bluuebunny/crossref_metadata_2025 huggingface dataset:
L’accompagnement citoyen pour l’intégration des aînés ayant un trouble mental
Authors: Aubin Ginette , Therriault Pierre-Yves
Published: November 2018

À partir des résultats d’une étude pilote, cet article met en lumière les effets d’une approche d’accompagnement citoyen pour l’intégration dans la communauté d’aînés ayant un trouble mental ou des difficultés psychosociales, à partir d’expériences croisées. L’intégration dans la communauté est envisagée comme un processus de reprise du pouvoir d’agir, menant à l’accomplissement d’activités significatives en réciprocité avec des membres de la communauté. L’accompagnement proposé consiste en des rencontres hebdomadaires personnalisées d’un aîné avec un citoyen provenant de la communauté. Les effets de cet accompagnement ont été documentés à l’aide d’entrevues, de questionnaires auprès des accompagnés et des journaux de bord des accompagnateurs. Des effets positifs sur le pouvoir d’agir ont été observés et rapportés, les intentions des accompagnés se traduisant en actions, par exemple, sur le plan de la dimension physique, par la mobilisation dans des activités nouvelles, sur le plan social, par une augmentation des interactions sociales et sur le plan psychologique, par un rehaussement du sentiment de communauté. Cette approche citoyenne pourra ainsi constituer une mesure alternative intéressante pour répondre aux besoins de socialisation et d’inclusion d’aînés ayant un trouble mental ou des difficultés psychosociales.
L’écologisme, une critique du capitalisme ? L’école française des conventions au risque de la question environnementale
Authors: Carnoye Leslie
Published: November 2018

La pensée conventionnaliste de l’environnement se heurte à un problème central : l’absence d’un ordre de grandeur écologiste qui obéisse à la même grammaire que les six autres. Cet article propose une piste afin de surmonter ce problème. Il s’agit d’envisager l’écologisme, non plus sous le modèle idéal de la cité, mais comme une critique du capitalisme. Dans cette perspective, les fondements théoriques et l’effectivité historique de la critique écologiste du capitalisme sont étudiés. Codes JEL  : B5, N5, O13, O440, P10, Q5
L’arme alimentaire jalons pour l’histoire d’un concept ( xvii e - xix e siècles)
Authors: Clément Alain
Published: November 2018

L’accès à la nourriture est le premier besoin de l’humanité et l’arme alimentaire correspond à l’ensemble des moyens mis en œuvre pour affamer volontairement une population. Quand un pays dispose du monopole d’exportation d’une denrée agricole essentielle ou d’une position dominante sur le marché d’une telle denrée, il peut utiliser ses moyens de gestion et de stockage pour exercer des pressions politiques sur les pays importateurs de cette denrée. L’arme alimentaire est donc un pouvoir mortel qu’un ou plusieurs exportateurs de céréales (notamment) peuvent détenir en condamnant à la famine un pays importateur dépendant. L’usage de l’arme alimentaire a été maintes fois observé au cours de l’histoire. Notre analyse retrace les formes variées de l’arme alimentaire, les conditions économiques de sa mise en œuvre, ses conséquences ainsi que les moyens de s’en protéger quand les pays sont menacés par cette arme. Nous étudions les textes économiques entre le xvii e et le xix e siècle, période au cours de laquelle la question des vivres devient une question centrale pour les économistes. Codes JEL  : B11, B12
Ce qu’une théorie économique historicisée veut dire. Retour sur les méthodes de trois générations d’institutionnalisme
Authors: Labrousse Agnès , Vercueil Julien , Chanteau Jean-Pierre , Grouiez Pascal , Lamarche Thomas , Michel Sandrine , Nieddu Martino
Published: November 2018

Cet article associe trois approches issues de l’institutionnalisme historique : l’école historique allemande, l’institutionnalisme américain originel et la théorie de la régulation. Il en dégage les principes méthodologiques partagés et analyse leur application au processus d’élaboration théorique. Codes JEL  : B15, B25, B40, B52, E02, Z13
Pourquoi tant de malls à Téhéran ?
Authors: des Vallières Ronan
Published: November 2018

Au tournant des années 2010, Téhéran a connu une explosion du nombre de centres commerciaux. Amorcé dans les années 1990, ce phénomène perdure alors même que ces-derniers s’avèrent très peu rentables. Pour expliquer cet état de fait, l’article s’inscrit dans le champ de l’économie politique de la production urbaine et mobilise les résultats d’une enquête réalisée auprès de professionnels de la promotion immobilière commerciale à Dubaï et Téhéran. Son hypothèse centrale est que la multiplication de ces établissements s’explique non par des stratégies entrepreneuriales mais par leur qualité d’actifs financiers, permettant une rentabilisation foncière rapide. Cet enjeu foncier s’inscrit dans la centralité historique du secteur immobilier à Téhéran, dans les évolutions de ce secteur et des ressources budgétaires municipales qui ont conduit les investisseurs et la mairie à favoriser l’immobilier commercial, et dans la récente émergence d’un secteur parapublic à même d’investir dans ces grands projets. Le jeu d’acteurs à l’œuvre révèle certains paradoxes de la métropolisation en Iran et de la libéralisation de son économie.
From Einstein Theories to Least Action Principle, a Relativistic Error of a Limit Case of Classical Mechanics
Authors: Massaro Alessandro
Published: November 2018

The authors prove that the standard least action principle implies a more general form of the same principle by which they can state generalized motion equation including the classical Euler equation as a particular case. This form is based on an observation regarding the last action principle about the limit case in the classical approach using symmetry violations. Furthermore, the well-known first integrals of the classical Euler equations become only approximate first integrals. The authors also prove a generalization of the fundamental lemma of the calculus of variation and they consider the application in electromagnetism. This chapter is an enhanced version of a published work. It proves the existence of particular relativistic error condition in classical mechanics, potentially significant on experiments of light propagation in matters. The work includes a discussion of applications potentially correlated with the found particle motion error condition.
Application of Statistical Quality Control in Testing Labs for Estimation of Machine Interference
Authors: Mandavgade Nitin K. , Jaju Santosh B. , Lakhe Ramesh R.
Published: November 2018

The performance and maintenance of testing laboratories is a prime issue. The quality of coal test results not only depends on performance of individual results but it also depends on the performance of various tests in the same laboratory. Machine interference is a significant problem in many manufacturing system and testing equipment. The variation of results for testing equipment may be due to various factors which need to calculate the uncertainty of measurement to show the accuracy of the machine. In case of coal testing laboratory, the plant layout and surrounding environment affects the performance of the system. The machine interference comes under variable causes which may affect the result. This chapter proposes a methodology for constructing system performance measures, finding out the various factors responsible for variations in result. The chapter deals with estimation of machine interference existence using variable control chart approach for coal testing equipment. The analysis of results for such machine interference will be useful and significant for system designers and practitioners.
Measurement Analysis of Ultra-Wide-Band and Ultra-Wide-Band-MIMO Antennas
Authors: Sharma Madan Kumar , Kumar Mithilesh Kumar , Singh Satya P.
Published: November 2018

This chapter mainly focused on the recent trends in the antenna design techniques for next-generation wireless communication systems. Ultra-wideband antenna and multi-input-multi-output antennas are very useful to achieve higher data rates. An antenna is a transducer that changes guided electromagnetic energy in a transmission line to radiated electromagnetic energy in free space. Antennas may also be observed as an impedance transformer, coupling among an input or line impedance, and the impedance of free space. The looming widespread commercial deployment of ultra-wideband (UWB) systems has flashed new interest in the subject of ultra-wideband antennas. The power levels approved by the FCC mean that every dB counts in a UWB system as much as or possibly even more so than in a standard narrowband system. Thus, in effect, UWB antenna is a precarious part of an overall UWB system design. Basic principles for ultra-wide-band (UWB) antenna design and radiation are presented and discussed in this chapter.
Exploring the Personal Drive Behind Small Social-Venture Set-Ups in the Netherlands
Authors: de Vries Ido
Published: November 2018

This chapter describes the development and growth of small social ventures in the Netherlands. It focusses on the motivations and purposes of owner-operator and micro or small scale social entrepreneurs creating social value in the transition of the Dutch welfare domain. Local municipalities are developing policies to support those social venture set-ups. But dealing with local policies is found not to be an easy task for small scale social entrepreneurs. Two aspects of the hindrance for social venture start-ups are elaborated: the hybridity of social entrepreneurship, combining social value logic and the logic of entrepreneurship; and the difficulties of dealing with different aspects of policies of cities in the Netherlands. An ecological system supportive for small social venture creation respecting the personal purpose of social entrepreneurs is outlined.
Faith-Based Social Enterprise and Value Creation in Communities
Authors: Oham Charles
Published: November 2018

This chapter explores the value creation activities of faith-based social enterprises (FBSE) in the economy. It discusses the challenges being faced by faith-based organizations (FBOs) from which FBSEs emerge. It makes the case for a coherent strategy in terms of a closer engagement of government with FBSEs that could scale up social impact and create systemic change. An account of FBSEs as a catalyst for value creation through economic and community development is presented using examples and case studies. It posits that a more precise engagement with this sector should be adopted to bring critical mass to society.
Financing Social Enterprises
Authors: Liu Chen
Published: November 2018

This chapter discusses funding and financing issues of small and micro social enterprises (SEs) following a systematic approach. It conducts a systematic review of the SE financing literature and proposes a systematic model to examine the SE financing ecosystem. Specifically, the chapter discusses some traditional financing sources of SEs, including internal money, donations, government grants, and conventional debt and equity and examines SEs' advantage and challenges in securing financing using these traditional ways. To address the challenges of SE financing, this chapter proposes a systematic approach of solution and discusses some new and innovative sources of financing for SEs, such as the social impact bonds and the social venture capital. It then discusses crowdfunding and its best use for various types and stages of SEs. The chapter also suggests a list of future research ideas.
Relationship Between Mission Drift and Financial Strategies in Social Enterprises
Authors: Bastida Ramon , Mas-Machuca Marta
Published: November 2018

Social enterprises (SEs) have an important role in the social services provision. Many of those enterprises provide services, such as care services to elderly people and young people at risk of exclusion, work integration services, mediation, etc. In European Union (EU) countries, public administrations are obliged to provide these services to the citizens, although they externalize the provision to SEs. In this chapter, the financial strategies of SEs are analyzed in order to assess if they have any impact on mission drift. The analysis is based on the experiences of three SEs that provide social services in Catalonia, Spain. Several interviews with managers and board members of SEs were done. The results indicate that there is an important financial dependency of these SEs on the public administration. Therefore, SEs have problems to remain mission-focused, and a mission drift into market positions has been observed.
Social Value and Public Services Procurement
Authors: Maher Chi
Published: November 2018

The UK government aims to increase the role of social enterprise as a vehicle to deliver public services directly to citizens and local communities. This chapter explores small social enterprises' experience of public service procurement in the UK including the introduction of the Social Value Act 2012. To understand small third sector social enterprises' experiences of gaining access to public services contracts, face-to-face interviews were conducted with 11 chief executive officers (CEOs) using an interview guide. Empirical evidence obtained suggests that some procurement policies and processes are impacting on these organizations' developments, growth, partnership arrangements and value creation.
Challenges for Asian American and Immigrant Asian Women in the U.S. Higher Education Administration
Authors: Roy Sayani
Published: November 2018

In spite of this rising presence and educational attainment, Asian American and immigrant Asian women are notably underrepresented in academic leadership roles. Asian American women fall far behind White females in leadership positions in higher education, especially in community colleges that are assumed to be more liberal in acceptances than four year universities while nurturing women in administrative positions. Only nine Asian American women held presidential positions in community colleges in 2010. There was no immigrant Asian woman who reached the supreme leadership position. This chapter explores the question: Why are Asian American and immigrant Asian women, in spite of their rising presence in academia, severely underrepresented in leadership roles in academic administration? This is the point of focus this chapter engages to study from existing research.
Women and Technology
Authors: Loy Jennifer
Published: November 2018

This chapter looks at challenges for women in leadership in technical disciplines, specifically mechanical and civil engineering. It considers strategies being employed to correct the gender imbalance and highlights the particular challenges faced by women working in these disciplines. The chapter responds to these challenges by building on the need for changes in thinking highlighted by thought leaders in the 21st century, to suggest a way forward for creating change that directly relates to the role of women in leadership in the discipline. The chapter is relevant for scholars researching gender equality and also for university leaders in developing strategies for adopting women in leadership initiatives in a changing educational landscape. It will also be of interest to academics within these and related disciplines as well as academics involved in the delivery of professional development courses for women in leadership.
Women in Leadership
Authors: Zappala-Piemme Kerri Erin
Published: November 2018

Through observation, research, shared experiences, and collective wisdom gained from failure and success, this chapter explores best practice to help leaders navigate the challenges and demands that they encounter in their careers. The topics explored in this chapter are critical for males and females alike because they provide specific examples of best practice and research on how to become an effective leader. Yet they are especially relevant for women in leadership positions because data and scenarios are shared that shed light on the gender inequities that still exist in leadership today. Understanding the unique dynamics that women face and changing practices and approaches to address these issues are necessary. Each topic assists leaders in positioning themselves so they are optimizing their potential for success.
Medi-Rings for Senior Citizens
Authors: Yellampalli Siva Sankar , Kiran N. Ravi , Malapur Ishwar
Published: November 2018

In this chapter, the authors propose Medi-Ring, a compact system to carry all the medical records for senior citizens to avoid improper medication, delay in treatment in emergency situation. The three main aspects of Medi-Ring are NFC technology, system memory, and a controller. NFC technology is used for transferring the data, the system memory is used to store the medical records which includes patient's details, doctor's prescription, and all other medical details. A controller is used to control the whole system. As the proposed Medi-Ring is wearable, compact, and flexible, it can be used as a medical companion for senior citizens.
Edge Detection on Light Field Images
Authors: Sabrina Yessaadi , Tayeb Laskri Mohamed
Published: November 2018

Digital fundus imaging is becoming an important task in computer-aided diagnosis and has gained an important position in the digital medical imaging domain. One of its applications is the retinal blood vessels extracting. Object detection in machine vision and image processing has gained increasing interest due to its social and security potential. Plenoptic imaging is a promising optical technique. This technique computes the location and the propagation direction information of the object light, which are used as efficient descriptors to detect and track the object displacement. In this chapter, the authors use an edge detection technique to extract and segment blood vessels in the retinal image. They propose a novel approach to detect vessels in a simulated light fields fundus image, based on the image representation with the first and the second order derivative, well known as gradient and Laplacian image descriptors. Since the difficulties to get a light field image of a fundus in the retinal image, the authors test their model in the image provided by Sha Tong et al.
Application of Big Data in Digital Epidemiology
Authors: Naaz Sameena , Siddiqui Farheen
Published: November 2018

Epidemiology is the study of dynamics of health and disease in human population. It aims to identify the occurrence, pattern, and etiology of human diseases so that the causes of these diseases can be understood, which in turn will help in preventing their spread. In traditional epidemiology, the data is collected by various public health agencies through various means. Many times, the actual figures vary a lot from the one reported. Sometimes this difference is due to human errors, but most of the time, it is due to intentional underreporting. Big data techniques can be used to analyze this huge amount of data so as to extract useful information from it. The electronic health data is so large and complex that it cannot be processed using traditional software and hardware. It is also not possible to manage this data using traditional data management tools. This data is huge in terms of volume as well as diversity and the speed at which it is being generated. The ability to combine and analyze these different sources of data has huge impact on epidemic tracking.
Innovative Methods in Financial Risk Management
Authors: Doguc Ozge
Published: November 2018

The regulations that emerged from the global financial crisis of 2008 and fines that were imposed afterwards triggered a wave of changes in how risk is managed. Innovative methods for risk management became more important as the standards for compliance and management tightened. Institutions also invested in strengthening their risk cultures and involved their boards more closely in key risk decisions. This chapter discusses major risk factors for financial institutions and the innovative solutions that they introduced to manage risk better. Innovative solutions in risk management are not limited to advances in technology such as machine learning and data mining, but also include new regulations, better monitoring, and stricter auditing. Financial institutions improved boards' oversight of risk, created new committees for risk assessment and monitoring. and developed new methodologies for risk management.
Facing Disruptive Innovation
Authors: Tammam Davide , Brunetta Federica , Vicentini Francesca , Graziano Elvira Anna
Published: November 2018

Technological change is creating strategic and managerial challenges. This holds true in the case of disruptive innovations, which are reshaping industry boundaries, exposing organizations to new competitive logics and threats. Companies face the need of new strategies and innovative thinking capabilities. This chapter provides a systematic literature review on the role of disruptions by identifying the changes they have brought in the markets and the new challenges for managers, especially within the domain of strategic management, since disruptive innovations may modify strategic and innovative thinking. The final analysis has been conducted on 19 journal articles published between 1995 and 2018. The results show the strong interplay existing between strategy and innovation management, but they also highlight the relationship between innovative thinking, learning, human capital, and capabilities' acquisition. Furthermore, they encourage further research in the light of the multiple trajectories offered by innovation and disruptions for diverse companies and industries.
How Social Media is Transforming Marketing?
Authors: Kırcova İbrahim , Enginkaya Ebru
Published: November 2018

Integrating companies to digital channels is a necessity to build and maintain a competitive advantage in today's market conditions. In the business environment, companies realize that sustainable competitive advantage can be gained only by understanding customers' needs and expectations, developing activities that meet their demands, ease their work, and engage them to the brand to create difference and value. Success in marketing will be driven by an effective communication and consumer experience. Marketing and brand managers are in the process of determining how social media tools impact them and what their digital transformation approach and communication strategy should be. This chapter examines the importance of social media for companies and benefits of social media on the performance of marketing processes that enable better communication, planning, and execution from consumer engagement to consumer purchase.
Big Data Security Framework for Distributed Cloud Data Centers
Authors: Thota Chandu , Manogaran Gunasekaran , Lopez Daphne , Vijayakumar V.
Published: November 2018

The rapid development of data generation sources such as digital sensors, networks, and smart devices along with their extensive use is leading to create huge database and coins the term Big Data. Cloud Computing enables computing resources such as hardware, storage space and computing tools to be provided as IT services in a pay-as-you-go fashion with high efficiency and effectiveness. Cloud-based technologies with advantages over traditional platforms are rapidly utilized as potential hosts for big data. However, privacy and security is one of major issue in cloud computing due to its availability with very limited user-side control. This chapter proposes security architecture to prevent and secure the data and application being deployed in cloud environment with big data technology. This chapter discuss the security issues for big data in cloud computing and proposes Meta Cloud Data Storage architecture to protect big data in cloud computing environment.
Sustainable Cloud Computing Frameworks for E-Government
Authors: Leone Sabrina , Biancofiore Giovanni
Published: November 2018

Computerizing the country is a priority for the Italian government, which has set up the Digital Agenda for innovation driven by information and communication technologies to deliver smart, sustainable and inclusive growth, in adherence to European Union's policies. Cloud computing is one of the pillars of this strategic plan, since by accelerating the implementation of the Digital Agenda, it represents a chance for Italy to meet its increasingly crucial need for innovation and revitalization of competitiveness. Among the different solutions that Italian public administrations have been adopting, sustainable cloud computing frameworks have been chosen, with minimal management effort, for their contribution to smart working, and their capability of reconciling economic demands, environmental resilience, and social equity. This chapter aims to explore the ongoing change in the technological architecture for e-Government in Italian municipalities and the effects of the activation of sustainable cloud computing frameworks for this purpose, with particular emphasis on personnel's empowerment. On the basis of the benchmarking of the best practices, recommendations will be provided for an effective implementation of Google Apps as a sustainable cloud computing solution to foster staff's continuing professional and personal development in Italian municipalities.
Big Data in Cloud Computing Environment for Market Trends
Authors: Hariharanath K.
Published: November 2018

The Industrial and Business landscape is changing because of the convergence of information technology and communication technologies. This convergence is creating new types of companies competing with each other. It is not about east or west, or developed markets versus developing markets; It is all about how soon a business enterprise understands the emerging technology and adapts it into its business. It is not enough that a business enterprise understands the technology but one has to be good at thinking about the applications of the technology. Now it has become a necessity for business enterprises to manage complex and interdisciplinary requirements in their organization. This chapter explores a business model developed by a textile mill to remain competitive in global market that uses the concepts of big data, cloud computing, virtual reality, and data warehousing.
Big Data Analytics in Health Care
Authors: Suneetha Keerthi
Published: November 2018

With the arrival of technology and rising amount of data (Big Data) there is a need towards implementation of effective analytical techniques (Big Data Analytics) in health sector which provides stakeholders with new insights that have the potential to advance personalized care to improve patient outcomes and avoid unnecessary costs. This chapter covers how to evaluate this big volume of data for unknown and useful facts, associations, patterns, trends which can give birth to new line of handling of diseases and provide high quality healthcare at lower cost to all citizens. This chapter gives a wide insight of introduction to Big Data Analytics in health domain, processing steps of BDA, Challenges and Future scope of research in healthcare.
Data, Information, and Knowledge
Authors: Erickson G. Scott , Rothberg Helen N.
Published: November 2018

This chapter examines the similarities and differences between big data and knowledge management. Big data has relatively little conceptual development, at least from a strategy and management perspective. Knowledge management has a lengthy literature and decades of practice but has always explicitly focused only on knowledge assets as opposed to precursors like data and information. Even so, there are considerable opportunities for cross-fertilization. Consequently, this chapter considers data from McKinsey Global Strategies on data holdings, by industry, and contrasts that with data on knowledge development, essentially the intangible assets found in the same industries. Using what we know about the variables influencing the application of intangible assets such as knowledge and intelligence, we can then better identify where successful employment of big data might take place. Further, we can identify specific variables with the potential to grant competitive advantage from the application of big data and business analytics.
Disease Surveillance System for Big Climate Data Processing and Dengue Transmission
Authors: Manogaran Gunasekaran , Lopez Daphne
Published: November 2018

Ambient intelligence is an emerging platform that provides advances in sensors and sensor networks, pervasive computing, and artificial intelligence to capture the real time climate data. This result continuously generates several exabytes of unstructured sensor data and so it is often called big climate data. Nowadays, researchers are trying to use big climate data to monitor and predict the climate change and possible diseases. Traditional data processing techniques and tools are not capable of handling such huge amount of climate data. Hence, there is a need to develop advanced big data architecture for processing the real time climate data. The purpose of this paper is to propose a big data based surveillance system that analyzes spatial climate big data and performs continuous monitoring of correlation between climate change and Dengue. Proposed disease surveillance system has been implemented with the help of Apache Hadoop MapReduce and its supporting tools.
A Specification Framework for Big Data Initiatives
Authors: Ta Anh D. , Tanque Marcus , Washington Montressa
Published: November 2018

Given the emergence of big data technology and its rising popularity, it is important to ensure that the use of this avant-garde technology directly addresses the enterprise goals which are required to maximize the Return-On-Investment (ROI). This chapter aims to address a specification framework for the process of transforming enterprise data into wisdom or actionable information through the use of big data technology. The framework is based on proven methodologies, which consist of three components: Specify, Design, and Refine. The recommended framework provides a systematic, top-down process to extrapolate big data requirements from high-level technical and enterprise goals. The framework also provides a process for managing the quality and relationship between raw data sources and big data products.
Discovering Knowledge Hidden in Big Data From Machine-Learning Techniques
Authors: Rao Adiraju Prashantha
Published: November 2018

As the speed of information growth exceeds in this new century, excessive data is making great troubles to human beings. However, there are so much potential and highly useful values hidden in the huge volume of data. Big Data has drawn huge attention from researchers in information sciences, policy and decision makers in governments and enterprises. Data analytic is the science of examining raw data with the purpose of drawing conclusions about that information. Data analytics is about discovering knowledge from large volumes data and applying it to the business. Machine learning is ideal for exploiting the opportunities hidden in big data. This chapter able to discover and display the patterns buried in the data using machine learning.
Big Data Techniques for Supporting Official Statistics
Authors: Virgillito Antonino , Polidoro Federico
Published: November 2018

Following the advent of Big Data, statistical offices have been largely exploring the use of Internet as data source for modernizing their data collection process. Particularly, prices are collected online in several statistical institutes through a technique known as web scraping. The objective of the chapter is to discuss the challenges of web scraping for setting up a continuous data collection process, exploring and classifying the more widespread techniques and presenting how they are used in practical cases. The main technical notions behind web scraping are presented and explained in order to give also to readers with no background in IT the sufficient elements to fully comprehend scraping techniques, promoting the building of mixed skills that is at the core of the spirit of modern data science. Challenges for official statistics deriving from the use of web scraping are briefly sketched. Finally, research ideas for overcoming the limitations of current techniques are presented and discussed.
Comparison of Graduates' and Academics' Perceptions of the Skills Required for Big Data Analysis
Authors: Puang-Ngern Busayasachee , Bilgin Ayse A. , Kyng Timothy J.
Published: November 2018

There is currently a shortage of graduates with the necessary skills for jobs in data analytics and “Big Data”. Recently many new university degrees have been created to address the skills gap, but they are mostly computer science based with little coverage of statistics. In this chapter, the perceptions of graduates and academics about the types of expertise and the types of software skills required for this field are documented based on two online surveys in Australia and New Zealand. The results showed that Statistical Analysis and Statistical Software Skills were the most necessary type of expertise required. Graduates in industry identified SQL as the most necessary software skill while academics teaching in relevant disciplines identified R programming as the most necessary software skill for Big Data analysis. The authors recommend multidisciplinary degrees where the appropriate combination of skills in statistics and computing can be provided for future graduates.
Data Science and Big Data Analytics in Financial Services
Authors: Behari Suren , Cater-Steel Aileen , Soar Jeffrey
Published: November 2018

The chapter discusses how Financial Services organizations can take advantage of Big Data analysis for disruptive innovation through examination of a case study in the financial services industry. Popular tools for Big Data Analysis are discussed and the challenges of big data are explored as well as how these challenges can be met. The work of Hayes-Roth in Valued Information at the Right Time (VIRT) and how it applies to the case study is examined. Boyd's model of Observe, Orient, Decide, and Act (OODA) is explained in relation to disruptive innovation in financial services. Future trends in big data analysis in the financial services domain are explored.
Software-Defined Networking for Scalable Cloud-Based Services to Improve System Performance of Hadoop-Based Big Data Applications
Authors: Hagos Desta Haileselassie
Published: November 2018

The rapid growth of Cloud Computing has brought with it major new challenges in the automated manageability, dynamic network reconfiguration, provisioning, scalability and flexibility of virtual networks. OpenFlow-enabled Software-Defined Networking (SDN) alleviates these key challenges through the abstraction of lower level functionality that removes the complexities of the underlying hardware by separating the data and control planes. SDN has an efficient, dynamic, automated network management, higher availability and application provisioning through programmable interfaces which are very critical for flexible and scalable cloud-based services. In this study, the author explores broadly useful open technologies and methodologies for applying an OpenFlow-enabled SDN to scalable cloud-based services and a variety of diverse applications. The approach in this paper introduces new research challenges in the design and implementation of advanced techniques for bringing an SDN-enabled components and big data applications into a cloud environment in a dynamic setting. Some of these challenges become pressing concerns to cloud providers when managing virtual networks and data centers, while others complicate the development and deployment of cloud-hosted applications from the perspective of developers and end users. However, the growing demand for manageable, scalable and flexible clouds necessitates that effective solutions to these challenges be found. Hence, through real-world research validation use cases, this paper aims at exploring useful mechanisms for the role and potential of an OpenFlow-enabled SDN and its direct benefit for scalable cloud-based services. Finally, it demonstrates the impact of an OpenFlow-enabled SDN that fully embraces the opportunities and challenges of cloud infrastructures to improve the system performance of Hadoop-based big data applications by utilizing the network control capabilities of an OpenFlow to solve network congestion.
Evolution of Cloud in Big Data With Hadoop on Docker Platform
Authors: Gupta Meenu , Singla Neha
Published: November 2018

Data can be anything but from a large data base extraction of useful information is known as data mining. Cloud computing is a term which represent a collection of huge amount of data. Cloud computing can be correlated with data mining and Big Data Hadoop. Big data is high volume, high velocity, and/or high variety information asset that require new form of processing to enable enhanced decision making, insight discovery and process optimization. Data growth, speed and complexity are being accompanied by deployment of smart sensors and devices that transmit data commonly called the Internet of Things, multimedia and by other sources of semi-structured and structured data. Big Data is defined as the core element of nearly every digital transformation today.
Big Data Analytics for Predictive Maintenance Strategies
Authors: Lee C. K. M. , Cao Yi , Ng Kam Hung
Published: November 2018

Maintenance aims to reduce and eliminate the number of failures occurred during production as any breakdown of machine or equipment may lead to disruption for the supply chain. Maintenance policy is set to provide the guidance for selecting the most cost-effective maintenance approach and system to achieve operational safety. For example, predictive maintenance is most recommended for crucial components whose failure will cause severe function loss and safety risk. Recent utilization of big data and related techniques in predictive maintenance greatly improves the transparency for system health condition and boosts the speed and accuracy in the maintenance decision making. In this chapter, a Maintenance Policies Management framework under Big Data Platform is designed and the process of maintenance decision support system is simulated for a sensor-monitored semiconductor manufacturing plant. Artificial Intelligence is applied to classify the likely failure patterns and estimate the machine condition for the faulty component.
A Survey of Cloud-Based Services Leveraged by Big Data Applications
Authors: Goher S. ZerAfshan , Javed Barkha , Bloodsworth Peter
Published: November 2018

Due to the growing interest in harnessing the hidden significance of data, more and more enterprises are moving to data analytics. Data analytics require the analysis and management of large-scale data to find the hidden patterns among various data components to gain useful insight. The derived information is then used to predict the future trends that can be advantageous for a business to flourish such as customers' likes/dislikes, reasons behind customers' churn and more. In this paper, several techniques for the big data analysis have been investigated along with their advantages and disadvantages. The significance of cloud computing for big data storage has also been discussed. Finally, the techniques to make the robust and efficient usage of big data have also been discussed.
Impact of EU Data Protection Laws on Cloud Computing
Authors: Eldred Morgan , Adams Carl , Good Alice
Published: November 2018

The global nature of cloud computing has resulted in emerging challenges, such as clashes between legal systems, cultural differences, and business practice norms: cloud-computing is at the forefront of recognising, and “smoothing over,” emergent differences between nation states as we move towards a more globally connected world. This chapter uses the emergent differences over regulation governing data protection; as the world becomes more interconnected, we are likely to see more examples of technology practices and models sweeping around the globe, and raising further areas for clashes between nations and regions, much like the fault lines between tectonic plates. This chapter provides contribution by capturing some emergent “fault lines” in an in-depth case study comparing the evolving EU directives covering data protection and how they relate to non-EU data protection legal systems. This provides the foundations to consider cloud-computing challenges, inform policymakers in measures to resolve “clashes,” and in informing researchers investigating other global technology phenomena.
Modelling the Dynamics of Trust Across a Cloud Brokerage Environment
Authors: Carroll Noel
Published: November 2018

The globalised nature of cloud computing presents us with new challenges towards the development of effective business relationships across a dynamic service ecosystem. While availing of additional service capabilities, organisations are tasked with managing unfamiliar relationships with unfamiliar cloud service providers to generate increased business value. This calls for more attention towards the concept of trust within a cloud service environment. Cloud computing presents new economic and flexible business and technological models which supports the co-creation nature of service quality and ultimately business value. This research examined various methods to assess service quality and service capability assessment. During the course of this work, the author has identified the need to revisit the concept of ‘trust' within a cloud computing context and prescribe a method to model its complexity. The objective of this paper is to argue that, while cloud computing allows organisations to avail of increased service capabilities; it challenges the concept of trust. To support this argument the author presents the Cloud Services Trust Model to explain the dynamics of trust. In doing so, it introduces a notion of a distributed relational structure in service value co-creation. The paper also draws on theoretical developments to highlight the fundamental changes in the nature of service provision and how they impact on the assessment of service value and service quality. The author supports the need for greater transparency in the move towards greater accountability in the cloud ecosystem. The paper applies social network analysis (SNA) to model the trust relationships of a cloud brokerage environment.
Big Data From Management Perspective
Authors: Bolhari Alireza
Published: November 2018

Competency matters. Social media, customer transactions, mobile sensors, and feedback contents are all piled up with data. This might be unstructured and complex data in voluminous quantity, often called Big Data. However, if this Big Data is managed, it might bring competency for organizations. This chapter introduces the must-know concepts and materials for organizational managers who face Big Data. Through the chapter, Big Data is defined and its emergence over the time is reviewed. The four Vs model in Big Data literature and its link to a banking system is analyzed. The chapter concludes by making a managerial awareness concerning ethical issues in Big Data. This is of high priority in public sectors as data relies for every individual in the society.
Analysis of Grievances in the Banking Sector through Big Data
Authors: Jain Arushi , Bhatnagar Vishal
Published: November 2018

Banking sector is one of the sectors which face the problem because of the huge amounts of data coming in at a rapid pace. In this paper the authors analyzed grievances in the banking sector through big data. The customers may have a wide variety of complaints and suggestions regarding the working style and other procedural methods which are followed by the banks for effective customer dealing and satisfaction. Quick rectification of complaints and working on customer suggestions can help banks gain a good name in the market, win customers' loyalties and attract new customers. To accomplish this gargantuan task, banks must maintain a complaints database which stores the information on customer complaints across the above mentioned categories along with the response to the complaints by the relevant employees which is collected over a period of time can reveal crucial and critical information for effective CRM in the organizations. In this paper, authors had analyzed the grievances to uncover the valuable suggestions of the customer to provide them a higher level of satisfaction
A Hybrid Approach to Big Data Systems Development
Authors: Aggarwal Anil K.
Published: November 2018

Data has always played a critical part in business decision making. The digital economy is generating Tsunami of data which must be analyzed and used by both the public and private sector. Survival and citizen satisfaction may depend on how governments use big data to develop citizen-centric services. Big data analysis can lead to better transparency, less corruption and citizen satisfaction. Big data is an emerging area where models and applications are still emerging. Currently there are few, if any, models that provide guidance in developing applications. This chapter proposes a hybrid approach which can be used as a starting point for future development.
Eco-Cultural Tourism for Biodiversity Conservation and Sustainable Development of Remote Ecosystems in the Third World
Authors: Poyyamoli G.
Published: November 2018

Most of the remote areas such as mountains and islands are characterized by the features such as remoteness, fragility, endemism, and upland/lowland or island/mainland linkages, besides richer biodiversity and indigenous knowledge, thus attracting a large number of quality conscious tourists. However, conventional “top-down”, reactive and ad-hoc approaches and ill-conceived “development” activities such as infrastructure for mass tourism will destroy the very natural and cultural resource base on which the tourism thrives in these areas. These trends have led to the paradigm shifts towards community-based, participatory, and pro-active management strategies. Appropriate strategies for integrating biodiversity conservation and sustainable livelihoods by regenerating nature and culture for facilitating sustainable development of remote ecosystems in the third world are discussed in this chapter.
Smart Sustainable Marketing of the World Heritage Sites
Authors: Chhabra Deepak
Published: November 2018

This chapter revisits the author's earlier findings that scrutinized online marketing strategies employed by the world heritage sites (WHS) based on a predetermined set of sustainability indicators. Recent data shows that, for the most part, the WHS continue to lack behind in sustainable initiatives to promote their sites in a responsible manner. Only slight improvement is noted in terms of efforts to seek host community views on how the local heritage should be showcased and the manner on which culturally appropriate representations can be promoted. In the light of unexpected decreased visitation levels at most of the WHS, as reported by literature, a retro brand marketing strategy is suggested which strives to marry the rich historical past of the sites with the present need. A smart sustainable marketing agenda is proposed to improve brand equity and facilitate coordination between different stakeholders of the heritage sites and to attract increased visitations.