bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of former landfills in gravel plain using geomorphometric analysis and High-Resolution LiDAR DTM
Authors: Breg Valjavec Mateja
Published: March 2015

The article represents the application of geomorphologic approach to discover the potential areas of buried waste in agricultural landscape of Ljubljana gravel plain. Some former waste disposal sites or landfills are underground sites characterized by heterogeneous old waste buried in formerly concave landforms: old inactive gravel pits or paleo-riverbeds. They form different types of anthropogenic landforms. They were primary recognized and located with the terrain visualization (analytical shading, hypsometry) of LiDAR data and in continuation with geomorphometric analysis and classification of fluvial terrain. Due to subsidence of heterogeneous waste, terrain of former landfill sites is bumpy and uncharacteristic of fluvial surface morfology or terrain. The geomorphometric analysis was applied to differentiate the anthropogenic landforms (gravel pits, filled gravel pits …) from natural alluvial landforms with combination of two geomorphometrics: multiresolution index of valley bottom flatness (MrVBF) and convergence index and high density LiDAR data. Result is the automatically derived classification of terrain in to three classes: (1) bumpy terrain, typical for areas with high terrain potential for landfill, (2) flat terrain, typical for dry paleo riverbeds and (3) »agricultural« terrain, typical for intensive fields and meadows. By comparing the results of geomorphometric analysis with the results of visual analysis the 26 of 46 visually detected anthropogenic landforms are overlapping the areas of high terrain potential for landfill and among these 8 objects were proved with geohistorical analysis of archive aerial photographs.
A geographical methodology for assessing nodality of a road network. Case study on the western Moldavia
Authors: Tudora Daniel , Eva Mihail
Published: March 2015

The study tests the concept of nodality in a three-dimensional space, both as a projection of the physical-geographical support and an expression of topological centrality, which is insufficiently employed in papers attempting to evaluate the geographical or potential accessibility. The junctions of the reticular systems will be positioned differently within the network depending on the acquired nodality values, which may influence through their importance the potential for development of the polarized territory. By focusing on a methodology specific to nomothetic epistemology, aimed at highlighting the vulnerabilities induced by the dysfunctions within the road network and obtaining nodal hierarchies, the study allows for the extraction of legitimate relationships, which can be extrapolated beyond the particular space matrix selected for demonstration purposes only.
The importance of vulnerable areas with potential tourism development: a case study of the Bohemian forest and South Bohemia tourism regions
Authors: Navrátil Josef , Lesjak Miha , Pícha Kamil , Martinát Stanislav , Navratilová Jana , White Baravalle Gilliam Vivian L. , Knotek Jaroslav , Kučera Tomáš , Švec Roman , Balounová Zuzana , Rajchard Josef
Published: March 2015

The significance of the vulnerability of nature-rich areas with high development potential for tourism was studied using three types of data: 1) spatial distribution of tourist attractions, 2) the appeal level of these attractions, and 3) the number of visitors. The Bohemian Forest and South Bohemia were chosen as study areas. Nine types of landscape spatial appeal were identified in the study area. Two most important types were defined based on their appeal where there are rare relic features in the natural environment dominated by the presence of peat bogs and natural habitats with scrub undergrowth or virgin forests. These types were also found in the areas with the greatest potential for tourism development. However, these areas are also the most important from the point of view of nature conservation and landscape protection in Central Europe.
Localization factors and development strategies for producer services: a case study of Belgrade, Serbia
Authors: Gligorijević Vera , Devedžić Mirjana , Ratkaj Ivan
Published: March 2015

This article highlights the patterns of Advanced Producer Services (APS) in Belgrade and relates them to contemporary spatial and economic intrametropolitan transformations. The locational strategies of APS have influenced the creation of another center called New Belgrade next to the traditional central business district (CBD). Over the last ten years, government planning documents and the location preferences of foreign firms have made New Belgrade the most attractive business location in Serbia. In a sample of the leading APS firms in Belgrade, 129 firms are analyzed in terms of firm sector, ownership, and location. The results confirm the multipolar-monocentric pattern, which appears to be a common feature in many European cities.
Evaluation of Fruška Gora National Park (Serbia) for sport and recreational tourism
Authors: Vujko Aleksandra , Plavša Jovan
Published: March 2015

The Fruška Gora National Park has one of the biggest sport and recreational potentials in Vojvodina, Serbia. Because of its favorable natural and geographical features Fruška Gora National Park. Since sports and recreational tourism is of growing importance in the tourism industry, the evaluation method to create a high quality tourism product becomes inevitable. Empirical research conducted on a sample of 304 respondents was aimed at showing the existing potentials of Fruška Gora National Park related to sport and recreational tourism. The interviews with experts from the Provincial Secretariat for Environmental Protection, the National Park and the Cycling Association of Vojvodina helped the SWOT analysis of sport and recreational tourism on Fruška Gora National Park.
Analysis of high waters on the Kriva Reka River, Macedonia
Authors: Vasileski Dragan , Radevski Ivan
Published: March 2015

The Kriva Reka River is located in northeastern Macedonia. Only a few manmade facilities, such as canals, dams, embankments, and hydropower plants, have been built along the river. This river type is particularly useful for calculating high waters using mathematical and statistical methods. To this end, five theoretical distributions were used in this study: the Gaussian normal distribution, log-normal distribution, Gumbel distribution, Pearson type III distribution, and log-Pearson type III distribution. In order to determine the probability of the occurrence of high waters at the Trnovec gauging station on the Kriva Reka, a period of 39 hydrologic years was processed, each year beginning in October.
Modelling of the Aral and Caspian seas drying out influence to climate and environmental changes
Authors: Marković Slobodan B. , Ruman Albert , Gavrilov Milivoj B. , Stevens Thomas , Zorn Matija , Komac Blaž , Perko Drago
Published: March 2015

The complete drying out of the Aral and Caspian seas, as isolated continental water bodies, and their potential impact on the climate and environment is examined with numerical simulations. Simulations use the atmospheric general circulation model (ECHAM5) as well as the hydrological discharge (HD) model of the Max-Planck-Institut für Meteorologie. The dry out is represented by replacing the water surfaces in both of the seas with land surfaces. New land surface elevation is lower, but not lover than 50 m from the present mean sea level. Other parameters in the model remain unchanged. The initial meteorological data is real; starting with January 1, 1989 and lasting until December 31, 1991. The final results were analyzed only for the second, as the first year of simulation was used for the model spinning up.The drying out of both seas leads to an increase in land surface and average monthly air temperature during the summer, and a decrease of land surface and average monthly air temperature during the winter, above the Caspian Sea. The greatest difference in temperature between dry and not dry cases have the same values, about 7–8 °C in both seasons, while daily extremes of temperature are much more pronounced. In the wider local/regional area, close to both seas, drying out leads to a difference in average annual temperatures by about 1 °C. On a global scale, the average annual temperature remains unchanged and the configuration of the isotherms remain unchanged, except for over some of the continents. In winter, Central Asia becomes cooler, while over Australia, southern Africa, and South America, it becomes slightly less warm. Furthermore, a new heat island occurs in western Sahara during summer.
The phylosophy and applicability of ecoremediations for the protection of water ecosystems
Authors: Svirčev Zorica , Krstić Svetislav , Važić Tamara
Published: March 2015

The problem of accelerated eutrophication of the water ecosystems has not been appreciated proportionally to the development of human society today. Accelerated or fast eutrophication is detected destiny in majority of ecosystems today, mainly due to adverse human impact. This paper aims to introduce ERM methods in treating the problems arising from increased total capacity and saprobity and also accelerated eutrophication. In this way the broadness and importance of ERM as an ecosystem service for the water protection should be emphasized. The basic characteristics of ERM are its high buffer and self-protective capacities, and preservation of natural habitats and biological diversity. ERM represents the ‘returning to nature’ approach aiming to preserve or re-establish the natural balance of the ecosystems, but also a human endeavor that enables new jobs and by-side activities important for economic and social development of the human society.
A comparison of Spanish lexical stress and two standard Mandarin tones in isolated words: The tonal contour
Authors: Yao Junming
Published: March 2015

This comparative study investigates the relationship between the contour of the word-level stress in Spanish and that of two standard tones in Mandarin Chinese, namely the first and the fourth tones. The experiment was carried out with isolated Spanish words. Contour similarity was found between the word-level stress in Spanish par-oxytone (non-hiatus) and proparoxytone words and the first Chinese tone, as well as between the stress in oxytone words and the fourth tone. These results could be used in teaching Spanish to Chinese students and vice versa.
Emerging Application of Fuzzy Expert System in Medical Domain
Authors: Kumar A. V. Senthil , Kalpana M.
Published: March 2015

Fuzzy expert system is an artificial intelligence tool that helps to resolve the decision-making problem with the existence of uncertainty and plays an important role in medicine for symptomatic diagnostic remedies. In this chapter, construction of Fuzzy expert system is the focused, which helps to diagnosis disease. Fuzzy expert system is constructed by using the fuzzification to convert crisp values into fuzzy values. Fuzzy expert system consists of fuzzy inference, implication, and aggregation. The system contains a set of rules with fuzzy operators T-norm and of T-Conorm. By applying the fuzzy inference mechanism, diagnosis of disease becomes simple for medical practitioners and patients. Defuzzification method is adopted to convert the fuzzy values into crisp values. With crisp values, the knowledge regarding the disease is given to medical doctors and patients. Application of Fuzzy expert system to diagnosis of disease is mainly focused on in this chapter.
Fuzzy-Based Medical Image Processing
Authors: Sinha G. R.
Published: March 2015

Medical Image Processing (MIP) is a set of tools applied over medical images, which consists of several components such as image acquisition, enhancement, segmentation, restoration, etc. The most important component of MIP is medical image segmentation used in Computer-Aided Diagnosis (CAD) systems used for detection of abnormalities in medical images. This chapter presents an overview and the importance of soft computing techniques in solving the problems of medical imaging. The authors highlight the significance of fuzzy-based clustering and similar methods for MIP and its applications. Fuzzy C-Means Clustering Method (FCM) is found the most suitable method among existing clustering methods for medical images. FCM addresses the problem of over-segmentation and helps in improvement of diagnosis accuracy. Application of optimization tool causes the reduction of execution time. A comparison of fuzzy-based methods over conventional methods suggests that neuro-fuzzy system as hybrid approach is an efficient method for medical image analysis.
Fuzzy Logic for Breast Cancer Diagnosis Using Medical Thermogram Images
Authors: Kamath Surekha
Published: March 2015

In this chapter, how medical thermography can be utilized as early detection technique for breast cancer with fuzzy logic is explained. Breast cancer is the leading cause of death among women. This fact justifies researches to reach early diagnosis, improving patients' life expectancies. Moreover, there are other pathologies, such as cysts and benign neoplasms, that deserve investigation. In the last ten years, the infrared thermography has shown to be a promising technique to early diagnosis of breast pathologies. Works on this subject presented results that justify the thermography as a complementary exam to detect breast diseases. Various algorithms that can be utilized for Breast Cancer diagnosis utilizing medical thermography are listed and also the advantages of medical thermography over other imaging modalities is given.
Developing and Validating Fuzzy-Based Trust Measures for Online Medical Diagnosis and Symptoms Analysis
Authors: Kohli Shruti
Published: March 2015

The wealth of medical information in the Web makes it expedient for non-experts to conduct their own diagnosis and healthcare assessment based on limited knowledge of signs, symptoms, and disorders. The goal of this chapter is to explain how to measure trust of websites that provide functionalities like Online Medical Diagnosis and exploration of Symptoms Analysis using fuzzy logic and soft computing techniques. Trust is qualitative and can be measured by analyzing how people interact with the websites. The interaction can be captured and analyzed by studying website logs using tools like Google analytics, click tail, etc. The chapter also provides a literature survey on the work being conducted by researchers in area of measuring website trust and tools being developed for same. It also covers archetypal techniques used for Web pattern recognition and taxonomy of trust. The main point driven by this literature survey is the frequent use of fuzzy logic in the design and implementation of trust measuring tools. This point is contrasted with the up-to-the-minute information, more specifically the authors' current work, on the use of a rule-based expert for developing trust-measuring tools.
Lookable User Interfaces and 3D
Authors: Radley Alan
Published: March 2015

A new philosophy of user interface design is described. Named the “Lookable User Interface,” or LUI, the approach is based on the concept of a Personal Reality (PR) system. Here the computer adapts to the user's worldview in a personalized way, and according to the specific requirements, behaviors, and perceptive skills of the individual. Typically, a PR system creates and adjusts (in real-time) 3D perspective view(s) of a data-set, including (potentially) the field of view of a scene and the apparent distance and scale of objects, whilst also creating an aesthetic “eye-friendly” context for computing operations. A Lookable User Interface (LUI) affords the maximum degree of visual accessibility to digital content. The authors examine the results of testing a Lookable User Interface. Spectasia is one example of a Personal Virtual Reality (PVR) that can be used to visualize links between universals and particulars within digital worlds.
Self as Computer
Authors: Radley Alan
Published: March 2015

The present chapter considers the computer not as a tool, or as a bicycle-for-the-mind, but simply as self. The authors argue that humans are becoming so enmeshed with the computer, in terms of how we think, act, and communicate, that soon it may no longer be possible to identify where the self ends and the computer begins, and vice-versa. It follows that if such a postulate holds any truth, computing systems must be carefully designed to preserve, and not to harm, human rights. Predicted by some are marvelous benefits for technology, in terms of enhancements to our social, creative, and personal lives. But already clear is that not all of the associated problems lie in the realm of speculation. One example is that the Internet is moving ever further away from the free and open system as foreseen by its original designers, whereby citizens are routinely censored, controlled, and spied upon.
Vision of Best Practices for IMS Implementation
Authors: Biga Daniel , Del Giorgio Horacio , Dufour Fernando , Serra Ariel
Published: March 2015

The IMS technology is a framework architecture for delivering IP multimedia services, which allows voice and multimedia applications to communicate from multi-access scenarios (Wireless, PacketCable, DSL, etc.), thus allowing the convergence of fixed and mobile networks. The authors carry out an investigation into the current state of the art of this technology, focusing on its architecture, operating principles, and especially on the current state of development in Argentina. They make a forecast of what will happen in the next three years and their vision of what today are the best practices for its implementation.
Critical Parameters for Fuzzy Data Mining
Authors: Bhattacharya Sinchan , Bhatnagar Vishal
Published: March 2015

Research on data mining is increasing at an incessant rate and to improve its effectiveness other techniques have been applied such as fuzzy sets, rough set theory, knowledge representation, inductive logic programming, or high-performance computing. Fuzzy logic due to its proficiency in handling uncertainty has gained its importance in a variety of applications in combination with the use of data mining techniques. In this chapter we take this association a notch further by examining the parameters which allow fuzzy sets and data mining to be combined into what has come to be known as fuzzy data mining. Analyzing and understanding these critical parameters is the main purpose of this chapter, so as to acquire maximum efficiency in applying the same which impelled the authors to work extensively and find out the crucial parameters essential to the application of fuzzy data mining.
Navigators on the Research Path
Authors: Hansman Catherine A.
Published: March 2015

Qualitative research methods courses have become common or required in most doctoral and some master's degree graduate programs' curricula. However, although many graduate students enter their programs with some knowledge of quantitative methodology, they have little to no understanding of qualitative research methodologies. There are many challenges associated with teaching qualitative research in a context that promotes and embraces numerically based forms of knowledge and marginalizes other types of research. In addition, although most learners in qualitative research classes are adult learners, adult learning theories and teaching strategies may not be a preferred approach by qualitative instructors. The purpose of this chapter is to discuss the challenges faced by faculty members who plan and teach qualitative research courses, using the literature to highlight current qualitative research pedagogy while discussing new strategies and models that may assist developing graduate students as qualitative researchers in their graduate programs and their future careers.
Dynamic Spectrum Access Techniques
Authors: Amraoui Asma , Benmammar Badr
Published: March 2015

It is now widely recognized that wireless communications systems don't exploit the whole available frequency band. The idea has naturally emerged to develop tools to better use the spectrum. Cognitive Radio (CR) is the concept that meets this challenge. The CR is a form of wireless communication in which a transmitter/receiver can detect intelligently communication channels that are in use and those that are not, and can move to unused channels. This optimizes the use of available radio frequency spectrum while minimizing interference with other users. CRs must have the ability to learn and adapt their wireless transmission according to the ambient radio environment. The application of Artificial Intelligence (AI) approaches in the CR is very promising because they are essential for the implementation of CR networks architecture. They must be able to coexist to make CR systems practical, which may cause interference to other users. To solve the problem of congestion, CR networks use Dynamic Spectrum Access (DSA). In order to deal with this problem, the idea of cooperation between users to detect and share spectrum without causing interferences is introduced. The authors found a large number of suggested works relating to spectrum access, those using Auctions, a large number of approaches use the Game theory, but those using Markov chains are fewer. However, some research has been done in this area using Multi Agent Systems (MAS).
Hybrid Adaptive NeuroFuzzy Bspline Based SSSC Damping Control Paradigm
Authors: Khan Laiq , Badar Rabiah
Published: March 2015

This work explores the potential of Bspline based Adaptive NeuroFuzzy Wavelet control to damp low frequency power system oscillations using Static Synchronous Series Compensator (SSSC). A comparison of direct and indirect adaptive control based on Hybrid Adaptive Bspline Wavelet Control (ABSWC) is presented by introducing the online identification block. ABSWC with Identification (ABSWCI) provides the sensitivity information of the plant to control system. The parameters of the control and identification block are updated online using gradient descent based back propagation algorithm. The robustness of the proposed control algorithm has been evaluated for local and inter-area modes of oscillations using different faults. The nonlinear time domain simulation results have been analyzed on the basis of different performance indices and time-frequency representation showing that ABSWC effectively damps low frequency oscillations and incorporation of online identification optimizes the control system performance in terms of control effort which reduces the switching losses of the converter.
A Framework Proposal to Assess the LARG Index of a Supply Chain in a Fuzzy Context
Authors: Fazendeiro Paulo , Azevedo Susana G. , Cruz-Machado V.
Published: March 2015

Bearing in mind the new Supply Chain Management (SCM) paradigms, it is important that supply chains be aware of the implementation level of the main practices associated to each SCM paradigm (Lean, Agile, Resilient, and Green, hereafter referred as LARG). The main objective of this chapter is to propose a framework, based on Enterprise 2.0 approach, for global supply chains to assess their LARG index in order to evaluate the leanness, agility, resilience, and greenness of their practices. Enterprise 2.0 technologies and Fuzzy Logic techniques are used as enablers to the proposed LARG evaluation model in the following assessment tasks: 1) determination of an adequate set of Lean, Agile, Resilient, and Green practices; 2) consensual definition of the relative weights of the considered practices; 3) adjustment of the evaluation policy to the particular supply chain; and 4) effective follow-up of the assessment results.
Risk Management Research Design Ideologies, Strategies, Methods, and Techniques
Authors: Strang Kenneth David
Published: March 2015

The researcher interviewed 11 doctoral students and 12 International Disaster Conference attendees to understand how research guidelines could be improved to help these emerging scholars achieve more publications. Empirical studies were cited to substantiate the need for better research method guidance. A research design model was then created as a top-down typology based on a literature review and practitioner experience. The design model consisted of four components: research ideology, unit and level of analysis strategy, formal research method, and analysis techniques. The discussion illustrated how all researcher philosophies can be simplified into one of three ideologies: post-positivist, pragmatic or social-constructivist. Additionally, the author explained how the level and unit of analysis goals are developed into an analysis strategy with research questions or hypotheses. Inquire strategy was integrated with formal research method and ideology, to facilitate the selection of data collection sampling and analysis techniques. Numerous research methods thought leaders were cited to direct new scholars towards best practices. A unique feature of the model was its simplicity and application across all the generally accepted research philosophies, methods and techniques as well as disciplinary fields. Although the study was directed toward risk management practitioners, it applies to any field or industry.
Demonic Fuzzy Relational Calculus
Authors: Tchier Fairouz , Alrashidi Huda
Published: March 2015

In this chapter, the authors categorize methods that are used to formally specify and verify software requirements. They discuss several formal method-related subjects such as calculus fuzzy and relational calculus.
Chaotic Map Model-Based Interference Employed in Quantum-Inspired Genetic Algorithm to Determine the Optimum Gray Level Image Thresholding
Authors: Dey Sandip , Bhattacharyya Siddhartha , Maulik Ujjwal
Published: March 2015

In this chapter, a Quantum-Inspired Genetic Algorithm (QIGA) is presented. The QIGA adopted the inherent principles of quantum computing and has been applied on three gray level test images to determine their optimal threshold values. Quantum random interference based on chaotic map models and later quantum crossover, quantum mutation, and quantum shift operation have been applied in the proposed QIGA. The basic features of quantum computing like qubit, superposition of states, coherence and decoherence, etc. help to espouse parallelism and time discreteness in QIGA. Finally, the optimum threshold value has been derived through the quantum measurement phase. In the proposed QIGA, the selected evaluation metrics are Wu's algorithm, Renyi's algorithm, Yen's algorithm, Johannsen's algorithm, Silva's algorithm, and finally, linear index of fuzziness, and the selected gray level images are Baboon, Peppers, and Corridor. The conventional Genetic Algorithm (GA) and Quantum Evolutionary Algorithm (QEA) proposed by Han et al. have been run on the same set of images and evaluation metrics with the same parameters as QIGA. Finally, the performance analysis has been made between the proposed QIGA with the conventional GA and later with QEA proposed by Han et al., which reveals its time efficacy compared to GA along with the drawbacks in QEA.
Practical Wisdom of Tool and Task
Authors: Smith Nancy J , Bhattacharya Kakali
Published: March 2015

The purpose of this chapter is to explain the effective use of digital tools to display and analyze mixed methods data and to identify the challenges and possibilities of doing a qualitatively driven mixed methods study of technology use in education. To frame this chapter, examples from a qualitatively driven mixed methods study of doctoral students, which explored how the use of mobile technology affected engagement in the class experience, are presented. Additionally, the authors discuss the limits, implications, and possibilities of inductively driven mixed methods, while dealing with issues of academic rigor and trustworthiness using Morse and Niehaus's (2009) guidelines for mixed methods research design and the ways in which digital tools enhance rigor and trustworthiness.
A Hybrid Technique Using PCA and Wavelets in Network Traffic Anomaly Detection
Authors: Novakov Stevan , Lung Chung-Horng , Lambadaris Ioannis , Seddigh Nabil
Published: March 2015

Research into network anomaly detection has become crucial as a result of a significant increase in the number of computer attacks. Many approaches in network anomaly detection have been reported in the literature, but data or solutions typically are not freely available. Recently, a labeled network traffic flow dataset, Kyoto2006+, has been created and is publicly available. Most existing approaches using Kyoto2006+ for network anomaly detection apply various clustering techniques. This paper leverages existing well known statistical analysis and spectral analysis techniques for network anomaly detection. The first popular approach is a statistical analysis technique called Principal Component Analysis (PCA). PCA describes data in a new dimension to unlock otherwise hidden characteristics. The other well known spectral analysis technique is Haar Wavelet filtering analysis. It measures the amount and magnitude of abrupt changes in data. Both approaches have strengths and limitations. In response, this paper proposes a Hybrid PCA–Haar Wavelet Analysis. The hybrid approach first applies PCA to describe the data and then Haar Wavelet filtering for analysis. Based on prototyping and measurement, an investigation of the Hybrid PCA–Haar Wavelet Analysis technique is performed using the Kyoto2006+ dataset. The authors consider a number of parameters and present experimental results to demonstrate the effectiveness of the hybrid approach as compared to the two algorithms individually.
Genetic Algorithms Quality Assessment Implementing Intuitionistic Fuzzy Logic
Authors: Pencheva Tania , Angelova Maria , Atanassov Krassimir
Published: March 2015

Intuitionistic fuzzy logic has been implemented in this investigation aiming to derive intuitionistic fuzzy estimations of model parameters of yeast fed-batch cultivation. Considered here are standard simple and multi-population genetic algorithms as well as their modifications differ from each other in execution order of main genetic operators (selection, crossover, and mutation). All are applied for the purpose of parameter identification of S. cerevisiae fed-batch cultivation. Performances of the examined algorithms have been assessed before and after the application of a procedure for narrowing the range of model parameters variation. Behavior of standard simple genetic algorithm has been also examined for different values of proof as the most sensitive genetic algorithms parameter toward convergence time, namely, generation gap (GGAP). Results obtained after the intuitionistic fuzzy logic implementation for assessment of genetic algorithms performance have been compared. As a result, the most reliable algorithm/value of GGAP ensuring the fastest and the most valuable solution is distinguished.
Computational Intelligence in Used Products Retrieval and Reproduction
Authors: Gao Wen-Jing , Xing Bo , Marwala Tshilidzi
Published: March 2015

Remanufacturing has become a superior option for product recovery management system. It mainly consists of three stages: retrieval, reproduction, and redistribution. So far, many different approaches have been followed in order to improve the efficiency of a remanufacturing process. However, as the complexity increases, the use of computational intelligence (CI) in those problems is becoming a unique tool of imperative value. In this paper, different CI methods, such as artificial neural network (ANN), ant colony optimization (ACO), biogeography-based optimization (BBO), cuckoo search (CS) and fuzzy logic (FL), are utilized to solve the problems involved in retrieval and reproduction stages for remanufacturing. The key issues in implementing the proposed approaches are discussed, and finally the applicability of the proposed methods are illustrated through different examples.
A Particle Swarm Optimizer for Constrained Multiobjective Optimization
Authors: Leong Wen Fung , Wu Yali , Yen Gary G.
Published: March 2015

Generally, constraint-handling techniques are designed for evolutionary algorithms to solve Constrained Multiobjective Optimization Problems (CMOPs). Most Multiojective Particle Swarm Optimization (MOPSO) designs adopt these existing constraint-handling techniques to deal with CMOPs. In this chapter, the authors present a constrained MOPSO in which the information related to particles' infeasibility and feasibility status is utilized effectively to guide the particles to search for feasible solutions and to improve the quality of the optimal solution found. The updating of personal best archive is based on the particles' Pareto ranks and their constraint violations. The infeasible global best archive is adopted to store infeasible nondominated solutions. The acceleration constants are adjusted depending on the personal bests' and selected global bests' infeasibility and feasibility statuses. The personal bests' feasibility statuses are integrated to estimate the mutation rate in the mutation procedure. The simulation results indicate that the proposed constrained MOPSO is highly competitive in solving selected benchmark problems.
Applications of Fuzzy Logic to Systems' Modelling
Authors: Voskoglou Michael Gr.
Published: March 2015

They appear often situations in a system's operation characterized by a degree of vagueness and/or uncertainty. In the present paper, the author uses principles of fuzzy logic to develop a general model representing such kind of situations. They also present three alternative methods for measuring a fuzzy system's effectiveness, including the use of its total possibilistic uncertainty, the classical Shannon's entropy properly modified for use in a fuzzy environment and the “centroid” method in which the coordinates of the center of mass of the graph of the membership function involved provide an alternative measure of the system's performance The advantages and disadvantages of each of the above methods are discussed and a combined use of them is suggested in obtaining the ideal profile of the system's performance according to the user's personal criteria of goals. An application of their general model is also developed for the Mathematical Modelling process illustrating the use of the author's fuzzy model in practice.
Application of Meta-Heuristic Optimization Algorithms in Electric Power Systems
Authors: Voropai N.I. , Gamm A. Z. , Glazunova A. M. , Etingov P. V. , Kolosok I. N. , Korkina E. S. , Kurbatsky V. G. , Sidorov D. N. , Spiryaev V. A. , Tomin N. V. , Zaika R. A. , Bat-Undraal B.
Published: March 2015

Optimization of solutions on expansion of electric power systems (EPS) and their control plays a crucial part in ensuring efficiency of the power industry, reliability of electric power supply to consumers and power quality. Until recently, this goal was accomplished by applying classical and modern methods of linear and nonlinear programming. In some complicated cases, however, these methods turn out to be rather inefficient. Meta-heuristic optimization algorithms often make it possible to successfully cope with arising difficulties. State estimation (SE) is used to calculate current operating conditions of EPS using the SCADA measurements of state variables (voltages, currents etc.). To solve the SE problem, the Energy Systems Institute of Siberian Branch of Russian Academy of Sciences (ESI of SB RAS) has devised a method based on test equations (TE), i.e. on the steady state equations that contain only measured parameters. Here, a technique for EPS SE using genetic algorithms (GA) is suggested. SE is the main tool for EPS monitoring. The quality of SE results determines largely the EPS control efficiency. An algorithm for exclusion of wrong SE calculations is described. The algorithm using artificial neural networks (ANN) is based on the analysis of results of the calculation performed solving the SE problem with different combinations of constants. The proposed procedure is checked on real data.
The Use of Mixed Methods in Organizational Communication Research
Authors: Salem Philip
Published: March 2015

Most organizational research employs either quantitative or qualitative methods. Furthermore, users of one methodology often dismiss those who use another. The purpose of this report was to describe how researchers could use mixed methods, especially online. Researchers often begin investigations with paradigmatic assumptions or multiple constructs that should lead to mixed methods. However, quantitative methodological assumptions may seem to contradict qualitative methodological assumptions, and scholars have found it easier and quicker to deliver results adopting only one methodology. Additionally, researchers may be resistant because making high quality inferences from mixed methods might seem too demanding. This chapter describes how one researcher grappled with these challenges when using mixed methods off-line. Online technologies contribute to resolving some difficulties more easily.
Combining Research Paradigms to Improve Poor Student Performance
Authors: Goede Roelien , Taylor Estelle , van Aardt Christoffel
Published: March 2015

The aim of this chapter is to demonstrate the advantages of combining methods from different research paradigms. Positivism, interpretivism, and critical social theory are presented as major paradigms in Information Systems research. The chapter demonstrates the use of methods representative of these three research paradigms in a single research setting. The main problem in the research setting is the poor performance of students in a specific module of their academic programme. This problem is addressed by initiating an action research project using methods representing different research paradigms in the different phases of the project. The argument for using mixed methods is presented by providing information on research paradigms, discussing the problem environment, describing the research process, and finally, reflecting on research paradigms and their application in this environment.
Building a User Centric Success Factors Model for Mobile Government
Authors: Al-masaeed Sultan , Love Steve
Published: March 2015

Mobile government is an emergent phenomenon that represents a solution for many countries to reach their citizens and improve delivery of government-to- citizens' services (G2C). Despite the fact that mobile government benefits are very promising; there are some factors that determine success or failure of mobile government applications. In this study, a systematic review of previous studies using a meta-analysis method was undertaken and a conceptual success factors model for mobile government to citizen services (G2C) was created. Furthermore, the second phase of this study was a survey with 40 academics to validate the use of meta-analysis and validate and refine the conceptual model.
An On-Line PSO-Based Fuzzy Logic Tuning Approach
Authors: Babahajyani P. , Habibi F. , Bevrani H.
Published: March 2015

Modern power systems require increased intelligence and flexibility in control and optimization. This issue is becoming more significant today due to the increasing size, changing structure, emerging renewable energy sources and Microgrids, environmental constraints, and the complexity of power systems. The control units and their associated tuning methods for modern power systems surely must be intelligent (based in flexible intelligent algorithms). This chapter addresses a new intelligent approach using a combination of fuzzy logic and Particle Swarm Optimization (PSO) techniques for optimal tuning of the existing most popular Proportional-Integral (PI) or Proportional-Integral-Derivative (PID) controllers in the power electric industry. In the proposed control strategy, the PI (PID) parameters are automatically tuned using fuzzy rules, according to the on-line measurements. In order to obtain an optimal performance, the PSO technique is used to determine the membership functions' parameters. The proposed optimal tuning scheme offers many benefits for a new power system with numerous distributed generators and Renewable Energy Sources (RESs).In the developed tuning algorithm, the physical and engineering aspects have been fully considered. To demonstrate the effectiveness of the proposed control scheme, secondary frequency control problem in an islanded Microgrid (MG) system is considered a case study. The main source of power for a Microgrid is small generating units of tens of kW that are placed at the customer site. Simulation studies are performed to illustrate the capability of the proposed intelligent/optimal control approach.
Computer-Aided Deductive Critical Discourse Analysis of a Case Study from Mauritius with ATLAS-ti 6.2
Authors: Rambaree Komalsingh
Published: March 2015

This chapter considers computer-aided deductive critical discourse analysis with ATLAS-ti 6.2 using a case study on eco-social work research from Mauritius. Data for this case study were gathered in digital audio format from eight focus group discussions, three semi-structured interviews and various reports from secondary sources. For the analysis, a literature review using ATLAS-ti was first carried out, in order to develop a conceptual/theoretical framework related to eco-social work. Then, the gathered data were directly plugged into ATLAS-ti for a computer-aided deductive critical discourse analysis using the developed eco-social work conceptual/theoretical framework from the literature review. Using the case study as an example, this chapter (a) demonstrates the techniques, and (b) appraises the opportunities, limitations and challenges of computer-aided critical discourse analysis.
Fuzzy Systems for Spectrum Access, Mobility and Management for Cognitive Radios
Authors: Kaur Prabhjot , Uddin Moin , Khosla Arun
Published: March 2015

This chapter addresses the issues in air interface designs for Cognitive Radios. Fuzzy logic system is used as one of the soft computing techniques to learn to sub optimality and vagueness. Many good, simple, and quick fuzzy based solutions have been developed since few decades in many diverse domains. Through this chapter, the authors first discuss the significance and need of soft computing techniques in designing such solutions and then present fuzzy based solutions for spectrum access, mobility, and management. Hierarchical fuzzy systems have been used to get over to the problem of curse of dimensionality. The proposed solutions consider an architecture, similar to the one proposed by IEEE 802.22 working group, for spectrum sharing and management. Models have been designed using fuzzy logic toolbox in MATLAB, and the system performance is checked using SIMULINK.
Uncertainty Modeling Using Expert's Knowledge as Evidence
Authors: Datta D.
Published: March 2015

In this paper we discuss the uncertainty modeling using evidence theory. In practice, very often availability of data is incomplete in the sense that sufficient amount of data which is required may not be possible to collect. Therefore, uncertainty modeling in that case with this incomplete data set is not possible to carry out using probability theory or Monte Carlo method. Fuzzy set theory or any other imprecision based theory is applicable in this case. With a view to this expert's knowledge is represented as the input data set. Belief and plausibility are the two bounds (lower and upper) of the uncertainty of this imprecision based system. The fundamental definitions and the mathematical structures of the belief and plausibility fuzzy measures are discussed in this chapter. Uncertainty modeling using this technique is illustrated with a simple example of contaminant transport through groundwater.
An Introduction to the Basic Concepts in QSAR-Aided Drug Design
Authors: Hamzeh-Mivehroud Maryam , Sokouti Babak , Dastmalchi Siavoush
Published: March 2015

The need for the development of new drugs to combat existing and newly identified conditions is unavoidable. One of the important tools used in the advanced drug development pipeline is computer-aided drug design. Traditionally, to find a drug many ligands were synthesized and evaluated for their effectiveness using suitable bioassays and if all other drug-likeness features were met, the candidate(s) would possibly reach the market. Although this approach is still in use in advanced format, computational methods are an indispensable component of modern drug development projects. One of the methods used from very early days of rationalizing the drug design approaches is Quantitative Structure-Activity Relationship (QSAR). This chapter overviews QSAR modeling steps by introducing molecular descriptors, mathematical model development for relating biological activities to molecular structures, and model validation. At the end, several successful cases where QSAR studies were used extensively are presented.
Evolution of Multivariate Image Analysis in QSAR
Authors: Freitas Matheus P. , Duarte Mariene H.
Published: March 2015

Multivariate Image Analysis applied in Quantitative Structure-Activity Relationship (MIA-QSAR) is a simple method to achieve, at least in a variety of examples, QSAR models with predictive abilities comparable to those of sophisticated tridimensional methodologies. MIA-QSAR is based on the correlation between properties (e.g. biological activities) and chemical descriptors, which are pixels of images representing chemical structures in a congeneric series of molecules. The MIA-QSAR approach has been improved since its creation, in 2005, both in terms of data analysis and development of more descriptive information. This chapter reports the MIA-QSAR method, including its augmented version, named aug-MIA-QSAR because of the introduction of new dimensions to better encode atomic properties. In addition, the application to a case study illustrates the main practical differences between traditional and augmented MIA-QSAR. The use of a neglected disease as example represents a challenge in QSAR, which is particularly focused on diseases with higher economical appearance.
Importance of Applicability Domain of QSAR Models
Authors: Roy Kunal , Kar Supratik
Published: March 2015

Quantitative Structure-Activity Relationship (QSAR) models have manifold applications in drug discovery, environmental fate modeling, risk assessment, and property prediction of chemicals and pharmaceuticals. One of the principles recommended by the Organization of Economic Co-operation and Development (OECD) for model validation requires defining the Applicability Domain (AD) for QSAR models, which allows one to estimate the uncertainty in the prediction of a compound based on how similar it is to the training compounds, which are used in the model development. The AD is a significant tool to build a reliable QSAR model, which is generally limited in use to query chemicals structurally similar to the training compounds. Thus, characterization of interpolation space is significant in defining the AD. An attempt is made in this chapter to address the important concepts and methodology of the AD as well as criteria for estimating AD through training set interpolation in the descriptor space.
QSAR Studies on Bacterial Efflux Pump Inhibitors
Authors: Thai Khac-Minh , Do Trong-Nhat , Nguyen Thuy-Viet-Phuong , Nguyen Duc-Khanh-Tho. , Tran Thanh-Dao
Published: March 2015

Antimicrobial drug resistance occurs when bacteria undergo certain modifications to eliminate the effectiveness of drugs, chemicals, or other agents designed to cure infections. To date, the burden of resistance has remained one of the major clinical concerns as it renders prolonged and complicated treatments, thereby increasing the medical costs with lengthier hospital stays. Of complex causes for bacterial resistance, there has been increasing evidence that proved the significant role of efflux pumps in antibiotic resistance. Coadministration of Efflux Pump Inhibitors (EPIs) with antibiotics has been considered one of the promising ways not only to improve the efficacy but also to extend the clinical utility of existing antibiotics. This chapter begins with outlining current knowledge about bacterial efflux pumps and drug designs applied in identification of their modulating compounds. Following, the chapter addresses and provides a discussion on Quantitative Structure-Activity Relationship (QSAR) analyses in search of novel and potent efflux pump inhibitors.