bluuebunny/crossref_metadata_2025 huggingface dataset:
La réforme régionale en France : une occasion manquée ?
Authors: Bonnet-Pineau Élisabeth
Published: April 2016

À chaque année sa réforme : en 2014, la nouvelle carte administrative française ramène de 22 à 13 le nombre des régions. L’émergence de la région devenue une collectivité territoriale de plein exercice fut lente et consacrée seulement en 1982. Depuis quelques années, plusieurs rapports ont proposé la réduction du nombre des régions et une redéfinition des compétences des conseils départementaux et régionaux.L’objet principal de la réforme visait à « doter les régions d’une taille critique » pour leur permettre d’ « exercer  les compétences stratégiques qui leur sont attribuées et de réaliser des gains d’efficience ».Or la région n’est toujours pas consacrée comme chef de file et les conseils départementaux sont plus que jamais inscrits dans le paysage institutionnel aux côtés des intercommunalités de plus en plus larges. L’objectif d’économies ne pourra être obtenu que par le renforcement de ces intercommunalités, tant les dotations du gouvernement aux collectivités ont été rabotées. Et si les fusions ont été privilégiées, l’effet de taille est loin d’avoir été appliqué. La réforme paraît être une occasion manquée …
Administrative division of Poland - 25 years of experience during the systemic transformation
Authors: Kaczmarek Tomasz
Published: April 2016

This article seeks to present the chief features of Poland's territorial division and assess it at its three levels: voivodeships, poviats and communes. The reference point is the territorial divisions of other EU states, especially those that, like Poland, have a three-tier structure. The basic thesis is that the territorial organisation of public administration should change so as to keep up with political, economic, social and spatial processes, the last being especially important for it. The article closes with recommendations for ways of changing local and regional administrative structures, like establishing a new voivodeship and metropolitan poviats, combining urban and rural poviats, and fusions of communes.
Le conflit ukrainien : Du basculement des évènements Place Maïdan vers l’émergence d’un conflit armé dans le Donbass
Authors: Khodalitzky Elsa
Published: April 2016

Tout comme les évènements de Géorgie en 2008, les affrontements qui ont lieu en Ukraine depuis fin 2013 mettent en exergue les tensions toujours latentes entre le monde occidental et le monde russe. Mais au-delà des considérations politiques qui risquent de biaiser l’analyse, l’actualité ukrainienne apparaît comme une illustration de l’émergence d’un conflit armé et des difficultés de sa qualification juridique. La présente contribution sera exclusivement consacrée à la question de l’intensité des affrontements ; l’organisation des parties en présence fera l’objet d’une seconde note.
The Performance Mining Method
Authors: Pachidi Stella , Spruit Marco
Published: April 2016

Software Performance is a critical aspect for all software products. In terms of Software Operation Knowledge, it concerns knowledge about the software product's performance when it is used by the end-users. In this paper the authors suggest data mining techniques that can be used to analyze software operation data in order to extract knowledge about the performance of a software product when it operates in the field. Focusing on Software-as-a-Service applications, the authors present the Performance Mining Method to guide the process of performance monitoring (in terms of device demands and responsiveness) and analysis (finding the causes of the identified performance anomalies). The method has been evaluated through a prototype which was implemented for an online financial management application in the Netherlands.
Big Data Security Management
Authors: Tang Zaiyong , Pan Youqin
Published: April 2016

Big data is a buzzword today, and security of big data is a big concern. Traditional security standards and technologies cannot scale up to deliver reliable and effective security solutions in the big data environment. This chapter covers big data security management from concepts to real-world issues. By identifying and laying out the major challenges, industry trends, legal and regulatory environments, security principles, security management frameworks, security maturity model, big data analytics in solving security problems, current research results, and future research issues, this chapter provides researchers and practitioners with a timely reference and guidance in securing big data processing, management, and applications.
Feature-Based Uncertainty Visualization
Authors: Wu Keqin , Zhang Song
Published: April 2016

While uncertainty in scientific data attracts an increasing research interest in the visualization community, two critical issues remain insufficiently studied: (1) visualizing the impact of the uncertainty of a data set on its features and (2) interactively exploring 3D or large 2D data sets with uncertainties. In this chapter, a suite of feature-based techniques is developed to address these issues. First, an interactive visualization tool for exploring scalar data with data-level, contour-level, and topology-level uncertainties is developed. Second, a framework of visualizing feature-level uncertainty is proposed to study the uncertain feature deviations in both scalar and vector data sets. With quantified representation and interactive capability, the proposed feature-based visualizations provide new insights into the uncertainties of both data and their features which otherwise would remain unknown with the visualization of only data uncertainties.
Big Data Architecture
Authors: Duggirala Siddhartha
Published: April 2016

With the unprecedented increase in data sources, the question of how to collect them efficiently, effectively, and elegantly, store them securely and safely, leverage those stocked, polished, and maintained data in a smarter manner so that industry experts can plan ahead, take informed decisions, and execute them in a knowledgeable fashion remains. This chapter clarifies several pertinent questions and related issues with the unprecedented increase in data sources.
Sentiment Analysis for Health Care
Authors: Khan Muhammad Taimoor , Khalid Shehzad
Published: April 2016

Sentiment analysis for health care deals with the diagnosis of health care related problems identified by the patients themselves. It takes the patients opinions into perspective to make policies and modifications that could directly address their problems. Sentiment analysis is used with commercial products to great effect and has outgrown to other application areas. Aspect based analysis of health care, not only recommend the services and treatments but also present their strong features for which they are preferred. Machine learning techniques are used to analyze millions of review documents and conclude them towards an efficient and accurate decision. The supervised techniques have high accuracy but are not extendable to unknown domains while unsupervised techniques have low accuracy. More work is targeted to improve the accuracy of the unsupervised techniques as they are more practical in this time of information flooding.
Essentiality of Machine Learning Algorithms for Big Data Computation
Authors: Narayanapppa Manjunath Thimmasandra , Kumar T. P. Puneeth , Hegadi Ravindra S.
Published: April 2016

Recent technological advancements have led to generation of huge volume of data from distinctive domains (scientific sensors, health care, user-generated data, finical companies and internet and supply chain systems) over the past decade. To capture the meaning of this emerging trend the term big data was coined. In addition to its huge volume, big data also exhibits several unique characteristics as compared with traditional data. For instance, big data is generally unstructured and require more real-time analysis. This development calls for new system platforms for data acquisition, storage, transmission and large-scale data processing mechanisms. In recent years analytics industries interest expanding towards the big data analytics to uncover potentials concealed in big data, such as hidden patterns or unknown correlations. The main goal of this chapter is to explore the importance of machine learning algorithms and computational environment including hardware and software that is required to perform analytics on big data.
Chinese Text Sentiment Analysis Utilizing Emotion Degree Lexicon and Fuzzy Semantic Model
Authors: Wu Xing , Zhuo Shaojian
Published: April 2016

Text on the web has become a valuable source for mining and analyzing user opinions on any topic. Non-native English speakers heavily support the growing use of Network media especially in Chinese. Many sentiment analysis studies have shown that a polarity lexicon can effectively improve the classification consequences. Social media, where users spontaneously generated content have become important materials for tracking people's opinions and sentiments. Meanwhile, the mathematical models of fuzzy semantics have provided a formal explanation for the fuzzy nature of human language processing. This paper investigated the limitations of traditional sentiment analysis approaches and proposed an effective Chinese sentiment analysis approach based on emotion degree lexicon. Inspired by various social cognitive theories, basic emotion value lexicon and social evidence lexicon were combined to improve sentiment analysis consequences. By using the composite lexicon and fuzzy semantic model, this new sentiment analysis approach obtains significant improvement in Chinese text.
Application of Big Data in Healthcare
Authors: Hoque Md Rakibul , Bao Yukun
Published: April 2016

This chapter investigates the application, opportunities, challenges and techniques of Big Data in healthcare. The healthcare industry is one of the most important, largest, and fastest growing industries in the world. It has historically generated large amounts of data, “Big Data”, related to patient healthcare and well-being. Big Data can transform the healthcare industry by improving operational efficiencies, improve the quality of clinical trials, and optimize healthcare spending from patients to hospital systems. However, the health care sector lags far behind compared to other industries in leveraging their data assets to improve efficiencies and make more informed decisions. Big Data entails many new challenges regarding security, privacy, legal concerns, authenticity, complexity, accuracy, and consistency. While these challenges are complex, they are also addressable. The predominant ‘Big Data' Management technologies such as MapReduce, Hadoop, STORM, and others with similar combinations or extensions should be used for effective data management in healthcare industry.
Improving Healthcare with Data-Driven Track-and-Trace Systems
Authors: Sultanow Eldar , Chircu Alina M.
Published: April 2016

This chapter illustrates the potential of data-driven track-and-trace technology for improving healthcare through efficient management of internal operations and better delivery of services to patients. Track-and-trace can help healthcare organizations meet government regulations, reduce cost, provide value-added services, and monitor and protect patients, equipment, and materials. Two real-world examples of commercially available track-and-trace systems based on RFID and sensors are discussed: a system for counterfeiting prevention and quality assurance in pharmaceutical supply chains and a monitoring system. The system-generated data (such as location, temperature, movement, etc.) about tracked entities (such as medication, patients, or staff) is “big data” (i.e. data with high volume, variety, velocity, and veracity). The chapter discusses the challenges related to data capture, storage, retrieval, and ultimately analysis in support of organizational objectives (such as lowering costs, increasing security, improving patient outcomes, etc.).
Towards Security Issues and Solutions in Cognitive Radio Networks
Authors: Alrabaee Saed , Khasawneh Mahmoud , Agarwal Anjali
Published: April 2016

Cognitive radio technology is the vision of pervasive wireless communications that improves the spectrum utilization and offers many social and individual benefits. The objective of the cognitive radio network technology is to use the unutilized spectrum by primary users and fulfill the secondary users' demands irrespective of time and location (any time and any place). Due to their flexibility, the Cognitive Radio Networks (CRNs) are vulnerable to numerous threats and security problems that will affect the performance of the network. Little attention has been given to security aspects in cognitive radio networks. In this chapter, the authors discuss the security issues in cognitive radio networks, and then they present an intensive list of the main known security threats in CRN at various layers and the adverse effects on performance due to such threats, and the current existing paradigms to mitigate such issues and threats. Finally, the authors highlight proposed directions in order to make CRN more authenticated, reliable, and secure.
Costs of Information Services and Information Systems
Authors: Parsons Steve G.
Published: April 2016

The large number of cost terms in use regarding information services contributes to confusion in discussion and cost analysis. This confusion can largely be resolved by focusing on decisions rather than on products and cost terms. This decision focus is consistent with the proper application of total cost of ownership approaches and a real options perspective for evaluating managerial flexibility. Information services also tend to display public good-like characteristics. The non-rivalrous nature of production (i.e., low marginal cost of production) and the perishability of services have critical implications for investments and complex pricing. In addition, some information services and other Internet-based services, can display network effects, which also have important implications for managing the life cycle of the service. Finally, the implications of big data for information services are briefly considered.
Visualization of Human Behavior Data
Authors: Marcengo Alessandro , Rapp Amon
Published: April 2016

Although in recent years the Quantified Self (QS) application domain is growing, there are still some palpable fundamental problems that relegate the QS movement in a phase of low maturity. The first is a technological problem, and specifically, a lack of maturity in technologies for the collection, processing, and data visualization. This is accompanied by a perhaps more fundamental problem of deficit, bias, and lack of integration of aspects concerning the human side of the QS idea. The step that the authors tried to make in this chapter is to highlight aspects that could lead to a more robust approach in QS area. This was done, primarily, through a new approach in data visualization and, secondly, through a necessary management of complexity, both in technological terms and, for what concerns the human side of the whole issue, in theoretical terms. The authors have gone a little further stressing how the future directions of research could lead to significant impacts on both individual and social level.
Bringing the Arts as Data to Visualize How Knowledge Works
Authors: Xu Lihua , Diket Read , Brewer Thomas
Published: April 2016

Professional audiences, scholars, and researchers bring varied experiences and expertise to the acquisition of new understandings and to problem solving in visual art and literary contexts. The same breadth of experience and learning capability was found for students at eighth grade, sampled from the national population of students in the United States who were queried in the National Assessment of Educational Progress (NAEP) about formal knowledge, technical skills, and abstract reasoning in visual art and in language arts. This chapter explores statistical data relating to the presence of art specialists in the sampled eighth grade classrooms. In particular, schools with specialists in place varied in density across the country as is demonstrated through geographic mapping. Secondary analysis of NAEP restricted data showed that students in schools with art specialists performed significantly better than students in schools with other types of teachers, or no teacher. The authors surmise that art specialists conveyed something fundamental to NAEP 2008 Response scores. An aspirational model of assessment assumes broad audience clarity through knowledge visualization technology, via thematic mapping. The authors explore through analog Deleuze and Guattari's double articulation of signs in natural and programming languages and demonstrate through knowledge representation the means by which complex primary and secondary statistical data can be understood in a discipline and articulated across disciplines. This chapter considers NAEP data that might substantiate a general model of aspirational learning and associates patterns in perception discussed by researchers and philosophers.
Business Process Improvement through Data Mining Techniques
Authors: Tsironis Loukas K.
Published: April 2016

The chapter proposes a general methodology on how to use data mining techniques to support total quality management especially related to the quality tools. The effectiveness of the proposed general methodology is demonstrated through their application. The goal of this chapter is to build the 7 new quality tools based on the rules that are “hidden” in the raw data of a database and to propose solutions and actions that will lead the organization under study to improve its business processes by evaluating the results. Four popular data-mining approaches (rough sets, association rules, classification rules and Bayesian networks) were applied on a set of 12.477 case records concerning vehicles damages. The set of rules and patterns that was produced by each algorithm was used as input in order to dynamically form each of the quality tools. This would enable the creation of the quality tools starting from the raw data and passing through the stage of data mining, using automatic software was employed.
An Innovation Ecosystem beyond the Triple Helix Model
Authors: Ferraris Alberto , Leucci Stefano , Bresciani Stefano , Giunchiglia Fausto
Published: April 2016

In the current global scenario, the relevance and the importance of social innovation becomes critical in order to face this situation of crisis. For its close link with the local area in which it takes place, social innovation is deeply rooted in the overall system, and thus involves the action of many different actors. The aim of this chapter is to highlight the presence of a new managerial model that is more suitable to promote social innovation within an ecosystem. This analysis has been developed focusing on a new and innovative framework, the Social Innovation Pyramid, and on the Trentino's ecosystem based in North-East of Italy.
Big Data Analytics Demystified
Authors: Raj Pethuru
Published: April 2016

This chapter is mainly crafted in order to give a business-centric view of big data analytics. The readers can find the major application domains / use cases of big data analytics and the compelling needs and reasons for wholeheartedly embracing this new paradigm. The emerging use cases include the use of real-time data such as the sensor data to detect any abnormalities in plant and machinery and batch processing of sensor data collected over a period to conduct failure analysis of plant and machinery. The author describes the short-term as well as the long-term benefits and find and nullify all kinds of doubts and misgivings on this new idea, which has been pervading and penetrating into every tangible domain. The ultimate goal is to demystify this cutting-edge technology so that its acceptance and adoption levels go up significantly in the days to unfold.
Machine Learning Approaches for Sentiment Analysis
Authors: Agarwal Basant , Mittal Namita
Published: April 2016

Opinion Mining or Sentiment Analysis is the study that analyzes people's opinions or sentiments from the text towards entities such as products and services. It has always been important to know what other people think. With the rapid growth of availability and popularity of online review sites, blogs', forums', and social networking sites' necessity of analysing and understanding these reviews has arisen. The main approaches for sentiment analysis can be categorized into semantic orientation-based approaches, knowledge-based, and machine-learning algorithms. This chapter surveys the machine learning approaches applied to sentiment analysis-based applications. The main emphasis of this chapter is to discuss the research involved in applying machine learning methods mostly for sentiment classification at document level. Machine learning-based approaches work in the following phases, which are discussed in detail in this chapter for sentiment classification: (1) feature extraction, (2) feature weighting schemes, (3) feature selection, and (4) machine-learning methods. This chapter also discusses the standard free benchmark datasets and evaluation methods for sentiment analysis. The authors conclude the chapter with a comparative study of some state-of-the-art methods for sentiment analysis and some possible future research directions in opinion mining and sentiment analysis.
Deconstructing Smart Cities
Authors: Batty Michael
Published: April 2016

This chapter defines the smart city in terms of the process whereby computers and computation are being embedded into the very fabric of the city itself. In short, the smart city is the automated city where the goal is to improve the efficiency of how the city functions. These new technologies tend to improve the performance of cities in the short term with respect to how cities function over minutes, hours or days rather than over years or decades. After establishing definitions and context, the author then explores questions of big data. One important challenge is to synthesize or integrate different data about the city's functioning and this provides an enormous challenge which presents many obstacles to producing coherent solutions to diverse urban problems. The chapter augments this argument with ideas about how the emergence of widespread computation provides a new interface to the public realm through which citizens might participate in rather fuller and richer ways than hitherto, through interactions in various kinds of decision-making about the future city. The author concludes with some speculations as to how the emerging science of smart cities fits into the wider science of cities.
Issues Related to Network Security Attacks in Mobile Ad Hoc Networks (MANET)
Authors: Singh Rakesh Kumar
Published: April 2016

Mobile Ad Hoc Network (MANET) is a collection of communication devices or nodes that wish to communicate without any fixed infrastructure. The nodes in MANET themselves are responsible for dynamically discovering other nodes to communicate. A number of challenges like open peer-to-peer network architecture, stringent resource constraints, shared wireless medium, dynamic network topology etc. are posed in MANET. In this research, we identify the existent security threats an ad hoc network faces, the security services required to be achieved and the countermeasures for attacks in each layer. To accomplish our goal, we have done literature survey in gathering information related to various types of attacks and solutions, as well as we have made comparative study to address the threats in different layers. Finally, we have identified the challenges and proposed solutions to overcome them. There is no general algorithm that suits well against the most commonly known attacks such as wormhole, rushing attack, etc.
Advanced Dimensionality Reduction Method for Big Data
Authors: Das Sufal , Kalita Hemanta Kumar
Published: April 2016

The growing glut of data in the worlds of science, business and government create an urgent need for consideration of big data. Big data is a term that describes large volumes of high velocity, complex and variable data that require advanced techniques and technologies to enable the capture, storage, distribution, management, and analysis of the information. Big data challenge is becoming one of the most exciting opportunities for the next years. Data mining algorithms like association rule mining perform an exhaustive search to find all rules satisfying some constraints. it is clear that it is difficult to identify the most effective rule from big data. A novel method for feature selection and extraction has been introduced for big data using genetic algorithm. Dimensionality reduction can be considered a problem of global combinatorial optimization in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, to obtain the accuracy and saves the computation time and simplifies the result. A genetic algorithm was developed based approach utilizing a feedback linkage between feature selection and association rule using MapReduce for big data.
Collective Bargaining as a Tool for Industrial Conflict in Organization and Conflict Resolution
Authors: Ajayi Kassim Olusanmi , Muraina Kehinde O.
Published: April 2016

The major factor militating against organizational productivity is conflict between individuals or groups of individuals and the management. In any work situation, people are bound to have different interests and aspirations which may tend to conflict with each other. For example, management is committed to pursing a goal of profit maximization policies, while the workers through their unions want higher wages and a lucrative welfare package which tends to result in higher cost of doing business to the management. At times, unions want effective participation in most organizational decisions, even at the expense of encroaching on areas that fall exclusively within the confines of management prerogatives. Management cannot but resist this unwholesome behaviour. In the process, conflict would ensue. Therefore, an important duty of line for mangers to promote organizational productivity is through peaceful resolution of conflicts in the organization.
Habilitation, Healthy Agency, and Patient-Participation
Authors: Becker Lawrence C.
Published: April 2016

This chapter argues, on ethical grounds, that wherever possible patient-participation must be kept consistent with the level of healthy rational agency that is, or might be, available to the patient. Merely compliant patient-participation is not enough. This is also true of patient-adaptation or adjustment. Mere adaptive compliance is not enough. Accepting patient-consent, cooperation, and compliance as an adequate indication of genuine agentic participation is often hard to avoid, but such acceptance is also often inconsistent with appropriate healthcare. These conclusions follow, as a matter of empirically informed practical ethics, from an analysis of the lifelong habilitative tasks that face every human being, and the role that the patient's healthy agency plays in the development, protection, or restoration of the patient's agency itself and the patient's basic good health generally.
The Patient-Centered Medicine as the Theoretical Framework for Patient Engagement
Authors: Lidia Borghi , Federica Galli , Maria Vegni Elena Anna
Published: April 2016

The present contribution will describe the origin, development and main characteristics of the patient-centered medicine; the literature on patient-centeredness, in particular in the field of chronic disorders, will be discussed and the importance of this approach underlined; arguments about the importance of patient-centered medicine as theoretical frame founding and supporting the concept of patient engagement will be highlighted, considering that only within this medical epistemology the patient's engagement can find a full and complete expression.
A Relational Perspective on Patient Engagement
Authors: Donato Silvia , Bertoni Anna
Published: April 2016

Research on the engagement of patients and their partners and the literature on couple relationships have remained surprisingly separated. In response to this gap, the first aim of the chapter is to show the advantages of an integration of these two lines of research in the context of promoting engagement in patients and their partners. Particular attention is devoted to couples' stress and coping literature and to those few studies that investigated the role played for patient engagement by characteristics of patients, partners, and their relationship. Couple-based research can inform engagement literature about facilitators and barriers to couples' coping with illness and about how to promote engagement in the context of the couple. Within this research, the concept of dyadic coping can be especially helpful in understanding how partners can effectively deal with the stress related to acute and chronic illness as well as the barriers to this process. A second aim of the chapter is to connect the suggestions from couple-based research with the field of engagement promotion.
The Light Side of Preterm Behavioral Epigenetics
Authors: Provenzi Livio , Borgatti Renato , Montirosso Rosario
Published: April 2016

Preterm infants need long-lasting hospitalization in the Neonatal Intensive Care Unit (NICU). On the one hand, the NICU stay constitutes an early adverse experience, due to highly stressful experiences. On the other hand, Developmental Care (DC) interventions, including caregiver engagement, can exert neuro-protective effects for preterm infants. Recent evidence in the field of behavioral epigenetics is revealing the biochemical pathways through which adverse and care experiences are embedded in early human development through epigenetic mechanisms. Nonetheless, the application of behavioral epigenetics to preterm birth and NICU stay is still at its beginning. In the present chapter, insights are provided for the application of behavioral epigenetics to the study of the biochemical underpinnings of NICU-related stress and care, with a specific focus on caregiver engagement. This contribute should be intended as a preliminary roadmap to guide future behavioral epigenetic research on the adverse and protective effects of early NICU care of preterm infants.
The Value of Measuring Patient Engagement in Healthcare
Authors: Graffigna Guendalina , Barello Serena
Published: April 2016

The concept of patient engagement offers a unique opportunity to inform our understanding of patients' ability to be active in managing their care. However, unless promoting the active role of patients is today identified as a priority to promote care quality, a wide debate still exists on how to translate this principle into practice and how to assess initiatives aimed at increasing the level of patient participation in their care. Measuring patient engagement along the care course might ensure that the medical care truly serves patients' needs, priorities, and preferences. Unless the measurement of patient engagement is today a big issue for policy makers and healthcare practitioners, only few scientifically validated assessment tools currently exist to identify patients' level of involvement in their healthcare. In this chapter authors review the main validated tools currently available in the scientific community devoted to assess the patients' ability and availability to be actively engaged in their care, with a particular focus on the recently developed Patient Health Engagement Scale, specifically designed to assess the emotional and psychological adaptation of patients along their care process and their level of engagement in the healthcare management.
Smart Grid and Demand Side Management
Authors: Ozpinar Alper , Ozil Eralp
Published: April 2016

Energy becoming more and more crucial and critical in the civilized populations and locates itself as one of the major requirements of living standards. Obtaining the energy from fossil fuels still is one of the common sources of energy production; however, there is a common understanding of increasing the potential use of renewables, carbon capture and storage, energy efficiency and intelligence and smart applications for collecting, distributing and transmission of the energy between the supply and demand locations. Those applications and generating the new policies, roadmaps in order to make an energy revolution and increase the usage of low-carbon energy technologies targeting the decrease of energy related emissions. In this chapter, the authors explains the common issues about smart grid and demand side management and possible use artificial intelligence and metaheuristic algorithms for smart grid and demand side management optimization and scheduling.
Unified Wavelet Transform Analysis Adapted to Different Biomedical Applications
Authors: Garg Girisha , Singh Vijander
Published: April 2016

In biomedical signal processing, wavelet transform has gained an edge over other existing methods due to its highly efficient transforming capabilities. Relative wavelet energy is a technique used to extract meaningful and concise information from wavelet coefficients for signal classification. The possibility of classifying large datasets combined with the simplicity of the process makes this technique very attractive for many applications. The focus is on testing and validating the use of this technique on different signals keeping in view the specific needs for various biomedical applications. The importance of this unified technique is highlighted with statistical results and validation on several benchmark datasets.
Heuristic Optimization-Based Clustering Solution for Large Facility Location Problems
Authors: Küçükdeniz Tarık , Esnaf Şakir
Published: April 2016

Facility location-allocation problems are one of the most important decision making areas in the supply chain management. Determining the location of the facilities and the assignment of customers to these facilities affect the cap of achievable profitability for most of the companies' supply chains. Geographical clustering of the customers, while considering their demands, has been proved to be an effective method for the facility location problem. Heuristic optimization algorithms employ an objective function that is provided by user, therefore when the total transportation cost is selected as the objective function, their performance on facility location problems is considered to be promising. The disadvantage of population based heuristic optimization algorithms on clustering analysis is their requirement of the increased number of dimensions to represent the complete solution in a single member of the population. Thus in two-dimensional geographical clustering, number of dimensions required for each population member is double of the number of required facility. In this study, a new neighborhood structure for the standard particle swarm optimization algorithm is presented for uncapacitated planar multiple facility location problem. This new approach obsoletes the need for higher number of dimensions in particles. Proposed method is benchmarked against k-means, fuzzy c-means, fuzzy c-means & center of gravity hybrid method, revised weighted fuzzy c-means and the standard particle swarm optimization algorithms on several large data sets from the literature. The results indicate that the proposed approach achieves lower total transportation cost within less computational time in facility location problems compared with the standard particle swarm optimization algorithm.
Effect of aging on the configurational change of the aortic arch
Authors: Kojima Atsuhiro , Saga Isako
Published: April 2016

We explored the relationship between aging and the configuration of the aortic arch using computed tomography angiography (CTA). We retrospectively reviewed CTA obtained in 140 cases. The configuration of the aortic arch was categorized into three types based on the criteria mentioned by Madhwal et al., and the relationships between each configuration and patient characteristics were analyzed. Anomalies of the aortic arch were also explored. Twenty patients had a type-1 aortic arch (mean age, 56.1 years), 30 patients had a type-2 aortic arch (mean age, 66.3 years), and 89 patients had a type-3 aortic arch (mean age, 71.7 years). The mean age of patients with a type-3 aortic arch was significantly higher than that of patients with a type-1 aortic arch. No significant correlations between the type of aortic arch and other factors, such as smoking habit, were seen. The configuration of the aortic arch in our study appears to be significantly affected by the age of the patients.
Using patient-centered end-points in older adults participating in clinical trials
Authors: Mangoni Arduino A. , Ruxton Kimberley
Published: April 2016

Conventional end-points, primarily based on the pharmacodynamic effects of a specific drug, are used to assess the efficacy of pharmacological treatment in clinical trials. However, their application and interpretation in complex frail older patients, a patient group with high inter-individual variability, multiple coexisting disease states and prescribed medications, is becoming increasingly questionable. National surveys and qualitative studies have convincingly shown that the maintenance of functional independence is key to self-rated health and well being in old age. Therefore, the use of unconventional, patientcentered, end-points focused on functional status and perceived health seems appropriate, in combination with conventional end-points, to comprehensively investigate the impact of pharmacological treatments in this patient group. The recent availability of objective, quantifiable, and robust scoring tools, such as the multidimensional prognostic index, to assess key functional domains and clinical outcomes offers a unique opportunity to adequately characterize patient-centered endpoints in future clinical trials in older patients.
Evolutionary Genomics: Supplement Aims and Scope
Authors: Itan Yuval , Gerbault Pascale , Pines Gur
Published: April 2016

This supplement is intended to focus on evolutionary genomics. Evolutionary Bioinformatics aims to provide researchers working in this complex, quickly developing field with online, open access to highly relevant scholarly articles by leading international researchers. In a field where the literature is ever-expanding, researchers increasingly need access to up-to-date, high quality scholarly articles on areas of specific contemporary interest. This supplement aims to address this by presenting high-quality articles that allow readers to distinguish the signal from the noise. The editor in chief hopes that through this effort, practitioners and researchers will be aided in finding answers to some of the most complex and pressing issues of our time.
Maternal Obesity and Congenital Anomalies: Its Implications and Future Trends
Authors: Madhab Gayatri , Bharadwaz Arindam
Published: April 2016

Objectives

To find the current body of evidence for maternal obesity's association with and its burden on congenital malformations and to estimate its financial and mortality implications as well as future trend.

Materials and methods

Thorough search and review of current literature with deductive interpretations.

Results and evidence

Obesity is associated with certain types of congenital anomalies like neural tube defects (NTD), congenital heart defects (CHDs), orofacial defects, etc. The burden in absolute numbers for major CHD and NTD attributable to obesity can be estimated to be 0.42 to 1.05 and 0.588 to 1.12 per 10,000 births respectively.

Remarks and conclusion

Contribution of maternal obesity on perinatal mortality could be anywhere from 6 to 20 per 1,00,000 births. However, its economic implications could be substantial. Current trend indicates that contribution of obesity to certain congenital anomalies may increase in future.

How to cite this article

Madhab G, Bharadwaz A. Maternal Obesity and Congenital Anomalies: Its Implications and Future Trends. J South Asian Feder Obst Gynae 2015;7(3):134-142.
Successful Management of a Scary Case of Cesarean Scar Pregnancy with Combined Treatment using Methotrexate, Uterine Artery Embolization and Suction Evacuation
Authors: Joseph Santhosh , Vasanthalakshmi Gonnabaktula Naga , Vishwanath Usha , Anitha M
Published: April 2016

Cesarean scar pregnancy (CSP) is the rarest type of ectopic pregnancy implanted in the myometrium at the site of the previous cesarean section scar. It may lead catastrophic complications like uterine rupture and uncontrollable hemorrhage.4 Early diagnosis can offer treatment options of avoiding uterine rupture and hemorrhage, thus, preserving the uterus and future fertility.

The conservative treatment can be by local and/or systemic administration of methotrexate, dilatation and curettage, excision of trophoblastic tissues (laparoscopy/laparotomy), bilateral internal artery ligation with trophoblastic evacuation and uterine artery embolization7 combined with curettage and/ or methotrexate. We did successful treatment of a viable CSP by systemic injections of methotrexate followed by selective uterine artery embolization in combination with dilatation and curettage.

How to cite this article

Mehta P, Vishwanath U, Joseph S, Anitha M. Successful Management of a Scary Case of Cesarean Scar Pregnancy with Combined Treatment using Methotrexate, Uterine Artery Embolization and Suction Evacuation. J South Asian Feder Obst Gynae 2015;7(3):143-147.
Assessment of the Efficacy of Different Methods of Second Trimester Abortion: An Initial Experience in Eastern Nepal
Authors: Chhetri Shailaja , Pokharel Hanoon , Rijal Rohit , Lama Sushma
Published: April 2016

Background

Abortions performed in the second trimester account for a disproportionate amount of abortion-related morbidity and mortality.

Materials and methods

To assess the effectiveness of medical vs the surgical methods for second trimester abortions.

Results

A total number of 141 patients were included in the study from September 2009 till August 2012 who underwent second trimester abortion. A total number of 75 patients underwent medical abortion and 66 patients underwent surgical dilatation and evacuation (D&E). Surgical treatment with D&E was more effective and safer than medical treatment for second trimester abortion, The overall complications were seen more in the medically treated cohort with 20 vs 6% in the surgical cohort (p = 0.02), with higher incidence of incomplete abortion (13 vs 0) and a higher amount of blood loss (129.4 ± 20.6 ml vs 69.6 ± 11.4 ml, p < 0.001) requiring transfusion.

Conclusion

This study demonstrates that the surgical method of second trimester abortion is more effective and safe procedure in experienced centers and as compared to medical methods. The complication rates are lower and it also is more cost-effective as it can be performed in an outpatient setting and does not require hospital admission.

How to cite this article

Chhetri S, Pokharel H, Rijal R, Lama S. Assessment of the Efficacy of Different Methods of Second Trimester Abortion: An Initial Experience in Eastern Nepal. J South Asian Feder Obst Gynae 2015;7(3):182-184.
Twin Pregnancy Discordant for Anencephaly with Severe Polyhydramnios
Authors: Najam Rehana
Published: April 2016

Twin pregnancy is a high-risk pregnancy with many complications. Anencephaly is one anomaly which is commoner in twins than in singleton pregnancy. Dizygotic as well as monozygotic twins discordant for structural anomaly requires an individual approach regarding pregnancy complications. The major issue with these pregnancies require early diagnosis and management options, especially if diagnosed early. Selective fetocide is a management option in at least dizygotic twins.

How to cite this article

Najam R. Twin Pregnancy Discordant for Anencephaly with Severe Polyhydramnios. J South Asian Feder Obst Gynae 2015;7(3):223-224.
An Unusual Case of Anterior Vaginal Wall Cyst
Authors: Anitha GS , Prathiba M , Gowri Mangala
Published: April 2016

Vaginal cysts are rare and are mostly detected as an incidental finding during a gynecological examination. Gartner duct cysts, the most common benign cystic lesion of the vagina, represent embryologic remnants of the caudal end of the mesonephric (Wolffian) duct. These cysts are usually small and asymptomatic and have been reported to occur in as many as 1% of all women. A 17-year-old unmarried girl presented with mass per vagina since one and a half year. On examination, anterior vaginal wall cyst of 8 × 4 × 3 cm was detected. Surgical excision of the cyst was done under spinal anesthesia by sharp and blunt dissection. The cyst was filled with mucoid material and histopathological examination confirmed Gartner origin. This is a rare case of large Gartner cyst.

How to cite this article

Anitha GS, Prathiba M, Gowri M. An Unusual Case of Anterior Vaginal Wall Cyst. J South Asian Feder Obst Gynae 2015;7(3):227-230.
Takayasu's Arteritis and Pregnancy
Authors: Nanda Smiti , Malhotra Naveen , Malhotra Vani , Malhotra Parveen , Chauhan Meenakshi
Published: April 2016

Introduction

Takayasu's arteritis (TA) is a rare clinical entity characterized by the progressive obliteration of the aortic arch and the main vessels arising from it and, in some cases of the thoracic and abdominal aorta and its main branches.

Case

We report a case in which diagnosis of TA was made 6 years ago and present pregnancy was successfully managed.

Conclusion

Multidisciplinary management is essential for satisfactory clinical outcome during pregnancy and their blood pressure should be strictly controlled for a favorable maternal and fetal outcome and mode of delievery should be planned.

How to cite this article

Malhotra V, Malhotra P, Nanda S, Chauhan M, Malhotra N. Takayasu's Arteritis and Pregnancy. J South Asian Feder Obst Gynae 2015;7(3):234-235.
Convulsions: Eclampsia or Malaria or Both!
Authors: Jaju PB , Bhavi Shruti B
Published: April 2016

Introduction

Prevalence of malaria in pregnancy is 1.4%. A high index of suspicion is most important in the diagnosis of malaria and should be differentiated from other complications like eclampsia, intrauterine sepsis.

Case Report

Gravida 3 para 2 living 1 (G3P2L1) with 28 weeks gestation was referred with high blood pressure (BP), severe anemia. She was afebrile, severe pallor +, pedal edema +, pulse rate (PR)—110/ min, BP—140/80 mm Hg, per abdomen (P/A)— Ut 28 to 30 weeks size relaxed with fetal heart sounds (FHS) regular. Hemoglobin (HB) 5.3 gm%, platelet count 80,000. After 3 days, patient threw one convulsion. Low dose MgSO4 regime given. Peripheral smear (PS) for malarial parasite (MP) vivax positive and injection quinine 1200 mg in 10% dextrose started. She was induced and delivered.

Discussion

In pregnancy malaria is more common, more atypical, more severe and more fatal. Once diagnosed treatment should be started immediately and pregnant woman should be given full doses of antimalarials. Both eclampsia and malaria are to be treated.

How to cite this article

Jaju PB, Bhavi SB. Convulsions: Eclampsia or Malaria or Both! J South Asian Feder Obst Gynae 2015;7(3):245-246.