM AUTHOR]

Since 1992 the Italian local health units (LHU) gained financial independence and became responsible to provide and deliver health care at the local level. Management and financial accounting represent the tool utilized to monitor their net income and the working capital every year. From 2001 on, LHU budget data have being summarized by means of the 'income statement'. The income statement is considered the most relevant form for the monitoring of healthcare expenditures. A big amount of data have been collected after that obligation of publishing the income statement. The application of new methods for a better understanding of relationships among variables would be worthwhile. The development of artificial neural networks (ANNs) can represent a useful tool to analyze the relationships among these variables. The purpose of this paper is showing the potentialities of ANNs and especially of artificial neural networks what-if theory (AWIT) model when applied to health budgetary data. This innovative methodology has been employed, in the present paper, to analyze data from five Italian Regions, carrying out some comparison among them. In short, using one dataset that is defined as being the ideal standard containing the relationships necessary to measure desired outcomes, another dataset can be compared to determine its degree of closeness. We can determine the degree of closeness of the second or treated dataset with the original standard. This is the key concept of the method called AWIT. The descriptive analysis carried out outlines the areas of waste LHU and suggests to develop strategies to contrast an inefficient use of resources. [ABSTRACT FROM AUTHOR]

Information about the 6th International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom) is presented. One paper described two broadcast authentication schemes such as key pool scheme and key chain scheme. Another paper introduced an analytical framework needed in the assessment of cooperative transmissions in sensor networks. Third paper focused on the development of utility-based routing scheme (UDR).

Emotion can be classified based on 2-dimensional valence-arousal model which includes four categories of emotional states, such as high arousal high valence, low arousal high valence, high arousal low valence, and low arousal low valence. In this paper, we present the attempt to investigate feature extraction of electroencephalogram (EEG) based emotional data by focusing on empirical mode decomposition (EMD) and autoregressive (AR) model, and construct an EEG-based emotion recognition method to classify these emotional states. We first employ EMD method to decompose EEG signals into several intrinsic mode functions (IMFs), and then the features are calculated from IMFs based on AR model using a sliding window, and finally we use these features to recognize emotions. The average recognition rate of our proposed method is 86.28% for 4 binary-class tasks on DEAP dataset. Experimental results show that our proposed method has a uniform and stable performance of emotion recognition, which are quite competitive with the results of methods of comparison. [ABSTRACT FROM AUTHOR]

Doors are a significant object for the visually impaired and robots to enter and exit buildings. Although the accuracy of door detection is reported high in indoor scenes, it has become a difficult problem in outdoor scenes in computer vision. The reason may lie in the fact that such properties of a simple ordinary door such as handles, corners, and the gap between the door and the ground may not be visible due to the great variety of doors in outdoor environments. In this paper, we present a vision-based method for detecting building entrances in outdoor images. After extracting the lines and deleting the extra ones, regions between the vertical lines are specified and the features including height, width, location, color, texture and the number of lines inside the regions are obtained. Finally, some additional knowledge such as door existence at the bottom of the image, a reasonable height and width of a door, the difference between color and texture of the doors and those of the neighboring regions, and numerous lines on doors is used to decide on door detection. The method was tested on the eTRIMS dataset, door images from the ImageNet dataset, and our own dataset including doors of houses, apartments, and stores leading to acceptable results. The obtained results show that our approach outperforms comparable state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

Aiming at the data unbalance of sensor nodes in the wireless sensor networks (WSN), this paper mainly studies the data gathering algorithm for linear WSNs. As the data amount varies from the time spent on data gathering of entire network minimal, it is a key factor to balance energy consumption and further prolong the network lifetime. Therefore, this paper proposes a TDMA scheduling algorithm for general k-hop networks, and takes detail performance analysis on the algorithm. Furthermore, we present the method of selecting the optimal hop-count and its formula as well as the formula of the number of timeslots required for converge-cast in order to maximize network lifetime. Finally, we obtain some general conclusions of network optimization based on the theoretical analysis and simulations. Compared with the 1-hop algorithm in (C. Florens and R. McEliece, Packets Distribution Algorithms for Sensor Networks, IEEE INFOCOM, San Diego, pp. 1063–1072, 2003), the TDMA scheduling algorithm for the general k-hop network proposed in our paper is more universal and has more practical application value. [ABSTRACT FROM AUTHOR]

This paper introduces a new wireless sensor network planning problem referred to as the Optimal Sensor Configuration (OSC) problem. In this problem, the goal is to find an optimal subset of locations where directional sensors and base stations are installed in order to minimize the total network cost while satisfying the requirements of coverage and connectivity. This goal is achieved by appropriately choosing the base station type and configuring each sensor to be installed in the sensor field. The optimal configuration of each sensor is determined by three parameters which are sensing range, field of view and orientation. The paper also gives an integer linear programming formulation of the OSC problem. The viability and effectiveness of the proposed formulation are illustrated through numerical results. [ABSTRACT FROM AUTHOR]

The article discusses the importance of the historical context of date of the publication of scientific research papers. It argues that when scientists understand the historical context of the origin of knowledge, science becomes richer and sited the study by A. Dinsmore and colleagues in 2002 and by S. J. Pickering in 1907 on colloidal particles as examples. It mentions that research students should be asked on the importance of the research on his they are studying. The authors states that the students should understand why the research authors have chosen the specific topic. They add that students overlook the studies published within the issue the source study due to the use of the internet.

The article focuses on the impact of Web-based homeworks compared to paper-based homeworks on students engaged in a finance course. It notes various studies which reveals that groups given web-based homeworks and paper-based homeworks showed no significant differences in student performance. According to the author, students who are Hispanics and are major in accounting prefer web-based homework while Anglo management major students prefer paper-based.

We present the rationale, the background and the structure for version 2.0 of the GENESTAT information portal (www.genestat.org) for statistical genetics. The fast methodological advances, coupled with a range of standalone software, makes it difficult for expert as well as non-expert users to orientate when designing and analysing their genetic studies. The ultimate ambition of GENESTAT is to guide on statistical methodology related to the broad spectrum of research in genetic epidemiology. GENESTAT 2.0 focuses on genetic association studies. Each entry provides a summary of a topic and gives links to key papers, websites and software. The flexibility of the internet is utilised for cross-referencing and for open editing. This paper gives an overview of GENESTAT and gives short introductions to the current main topics in GENESTAT, with additional entries on the website. Methods and software developers are invited to contribute to the portal, which is powered by a Wikipedia-type engine and allows easy additions and editing.European Journal of Human Genetics (2009) 17, 533–536; doi:10.1038/ejhg.2008.216; published online 12 November 2008 [ABSTRACT FROM AUTHOR]

Due to the increasing complexity of software systems, there is a growing need for automated and scalable software synthesis and analysis. In the last decade, active research in the formal methods community brought interesting results and valuable tools. However, there are still challenges to face and hard problems that need to be solved. We briefly outline some recent trends, and review some of the latest achievements, introducing six papers selected from the 20th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2014). [ABSTRACT FROM AUTHOR]

Probability of withdrawal is a feature of initial public offering (IPOs), which can be an important parameter in decisions of investors and issuers. Considering the probability of offering withdrawal facilitates more precise estimation of underpricing. In this paper, the effective factors on probability of IPO withdrawal and underpricing in Tehran Stock Exchange have been characterized using regression, and then neural network is applied to estimate the probability of IPO withdrawal and underpricing. To evaluate the performance of our applied method, fuzzy regression is employed and compared with neural network. According to the obtained empirical results, neural network demonstrates better accuracy than fuzzy regression. The results indicate that there is a meaningful relationship between underpricing and probability of withdrawal, and the probability of IPO withdrawal plays an important role in precise evaluation of underpricing. [ABSTRACT FROM AUTHOR]

Digital natives are now of age and comprise the new generation of early career teachers (ECTs). This is an important change in teacher demographics given that new technologies have been introduced into classrooms with expectations that teachers embed them effectively into the teaching of mathematics. This paper draws on the data of three separate studies and reanalyses it to explore how a small group of four early career primary school teachers use information and communication technologies (ICT) in their teaching of mathematics. Two of the ECTs were observed using interactive whiteboards in their mathematics teaching, and two were observed predominantly using tablets. Two important variables developed from the research presented in this paper suggest that ECT's uses of technology to teach mathematics may not be without complications. First, the teachers appeared to experience 'device conflict', in that the type of device and its particular affordances and limitations were the primary factors that influenced their mathematics. This was particularly evident in the uses of fixed and mobile devices. The interactive whiteboard (IWB) did not pose pedagogical challenges to the ECTs as their stable location facilitated the opportunity to still use these devices in traditional teaching ways. However, tablets did pose a problem because of their mobility and the need to reconfigure the organisation and to some extent the roles of teacher and student. The second finding was that the teachers' mathematical knowledge for teaching appeared to be directly related to the ways they used their technology. [ABSTRACT FROM AUTHOR]

With the emergence of professional online communities, professionals in the radiology field needed such technology to discuss and share radiographic images between each other. As medical communities rise, they suffer from semantic gap in the process of retrieving radiographic images. This paper presents The Radiologists Lounge, a professional online community specializing in connecting professionals in the radiology field. It has proposed the use of semantics in data retrieval and in structuring radiographic images, with the aim of retrieving these images on the basis of their semantic content. It is implemented using standard biomedical ontology known as the Unified medical Language System (UMLS). The primary goal of our study is to determine how well the Radiologist Lounge prototype functions as a semantic online community that retrieves images based on their semantic content. We study the performance of Radiologist Lounge measured in; indexing speed, retrieval speed, precision of results, recall of results and F-measure of results. Radiographic images are described on two conceptual layers; semantic and logical. The precision, recall and F-measure of retrieved results are measured on the different layers; logical, semantic, combination of logical and semantic. All results are later compared with the precision, recall and F-measure of the tradition tag-based retrieval. The paper describes the limitations of the Radiologist Lounge, ways to improve its performance, and increase its recall, precision and F-measure. [ABSTRACT FROM AUTHOR]

Effectiveness of local binary pattern (LBP) features is well proven in the field of texture image classification and retrieval. This paper presents a more effective completed modeling of the LBP. The traditional LBP has a shortcoming that sometimes it may represent different structural patterns with same LBP code. In addition, LBP also lacks global information and is sensitive to noise. In this paper, the binary patterns generated using threshold as a summation of center pixel value and average local differences are proposed. The proposed local structure patterns (LSP) can more accurately classify different textural structures as they utilize both local and global information. The LSP can be combined with a simple LBP and center pixel pattern to give a completed local structure pattern (CLSP) to achieve higher classification accuracy. In order to make CLSP insensitive to noise, a robust local structure pattern (RLSP) is also proposed. The proposed scheme is tested over three representative texture databases viz. Outex, Curet, and UIUC. The experimental results indicate that the proposed method can achieve higher classification accuracy while being more robust to noise. [ABSTRACT FROM AUTHOR]

The article focuses on the initiatives implemented by the Nature Publishing Group to the journal "Nature" to enhance the accessibility of the research papers it has published. Machine access is being enhanced by the open text-mining. Papers reporting full genome sequences are freely accessible on the group's Web sites from the moment of publication. The group also introduces a creative commons licence for the reuse of such genome papers that allows non-commercial publishers to reuse the pdf and html versions of the paper.

Air transportation is an important freight transport mode. Shipper behavior has important relationship with transport mode of goods. Based on this, the paper constructs a multi-attribute decision-making mode based on the choice of cargo transportation mode of risk preference. After dividing the weights, using ELECTRE-II algorithm solves the mode. And then the sequencing of several air transportation modes is obtained by selection and calculation of goods transportation mode from Chongqing to Shanghai. The calculation results show that decision mode and ELECTRE-II algorithm can make effective decision on the way of air transportation, and provide scientific basis for the choice of freight transport mode. [ABSTRACT FROM AUTHOR]

Logistics and distribution system is the foundation of rural commerce network. With the rapid development of computer technology and geographic information system (GIS) technology, constructing digital distribution system is an important direction for the development of computer technology. Based on the design idea of Flex Viewer in Flex, this paper designs a user-friendly route search algorithm based on ArcGIS API for Flex. On the basis of analyzing the implementation principle of ArcGIS Server’s tile map, a customized-naming-format tile map was obtained through the Flex communication technology (out of Arc GIS Server map service) and applied to the map demonstration for distribution route search. Finally, we tested the accuracy of the algorithm, load performance and real-time level. The test results met the design requirements. [ABSTRACT FROM AUTHOR]

Analysis of self-reflections of undergraduate education students in a project involving web-supported counterintuitive science demonstrations is reported in this paper. Participating students (N = 19) taught science with counterintuitive demonstrations in local elementary school classrooms and used web-based resources accessed via wireless USB adapters. Student reflections to seven questions were analyzed qualitatively using four components of reflection (meeting objectives/perception of learning, dynamics of pedagogy, special needs accommodations, improving teaching) deriving 27 initial data categories and 12 emergent themes. Overall the undergraduates reported meeting objectives, engaging students in pedagogically relevant learning tasks including, providing accommodations to students with special needs, and gaining practice and insight to improve their own teaching. Additional research is needed to arrive at generalizable findings concerning teaching with web-supported counterintuitive science demonstrations in elementary classrooms. [ABSTRACT FROM AUTHOR]

Due to the rapid increase in the speed as well as the number of users over the Internet, the rate of data generation is enormously grown. In addition, at the same rate, the multimedia transmission especially the usage of VoIP calls is rapidly growing due to its cost effectiveness, dramatic functionality over the traditional telephone network and its compatibility with public switched telephone network (PSTN). In most of the developing countries, internet service providers (ISPs) and telecommunication authorities are concerned in detecting such calls to either block or prioritize commercial VoIP. Signature-based, port-based, and pattern-based detection techniques are inaccurate due to the complex and confidential security and tunneling mechanisms used by VoIP. Therefore, in this paper, we proposed a generic, robust, efficient statistical analysis-based solution to identify encrypted and tunneled voice media flows. We extracted six statistical parameters, which are extracted for each flow and compared with threshold values while generating a number of rules to identify VoIP media calls. The paper also offers a complete architecture that can efficiently process high-speed traffic in order to detect VoIP flows at real-time. The proposed system, including the architecture and the algorithm, can be practically implemented in a real environment, such as ISP or telecommunication authority’s gateway. We implemented the system using the parallel environment of Hadoop ecosystem with Spark on the top of it to achieve the real-time processing. We evaluated the system by considering 1) the accuracy in terms of detection rate by computing the direct rate and false positive rate and 2) the efficiency in terms of processing power. The result shows that the system has 97.54% direct rate and.00015% false positive rate, which are quite high. The comparative study proved that the proposed system is more accurate than the existing techniques. [ABSTRACT FROM AUTHOR]

One of the major shortcomings of the Participatory Irrigation Management/Irrigation Management Transfer (PIM/IMT) programs undertaken in many countries of the world, is the predominant absence of Monitoring & Evaluation (M&E) systems specifically addressed to accompany these processes, and become a major instrument to correct, improve and learn. To contribute to closing this gap, this paper presents the main features of 'MONEVA', an M&E system tailored to PIM/IMT programs, and adapted to different Mediterranean Countries. The system is based on the principles of the Logical Framework Analysis (LFA), which permitted the development of objectives, outcomes, outputs and appropriate indicators for the monitoring of results. MONEVA is integrated with seven menus and many submenus which detailed description is reported in the embedded User's Manual. Only selected options are presented in this paper. The important and innovative features of MONEVA are its capacity to adapt to every country by using only the indicators relevant to the country, and a simple and objective system of evaluation. The results of its application in the pilot countries Jordan and Tunisia, i) demonstrated its flexibility to adapt to local contexts and the easiness of its application which supported its adoption, and ii) validated its characteristics as a Decision Support System (DSS), having a great potential for improving the implementation of the PIM/IMT programs, through the identification of their criticalities and thus, facilitating the definition of corrective actions at government and agency levels, but particularly, at the Water Users' Association (WUA) level. [ABSTRACT FROM AUTHOR]

Lately software based virtual mobile voice over Internet Protocol (VMVoIP) services have become available to end-users which may endanger profit of regular telephone operators from phone calls. In this situation, telephone operators should decide on a proper mechanism for interconnection with such VMVoIP operators which secures mutual benefit of both operators. In this paper, we study both monopolistic and oligopolistic markets of VMVoIP in which a single VMVoIP and several VMVoIP operators available in the market respectively. We model the interaction among a phone operator, VMVoIP operators and end-users as a leader-follower dynamic game and find a sub-game perfect Nash equilibrium (SPNE) for the game. The SPNE shows the phone operator's best pricing strategy (i.e., wholesale price for VMVoIP operators and retail price for end-users) and its best decision on the interconnection with VMVoIP operators. We further study economic interpretation of the SPNE. We show that in specific end-users' demands, the phone operator may increase its total profit by allowing the interconnection and taking right price discrimination strategy. [ABSTRACT FROM AUTHOR]

This paper proposes a host behavior based darknet traffic decomposition approach to identifying groups of malicious events from massive historical darknet traffic. In this approach, we segment traffic flows from captured darknet data, distinguish scan from non-scan flows, and categorize scans according to scan width spreads. Consequently, event groups are appraised by applying the criterion that malicious events generated by the same attacker or malicious software should have similar average packet delay, AvgDly. We have applied the proposed approach to 12 months darknet traffic data for malicious events grouping. As a result, several large scale event groups are discovered on host behavior in the category of port scan, IP scan and hybrid scan, respectively. [ABSTRACT FROM AUTHOR]

Cloud computing is an emerging technology and is being widely considered for resource utilization in various research areas. One of the main advantages of cloud computing is its flexibility in computing resource allocations. Many computing cycles can be ready in very short time and can be smoothly reallocated between tasks. Because of this, there are many private companies entering the new business of reselling their idle computing cycles. Research institutes have also started building their own cloud systems for their various research purposes. In this paper, we introduce a framework for virtual cluster system called vcluster which is capable of utilizing computing resources from heterogeneous clouds and provides a uniform view in computing resource management. vcluster is an IaaS (Infrastructure as a Service) based cloud resource management system. It distributes batch jobs to multiple clouds depending on the status of queue and system pool. The main design philosophy behind vcluster is cloud and batch system agnostic and it is achieved through plugins. This feature mitigates the complexity of integrating heterogeneous clouds. In the pilot system development, we use FermiCloud and Amazon EC2, which are a private and a public cloud system, respectively. In this paper, we also discuss the features and functionalities that must be considered in virtual cluster systems. [ABSTRACT FROM AUTHOR]

Adhesive joints are being used widely in engineering industries due to the increasing demand for designing lightweight structures. Because of the physical properties of the most adhesives, they creep even at room temperature. Therefore, the creep behavior of a single lap adhesive joint is studied in this paper. For this purpose, using the experimental data, creep constitutive equations for the adhesive has been obtained. Then, these equations have been employed to investigate the creep behavior of the joint. The results show that due to the creep straining, the stresses in the joint corners, decrease. However, creep strain accumulates in these areas which this in turn may lead to separation of adhesive from adherent. In order to eliminate the effect of strain accumulation, two modifying methods have been proposed in this paper: increasing the layer thickness and using filleted joints. [ABSTRACT FROM AUTHOR]

Developing new mathematical frameworks such as distributed dynamic routing algorithms for constructing optimal incremental paths from a node to another node is an important challenge in data communication networks. These new algorithms can model network resources optimally and increase network performances. A bundle of single routes in a current communication path, which starts from a source node and ends to a destination node, can consist of several successive nodes and links. The Incremental term emphasizes that the number of routes (links and nodes) in a current path can change so that achieving more data rate and optimal efficiency in the network. In this paper, our problem is to add/omit some routes consisting of some nodes and links to/from the current unicast path dynamically and optimally. We call this problem the Optimal Dynamic Distributed Unicast Routing (ODDUR) problem and it is a NP-complete problem. This problem can be formulated as a new type of Linear Programming Problem (LPP) for finding a minimum cost multichannel unicast path, which this path will minimize end-to-end delay and bandwidth consumption along the routes from the source node to the destination node. In this paper, at first a new mathematical framework will be constructed and then this framework will propose the new optimal dynamic distributed unicast routing algorithm for solving our LPP problem. This algorithm will compute an optimal solution for our LPP based on the simplex method and postoptimality computations and will reduce computations and consumed time. Simulation results will show that our new algorithm is more efficient than other available algorithms in terms of utilization of bandwidths and data rate. [ABSTRACT FROM AUTHOR]

3D building models of the world exhibit multi-scale properties. Different level-of-details (LoDs) are important for different applications. Therefore, generation of multi-scale representation of 3D building models to fulfill the demands of these applications is a generalization problem. In order to generalize 3D buildings, different pieces of information need to be preserved or removed to restrict the amount of data represented on a certain LoD. In this work, a three-step strategy based on simplification, aggregation and reconstruction of generalized buildings represented in City Geography Markup Language (CityGML) is proposed. The minimum length of edges (threshold value) for removal of amount of data is restricted to generalization specifications of CityGML characterized by differing accuracies and minimal dimensions of objects for each LoD. The main part of this paper is simplification of ground plans. For this purpose, a new approach is proposed to restrict number of edges, curves, and corners of ground plan of 3D building model on a certain LoD. Algorithms for simplification with the aim to derive LoD1 from exterior shells of buildings at LoD3 are implemented and tested on a number of buildings of Putrajaya city. The experiments showed that length of edge as threshold value is directly proportional to the size of generalized models. [ABSTRACT FROM AUTHOR]

Deduplication serves as a fundamental way to eliminate replicas and save space and network bandwidth in various storage systems. However, the performance of most existing deduplication systems can be further improved on normal reads, which carry crucial weight in currently popular WORM access model. Specifically, most existing deduplication systems achieve globally even layout via the simple round-robin algorithm and ignore the interrelationship between chunks and IO requests in the placement policy, thus failing to achieve the local even placement within a request and causing read imbalance problem. In this paper, we focus on deduplication over small-scale storage systems with adequate bandwidth in between and propose a deduplication system with request-aware placement policy named GLE-Dedup to achieve even placement both globally and locally for better read performance. Differing from conventional approaches of chunk-based placement, GLE-Dedup employs a group placement for chunks and the group size is mainly determined by the request ID to achieve request-awareness. We place chunks belonging to the same IO request into different independent nodes as much as possible to achieve even placement locally within a request and meanwhile maintain global balance with rotation among chunk groups. In this way, better parallelism is exploited for higher read performance. Experiment results under the real-world CAFTL trace have shown the effectiveness and advantage of GLE-Dedup over B-Dedup and R-Dedup respectively under round-robin and random placement. For example, our GLE-Dedup could achieve about 18.9 and 24 % read improvement respectively compared with B-Dedup and R-Dedup. [ABSTRACT FROM AUTHOR]

In this paper, we study using Destination Artificial Noise (DAN) besides Source Artificial Noise (SAN) to enhance physical layer secrecy with an outage probability based approach. It is assumed that all nodes in the network (i.e. source, destination and eavesdropper) are equipped with multiple antennas. In addition, the eavesdropper is passive and its channel state and location are unknown at the source and destination. In our proposed scheme, by optimized allocation of power to the SAN, DAN and data signal, a minimum value for the outage probability is guaranteed at the eavesdropper, and at the same time a certain level of signal to noise ratio at the destination is ensured. Our simulation results show that using DAN along with SAN brings a significant enhancement in power consumption compared to methods that merely adopt SAN to achieve the same outage probability at the eavesdropper. [ABSTRACT FROM AUTHOR]

A huge amount of sensing data are generated by a large number of pervasive IoT devices. In order to find meaningful information from the big data, it is essential to perform pre-processing, in which many outlier data points need to be removed, because they deteriorate as time passes. Although pre-processing is essential in the big data field, there has been a significant lack of research works with case studies. In this paper, big data pre-processing methods are investigated and proposed. To evaluate the pre-processing methods for accurate analysis, we used a collection of digital tachograph (DTG) data. We obtained DTG sensing data of 6198 driving vehicles over a year. We studied five kinds of pre-processing methods: filtering ranges, excluding meaningless values, comparing filters from variables, applying statistical techniques, and finding driving patterns. In addition, we developed a MapReduce program using a Hadoop ecosystem and deployed big data to perform the pre-processing analysis. Through the pre-processing steps, we confirmed that the proportion of DTG sensing data points including any errors was up to 27.09%. Compared to the traditional brute-force way to detect, ours had 71.1% additional detection effect. In addition, we confirmed that outlier data points, which are difficult to detect through simple range error pre-processing, could be well detected. [ABSTRACT FROM AUTHOR]

This paper presents the approach to functional test automation of services (black-box testing) and service architectures (grey-box testing) that has been developed within the MIDAS project and is accessible on the MIDAS SaaS. In particular, the algorithms and techniques adopted for addressing input and oracle generation, dynamic scheduling, and session planning issues supporting service functional test automation are illustrated. More specifically, the paper details: (i) the test input generation based on formal methods and temporal logic specifications, (ii) the test oracle generation based on service formal specifications, (iii) the dynamic scheduling of test cases based on probabilistic graphical reasoning, and (iv) the reactive, evidence-based planning of test sessions with on-the-fly generation of new test cases. Finally, the utilisation of the MIDAS prototype for the functional test of operational services and service architectures in the healthcare industry is reported and assessed. A planned evolution of the technology deals with the testing and troubleshooting of distributed systems that integrate connected objects. [ABSTRACT FROM AUTHOR]

Mobile health monitoring, which has been expected as an effective way to improve medical service quality, can monitor the medical users' real-time physiology parameters and the Emergency Response Support System (ERSS) is built up to deal with emergencies. Unfortunately, the information privacy of both the medical users and the healthcare service providers is at risk when their private information is uploaded to the health center. Especially, when emergencies happen, the privacy must be protected and the responding time of the system should not be compromised. In order to protect the privacy and also maintain high efficiency when an emergency occurs, this paper proposes a privacy-preserving based scheduling scheme for emergency response (PPSSER) system. The system can protect physiological data privacy, location privacy and personal attribute privacy. Also it can defend collusion attack. The simulation demonstrates the effectiveness and feasibility of the proposed scheme. [ABSTRACT FROM AUTHOR]

The popularity of GPS-equipped gadgets and mapping mashup applications has motivated the growth of geotagged Web resources as well as georeferenced multimedia applications. More and more research attention have been put on mining collaborative knowledge from mass user-contributed geotagged contents. However, little attention has been paid to generating high-quality geographical clusters, which is an important preliminary data-cleaning process for most geographical mining works. Previous works mainly use geotags to derive geographical clusters. Simply using one channel information is not sufficient for generating distinguishable clusters, especially when the location ambiguity problem occurs. In this paper, we propose a two-level clustering framework to utilize both the spatial and the semantic features of photographs for clustering. For the first-level geoclustering phase, we cluster geotagged photographs according to their spatial ties to roughly partition the dataset in an efficient way. Then we leverage the textual semantics in photographs' annotation to further refine the grouping results in the second-level semantic clustering phase. To effectively measure the semantic correlation between photographs, a semantic enhancement method as well as a new term weighting function have been proposed. We also propose a method for automatic parameter determination for the second-level spectral clustering process. Evaluation of our implementation on real georeferenced photograph dataset shows that our algorithm performs well, producing distinguishable geographical cluster with high accuracy and mutual information. [ABSTRACT FROM AUTHOR]