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The Learning Analytics and Knowledge (LAK) Dataset represents an unprecedented corpus which exposes a near complete collection of bibliographic resources for a specific research discipline, namely the connected areas of Learning Analytics and Educational Data Mining. Covering over five years of scientific literature from the most relevant conferences and journals, the dataset provides Linked Data about bibliographic metadata as well as full text of the paper body. The latter was enabled through special licensing agreements with ACM for publications not yet available through open access. The dataset has been designed following established Linked Data pattern, reusing established vocabularies and providing links to established schemas and entity coreferences in related datasets. Given the temporal and topic coverage of the dataset, being a near-complete corpus of research publications of a particular discipline, it facilitates scientometric investigations, for instance, about the evolution of a scientific field over time, or correlations with other disciplines, what is documented through its usage in a wide range of scientific studies and applications. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including information technology (IT) services management (ITSM) and engineering, IT service support process engineering, and IT governance decision-making support framework.

OBJECTIVE: This paper aims at proposing a new framework for the classification of RFID deployments in fashion and apparel retailing. The framework encompasses several different use cases (UCs) pursued by fashion and apparel retailers in the last decade, and updates, expands and goes beyond what has already been presented in the related literature. DESIGN, METHODOLOGY, APPROACH: We carried out a comprehensive literature review on RFID deployments in fashion and apparel retail. We searched different sources of information, that is, scientific papers, conferences and seminars proceedings, websites, magazines, newspapers etc., up to 160 papers that were carefully analysed and organised in a structured database. This data set also comprehends information from confidential projects. We analyse contents on the level of single RFID projects, that is, feasibility studies, proofs of concept, pilots or deployments. For each project, we determine what specific UCs were at stake. Eventually, the framework of all possible RFID UCs emerged from the analysis, and we set up a panel of industry partners to validate the framework using the Delphi method. FINDINGS:We structured the new framework along two levels: first, 6 categories were identified (i.e., level 1 use cases). Each category was then detailed, resulting in a total of 18 specific UCs (i.e., level 2 use cases). Each level 2 UC corresponds to a very specific objective pursued by an RFID implementation. For each UC, we propose a set of business metrics to evaluate deployment success as well as benefits achieved. PRACTICAL IMPLICATIONS: From a practitioner's perspective, the framework offers a comprehensive and well-structured overview of the cost- and the revenue-related potentials of RFID implementations in the industry. Researchers, on the other hand, may use the framework to identify opportunities for further research regarding RFID deployments in retailing. ORIGINALITY/VALUE: Our framework is based on the current body of literature, and complements prior studies, which served as the starting point for our research. [ABSTRACT FROM AUTHOR]

The world wide web has two main forms of architecture, the first is that which is explicitly encoded into web pages, and the second is that which is implied by the web content, particularly pertaining to look and feel. The latter is exemplified by the concept of a website, a concept that is only loosely defined, although users intuitively understand it. The Website Boundary Detection (WBD) problem is concerned with the task of identifying the complete collection of web pages/resources that are contained within a single website. Whatever the case, the concept of a website is used with respect to a number of application domains including; website archiving, spam detection, and www analysis. In the context of such applications it is beneficial if a website can be automatically identified. This is usually done by identifying a website of interest in terms of its boundary, the so called WBD problem. In this paper seven WBD techniques are proposed and compared, four statistical techniques where the web data to be used is obtained apriori, and three dynamic techniques where the data to be used is obtained as the process progresses. All seven techniques are presented in detail and evaluated. [ABSTRACT FROM AUTHOR]

According to daily scientific research and communication needs of the author's laboratory, the author puts forward a system for providing a unified platform for daily management and record of scientific research. The system contains records of daily reports, papers, patents, projects and multimedia files storage function. Compared with existing laboratory systems, the system focuses on needs of graduate students in laboratory, replaces equipment management and fund management of traditional laboratory for daily reporting and scientific research of graduate students in laboratory. The system is built on cloud platform. There are two innovations in this system. Firstly, the perspective of this paper is professional laboratory for postgraduate students. A set of systems are set to meet demands of graduate students in laboratory, which are different and at the same time have common points, so as strengthen communication between teachers and students and strengthen exchange among students, as well as improve the quality of postgraduate training. Secondly, as the system is applied in a number of laboratories, they have common features. Therefore, this system conforms to the development trend of technology, and the combination of cloud computing technology becomes preliminary exploration for the development of laboratory management system. [ABSTRACT FROM AUTHOR]

There has been a growing concern regarding political disengagement among citizens within liberal western representative democracies. This concern has brought about calls for local political online forums to be used to support participatory and deliberative democracy online to reverse this trend. However, little empirical investigation has been conducted into what such forums can support in terms of deliberative democracy. This paper, focusing solely on deliberation will answer the following question: Can local political online forums support all categories of deliberation? A two pronged methodological approach consisting of both a quantitative deductive method and a qualitative inductive method was used to examine this research question. This paper argues that within the literature deliberation falls into three main categories. However, another form of online discussion was identified as part of this empirical research named Cross Cutting Discussion. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented in which the editor discusses various reports within the issue including the access to WikiLeaks, the important aspect of Freedom of Information, and the record management in the local government.

Copyright of Informatica is the property of IOS Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents an intelligent support of decision making to improve security analysis called Adast. The adopted approach in this research is based on acquiring and reusing past accident scenarii, historically validated on other homologated transport systems. The advantage of this approach, based primarily on Case-Based Reasoning (CBR) and ontologies, lies not only on the capitalization of knowledge from experience feedback, but also on benefit in order to provide assistance to domain experts in their crucial task of analyzing and improving security. Also, the problems of knowledge and case representation are considered in this paper. A prototype of intelligent decision support system based on Adast has been implemented to better integrate the proposed CBR cycle and ontology. [ABSTRACT FROM AUTHOR]

This paper describes a scenario-based methodology called the NeOn Methodology framework. The aim of this framework is to speed up the construction of ontologies and ontology networks by reusing available knowledge resources (ontologies, non-ontological resources and ontology design patterns). The methodology is founded on four pillars: (1) a glossary of processes and activities; (2) a set of nine scenarios for building ontologies and ontology networks; (3) two ontology life-cycle models; and (4) a set of prescriptive methodological guidelines for performing specific processes and activities. The paper also shows how to apply this methodology framework to develop an ontology network within the multimedia domain. Finally, it presents an empirical evaluation of the NeOn Methodology framework. [ABSTRACT FROM AUTHOR]

The RDF collections and containers is one of the most used features by RDF technicians and practitioners. Although some work has been published in past, there is not a standard and accepted way for defining collections within OWL DL frameworks. Here, we attempt to address this issue with the introduction of the Collections Ontology (CO) version 2.0. CO is an OWL 2 DL ontology developed for creating sets, bags and lists of resources, and for inferring collection properties even in the presence of incomplete information. [ABSTRACT FROM AUTHOR]

In this paper we discuss the issues related to the formal representation of thematic roles in an ontology modeling historical events. We start by analyzing the ontological distinctions between thematic roles and social roles, which suggest different formal representations. Coupling the study of existing approaches with an analysis of historical texts - available within the Harlock'900 project - we propose a formal representation of thematic roles in HERO (Historical Event Representation Ontology), based on binary properties, directly connecting the event to its participants. Moreover, we show that a fine-grained formal ontological model of participation in (historical) events should include general thematic roles (e.g., agent, patient) - able to capture the common aspects of the ways entities are involved in events - and event-specific roles (e.g., sniper), introduced in the ontology according to a specific criterion, that guarantees the needed expressivity without proliferating roles. We conclude the paper by discussing the benefits of our approach. [ABSTRACT FROM AUTHOR]

In this study, a questionnaire on learning preferences was administered to students who were enrolled in e-learning courses offered by the collaborative project among several higher education institutions and we extracted factors in learning preferences. A strong correlation between the factor loadings (the preference for asynchronous learning and the one for the use of ICT) and the adaptability to e-learning courses was found. As a result of multiple regression analyses, it was found that, to some extent, we could predict the student's adaptability to an e-learning course by measuring his/her preferences for asynchronous learning and the use of ICT. Furthermore, based on these analyses, the paper discusses an effective e-learning system that offers learning courses and learning objects that are suitable for particular students. [ABSTRACT FROM AUTHOR]

Recently, the number of digital content objects is increasing rapidly with the progress of information technology. It has become important how we manage enormous digital content objects effectively and utilize them efficiently. Up to now, a lot of researches on digital content management have been reported. One of the important objectives of conventional management techniques is to search digital content objects that satisfy an information request of a user. This is based on the assumption that a user has one or more information requests. However, a user may have no information request explicitly when the user uses some kinds of devices for presenting digital content such as a digital photoframe. Such devices are expected to provide a presentation of digital content that rouses user's interest. In this paper, we introduce an approach for composing photo slideshow that attracts user's interest automatically. [ABSTRACT FROM AUTHOR]

Identity Federation enables Users to effectively manage their multiple Identities spread across different administrative domains. It leverages trust between the Identity Providers to allow Users to federate and share their Identity information to receive cross-domain Identity benefits. In this paper, we argue that with increasing number of VoIP providers as well as the ability for Users to host and self-manage their own VoIP Identities, an Identity Federation-based solution is required for VoIP as well. The paper analyzes differences for Identity Federation within VoIP scenarios, as compared to existing Web-based scenarios. We propose the VoIP Identity Federation Framework, enabling a User to establish Identity Federation as well as the assertion of any relevant Identity information from one VoIP context to another. The framework is designed using simple application-usage agnostic primitives viz. federate-out and federate-in, which can be applied within any VoIP Protocol scenario. One of the primary design goals has been to model these enablers as an independent protocol, so that they can be piggybacked on any of the existing VoIP protocol scenarios. As a result, Identity Federation benefits can be easily applied to any existing or future VoIP-based application usages. Another important aspect is to enable sufficient User control within the Identity Federation framework. We also present a set of exemplary yet novel use-cases enabled by the proposed framework. [ABSTRACT FROM AUTHOR]

This paper proposes an improvement to the TCP startup procedure in large bandwidth-delay networks. Current TCP congestion control algorithms may lead to the premature termination of the slow-start phase, resulting in an under-utilization of network resources and a corresponding degradation of the network performance. Consequently, this paper develops an algorithm which estimates the network conditions during the startup phase and rapidly expands the congestion window to match the available bandwidth. The simulation results confirm that the proposed TCP startup procedure improves the throughput of the modified TCP connection while remaining fair to other active TCP implementations in terms of bandwidth consumption. [ABSTRACT FROM AUTHOR]

In this paper we introduce a method to measure the social importance of an agent in a multiagent system, using a directed graph representing dependencies among agents to achieve their goals, so-called dependence graphs pioneered by Castelfranchi, Conte and Sichman. Our measure is derived from van den Brink and Gilles' β-measure to rank agents, using a directed graph representing an abstract dominance relation among agents. In particular, we show how to define power structures and dependence networks from the goals and skills of individual agents, and how to adapt the β-measure for such dependence networks based on their topological properties. Moreover, we show that our notion of social importance can be given an intuitive meaning: it measures the discontent of the other agents in case the agent would leave the society. [ABSTRACT FROM AUTHOR]

The paper proposes enhanced algorithms for two of the three basic steps in Low Earth Orbit (LEO) satellite network routing: the downlink routing and the inter-satellite links (ISLs) routing. In this study we refer to polar/near-polar constellations and to connectionless routing protocols such as the ones based on the Internet Protocol (IP). In particular a downlink routing procedure is proposed that does not exploit any external localization system to identify the position of the destination mobile terminal. In addition, an ISL routing algorithm is proposed that improves the one based on the minimization of the number of hops, by reducing the overall path length of the connection and, hence, the end-to-end delay. The improved algorithms are evaluated in terms of system performance and computational burden. At the price of a neglectable increase in the computational complexity, a significant improvement in the end-to-end delay is achieved by using the proposed algorithm, when the source and the destination interface are largely spaced in latitude and longitude, with a consequent benefit on the overall LEO network efficiency. [ABSTRACT FROM AUTHOR]

Large scale networks such as computational Grid is a distributed computing infrastructure that can provide globally available network resources. Their size and complexity continue to increase and permit an almost ubiquitous availability of resources; users become able to access network resources irrespective to their location. Therefore, new resource management and access models are required and need to be highly flexible with self-organizing capabilities in order to cope with a dynamically changing environment. In this paper, a distributed and adaptive holonic multi-agent system for resource discovery in Grids is presented. Simulations are presented to demonstrate that structuring servers into holons improves the performance of request resolution processes in dynamic Grid environment. [ABSTRACT FROM AUTHOR]

The extensive amount of diversified Web-based information necessitates the development of automated subject-specific Web site classification techniques. Given that Web sites are in essence heterogeneous, multi-structured and often accompanied with much noise, it is important to design Web site classification algorithms that can scale well in the context of noise and heterogeneity. In this paper, we propose a novel approach for Web site classification based on the content, structure and context information of Web sites. In our approach, the site structure is represented as a two-layered tree, i.e., each page is modeled as a DOM (Document Object Model) tree, and a page tree is used to hierarchically link all pages within the site. Two context models are formulated to characterize the topical dependences between nodes in the two-layered tree. Using the Hidden Markov Tree (HMT) as the statistical model of page trees and DOM trees, a two-phase Web site classification algorithm is presented. Moreover, for further improving accuracy while reducing the classification overheads, a two-stage denoising procedure is adopted to remove the noise information within sites, and an entropy-based strategy is introduced to dynamically prune the page trees. The experiments demonstrate that the proposed approach is able to offer high accuracy and efficient processing performance. [ABSTRACT FROM AUTHOR]

In this paper we present an implementation-based comparison of Measurement-based Admission Control algorithms. Through the use of a special purpose environment, a performance and behaviour comparison is made. The results of this paper illustrate the independence of traffic from admission control behaviour in the homogeneous traffic environment. While illustrating the impact the admission decision will make upon heterogenous traffic systems. These results highlight the importance of estimators being robust to statistical variation in measurements and offering calibrated controls. While based upon a comparison of measurement-based admission control algorithms - these conclusions are applicable to any application of measurement-based estimation. [ABSTRACT FROM AUTHOR]

Speech recognition can give people with severe disabilities more control over their personal environments. For people with physical disabilities affecting the use of their hands, productivity is far more personal. Speech recognition can enable some people to perform daily living tasks without assistance. For others, such as the growing number of professionals afflicted with repetitive stress syndrome (RSI), speech recognition represents a means of getting or keeping employment. Thus speech recognition as a navigation aid is a key in solving the dilemma of a subset of disabled surfers. This paper reviews the technologies currently available for speech interaction with computers and suggests how the future of web navigation may benefit from these technologies. The paper also discusses the results obtained from evaluation of a prototype website catering to users with a disability. The results of the evaluation by local health board officials indicated a positive response to the Voice Navigable website and aided recommendations for future work. [ABSTRACT FROM AUTHOR]

This paper discusses the provision of Internet-based distance learning courses in the LIS field and aims to investigate not only what courses are available, but also to assess the current market situation for online courses. It has relevance for departments interested in the provision of online distance learning courses and is also valuable for students interested in online courses, particularly LIS courses. The key observations from the research are that online education ranges from short self-instruction courses to degree-level programmes. And although provision of online education appears to be increasing, evidence was found for fewer than 10 online distance learning degree programmes in the LIS field. Areas of apparent expansion are short online courses offered by commercial consortia and non-traditional universities. This research is inevitably not an exhaustive search of the entire World Wide Web, but a 'snapshot' of what is currently available during the research period (April-June 2000). [ABSTRACT FROM AUTHOR]

As the size of websites continues to grow, current research focuses on the development of intelligent websites which facilitate the browsing by providing a navigation aid to the website users. Web page recommendation systems provide suggestions to the website users about the webpages that may be of concern to them by evaluating the collective navigation behavior of previous website users. The main motive of this study was to explore the utilization of partially ordered sequential rules (POSR) in making future predictions for website users. Sequential rules provide the association between the events that occur in a particular sequence. In this paper, two sequential rule mining algorithms, namely TRuleGrowth and CMRules have been separately used to generate sequential rules. Then the sequential rules were used to make predictions about the future interests of the users regarding webpages. The experimental results on a real life dataset have revealed that the rules generated by TRuleGrowth algorithm were able to make predictions with higher accuracy than those generated by CMRules algorithm. [ABSTRACT FROM AUTHOR]

Automatic computer-aided diagnosis (CAD) systems have been widely used in classification of patients who suffer from Alzheimer's disease (AD). This paper presents an automatic CAD system based on histogram feature extraction from single-subject gray matter similarity-matrix for classifying the AD patients from healthy controls (HC) using structural magnetic resonance imaging (MRI) data. The proposed CAD system is composed of five stages. In the first stage, segmentation is employed to perform pre-processing on the MRI images, and segment into gray matter, white matter, and cerebrospinal fluid using the voxel-based morphometric toolbox procedure. In the second stage, gray matter MRI scans are used to construct similarity-matrices. In the third stage, a novel statistical feature-generation process is proposed, utilizing the histogram of the individual similarity-matrix to represent statistical patterns of the respective similarity-matrices of different size and order into fixed-size feature-vectors. In the fourth stage, we propose to combine MRI measures with a neuropsychological test, the Functional Assessment Questionnaire (FAQ), to improve the classification accuracy. Finally, the classification is performed using a support vector machine and evaluated with the 10-fold cross-validation strategy. We evaluated the proposed method on 99 AD and 102 HC subjects from the J-ADNI. The proposed CAD system yields an 84.07% classification accuracy using MRI measures and 97.01% for combining MRI measures with FAQ scores, respectively. The experimental results indicate that the performance of the proposed system is competitive with respect to state-of-the-art techniques reported in the literature. [ABSTRACT FROM AUTHOR]

As the age of open data and data visualization arrives, the Statistics Bureau of Japan and the National Statistics Center of Japan have released a new geostatistics web service. Called jSTAT MAP, the web service can aggregate data and produce choropleth maps based on small area statistics, whether they may be census data or users' own data. jSTAT MAP has expanded horizons for the integration of statistical and geospatial information and acquired a new statistical user base in Japan. This paper describes the key elements of jSTAT MAP and reports on the impact it has brought about on statistical users. [ABSTRACT FROM AUTHOR]

Abstract. Present distributed applications are not typically designed to adapt to changes in network conditions. In addition, network-based adaptation does not typically consider the requirements of specific applications and, therefore, may take actions contradictory to application's needs. This paper presents a cooperative solution in which a configurable communication layer is used to adapt communication in response to both application requirements and network resource availability. Adaptation decisions are based on (1)payoff functions which capture the application requirements in a functional form, and (2) service availability curves which represent network resource availability. Experimentation with multimedia applications and a variable reliability protocol demonstrates the benefit of using payoff-based adaptation. [ABSTRACT FROM AUTHOR]

Discusses about the issues involved in the discussion of who should provide electronic journal archives and where and how they are constructed. Developments of electronic publications; Defining electronic archives; Issues involved in electronic archiving; Library perspectives and considerations concerning electronic archiving.

Nowadays, secret keys of networked devices are profoundly attacked by power analysis attacks, caused by the dramatic evolution of statistical analysis with a simple experimental setup. Recently, OpenSSL and CoreBitcoin running on Android and iOS have been broken by power analysis. Moreover, sensors and actuators can also be attacked thereby threatening user's privacy and security. To resolve these challenges, power-analysis-resistant implementations of cryptographic algorithms in networked devices have received a lot of attentions. Masking schemes have been developed to implement secure cryptographic algorithms against side-channel analysis (SCA) attacks. Technically, the firstorder masking method is vulnerable to the second order differential power analysis (2ODPA) attacks, but the current solutions against 2ODPA are expensive to be implemented. Moreover, worse performance will be shown if the cryptographic algorithms include boolean and arithmetic operations. In this paper, we propose a new countermeasure scheme to resist SCA attacks. Our scheme randomizes all the intermediate values of block cipher by encoding functions in the algorithm to lookup table and makes it resistant to power analysis attack. We apply our scheme to the block cipher algorithm, HIGHT. Our protected implementation of HIGHT takes only 1.79 times compared to the straightforward algorithm, and it needs 25 kbytes to store lookup tables in memory. [ABSTRACT FROM AUTHOR]

Crowdsourcing techniques provide effective means for solving a variety of ontology engineering problems. Yet, they are mainly used as external support to ontology engineering, without being closely integrated into the work of ontology engineers. In this paper we investigate how to closely integrate crowdsourcing into ontology engineering practices. Firstly, we show that a set of basic crowdsourcing tasks are used recurrently to solve a range of ontology engineering problems. Secondly, we present the uComp Protégé plugin that facilitates the integration of such typical crowdsourcing tasks into ontology engineering from within the Protégé ontology editor. An evaluation of the plugin in a typical ontology engineering scenario where ontologies are built from automatically learned semantic structures, shows that its use reduces the working times for the ontology engineers 11 times, lowers the overall task costs by 40% to 83% depending on the crowdsourcing settings used and leads to data quality comparable with that of tasks performed by ontology engineers. Evaluations on a large anatomy ontology confirm that crowdsourcing is a scalable and effective method: good quality results (accuracy of 89% and 99%) are obtained while achieving cost reductions of 75% from the ontology engineer costs and providing comparable overall task duration. [ABSTRACT FROM AUTHOR]

Named Data Network (NDN) has various routing and forwarding strategies, but most of which have failed to achieve the ability of Quality-of-Service (QoS), such as high resource consumption and low transmission efficiency. Leveraged by antcolony optimization (ACO), a QoS-supported routing forwarding strategy is proposed in this paper to address those problems. Specifically, the proposed strategy is able to consistently select a route which meets the QoS requirement and optimal routing strategy is realized in NDN network. Experimental results show that the proposed routing strategy outperforms the random forwarding strategy in terms of average delay, costs, and packet loss rate in NDN. [ABSTRACT FROM AUTHOR]

Copyright of Informatica is the property of IOS Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The national information communications technology (ICT) industry association (popularly known as PIKOM) in collaboration with the largest online job recruitment service provider, namely Jobstreet.com, has been publishing salary profile of ICT professionals in Malaysia annually since 2006. The series has been publishing average salary of ICT professionals by industry, job category, employment size, geographical locations and top paying industry. The online job registration system that Jobstreet.com biannually updates constituted the data source for the statistical activity. The reported data are of high quality as there is an inherent tendency for jobseekers to furnish accurate information in search of new jobs or career advancements. The past series also demonstrated consistency and stability in data trends that official statistics is equally concerned about. Not only private sector, the mainstream policy and planning agencies also have become vivid user of PIKOM data, in particular ICT salary records at three digit occupation and five digit industry levels. Typically such levels of data dissemination are not feasible under national sample surveys. More importantly, the ICT salary data are published as official statistics in the Digital Economy Satellite Account (DESA) system that consolidates all ICT data in the country including private sector initiatives. As next level collaboration, the paper also discusses big data analytics (BDA) targeted at semi-structured and unstructured data that the online job registration system entails. [ABSTRACT FROM AUTHOR]

Data about Amsterdam are widely available. Two important sources are the municipal website of the Bureau for Research and Statistics {www.os.amsterdam.nl} and the Open Data platform which contained 326 datasets at the start of 2014 [1]. This paper examines which policy goals are met with the products based on open data provided by the City of Amsterdam. We also conduct a survey among the citizens of Amsterdam to see if they use the apps and internet sites. Finally, we compare the characteristics of the first products that use open data with the objectives of the open data movement in Amsterdam, i.e. economic growth, internal efficiency and external transparency. [ABSTRACT FROM AUTHOR]

Extracting semantic polarity of Chinese Multiword Expression, especially some newly generated Multiword Expression from internet(such as weibo or microblog), is an important task for sentiment analysis of web texts or other real word text as some Multiword Expressions can express more integrative sentiments than words units. This paper proposes a method that contains a novel latent discriminative algorithm, which attempts to attack this problem by integrating discriminative model and latent value model. Although Chinese Multiword Expressions consist of multiple words, the semantic polarity of the Multiword Expression is not just simple integration of polarities of the component words, as some words can invert the affective polarity so the Multiword Expressions can have totally opposite semantic polarity, such as ironic texts. In order to capture the property of such Multiword Expressions, hidden semi-CRF which includes a latent valuable layer, which can be used to address dual-sequence labeling tasks synchronously, is adopted. The method is tested experimentally by adopting a manually labeled set of positive and negative Multiword Expressions from microblog or other internet resources, and the experiments have shown very promising results, which is comparable to the best value ever reported. [ABSTRACT FROM AUTHOR]

Computer support for crisis management is today mostly focused on immediate emergency and rescue operations, while there are few all-in-one systems capable of deploying support to decision making processes in state administration and at international level. The paper presents the concept of a Hybrid Decision Support System for Crisis Management (HDSSCM) which is an intelligent platform providing direct support for crisis decision makers. The idea has been developed with a view to, firstly, demonstrating the potential inherent in systems that would be able to address a wide range of emergency response operations, and secondly, to outlining a system architecture proposal. The discussion is placed in the context of Poland's crisis management system. Specific parameters of polish system represents both an inspiration and an underpinning for the proposed intelligent platform. The authors also describe some recent applications and current trends in the area of crisis/disaster management systems. [ABSTRACT FROM AUTHOR]

This paper describes the Atlante Sintattico d'Italia, Syntactic Atlas of Italy (ASIt) linguistic linked dataset. ASIt is a scientific project aiming to account for minimally different variants within a sample of closely related languages; it is part of the Edisyn network, the goal of which is to establish a European network of researchers in the area of language syntax that use similar standards with respect to methodology of data collection, data storage and annotation, data retrieval and cartography. In this context, ASIt is defined as a curated database which builds on dialectal data gathered during a twenty-year-long survey investigating the distribution of several grammatical phenomena across the dialects of Italy.Both the ASIt linguistic linked dataset and the Resource Description Framework Schema (RDF/S) on which it is based are publicly available and released with a Creative Commons license (CC BY-NC-SA 3.0). We report the characteristics of the data exposed by ASIt, the statistics about the evolution of the data in the last two years, and the possible usages of the dataset, such as the generation of linguistic maps. [ABSTRACT FROM AUTHOR]

Universal, effective, fair, and consistent methods for evaluating faculty scholarly activities have remained elusive for years. This research utilized the Analytic Hierarchy Process (AHP) to assess the professoriate's own perceptions of the appropriate assessment of faculty research. The paper also incorporated the Boyer model of scholarship as one of the main criteria for scholarship evaluation. We addressed the "how" and "how much" in the weighting of scholarship output based on a survey of faculty at five Canadian teaching-intensive universities. The surprising lack of weighting value assigned to the Scholarship of Teaching and Learning, and the overall structure of the AHP model present interesting results. [ABSTRACT FROM AUTHOR]

Resource allocation in cloud computing is an optimization problem that determines the allocation of computer and network resources of service providers to requested services of users for meeting user service requirements. A distributed cloud computing environment for IT services requires resource allocation in a decentralized manner through the coordination of service providers and service users. Achieving the optimal solution of service planning through the decentralized service provider-user coordination remains as a challenge. This paper looks into elements of service provider-user coordination first in the formulation of the resource allocation problem in a centralized manner and then in the formulation of the problem in a decentralized manner for various problem cases. By examining differences between the centralized, optimal solutions and the decentralized solutions for those problem cases, the analysis of how the decentralized service provider-user coordination breaks down the optimal solutions is performed. Based on this analysis, strategies of decentralized service provider-user coordination are developed. [ABSTRACT FROM AUTHOR]

A collaborative and knowledge sharing virtual activity on Second Life using a learner-centred teaching methodology was initiated between Temasek Polytechnic and The Hong Kong Polytechnic University (HK PolyU) in the October 2011 semester. This paper highlights the author's experience in designing and implementing this e-learning activity and incorporating it into the curriculum of the Diploma in Interactive Media Informatics at Temasek Polytechnic, Singapore. Students from Temasek Polytechnic and HK PolyU met up at Temasek Polytechnic Island and HK PolyU campus on Second Life and networked amongst themselves using Avatars and interactive 3D objects. Students from both institutions worked in groups to share and exchange knowledge through experiential learning, knowledge sharing and teamwork in a virtual environment. At the end of the module, two online self-reported surveys were conducted to get students' feedback on the effectiveness of the subject delivery and teaching methods. The survey results indicate that Second Life has positive effects on students' learning, motivation and attitudes towards learning. The interactive 3D environment within Second Life promotes learner-centered teaching by enabling learning to be more engaging, fun and interesting, thus increasing students' motivation to learn and develop their abilities to acquire relevant problem solving skills and knowledge. [ABSTRACT FROM AUTHOR]

Obligations are an essential element of security policies since they enable the specification of many security requirements such as availability, privacy, usage control and data protection. In everyday life, the fulfillment of obligations is often the responsibility of more than one subject, e.g., 'All patients must be checked by one of the doctors'. Obligations may also be fulfilled in different ways, e.g., 'Every customer should pay either in cash or by check'. Current security policy languages do not enable the specification of these intuitive and much needed requirements. In this paper, we show how policy languages can be extended to support the specification of these requirements which we call group obligations. To clarify the semantics of group obligations, we introduce state-based models for both group and individual obligations and show how group obligations can be managed according to change in the state of individual obligations. We formalize the semantics of the model and interactions between individual and group obligations by introducing a policy-enforcement language ℒE. ℒE enables the formal description of the application domain and the policy and provides operational semantics for policy management. Moreover, we discuss termination and determinism of policy enforcement in the proposed framework and show how different sanction/reaction policies may be activated when group obligations are violated. [ABSTRACT FROM AUTHOR]

E-Governance is the application of information and communication technology (ICT) for delivering government services, exchange of information and communication between government and public. Government services are made available to the citizens in a convenient, efficient and transparent manner through e-Governance. E-Government is a means for governments to use the most innovative ICTs through electronic networks with more convenient access to government information and services. The objective of this paper is to present how public participation is significant to enhance quality government services and need of ethical issues on e-Government practices and for formation of good governance. The current study is review of various literatures relating to e-government, public participation for e-governance, challenges and ethical issues. The key benefits of e-Governance include efficiency, improved services, better accessibility of public services, and transparency. The e-governance requires a considerable increase in regulation and policy making abilities, with all the expertise and opinion-shaping processes. [ABSTRACT FROM AUTHOR]

Interest in the application of computer vision techniques to automatic video-based analysis of traffic is high at present. This is due in part to the capabilities of video sensors, as well as to social demands for traffic safety. In general, these systems are cheaper and less disruptive than other kinds of devices like loop detectors for traffic monitoring. Automatic traffic surveillance is, however, still a challenging problem when we consider many of the practical difficulties involved (i.e. limited number of cameras and positions of these with respect to the scene, variable illumination and weather conditions, intrinsic complexity of analyzed traffic events, need for a real-time frame rate processing, among others). In this paper, we propose a multi-level framework for automatic analysis of complex traffic videos which present different kind of variations. The accurate and efficient extraction of relevant scene information from the video frames is performed in a hierarchical bottom-up form using the system presented. First of all, foreground moving pixels are detected in each frame using a proposed method of adaptive background subtraction. After that, these pixels are grouped into blobs if they share some common properties. Blobs detected in predefined scene entry regions are identified as vehicles and these are tracked along the controlled road area. At the upper level, some traffic monitoring statistics and also related linguistic reports on the evolution of traffic in the scene are generated periodically. Experimental results on the adaptive background method proposed, as well as regarding its integration in the multi-level traffic analysis system, are very satisfactory for the traffic videos analyzed. [ABSTRACT FROM AUTHOR]

Intelligent Environments are currently mostly implemented with WSN technologies using conventional connectionbased communications. However, connection-based communications may impede progress towards intelligent environments involving massive amounts of sensor nodes. The goal of this paper is to chart a field of more suitable technologies for communication in intelligent environments, which we call collective transmission methods. The idea of collective transmission is to establish communication not between single senders and single receivers but between collectives of senders and receivers, by making use of constructive interference of simultaneously sent signals. We detail how the collective transmission approach can be realized for a concrete application scenario: item-level tagging using printed organic electronics. We describe an algorithm that can be realized on very simple tags. With a testbed implementation, we show that this algorithm can realize robust, collective, approximate read-out of 21 simultaneously sent signals. [ABSTRACT FROM AUTHOR]

Many scientific workflow applications are driven by simulation generated data, or data collected from sensors or instruments, and the processing of the data is commonly done at a different location from where the data is stored. Moving large quantities of data among different locations is thus a frequently invoked process in scientific workflow applications. These data transfers often have high quality requirements on the network services, especially when the application requires steering from human interaction. Advanced networks such as hybrid networks make it feasible for high level applications to request network paths and service provisioning. However, current workflow applications tune the execution quality neglecting network resources, and by selecting only optimal software services and computing resources. Including network services in the resource scheduling adds an extra dimension for workflow applications to optimize the runtime performance. In this paper we present a system called NEtwork aware Workflow QoS Planner (NEWQoSPlanner) to complement existing workflow systems on selecting network resources in the context of workflow composition, scheduling and execution when advanced network services are available. [ABSTRACT FROM AUTHOR]

The internet is now an important element of most political parties' communication strategies during elections. While online communication might be claimed to enable smaller parties and marginal voices to compete more effectively with major parties, it might also enable minority languages to challenge the existing dominance of majority languages in traditional political communication. This paper explores Welsh-language provision on the websites of the 18 parties which fielded candidates in Wales during the 2010 UK General Election. Three websites making bilingual provision are examined in greater detail, considering the Welsh-language experience in terms of information seeking tasks, the use of web2.0 and resource generation. Overall the provision of regional information relating to Wales and of Welsh-language material has remained remarkably static since the last General Election in 2005. It appears that only parties which regularly contest seats in Wales make regional provision and that Welsh-language provision is limited to those parties who have websites specifically orientated to Wales. The Welsh language does not appear to have been a priority in terms of online political communication for most of the parties campaigning in Wales during the General Election. Even on those sites making a bilingual provision, the quality, timeliness and extent of the Welsh-language experience varied considerably. [ABSTRACT FROM AUTHOR]

Independent studies have shown that mobile government (M-Government) can have an important influence on business and society in the future. Hence, network designers, service providers, government and application developers must carefully take the needs and considerations of various users into account to provide better services and attract them to M-Government Consequently, identifying the M-Government user requirements and their significance becomes an essential and crucial process for the standardization and improvement of associated systems. On this line, the objective of this paper is to propose a requirements model as a result of quantitative and qualitative methods, this model provide practitioners a more effective and efficient model for prioritizing M-Government user requirements. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the current XML-related courses available in 96 LIS schools in South East Asia and Taiwan's 9 LIS schools. Also, this study investigates the linkage of library school graduates in Taiwan who took different levels of XML-related education (that is XML arranged as an individual course or XML arranged as a section unit in courses) and their professional qualification. Research questions include what is the availability of XML-related courses in countries in Taiwan and South East Asia? What are Taiwan LIS graduates' views on degree of XML-related courses satisfaction, cognition of learning XML technology, and views of XML-related courses? What is the linkage of Taiwan LIS graduates who studied different levels of XML-related education and their professional qualifications? This study applies 3 research methodologies: information gathering from the internet; questionnaire surveys; in-depth interviews. Results of the analysis show that LIS schools should provide optional XML-related courses with practical sessions, and library associations should provide regular XML-related continuing education to enhance LIS students' professional qualifications. [ABSTRACT FROM AUTHOR]

Several recent studies have explored the virtues of behavioral targeting and personalization for online advertising. In this paper, we add to this literature by proposing a cost-effective methodology for the prediction of demographic website visitor profiles that can be used for web advertising targeting purposes. The methodology involves the transformation of website visitors' clickstream patterns to a set of features and the training of Random Forest classifiers that generate predictions for gender, age, level of education and occupation category. These demographic predictions can support online advertisement targeting (i) as an additional input in personalized advertising or behavioral targeting, or (ii) as an input for aggregated demographic website visitor profiles that supportmarketingmanagers in selecting websites and achieving an optimal correspondence between target groups and website audience composition. The proposed methodology is validated using data from a Belgian web metrics company. The results reveal that Random Forests demonstrate superior classification performance over a set of benchmark algorithms. Further, the ability of the model set to generate representative demographic website audience profiles is assessed. The stability of the models over time is demonstrated using out-of-period data. [ABSTRACT FROM AUTHOR]