bluuebunny/crossref_metadata_2025 huggingface dataset:
Rheumatoid Arthritis Drugs for Schizophrenia?
Authors: Buckley Peter F. , Miller Brian J.
Published: May 2018

Any relationship between treatment of rheumatoid arthritis and the current treatment of schizophrenia seems, at first glance, far-fetched. And yet, in a relatively short period of intensive research work, the field of schizophrenia research has come to appreciate that there are fundamental immunological associations with schizophrenia. Several groups have conducted studies of antirheumatic drugs—from various nonsteroidal anti-inflammatory drugs to more selective anticytokine monoclonal antibodies—in patients with schizophrenia. The results and focus of this work are detailed in this article.

[
Psychiatr Ann.
2018;48(5):232–236.]
Inflammation and Schizophrenia
Authors: Bowcut Jana Caylor , Weiser Mark
Published: May 2018

The causes of schizophrenia are unknown; many etiologies have been implicated but none proven. Renewed interest in immunological etiologies has led investigators to examine the plasma of patients with schizophrenia in which they have found increased levels of some cytokines and antibodies to cytomegalovirus and
Toxoplasma gondii.
Elevated plasma C-reactive protein is associated with increased risk of later schizophrenia. Prenatal exposure to some infectious agents and increased maternal levels of interleukin-8 during pregnancy are associated with increased risk for schizophrenia. These findings suggest that in a subset of patients, an immunological and, perhaps infectious mechanism, might be involved. This article reviews treatment trials that have an anti-inflammatory or anti-infectious mechanism of action. These include antibiotics, nonsteroidal anti-inflammatory drugs, anti-toxoplasma drugs, monoclonal antibodies, and other drugs effective against inflammatory or infectious diseases. To date, none of these anti-inflammatory compounds have consistently shown efficacy; studies on many promising compounds are ongoing.

[
Psychiatr Ann.
2018;48(5):237–243.]
The Optimal Management of Opioid Use Disorder: Leveraging Advances in Addiction Psychopharmacology to Enhance Treatment Outcomes
Authors: McGee Michael D.
Published: May 2018

Discharge after inpatient or institutional detoxification for opioids results in postdischarge relapse rates of up to 91%. Addiction psychopharmacology with buprenorphine, methadone, or long-acting injectable naltrexone, augmented with clonidine, can reduce postdischarge relapse rates to as low as 40%. Given the safety and efficacy of these medications when properly prescribed, prescribing clinicians have a duty to inform patients of these treatment options as part of the routine course of treatment and discharge planning.

[
Psychiatr Ann.
2018;48(5):248–253.]
Developing Students' Cross-Cultural Competence Through Academic Programs
Authors: Eisenberg Jacob
Published: May 2018

Realizing the increased demand and need for equipping graduates with cross-cultural competencies, universities have been offering a growing array of academic courses aimed at increasing students' cultural competence. This research review chapter addresses the question of what do empirical studies tell us about the impact of academic educational interventions on students' cultural competence. Among the various competences, this review pays special attention to cultural intelligence (CQ). Covering diverse educational interventions, ranging from short intensive training-like courses to full-term courses to study abroad visits, the chapter concludes that several academic interventions, both traditional and virtual, were effective in increasing cultural competencies. This chapter would be of interest for academics contemplating course design in international management, for business school program directors who wish to promote students' cultural competencies, and for university staff involved in managing various international exchange programs.
Utilizing Learner Knowledge in Cross-Culture Management Education
Authors: Starr-Glass David
Published: May 2018

In many business schools, the cross-culture management course has become a central response to the increasingly globalized and internationalized world in which graduates will work. The core content, pedagogic assumptions, and anticipated learner outcomes of this course have changed over the last two decades, moving from the passive transmission of national culture knowledge to more active and responsive knowledge-creation that might better serve students in approaching cross-culture management challenges. In restructuring his cross-culture management course, the present author reflected on these shifts and on the national culture richness of the envisaged students. This chapter explores ways of utilizing the informal cultural learning and tacit national culture knowledge of course participants to create a learning experience that might be more useful for students who will engage in the international organizational and corporate world of the twenty-first century.
Cultural Quotient
Authors: Kapse Manohar , Bhattacharjee Sanjib , Raj Priya
Published: May 2018

Analytical competency is an essential skill when it comes to the present-day business scenario of the world. However, these days we see a shift in the business needs when it comes to working in a globalized environment. Not only is the intelligence quotient (IQ) looked at but organizations these days are in pursuit of individuals who have another side to their profile – the culturally intelligent side (assessed using the cultural quotient). The need of such a skill can be attributed to the fact that organizations are now churning out their human side of addressing the employees when it comes to ensuring that they blend in the organization with ease. Acquiring a workforce which possesses high cultural intelligence can be a tough task; however, training employees to become culturally competent can be a doable task. Like any other personality trait which can be imbibed over time through constant analysis and observation, cultural competency is one such area which may be cultivated through various methodologies and practices.
Challenges and Benefits of Multi-Cultural Teaching
Authors: Conger Sue
Published: May 2018

In an average semester, five or more countries will be represented in the typical information technology classroom. This diversity requires fleetness to develop trust, awareness of our cultural differences and requirements, and students' free participation. It also requires understanding of components of self-esteem and how it relates to learning; bricolage and when to deviate from planned activities; and many forms of experiential learning. This chapter develops these concepts and demonstrates how to effectively weave them together in engaging students from many cultures. The benefits of the work this effort involves many students who learn today and apply tomorrow in internships, and who, years later, return with tales of successes that build on foundations of concepts and techniques learned in such courses.
Globalization and Rethinking of Environmental Consumption From a Sustainability Perspective
Authors: Amadi Luke A. , Igwe Prince Ikechukwu
Published: May 2018

Sustainable environmental consumption has been a marginalized concept in international development studies and cooperation. In recent decades, there has been growing interest in identifying robust indicators that demonstrate the evidence of globalization and unsustainable environmental consumption. Globalization is premised on integrating the world into a global village. Various dimensions of globalization have different effects on the ecosystem. Plausible evidence linking globalization trajectories into practical interactions suggesting sustainable environmental consumption has been less lucid as the effects of globalization on the ecological environment does not provide clear patterns. This hugely significant problem has reopened critical debates on novel thinking on dynamics of environmental consumption patterns of the affluent societies in the era of globalization and its implications on environmental sustainability. This chapter deployed content analysis methodology and political ecology framework to review and analyze seminal studies on sustainable consumption and globalization, including relevant globalization indexes. The aim is to provide evidence of the impact of globalization on environmental consumption. The chapter suggests that globalization results in asymmetrical and deleterious natural resource extraction between the affluent North and poor South. It offered alternative thinking in which sustained policy framings and international development collaboration could be institutionalized to strengthen sustainable environmental consumption one which is premised on ecological justice and natural resource equality.
Consumer Cooperation in Sustainability
Authors: Mkhize Njabulo , Ellis Debbie
Published: May 2018

The planet is under threat. Unless all stakeholders, that is governments, businesses, and consumers, become more environmentally friendly, some predict dire consequences for the earth and all those who inhabit it. While governments and businesses have a role to play, green consumer behavior is vital to the sustainability of the environment. Consumers have been shown to express increasing concern for the environment, but in many studies this concern has been found not to be matched by actions, a phenomenon labelled the green gap. This chapter describes a study that investigated the existence and extent of the green gap amongst a sample of South African adult consumers and sought to determine possible reasons for a lack of green behavior. Recommendations are made to marketers and policy makers to encourage consumer cooperation in environmental sustainability.
Making Connections Between E-Learning and Natural Learning
Authors: Caine Geoffrey
Published: May 2018

This chapter develops a model of learning that takes advantage of the ways in which the brain naturally functions in any learning situation. This model is framed in terms of a set of 12 principles called the brain/mind principles of natural learning. It is the sort of learning that helps all people adapt and adjust consciously and unconsciously to an ever-changing world. The core point is that every person is an integrated living system, which means the body, brain, heart, and mind are all involved in learning. Whether working face-to-face or online students need to employ their natural systems to learn well. This chapter gives teachers more ideas about the teaching/learning process to assist their students to deploy their knowledge and skills in the real world. This chapter argues that instructors should understand and implement learning in ways that assist learners in using their natural perception-action cycles.
Democratic Thinking and Student-Centered Pedagogy
Authors: Preble William K. , Locke Sharon
Published: May 2018

This chapter offers a set of philosophical, historical, and critical lenses to examine the U.S. educational system. The authors show how US schools have been built on philosophies and structures dating back to the earliest days of Western Civilization, and how many of these ideas and practices have perpetuated long-standing societal and educational inequalities. They also show how a set of more modern philosophies and pedagogical models can be used in schools to dramatically shift power relations and deepen student engagement. They discuss how the convergence of new thinking, new purposes, and the use of new twenty-first century educational technologies can help educational institutions and schools make the jump from traditional, inequitable educational systems, to more modern, empowering, and equitable institutions. The chapter concludes with a set of specific instructional strategies that can help schools and teachers effectively apply new learning technologies to amplify student voice and provide student-centered learning opportunities.
Adult Learner-Centered and Scalable Online Competency-Based Education
Authors: Leasure David E. , Apple Daniel K. , Fulton Amy P. , Kavlie Lucas B.
Published: May 2018

The challenges of educating a shifting demographic for a shifting job market, with a solution that enhances educational equity and effectively develops competence, has been demonstrated by WGU's implementation of competency-based education (CBE). WGU's model is scalable and maintains affordability. The chapter presents an idealized model of CBE that extends the practice and analyzes its and WGU's contribution to equitable education, affordability, and scalability. The analysis of the model's contribution to equity highlights the importance of explicitly including identity and personal factors in assessment and evaluation. The idealized model is recommended to improve equity through encouraging self-growth, identity formation, evaluation, and assessment for improvement.
Introduction to Online Learning and the Adult Learner
Authors: Stan Rosana , Kállay Éva
Published: May 2018

Web technologies are changing old patterns of learning. Online learning is simultaneously a tool and a challenge in improving our learning process because working online is a fundamental competence for today's society. Rethinking needs and course design for online learning to be applied to all subjects at all levels (digital natives and digital immigrants as well) is, maybe, the biggest challenge in education. It is necessary to give teachers adequate training to teach using technologies in a way that supports specific pedagogical mode. Online learning for adult learners has both advantages and disadvantages. Research into online learning is an emerging field and all of this information has practical implication for design and tutoring online activities in the case of adult learners.
Learning to Teach Students With Attention Deficit Hyperactivity Disorder
Authors: Cretu Daniela-Maria
Published: May 2018

The presence of special needs students in regular classrooms makes it difficult for teachers to manage the situation, especially since in Romania the initial teacher-training curriculum doesn't include a class addressing the issue. This chapter talks about the teaching, learning, and evaluation experiences offered by an instructional unit on the subject of ADHD for over 700 primary and secondary school teachers from all areas of expertise. The purpose of this unit was to increase the teachers' knowledge and understanding of students with attention deficit hyperactivity disorder (ADHD) in an educational frame. This chapter presents content elements, learning, and assessment activities that the participants proposed and implemented during the work sessions: both face to face and online. The authors mention that this training experience was part of a larger project called “e-Mentor: Developing ITC Skills and Educational Mentor-ship of Disabled Persons, for Teachers” implemented by “Lucian Blaga” University of Sibiu.
Collaborative Scientific Writing Between Writing Art and Project Management
Authors: Iliescu Dragoș , Banciu Felicia Veronica , Vasilache Simona
Published: May 2018

This chapter investigates collaborative scientific writing. The study presents a baseline and concepts embedded by research for an ad hoc group of authors. Transactive memory, which is a quality of a group achieving the desired synergy, is approached in literature through metaphors. The investigation focuses on a proposal to evaluate the transactive memory's quale. A specialization between group and team expresses the ability of online technology to enhance the authors' communication. The research examines synergy among the authors for different phases of experienced collaboration to achieve successful publishing. Three hypotheses were researched for the evaluation of transactive memory's quale. The findings suggest that the total amount of knowledge experienced by the group of authors, as resulting from the collaborative scientific writing, corresponds to the aggregated domains of deterministic and probabilistic spaces.
The Application of the Learning Sciences to the Design and Delivery of Student-Centered Learning Activities
Authors: Hamlin Michael D.
Published: May 2018

The goal of this chapter is to provide a framework for creating student-centered learning activities that rest on a firm theoretical foundation and are based on a definition that highlights the actual learner abilities involved in successful student performance. To achieve this goal, it is important to establish a definition of student-centered learning that can be used to guide the selection of the important pedagogical elements that must be addressed in the design of student-centered learning activities. Having established these foundational elements, the chapter provides a framework for the design of case-based instruction that incorporates teaching and learning principles derived from theory and research in the learning sciences.
An Inquiry Into Creating and Supporting Engagement in Online Courses
Authors: Hummel Robin , Lowry Genevieve , Pinkney Troy , Zadoff Laura
Published: May 2018

This chapter focused on the challenge to build an interactive online environment based on a progressive pedagogy that puts the student at the center of the learning. The authors grappled with the question, How do instructors transform discursive dialogue into generative discourse? Helping students understand what it means to engage in discourse is part of this challenge and it is not separate from building an understanding of content. They are interconnected and interdependent. Online learning, like on campus learning, requires purposeful experiences in which learners are able to negotiate meaning and reflect on what they have learned. The authors set out to discover how to create the structures that support active engagement. It was their understanding that through the learning environment they created, they would model and define how to engage in the discourse of the discipline. In exploring this understanding, the authors offered the distinction between participation and engagement.
Cross-Cultural Languages Behind Technology-Enhanced Language Learning
Authors: Roberto John Alexander
Published: May 2018

Technology-enhanced language learning (TELL) is the result of the evolution of digital language, that is, a special code created by human beings to interact with computers. Digital language has, in turn, allowed for the creation of more specific languages. On the web, TELL is supported by three cross-cultural languages: natural language, visual language, and artificial language. A natural language, such as English or Spanish, becomes cross-cultural when it is processed by automatic means. A visual language is a system of communication using visual elements, such as pictograms. An artificial language, such as programming languages, is designed to communicate instructions to a machine. The author calls this trilogy of languages W3langs. This chapter explores the relationship between TELL and W3langs.
It's All in the Numbers
Authors: Balchin Kevin , Wild Carol
Published: May 2018

This chapter focuses on teacher professional development and TELL, and the constraints of TELL. More specifically, it explores some of the barriers and enablers to the use of technology in English language classes in six secondary school across Malaysia, in both rural and urban settings. The cross-cultural aspect of the study comes from a comparison of the schools involved and considerations of context-appropriate technological tools and materials in the differing school environments. The backdrop to the study is the Malaysian Ministry of Education (MMoE). One particular issue highlighted in the study is the benefit of communities of teachers working together to implement and integrate technology into their teaching.
Intercultural Learning via Videoconferencing
Authors: Vurdien Ruby , Puranen Pasi
Published: May 2018

Although asynchronous communication tools have traditionally been used in online interactions, recently increasing popularity has been noted in the application of synchronous communication tools to facilitate intercultural learning. This chapter will explore and report on a study of how students from two countries, Spain and Finland, developed intercultural competence through the use of a video-conferencing platform, Adobe Connect, as a learning context. English was the lingua franca and the exchange of information was aimed at helping the students to learn about different aspects of each other's culture to develop intercultural competence. The findings suggest that the students' attitude to their learning experience was positive, since they were curious to explore each other's cultural traits. Videoconferencing was considered an effective tool because it enabled them to share experiences and build up a relationship, thereby enhancing their knowledge of both cultures. Body language also encouraged interaction since they could see each other via videoconferencing.
A New Approach of an Intelligent E-Learning System Based on Learners' Skill Level and Learners' Success Rate
Authors: Mohamed Hafidi , Lamia Mahnane
Published: May 2018

Learners usually meet cognitive overload and disorientation problems when using e-learning system. At present, most of the studies in e-learning either concentrate on the technological aspect or focus on adapting learner's interests or browsing behaviors, while, learner's skill level and learners' success rate is usually neglected. In this paper, the authors propose an online course generation based not only on the difficulty level of a learning unit, but also the changing learning performance of the individual learner during the learning process. Therefore, considering learner's skill level and learners' success rate can promote personalized learning performance. Learners' skill level is obtained from pre-test result analysis, while learners' success rate is acquired through specific tests after completing a learning unit. After computing success rate of a learning unit, the system then modifies the difficulty level of the corresponding learning unit to update courseware material sequencing. Experiment results indicate that applying the proposed intelligent e-learning system can generate high quality learning paths, and help learners to learn more effectively.
Computational and Cognitive Approaches to Narratology From the Perspective of Narrative Generation
Authors: Ogata Takashi
Published: May 2018

This chapter surveys and discusses interdisciplinary approaches to primarily Artificial Intelligence (AI)-based computational narrative or story generation systems by way of introducing cognitive science, and narratology and related literary theories. The first part of this chapter provides a general description (from the perspective of the research framework of the author) and the second part presents processes, theories, designs, and implementations of narrative generation by the author. In particular, the first part includes an overview of narratology and the relevant literary theories, computational and cognitive theories and techniques related to narratology and narrative generation, and narrative generation systems. The second part presents, in relative detail, components that constitute a systematic study for narrative generation by the author and an integrated narrative generation system of all of the previous attempts.
Cognitive Informatics and Computational Intelligence
Authors: Wang Yingxu , Rolls Edmund T. , Howard Newton , Raskin Victor , Kinsner Witold , Murtagh Fionn , Bhavsar Virendrakumar C. , Patel Shushma , Patel Dilip , Shell Duane F.
Published: May 2018

Cognitive Informatics (CI) is a contemporary multidisciplinary field spanning across computer science, information science, cognitive science, brain science, intelligence science, knowledge science, cognitive linguistics, and cognitive philosophy. Cognitive Computing (CC) is a novel paradigm of intelligent computing methodologies and systems based on CI that implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain. This paper reports a set of position statements presented in the plenary panel of IEEE ICCI*CC'14 on Cognitive Informatics and Cognitive Computing. The summary is contributed by invited panelists who are part of the world's renowned researchers and scholars in the transdisciplinary field of cognitive informatics and cognitive computing.
For an Intelligent E-Learning
Authors: Kose Utku
Published: May 2018

During a typical e-learning process, there are many different factors that should be taken into consideration to keep the stability of the process or improve the process to get more effective results. Nowadays, employing Artificial Intelligence-based approaches is one of the most popular ways to improve the process and obtain the desired objectives rapidly. In this sense, there are many different kinds of scientific works in order to improve the related literature. However, ensuring control among the performed Artificial Intelligence-based e-learning process is a critical point because there is sometimes a misunderstanding about employing intelligent e-learning process that running intelligent educational tools or materials does not always mean the related e-learning process will improve greatly. In order to ensure that there should be some managerial procedures focused on some aspects of the process, this chapter aims to introduce a managerial model that can be used for especially Artificial Intelligence-supported e-learning content flow in order to improve the educational process. The suggested model is usable for the educational institutions, which focus on especially Artificial Intelligence-oriented e-learning solutions, research works, and educational activities.
Intelligent Educational Support System
Authors: Mutlu-Bayraktar Duygu
Published: May 2018

Increasing student numbers lead to new needs in the education sector. New systems are needed due to expert numbers that are insufficient in specialties, such as instructors, directors, and advisors. Type, goal, and specialty of intelligent systems programmed to satisfy this need are being developed with each passing day. The aim of this chapter is to develop an intelligent system that provides support with schedule, academic orientation, choice of profession, and career planning to students. To make a regular schedule for students would generally cause an inappropriate program, which is hardly followed by students in case they were indiscriminately prepared without any information about students' characteristics. Instead of this method, it is the point to be familiar with the academic success, study, resting, and even meal time of the student, and to know which lessons are studied on which days and to make an appropriate schedule for studying. According to the teachers, it is time-consuming and difficult to perform this method for all students. Within this scope, an intelligent system preparing a study schedule is developed considering the students' characteristics and study habits.
Supporting Physicians in the Detection of the Interactions between Treatments of Co-Morbid Patients
Authors: Piovesan Luca , Molino Gianpaolo , Terenziani Paolo
Published: May 2018

The treatment of patients affected by multiple diseases (comorbid patients) is one of the main challenges for modern healthcare. Clinical practice guidelines are widely used to support physicians, providing them evidence-based information of interventions, but only on individual pathologies. This sets up the urgent need of developing methodologies to support physicians in the detection of interactions between guidelines, to help them in the treatment of comorbid patients. In this chapter, the authors identify different levels of abstractions in the analysis of interactions, based on both the hierarchical organization of clinical guidelines (in which composite actions are refined into their components) and the hierarchy of drug categories. They then propose a general methodology (data/knowledge structures and reasoning algorithms operating on them) supporting user-driven and flexible interaction detection over multiple levels of abstraction.
Developing Secure Software Using UML Patterns
Authors: Schmidt Holger , Hatebur Denis , Heisel Maritta
Published: May 2018

This chapter presents a security engineering process based on UML security problem frames and concretized UML security problem frames. Both kinds of frames constitute patterns for analyzing security problems and associated solution approaches. They are arranged in a pattern system that makes dependencies between them explicit. The authors describe step-by-step how the pattern system can be used to analyze a given security problem and how solution approaches can be found. Then, solution approaches are specified by generic security components and generic security architectures, which constitute architectural patterns. Finally, the generic security components and the generic security architecture that composes them are refined, and the result is a secure software product built from existing and/or tailor-made security components.
Development of the System for Authoring Three-Dimensional Learning Applications for Use in E-Learning Environment
Authors: Evseeva Julia Igorevna , Bozhday Alexander , Gudkov Alexei Anatolievich
Published: May 2018

The problem of automated development of learning applications based on the three-dimensional graphics and having the property of adaptability is important when addressing a number of issues related to e-learning. Effective solution of this problem will provide some benefits to organizations that use in their work or provide e-learning technologies. This article describes the main benefits of using a common approach and tools to design learning applications for use in e-learning and based on the three-dimensional graphics and properties of adaptability. The existing software systems and technologies, which can be used for these purposes, are considered; their shortcomings are revealed. Methods for authoring three-dimensional adaptive applications that do not have the disadvantages of existing systems are suggested. The technology of modeling variability underlying the most important component functionality is proposed. The structure of the proposed system is considered.
Multifaceted Applications of Data Mining, Business Intelligence, and Knowledge Management
Authors: Kasemsap Kijpokin
Published: May 2018

This article reviews the literature in the search for the multifaceted applications of data mining (DM), business intelligence (BI), and knowledge management (KM). The literature review highlights the overviews of DM, BI, and KM; the practical applications of DM, BI, and KM; and the prospects of DM, BI, and KM in terms of marketing, business, human resources, and manufacturing. DM plays a key role in organizing huge amount of data and condensing it into valuable information. BI involves the delivery and integration of relevant and useful business information in an organization. KM allows companies to manage a system of core competencies in order to maximize business opportunities and minimize the risk of losing business opportunities. The findings present valuable insights and further understanding of the way in which DM, BI, and KM efforts should be focused.
Agent-Based Distributed Intelligent Tutoring System Using Case-Based Reasoning
Authors: Shweta  , Dhyani Praveen , Rishi O. P.
Published: May 2018

Intelligent Tutoring Systems have proven their worth in multiple ways and in multiple domains in education. In this chapter, the proposed Agent-Based Distributed ITS using CBR for enhancing the intelligent learning environment is introduced. The general architecture of the ABDITS is formed by the three components that generally characterize an ITS: the Student Model, the Domain Model, and the Pedagogical Model. In addition, a Tutor Model has been added to the ITS, which provides the functionality that the teacher of the system needs. Pedagogical strategies are stored in cases, each dictating, given a specific situation, which tutoring action to make next. Reinforcement learning is used to improve various aspects of the CBR module: cases are learned and retrieval and adaptation are improved, thus modifying the pedagogical strategies based on empirical feedback on each tutoring session. The student modeling is a core component in the development of proposed ITS. In this chapter, the authors describe how a Multi-Agent Intelligent system can provide effective learning using Case-Based Student Modeling.
An Efficient Diagnosis System for Detection of Liver Disease Using a Novel Integrated Method Based on Principal Component Analysis and K-Nearest Neighbor (PCA-KNN)
Authors: Singh Aman , Pandey Babita
Published: May 2018

Talk about organ failure and people immediately recall kidney diseases. On the contrary, there is no such alertness about liver diseases and its failure despite the fact that this disease is one of the leading causes of mortality worldwide. Therefore, an effective diagnosis and in time treatment of patients is paramount. This study accordingly aims to construct an intelligent diagnosis system which integrates principle component analysis (PCA) and k-nearest neighbor (KNN) methods to examine the liver patient dataset. The model works with the combination of feature extraction and classification performed by PCA and KNN respectively. Prediction results of the proposed system are compared using statistical parameters that include accuracy, sensitivity, specificity, positive predictive value and negative predictive value. In addition to higher accuracy rates, the model also attained remarkable sensitivity and specificity, which were a challenging task given an uneven variance among attribute values in the dataset.
Using DEMATEL-Based ANP Model to Measure the Successful Factors of E-Commerce
Authors: Wu Chia-Huei , Tsai Sang-Bing
Published: May 2018

Factors affecting online businesses are complicated and intertwined. To stimulate online sales, understanding of key influential factors and causal relationships among the factors is important. This paper introduces a hybrid method, called the DANP method, to expose the driving factors that most influence the online businesses. A hierarchy of fourteen criteria in six dimensions is formed to denote the influence levels and weights of factors. The causal graph shows that “Uncertainty” dimension has the highest degree of direct impact on other dimensions; thus, strong efforts should be made to eliminate the influence of this dimension throughout the online shopping process. In addition, the results also show “perceived price” to be the greatest important criterion among all; thus, it should be treated with top priority to boost the online businesses.
Some Generalized Intuitionistic Fuzzy Geometric Aggregation Operators With Applications in Multi-Criteria Decision Making Process
Authors: Joshi Bhagawati Prasad
Published: May 2018

The aggregation operators play an important role in the fusion of multidimensional information in decision making process. In this study, a series of generalized aggregation operators such as: the generalized intuitionistic fuzzy weighted geometric (GIFWG) operator, the generalized intuitionistic fuzzy ordered weighted geometric (GIFOWG) operator and the generalized intuitionistic fuzzy hybrid geometric (GIHG) operator are proposed under intuitionistic fuzzy environment by controlling the power of the argument values with an additional parameter p. Some of the important properties and some special cases of these operators are also included in this study. Further, the developed approach is utilized to deal with multi-criteria decision making (MCDM) problems. Numerical examples are constructed to illustrate the developed approach effectively.
Object-Oriented Cognitive Complexity Measures
Authors: Misra Sanjay , Adewumi Adewole
Published: May 2018

This chapter presents the analysis of ten recently proposed object-oriented metrics based on cognitive informatics. The metrics based on cognitive informatics use cognitive weight. Cognitive weight is the representation of the understandability of the piece of software that evaluates the difficulty experienced in comprehending and/or performing the piece of software. Development of metrics based on Cognitive Informatics (CI) is a new area of research, and from this point of view, for the analysis of these metrics, it is important to know their acceptability from other existing evaluation and validation criteria. This chapter presents a critical review on existing object-oriented cognitive complexity measures. In addition, a comparative study based on some selected attributes is presented.
Intelligent Control of Vehicles' Number Plates on Toll Gates in Developing Nations
Authors: Mushiri Tawanda , Mbohwa Charles , Sarupinda Simbarashe
Published: May 2018

Developing nations have implemented toll gates in their countries major trunk highways as a move towards the improvement in fiscal levels. However, several problems have arisen in the toll collection system that has been implemented. The system exists as an incomplete system in comparison to internationally acclaimed systems and methods. This chapter therefore seeks to introduce an automated toll collection system which has enhanced security features and intelligent vehicle classification methods. Utilising machine intelligence and computer vision methods in the system, the researchers intend to develop the automated and intelligent toll collection system for developing nation's tollgates. The mechatronic system will combat security loopholes and enhance the efficiency of the toll collection process.
A Sequential Probabilistic System for Bankruptcy Data Classification
Authors: Lahmiri Salim , Gagnon Stéphane
Published: May 2018

In the last decade, the development of bankruptcy prediction models has been one of important issues in accounting and corporate finance research fields. Indeed, bankruptcy is a critical event that yields important loss to management, shareholders, employees, and also to government. Statistical methods such as discriminant analysis, logistic and probit models were widely used for developing bankruptcy prediction systems. However, statistical-based approaches are assumes strong assumptions including linearity of the relationship among dependent and independent variables, normality of the errors which limit their applicability in bankruptcy real world problems. Recently, machine learning and soft computing techniques including artificial neural networks, support vector machines, and evolutionary intelligence have brought forth new alternatives in solving nonlinear problems with applications in bankruptcy prediction. The purpose of this chapter is to present a sequential probabilistic system for bankruptcy data classification to help manager in making decisions.
Using a Knapsack Model to Optimize Continuous Building of a Hybrid Intelligent Tutoring System
Authors: Khemaja Maha
Published: May 2018

Intelligent Tutoring Systems (ITS) provide an alternative to the traditional “one size fits all” approach. Their main aim is to adapt learning content, activities and paths to support learners. Meanwhile, during the last decades, advances in lightweight, portable devices and wireless technologies had drastically impacted Mobile and Ubiquitous environments' development which has driven opportunities towards more personalized, context-aware and dynamic learning processes. Moreover, mobile and hand held devices could be advantageous to incremental learning, based on very short and fine grained activities and resources delivery. However, measuring efficiency and providing the most relevant combination/orchestration of learning activities, resources and paths remains and open and challenging problem especially for enterprises where choices and decisions face several constraints as time, budget, targeted core competencies, etc. This paper, attempts to provide a knapsack based model and solution in order to implement ITS's intelligent decision making about best combination and delivery of e-training activities and resources especially in the context of fast changing Information and Communication Technology (ICT) domain and its required skills. An android and OSGi based prototype is implemented to validate the proposal through some realistic use cases.
A Differential Evolution Based Multiclass Vehicle Detector and Classifier for Urban Environments
Authors: Dawar Deepak , Ludwig Simone A.
Published: May 2018

Video analytics is emerging as a high potential area supplementing intelligent transportation systems (ITSs) with wide ranging applications from traffic flow analysis to surveillance. Object detection and classification, as a sub part of a video analytical system, could potentially help transportation agencies to analyze and respond to traffic incidents in real time, plan for possible future cascading events, or use the classification data to design better roads. This work presents a specialized vehicle classification system for urban environments. The system is targeted at the analysis of vehicles, especially trucks, in urban two lane traffic, to empower local transportation agencies to decide on the road width and thickness. The main thrust is on the accurate classification of the vehicles detected using an evolutionary algorithm. The detector is backed by a differential evolution (DE) based discrete parameter optimizer. The authors show that, though employing DE proves expensive in terms of computational cycles, it measurably improves the accuracy of the classification system.
High Order Time Series Forecasting Using Fuzzy Discretization
Authors: Bose Mahua , Mali Kalyani
Published: May 2018

In recent years, various methods for forecasting fuzzy time series have been presented in different areas, such as stock price, enrollments, weather, production etc. It is observed that in most of the cases, static length of intervals/equal length of interval has been used. Length of the interval has significant role on forecasting accuracy. The objective of this present study is to incorporate the idea of fuzzy discretization into interval creation and examine the effect of positional information of elements within a group or interval to the forecast. This idea outperforms the existing high order forecast methods using fixed interval. Experiments are carried on three datasets including Lahi production data, enrollment data and rainfall data which deal with a lot of uncertainty.
Application of DEMATEL and MMDE for Analyzing Key Influencing Factors Relevant to Selection of Supply Chain Coordination Schemes
Authors: Behera Pradeep Kumar , Mukherjee Kampan
Published: May 2018

Any selection decision of supply chain coordination schemes (SCCS) is essentially affected by the environment where the schemes are to be implemented, the necessary conditions required for their implementation, the risk associated with the implementation, and the impact on the performance of the supply chain. Because of the multi-dimensional characteristics; the selection of appropriate SCCS in a given situation remains a challenging task for supply chain managers. This study explores relevant factors that influence this selection process. A structural model is proposed to capture relationships among these factors for development of Impact Relationship Maps (IRM) by applying Decision Making Trial and Evaluation Laboratory (DEMATEL) and Maximum Mean De-Entropy (MMDE) algorithm. A study has been conducted and the outcome leads to add significant value to the decision making process with knowledge on the roles of the factors and inter-factor relations which helps in taking meaningful decision on SCCS selection and implementation.
A Semantic Approach for Multi-Agent System Design
Authors: Girardi Rosario , Leite Adriana
Published: May 2018

Automating software engineering tasks is crucial to achieve better productivity of software development and quality of software products. Knowledge engineering approaches this challenge by supporting the representation and reuse of knowledge of how and when to perform a development task. Therefore, knowledge tools for software engineering can turn more effective the software development process by automating and controlling consistency of modeling tasks and code generation. This chapter introduces the description of the domain and application design phases of MADAE-Pro, an ontology-driven process for agent-oriented development, along with how reuse is performed between these sub-processes. Two case studies have been conducted to evaluate MADAE-Pro from which some examples of the domain and application design phases have been extracted and presented in this chapter. The first case study assesses the Multi-Agent Domain Design sub-process of MADAE-Pro through the design of a multi-agent system family of recommender systems supporting alternative (collaborative, content-based, and hybrid) filtering techniques. The second one evaluates the Multi-Agent Application Design sub-process of MADAE-Pro through the design of InfoTrib, a Tax Law recommender system that provides recommendations based on new tax law information items using a content-based filtering technique.
A Novel Approach to Segmentation Using Customer Locations Data and Intelligent Techniques
Authors: Öztayşi Başar , Gokdere Ugur , Simsek Esra Nur , Oner Ceren Salkin
Published: May 2018

Customer segmentation has been one of hottest topics of marketing efforts. The traditional sources of data used for segmentation are demographics, monetary value of transactions, types of product/service selected. Today, data gathered by location based services can also be used for customer segmentation. In this chapter a real world case study is summarized and the initial segmentation results are presented. As the application, data gathered from beacons sited in 4000 locations and Fuzzy c-means clustering algorithm are used. The steps of the application are as follows: (1) Categorization of the shops, (2) Summarization of the location data, (3) Applying fuzzy clustering technique, (4) Analyzing the results and profiling. Results show that customers' location data can provide a new perspective to customer segmentation.
Assessing Organizational Readiness for Implementing ERP System Using Fuzzy Expert System Approach
Authors: Hajilari Amir Beirami , Ghadaksaz Mahsa , Fasghandis Gholamreza Soltani
Published: May 2018

Efficient use of enterprise resource planning systems is the only way to achieve competitive advantage in many industries. However, many reports indicate high failure rate of ERP implementation projects and the lack of access to benefits and advantages that enterprises have expected from ERP deployment. Managers are concerned about being ready to deploy such a system. Despite its enormous cost, implementing enterprise resource planning systems fail in practice. Accordingly, this study aims at providing a model for assessing the readiness of organizations for the implementation of ERP by using fuzzy expert systems. The model is composed of six fuzzy expert systems which are designed at two levels. The first five levels are the factors affecting the readiness of a system to produce the scores for an output. These outputs have been used as input to the final system for assessing the organization's readiness to implement the ERP system. In the design of each fuzzy expert system, fuzzy triangular membership functions were applied that had been selected for increasing the efficiency and ease of use. The Results of the model and its use in Shahid Ghazi Pharmaceutical Company show the status of readiness of the proposed model for ERP implementation. Moreover, the model shows the status of the organizations with regard to each of the factors affecting the implementation of the ERP system.