bluuebunny/crossref_metadata_2025 huggingface dataset:
An Enterprise Ontology Based Conceptual Modeling Grammar for Representing Value Chain and Supply Chain Scripts
Authors: Laurier Wim , Poels Geert
Published: December 2015

In business modeling the focus is shifting from individual enterprises to the supply chains in which they collaborate. Contemporary business modeling grammars should allow each enterprise taking part in a supply chain to develop its own information system and at the same time support the creation of system interoperability and information sharing amongst business partners in the supply chain. This paper presents a conceptual modeling grammar for representing business scripts in a way that is both observer-dependent and independent. That is, value chain information should be represented in a format that is suitable for the perspective of any partner in the supply chain (e.g., enterprise, supplier, customer, customer's customer, supplier's supplier) and for the perspective of a completely neutral third party (e.g., government). The proposed observer-independent conceptual-modeling grammar, which is given strength by grounding it in the mature Resource-Event-Agent model, is shown to represent information about business phenomena of diverse supply chain partners such that it can be integrated across enterprise boundaries
Competitive Advantage and Automated Sharing of Tacit Knowledge
Authors: Chilton Michael A. , Bloodgood James M.
Published: December 2015

In this chapter, the authors investigate how raw data, obtained from a variety of sources, can be processed into knowledge using automated techniques that will help organizations gain a competitive advantage. Firms have amassed so much data that only automated methods, such as data mining or converting existing knowledge into expert systems is possible to make any sense of it or to protect it from competitors. Further, the data that is processed may be considered tacit knowledge because it is hidden from people until it is processed. In this chapter, the authors discuss various sources of data that might help an organization achieve and sustain a competitive advantage. A firm can data mine its own production database for insight regarding its customers and markets that have previously been ignored. It might also mine social media (e.g., Facebook and Twitter), which has become a forum for individual preferences and activities from which the savvy organization could turn into competitive advantage. They also discuss how this knowledge can be protected from intrusion by competitors to sustain the competitive position it may achieve as a result of the discovery of knowledge from massive data sets.
Rules Extraction using Data Mining in Historical Data
Authors: Kumar Manish , Srivastava Shashank
Published: December 2015

Rules are the smallest building blocks of data mining that produce the evidence for expected outcomes. Many organizations like weather forecasting, production and sales, satellite communications, banks, etc. have adopted this mode of technological understanding not for the enhanced productivity but to attain stability by analyzing past records and preparing a rule-based strategy for the future. Rules may be extracted in different ways depending on the requirements and the dataset from that has to be extracted. This chapter covers various methodologies for extracting such rules. It presents the impact of rule extraction for the predictive analysis in decision making.
A Perturbation Method Based on Singular Value Decomposition and Feature Selection for Privacy Preserving Data Mining
Authors: Keyvanpour Mohammad Reza , Moradi Somayyeh Seifi
Published: December 2015

In this study, a new model is provided for customized privacy in privacy preserving data mining in which the data owners define different levels for privacy for different features. Additionally, in order to improve perturbation methods, a method combined of singular value decomposition (SVD) and feature selection methods is defined so as to benefit from the advantages of both domains. Also, to assess the amount of distortion created by the proposed perturbation method, new distortion criteria are defined in which the amount of created distortion in the process of feature selection is considered based on the value of privacy in each feature. Different tests and results analysis show that offered method based on this model compared to previous approaches, caused the improved privacy, accuracy of mining results and efficiency of privacy preserving data mining systems.
Alignment of Knowledge Sharing Mechanism and Knowledge Node Positioning
Authors: Chu Mei-Tai , Khosla Rajiv
Published: December 2015

As the organizational memory in terms of collective knowledge evolves, how to construct an effective knowledge sharing mechanism to covert individual knowledge into collective knowledge becomes fairly demanding. CoPs approach is widely accepted as effective mechanism to facilitate knowledge sharing. Knowledge nodes in the context of knowledge flow, unlike workflow, can often transcend organizational boundaries and are distinct and different than workflow models. This paper aims to develop, implement, and analyze a CoPs Centered knowledge flow model in a multinational organization. This model is underpinned in a CoPs framework built around four expected performance including four dimensions and sixteen criteria as a comprehensive mechanism to intensify knowledge sharing effect. Next, this study clusters knowledge workers/nodes with common criteria (attitudes and beliefs) towards this model. These common attitudes and beliefs between two knowledge workers/nodes imply that knowledge sharing among them is likely to be more effective than between knowledge workers/nodes with dissimilar attitudes and beliefs. Fuzzy Multi-Criteria Decision Making MCDM) and cluster analysis techniques are adopted as research methods. A Dynamic knowledge flow activity analysis model is also defined as part of future work.
A Hybrid Analysis of E-Learning Types and Knowledge Sharing Measurement Indicators
Authors: Qorbani Davood , Vanani Iman Raeesi , Sohrabi Babak , Forte Peter
Published: December 2015

E-learning as a method of effective transference of knowledge is being widely used. This chapter introduces a conceptual model that shows administrators/directors of e-learning environments how to recognize and utilize different sets of knowledge sharing indicators (a combination of individual, social, organizational, and technical indicators) to enhance the quality of learning in e-learning environments. A model in which different types of e-learning can be employed is introduced and elaborated. Then, several knowledge-sharing indicators that have the potential of facilitating and enhancing the e-learning environment are presented. Finally, the conceptual model of knowledge sharing indicators to facilitate different types of e-learning environments is provided and discussed.
The Role of Knowledge Sharing on Organisational Innovation
Authors: Kasemsap Kijpokin
Published: December 2015

This chapter introduces the framework and causal model of organisational learning, knowledge management, knowledge-sharing behaviour, and organisational innovation. It argues that dimensions of organisational learning, knowledge management, and knowledge-sharing behaviour have mediated positive effect on organisational innovation. Knowledge-sharing behaviour positively mediates the relationships between organisational learning and organisational innovation and between knowledge management and organisational innovation. Organisational learning is positively related to knowledge management. Understanding the theoretical learning is positively beneficial for organisations aiming to increase organisational innovation and achieve business goals.
Lessons from the Private Sector
Authors: O'Brien Jamie
Published: December 2015

The primary aim of this chapter is to operationalize a Knowledge Assessment Framework (KAF) using two exploratory case studies. The development of a KAF is important for the public sector for three reasons. Firstly, the use of knowledge assessment allows firms to pinpoint knowledge gaps. Secondly, it allows firms to manage knowledge more effectively. Thirdly, it gives public sector organizations a diagnostic tool with which to gauge their knowledge base. The effective management of knowledge can be considered a competency that enables a greater level of service to be extracted from other resources within the organization.
BISC
Authors: Dokhanchi Atieh , Nazemi Eslam
Published: December 2015

Despite the importance and the strategic role of Business Intelligence (BI) in organizations and its key impact on successfully executing corporate strategies, in most cases, strategic planning and performance management projects are done independently from BI projects, therefore a holistic and an integrated framework has been proposed in this paper for aligning Business Intelligence initiatives with corporate strategies. This framework as an interdisciplinary work borrows the approach of the Enterprise Architecture frameworks and its structured logical thinking about the organization and was refined through gathering and analyzing expert's opinions. This paper also uses a case study in one bank with the aim of clarifying the application of the proposed framework.
Applications of Data Mining in Software Development Life Cycle
Authors: Dahiya Naveen , Bhatnagar Vishal , Singh Manjeet , Sangwan Neeti
Published: December 2015

Data mining has proven to be an important technique in terms of efficient information extraction, classification, clustering, and prediction of future trends from a database. The valuable properties of data mining have been put to use in many applications. One such application is Software Development Life Cycle (SDLC), where effective use of data mining techniques has been made by researchers. An exhaustive survey on application of data mining in SDLC has not been done in the past. In this chapter, the authors carry out an in-depth survey of existing literature focused towards application of data mining in SDLC and propose a framework that will classify the work done by various researchers in identification of prominent data mining techniques used in various phases of SDLC and pave the way for future research in the emerging area of data mining in SDLC.
X-CM
Authors: Chin Swee-Mei , Haw Su-Cheng , Chua Fang-Fang
Published: December 2015

The emergence of XML as the de facto for data exchange in the World Wide Web and the increase popularity of XML in the business application have urge momentum research on way to generate a well-formed XML document to store and maintain it in the databases. Thus, a good schema such as XML schema is undeniable needed in order to define the syntax and structure of the XML instance to ensure data integrity. Nevertheless, schemas serve as logical model rather than conceptual model where semantics of the underlying document are hardly expressed. As such, in this paper, the authors proposed X-CM, a new conceptual modeling for XML as the mechanism to model components of XML conceptually and to express the underlying semantic explicitly. First, the authors reviewed the semantics and structure of conceptual modeling of existing approaches. Then, the authors proposed their X-CM modeling construct and implemented X-CM in a university based scenario. Lastly, the authors summarized the evaluation result and comments provided by the XML database experts and evaluators based on the authors proposed model.
The Use of Arabic WordNet in Arabic Information Retrieval
Authors: Abbache Ahmed , Barigou Fatiha , Belkredim Fatma Zohra , Belalem Ghalem
Published: December 2015

Research and experimentation using Arabic WordNet in the field of information retrieval are relatively new. It is limited compared to the research that has been done using Princeton WordNet. This work attempts to study the impact of Arabic WordNet on the performance of Arabic information retrieval. We extend Lucene with Arabic WordNet to expand user's queries. The major contribution of this study is to propose an interactive query expansion (IQE) methodology using the word's part-of-speech, according to the part it plays in a query. First, the user selects the appropriate part of speech for each term in the original query, and then he reselects the appropriate synonyms. Experimental results show that our IQE strategy produces a good Mean Average Precision (MAP), it is able to improve MAP by 12.6%, but no variant of automatic query expansion (AQE) strategies did. Nevertheless, the experiments allow us to conclude that with an appropriate use of Arabic WordNet as a source of linguistic information for AQE can improve effectiveness for Arabic information retrieval.
ConChi
Authors: Cagliero Luca
Published: December 2015

Mobile context-aware systems focus on adapting mobile service provisions to the actual user needs. They offer personalized services based on the context in which mobile users' requests have been submitted. Since contextual information changes over time, the application of established itemset change mining algorithms to context-aware data is an appealing research issue. Change itemset discovery focuses on discovering patterns which represent the temporal evolution of frequent itemsets in consecutive time periods. However, the sparseness of the analyzed data may bias the extraction process, because itemsets are likely to become infrequent at certain time periods. This chapter presents ConChI, a novel context-aware system that performs change itemset mining from context-aware data with the aim at supporting mobile expert decisions. To counteract data sparseness itemset change mining is driven by an analyst-provided taxonomy which allows analyzing data correlation changes at different abstraction levels. In particular, taxonomy is exploited to represent the knowledge that becomes infrequent in certain time periods by means of high level (generalized) itemsets. Experiments performed on real contextual data coming from a mobile application show the effectiveness of the proposed system in supporting mobile user and service profiling.
Social Networks Discovery Based on Information Retrieval Technologies and Bees Swarm Optimization
Authors: Drias Yassine , Drias Habiba
Published: December 2015

Unlike the previous works where detecting communities is performed on large graphs, our approach considers textual documents for discovering potential social networks. More precisely, the aim of this paper is to extract social communities from a collection of documents and a query specifying the domain of interest that may link the group. We propose a methodology that develops an information retrieval system capable to generate the documents that are in relationship with any topic. The authors of these documents are linked together to constitute the social community around the given thematic. The search process in the information retrieval system is designed using BSO, the bee swarm optimization method in order to optimize the retrieval time for large amount of documents. Our approach was implemented and tested on CACM and DBLP and the time of building a social network is quasi instant.
The Importance of Visualization and Interaction in the Anomaly Detection Process
Authors: Riveiro Maria
Published: December 2015

Large volumes of heterogeneous data from multiple sources need to be analyzed during the surveillance of large sea, air, and land areas. Timely detection and identification of anomalous behavior or any threat activity is an important objective for enabling homeland security. While it is worth acknowledging that many existing mining applications support identification of anomalous behavior, autonomous anomaly detection systems for area surveillance are rarely used in the real world since these capabilities and applications present two critical challenges: they need to provide adequate user support and they need to involve the user in the underlying detection process. Visualization and interaction play a crucial role in providing adequate user support and involving the user in the detection process. Therefore, this chapter elaborates on the role of visualization and interaction in the anomaly detection process, using the surveillance of sea areas as a case study. After providing a brief description of how operators identify conflict traffic situations and anomalies, the anomaly detection problem is characterized from a data mining point of view, suggesting how operators may enhance the process through visualization and interaction.
Detection of Non-Technical Losses
Authors: Guerrero Juan I. , Monedero Íñigo , Biscarri Félix , Biscarri Jesús , Millán Rocío , León Carlos
Published: December 2015

The MIDAS project began in 2006 as collaboration between Endesa, Sadiel, and the University of Seville. The objective of the MIDAS project is the detection of Non-Technical Losses (NTLs) on power utilities. The NTLs represent the non-billed energy due to faults or illegal manipulations in clients' facilities. Initially, research lines study the application of techniques of data mining and neural networks. After several researches, the studies are expanded to other research fields: expert systems, text mining, statistical techniques, pattern recognition, etc. These techniques have provided an automated system for detection of NTLs on company databases. This system is in the test phase, and it is applied in real cases in company databases.
Resource Scheduling Techniques in Utility Computing
Authors: Chana Inderveer , Kaur Tarandeep
Published: December 2015

Utility Computing offers on-demand services from a shared pool of resources and can be envisaged to be a benchmark in the IT development. The capability to provide on-demand services involves management of large number of resources that are geographically dispersed and thus poses a number of resource management and scheduling challenges in the domain of resource heterogeneity, dynamic resource locations and load balancing. Proficient resource allocations and efficient scheduling helps in achieving optimal resource utilization and hence enhances the performance of the system. This paper evaluates existing resource management systems, listing their key characteristic features and highlighting the factors that make the existing systems excel upon each other. It also discusses various resource scheduling techniques currently available and characterizes the techniques based on Quality of Service (QoS) parameters supported by them along with the classification on basis of their operating environment and further extends towards load balancing and energy efficiency support if available.
On Trust, Knowledge Sharing and Innovation
Authors: Martins Isabel , Martins Ana , Pereira Orlando Petiz
Published: December 2015

Organisations continuously innovate, create, and are competitive if they improve their performance through continuous intellectual capital development, a key resource for value creation and organisational performance driver. Apart from sustaining competitive advantage, intellectual capital is increasingly important due to its ability to increase shareholder value, especially in public organisations. Employee learning, talent development, and knowledge creation allow the organisation to generate innovative ideas due to the quickness of knowledge obsolescence. The organisation's dynamic capabilities create and re-ignite organisational competencies for business sustainability being co-ordinated by well-structured organisational strategic routines ensuring continuous value creation streams into the business. This chapter focuses on the relationship between notions of knowledge sharing and trust in organisations. Lack of trust can impact negatively organisational knowledge sharing, dependent on trust, openness, and communication. The research sample included graduates and postgraduate students from two universities in Portugal. The findings revealed different perceptions according to the age group.
Employing Individuals' Social Capital to Create Value in the Public Sector Organisations
Authors: Ghaznavi Mahmood , Iqbal Salman , Toulson Paul
Published: December 2015

Social capital provides individuals with access to knowledge. Knowledge Management (KM) research recognises the importance of individuals' social capital in problem solving and innovation. However, while discussing the link between social capital and value creation, the literature seems ambitious in portraying that social capital can create new knowledge and drive innovation in firms. The authors argue that social capital can provide access to knowledgeable individuals but purposeful knowledge collaboration needs to be arranged by knowledge workers according to their specific knowledge needs. In this chapter, the authors discuss how public sector knowledge workers can utilise their social capital to create value for their organisation. The chapter presents a task-based knowledge collaboration model to improve performance and innovation capability of the public sector organisations. The model suggests that public sector organisations should support and encourage cross-organisational knowledge collaboration through informal (personal) networking of employees.
Predicting Student Academic Performance
Authors: Aslam M.M. Haris , Siddiqi Ahmed F. , Shahzad Khuram , Bajwa Sami Ullah
Published: December 2015

The biggest challenge in nurturing an academic community is encouraging knowledge sharing among its members. Literature on communities, however, has paid less attention on the role of outcome expectations in encouraging the knowledge sharing behaviors. This study examines the effects of Personal Outcome Expectations (POE) and Community-related Outcome Expectations (COE) on the knowledge sharing behaviors of students and its consequent impact on their academic performance. In order to study these relationships a survey of university students was conducted. Based on structural equation modeling approach, it was found that COE have significant impact on knowledge sharing among the students.
Multi-Group Moderation Analysis for Relationship between Knowledge Sharing Orientation and Business Performance
Authors: Vij Sandeep , Farooq Rayees
Published: December 2015

This paper examines the moderating effect of firm age on relationship between knowledge sharing orientation and business performance. Convenience sample of 274 firms from manufacturing and service sector was taken as sample for the study from National Capital Region (NCR) and Punjab State of India. The survey questionnaire was administered to the managerial level employees (C.E.O's, top level and middle level managers who were key decision makers in the organizations). The findings show that the knowledge sharing orientation exhibits a positive impact on business performance; firm age does not moderate the relationship between knowledge sharing orientation and business performance. The findings of the research will help knowledge management researchers as well as practitioners develop a better understanding of the role of knowledge sharing in successful implementation of knowledge management programs.
Knowledge Sharing, Social Relationships, and Contextual Performance
Authors: Peng Jianping , Quan Jing ("Jim") , Zhang Guoying , Dubinsky Alan J.
Published: December 2015

A firm's core competitiveness results primarily from its ability to innovate. Knowledge sharing plays an important role in promoting sustained innovation. This research examines two factors that enable employee knowledge sharing. Using responses from a questionnaire that was distributed to professionals in a research and development (R&D) department of a Chinese commercial elevator firm, the investigation examines whether social relationships and contextual performance influence knowledge sharing through the moderating effect of employee IT competence. Study findings reveal that social relationships—which include both the degree of centrality of the employee's social network and frequency of interpersonal interaction—and employee contextual performance have a significant positive impact on knowledge sharing. This association, however, is found to be positively moderated by employee IT competence. The findings provide managerial and future research insights pertaining to promoting knowledge sharing by enhancing employee social relationships, rewarding contextual performance, and providing regular IT training for employees.
Knowledge Management Practices and the Focus on the Individual
Authors: Rechberg Isabel , Syed Jawad
Published: December 2015

This chapter reviews the current knowledge management (KM) practices to examine the attention (or lack thereof) paid to the individual in managing knowledge in organisations. It identifies and reviews four key practices of KM - i.e., information technology, organisational culture and structure, communities of practice, and human resource practices - to examine how knowledge is interpreted, processed and managed, and the role individuals play in such interpretations, processing and management. The review shows that existing KM practices may be improved through an increased focus on the role of individuals (an individual-centric approach) in designing and implementing KM in organisations.
Face-to-Face Matters
Authors: Jackson Corey , Huang Yun , Kasowitz-Scheer Abby S.
Published: December 2015

This study describes new features for a mobile application designed to initiate face-to-face communication. While many mobile applications are designed to facilitate digitally mediated relationships (e.g., Facebook, Twitter) between previously known parties, systems focused on initiating face-to-face communication are less popular. The authors' mobile application takes inspiration from a Human Library event where participants come together to share stories with previously unknown persons. Through survey and interviews the authors describe new features of a mobile application to mediate face-to-face meetups. In the next phase of research the authors plan to implement those features and conduct additional user studies on our mobile application with the goal of increasing adoption.
The Roles of Knowledge Management and Organizational Innovation in Global Business
Authors: Kasemsap Kijpokin
Published: December 2015

This chapter explains the roles of Knowledge Management (KM) and organizational innovation in global business, thus describing the theoretical and practical concepts of KM and organizational innovation; the significance of KM in global business; and the significance of organizational innovation in global business. The accomplishment of KM and organizational innovation is vital for modern organizations that seek to serve suppliers and customers, increase business performance, strengthen competitiveness, and attain regular success in global business. Thus, it is necessary for modern organizations to investigate their KM and organizational innovation applications, create a strategic plan to constantly explore their functional advancements, and immediately respond to KM and organizational innovation needs of customers. Applying KM and organizational innovation will significantly enhance organizational performance and achieve strategic goals in the information age.
Knowledge Integration in Problem Solving Processes
Authors: Sousa Maria José
Published: December 2015

This article analyses the knowledge integration in problem-solving situations which requires a high level of interaction and trust among workers. Literature review explores the main barriers associated to knowledge integration and use and even if most problem situations are solved in an unconscious way, automatically and in a few seconds, others situations requires more time, effort, teamwork, collaboration and extensive abstract knowledge. This research goal is to analyses the perceptions of the workers from Alpha Organisation. The research findings allow us to conclude that depending on the complexity of the workstation, the Operator decides if he has the knowledge and the tools to solve the problem or if he needs help from Managers. The use and share of employees' knowledge is an important factor to solve problems and strengthen performance. However, several organisational and individual barriers condition the process.
Data Mining and Business Intelligence
Authors: Azevedo Ana
Published: December 2015

Data Mining (DM) is being applied with success in Business Intelligence (BI) environments, and several examples of applications can be found. BI and DM have different roots and, as a consequence, have significantly different characteristics. DM came up from scientific environments; thus, it is not business oriented. DM tools still demand heavy work in order to obtain the intended results. On the contrary, BI is rooted in industry and business. As a result, BI tools are user-friendly. This chapter reflects on this difference from a historical perspective. Starting with a separated historical perspective of each one, BI and DM, the author then discusses how they converged into the current situation, when DM is used, and integrated, in BI environments with success.
Exploration of Soft Computing Approaches in Itemset Mining
Authors: Pillai Jyothi , Vyas O. P.
Published: December 2015

Data Mining is largely known to extract knowledge from large databases in an attempt to discover existing trends and newer patterns. While data mining refers to information extraction, soft computing is more inclined to information processing. Using Soft Computing, the tolerance for imprecision, uncertainty, approximate reasoning, and partial truth for achieving tractability, robustness, and low-cost solutions can be revealed. For effective knowledge discovery from large databases, both Soft Computing and Data Mining can be merged. Soft computing techniques are Fuzzy Logic (FL), Neural Network (NN), Genetic Algorithm (GA), Rough Set (RS), etc. For handling different types of uncertainty in huge data, FL and RS are highly suitable. NNs are a nonparametric, robust technique and provide good learning and generalization capabilities in data-rich environments. GAs provide efficient search algorithms for selecting a model, from mixed-media data, based on some priority criterion. In one of its realms, Association Rule Mining (ARM) and Itemset mining have been a focus of research in data mining for a decade, including finding most frequent item sets and corresponding association rules and extracting rare itemsets including temporal and fuzzy concepts in discovered patterns. The objective of this chapter is to explore the usage of Soft Computing approaches in itemset utility mining, both frequent and rare itemsets. In addition, a literature review of applications of soft computing techniques in temporal mining is described.
Rethinking Knowledge Sharing Barriers
Authors: Cleveland Simon , Ellis Timothy J.
Published: December 2015

The current work force will not only lose 3.6 million “baby boomers” by 2020, but also a substantial organizational knowledge. Presently, there is a gap in understanding how to promote effective organizational knowledge sharing due to the limited awareness of factors that inhibit knowledge sharing behaviors. The focus of this article is to explore the most commonly noted barriers to employees' knowledge seeking and knowledge contributing practices and extract potential factors that influence these barriers. A content analysis study is performed on 103 knowledge management articles from ten computer and information science databases. The results demonstrate a clear division between the barriers limiting each specific behavior: knowledge seeking behaviors depend largely on the time availability of knowledge seekers, while poor communication skills and lack of trust appear to be the major inhibitors to knowledge contribution. Three main factors were found to influence these barriers: role conflict, role ambiguity and locus of control. The findings are consistent with the information foraging and social exchange theories. Implications for future research are proposed.
A Comprehensive Relational Model of Factors Influencing Knowledge Sharing
Authors: Shanshan Shang
Published: December 2015

This chapter aims to get the main factors affecting knowledge sharing and their influencing route so that to promote knowledge implementation through theory analysis and empirical test. The paper collects almost all the factors that have significant influence on knowledge sharing from a large amount of relative researches, and classifies the effect of factors as direct, indirect, mediate and moderate effect. Based on the deep review and analysis, the paper selects top management support, organization culture, social relationship, attitude to knowledge sharing, self-efficacy, trust, motivation, intention to knowledge sharing, IT, and training as the major influential factors and proposes a comprehensive relational model according to the effects of the factors. Finally, the paper verifies the model and examines the effects of the factors by empirical test through the data collected from questionnaires. The findings can give some guidance to managers and scholars.
Ajzen and Fishbein's Theory of Reasoned Action (TRA) (1980)
Authors: Al-Suqri Mohammed Nasser , Al-Kharusi Rahma Mohammed
Published: December 2015

This chapter provides an overview of the TRA and the main variants on this model, considers the main criticisms and limitations of the theory, and discusses examples of empirical studies that have helped validate this theoretical perspective and contributed to its development over time. It also considers the relevance of these theories for Library and Information Science. Potential future research directions relating to the TRA and related theories are discussed. These include additional meta-analyses using statistical techniques to refine the underlying structure of the theory and enhance understanding of its applicability in different contexts, and the use of qualitative research to improve understanding of the thought processes involved in behavioral decision-making and the factors that influence these.
Business Intelligence as a Service
Authors: Spruit Marco , de Boer Tim
Published: December 2015

Demand for business intelligence (BI) applications continues to grow even at a time when demand for most information technology (IT) products is low, showing the importance of BI products for a modern organization. However, globalization changes the way organizations use BI, where geographic location and time independency is becoming more and more important. Gartner's hype-cycle on BI depicts the technology of BI as a Service as being almost on top of the hype cycle, indicating there are high expectations of this new technology. This research advances on existing literature on business intelligence and cloud computing from a development perspective by introducing the concept of business intelligence as a service (BIaaS). The most important deliverable is the BIaaS capability maturity model (CMM) that is introduced here. The BIaaS CMM explains the conceptual model of BIaaS by the creation of the first BIaaS capability model containing key capabilities of BIaaS. The capability model is further enhanced with maturity levels depicting the importance of each BIaaS capability, a maturity matrix suggesting a roadmap for BIaaS solution development, and a BIaaS assessment model introducing a tool for finding problem areas in existing BIaaS solutions. The developed BIaaS CMM ought to support (starting) BIaaS vendors to develop BIaaS solutions by providing an assessment tool for BIaaS solutions. The assessment outcome provides the current maturity of the BIaaS solution and also includes problem areas for solution improvement. The introduction of the CApability Maturity Positioning (CAMP) method for the development of a maturity matrix, which results in the BIaaS maturity model, is significantly different from conventional maturity modeling. To calculate the weight of each capability from the BIaaS capability model, a thorough product review of existing business intelligence and cloud computing products is performed. Analysis of the results and normalizing the outcome of that analysis together with the introduction of a calculation mapping, is input for the creation of the maturity matrix. The maturity matrix is the essential foundation for the developed business intelligence as a Service capability maturity model, which is the main deliverable of this research.
Modeling the Knowledge Sharing Barriers
Authors: Sharma B. P. , Singh M. D.
Published: December 2015

In the knowledge-based economy, the survival and growth of the engineering industries depends upon the knowledge management (KM). In the present environment, KS is the corner stone of the KM. Some variables hinder KS in the industries are known as knowledge sharing barriers (KSBs). The objective of this paper is to identify and recognize the critical KSBs and their mutual influences in the industries. The interpretive structural modeling (ISM) methodology has been used to develop hierarchy of the identified KSBs evolving their mutual relationships. Identified KSBs at the root of the hierarchy (called driving KSBs) and at the top of the hierarchy (called dependent KSBs). It is observed that two KSBs namely “lack of top management commitment” and “KM is not well understood” have highest driving power. Therefore, these KSBs require serious attention by the managers in the engineering industries. The study concludes with discussion and managerial implications.
Pattern Based Feature Construction in Semantic Data Mining
Authors: Ławrynowicz Agnieszka , Potoniec Jędrzej
Published: December 2015

The authors propose a new method for mining sets of patterns for classification, where patterns are represented as SPARQL queries over RDFS. The method contributes to so-called semantic data mining, a data mining approach where domain ontologies are used as background knowledge, and where the new challenge is to mine knowledge encoded in domain ontologies, rather than only purely empirical data. The authors have developed a tool that implements this approach. Using this the authors have conducted an experimental evaluation including comparison of our method to state-of-the-art approaches to classification of semantic data and an experimental study within emerging subfield of meta-learning called semantic meta-mining. The most important research contributions of the paper to the state-of-art are as follows. For pattern mining research or relational learning in general, the paper contributes a new algorithm for discovery of new type of patterns. For Semantic Web research, it theoretically and empirically illustrates how semantic, structured data can be used in traditional machine learning methods through a pattern-based approach for constructing semantic features.
Business Intelligence for Healthcare
Authors: Cook Jack S. , Neely Pamela A.
Published: December 2015

Using an interpretive case study approach, this chapter describes the data quality problems in two companies: (1) a Multi-Facility Healthcare Medical Group (MHMG), and (2) a Regional Health Insurance Company (RHIS). These two interpretive cases examine two different processes of the healthcare supply chain and their integration with a business intelligence system. Specifically, the issues examined are MHMG's revenue cycle management and RHIS's provider enrollment and credentialing process. A Data and Information Quality (DIQ) assessment of the revenue cycle management process demonstrates how a framework, referred to as PGOT, can identify improvement opportunities within any information-intensive environment. Based on the assessment of the revenue cycle management process, data quality problems associated with the key processes and their implications for the healthcare organization are described. This chapter provides recommendations for DIQ best practices and illustrates these best practices within this real world context of healthcare.
Adaptive Intrusion Detection Systems
Authors: Bensefia Hassina , Ghoualmi-Zine Nassira
Published: December 2015

This chapter deals with a challenging issue in intrusion detection research field, which is IDS adaptability. First, it introduces the intrusion detection concepts, then presents with details the two existing generations of IDSs and addresses their major problem: permanent coverage of new attacks patterns in a dynamic changing environment. Thereafter, it evokes the requirement of adaptability in IDS as a mean to remedy this deficiency. Later, it explores the most eminent approaches that are proposed for IDS adaptability. It describes their functional architecture and discusses their strong aspects and weaknesses. At the end, new trends toward the intrusion detection adaptability problematic are mentioned and followed by a conclusion.
Development of Coatings Based on Modified Epoxide Binder for Metal Surface Protection
Authors: Kudina Elena F. , Vinidiktova Natalia S. , Jevremović Vladeta , Nikolić Radovan
Published: December 2015

Epoxy-silicate modifiers were obtained by a sol-gel procedure from the alkali-silicate solutions and their effect on physico-mechanical properties of the coatings based on the binary epoxide binder were investigated. It is shown that pretreatment of the metal surface effects strength of adhesive bonding with the epoxide coating.
Applying of the Functional Approach to Obtaining Blind and through Cuts in the Workpieces of Hard and Superhard Sintered Materials by Jet Methods
Authors: Salenko Oleksandr , Mana Oleksandr , Shkel Sergiy , Nikitin Vladimir , Myronov Yaroslav
Published: December 2015

We have shown the feasibility of using multipass processing for obtaining precision profile cuts of hard-alloys material using the changable cutting feed that leads to significant reduction in deviations from intended form of jet. Found that the decrease in speed around the contour should be proportional to the thickness of the processed material and its physical and mechanical characteristics.
Substantiation of the Operational Parameters of the Sandwich Belt High Angle Conveyors with due Regard for Strain Deformed State of Belts
Authors: Galkin Vladimir Ivanovich , Sheshko Evgeniya Evgenievna
Published: December 2015

The article deals with the advantages of special types of conveyors and, in particular, the sandwich belt high-angle conveyors, and also several problems appearing when designing and creating high-productive installations under high conveying angle and to considerable height. Processes of overstrain of separate sections of the belt and also considerable deformations of edges and the middle of the belt are established in the article. It is shown that an effective method of the solution of such tasks is the modeling of strain deformed state of belts with utilization of methods and the software application of the ANSYS complex. Decision examples for separate sections are given in the article too. The role of elastic properties of the belts and their durability when basing parameters of the considered sections is proved in the article. It is shown that modern rubber fabric and rubber cable belts give the chance of creation of powerful conveyor installations with a cover belt for large conveying angles and high productivity.
Sound-Absorbing Composites Based on Flax and Polymer Fibers
Authors: Yakimovich Nikolay V. , Bukharov Sergey N. , Kozhushko Victor V. , Khmara Anastasiya S. , Sergienko Vladimir P.
Published: December 2015

The paper considers sound absorption of the composite materials, which are based on the natural flax and polymer fibers. The thickness of a single layer of obtained nonwoven composite is about 10 mm. The analysis of absorption dependences is carried out for different thicknesses of the material. It is shown that in the low frequency range the absorption almost linearly increases depending on the thickness. The coefficient of the normal absorption increases with the frequency in the range from 50 Hz up to 1600 Hz. The hot-pressed material can be used for panel production. The sound absorption increases with the thickness of the pressed material. The measurements show the possibilities of application of the composite for the production of the parts of cabs’ interior.
The Calculation of Force Effects of a Conveyor Belt of the Pipe Conveyor to Forming Rollers by FEM
Authors: Fedorko Gabriel , Molnár Vieroslav , Michalik Peter , Husáková Nikoleta , Ristović Ivica , Kačmáry Peter
Published: December 2015

The paper interprets the calculation of the size of force effects created by the reason of the effect of balled conveyor belt of pipe conveyor to the guide rollers located in the ring idler stations. Knowing them is essential for the research of dynamic resistances by pipe conveyors operations. Examined force effects were determined by the help of finite element methods. The calculation was performed by the program Abaqus. Presented calculation is realized by original calculation model. The results of the calculation present information about action of the effect force of the balled conveyor belt to the guide rolls in the ring idler station. Results became a basis for determination of postulates for identification of dynamic resistances. Their knowledge is the key element for conveyor belts lifetime increase.
Time Series Analysis of New Cars Sale in Bosnia and Herzegovina
Authors: Jakupović Esad , Stojanović Vladimir , Jakupović Sanel , Trnavac Dragana
Published: December 2015

The paper provides analysis of new car sales in Bosnia and Herzegovina for the period 2007-2014. For the examined period new car sales in B&H was reduced by 53.67%, from 12449 in 2007 to 6682 in 2014. The trend can be approximated using 3rd degree polynomial regression model with coefficient of determination R2=0,845. Most new cars sold were by Skoda and least was sold by Porsche. Total number of sold vehicles for this period was 73152. We also present annual growth, chain growth and cumulative growth index for the given period.
Investigation of Efficiency of Use of High-Temperature Greases in Steel Rolling - Part 1
Authors: Avdeenko Anatoly P. , Lutovac Mitar , Konovalova Svetlana A. , Fedorynov Mykhailo V.
Published: December 2015

It has been shown the efficiency of use of high-temperature greases “Natol-H-1(2)” in steel rolling in the result of research of friction coefficients (steel-to-steel) for various rolling pressures on application of greases “Natol”. Medium-temperature putted greases Natol-M-1(2) and pumpable consistent greases “Natol-Р-1(2, 3)” are not suitable for steel rolling. The influence of various components and their percentages in greases on magnitude of friction coefficients was found.
Modelling of Influence of Intensive Heat Flow on Stress Inhomogeneity in Ceramic System TiC-Y2O3-Si3N4
Authors: Kuzin Valery V. , Fedorov Mike , Dašić Predrag , Portnoy Mike
Published: December 2015

Modelling is necessary for the control of exploitation process of ceramic details to achieve improved reliability and high productivity. Of most importance in exploitation of nitride ceramic details is the establishment of models that relates external loading with stress-strain state through consideration of mechanical and thermal interactions between the ceramic structural elements. This paper evaluates several interrelationships between heat flow and stress inhomogeneity in nitride ceramics which revealed the results of simulation analysis.
Delamination Analyses of GFRP Composites under High Speed Conditions and Various Drill Geometries
Authors: Keh Gou Zhou , Tan Chye Lih , Irina W.M.M. , Azmi Azwan Iskandar , Leong K.W. , Radzi M.N.M.
Published: December 2015

It is well understood that the fabrication process for glass fibre reinforced polymer (GFRP) composite is a near net-shape process. Nevertheless, drilling is often performed in the final stage in product component manufacture. Drilling of GFRP composites usually produces delamination damage that deteriorates the long-term performance of the composite materials. Hence, this project aims to obtain desired drilling parameters for minimum delamination damage under high-speed conditions. Taguchi L27 orthogonal array has been employed for the experimentation and the controlled variables include spindle speed, feed rate, and drill bit. The results of Taguchi analyses showed that feed rate and drill geometry have major influence towards delamination damage.