bluuebunny/crossref_metadata_2025 huggingface dataset:
Patterns of Technology Acquisition
Authors: Moreira António Carrizo
Published: February 2018

Although MNEs are important players in the present global world, there has been a debate regarding, on one hand, how MNEs contribute to the development of indigenous firms in host countries, and on the other hand, how indigenous suppliers are able to cope with their international technology demanding clients. This chapter analyzes the patterns of technology acquisition of 40 firms that supply eight multinational firms that belong to four different industries. It is possible to conclude that there are certain differences among foreign and indigenous suppliers as well across the industries they belong to. These differences are the result of a cumulative process over time, which reflect the different performances of the companies and their relationships with the environment.
Homeschooling/Unschooling in Gifted Education
Authors: Goodowens Samantha , Cannaday Jessica
Published: February 2018

This chapter discusses the lived experiences of one parent of a profoundly gifted student. Parental perceptions of gifted programming in the public school system, parental reasons for leaving the public school system, and the alternative schooling designs of homeschooling and unschooling are discussed. Further discussed is the parental perception of the general lack of knowledge teacher educators possess in regards to highly, exceptionally, and profoundly gifted students. Parent recognition and discussion of the incompatibility between the traditional schooling system and their child's personal characteristics is a main theme. Parental design of new educational experiences to meet the unique needs of their individual child is shared. Insights into the alternative education practices of homeschooling and unschooling for highly and profoundly gifted students, as well as one parent's perspective of the current school system, are shared with teacher education faculty preparing new teachers to work with gifted students.
A Review of Security Challenges in Cloud Storage of Big Data
Authors: Usmani Sara , Rehman Faiza , Umair Sajid , Khan Safdar Abbas
Published: February 2018

The novel advances in the field of Information Technology presented the people pleasure, luxuries and ease. One of the latest expansions in the Information Technology (IT) industry is Cloud Computing, a technology that uses the internet for storage and access of data. It is also known as on-demand computing. The end user can access personal data and applications anywhere any time with a device having internet. Cloud Computing has gained an enormous attention but it results in the issues of data security and privacy as the data is scattered on different machines in different places across the globe which is a serious threat to the technology. It has many advantages like flexibility, efficiency and scalability but many of the companies are hesitant to invest in it due to privacy concerns. In this chapter, the objective is to review the privacy and security issues in cloud storage of Big Data and to enhance the security in cloud environment so that end users can enjoy a trustworthy and reliable data storage and access.
Architecture for Big Data Storage in Different Cloud Deployment Models
Authors: Thota Chandu , Manogaran Gunasekaran , Lopez Daphne , Sundarasekar Revathi
Published: February 2018

Cloud Computing is a new computing model that distributes the computation on a resource pool. The need for a scalable database capable of expanding to accommodate growth has increased with the growing data in web world. More familiar Cloud Computing vendors such as Amazon Web Services, Microsoft, Google, IBM and Rackspace offer cloud based Hadoop and NoSQL database platforms to process Big Data applications. Variety of services are available that run on top of cloud platforms freeing users from the need to deploy their own systems. Nowadays, integrating Big Data and various cloud deployment models is major concern for Internet companies especially software and data services vendors that are just getting started themselves. This chapter proposes an efficient architecture for integration with comprehensive capabilities including real time and bulk data movement, bi-directional replication, metadata management, high performance transformation, data services and data quality for customer and product domains.
Scalable Data Warehouse Architecture
Authors: Guster Dennis C. , Brown Christopher G. , Rice Erich P.
Published: February 2018

This chapter looks at the feasibility of creating a scalable data warehouse architecture in a higher education institution. The authors lay out the background of the historical data environment of the institution and look at ways in which the application of new technologies could better meet and exceed the needs of the institution moving forward. The chapter also covers the increased role security plays in the management and governance of data and the ways in which developing more secure aware employees through the use of People Centric Security (PCS) can reduce risk and drive positive change. The authors then look at the ten steps to create a better data framework which will allow for enhanced analytics and a greater return on investment.
Big Data Storage for the Modeling of Historical Time Series Solar Irradiations
Authors: Ali Abid , Nor Nursyarizal Mohd , Ibrahim Taib , Romlie Mohd Fakhizan , Bingi Kishore
Published: February 2018

This chapter proposes Big Data Analytics for the sizing and locating of solar photovoltaic farms to reduce the total energy loss in distribution networks. The Big Data Analytics, which uses the advance statistical and computational tools for the handling of large data sets, has been adopted for modeling the 15 years of solar weather data. Total Power Loss Index (TPLI) is formulated as the main objective function for the optimization problem and meanwhile bus voltage deviations and penetrations of the PV farms are calculated. To solve the optimization problem, this study adopts the Mixed Integer Optimization using Genetic Algorithm (MIOGA) technique. By considering different time varying voltage dependent load models, the proposed algorithm is applied on IEEE 33 bus and IEEE 69 bus test distribution networks and optimum results are acquired. From the results, it is revealed that compared to single PV farm, the integration of two PV farms reduced more energy loss and reduced the total size of PV farms. Big Data Analytics is found very effective for the storing, handling, processing and the visualizing of the weather Big Data.
Big Data Visualization Tools and Techniques
Authors: Okechukwu Obinna Chimaobi
Published: February 2018

In this chapter, a discussion is presented on the latest tools and techniques available for Big Data Visualization. These tools, techniques and methods need to be understood appropriately to analyze Big Data. Big Data is a whole new paradigm where huge sets of data are generated and analyzed based on volume, velocity and variety. Conventional data analysis methods are incapable of processing data of this dimension; hence, it is fundamentally important to be familiar with new tools and techniques capable of processing these datasets. This chapter will illustrate tools available for analysts to process and present Big Data sets in ways that can be used to make appropriate decisions. Some of these tools (e.g., Tableau, RapidMiner, R Studio, etc.) have phenomenal capabilities to visualize processed data in ways traditional tools cannot. The chapter will also aim to explain the differences between these tools and their utilities based on scenarios.
Optimal Strategies for Deteriorating Inventory Systems Under Trapezoidal Type Demand
Authors: Shukla Kunal Tarunkumar , Suthar Mihir S.
Published: February 2018

In this chapter, we study different inventory systems with trapezoidal demand rate, i.e., demand rate is a piecewise linear and continuous function. This chapter presents mathematical formulations of optimal replenishment policies for items with trapezoidal demand rate. Section 1 presents detailed literature survey for inventory systems with ramp type and trapezoidal type demand. In Section 2, Formulation technique for inventory system of items, which follows trapezoidal type demand rate. Section 3 presents effect of deterioration in model discussed in Section 2. Optimal strategy for deteriorating items with expiration dates under trapezoidal type demand and partial backlogging is discussed in Section 4. In Section 5, sensitivity analysis is carried out and chapter is concluded along with future research scope in Section 6.
Two-Level Trade Credit in Supply Chain Management Quadratic With Fix Life Under Quadratic Demand
Authors: Gilotra Manavi , Pareek Sarla
Published: February 2018

In this paper, supply chain inventory models are formulated with quadratic demand. The demand increases linearly for times when a product is launched and when with new substitute available demand decreases exponentially. The inventory of every player is subject to deteriorate after a fixed life time. The deterioration rate under the retailer is lower in comparison to manufacturer. Under two level trade credit, manufacturer offers delay period to settle the account to the distributor and the distributor also offers some credit period to the retailer. Interest is charged if the account is not settled in a given stipulated time period. The cost of the integrated inventory system is minimized with respect to a number of shipments from the manufacturer to the distributor and the distributor to the retailer and each player's replenishment times. A solution procedure is worked out to obtain the best possible decision for the player of the supply chain. The results are validated with the numerical examples for different scenarios. Managerial decisions are suggested.
Imprecise Inventory Model for Items With Imperfect Quality Subject to Learning Effects Having Shortages
Authors: Saha Sumana , Chakrabarti Tripti
Published: February 2018

The fundamental assumption of an economic order quantity (EOQ) model is that 100% of items in an ordered lot are perfect. This assumption is not always pertinent for production processes because of process deterioration or other factors. This paper develops an EOQ model for that each ordered lot contains some defective items and shortages backordered. Here, an inventory model is developed to deal the impreciseness present in market demand. It is assumed that the received items are not of perfect quality and after screening, imperfect items are withdrawn from inventory and sold at discounted price. However, in practice, errors occur in screening test. So, the screening process fails to be perfect. Due to acquaintance with handling methodology and system, holding cost and ordering cost are gradually decreases from one shipment to another. So, learning effect is incorporated on holding cost, ordering cost and number of defective items present in each lot. Due to impreciseness in market demand and in different inventory costs, profit expression is fuzzy in nature. To fuzzify the profit expression, Extension Principle is used and for defuzzification Signed distance method is applied. Finally, the feasibility of proposed model and the effect of learning on optimal solution are shown through numerical example.
Optimal Ordering Policy With Inventory Classification Using Data Mining Techniques
Authors: Agarwal Reshu , Mittal Mandeep
Published: February 2018

Data mining is a technique to identify valid novel, potentially useful, and understandable correlations and patterns in existing data. Data mining techniques, such as clustering, association rule mining, classification, and sequential pattern mining, have attracted a great deal of attention in the information industry and in society as a whole in recent years. Some research studies have also extended the usage of this concept in inventory management. Yet, not many research studies have considered the application of data mining approach on determining both optimal order quantity and loss profit of frequent items. This helps inventory manager to determine optimum order quantity of frequent items together with the most profitable item for optimal inventory control. In this chapter, two different cases for determining ordering policy and inventory classification based on loss rule are presented. An example is illustrated to validate the results.
Application of Distribution-Free Approach in Integrated and Dual-Channel Supply Chain Under Buyback Contract
Authors: Guchhait Rekha , Pareek Sarla , Sarkar Biswajit
Published: February 2018

Customer's aim is to obtain good quality products with less effort. Nowadays, the preference of online selling is very high compare to offline selling. A dual channel supply chain model is introduced to control the quality of products with more profit using buyback contract by reducing lost sale costs. Manufacturer sells product through retail and e-tail channel, i.e., by dual channel. Demand of products depends on e-tail price, retail price, demand sensitivity, advertisement of retail channel, service level of e-tail channel, and delivery cost e-tail channel. This delivery cost has inverse impact on demand of e-tail chain. This study finds the maximum profit for each case and compares results when advertisement and service level are not present in supply chain. The model is solved for centralized and decentralized ways for RC (retail channel) using Stackelberg game policy, EC (e-tail channel), and DC (dual channel). Numerical results give that the model obtains maximum profit at optimum point. Sensitivity analysis is conducted to test the effects of key parameters of the model.
Promoting Business Activities Using Utility Mining Techniques
Authors: C. Sivamathi , S. Vijayarani
Published: February 2018

Inventory control can be defined as the process of inspecting stocks in a shop. Today even small and mid-sized businesses are using computerized inventory management systems for their business. Data mining discovers the knowledge and patterns which are potentially useful and previously unknown. Utility mining is one of the recent emerging fields in data mining. It incorporates usefulness of the knowledge or pattern retrieved. Such usefulness of the knowledge retrieved is termed as utility. In retail industry, utility mining can be used to retrieve highly profitable product in a market. Identifying such profitable products helps in better decision in inventory management. This chapter discusses how utility mining concepts can be implemented in inventory control.
Collaborative Consumption as a Tool for Agricultural Expansion in Developing Countries
Authors: Benna Abubakar U.
Published: February 2018

Collaborative consumption is a broader term encompassing emerging areas, such as crowdfunding and the sharing economy, which enhance consumer enablement through direct interaction. This chapter addresses opportunities and challenges of how to support small- and medium-scale farmers in developing countries. Traditional agriculture, as well as urban agriculture, is rising with the significant urbanization that is occurring in developing economies. There is currently limited research on the value of collaborative consumption as a catalyst for agricultural development. Consequently, the aim of this chapter is to provide an overview of how collaborative consumption in agriculture can be supported. The study is conducted based on the review of literature and case studies related to both agriculture and collaborative consumption. A few key observations are provided in order to assist with the formulation of strategies that increase producer and customer satisfaction, value addition, and engagement.
A Comparative Analysis of Online Crowdfunding Platforms in Africa and the Middle East
Authors: Sulaiman Muhammad Aliyu
Published: February 2018

This chapter seeks to fill a gap in the regional analysis of online crowdfunding platforms and projects by examining selected platforms in Africa and in the Middle East. The authors considered the quantity and quality of the actors: fundraisers, funders, and other stakeholders; analyzed characteristics, quality, fees, and general value for money; and evaluated the capacity of the platforms in terms of system interface, projects, and customer crowds aiming to enhance their overall capacity to become nodes of local and regional crowdfunding activities. These are connected to other district and urban centers that would serve as a springboard to organize and network with overseas centers for the growth and development of the regional centers.
Strategies to Mentor Female Faculty
Authors: Conway Cassandra Sligh , Sims Yvonne , McCrary-Quarles Audrey , Nicholson Cynthia Salley , Ethridge Glacia , Maultsby Michelle , Thomas Tammara Petrill , Smith Susan
Published: February 2018

Historically, the percentage of women in higher education has been small. It is important for women to receive mentoring in order to stay in higher education. Mentoring is one of the key determining and empowering factors for measuring whether women faculty stay in higher education positions or decide to leave. This chapter will include the following objectives: 1) provide a review of research on mentoring women in general; 2) provide a review of conceptual and empirical research available on the mentoring experiences of women; 3) discuss the global implications of mentoring women in these careers; 4) provide suggestions and recommendations related to future opportunities that may assist women in becoming empowered to obtain more career and professional development opportunities globally; and 5) provide solutions and recommendations as positive strategies for women to consider at any academic institution, e.g. HBCU, PWI, private, or public universities. Mentoring can assist women in becoming successful both personally and professionally.
Organizational Change and Online Education at HBCUs
Authors: Witherspoon Sheila , Wright Leonis S.
Published: February 2018

This chapter examines how mentoring pre-tenured and tenured faculty during organizational change of implementing fully online academic programs impacts resistant and/or supportive faculty. By using a case of an experience of some faculty at HBCUs, the authors examine how mentorship is necessary to engender a supportive and successful transition in the face of faculty members' resistance to including online education. Influence on faculty becoming adept experts of online teaching and education, prioritizing online teaching and its impact on how they approach live instruction, and anticipating how a designated mentor(s) affects teaching evaluations and research scholarship necessary to achieve rank and tenure promotion will be delineated.
Strengthening Performance of Civil Society Through Dialogue and Critical Thinking in Nigeria
Authors: Essien Essien
Published: February 2018

This chapter discusses dialogue and critical thinking as a tool for civil society's performance and achievements in contemporary societies. The problem statement raises the need for knowledge of what dialogue and critical thinking is, as well as the competence in how to employ and apply its tools in policy engagement. Drawing upon extensive contemporary literature on civil society and policy engagement, this study examines how to enhance the performance of civil society organizations through the paradigm of dialogue and critical thinking. Findings reveal that critical thinking and dialogue is crucial in the success story of civil society organizations, just as the quality of the work accomplished is contingent upon the quality of the ideas, critical thinking and analysis of the problems to be solved. This chapter therefore, has a significant implications for cumulative research on the nexus between critical thinking and dialogue in Civil Society in contemporary societies
Reconnoitering the Fight Against Political Corruption and the Way Forward in Nigeria
Authors: Omotosho Babatunde Joshua
Published: February 2018

This chapter describes how one of the challenges developing countries face in their quest for effective service delivery and national development relates to the corrupt practices of political office holders. While there has been a continued effort among stakeholders to address this challenge, corruption has continued to fight back. This scenario has implications on the well-being of citizens and the development of the given country. This chapter investigates the challenges of addressing corruption and suggests how it can be addressed using Nigeria as a case.
“Don't Be Evil” and Beyond for High Tech Organizations
Authors: Oravec Jo Ann
Published: February 2018

Societal pressures on high tech organizations to define and disseminate their ethical stances are increasing as the influences of the technologies involved expand. Many Internet-based businesses have emerged in the past decades; growing numbers of them have developed some kind of moral declaration in the form of mottos or ethical statements. For example, the corporate motto “don't be evil” (often linked with Google/Alphabet) has generated considerable controversy about social and cultural impacts of search engines. After addressing the origins of these mottos and statements, this chapter projects the future of such ethical manifestations in the context of critically-important privacy, security, and economic concerns. The chapter analyzes potential influences of the ethical expressions on corporate social responsibility (CSR) initiatives. The chapter analyzes issues of whether “large-grained” corporate mottos can indeed serve to supply social and ethical guidance for organizations as opposed to more complex, detailed codes of ethics or comparable attempts at moral clarification.
Child Labour
Authors: Ahuja Daman
Published: February 2018

This chapter describes how the Child Labour (Prohibition and Regulation) Act of 1986 talks about hazardous units of employability and prohibits employers to employ children in them and regulate the employability of children in the non-hazardous units. Law has laid an emphasis on physical injury that effects the physiology of a child, but the “psychological injury” is left unexamined. Psychological injury can have disastrous impacts on the shape of the personality of a child. The chapter reviewed types of non-hazardous occupations where children are involved at work; methods involved; Ericson's developmental stages of children affected by child labour activities; assessing psychological effects; constitutional provisions; and psycho-social analysis. With an analysis of these factors, it is concluded that once a child gets employed he loses the freedom to spend his time by his own free will.
Unified Swarm Intelligence Algorithms
Authors: Shi Yuhui
Published: February 2018

In this chapter, the necessity of having developmental learning embedded in a swarm intelligence algorithm is confirmed by briefly considering brain evolution, brain development, brainstorming process, etc. Several swarm intelligence algorithms are looked at from a developmental learning perspective. A framework of a developmental swarm intelligence algorithm, which contains capacity developing stage and capability learning stage, is further given to help understand developmental swarm intelligence (DSI) algorithms, and to guide to design and/or implement any new developmental swarm intelligence algorithm and/or any developmental evolutionary algorithm. Following DSI, innovation is discussed and an innovation-inspired optimization (IO) algorithm is designed and developed. Finally, by combing the DSI and IO algorithm together, a unified swarm intelligence algorithm is proposed, which contains capacity developing stage and capability learning stage and with three search operators in its capability learning stage to mimic the three levels of innovations.
Swarm-Intelligence-Based Communication Protocols for Wireless Sensor Networks
Authors: Ketshabetswe Lucia Keleadile , Zungeru Adamu Murtala , Chuma Joseph M. , Mangwala Mmoloki
Published: February 2018

Social insect communities are formed from simple, autonomous, and cooperative organisms that are interdependent for their survival. These communities are able to effectively coordinate themselves to achieve global objectives despite a lack of centralized planning, and the behaviour is referred to as swarm intelligence. This chapter presents a study of communication protocols for wireless sensor networks utilizing nature-inspired systems: social insect-based communities and natural creatures. Three types of insects are used for discussion: ants, termites, and bees. In addition, a study of the social foraging behavior of spider monkeys is presented. The performances of these swarm-intelligence-based algorithms were tested on common routing scenarios. The results were compared with other routing algorithms with varying network density and showed that swarm-intelligence-based routing techniques improved on network energy consumption with a control over best-effort service. The results were strengthened with a model of termite-hill routing algorithm for WSN.
Image Reconstruction of Electrical Impedance Tomography Using Fish School Search and Differential Evolution
Authors: Barbosa Valter Augusto de Freitas , Pinheiro dos Santos Wellington , Emmanuel de Souza Ricardo , Ribeiro Reiga Ramalho , Feitosa Allan Rivalles Souza , Araújo da Silva Victor Luiz Bezerra , Ribeiro David Edson , Freitas Rafaela Covello , Paschoal Manoela , Soares Natália Souza , Valença Rodrigo Beltrão , Ogava Rodrigo Luiz Tomio , Dias Ítalo José do Nascimento Silva Araú
Published: February 2018

Electrical impedance tomography (EIT) is a noninvasive imaging technique that does not use ionizing radiation with application both in environmental sciences and in health. Image reconstruction is performed by solving an inverse problem and ill-posed. Evolutionary and bioinspired computation have become a source of methods for solving inverse problems. In this chapter, the authors investigate the performance of fish school search (FSS) and differential evolution (DE) using non-blind search (NBS) considering meshes of 415, 3190, and 9990 finite elements. The methods were evaluated using numerical phantoms consisting of electrical conductivity images with objects in the center, between the center and the edge, and on the edge of a circular section. Twenty simulations were performed for each configuration. Results showed that both FSS and DE are able to perform EIT image reconstruction with large meshes and converge faster by using non-blind search.
Using Cuckoo Search Algorithm for Hybrid Flow Shop Scheduling Problems Under Makespan Criterion
Authors: Marichelvam M. K. , Tosun Ömür
Published: February 2018

In this chapter, cuckoo search algorithm (CSA) is used to solve the multistage hybrid flow shop (HFS) scheduling problems with parallel machines. The objective is the minimization of makespan. The HFS scheduling problems are proved to be strongly non-deterministic polynomial time-hard (NP-hard). Proposed CSA algorithm has been tested on benchmark problems addressed in the literature against other well-known algorithms. The results are presented in terms of percentage deviation (PD) of the solution from the lower bound. The results indicate that the proposed CSA algorithm is quite effective in reducing makespan because average PD is observed as 1.531, whereas the next best algorithm has result of average PD of 2.295, which is, in general, nearly 50% worse, and other algorithms start from 2.645.
Semantic Web, Ontology, and Linked Data
Authors: Basu Anindya
Published: February 2018

Enormous amount of information is being produced every day and get consumed according to the needs of human being. Semantic web and ontology represent information which are machine processable and understand the semantics present among the entities. Ontology can be represented as Knowledge Organization and data modelling tool. Librarians are designated as “Information Custodian” or “Knowledge Keepers”. Implication and application of concepts in LIS can play big role in shaping knowledge-based services and mining and inferring them in better way in future. Ontology and semantic web is the future of LIS as speculated by several professionals and experts. This chapter would delineate a basic overview of Semantic Web, Ontology and linked data.
Geographic Knowledge Discovery in Multiple Spatial Databases
Authors: Mehenni Tahar
Published: February 2018

Voluminous geographic data have been, and continue to be, collected from various Geographic Information Systems (GIS) applications such as Global Positioning Systems (GPS) and high-resolution remote sensing. For these applications, huge amount of data is maintained in multiple disparate databases and different in spatial data type, file formats, data schema, access mechanism, etc. Spatial data mining and knowledge discovery has emerged as an active research field that focuses on the development of theory, methodology, and practice for the extraction of useful information and knowledge from massive and complex spatial databases. This chapter highlights recent theoretical and applied research in geographic knowledge discovery and spatial data mining in a distributed environment where spatial data are dispersed in multiple sites. The author will present in this chapter, an overall picture of how spatial multi-database mining is achieved through several common spatial data-mining tasks, including spatial cluster analysis, spatial association rule and spatial classification.
Need of Intelligent Search in Dynamic Social Network
Authors: Sonkar Shailendra Kumar , Bhatnagar Vishal , Challa Rama Krishna
Published: February 2018

The user of dynamic social network does not require irrelevant and vast amount of information during a search. A need of an intelligent search is required to get the reduced, filtered and relevant information that is achieved using an intelligent information retrieval and web mining. In this paper, identification and description of facts related to needs of an intelligent search in dynamic social network has been done by the authors after the deep and thorough study conducted on several journal and conference papers that are scattered on different electronic databases globally. The usage of intelligent agent for effective information retrieval from the social network site is a very emerging area and it will help the users to find the relevant and concerned information quickly and efficiently. The findings of the authors will help researchers and scholars who are already working in this area to get the relevant information in the direction of future research.
Query Expansion Based on Central Tendency and PRF for Monolingual Retrieval
Authors: Vaidyanathan Rekha , Das Sujoy , Srivastava Namita
Published: February 2018

Query Expansion is the process of selecting relevant words that are closest in meaning and context to that of the keyword(s) of query. In this paper, a statistical method of automatically selecting contextually related words for expansion, after identifying a pattern in their score, is proposed. Words appearing in top 10 relevant document is given a score w.r.t partitions they appear in. Proposed statistical method, identifies a pattern of central tendency in the high scores and selects the right group of words for query expansion. The objective of the method is to keep the expanded query with minimum words (light), and still give statistically significant MAP values compared to the original query. Experimental results show 17-21% improvement of MAP over the original unexpanded query as baseline but achieves a performance similar to that of the state of the art query expansion models - Bo1 and KL. FIRE 2011 Adhoc English and Hindi data for 50 topics each were used for experiments with Terrier as the Retrieval Engine.
Hypermedia-Based Discovery for Source Selection Using Low-Cost Linked Data Interfaces
Authors: Vander Sande Miel , Verborgh Ruben , Dimou Anastasia , Colpaert Pieter , Mannens Erik
Published: February 2018

Evaluating federated Linked Data queries requires consulting multiple sources on the Web. Before a client can execute queries, it must discover data sources, and determine which ones are relevant. Federated query execution research focuses on the actual execution, while data source discovery is often marginally discussed—even though it has a strong impact on selecting sources that contribute to the query results. Therefore, the authors introduce a discovery approach for Linked Data interfaces based on hypermedia links and controls, and apply it to federated query execution with Triple Pattern Fragments. In addition, the authors identify quantitative metrics to evaluate this discovery approach. This article describes generic evaluation measures and results for their concrete approach. With low-cost data summaries as seed, interfaces to eight large real-world datasets can discover each other within 7 minutes. Hypermedia-based client-side querying shows a promising gain of up to 50% in execution time, but demands algorithms that visit a higher number of interfaces to improve result completeness.
Using Ontological E-Services Framework to Orchestrate E-Business Process Services
Authors: Chou Tung-Hsiang , Lee Ching-Chang , Lin Chin-Wen
Published: February 2018

The Internet has come a long way over the past twenty years, and many Internet-era enterprises have had to face daunting challenges while trying to create innovative business models. Many types of Internet interactions can facilitate networking (e.g., The Web, Web services). Since the advent of the Internet, service requesters and service providers have generated diverse electronic services (e-services), and since 2003, many experts have proposed the concept of Web 2.0. People rely on Internet e-services to execute activities and meet requirements; however, e-services lack a standardization method for constructing and managing them. The current study presents a framework design and a comprehensive interface for e-service providers and requesters. The study adopts the concept of Web 2.0 by using Web services with related standards for developing the framework design. Specifically, the study uses semantic Web technologies to complete the construction of e-services. After that, Internet users can quickly and conveniently access the framework to obtain suitable e-services.
Generating Semantic Annotation of Video for Organizing and Searching Traffic Resources
Authors: Xu Zheng , Zhi Fenglin , Liang Chen , Mei Lin , Luo Xiangfeng
Published: February 2018

Image and video resources play an important role in traffic events analysis. With the rapid growth of the video surveillance devices, large number of image and video resources is increasing being created. It is crucial to explore, share, reuse, and link these multimedia resources for better organizing traffic events. Most of the video resources are currently annotated in an isolated way, which means that they lack semantic connections. Thus, providing the facilities for annotating these video resources is highly demanded. These facilities create the semantic connections among video resources and allow their metadata to be understood globally. Adopting semantic technologies, this paper introduces a video annotation platform. The platform enables user to semantically annotate video resources using vocabularies defined by traffic events ontologies. Moreover, the platform provides the search interface of annotated video resources. The result of initial development demonstrates the benefits of applying semantic technologies in the aspects of reusability, scalability and extensibility.
A Data Mining Framework for Forest Fire Mapping
Authors: Toujani Ahmed , Achour Hammadi
Published: February 2018

Forest fires constitute the major reasons for the loss of biodiversity and degradation of ecosystems. Locally, forest fires are one of the major natural risks in the Kroumirie mountains, northwestern Tunisia. In these massifs, fires occur frequently, and this requires understanding the complex biophysical parameters of this phenomenon. The special attention of the research is paid to the spatial forecasting of forest fires. Different types of classical frequent itemset algorithms have been tested and employed to reveal forest fire patterns that relate the spatial parameters with the probability of fire occurrence. Extracted frequent patterns are then being aggregated through a defined measurement of pertinence. The forest fire risk zone maps are then generated, resulting in extracted spatial patterns. The experiments showed that, the integration of these patterns into GIS could be advantageous to determine risky places and able to produce good prediction accuracy.
Novel Text Summarization Techniques for Contextual Advertising
Authors: Armano Giuliano , Giuliani Alessandro
Published: February 2018

Recently, there has been a renewed interest on automatic text summarization techniques. The Internet has caused a continuous growth of information overload, focusing the attention on retrieval and filtering needs. Since digitally stored information is more and more available, users need suitable tools able to select, filter, and extract only relevant information. This chapter concentrates on studying and developing techniques for summarizing Webpages. In particular, the focus is the field of contextual advertising, the task of automatically suggesting ads within the content of a generic Webpage. Several novel text summarization techniques are proposed, comparing them with state of the art techniques and assessing whether the proposed techniques can be successfully applied to contextual advertising. Comparative experimental results are also reported and discussed. Results highlight the improvements of the proposals with respect to well-known text summarization techniques.
Enhanced Artificial Social Cockroaches (EASC) for Modern Information Retrieval
Authors: Bouarara Hadj Ahmed , Hamou Reda Mohamed , Abdelmalek Amine
Published: February 2018

This article deals on an improved version of the recently developed Artificial Social Cockroaches (ASC) algorithm based on several modifications. The EASC has as input a set of artificial cockroaches and N selected shelters. It is based on a random displacement step and a set of operators (selection cockroaches, shelter attraction, congener's attraction, shelter permutation). Each cockroach must be hidden in the shelter where it feels safer (evaluation function). In the recent years with the coming of the world wide web, the amount of unstructured documents available in the digital society increases and becomes easily accessible, all this has led that satisfy the needs of users in terms of relevant information has become a substantial problem in the scientific community. The second component of the authors' study is to apply the algorithm (EASC) as an information retrieval system using multilingual pre-processing and thesaurus to solve the problems of multilingual query and searching with synonymy. The relevant documents will be rendered as a list of ranked and classified documents from the most relevant to the least relevant. Lastly the authors apply the benchmark Medline and a series of valuation measures (precision, recall, f-measure, entropy, error, accuracy, specificity, TCR, ROC) for the experimentation, also they have compared their results with the outcomes of set of existed systems (social worker bees, taboo search, genetic algorithm, simulating annealing, naïve method). The third component of the authors' system is the visualization step that ensures the presentation of the result in the form of a cobweb with some realism to be understandable by users.
Documenting Provenance for Reproducible Marine Ecosystem Assessment in Open Science
Authors: Ma Xiaogang , Beaulieu Stace E. , Fu Linyun , Fox Peter , Di Stefano Massimo , West Patrick
Published: February 2018

Open Science not only means the openness of various resources involved in a scientific study but also the connections among those resources that demonstrate the origin, or provenance, of a scientific finding or derived dataset. In this chapter, the authors used the PROV Ontology, a community standard for representing and exchanging machine-readable provenance information in the Semantic Web, and extended it for capturing provenance in the IPython Notebook, a software platform that enables transparent workflows. The developed work was used in conjunction with scientists' workflows in the Ecosystem Assessment Program of the U.S. NOAA Northeast Fisheries Science Center. This work provides a pathway towards formal, well-annotated provenance in an electronic notebook. Not only will the use of such technologies and standards facilitate the verifiability and reproducibility of ecosystem assessments, their use will also provide solid support for Open Science at the interface of science and ecosystem management for sustainable marine ecosystems.
Arabic Query Expansion Using WordNet and Association Rules
Authors: Abbache Ahmed , Meziane Farid , Belalem Ghalem , Belkredim Fatma Zohra
Published: February 2018

Query expansion is the process of adding additional relevant terms to the original queries to improve the performance of information retrieval systems. However, previous studies showed that automatic query expansion using WordNet do not lead to an improvement in the performance. One of the main challenges of query expansion is the selection of appropriate terms. In this paper, the authors review this problem using Arabic WordNet and Association Rules within the context of Arabic Language. The results obtained confirmed that with an appropriate selection method, the authors are able to exploit Arabic WordNet to improve the retrieval performance. Their empirical results on a sub-corpus from the Xinhua collection showed that their automatic selection method has achieved a significant performance improvement in terms of MAP and recall and a better precision with the first top retrieved documents.
On the Updating of Domain OWL Models at Runtime in Factory Automation Systems
Authors: Puttonen Juha , Lobov Andrei , Lastra José L. Martinez
Published: February 2018

Software agents controlling production devices must maintain an up-to-date view of the physical world state in order to efficiently reason and plan their actions. Especially in a factory automation system, the world state undergoes rapid evolution. To enable accurate decision-making, the world view must constantly be synchronized with the changes. This paper discusses two approaches to updating the world view based on event notifications sent by web services representing production devices in a manufacturing system. One approach requires that a set of update rules is separately specified, whereas the other involves automatically deriving the update rules from the semantic web service descriptions. While this paper specifically focuses on the factory automation domain, both of the approaches presented are applicable to other domains as well. The main assumptions are that the domain is composed of world-altering web services, which provide adequate service interfaces to detect changes in their state, and that all relevant changes in the overall domain state can be directly derived from the service state changes.
Information Architecture
Authors: Magalhães Pessoa Cláudio Roberto , Erichsen Monica Nassif , Baracho Renata Maria Abranches , Jamil George Leal
Published: February 2018

This paper main objective is to raise information and knowledge demands in an information technology consulting organization, aiming to prepare an information architecture project, where the information and knowledge management will contribute to the expected improvement. A descriptive research has been prepared, using an interview script that enabled to reach the desired goal. It was concluded that existing investments are isolated, without an effective planning that might allow the company to achieve results that would bring real improvements to it.
Learning Analytics
Authors: Zeirhun Zenawi
Published: February 2018

The aim of learning analytics is to apply available facts from different systems and databases if you want to assist students and instructors in learning and teaching processes. In order to ensure that important groups of users get what they need the most with the aid of the usage of getting to know analytics, it may be vital to broaden possible needs evaluation methodology as well as to perform the wishes evaluation in step with it. There is much less research into the role and implementation of analytics in college training than in higher schooling. This chapter focuses on primary and secondary schools. Final results are presented in the form of the most relevant questions posed by students and teachers that a learning analytics system is supposed to answer.
An Intervention Program for Advancing the Academic Performance of International Pathway “STAR”
Authors: Velliaris Donna Marie
Published: February 2018

As part of an intervention and support strategy, this chapter discusses the evidence-based merits of a tertiary skills development (TSD) course delivered at the Eynesbury Institute of Business and Technology (EIBT) to “students at risk” (STAR). The effectiveness of the TSD course was measured via quantitative means by comparing students' academic performance before, during, and after TSD intervention. It was found that student performance analysed over three consecutive trimesters underwent a significant improvement when the support strategy was provided, followed by a small downturn in performance when the support was removed and students were again relying solely on their independent study skills and self-directed learning.
Evaluation of Impact of New Democracy on Consumption, Income and Growth of the Nigerian Economy
Authors: Aruofor Rex Oforitse , Ogbeide Daniel Risiagbon
Published: February 2018

This article describes how the new democracy in Nigeria has existed for eighteen uninterrupted years and many scholars believe that it has been an improvement over past regimes. The acid test of this claim is to find out if the new democracy has indeed caused a shift in the consumption pattern and a change in the consumption habit of Nigerians. The total differential modeling approach was applied to test the null hypothesis that the new democracy has not impacted the standard of living of the average Nigerian. The results indicated that the new democracy did cause a shift of N6.61E+06 and N9.27E+08 on consumption and income, respectively, in 1999 as well as caused a change in consumption habit of N32.9 million annually. Nominal income also changed by N46.13 million annually as a result of the new democracy. The growth in consumption and nominal income were N22708022 million and N31832692 million, respectively. In addition, the new democracy induced a change of N0.995 mill/annum in real income. Therefore, it will seem that the new democracy has positively impacted the Nigerian economy. However, while the growth rate associated with past administrations is 0.6634%, in terms of real growth, it will seem that there is no significant growth in the economy associated with the current democracy. This article also shares some recommendations that will make this impact manifest on the economy.
Impact of Training and Development on Employee Performance
Authors: Abogsesa Alsharif S , Kaushik Geetanjali
Published: February 2018

This article was aimed at investigating the impact of training and development on employee performance and productivity in Jumhuria bank. Interviews were conducted with employees. It was observed that there was a lack of a comprehensive system for assessing the training needs, participant selection and effective procedures for their evaluation. Further the evaluation of training was poor and only for namesake. Also, rather than playing highly proactive role training was just reactive in nature. It was also found that training and development was highly relevant and effective in improving the staff member's knowledge, skills, behaviour and attitudes. training did not have any impact over innovation, absenteeism, job turnover rate and job satisfaction. Nevertheless, training increased the employee's job performance and productivity. It was observed that the process of training and development was associated with various problems.