bluuebunny/crossref_metadata_2025 huggingface dataset:
Collaborative Writing 2.0
Authors: Martínez-Carrasco Robert
Published: May 2018

Technology-enhanced language learning has broadened the horizons of collaboration in the L2 classroom. At the same time, it has brought the cultural component closer, enriching the overall picture for students when learning a foreign language. This highlights the need for students to develop solid cross-cultural skills regarding the meaning negotiation processes underlying the discursive practices of their respective L2 communities. Only by acknowledging the referential, semiological nature of language and understanding cultural practices in situated terms may students be truly socialized in their L2. This study explores the perception of students regarding wiki-based collaborative writing as a resource in the L2 classroom while paying special attention to the treatment of culture specific elements that may hinder effective cross-cultural communication in their L2.
Towards a New Model for Causal Reasoning in Expert Systems
Authors: Wright M. Keith
Published: May 2018

This paper presents ideas for improved conditional probability assessment and improved expert systems consultations. It cautions that knowledge engineers may sometimes be imprecise when capturing causal information from experts: their elicitation questions may not distinguish between causal and correlational expertise. This paper shows why and how such models cannot support normative inferencing over conditional probabilities as if they were all based on frequencies in the long run. In some cases, these probabilities are instead causal theory-based judgments, and therefore are not traditional conditional probabilities. This paper argues that these should be processed as if they were causal strength probabilities or causal propensity probabilities. This paper reviews the literature on causal and probability judgment, and then presents a probabilistic inferencing model that integrates theory-based causal probabilities with frequency-based conditional probabilities. The paper also proposes guidelines for elicitation questions that knowledge engineers may use to avoid conflating causal theory-based judgment with frequency based judgment.
Fuzzy Social Network Modeling for Influencing Consumer Behavior
Authors: Yager Ronald R. , Yager Rachel L.
Published: May 2018

Social networks have become an important component in most companies' bag of tools for managing and influencing consumer behavior. It is imperative for modern organizations to fully understand these social networks and have at their disposal an armada of tools to intelligently model and manipulate these complex structures in order to accomplish their goals. In order to most effectively and intelligently use social networks, decision makers and planners must be able to bring to bear their expertise, experience, and professional intuition on issues involving these networks. This requires an understanding, comprehension, and view of social networks that is compatible with their human cognition and perception. They must be able to understand the structure and dynamics of social networks in terms of human-focused concepts. In this chapter, the authors investigate and describe the use of the FISNA technology to help in the modeling of consumer behavior-related concepts in social networks.
A Framework of Statistical and Visualization Techniques for Missing Data Analysis in Software Cost Estimation
Authors: Angelis Lefteris , Mittas Nikolaos , Chatzipetrou Panagiota
Published: May 2018

Software Cost Estimation (SCE) is a critical phase in software development projects. However, due to the growing complexity of the software itself, a common problem in building software cost models is that the available datasets contain lots of missing categorical data. The purpose of this chapter is to show how a framework of statistical, computational, and visualization techniques can be used to evaluate and compare the effect of missing data techniques on the accuracy of cost estimation models. Hence, the authors use five missing data techniques: Multinomial Logistic Regression, Listwise Deletion, Mean Imputation, Expectation Maximization, and Regression Imputation. The evaluation and the comparisons are conducted using Regression Error Characteristic curves, which provide visual comparison of different prediction models, and Regression Error Operating Curves, which examine predictive power of models with respect to under- or over-estimation.
A Soft Computing Approach to Customer Segmentation
Authors: Hiziroglu Abdulkadir
Published: May 2018

There are a number of traditional models designed to segment customers, however none of them have the ability to establish non-strict customer segments. One crucial area that can meet this requirement is known as soft computing. Although there have been studies related to the usage of soft computing techniques for segmentation, they are not based on the effective two-stage methodology. The aim of this study is to propose a two-stage segmentation model based on soft computing using the purchasing behaviours of customers in a data mining framework and to make a comparison of the proposed model with a traditional two-stage segmentation model. Segmentation was performed via neuro-fuzzy two stage-clustering approach for a secondary data set, which included more than 300,000 unique customer records, from a UK retail company. The findings indicated that the model provided stronger insights and has greater managerial implications in comparison with the traditional two-stage method with respect to six segmentation effectiveness indicators.
A Proposed Pragmatic Software Development Process Model
Authors: Misra Sanjay , Omorodion M. , Mishra Amit , Fernandez Luis
Published: May 2018

The rapid growth in technology and the dynamism in our society today poses a lot of problems for Software Engineering practitioners. The result is a series of software development process methods that can be used to combat or meet up with the problems. What we can do is evolve, grow, and adapt to the changes that come along with development. This is the dynamism inherent in man—to adapt to change and improve ourselves and our existing systems—since the world is a far cry from what it was a few decades ago. On this basis lay the need to develop the model proposed in this chapter to meet the variations that exist as a result of technological development.
An Integrated Grey Relations Analysis and VIKOR Method for Multi Criteria Decision Making Under Fuzzy Environment
Authors: Selvi Ihsan Hakan , Torkul Orhan , Cedimoglu Ismail Hakki
Published: May 2018

Today, suppliers of companies are no longer local. Companies have to offer their products to the market just in time and as fast as possible in order to compete. This situation is possible by establishing an effective supply chain for the goods and services they need in the manufacturing system. Finding the right suppliers who are able to provide the companies with the high quality products and services at the reasonable price, at just on time and in the right quantities is an important issue concerned in the process of supply chains concept. There are certain techniques developed in this respect. Some of such methods are approaches developed for situations unmindful of fuzziness and vagueness. Nonetheless, the process of supplier selection contains both vagueness and fuzziness. This study improves the Grey Relational Analysis and VIKOR methods, to fuzzy and ambiguous environments. Then, these approaches are applied to a supplier selection problem, which is previously solved through fuzzy logic and AHP method in literature, and the comparative results of both techniques are given.
Modeling Gender Based Customer Preferences of Information Search Channels
Authors: Khatwani Gaurav , Srivastava Praveen Ranjan
Published: May 2018

The disparity in consumer and organization preferences of information channels is a major concern. Further, making decisions in the presence of a wide range of conflicting criteria through the use of a multiple criteria decision-making (MCDM) approach has gained increased prominence in recent years and research in this area has become an important consideration for business operations that involve dealing with complex decision problems. This paper describes how an integrated approach can be applied to a decision-making problem that combines a fuzzy analytical hierarchy process (AHP) and TOPSIS for identifying preferences consumers of information search channels according to demographic factors such as gender.
A Combined Fuzzy Method for Evaluating Criteria in Enterprise Resource Planning Implementation
Authors: Hamidi Hodjatollah
Published: May 2018

Enterprise resource planning (ERP) system is an information system that supports and integrates many facets of a business, sales, and marketing. ERP system success depends on the rigor of the ERP Implementation processes. Scope creep, inadequate allocation of human resources over time, and vendor management are some common problems associated with the implementation of an enterprise system. This paper evaluates critical elements of ERP system that contributed to the success of the ERP implementation. For those organizations adopting ERP, the findings provide a roadmap to follow in order to avoid making critical, ERP Implementation mistakes. In this study, the combined fuzzy method is applied to assess ERP implementation factors. The combined fuzzy method is also capable of taking into consideration both tangible and intangible criteria. This method not only leads to a logical result but also visualizes the impact of various criteria on the final result. Applying the characteristics of dependence and feedback to combined fuzzy method could result in assessments that are more precise than those possible with other multiple criteria decision making approaches. The combined fuzzy method provides a useful assessment approach to this study. The benefits of using the combined fuzzy method for evaluating the ERP implementation come from the clear priority weights between alternatives. Also, a real case study from Iran is also presented to demonstrate efficiency of this method in practice.
Fuzzy Structural Models and Based Applications in Digital Marketplace
Authors: Kumar Anil , Dash Manoj Kumar
Published: May 2018

One of the well-known topics of decision making is Multi-Criteria Decision Making (MCDM). Fuzzy set theory helps to provide a useful way to address a MCDM problem. Without models, MCDM methods cannot be practiced effectively, therefore, it is interesting to clarify the structure among criteria. But the shortcoming of MCDM is unable to capture imprecision or vagueness inherent in the information. Fuzzy set theory has great potential to handle such situations and fuzzy structural models have been developed. In this chapter widely used structural models i.e. Interpretive Structural Modeling (ISM), Decision Making Trial and Evaluation Laboratory (DEMATEL), and Cognition Maps (CMs) are first summarized briefly along with their mathematical formulation and then diffusion these models into fuzzy set theory is explained along with a literature review of the based applications of these models in the digital marketplace.
Design of Intelligent Transportation System Supported by New Generation Wireless Communication Technology
Authors: Yang Wenli , Wang Xiaojing , Song Xianghui , Yang Yun , Patnaik Srikanta
Published: May 2018

The development of Intelligent Transportation System (ITS) will transition into a next level development of variously new requirements coupled with the new generation wireless communication technology. In this paper, the process-oriented structured system analysis is extended on the existing intelligent transportation architecture to establish an intelligent transportation system based on the new generation wireless communication technology, and further in-depth analysis will be performed to discuss the required additional capabilities of network, services and application support in the view of user, function, information, connection and communication. In order to comprehensively understand the technical characteristics and development of the new generation intelligent transportation system, it lays a foundation for implementation of the new generation ITS technology.
Modeling and Performance Enhancement of Low-Frequency Energy Harvesters
Authors: Abdelkefi Abdessattar
Published: May 2018

There exist numerous low-frequency excitation sources, such as walking, breathing, and ocean waves, capable of providing viable amounts of mechanical energy to power many critical devices, including pacemakers, cell phones, MEMS devices, wireless sensors, and actuators. Harvesting significant energy levels from such sources can only be achieved through the design of devices capable of performing effective energy transfer mechanisms over low frequencies. In this chapter, two concepts of efficient low-frequency piezoelectric energy harvesters are presented, namely, variable-shaped piezoelectric energy harvesters and piezomagnetoelastic energy harvesters. Linear and nonlinear electromechanical models are developed and validated in this chapter. The results show that the quadratic shape can yield up to two times the energy harvested by a rectangular one. It is also demonstrated that depending on the available excitation frequency, an enhanced energy harvester can be tuned and optimized by changing the length of the piezoelectric material or by changing the distance between the two tip magnets.
Position and Tilt Control of Two-Wheeled Robot (TWR)
Authors: Kharola Ashwani , Patil Pravin P.
Published: May 2018

This paper presents a fuzzy based adaptive control approach for stabilization of Two wheeled robot (TWR) system. The TWR consists of a robot chassis mounted on two movable wheels. The objective is to stabilize the proposed system within desired time, minimum overshoot and at desired location. The data samples collected from simulation results of fuzzy controllers were used for training, tuning and optimisation of an adaptive neuro fuzzy inference system(ANFIS) controller. A Matlab Simulink model of the system has been built using Newton's second law of motion. The effect of shape and number of membership functions on training error of ANFIS has also been analysed. The designing of fuzzy rules for both fuzzy and ANFIS controller were carried out using gbell shape memberships. Simulations were performed which compared and validated the performance of both the controllers.
A Classification Framework on Opinion Mining for Effective Recommendation Systems
Authors: Goyal Mahima , Bhatnagar Vishal
Published: May 2018

With the recent trend of expressing opinions on the social media platforms like Twitter, Blogs, Reviews etc., a large amount of data is available for the analysis in the form of opinion mining. This analysis plays pivotal role in providing recommendation for ecommerce products, services and social networks, forecasting market movements and competition among businesses, etc. The authors present a literature review about the different techniques and applications of this field. The primary techniques can be classified into Data Mining methods, Natural Language Processing (NLP) and Machine learning algorithms. A classification framework is designed to depict the three levels of opinion mining –document level, Sentence Level and Aspect Level along with the methods involved in it. A system can be recommended on the basis of content based and collaborative filtering
iTrade
Authors: Hu Yong , Zhang Xiangzhou , Feng Bin , Xie Kang , Liu Mei
Published: May 2018

Among all investors in the Chinese stock market, more than 95% are non-professional individual investors. These individual investors are in great need of mobile apps that can provide professional and handy trading analysis and decision support everywhere. However, financial data is challenging to analyze because of its large-scale, non-linear and noisy characteristics in a varying stock environment. This paper develops a Mobile Data-Driven Stock Trading System (iTrade), which is a mobile app system based on Client-Server architecture and various data mining techniques. The iTrade is characterized by 1) a data-driven intelligent learning model, which can provide further insight compared to empirical technical analysis, 2) a concept drift adaptation process, which facilitates the model adaptation to market structure changes, and 3) a rigorous benchmark analysis, including the Buy-and-Hold strategy and the strategies of three world-famous master investors (e.g., Warren E. Buffett). Technologies used in iTrade include the Least Absolute Shrinkage and Selection Operator (Lasso) algorithm, Support Vector Machine (SVM) and risk-adjusted portfolio optimization. An application case of iTrade is presented, which is based on a seven-year (2005-2011) back-testing. Evaluation results indicated that iTrade could gain much higher cumulative return compared to the benchmark (Shanghai Composite Index). To the best of our knowledge, this is the first study and mobile app system that emphasizes and investigates the concept drift phenomenon in stock market, as well as the performance comparison between data-driven intelligent model and strategies of master investors.
An Integrated Fuzzy VIKOR Method for Performance Management in Healthcare
Authors: Shekarian Ehsan , Abdul-Rashid Salwa Hanim , Olugu Ezutah Udoncy
Published: May 2018

Poor quality control has become a major threat to medical laboratory services, especially in the developing countries. It has become necessary to assess and rank the quality of diagnostic services in medical laboratories using systematic approaches. The main aim of this research is to develop and apply a quantitative method in ranking medical laboratory services. This method is based on a combination of Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) with fuzzy set theory. VIKOR is a multiple criteria decision making technique which focuses on ranking and selection from a set of alternatives, and determines the compromise solution for a problem with different criteria. This approach aids decision makers to achieve the most acceptable decision amidst numerous alternatives. In the present evaluation method, international standard ISO 15189 (Medical Laboratories Particular Requirements for Quality and Competence) proposed by International Organization for Standardization (ISO) is used as a fundamental source of selected attributes of a medical laboratory. The study compares three medical laboratories to each other and ranks them. This study will be a valuable and effective contribution in enhancing both qualitative and quantitative criteria in the field of medical laboratory services. Finally, some directions for further studies are proposed.
Applying an Electromagnetism-Like Algorithm for Solving the Manufacturing Cell Design Problem
Authors: Lanza-Gutierrez Jose M. , Soto Ricardo , Crawford Broderick , Gomez-Pulido Juan A. , Fernandez Nicolas , Castillo Carlos
Published: May 2018

Group technology has acquired a great consideration in the last years. This technique allows including the advantages of serial production to any manufacturing industry by dividing a manufacturing plant into a set of machine-part cells. The identification and formation of the cells are known as the Manufacturing Cell Design Problem (MCDP), which is an NP-hard problem. In this paper, the authors propose to solve the problem through a swarm intelligence metaheuristic called ElectroMagnetism-like (EM-like) algorithm, which is inspired by the attraction-repulsion mechanism of particles in the context of the electromagnetic theory. The original EM-like algorithm was designed for solving continuous optimization problems, while the MCDP is usually formulated by assuming a binary approach. Hence, the authors propose an adaptation of this algorithm for addressing the problem. Such adaptation is applied for solving a freely available dataset of the MCDP, obtaining competitive results compared to recent approaches.
Automated Generation of Course Improvement Plans Using Expert System
Authors: Imam Muhammad Hasan , Tasadduq Imran Ali , Ahmad Abdul-Rahim , Aldosari Fahd , Khan Haris
Published: May 2018

To satisfy ABET's continuous improvement criterion, an instructor, teaching a course suggests, at the end of the course, an improvement plan to be implemented when the same course is taught next time. Preparation of such a course improvement plan may be mandatory if a pre-specified target level of students' learning is not attained. Since, manual preparation of a course improvement plan is difficult, an idea of generating it using an expert system is presented. The objective is to make the task of improvement plan preparation easier and enjoyable. The proposed expert system has a set of remedies and a set of rules in a data base. A web-based interface queries the instructor about teaching and assessment tools used in the course. The inference engine selects the most appropriate remedy based on instructor's preferences. A cloud implementation of the expert system has been used to test it for a course.
On Design and Development of QLIFEX
Authors: Atanasova Irena
Published: May 2018

This article presents an architectural framework of an expert system in the social area domain, and describes the design and the process of development of the expert system. The designed system is intended for the evaluation of quality of life (QL). The development of expert system for quality of life evaluation is a new information technology derived from artificial intelligence research. The new expert system will contain knowledge about sets of factors and indicators, which may be used for quality of life measure, as followings: equal protection by the law; freedom from discrimination; right to be treated equally without regard to gender, race, language, religion, political beliefs, etc. Details of the expert system for quality of life evaluation, its basic modules, design and some implementation details are also explained. The system uses the vast database and the knowledge acquired from social experts. The system is being developed in C Language Integrated Production System CLIPS. The expert system, described in this paper, is called QLIFEX, and it has already been designed so it uses the same knowledge for the following function: to provide expert evaluation for quality of life in the social area. The knowledge for the expert system will be acquired from domain experts, texts and other related sources.
Expert Systems in Distance Education
Authors: Mutlu-Bayraktar Duygu , Esgin Esad
Published: May 2018

Computers have been used in educational environments to carry out applications that need expertise, such as compiling, storing, presentation, and evaluation of information. In some teaching environments that need expert knowledge, capturing and imitating the knowledge of the expert in an artificial environment and utilizing computer systems that have the ability to communicate with people using natural language might reduce the need for the expert and provide fast results. Expert systems are a study area of artificial intelligence and can be defined as computer systems that can approach a problem for which an answer is being sought like an expert and present solution recommendations. In this chapter, the definition of expert systems and their characteristics, information about the expert systems in teaching environments, and especially their utilization in distance education are given.
Designing a Compact Wireless Network Based Device-Free Passive Localisation System for Indoor Environments
Authors: Vance Philip , Prasad Girijesh , Harkin Jim , Curran Kevin
Published: May 2018

Determining the location of individuals within indoor locations can be useful in various scenarios including security, gaming and ambient assisted living for the elderly. Healthcare services globally are seeking to allow people to stay in their familiar home environments longer due to the multitude of benefits associated with living in non-clinical environments and technologies to determine an individual's movements are key to ensuring that home emergencies are detected through lack of movement can be responded to promptly. This paper proposes a device-free localisation (DFL) system which would enable the individual to proceed with normal daily activities without the concern of having to wear a traceable device. The principle behind this is that the human body absorbs/reflects the radio signal being transmitted from a transmitter to one or more receiving stations. The proposed system design procedure facilitates the use of a minimum number of wireless nodes with the help of a principle component analysis (PCA) based intelligent signal processing technique. Results demonstrate that human detection and tracking are possible to within 1m resolution with a minimal hardware infrastructure.
Utilization of Classification Techniques for the Determination of Liquefaction Susceptibility of Soils
Authors: Jagan J. , Gundlapalli Prabhakar , Samui Pijush
Published: May 2018

The determination of liquefaction susceptibility of soil is a paramount project in geotechnical earthquake engineering. This chapter adopts Support Vector Machine (SVM), Relevance Vector Machine (RVM) and Least Square Support Vector Machine (LSSVM) for determination of liquefaction susceptibility based on Cone Penetration Test (CPT) from Chi-Chi earthquake. Input variables of SVM, RVM and LSSVM are Cone Resistance (qc) and Peak Ground Acceleration (amax/g). SVM, RVM and LSSVM have been used as classification tools. The developed SVM, RVM and LSSVM give equations for determination of liquefaction susceptibility of soil. The comparison between the developed models has been carried out. The results show that SVM, RVM and LSSVM are the robust models for determination of liquefaction susceptibility of soil.
Using Hybrid Classifiers to Conduct Intangible Assets Evaluation
Authors: Lu Yu-Hsin , Lin Yu-Cheng
Published: May 2018

Traditional financial reporting usually ignores intangible assets, even though these assets play an increasingly important role in today's knowledge-based economy. As such, the valuation of intangible assets, while typically overlooked in traditional reporting, has nonetheless garnered widespread interest. This paper uses data-mining technologies to identify important valuation factors and to determine an optimal valuation model. In the feature selection process, the paper focus on three methods, namely, decision trees, association rules, and genetic algorithms in data mining, to identify important valuation factors. The results show that decision trees have approximately 75% prediction accuracy and select seven critical variables. In the prediction process, the paper constructs and compares many kinds of evaluation and prediction models. The results show that hybrid classifiers (i.e., k-means + k-NN) perform best in terms of prediction accuracy (91.52%), Type I and II errors (11.17% and 7.15%, respectively), and area under ROC curve (0.908).
Credit Risk Evaluation Based on Text Analysis
Authors: Wang Shuxia , Qi Yuwei , Fu Bin , Liu Hongzhi
Published: May 2018

The main difficulty of credit risk evaluation is to evaluate borrowers' willingness of repayment, which is a subjective factor depending on the thoughts and ideas of borrowers. Text description is a kind of human behavior which reflects the mental process of writers. The authors identify the characteristics of borrowers from their text descriptions and further use them to evaluate the credit risk of loans. Experimental results show that: (1) textual information is a good choice when traditional financial information is missing. The authors can achieve similar accuracy using only textual information as traditional methods which use financial information and credit information from the third party. (2) Textual information is a good complementary information source to traditional financial information sources. Using textual information can improve the performance of credit risk evaluation system when combined with traditional financial information.
Diagnosis of Liver Disease by Using Least Squares Support Vector Machine Approach
Authors: Singh Aman , Pandey Babita
Published: May 2018

A healthy liver leads to healthy life. In India, as well as in other parts of the world, liver disease is one of the principle areas of concern in medicine. For this study, diagnosis of liver disease is performed by deploying classification methods include linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), feed-forward neural network (FFNN) and support vector machine (SVM) based approaches. Experimental results concluded that SVM based approaches outperformed all other classification methods in terms of diagnostic accuracy rates. Furthermore, least squares support vector machine (LSSVM) with gaussian radial basis kernel function based machine learning approach had emerged as the as the best predictive model by reducing inefficiencies caused by false diagnosis. LSSVM also performed better than linear SVM, polynomial SVM, quadratic SVM and multilayer perceptron SVM despite the uneven variance in attribute values in the health examination data.
Resolving the Paradox of Overconfident Students With Intelligent Methods
Authors: Smolin Denis , Butakov Sergey
Published: May 2018

The chapter presents a case study of using data mining tools to solve the puzzle of inconsistency between students' in-class performance and the results of the final tests. Classical test theory cannot explain such inconsistency, while the classification tree generated by one of the well-known data mining algorithms has provided reasonable explanation, which was confirmed by course exit interviews. The experimental results could be used as a case study of implementing Artificial Intelligence-based methods to analyze course results. Such analyses equip educators with an additional tool that allows closing the loop between assessment results and course content and arrangements.
Decision-Making Support Systems in Quality Management of Higher Education Institutions
Authors: Mora Manuel , Wang Fen , Gómez Jorge Marx , Rainsinghani Mahesh S. , Shevchenko Valentyna Savkova Taras
Published: May 2018

The provision of high-quality educational services is a mandatory objective for Higher Education Institutions (HEIs) nowadays. Consequently, HEIs implement Quality Management System (QMS) process frameworks. A core managerial activity conducted in these QMS is decision making, which impacts the overall quality of the provided HEI's educational services. This managerial context found in HEIs demands an adequate and reliable managerial decision-making support. In this article, we elaborate a new Process-Task-Decision scheme for HEIs based on a relevant international QMS process framework (ISO 9001 IWA 2:2007), and we survey selectively DMSS and HEI literature in the 1996-2016 period. We found that DMSS have been used in a variety of Process-Task-Decision situations in HEIs from early periods to the present, but their utilization is still scarce and partially deployed. Thus, open opportunities to apply them in HEIs and relevant knowledge gaps still exist to be further researched.
A Comprehensive Workflow for Enhancing Business Bankruptcy Prediction
Authors: Sarmento Rui , Trigo Luís , Fonseca Liliana
Published: May 2018

Forecasting enterprise bankruptcy is a critical area for Business Intelligence. It is a major concern for investors and credit institutions on risk analysis. It may also enable the sustainability assessment of critical suppliers and clients, as well as competitors and the business environment. Data Mining may deliver a faster and more precise insight about this issue. Widespread software tools offer a broad spectrum of Artificial Intelligence algorithms and the most difficult task may be the decision of selecting that algorithm. Trying to find an answer for this decision in the relatively large amount of available literature in this area with so many options, advantages, and pitfalls may be as informative as distracting. In this chapter, the authors present an empirical study with a comprehensive Knowledge Discovery and Data Mining (KDD) workflow. The proposed classifier selection automation selects an algorithm that has better prediction performance than the most widely documented in the literature.
A Strategic Approach to Global Financial Crisis in Banking Sector
Authors: Dinçer Hasan , Hacıoğlu Ümit , Yüksel Serhat
Published: May 2018

Financial crisis affected many people and companies in the world negatively in terms of job loss and bankruptcy. Owing to this aspect, today many banks developed strategies in order to minimize the effects of any potential crisis which might be occurred in the future. Present study aims to evaluate the strategies of Turkish banks to minimize the effects of financial crisis by using fuzzy ANP and fuzzy TOPSIS methods. The study identifies that capital injection is the most significant strategy whereas the strategy of decreasing interest rate has the weakest importance. In addition to this aspect, it was also determined that privately-owned banks are the most successful banking group of Turkey with respect to the achievement of strategic goals during a financial crisis. On the other hand, state-owned banks have the lowest degree regarding this concept. The study recommends that Turkish banks should mainly focus on increasing capital amount in order to minimize the negative aspects of the crisis
Modelling and Simulation Perspective in Service Design
Authors: Dragoicea Monica , Falcao e Cunha Joao , Alexandru Monica Viorela , Constantinescu Denisa Andreea
Published: May 2018

This chapter discusses the development of improved citizen services taking into consideration integration of agent-based modelling and simulation experience into conceiving, design and implementation activities with a strong focus on technology enabled service systems. Service design is formalized here towards the integration of customer experience, validated through service interaction modelling. Integration of user experience at design stage in the value co-creation process is a possible immediate evolution direction of projects in the Smarter Cities perspective. Guidelines for integrating a modelling and simulation perspective in service design are presented along with the Socio-Technical Systems Engineering process. The case study presented here is dedicated to Smart Transport. The chapter opens a larger discussion on specific research directions and knowledge transfer related to Smart Transport as highlighted in EU projects.
Growth of Census Towns in Capital Region of India
Authors: Jain Manisha , Knieling Jörg
Published: May 2018

Managing urban growth has become one of the important challenges of the 21st century in the Global South, where agglomerations are being formed by the coalescence of urban and rural areas. The scale and speed of transformation have outstripped the capacity of local governments to provide adequate basic amenities. Using the National Capital Region as a case study, and census data and spatial boundaries, this chapter attempts to understand the process of urbanization underway in India. Results show that the region is currently in the stage of sub-urbanization, and that recent growth has been predominantly in ‘census towns' as informal urbanization. Three main reforms are required to achieve sustainable urbanization: First, integration of infrastructure development into spatial planning at the national level and in lower tiers of planning. Second, empowering local authorities to incentivize urban development in order to fund urban infrastructure. Third, notifying census towns with municipalities, thereby providing for urban infrastructure and controlling unplanned growth.
Urban Master Data Management
Authors: Eteme Adolphe Ayissi , Ngossaha Justin Moskolai
Published: May 2018

The use of information technology in council management has resulted in the generation of a large amount of data through various autonomous urban bodies. The relevant bodies barely or never reuse such locally-generated data. This may be due particularly to managers', policy makers' and users' lack of awareness of existing information. The Platform for the Integration and Interoperability of the Yaounde Urban Information Systems (YUSIIP) project seeks to reduce this deficit by establishing a federated operational platform of heterogeneous and distributed data systems based on a distributed data repository. The position developed in this paper is that Master Data Management (MDM) will contribute to achieving this objective in a context marked by the dispersion and duplication of data and diversity of information systems.
Achieving Sustainable Cities in Saudi Arabia
Authors: Abubakar Ismaila Rimi , Aina Yusuf Adedoyin
Published: May 2018

This chapter highlights the challenges of rapid urbanization in Saudi Arabia and the implications of its burgeoning urban population on urban sustainability. The first section of the chapter reviews the trend of urbanization in the Third World, and Saudi Arabia in particular, and the factors responsible for rapid urban growth. The second section critically analyzes major urbanization challenges in Saudi Arabia and their impacts on the people and the environment. The final section assesses the extent to which some sustainability initiatives being implemented by the government are meeting the competing and sometimes conflicting urbanization challenges. The chapter concludes with some policy implications.
Revisiting Urban Theories
Authors: Benna Umar , Benna Indo
Published: May 2018

Urban theory has been dominated by the accumulation of social theories and has significant impact on global urbanization. The urban is becoming more complex and more global due to the contesting technological, political, social, economic and environmental forces. These disciplinary forces may be added to the global shifts in population and political power from rural to urban and from the developed to the developing nations, creating new global challenges. To cope with these challenges, the prevailing urban theories need a shift. By critically revisiting urban theories and testing them against emerging challenges, this chapter is advocating for and pointing to a new direction. The chapter revisits urban sociological theories, those global theories advocating planetary urbanization, the models responding to glocal forces as well as those promoting world systems. This is followed by an outline of the proposal for Activity Theoretical Framework. Possible future research direction for the inclusive and universal urbanization is identified.
Indicator Modelling and Interactive Visualisation for Urban Sustainability Assessment
Authors: Falconer Ruth E. , Isaacs John P. , Gilmour Daniel , Blackwood David J.
Published: May 2018

This chapter presents a novel framework for the integration of the principles of sustainable development within the urban design processes. The framework recognises that decision making for sustainable urban planning is a challenging process: requiring an understanding of the complex interactions amongst environmental, economic, and social issues. Methodologies are required that would support non-experts to become more involved in the urban design process. Towards this, the authors develop an indicator modelling and visualisation tool which comprises 1) indicator selection, 2) modelling techniques that allow spatio-temporal prediction of indicators, 3) interactive 3D virtual world where visualisation techniques are used to present indicator information overlaying the virtual world to facilitate effective communication with a wide range of stakeholders. The sustainability modelling and 3D visualisations are shown to have the potential to enhance community engagement within the planning process, thus enhancing public acceptance and participation within the urban or rural development project.
Urbanization and Socio-Economic Growth in South Asia Region
Authors: Chandiramani Jyoti , Airy Aanchal
Published: May 2018

Urbanization in the South Asia Region (SAR) stood at 34% (2014) and is relatively sluggish when compared to that of the World at 54%. The World Urbanization Prospects (2014) and World Bank Report (2016) reveals that the future urbanization globally will be concentrated in Asia and predominantly in the select countries of SAR - Bangladesh, India and Pakistan. The chapter analyses the demographic and socio-economic characteristics of the select countries, which are indicative of the quality of life of citizens, benchmarking it with that of Asia and the world. The analysis reveals the slow, messy and hidden nature of urbanization in the region which is required to be addressed. The conclusions recommend large investment and policy imperatives which should bring about sustainable urbanization ensuring basic urban services resulting in improved demographics, Human Development Indices and other socio-economic characteristics of the people in the region.
Evaluating the Smart and Sustainable Built Environment in Urban Planning
Authors: Lombardi Patrizia , Giordano Silvia
Published: May 2018

The measurement of urban performance is one of the important ways in which one can assess the complexity of urban change, and judge which projects and solutions are more appropriate in the context of smart and sustainable urban development. This chapter introduces a new system for measuring urban performances. This is the result of two years of joint cooperation between the authors and the Italian iiSBE members group. It is based on previous research findings in the field of evaluation systems for the sustainable built environment. This new approach is useful for evaluating smart and sustainable urban redevelopment planning solutions, as it is based on benchmarking approaches and multi-scalar quantitative performance indicators (KPIs), from individual building level to city level. A number of important implications of the main findings of this study are set out in the concluding section, together with suggestions for future research.
Socioeconomic Challenges and Opportunities of Urbanization in Nigeria
Authors: Abubakar Ismaila Rimi , Dano Umar Lawal
Published: May 2018

Nigeria, with a population of about 186 million people (48% living in urban areas) in 2016, is the most populous country in Africa and eighth in the world, and by 2050 it is projected to become the third largest country in the world. This chapter highlights major challenges of rapid urbanization in Nigeria, caused mainly by in-migration of rural dwellers in search of better living conditions and employment opportunities. They include unemployment and urban poverty, social exclusion and crimes, poor housing and slum, inadequate provision of public services and proliferation of the informal sector. Notwithstanding, Nigeria can exploit these urbanization challenges and turn them into opportunities for socioeconomic development. As such, some key opportunities for sustainable urbanization in Nigeria has been discussed: (a) local economic development; (b) promoting urban sustainability; and (c) smart and knowledge city initiative. The chapter concludes with some future research directions.
Socio-Economic and Environmental Impacts of Urbanization in Lagos, Nigeria
Authors: Onwuemele Andrew
Published: May 2018

Urbanization is simply defined as the shift from rural to an urban society, which is triggered by social, economic, and political developments. Nigerian cities are not left out in the global urbanization trends. Nigeria has an annual urban population growth of 5.8 percent. Lagos as the economic focal point of Nigeria has one of highest rates of urbanization. Several scholars have looked into specific sectoral challenges of urbanization in Lagos; however, there is lack of synthesis posing new challenges for policy development. The goal of the chapter therefore is to examine the socio-economic and environmental consequences of urbanization in Lagos State. The chapter relies on empirical results from literature for its analysis. Results indicate two categories of socio-economic and environmental consequences of urbanization in Lagos. The chapter calls for the termination of urban biased development approach of many sub-national governments in Nigeria as well as equitable deployment of development projects.
An Empirical Study of E-Participation Levels in Jordan
Authors: Abu-Shanab Emad , Al-Dalou' Raya
Published: May 2018

The relationship between citizens and governments is the core of e-government. E-participation is one of the political dimensions of e-government which focuses on informing, consulting, involving, collaborating, and empowering citizens to take part of the decision making process. This study adopted a framework for the five levels of e-participation and tried to test such model empirically using 400 responses from Jordanians. The study tried to measure Jordanian perceptions towards e-participation initiatives and practices in Jordan, and to measure the achievements on each level as perceived and reported by subjects. Results indicated that the highest perceived level was e-involving, and the lowest was e-consulting. Also, the CFA results indicated a distorted distribution of items between the major levels. Results of other issues explored are discussed further in this study.
Building Smarter Cities Through Social Entrepreneurship
Authors: Bernardino Susana , Santos J. Freitas
Published: May 2018

The objective of the present study is to examine the extent to which social ventures are able to increase the “smartness” of cities. To achieve this goal, we adopt a qualitative approach using a case study method to obtain valuable insights about different characteristics and strategies of Cais (a non-profit association dedicated to helping disadvantaged people in urban areas). Through our analysis of Cais's activities, we assess whether its social interventions match the dimensions proposed by Giffinger et al. (2007) to rank smart cities' performance; specifically, it has smart: economy, people, governance, mobility, environment, and living. The research shows that the action pursued comprises elements from all the above-mentioned dimensions. Further, the analysis reveals that Cais reinforces the smartness of the city in which it acts (in terms of attributes such as living, economy, people, and environment).
Strategic Challenges of the Portuguese Molds Industry
Authors: Moreira António Carrizo , Ferreira Miguel A. M. M.
Published: May 2018

In a competitive environment shaped by continuous change, the understanding of the different forces that support or hinder the development of an industry, enables more informed, and assertive decision making. As such, following a sectoral system of innovation perspective that takes into account the temporal evolution of its most important events, the main objective of this chapter is to define a set of strategic lines for the sustainable development of the Portuguese molds industry. The study supports set of strategic priorities so that the Portuguese molds industry can embrace both an international favorable position and an entrepreneurial outward looking governance perspective. This chapter proposes that the future outlook will support the diversification to and the penetration of new sectoral markets, associated with a strong international product engineering and development cluster capable of supplying integrated solutions to several international markets.