Search results for: context based recommendation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 12056

Search results for: context based recommendation

11966 Nuclear Data Evaluation for 217Po

Authors: Sherif S. Nafee, Amir K. Al-Ramady, Salem S. Shaheen

Abstract:

Evaluated nuclear decay data for the 217Po nuclide is presented in the present work. These data include recommended values for the half-life T1/2, α-, β-- and γ-ray emission energies and probabilities. Decay data from 221Rn α and 217Bi β—decays are presented. Q(α) has been updated based on the recent published work of the Atomic Mass Evaluation AME2012. In addition, the logft values were calculated using the Logft program from the ENSDF evaluation package. Moreover, the total internal conversion electrons and the K-shell to L-shell and L-shell to M-shell and to N-shell conversion electrons ratios K/L, L/M and L/N have been calculated using Bricc program. Meanwhile, recommendation values or the multi-polarities have been assigned based on recently measurement yield a better intensity balance at the 254 keV and 264 keV gamma transitions.

Keywords: Atomic Mass Evaluation, Nuclear Data Evaluation, Total Electron Conversion Electrons.

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11965 The Context-s Influence on the Evolution of Cioran: The Options of an Engaged Philosopher

Authors: Mara Magda Maftei

Abstract:

The article emphasizes the ideological commitment of the philosopher Emil Cioran. It presents firstly Cioran's works on the theme announced by the title, then the European context that determined the political option of Cioran and a brief analysis of his relationship with History during his French period. The anti- Semitism of Cioran was favored by his attachment to a few philosophers, but also by the European extremist and anti-Semitic context. The article seeks to demonstrate that the philosopher Cioran, known more for his pessimism and nihilism, maintained in time an obsessive relationship with History. His political philosophy is as important as his subjective philosophy, better known than the former.

Keywords: Cioran, French writings, History, Iron Guard

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11964 Corpus-Assisted Study of Gender Related Tiger Metaphors in the Chinese Context

Authors: Na Xiao

Abstract:

Animal metaphors have many different connotations, ranging from loving emotions to derogatory epithets, but gender expressions using animal metaphors are often imbalanced. Generally, animal metaphors related to females tend to be negative. Little known about the reasons for the negative expressions of animal female metaphors in Chinese contexts still have not been quantified. The study was based on the conceptual metaphor theory, and it used the Modern Chinese Corpus at the Center for Chinese Linguistics at Peking University (CCL Corpus) as a database, which identified the influencing variables of gender differences in the description of animal metaphors mapping humans in the Chinese context by observing the percentage of "tiger" metaphor. This study has proved that the tiger metaphors associated with humans in the Chinese context tend to be negative. Importantly, this study has also shown that the proportion of tiger metaphorical idioms that are related to women is very high. This finding can be used as crucial information for future studies on other gender-related animal metaphorical idioms and can offer additional insights for understanding trends in other animal metaphors.

Keywords: Chinese, CCL Corpus, gender differences, metaphorical idioms, tigers.

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11963 Trust Management for an Authentication System in Ubiquitous Computing

Authors: Malika Yaici, Anis Oussayah, Mohamed Ahmed Takerrabet

Abstract:

Security of context-aware ubiquitous systems is paramount, and authentication plays an important aspect in cloud computing and ubiquitous computing. Trust management has been identified as vital component for establishing and maintaining successful relational exchanges between trading partners in cloud and ubiquitous systems. Establishing trust is the way to build good relationship with both client and provider which positive activates will increase trust level, otherwise destroy trust immediately. We propose a new context-aware authentication system using a trust management system between client and server, and between servers, a trust which induces partnership, thus to a close cooperation between these servers. We defined the rules (algorithms), as well as the formulas to manage and calculate the trusting degrees depending on context, in order to uniquely authenticate a user, thus a single sign-on, and to provide him better services.

Keywords: Ubiquitous computing, context-awareness, authentication, trust management.

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11962 Shoplifting in Riyadh, Saudi Arabia

Authors: Saleh Dabil

Abstract:

the research was conducted using the self report of shoplifters who apprehended in the supermarket while stealing. 943 shoplifters in three years were interviewed right after the stealing act and before calling the police. The aim of the study is to know the shoplifting characteristics in Saudi Arabia, including the trait of shoplifters and the situation of the supermarkets where the stealing takes place. The analysis based on the written information about each thief as the documentary research method. Descriptive statistics as well as some inferential statistics were employed. The result shows that there are differences between genders, age groups, occupations, time of the day, days of the week, months, way of stealing, individual or group of thieves and other supermarket situations in the type of items stolen, total price and the count of items. The result and the recommendation will serve as a guide for retailers where, when and who to look at to prevent shoplifting.

Keywords: Shoplifting, stealing, theft, supermarket.

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11961 Fast Approximate Bayesian Contextual Cold Start Learning (FAB-COST)

Authors: Jack R. McKenzie, Peter A. Appleby, Thomas House, Neil Walton

Abstract:

Cold-start is a notoriously difficult problem which can occur in recommendation systems, and arises when there is insufficient information to draw inferences for users or items. To address this challenge, a contextual bandit algorithm – the Fast Approximate Bayesian Contextual Cold Start Learning algorithm (FAB-COST) – is proposed, which is designed to provide improved accuracy compared to the traditionally used Laplace approximation in the logistic contextual bandit, while controlling both algorithmic complexity and computational cost. To this end, FAB-COST uses a combination of two moment projection variational methods: Expectation Propagation (EP), which performs well at the cold start, but becomes slow as the amount of data increases; and Assumed Density Filtering (ADF), which has slower growth of computational cost with data size but requires more data to obtain an acceptable level of accuracy. By switching from EP to ADF when the dataset becomes large, it is able to exploit their complementary strengths. The empirical justification for FAB-COST is presented, and systematically compared to other approaches on simulated data. In a benchmark against the Laplace approximation on real data consisting of over 670, 000 impressions from autotrader.co.uk, FAB-COST demonstrates at one point increase of over 16% in user clicks. On the basis of these results, it is argued that FAB-COST is likely to be an attractive approach to cold-start recommendation systems in a variety of contexts.

Keywords: Cold-start, expectation propagation, multi-armed bandits, Thompson sampling, variational inference.

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11960 The Implications of Social Context Partisan Homogeneity for Voting Behavior: Survey Evidence from South Africa

Authors: C. Schulz-Herzenberg

Abstract:

Due to the legacy of apartheid segregation South Africa remains a divided society where most voters live in politically homogenous social environments. This paper argues that political discussion within one’s social context plays a primary role in shaping political attitudes and vote choice. Using data from the Comparative National Elections Project 2004 and 2009 South African post-election surveys, the paper explores the extent of social context partisan homogeneity in South Africa and finds that voters are not overly embedded in homogenous social contexts. It then demonstrates the consequences of partisan homogeneity on voting behavior. Homogenous social contexts tend to encourage stronger partisan loyalties and fewer defections in vote choice while voters in more heterogeneous contexts show less consistency in their attitudes and behaviour. Finally, the analysis shows how momentous sociopolitical events at the time of a particular election can change the social context, with important consequences for electoral outcomes.

Keywords: Political communication, social context, South Africa, voting behaviour.

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11959 Using Suffix Tree Document Representation in Hierarchical Agglomerative Clustering

Authors: Daniel I. Morariu, Radu G. Cretulescu, Lucian N. Vintan

Abstract:

In text categorization problem the most used method for documents representation is based on words frequency vectors called VSM (Vector Space Model). This representation is based only on words from documents and in this case loses any “word context" information found in the document. In this article we make a comparison between the classical method of document representation and a method called Suffix Tree Document Model (STDM) that is based on representing documents in the Suffix Tree format. For the STDM model we proposed a new approach for documents representation and a new formula for computing the similarity between two documents. Thus we propose to build the suffix tree only for any two documents at a time. This approach is faster, it has lower memory consumption and use entire document representation without using methods for disposing nodes. Also for this method is proposed a formula for computing the similarity between documents, which improves substantially the clustering quality. This representation method was validated using HAC - Hierarchical Agglomerative Clustering. In this context we experiment also the stemming influence in the document preprocessing step and highlight the difference between similarity or dissimilarity measures to find “closer" documents.

Keywords: Text Clustering, Suffix tree documentrepresentation, Hierarchical Agglomerative Clustering

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11958 Improving the Flexibility of Employment in Polish Economic Practice

Authors: A. Bodak, A. Cierniak-Emerych, M. Gableta, A. Pietroń-Pyszczek, K. Piwowar-Sulej

Abstract:

Modern organizations operate under the pressure of dynamic and often unpredictable changes, both in external and internal environment. Market success, in this context, requires a particular competence in the form of flexibility, interpreted here both on the level of individuals and on the level of organization. This paper addresses the changes taking place in the sphere of employment, as observed in economic entities operating on Polish market. Based on own empirical studies, the authors focus on the progressing trend of ‘flexibilization’ of employment, particularly in the context of transformations in organizational structure, designed to facilitate the transition into management by projects and differentiation of labor forms.

Keywords: Flexibility of employment, changes in organizational structure, forms of employment, social effects of flexibility.

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11957 Towards an Effective Reputation Assessment Process in Peer-to-Peer Systems

Authors: Farag Azzedin, Ahmad Ridha

Abstract:

The need for reputation assessment is particularly strong in peer-to-peer (P2P) systems because the peers' personal site autonomy is amplified by the inherent technological decentralization of the environment. However, the decentralization notion makes the problem of designing a peer-to-peer based reputation assessment substantially harder in P2P networks than in centralized settings.Existing reputation systems tackle the reputation assessment process in an ad-hoc manner. There is no systematic and coherent way to derive measures and analyze the current reputation systems. In this paper, we propose a reputation assessment process and use it to classify the existing reputation systems. Simulation experiments are conducted and focused on the different methods in selecting the recommendation sources and retrieving the recommendations. These two phases can contribute significantly to the overall performance due to communication cost and coverage.

Keywords: P2P Systems, Trust, Reputation, Performance.

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11956 Classifications of Neuroscientific-Radiological Findings on “Practicing” in Mathematics Learning

Authors: Felicitas Pielsticker, Christoph Pielsticker, Ingo Witzke

Abstract:

Many people know ‘Mathematics needs practice!’ statement or similar ones from their mathematics lessons. It seems important to practice when learning mathematics. At the same time, it also seems important to practice how to learn mathematics. This paper places neuroscientific-radiological findings on “practicing” while learning mathematics in a context of mathematics education. To accomplish this, we use a literature-based discussion of our case study on practice. We want to describe neuroscientific-radiological findings in the context of mathematics education and point out stimulating connections between both perspectives. From a connective perspective we expect incentives that lead discussions in future research in the field of mathematics education.

Keywords: fMRI, education, mathematics learning, practicing.

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11955 Enhanced Disk-Based Databases Towards Improved Hybrid In-Memory Systems

Authors: Samuel Kaspi, Sitalakshmi Venkatraman

Abstract:

In-memory database systems are becoming popular due to the availability and affordability of sufficiently large RAM and processors in modern high-end servers with the capacity to manage large in-memory database transactions. While fast and reliable inmemory systems are still being developed to overcome cache misses, CPU/IO bottlenecks and distributed transaction costs, disk-based data stores still serve as the primary persistence. In addition, with the recent growth in multi-tenancy cloud applications and associated security concerns, many organisations consider the trade-offs and continue to require fast and reliable transaction processing of diskbased database systems as an available choice. For these organizations, the only way of increasing throughput is by improving the performance of disk-based concurrency control. This warrants a hybrid database system with the ability to selectively apply an enhanced disk-based data management within the context of inmemory systems that would help improve overall throughput. The general view is that in-memory systems substantially outperform disk-based systems. We question this assumption and examine how a modified variation of access invariance that we call enhanced memory access, (EMA) can be used to allow very high levels of concurrency in the pre-fetching of data in disk-based systems. We demonstrate how this prefetching in disk-based systems can yield close to in-memory performance, which paves the way for improved hybrid database systems. This paper proposes a novel EMA technique and presents a comparative study between disk-based EMA systems and in-memory systems running on hardware configurations of equivalent power in terms of the number of processors and their speeds. The results of the experiments conducted clearly substantiate that when used in conjunction with all concurrency control mechanisms, EMA can increase the throughput of disk-based systems to levels quite close to those achieved by in-memory system. The promising results of this work show that enhanced disk-based systems facilitate in improving hybrid data management within the broader context of in-memory systems.

Keywords: Concurrency control, disk-based databases, inmemory systems, enhanced memory access (EMA).

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11954 The Usage of Social Networks in Educational Context

Authors: Sacide Güzin Mazman, Yasemin Koçak Usluel

Abstract:

Possible advantages of technology in educational context required the defining boundaries of formal and informal learning. Increasing opportunity to ubiquitous learning by technological support has revealed a question of how to discover the potential of individuals in the spontaneous environments such as social networks. This seems to be related with the question of what purposes in social networks have been being used? Social networks provide various advantages in educational context as collaboration, knowledge sharing, common interests, active participation and reflective thinking. As a consequence of these, the purpose of this study is composed of proposing a new model that could determine factors which effect adoption of social network applications for usage in educational context. While developing a model proposal, the existing adoption and diffusion models have been reviewed and they are thought to be suitable on handling an original perspective instead of using completely other diffusion or acceptance models because of different natures of education from other organizations. In the proposed model; social factors, perceived ease of use, perceived usefulness and innovativeness are determined four direct constructs that effect adoption process. Facilitating conditions, image, subjective norms and community identity are incorporated to model as antecedents of these direct four constructs.

Keywords: Adoption of innovation, educational context, social networks.

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11953 The Wheel Garden: Project-Based Learning for Cross Curriculum Education

Authors: Sherry S. Herron, Douglas Magomo, Paula Gossard

Abstract:

In this article, we discuss project-based learning in the context of a wheel garden as an instructional tool in science and mathematics education. A wheel garden provides multiple opportunities to teach across the curriculum, to integrate disciplines, and to promote community involvement. Grounded in the theoretical framework of constructivism, the wheel garden provides a multidisciplined educational tool that provides a hands-on, non-traditional arena for learning. We will examine some of the cultural, art, science, and mathematics connections made with this project.

Keywords: Art education, cross-curriculum instruction, multicultural education, project-based learning, school gardens, task based learning.

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11952 A Recommender Agent to Support Virtual Learning Activities

Authors: P. Valdiviezo, G. Riofrio, R. Reategui

Abstract:

This article describes the implementation of an intelligent agent that provides recommendations for educational resources in a virtual learning environment (VLE). It aims to support pending (undeveloped) student learning activities. It begins by analyzing the proposed VLE data model entities in the recommender process. The pending student activities are then identified, which constitutes the input information for the agent. By using the attribute-based recommender technique, the information can be processed and resource recommendations can be obtained. These serve as support for pending activity development in the course. To integrate this technique, we used an ontology. This served as support for the semantic annotation of attributes and recommended files recovery.

Keywords: Learning activities, educational resource, recommender agent, recommendation technique, ontology.

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11951 Learning Style and Learner Satisfaction in a Course Delivery Context

Authors: Paul David Henry

Abstract:

This paper describes the results and implications of a correlational study of learning styles and learner satisfaction. The relationship of these empirical concepts was examined in the context of traditional versus e-blended modes of course delivery in an introductory graduate research course. Significant results indicated that the visual side of the visual-verbal dimension of students- learning style(s) was positively correlated to satisfaction with themselves as learners in an e-blended course delivery mode and negatively correlated to satisfaction with the classroom environment in the context of a traditional classroom course delivery mode.

Keywords: Course delivery mode, e-blended, hybrid, learner satisfaction, learning style.

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11950 User-Based Cannibalization Mitigation in an Online Marketplace

Authors: Vivian Guo, Yan Qu

Abstract:

Online marketplaces are not only digital places where consumers buy and sell merchandise, and they are also destinations for brands to connect with real consumers at the moment when customers are in the shopping mindset. For many marketplaces, brands have been important partners through advertising. There can be, however, a risk of advertising impacting a consumer’s shopping journey if it hurts the use experience or takes the user away from the site. Both could lead to the loss of transaction revenue for the marketplace. In this paper, we present user-based methods for cannibalization control by selectively turning off ads to users who are likely to be cannibalized by ads subject to business objectives. We present ways of measuring cannibalization of advertising in the context of an online marketplace and propose novel ways of measuring cannibalization through purchase propensity and uplift modeling. A/B testing has shown that our methods can significantly improve user purchase and engagement metrics while operating within business objectives. To our knowledge, this is the first paper that addresses cannibalization mitigation at the user-level in the context of advertising.

Keywords: Cannibalization, machine learning, online marketplace, revenue optimization, yield optimization.

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11949 Educational Values of Virtual Reality: The Case of Spatial Ability

Authors: Elinda Ai-Lim Lee, Kok Wai Wong, Chun Che Fung

Abstract:

The use of Virtual Reality (VR) in schools and higher education is proliferating. Due to its interactive and animated features, it is regarded as a promising technology to increase students- spatial ability. Spatial ability is assumed to have a prominent role in science and engineering domains. However, research concerning individual differences such as spatial ability in the context of VR is still at its infancy. Moreover, empirical studies that focus on the features of VR to improve spatial ability are to date rare. Thus, this paper explores the possible educational values of VR in relation to spatial ability to call for more research concerning spatial ability in the context of VR based on studies in computerbased learning. It is believed that the incorporation of state-of-the-art VR technology for educational purposes should be justified by the enhanced benefits for the target learners.

Keywords: Ability-as-compensator, ability-as-enhancer, spatialability, virtual reality.

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11948 Board Members' Financial Education and Firms' Performance: Empirical Evidence for Bucharest Stock Exchange Companies

Authors: Mădălina Maria Gîrbină, Cătălin Nicolae Albu, Nadia Albu

Abstract:

After the accounting scandals and the financial crisis, regulators have stressed the need for more financial experts on boards. Several studies conducted in countries with developed capital markets report positive effects of board financial competencies. As each country offers a different context and specific institutional factors this paper addresses the subject in the context of Romania. The Romanian capital market offers an interesting research field because of the heterogeneity of listed firms. After analyzing board members education based on public information posted on listed companies websites and their annual reports we found a positive association between the proportion of board members holding a postgraduate degree in financial fields and market based performance measured by Tobin q. We found also that the proportion of Board members holding degrees in financial fields is higher in bigger firms and firms with more concentrated ownership.

Keywords: financial education, corporate governance, board

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11947 Proposition of a Knowledge Management Approach Based on the Cloud Computing

Authors: Imane Chikhi, Hafida Abed

Abstract:

The significant growth in the use of technologies in all life domains created numerous hurdles that derailed many knowledge management projects. Cloud computing choices are commencement to untangle these obstacles. Linking Cloud computing with knowledge management (KM) is a challenging task. Small amount of researches have been done regarding cloud computing and KM. In this paper, we consider Cloud-based KM as a new KM approach, and study the contribution of Cloud Computing to organizational KM. In fact, KM and cloud computing have many things in common, this similarity allows deriving very interesting features. Our approach is based on these features and focuses on the advantages of Cloud computing in the context of organizational KM. Finally, we highlight some challenges that have to be addressed when adopting a Cloud Computing approach to KM.

Keywords: Knowledge management, cloud computing, knowledge management approaches, cloud-based knowledge management.

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11946 Transform-Domain Rate-Distortion Optimization Accelerator for H.264/AVC Video Encoding

Authors: Mohammed Golam Sarwer, Lai Man Po, Kai Guo, Q.M. Jonathan Wu

Abstract:

In H.264/AVC video encoding, rate-distortion optimization for mode selection plays a significant role to achieve outstanding performance in compression efficiency and video quality. However, this mode selection process also makes the encoding process extremely complex, especially in the computation of the ratedistortion cost function, which includes the computations of the sum of squared difference (SSD) between the original and reconstructed image blocks and context-based entropy coding of the block. In this paper, a transform-domain rate-distortion optimization accelerator based on fast SSD (FSSD) and VLC-based rate estimation algorithm is proposed. This algorithm could significantly simplify the hardware architecture for the rate-distortion cost computation with only ignorable performance degradation. An efficient hardware structure for implementing the proposed transform-domain rate-distortion optimization accelerator is also proposed. Simulation results demonstrated that the proposed algorithm reduces about 47% of total encoding time with negligible degradation of coding performance. The proposed method can be easily applied to many mobile video application areas such as a digital camera and a DMB (Digital Multimedia Broadcasting) phone.

Keywords: Context-adaptive variable length coding (CAVLC), H.264/AVC, rate-distortion optimization (RDO), sum of squareddifference (SSD).

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11945 Information Filtering using Index Word Selection based on the Topics

Authors: Takeru YOKOI, Hidekazu YANAGIMOTO, Sigeru OMATU

Abstract:

We have proposed an information filtering system using index word selection from a document set based on the topics included in a set of documents. This method narrows down the particularly characteristic words in a document set and the topics are obtained by Sparse Non-negative Matrix Factorization. In information filtering, a document is often represented with the vector in which the elements correspond to the weight of the index words, and the dimension of the vector becomes larger as the number of documents is increased. Therefore, it is possible that useless words as index words for the information filtering are included. In order to address the problem, the dimension needs to be reduced. Our proposal reduces the dimension by selecting index words based on the topics included in a document set. We have applied the Sparse Non-negative Matrix Factorization to the document set to obtain these topics. The filtering is carried out based on a centroid of the learning document set. The centroid is regarded as the user-s interest. In addition, the centroid is represented with a document vector whose elements consist of the weight of the selected index words. Using the English test collection MEDLINE, thus, we confirm the effectiveness of our proposal. Hence, our proposed selection can confirm the improvement of the recommendation accuracy from the other previous methods when selecting the appropriate number of index words. In addition, we discussed the selected index words by our proposal and we found our proposal was able to select the index words covered some minor topics included in the document set.

Keywords: Information Filtering, Sparse NMF, Index wordSelection, User Profile, Chi-squared Measure

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11944 Understanding and Designing Situation-Aware Mobile and Ubiquitous Computing Systems

Authors: Kai Häussermann, Christoph Hubig, Paul Levi, Frank Leymann, Oliver Siemoneit, Matthias Wieland, Oliver Zweigle

Abstract:

Using spatial models as a shared common basis of information about the environment for different kinds of contextaware systems has been a heavily researched topic in the last years. Thereby the research focused on how to create, to update, and to merge spatial models so as to enable highly dynamic, consistent and coherent spatial models at large scale. In this paper however, we want to concentrate on how context-aware applications could use this information so as to adapt their behavior according to the situation they are in. The main idea is to provide the spatial model infrastructure with a situation recognition component based on generic situation templates. A situation template is – as part of a much larger situation template library – an abstract, machinereadable description of a certain basic situation type, which could be used by different applications to evaluate their situation. In this paper, different theoretical and practical issues – technical, ethical and philosophical ones – are discussed important for understanding and developing situation dependent systems based on situation templates. A basic system design is presented which allows for the reasoning with uncertain data using an improved version of a learning algorithm for the automatic adaption of situation templates. Finally, for supporting the development of adaptive applications, we present a new situation-aware adaptation concept based on workflows.

Keywords: context-awareness, ethics, facilitation of system use through workflows, situation recognition and learning based on situation templates and situation ontology's, theory of situationaware systems

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11943 A Framework for Identifying the Critical Factors Affecting the Decision to Adopt and Use Inter-Organizational Information Systems

Authors: K. Bouchbout, Z. Alimazighi

Abstract:

The importance of inter-organizational system (IOS) has been increasingly recognized by organizations. However, IOS adoption has proved to be difficult and, at this stage, why this is so is not fully uncovered. In practice, benefits have often remained concentrated, primarily accruing to the dominant party, resulting in low rates of adoption and usage, and often culminating in the failure of the IOS. The main research question is why organizations initiate or join IOS and what factors influence their adoption and use levels. This paper reviews the literature on IOS adoption and proposes a theoretical framework in order to identify the critical factors to capture a complete picture of IOS adoption. With our proposed critical factors, we are able to investigate their relative contributions to IOS adoption decisions. We obtain findings that suggested that there are five groups of factors that significantly affect the adoption and use decision of IOS in the Supply Chain Management (SCM) context: 1) interorganizational context, 2) organizational context, 3) technological context, 4) perceived costs, and 5) perceived benefits.

Keywords: Business-to-Business relationships, buyer-supplier relationships, Critical factors, Interorganizational Information Systems, IOS adoption and use.

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11942 System Survivability in Networks in the Context of Defense/Attack Strategies: The Large Scale

Authors: A. Ben Yaghlane, M. N. Azaiez, M. Mrad

Abstract:

We investigate the large scale of networks in the context of network survivability under attack. We use appropriate techniques to evaluate and the attacker-based- and the defenderbased- network survivability. The attacker is unaware of the operated links by the defender. Each attacked link has some pre-specified probability to be disconnected. The defender choice is so that to maximize the chance of successfully sending the flow to the destination node. The attacker however will select the cut-set with the highest chance to be disabled in order to partition the network. Moreover, we extend the problem to the case of selecting the best p paths to operate by the defender and the best k cut-sets to target by the attacker, for arbitrary integers p,k>1. We investigate some variations of the problem and suggest polynomial-time solutions.

Keywords: Defense/attack strategies, large scale, networks, partitioning a network.

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11941 Towards a UTAUT-based Model for the Study of EGovernment Citizen Acceptance in Saudi Arabia

Authors: Alzahrani.M.E, Goodwin.R.D

Abstract:

Among the most fundamental prerequisites for the successful development of electronic Government Services (e- Government) is Citizen Acceptance. Based on the UTAUT model, the paper describes a hypothetical framework that integrates the unique features of E- government to improve our understanding of the acceptance and usage of e-Government Saudi Arabia. The proposed model, based on UTAUT, includes the characteristics of Egovernment, consideration and inclusion of trust, privacy, and Saudi culture and context.

Keywords: E-government, technology adoption, citizen acceptance, unified theory of acceptance and use of technology (UTAUT).

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11940 A Recommender System Fusing Collaborative Filtering and User’s Review Mining

Authors: Seulbi Choi, Hyunchul Ahn

Abstract:

Collaborative filtering (CF) algorithm has been popularly used for recommender systems in both academic and practical applications. It basically generates recommendation results using users’ numeric ratings. However, the additional use of the information other than user ratings may lead to better accuracy of CF. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's review can be regarded as the new informative source for identifying user's preference with accuracy. Under this background, this study presents a hybrid recommender system that fuses CF and user's review mining. Our system adopts conventional memory-based CF, but it is designed to use both user’s numeric ratings and his/her text reviews on the items when calculating similarities between users.

Keywords: Recommender system, collaborative filtering, text mining, review mining.

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11939 JENOSYS: Application of a Web-Based Online Energy Performance Reporting Tool for Government Buildings in Malaysia

Authors: Norhayati Mat Wajid, Abdul Murad Zainal Abidin, Faiz Fadzil, Mohd Yusof Aizad Mukhtar

Abstract:

One of the areas that present an opportunity to reduce the national carbon emission is the energy management of public buildings. To our present knowledge, there is no easy-to-use and centralized mechanism that enables the government to monitor the overall energy performance, as well as the carbon footprint, of Malaysia’s public buildings. Therefore, the Public Works Department Malaysia, or PWD, has developed a web-based energy performance reporting tool called JENOSYS (JKR Energy Online System), which incorporates a database of utility account numbers acquired from the utility service provider for analysis and reporting. For test case purposes, 23 buildings under PWD were selected and monitored for their monthly energy performance (in kWh), carbon emission reduction (in tCO₂eq) and utility cost (in MYR), against the baseline. This paper demonstrates the simplicity with which buildings without energy metering can be monitored centrally and the benefits that can be accrued by the government in terms of building energy disclosure and concludes with the recommendation of expanding the system to all the public buildings in Malaysia.

Keywords: Energy-efficient buildings. energy management systems, government buildings, JENOSYS.

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11938 Analysis of Energy Consumption Based on Household Appliances in Jodhpur, India

Authors: A. Kumar, V. Devadas

Abstract:

Energy is the basic element for any country’s economic development. India is one of the most populated countries, and is dependent on fossil fuel and nuclear-based energy generation. The energy sector faces huge challenges and is dependent on the import of energy from neighboring countries to fulfill the gap in demand and supply. India has huge setbacks for efficient energy generation, distribution, and consumption, therefore they consume more quantity of energy to produce the same amount of Gross Domestic Product (GDP) compared to the developed countries. Technology and technique use, availability, and affordability in the various sectors are varying according to their economic status. In this paper, an attempt is made to quantify the domestic electrical energy consumption in Jodhpur, India. Survey research methods have been employed and stratified sampling technique-based households were chosen for conducting the investigation. Pre-tested survey schedules are used to investigate the grassroots level study. The collected data are analyzed by employing statistical techniques. Thereafter, a multiple regression model is developed to understand the functions of total electricity consumption in the domestic sector corresponding to other independent variables including electrical appliances, age of the building, household size, education, etc. The study resulted in identifying the governing variable in energy consumption at the household level and their relationship with the efficiency of household-based electrical and energy appliances. The analysis is concluded with the recommendation for optimizing the gap in peak electrical demand and supply in the domestic sector.

Keywords: Appliance, consumption, electricity, households.

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11937 Context-aware Recommender Systems using Data Mining Techniques

Authors: Kyoung-jae Kim, Hyunchul Ahn, Sangwon Jeong

Abstract:

This study proposes a novel recommender system to provide the advertisements of context-aware services. Our proposed model is designed to apply a modified collaborative filtering (CF) algorithm with regard to the several dimensions for the personalization of mobile devices – location, time and the user-s needs type. In particular, we employ a classification rule to understand user-s needs type using a decision tree algorithm. In addition, we collect primary data from the mobile phone users and apply them to the proposed model to validate its effectiveness. Experimental results show that the proposed system makes more accurate and satisfactory advertisements than comparative systems.

Keywords: Location-based advertisement, Recommender system, Collaborative filtering, User needs type, Mobile user.

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