bluuebunny/crossref_metadata_2025 huggingface dataset:
An Adapted Ant-Inspired Algorithm for Enhancing Web Service Composition
Authors: Dahan Fadl , El Hindi Khalil , Ghoneim Ahmed
Published: November 2018

Web Service Composition (WSC) provides a flexible framework for integrating independent web services to satisfy complex user requirements. WSC aims to choose the best web service from a set of candidates. The candidates have the same functionality and different non-functional criteria such as Quality of Service (QoS). In this work, the authors propose an ant-inspired algorithm for such problem. They named it Flying Ant Colony Optimization (FACO). Flying ants inject pheromone not only on the nodes on their paths but also on neighboring nodes increasing their chances of being explored in future iterations. The amount of pheromone deposited on these neighboring nodes is inversely proportional to the distance between them and the nodes on the path. The authors believe that by depositing pheromone on neighboring nodes, FACO may consider a more diverse population of solutions, which may avoid stagnation. The empirical experiments show that FACO outperform Ant Colony Optimization (ACO) for the WSC problem, in terms of the quality of solutions but it requires slightly more execution time.
Big Data Predictive Analysis for Detection of Prostate Cancer on Cloud-Based Platform
Authors: Gangwal Ritesh Anilkumar , Deshmukh Ratnadeep R. , Emmanuel M.
Published: November 2018

Big data as the name would refer to a subsequently large quantity of data which is being processed. With the advent of social media the data presently available is text, images, audio video. In order to process this data belonging to variety of format led to the concept of Big Data processing. To overcome these challenges of data, big data techniques evolved. Various tools are available for the big data naming MAP Reduce, etc. But to get the taste of Cloud based tool we would be working with the Microsoft Azure. Microsoft Azure is an integrated environment for the Big data analytics along with the SaaS Cloud platform. For the purpose of experiment, the Prostate cancer data is used to perform the predictive analysis for the Cancer growth in the gland. An experiment depending on the segmentation results of Prostate MRI scans is used for the predictive analytics using the SVM. Performance analysis with the ROC, Accuracy and Confusion matrix gives the resultant analysis with the visual artifacts. With the trained model, the proposed experiment can statistically predict the cancer growth.
Affordances of Data Science in Agriculture, Manufacturing, and Education
Authors: Umachandran Krishnan , Ferdinand-James Debra Sharon
Published: November 2018

Continued technological advancements of the 21st Century afford massive data generation in sectors of our economy to include the domains of agriculture, manufacturing, and education. However, harnessing such large-scale data, using modern technologies for effective decision-making appears to be an evolving science that requires knowledge of Big Data management and analytics. Big data in agriculture, manufacturing, and education are varied such as voluminous text, images, and graphs. Applying Big data science techniques (e.g., functional algorithms) for extracting intelligence data affords decision markers quick response to productivity, market resilience, and student enrollment challenges in today's unpredictable markets. This chapter serves to employ data science for potential solutions to Big Data applications in the sectors of agriculture, manufacturing and education to a lesser extent, using modern technological tools such as Hadoop, Hive, Sqoop, and MongoDB.
H.265 Video Streaming in Mobile Cloud Networks
Authors: Wang Qi , Nightingale James , Alcaraz-Calero Jose M. , Luo Chunbo , Pervez Zeeshan , Wang Xinheng , Grecos Christos
Published: November 2018

Mobile video applications have started to dominate the global mobile data traffic in recent years, and both opportunities and challenges have arisen when the emerging mobile cloud paradigm is introduced to support the resource-demanding video processing and networking services. This chapter offers in-depth discussions for content- and context-aware, adaptive, robust, secure, and real-time video applications in mobile cloud networks. The chapter describes and analyses the essential building blocks including the state-of-the-art technologies and standards on video encoding, adaptive streaming, mobile cloud computing, and resource management, and the associated security issues. The focus is context-aware adaptive streaming based on the latest video coding standard H.265 in the context of Internet-centric mobile cloud networking. Built upon selected building blocks underpinned by promising approaches and emerging standards, an integrated architecture is proposed towards achieving next-generation smart video streaming for mobile cloud users, with future research directions in this field identified.
Computational Business Intelligence, Big Data, and Their Role in Business Decisions in the Age of the Internet of Things
Authors: Vidal-García Javier , Vidal Marta , Barros Rafael Hernández
Published: November 2018

The evolution of the big data and new techniques related to the processing and analysis of large databases is revolutionizing the management of companies in the age of the Internet of Things (IoT). In this chapter, we examine the possibilities of big data to improve the services offered by companies and the customer experience and increase the efficiency of these companies. Companies must accept the challenge of self-assessment and measure the barriers that threaten to prevent them from reaching to get the maximum potential derived from big data and analytics. The combination of big data and computational business intelligence will change completely processes, logistics and distribution strategies, the choice of marketing channels and any aspect of the production and marketing of products and services. A case of GE is presented to showcase the use of the IoT and big data. All companies, regardless of size or sector, will improve their business operations due to big data generated from the social media and IoT applications and its use in computational business intelligence.
Big Data Analytics for Childhood Pneumonia Monitoring
Authors: Peddoju Suresh Kumar , K. Kavitha , S. C. Sharma
Published: November 2018

In developing countries pediatric pneumonia is the second leading cause of deaths and 98% of pneumonia-induced deaths are identified across the world. It is mandatory to identify the symptoms of pneumonia in children to avoid mortality causing complications. Early identification of children at risk for treatment failure or at increased risk for death will help to improve overall health outcomes. If pneumonia is suspected, it is important to seek medical attention promptly so that an accurate diagnosis can be made and appropriate treatment is given in time. The proposed approach quickly provides history of previous patient's details, expert doctor's opinions who are in globe and their previous treatment for the same symptoms, all diagnostic reports such as blood tests, x-ray etc., from the cloud and gives analytics from big data to take fast and precise decisions by the doctors.
Analytics-as-a-Service (AaaS)
Authors: Verma Chitresh , Pandey Rajiv
Published: November 2018

Big Data Analytics is a major branch of data science where the huge amount raw data is processed to get insight for relevant business processes. Integration of big data, its analytics along with Service Oriented Architecture (SOA) is need of the hour, such integration shall render reusability and scalability to various business processes. This chapter explains the concept of Big Data and Big Data Analytics at its implementation level. The Chapter further describes Hadoop and its technologies which are one of the popular frameworks for Big Data Analytics and envisage integrating SOA with relevant case studies. The chapter demonstrates the SOA integration with Big Data through, two case studies of two different scenarios are incorporated that integrates real world implementation with theory and enables better understanding of the industrial level processes and practices.
Semantic Technologies and Big Data Analytics for Cyber Defence
Authors: Leenen Louise , Meyer Thomas
Published: November 2018

The Governments, military forces and other organisations responsible for cybersecurity deal with vast amounts of data that has to be understood in order to lead to intelligent decision making. Due to the vast amounts of information pertinent to cybersecurity, automation is required for processing and decision making, specifically to present advance warning of possible threats. The ability to detect patterns in vast data sets, and being able to understanding the significance of detected patterns are essential in the cyber defence domain. Big data technologies supported by semantic technologies can improve cybersecurity, and thus cyber defence by providing support for the processing and understanding of the huge amounts of information in the cyber environment. The term big data analytics refers to advanced analytic techniques such as machine learning, predictive analysis, and other intelligent processing techniques applied to large data sets that contain different data types. The purpose is to detect patterns, correlations, trends and other useful information. Semantic technologies is a knowledge representation paradigm where the meaning of data is encoded separately from the data itself. The use of semantic technologies such as logic-based systems to support decision making is becoming increasingly popular. However, most automated systems are currently based on syntactic rules. These rules are generally not sophisticated enough to deal with the complexity of decisions required to be made. The incorporation of semantic information allows for increased understanding and sophistication in cyber defence systems. This paper argues that both big data analytics and semantic technologies are necessary to provide counter measures against cyber threats. An overview of the use of semantic technologies and big data technologies in cyber defence is provided, and important areas for future research in the combined domains are discussed.
Drivers of Cloud Computing Adoption for E-Government Services Implementation
Authors: Mohammed Fathey , Ibrahim Othman Bin
Published: November 2018

Adopting and using Information and Communication Technologies (ICTs) in the public sector affords undeniable benefits in terms of efficient and cost-effective provision of services, facilitating public management and promoting transparency and participation through e-government systems. However, many governments around the globe face many challenges and still struggle to implement e-government initiatives successfully. Cloud computing may offer a new chance to address many of these challenges by providing elastic scalable, customized, and highly available environment. Moreover, it is already adopted and proved to be advantageous for governmental institutions in different countries. By analyzing some cases, this paper extracts the main drivers of cloud computing adoption in the public sector organizations. Cost saving and the need for scalability are the main common factors that drive public sector organizations to move their services to the cloud.
Big Data and Predictive Analysis Is Key to Superior Supply Chain Performance
Authors: Bag Surajit
Published: November 2018

The study considers samples from the South African engineering companies who are strategic suppliers to mining and minerals industry and further explores the uncertainties persisting in the supply chain network. Further investigation was done to understand the role of big data and predictive analysis (BDPA) in managing the supply uncertainties. The paper finally uses partial least square regression analysis to study the relationship among buyer-supplier relationship, big data and predictive analysis and supply chain performance. The analysis supported the second and third hypothesis. Therefore, it is established that firstly, there is a positive relationship between big data, predictive analysis and supply chain performance and secondly, there is a positive relationship between and big data, predictive analysis and buyer-supplier relationship. The study is a unique contribution to the current literature by shedding light on the practical problems persisting in the South African context.
Search of Web Service Based on Weighted Association Rule
Authors: Wang Lei , Xu Lingyu , Xue Yunlan , Zhang Gaowei , Luo Xiangfeng
Published: November 2018

The rapid growth of web services need efficiently discovering the desired web services for the users. Web service interfaces are defined with WSDL that is described by a bag of terms. Many similarity metrics are proposed to solve this problem, it is hardly to resolve the problem that only few pairs of terms between two services have high semantic distance, the semantic distance of other terms between two services are low. Using traditional keyword search metrics may acquire a wrong result that these two web services are similar, in addition, semantics of the web services is hardly to exploit. In this work the authors firstly help the request service to find the services that belong to the same class, and then they use association rule to find terms that are often appear together and find the most similar terms. The authors weaken the weight of the most similar term contained in an association rule and enhance the other terms' weight contained in an association rule to solve the situation above. The experiments show that our approach outperforms some searching methods.
Handling Critical Issues of Big Data on Cloud
Authors: Vaidya Madhavi
Published: November 2018

Big Data is driving radical changes in traditional data analysis platforms. To perform any kind of analysis on such voluminous and complex data, scaling up the hardware platforms becomes impending. With the entire buzz surrounding Big Data; it is being collected at an unprecedented scale. Big Data has potential to revolutionize much more than just research. Loading large data-sets is often a challenge. Another shift of this Big Data processing is the move towards cloud computing. As many communities begin to rely on cloud based data management, large shared data goes up extensively. Analysis of such large data on distributed processing system or cloud is a bit difficult task to handle. The aim of this chapter is to provide a better understanding of the design challenges of cloud computing and analytics of big data on it. The challenge is related to how a large extent of data is being harnessed, and the opportunity is related to how effectively it is used for analyzing the information from it.
Virtualization Evolution
Authors: Koumaras Harilaos , Damaskos Christos , Diakoumakos George , Kourtis Michail-Alexandros , Xilouris George , Gardikis Georgios , Koumaras Vaios , Siakoulis Thomas
Published: November 2018

This chapter discusses the evolution of the cloud computing paradigm and its applicability in various sections of the computing and networking/telecommunications industry, such as the cloud networking, the cloud offloading, and the network function virtualization. The new heterogeneous virtualized ecosystem that is formulated creates new needs and challenges for management and administration at the network part. For this purpose, the approach of Software-Defined Networking is discussed and its future perspectives are further analyzed.
ZAMREN Big Data Management (ZAMBiDM) Envisaging Efficiency and Analytically Manage IT Resources
Authors: Mbale Jameson
Published: November 2018

The ZAMREN member institutions deal with heterogeneous teaching and research materials drawn from all walks-of-life such as industry, and NRENs world over. To deal with such huge data that is in terabits for academic and economic gain becomes a mammoth task to manipulate, process, store and analyse. It is in view of that the ZAMREN Big Data and Data Management, in this work abbreviated as ZAMBiDM, is envisaged to collectively gather relevant heterogeneous large volumes of a wide variety of data from all sectors of economy. The data would be analytically managed in storage, processing and obtaining actionable insight real-time as a way to solve high-value skilled academic and industrial business problems, in order to prepare graduates for competitive future workforce. The data would be collected from all line-ministries of Zambia such as education, agriculture, health, mining, lands, communications, commerce, including industries and NRENs worldwide and be analytically analysed to exploit strategic actions that would enhance decision making in executing relevant tasks.
Management of SME's Semi Structured Data Using Semantic Technique
Authors: Singh Saravjeet , Singh Jaiteg
Published: November 2018

Management of data for an organization is crucial task but when data goes to its complex form then it becomes multifaceted as well as vital. In today era most of the organizations generating semi structured or unstructured data that requires special techniques to handle and manage. With the needs to handle unstructured data, semantic web technology provides a way to come up with the effective solution. In this chapter Synthetic Semantic Data Management (SSDM) is explained that is based semantic web technique and will helps to manage data of small and Midsized Enterprise (SME). SSDM provide the procedure to handle, store, manages and retrieval of semi structured data.
Cloud Adoption in Enterprises
Authors: Venkatraman Ramanathan , Venkatraman Sitalakshmi
Published: November 2018

This chapter proposes a security and migration framework with business strategic implementation guidelines for successfully adopting cloud services, namely Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS) in contemporary organisations. As a foundation to achieve this, the authors give emphasis to the importance of considering the security, privacy, and governance issues related to cloud implementations, along with the possible benefits of adopting cloud services in businesses. They discuss the various types of cloud, their deployment models, and service levels as these form the basis for strategically planning the security and migration framework implementation of cloud in an organization. In addition, the authors provide a step-wise security and migration framework that could serve as a business strategic guideline for a successful cloud service adoption in enterprises.
Strategies for Evaluating Cloud System Providers During the Transformation of Businesses
Authors: Firdhous Mohamed Fazil Mohamed
Published: November 2018

This chapter takes a comprehensive look at the strategies and mechanisms developed for evaluating cloud services during business transformation. During business transformation, enterprises need to make decisions that would have long lasting impacts on the performance and profitability of the businesses. One of the important decisions business leaders are required to make is whether to own and manage their own IT infrastructure or outsource them from a public cloud provider. Due to the attractiveness of cloud computing, there are many cloud providers in the market creating a confusion in the minds of the customers who to select. Hence it is necessary to use proper strategies and mechanisms to evaluate the performance and the suitability of the service providers in meeting the customer requirements. This chapter takes an in depth look at some of the strategies, frameworks, mechanisms and tools proposed by researchers for evaluating cloud services in the literature with reference to their applicability, suitability, advantages and disadvantages.
Quality Measures for Semantic Web Application
Authors: Rao Adiraju Prasanth
Published: November 2018

The Semantic Web is a standard of Common Data Formats on WWW with aim to convert the current web data of unstructured and semi-structured documents into a common framework that allows data to be shared and reused across applications, enterprises. The main purpose of the Semantic Web is driving the evolution of the current Web by enabling users to find, share, and combine information more easily. Humans are capable of using the Web to carry out tasks such as searching for the lowest price for a LAPTOP. However, machines cannot accomplish all of these tasks without human direction, because web pages are designed to be read by people, not machines. The semantic web is a vision of information that can be readily interpreted by machines, so machines can perform more of the tedious work involved in finding, combining, and acting upon information on the web. The chapter presents the architecture of semantic web, its challenging issues and also data quality principles. These principles provide a better decision making within organization and will maximize long term data integration and interoperability.
Cloud State Surveillance
Authors: Kierkegaard Sylvia
Published: November 2018

Concerns about government snooping in the wake of revelations by whistle blower Edward Snowden have deterred enterprises and IT professionals from keeping sensitive data in the clouds. Moving towards cloud-based computing has emerged and has gained acceptance as a solution to the tasks related to the processing of information. However, cloud computing carries serious risks to business information. The questions around risk and compliance are still largely unknown and need to be ironed out. Cloud computing opens numerous legal, privacy, and security implications, such as copyright, data loss, destruction of data, identity theft, third-party contractual limitations, e-discovery, risk/insurance allocation, and jurisdictional issues. This chapter discusses the associated legal risks inherent in cloud computing, in particular the international data transfer between EU and non-EU states.
Cloud Computing Economics
Authors: Bibi Stamatia , Katsaros Dimitrios , Bozanis Panayiotis
Published: November 2018

Cloud services and technologies are currently receiving increased attention from the industry mostly due to business-driven promises and expectations. Significant innovations in virtualization and distributed computing, as well as improved access to high-speed Internet and a weak economy, have accelerated interest in cloud computing. However, is the migration to the Cloud the most profitable option for every business? Enterprise adoption of cloud computing often requires a significant transformation of existing Information Technology (IT) systems and processes. To justify such a change, a viable business case must be made based on the economics of transformation. This chapter presents a study of the basic parameters for estimating the potential infrastructure and software costs deriving from building and deploying applications on cloud and on-premise assets. Estimated user demand and desired quality attributes related to an application are also addressed in this chapter as they are aspects of the decision problem that also influence the choice between cloud and in-house solutions.
Promoting Social and Solidarity Economy Through Big Data
Authors: López David De la Antonia
Published: November 2018

The aim of this chapter is to describe how to implement a strategy of Big Data to boost Social and Solidarity Economy (SSE). Because of reduction of prices in ICT systems, computing technology has changed and new techniques for distributed computing are the mainstream. With the evolution, it is now possible to manage immense volumes of data that previously could have only been handled by supercomputers at great expense. Through better analysis of the large volumes of data that are becoming available, there is the potential for making faster advances and improving the profitability of many enterprises. Thus, large companies can invest more money into these tools and consequently have more opportunities in obtaining good results. This new situation will widen the gap between large and small organizations, mainly those organizations of modest economic capacity as those that belong to SSE. Therefore, in this research we have made a complete development of software, techniques and tools for implementing a Big Data in SSE. It will help them to narrow the gap with large organizations.
Strategic Best-in-Class Performance for Voice to Customer
Authors: Roy Supriyo , Kumar Kaushik
Published: November 2018

For any forward-looking perspective, organizational information which is typically historical, incomplete and most of the time inaccurate, needs to be enriched with external information. However, traditional systems and approaches are slow, inflexible and cannot handle new volume and complexity of information. Big data, an evolving term, basically refers to voluminous amount of structured, semi-structured or unstructured information in the form of data with a potential to be mined for ‘best in class information'. Primarily, big data can be categorized by 3V's: volume, variety and velocity. Recent hype around big data concepts predicts that it will help companies to improve operations and makes faster and intelligent decisions. Considering the complexities in realms of supply chain, in this study, an attempt has been made to highlight the problems in storing data in any business, especially under Indian scenario where logistics arena is most unstructured and complicated. Conclusion may be significant to any strategic decision maker / manager working with distribution and logistics.
Unleashing Artificial Intelligence Onto Big Data
Authors: Mahanty Rupa , Mahanti Prabhat Kumar
Published: November 2018

We live in an ocean of data. Big Data is characterized by vast amounts of data sized in the order of petabytes or even exabytes. Though Big Data has great potential, Big data by itself has no value unless one can derive meaningful results from it. That is where Artificial Intelligence pitches in. Artificial Intelligence's most common application is about finding patterns in enormous quantities of data. The confluence of Big Data and Artificial Intelligence allows companies to automate and improve complex descriptive, predictive and prescriptive analytical tasks. In other words, Big Data can offer great insights with the help of Artificial Intelligence (AI). Artificial Intelligence can act as a catalyst to derive tangible value from Big data and serve as key to unlocking Big data. This review article focuses on applications of artificial intelligence to Big Data, its Limitations and issues.
Understanding Sustainable Tourism
Authors: Singh Chandresh
Published: November 2018

The concept of ‘Sustainable tourism' is still an evolving one and the scholars theorizing the concept and institutions trying to adopt it as a policy framework are having different set of meanings attached to this often quoted term. In last few decades issue of sustainability in various forms has also emerged as an important one within the domain of tourism planning and operations. The Growth of tourism along with its many benefits was also accountable for various adverse impacts on destinations and to minimize these impacts has become a matter of great concern worldwide. Efforts in this direction have encouraged industry experts and policy makers to promote ‘Sustainable tourism'. The stakeholders in varying degree are sensitive to these dangers and seek to protect tourist destinations and to protect tourism, which is forecasted to grow in future and is currently is world's largest and fastest growing industries. The constant growth of tourism is predicted to have severe impacts on biological diversity, indigenous cultures, environment which provide the base to facilitate tourism.
Enhancing Coopetition Among Small Tourism Destinations by Creativity
Authors: Redi Francesco
Published: November 2018

This chapter addresses on coopetition among tourism destinations with a focus on small ones and investigates on existing experiences, elaborating on the benefits of combinations with creative strategies and actions. Small destinations can achieve competitive advantages and access to strategic resources by adopting a cooperative behavior that, as observed, has no borders both geographical and of contents. Creativity can enhance coopetitive strategies and, consequently, gives positive impacts and advantages to tourism destinations. This area of research can be enriched with more contributes to assess costs and benefits in order to allow an evaluation of results and the designing of effective strategies. When adopting a coopetition strategy among destinations, the author foresees positive impacts and the achievement of economies and synergies that allow the increasing of the competitive advantage.
Sustainable Tourism Marketing Strategy
Authors: Kiráľová Alžbeta
Published: November 2018

The chapter describes how sustainable tourism marketing strategy can bring competitive advantage to a destination. It defines tourism destinations; characterizes the principles of sustainable tourism development and its role in competitiveness of the destination. The chapter also shows a destination´ best practice in the implementation of sustainable tourism marketing strategy. The destination was subject to research using onsite and internet surveys, semi-structured and informal interview and the results were subjected to evaluation using the VRIO model.
‘Stepping on the Heads of Our Gods'
Authors: Sherpa Yangji Doma , Sinclair A. John , Henley Thomas
Published: November 2018

The Himalayan region of India is experiencing rapid development in tourism, agriculture, highway construction and hydroelectric dam construction. This research considered the role of the public both within and outside of development decision-making processes in these high mountain environments using the proposed Himalayan Ski Village (HSV) in Manali as a case study. The qualitative data revealed that there has been an extensive array of public participation activity related to the HSV project over approximately 10 years. Very little of this activity has evolved, however, through the formal decision-making process. Rather, most participation activities, such as general house meetings, objection letters, public rallies, court cases against the proposed project, and a religious congregation were instigated by the public to protest the proposed development. The findings also show that involvement in the participatory activities undertaken by the public and project proponent fostered instrumental and communicative learning outcomes.
Barriers to Responsible Tourist Behaviour
Authors: Del Chiappa Giacomo , Pinna Mariella , Atzeni Marcello
Published: November 2018

Responsible tourism is an increasingly observed phenomenon. This study offers new insights into the factors that prevent tourists from travelling responsibly. In particular, a sample of 837 Italian travelers was profiled based on the main impediments toward responsible tourism. Findings of the study suggested that impediments toward responsible tourism are related to five main categories: ‘lack of accessibility', ‘unwillingness', ‘lack of trustworthiness', ‘stress', and ‘price'. Cluster analysis revealed the existence of four tourist segments: the ‘existential pessimists', the ‘distrustful and accessibility seekers', the ‘mindless', and the ‘accessibility and time-saving seekers'. Furthermore, a series of distribution tests (χ2) showed that significant differences exist between the segments only based on the level of education, whereas no differences were found related to gender, age, marital status, employment status, monthly household income, or association membership. Finally, managerial implications of the study are discussed, along with recommendations for future research.
Sustainable Development and Restructuring Romanian Tourism Product in Accordance With European Tourists Segments
Authors: Neamtu Liviu , Neamtu Adina Claudia
Published: November 2018

Sustainable tourism development will be achieved through some major changes taking place in the tourism industry in Romania, in the following period. These changes should cover both aspects of structure in tourism and processes and interactions in tourist activities. First of all, the tourism in Romania shall also adopt a diversification strategy, focusing on the integration of new activity fields, as new services, along with the improvement of the existent ones, new tourist facilities, by the construction of centers/units, in compliance with the standards requested by the current tourism, but in the first place of some new products and tourist programmes provided by the current tourist centers. By studying consumer behavior of European tourists visiting Romania, and trends in their preferences regarding requested touristic product the authors propose a pattern for tourism product diversification and expansion of several existing forms of tourism.
A Supply-Side Stakeholder Analysis of Rural Wine Tourism Development
Authors: Quadri-Felitti Donna
Published: November 2018

This exploratory study assessed the cohesiveness and discord among four separate supply-side stakeholder groups in the US Chautauqua-Lake Erie wine region. Results from 17 ANOVA tests indicated agreement on many important issues, a departure from previous studies in tourism (; ). Disagreement was shown about marketing, community appreciation for, and attention by government to wine tourism issues. The findings suggest more data are needed to source the causes of these disparities. Overall, the results signify a region ready for “the informed participation of all relevant stakeholders” () and stakeholder collaboration that is requisite for sustainable tourism development.
Fostering Entrepreneurship at the Spanish University
Authors: Pastor-Gosálbez Inmaculada , Blanco Ana Isabel , Rodríguez Adelina , Acosta Ana , Pontón Paloma , Belzunegui-Eraso Angel
Published: November 2018

In this chapter we discuss the policies for fostering entrepreneurship at Spanish universities and how these policies may be related with the low participation of women in university spin-offs. Using our results from the first part of the EQUASPIN project1, we also discuss the effects of the gender division of labour on the creation of freelance work within the specific framework of knowledge-transfer companies. We also present some of our findings with regard to gender differences in both the creation of spin-offs and the role of the university system in the production and reproduction of gender inequalities.
Women Entrepreneurs in Nigeria
Authors: Kayode-Adedeji Tolulope , Ige Oyinkansola , Ekanem Thelma
Published: November 2018

For ages, the African culture has limited the activities of women and conditioned, to a large extent, the mentality of most African countries about the place and positioning of women in the society. The mass media have been used as a tool in this. Promoting the abilities and achievements of women in the society is one of the important roles of the media in reducing the rate of gender discrimination. These achievements are becoming noticeable in politics and entrepreneurship; thus, setting a standard for other women in the society to build on. This chapter will explore the role of the media in promoting the woman entrepreneur in Nigeria. The study employed the survey research method for data gathering. Findings showed that women have equal opportunity to grow their businesses. Data shows that this growth is slow as there are no significant differences between respondents who agree or disagree with the availability of enabling environment for women to grow their business as compared to their male counterpart. The study recommends that the mass media need to give more voice to their businesses and activities to pave way and encourage the younger women in the society.
Structural Exclusion and Just Development
Authors: King Audra
Published: November 2018

The work of feminists and other critics of global development has successfully demonstrated the persistent failure of development to promote just and equitable social change. The author examines a central cause of this failure, which she refers to as the problem of structural exclusion. Structural exclusion occurs where participation in decision-making is restricted to a narrow range of structural perspectives and interests. The author provides a systematic account of structural exclusion as an epistemic obstacle to just and effective development policy. Drawing on this account, she then propose a principle of structural pluralism, which requires that all relevant structural perspectives be included on equal terms and have equal right and effective opportunity to contribute to or influence deliberations at all levels of decision-making about the appropriate vision and policies of development.
Role of ICT in Socio-Economic Development in Kenya
Authors: Macharia Juliet W.
Published: November 2018

The growth of Information Communication Technology (ICT) has empowered communities in diverse ways. Both males and females use ICTs to transact businesses and carry on relationships. Access and use of mobile phones have changed people's lives. This chapter discusses the magical revolution of mobile telephony in Africa and specifically in Kenya. Innovations such as MPESA have transformed people's lives in Kenya and in other emerging economies. Both males and females have used the innovations to bring about development that has enriched their lives. Secondly, the role of gender socialization is discussed in relation to how the ICTs have eliminated the long-held belief that females are not participants in societal development. Thirdly, the role of the media in development is examined because they socialize people into the gender roles. Through mobile telephones, females perform diverse roles. Positive portrayal of men and women in development acknowledges that men and women must be active members of the process.
Gender and Water
Authors: Das Mononita Kundu , Das Rituparna
Published: November 2018

This chapter examines the welfare implication of wage revisions for two Indian unorganized sector female workers with opposite preference patterns for income and leisure in drought-prone zone. The female workers here face a gender-based wage gap and the inconveniences caused by water shortage adversely affect their effective incomes since females are the major users of water in the family. This chapter also makes a couple of recommendations for policymakers and legislators. It experiments with alternative utility functions in neoclassical microeconomic behavioural model framework.
The Impact of Institutional Factors on Female and Male Owned Firm Financing
Authors: Locke Stuart Murrin , Hewa-Wellalage Nirosha
Published: November 2018

The study compares the impact of the commercial environment on external financing of female- owned micro, small and medium enterprises (MSMEs) compared to those that are male owned in seven South Asian countries. The region exhibits weak institutional and regulatory regimes which result in expropriation of profits from MSMEs. It is likely that such commercial environments add to the risk of lending to MSMEs and this may further manifest a gender bias toward males. This study uses a unique dataset of over 5000 firms from World Bank Enterprise Surveys and combines this with additional information drawn from World Bank macro-economic data. Interval and logit regressions are used. Contrary other studies, this research indicates that once females have access to formal financing they use a higher proportion of formal financing in their firm capital structure than their male-counterparts. A gap in accessing external finance for female-owned MSMEs presents both a waste of human resource and a lost potential to lift standards of living, presenting an opportunity for reform.
Does Demographics Affect Purchase Frequency in Online Retail?
Authors: Kalia Prateek
Published: November 2018

This research determines whether association exist between the demographic characteristics of online shoppers, such as education, age, gender, monthly income, occupation, marital status and their online purchase frequency. Web survey has been applied to 308 customers of four most popular e-retailers in India, who have made at least one online purchase in past six months. Based on extensive literature review hypotheses have been developed for six demographic factors i.e. education, age, income, occupation, marital status and gender. A chi-square test has been deployed to check association between demographic factors and purchase frequency. Significant association has been found between two demographic variables i.e. gender, occupation and purchase frequency. Further, a chi-square post hoc test via standard residual method confirmed that purchase frequency of 1-3 times in past six months by student customers contributes significantly to significant omnibus chi-square statistic.
Demographic Influences on E-Payment Services
Authors: Yaokumah Winfred , Kumah Peace , Okai Eric Saviour Aryee
Published: November 2018

This study investigated customers' preferences of payment systems and the influence of demography on the attitude of customers towards e-payment services. Survey responses were received from 558 bank customers. The t-test and the analysis of variance were employed to examine the differences in perception of security, ICT literacy, customer satisfaction, and the use of e-payment services based on customers' age, gender, and the level of education. The findings revealed no significant differences between the male and female customers in the use of e-payment services. However, the male customers had higher ICT skills, yet perceived e-payment services less secured. Moreover, there were no significant differences in satisfaction and e-payment use, though, customers with higher level of education felt less secured using the services. Also, whereas the older customers were more satisfied with e-payment services, the younger customers had more ICT skills and use the services much more. These findings are necessary for formulating strategies for marketing e-payment services.
Gender and Self-Selection Among Engineering Students
Authors: Cook Maci , Chimka Justin
Published: November 2018

Gender and graduation rates of first time engineering college students have been analyzed as a function of academic and demographic variables in order to investigate the hypothesis that an advantage to women with respect to student success might be attributed to their socioeconomic advantages as a student population. The authors present descriptive, graphical, and model-based evidence to support their ideas about gender and self-selection driven by other demographic factors that leave a disproportionate number of women out of higher education, but create a group of female students more likely than their male counterparts to succeed.
Review on Design Consideration and Code Provisions on Corrosion Resistant Reinforcing Bars
Authors: Reza Auchib , Saqif Musawer Ahmad
Published: November 2018

Premature deterioration of reinforced concrete structures due to corrosion of the reinforcing steel is a major concern worldwide. In this study code provisions and design considerations for using corrosion resistant reinforcing steel bars have been discussed at length. The most common corrosion resistant reinforcing bars available today are– Fusion Bonded Epoxy Coated Bars (ASTM A775), Hot Dip Galvanized Steel Bar (ASTMA767), Glass Fiber Reinforced ,Polymer Bars and Stainless Steel Rebars (ASTM A955). Especially in marine environments corrosion of reinforcement is one the major concerns regarding durability of RC Structures. Also parts of any structure that are subjected to intermittent wetting and drying (e.g. bridge piers) and those that are subjected to dampness (e.g. topmost roof slab of a building) are more susceptible to corrosion. It is well known that Bangladesh’s already struggling infrastructure is under a constant threat of deterioration due to various physical and environmental conditions while a huge shortfall in budget exists to ensure periodic maintenance and repair works. Corrosion resistant rebars are globally accepted corrosion resistant system that will ensure the structures can be used till the end of their design lives. While demand for all non-corroding bars is on the rise, expertise of engineers and construction workers in handling these bars should grow as well. Therefore recommended work practices while manufacturing, fabricating and concreting has to be included in the country’s standards and guidelines.
Polymer Nanofibrous Material for Enzyme Immobilization
Authors: Martinová Lenka , Novák Josef
Published: November 2018

NanospiderTMmethod allows preparation of nanofiber sheets with desired specific mass and fiber diameter between 100-600 nm. The fiber diameter can be modified by solvent system, concentration of polymer solution, and external conditions of the electrospinning process, in particular by air humidity and temperature. We have long experience with continual electrospinning from free surface of the polymer solution and in this case we focus on polymer blend polyamide 6/chitosan nanofiber form. Chitosan is an excellent material providing biocompatibility and numerous primary amine groups. On the other hand, polyamide 6 is well known and easy-to-prepare stable polymer guaranteeing sufficient mechanical properties. Blend nanofibers containing synthetic and natural polymers are usually difficult to continuously prepare. Natural polymer bring certain inhomogeneity due to varying chemical and physical properties of each brew. We compared chitosan from four different suppliers and finally fabricated homogenous and long-term stable layers. Successfully prepared nanofiber sheets were used as a support for enzyme immobilization. We showed that our layers can be used as a carrier for numerous biomolecules.
Reduced Graphene Oxide/Carbon Nanotube Composites for High Electrochemical Performance Supercapacitors
Authors: Huang Yan Zhen , Chen Xiao Min , Li Dong Xu
Published: November 2018

Graphene, whose structure is composed of a single-atom-thick sheet of sp2-hybridized carbon atom, provides large specific surface area, excellent mechanical and chemical properties. In this paper, reduced graphene oxide/carbon nanotube (rGO/CNT) composite, which had superior electrochemical performance, was synthesized via a facile, handy and cheap method. Electrochemical tests showed that rGO/CNT composite that the weight ratio of graphene oxide (GO) to CNTs is 7.5 to 1 exhibited the specific capacitance was 346.84 F/g at the current density of 2 A/g in 1 M H2SO4. The good performance of rGO/CNT composite was ascribed to huge surface area of rGO and homogeneous distribution of CNT, which prevented the aggregation of rGO sheets, increased the path of electron circulation and speeded up the electrolyte penetrating into the materials. Therefore, rGO/CNT composite had great potential on supercapacitors.
The Electrical Characterization of Hydrogenated Amorphous Silicon Germanium Film Used in Un-Cooled Micro-Bolometer
Authors: Chen Zhe Quan , Yong He , Fang Zhong , Phan Xu Chao , Yuan He
Published: November 2018

In this paper, the deposition and the electrical characterization of hydrogenated amorphous silicon germanium (a-SixGey:H) thin films were performed by plasma enhanced chemical vapour deposition (PECVD) at low temperature with different flow ratios of SiH4/GeH4. The temperature coefficient of resistance (TCR) and temperature dependence of conductivity were measured to study the influence of deposition parameter. The resistance uniformity were also investigated. The result showed that the film presented high TCR values of around 3.5%K-1and moderate conductivity value of 1.47×10-3(Ω•cm)-1respectively at room temperature, while the non-uniformity below 5% which indicated the high resistance uniformity in films.