bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimized Base Station Sleeping and Smart Grid Energy Procurement Scheme to Improve Energy Efficiency
Authors: Wang Qiang , Liu Hai-Lin
Published: February 2018

In this chapter, the authors propose a joint BS sleeping strategy, resource allocation, and energy procurement scheme to maximize the profit of the network operators and minimize the carbon emission. Then, a joint optimization problem is formulated, which is a mixed-integer programming problem. To solve it, they adopt the bi-velocity discrete particle swarm optimization (BVDPSO) algorithm to optimize the BS sleeping strategy. When the BS sleeping strategy is fixed, the authors propose an optimal algorithm based on Lagrange dual domain method to optimize the power allocation, subcarrier assignment, and energy procurement. Numerical results illustrate the effectiveness of the proposed scheme and algorithm.
Bates' Berrypicking Model (1989, 2002, 2005)
Authors: Lillard Linda L. , Ha YooJin
Published: February 2018

Bates' model integrated a biological and a socio-cultural perspective to argue that, in practice, information seeking does not follow a systematic search process but more commonly takes the form of “berry picking”, or finding information bit by bit using a range of sources. According to her theory, humans collect most of their information through passive, undirected behavior, while the remainder is generated using three types of behavior defined as monitoring, browsing and directed search. Bates argued that a process of sampling and selection that she refers to as “berry picking”, underlies most browsing and directed searches, and has evolved from traditional mating and foraging behaviors. The chapter discusses the diverse theoretical perspectives on which Bates' model is based, and its key contributions to Information Science.
Method to Reduce Complexity and Response Time in a Web Search
Authors: Romagnano María R. , Aciar Silvana V. , Marchetta Martín G.
Published: February 2018

Living in times of technological changes that alter our daily activities, involving tasks such as reading the newspaper, following the weather, scheduling a trip, are usually executed after perusal of the gigantic repository of information, commonly known as the World Wide Web. However some problems are still associated with the information found in such a vast amount of information: heterogeneity, availability, distribution, quality and quantity of irrelevant information. Recent work has suggested different ways of grouping similar information sources, trying to give solutions to these problems. However, some domains are more complex than others. For example, a person looking for tourist information, is generally overwhelmed by visiting various websites. This paper proposes the implementation of a method to retrieve and group web information sources, depending on the services they offer; thereby allowing the user to get accurate answers; thus reducing the time and complexity in the search.
Knowledge Discovery for Large Databases in Education Institutes
Authors: Saadatdoost Robab , Sim Alex Tze Hiang , Jafarkarimi Hosein , Hee Jee Mei
Published: February 2018

This project presents the patterns and relations between attributes of Iran Higher Education data gained from the use of data mining techniques to discover knowledge and use them in decision making system of IHE. Large dataset of IHE is difficult to analysis and display, since they are significant for decision making in IHE. This study utilized the famous data mining software, Weka and SOM to mine and visualize IHE data. In order to discover worthwhile patterns, we used clustering techniques and visualized the results. The selected dataset includes data of five medical university of Tehran as a small data set and Ministry of Science - Research and Technology's universities as a larger data set. Knowledge discovery and visualization are necessary for analyzing of these datasets. Our analysis reveals some knowledge in higher education aspect related to program of study, degree in each program, learning style, study mode and other IHE attributes. This study helps to IHE to discover knowledge in a visualize way; our results can be focused more by experts in higher education field to assess and evaluate more.
SPORTAL
Authors: Hasnain Ali , Mehmood Qaiser , Sana e Zainab Syeda , Hogan Aidan
Published: February 2018

Access to hundreds of knowledge bases has been made available on the Web through public SPARQL endpoints. Unfortunately, few endpoints publish descriptions of their content (e.g., using VoID). It is thus unclear how agents can learn about the content of a given SPARQL endpoint or, relatedly, find SPARQL endpoints with content relevant to their needs. In this paper, the authors investigate the feasibility of a system that gathers information about public SPARQL endpoints by querying them directly about their own content. With the advent of SPARQL 1.1 and features such as aggregates, it is now possible to specify queries whose results would form a detailed profile of the content of the endpoint, comparable with a large subset of VoID. In theory it would thus be feasible to build a rich centralised catalogue describing the content indexed by individual endpoints by issuing them SPARQL (1.1) queries; this catalogue could then be searched and queried by agents looking for endpoints with content they are interested in. In practice, however, the coverage of the catalogue is bounded by the limitations of public endpoints themselves: some may not support SPARQL 1.1, some may return partial responses, some may throw exceptions for expensive aggregate queries, etc. The authors' goal in this paper is thus twofold: (i) using VoID as a bar, to empirically investigate the extent to which public endpoints can describe their own content, and (ii) to build and analyse the capabilities of a best-effort online catalogue of current endpoints based on the (partial) results collected.
Information Retrieval Model Using Uncertain Confidence's Network
Authors: Naouar Fatiha , Hlaoua Lobna , Omri Mohamed Nazih
Published: February 2018

This paper proposes a new relevance feedback approach to collaborative information retrieval based on a confidence's network, which performs propagation relevance between annotations terms. The main contribution of our approach is to extract relevant terms to reformulate the initial user query considering the annotations as an information source. The proposed model introduces the concept of necessity that allows determining the terms that have strong association relationships. The authors estimated the association relationship to a measure of a confidence. Another contribution consists on determining the relevant annotations for a given evidence source. Since the user is over whelmed by a variety of contradictory annotations on even one which are far from the original subject, the authors' model proceed filtering these annotations to determine the relevant one and then it classify them by grouping those related semantically. The experimental study conducted on different queries gives promoters results. They show very encouraging results that could reach an improvement rate.
Web Semantics for Personalized Information Retrieval
Authors: Singh Aarti , Sharma Anu
Published: February 2018

This chapter explores the synergy between Semantic Web (SW) technologies and Web Personalization (WP) for demonstrating an intelligent interface for Personalized Information Retrieval (PIR) on web. Benefits of adding semantics to WP through ontologies and Software Agents (SA) has already been realized. These approaches are expected to prove useful in handling the information overload problem encountered in web search. A brief introduction to PIR process is given, followed by description of SW, ontologies and SA. A comprehensive review of existing web technologies for PIR has been presented. Although, a huge contribution by various researchers has been seen and analyzed but still there exist some gap areas where the benefits of these technologies are still to be realized in future personalized web search.
Artificial Haemostasis System for Modern Information Retrieval With 3D Result-Mining
Authors: Bouarara Hadj Ahmed , Hamou Reda Mohamed , Amine Abdelmalek
Published: February 2018

The Human, existed since millions of years and consequently, be inspired from the physiological phenomenon of the human body organs is something really interesting. This is the origin of the authors' new bio-inspired technique, called artificial haemostasis system (AHS), based on the haemostasis phenomenon that prevents and stops bleeding in case of external haemorrhage. Aiming at contributing to web searching they have applied their AHS to solve the problem of information retrieval following four steps: multilingual pre-processing (pre-haemostasis) to transform each text into a vector and ensure the service of multilingual search; The texts vectors pass through three filters: the primary information retrieval (primary haemostasis), the secondary information retrieval (secondary haemostasis) and the final information retrieval (fibrinolysis) using a selection step (plasminogen activation) to evaluate the relevance of each document to the query; the authors' experiments were performed on MEDLARS collection in order to show the benefit gained from using such approach compared to the classic one validated by a set of evaluation measures (recall, precision, FNR, FPR, f-measure, ROC, accuracy, Error, sensibility, and TCR); Finally, a result-mining step to see the results in graphical form with more realism, where the 3D cub method is largely preferred by the user than the cobweb method; The results of the system, are positive compared to the results provided by a conventional method and a set of bio-inspired techniques existed In literature (Simulating annealing (SA), Social worker bees (SWB), and Artificial social cockroaches (ASC)).
Information Retrieval Models
Authors: Krishnamurthy Saruladha , V Akila
Published: February 2018

Information retrieval is currently an active research field with the evolution of World wide web. The objective of this chapter is to provide an insight into the information retrieval definitions, process, models. Further how traditional information retrieval has evolved and adapted for search engines is also discussed. The information retrieval models have not only been used for search purpose it also supports cross lingual translation and retrieval tasks. This chapter also outlines the CLIR process in a brief manner. The tools which are usually used for experimental and research purpose is also discussed. This chapter is organized as Introduction to the concepts of information retrieval. Description of the information retrieval process, the information retrieval models, the role of external sources like ontologies in information retrieval systems. Finally the chapter provides an overview of CLIR and the tools used in developing IR systems is mentioned. Further the latest research directions in IR is explained.
Using a Dialogue Manager to Improve Semantic Web Search
Authors: Melo Dora , Rodrigues Irene Pimenta , Nogueira Vitor Beires
Published: February 2018

Question Answering systems that resort to the Semantic Web as a knowledge base can go well beyond the usual matching words in documents and, preferably, find a precise answer, without requiring user help to interpret the documents returned. In this paper, the authors introduce a Dialogue Manager that, through the analysis of the question and the type of expected answer, provides accurate answers to the questions posed in Natural Language. The Dialogue Manager not only represents the semantics of the questions, but also represents the structure of the discourse, including the user intentions and the questions context, adding the ability to deal with multiple answers and providing justified answers. The authors' system performance is evaluated by comparing with similar question answering systems. Although the test suite is slight dimension, the results obtained are very promising.
The Implementation of DSSim
Authors: Vargas-Vera Maria
Published: February 2018

This paper presents the decisions taken during the implementation of DSSim (DSSim stands for Similarity based on Dempster-Shafer) our multi-agent ontology mapping system. It describes several types of agents and their roles in the DSSim architecture. These agents are mapping agents which are able to perform either semantic or syntactic similarity. Our architecture is generic as no mappings need to be learned in advance and it could be easily extended by adding new mapping agents in the framework. The new added mapping agents could run different similarity algorithms (either semantic or syntactic). In this way, DSSim could assess which algorithm has a better performance. Additionally, this paper presents the algorithms used in our ontology alignment system DSSim.
Context Window Based Co-Occurrence Approach for Improving Feedback Based Query Expansion in Information Retrieval
Authors: Singh Jagendra , Sharan Aditi
Published: February 2018

Pseudo-relevance feedback (PRF) is a type of relevance feedback approach of query expansion that considers the top ranked retrieved documents as relevance feedback. In this paper the authors focus is to capture the limitation of co-occurrence and PRF based query expansion approach and the authors proposed a hybrid method to improve the performance of PRF based query expansion by combining query term co-occurrence and query terms contextual information based on corpus of top retrieved feedback documents in first pass. Firstly, the paper suggests top retrieved feedback documents based query term co-occurrence approach to select an optimal combination of query terms from a pool of terms obtained using PRF based query expansion. Second, contextual window based approach is used to select the query context related terms from top feedback documents. Third, comparisons were made among baseline, co-occurrence and contextual window based approaches using different performance evaluating metrics. The experiments were performed on benchmark data and the results show significant improvement over baseline approach.
Document Retrieval Using Efficient Indexing Techniques
Authors: Gupta Shweta , Yadav Sunita , Prasad Rajesh
Published: February 2018

Document retrieval plays a crucial role in retrieving relevant documents. Relevancy depends upon the occurrences of query keywords in a document. Several documents include a similar key terms and hence they need to be indexed. Most of the indexing techniques are either based on inverted index or full-text index. Inverted index create lists and support word-based pattern queries. While full-text index handle queries comprise of any sequence of characters rather than just words. Problems arise when text cannot be separated as words in some western languages. Also, there are difficulties in space used by compressed versions of full-text indexes. Recently, one of the unique data structure called wavelet tree has been popular in the text compression and indexing. It indexes words or characters of the text documents and help in retrieving top ranked documents more efficiently. This paper presents a review on most recent efficient indexing techniques used in document retrieval.
Document Clustering Using an Ontology-Based Vector Space Model
Authors: Costa Ruben , Lima Celson
Published: February 2018

This paper introduces a novel conceptual framework to support the creation of knowledge representations based on enriched Semantic Vectors, using the classical vector space model approach extended with ontological support. One of the primary research challenges addressed here relates to the process of formalization and representation of document contents, where most existing approaches are limited and only take into account the explicit, word-based information in the document. This research explores how traditional knowledge representations can be enriched through incorporation of implicit information derived from the complex relationships (semantic associations) modelled by domain ontologies with the addition of information presented in documents. The relevant achievements pursued by this work are the following: (i) conceptualization of a model that enables the semantic enrichment of knowledge sources supported by domain experts; and (ii) implementation of a proof-of-concept, named SENSE (Semantic Enrichment knowledge Sources).
Quantifying the Connectivity of a Semantic Warehouse and Understanding Its Evolution Over Time
Authors: Mountantonakis Michalis , Minadakis Nikos , Marketakis Yannis , Fafalios Pavlos , Tzitzikas Yannis
Published: February 2018

In many applications one has to fetch and assemble pieces of information coming from more than one source for building a semantic warehouse offering more advanced query capabilities. In this paper the authors describe the corresponding requirements and challenges, and they focus on the aspects of quality and value of the warehouse. For this reason they introduce various metrics (or measures) for quantifying its connectivity, and consequently its ability to answer complex queries. The authors demonstrate the behaviour of these metrics in the context of a real and operational semantic warehouse, as well as on synthetically produced warehouses. The proposed metrics allow someone to get an overview of the contribution (to the warehouse) of each source and to quantify the value of the entire warehouse. Consequently, these metrics can be used for advancing data/endpoint profiling and for this reason the authors use an extension of VoID (for making them publishable). Such descriptions can be exploited for dataset/endpoint selection in the context of federated search. In addition, the authors show how the metrics can be used for monitoring a semantic warehouse after each reconstruction reducing thereby the cost of quality checking, as well as for understanding its evolution over time.
Search Engines and Meta Search Engines for Effective Information Retrieval and Scholarly Communication
Authors: Vivekavardhan J.
Published: February 2018

Search Engines (SEs) and Meta-Search Engines (MSEs) are the tools that allows people to find information on the World Wide Web. SEs and MSEs on internet have improved continually with application of new methodologies to satisfy their users by providing them with relevant information. Understanding and Utilization of SEs and MSEs are useful for information scientist, knowledge manager, librarians and most importantly for authors and researchers for effective information retrieval and scholarly communication. The paper explores on how Search Engines and Meta-Search Engines discover web pages, indexes content, and provide search results. The paper discusses about the technological evolution of SEs and MSEs, working process and different types of SEs and MSEs. Finally paper presents conclusions and suggestions for further research.
How Experience and Expertise Affect the Use of a Complex Technology
Authors: Goeke Richard J. , Faley Robert H. , Brandyberry Alan A. , Dow Kevin E.
Published: February 2018

As end-users work with increasingly complex technologies, it is important that these technologies be used to the fullest extent possible. Time is needed to learn how to use these new technologies and fit them to user tasks, but the fact that a user has gained experience does not mean that expertise has also been gained. Using survey data collected from 187 data warehouse end-users, we found that experience and expertise have a significant positive correlation (r = 0.35, p < 0.001), but expertise has a significantly greater effect on ease-of-use perceptions (t=10.2, p < 0.0001) and the use of a technology (t=21.08, p < 0.0001) than experience. Therefore, it is critical that researchers properly delineate which construct – end-user expertise or experience – is being assessed, when measuring the effect that individual differences have on the perceptions and use of technology.
Data Storages in Wireless Sensor Networks to Deal With Disaster Management
Authors: Gheisari Mehdi , Esnaashari Mehdi
Published: February 2018

Sensor networks are dense wired or wireless networks used for collecting and disseminating environmental data. They have some limitations like energy that usually provide by battery and storages in order that we cannot save any generated data. The most energy consumer of sensors is transmitting. Sensor networks generate immense amount of data. They send collected data to the sink node for storage to response to users queries. Data storage has become an important issue in sensor networks as a large amount of collected data need to be archived for future information retrieval. The rapid development and deployment of sensor technology is intensifying the existing problem of too much data and not enough knowledge. Sensory data comes from multiple sensors of different modalities in distributed locations. In this chapter we investigate some major issues with respect to data storages of sensor networks that can be used for disaster management more efficiently.
Digital Identity of Researchers 2.0
Authors: Oliveira Nuno Ricardo , Morgado Lina
Published: February 2018

This chapter results from an investigation into the digital identity of a community of researchers, part of a PhD study on Education focused on Personal Learning Networks (PLN). Today the social web is a massive reality in academic research, which leads to question the importance of the digital presence of researchers in these informal contexts and how they relate to each other. With the evolution of the internet, new challenges are posed to researchers, both socially (social web) and academically. Immersion in these digital environments promotes the development of open research practices, with evidence of interactions between group members, stressing the collaborative way we interact in the context of learning throughout life. Thus, the social web allows the researcher 2.0 to access the work of other researchers quickly and effectively, sharing content and collaborating with others through a PLN. This personal network requires a range of skills related to the digital identity of researchers, considering the environment in which they are operating.
Using Information Retrieval for Interaction With Mobile Devices
Authors: Yuksel Kamer Ali
Published: February 2018

Future's environments will be sensitive and responsive to the presence of people to support them carrying out their everyday life activities, tasks and rituals, in an easy and natural way. Such interactive spaces will use the information and communication technologies to bring the computation into the physical world in order to enhance ordinary activities of their users. Human-computer interaction (HCI) and information retrieval (IR) fields have both developed innovative techniques to address the challenge of navigating complex information spaces, but their insights have often failed to cross-disciplinary borders. Human-computer information retrieval (HCIR) has emerged in academic research and industry practice to bring together research in the fields of IR and HCI, in order to create new kinds of search systems that depend on continuous human control of the search process. HCIR is the study of information retrieval techniques that bring human intelligence into the search process. This chapter will describe search-based interaction techniques using two human-computer interaction information retrieval systems: (1) a speech-based spoken multimedia retrieval system that can be used to present relevant video-podcast (vodcast) footage in response to spontaneous speech and conversations during daily life activities, and (2) a novel shape retrieval technique that allows 3D modeling of indoor/outdoor environments using multi-view sketch input from a mobile device.
The Importance of Authoritative URI Design Schemes for Open Government Data
Authors: Bulazel Alexei , DiFranzo Dominic , Erickson John S. , Hendler James A.
Published: February 2018

A major challenge when working with open government data is managing, connecting, and understanding the links between references to entities found across multiple datasets when these datasets use different vocabularies to refer to identical entities (i.e.: one dataset may refer to Microsoft as “Microsoft”, another may refer to the company by its SEC filing number as “0000789019”, and a third may use its stock ticker “MSFT”.) In this paper the authors propose a naming scheme based on Web URLs that enables unambiguous naming and linking of datasets and, more importantly, data elements, across the Web. They further describe their ongoing work to demonstrate the implementation and authoritative management of such schemes through a class of web service they refer to as the “instance hub”. When working with linked government data, provided either directly from governments via open government programs or through other sources, the issue of resolving inconsistencies in naming schemes is particularly important, as various agencies have disparate conventions for referring to the same concepts and entities. Using linked data technologies the authors have created instance hubs to assist in the management and linking of entity references for collections of categorically and hierarchically related entities. Instance hubs are of particular interest to governments engaged in the publication of linked open government data, as they can help data consumers make better sense of published data and can provide a starting point for development of linked data applications. In this paper the authors present their findings from the ongoing development of a prototype instance hub at the Tetherless World Constellation at Rensselaer Polytechnic Institute (TWC RPI). The TWC RPI Instance Hub enables experimentation and verification of proposed URI design schemes for open government data, especially those developed at TWC in collaboration with the United States Data.gov program. They discuss core principles of the TWC RPI Instance Hub design and implementation, and summarize how they have used their instance hub to demonstrate the possibilities for authoritative entity references across a number of heterogeneous categories commonly found in open government data, including countries, federal agencies, states, counties, crops, and toxic chemicals.
Semantic Mediation in MedPeer
Authors: Ougouti Naïma Souâd , Belbachir Haféda , Amghar Youssef
Published: February 2018

Peer-to-Peer (P2P) infrastructure is an emerging paradigm that offers new opportunities for the development of large-scale distributed systems. This architecture combined with the new techniques introduced by semantic web as ontologies encouraged the emergence of new multi-source data integration possibilities for sharing information. A challenging problem in such systems is to find correspondences between concepts of their different ontologies. This is a necessary step before locating peers that are relevant with respect to a given query. In this paper, the authors propose a new ontology alignment method which deals with both linguistic and semantic characteristics of concepts and uses graph structure to explore multiple depth levels of neighborhood in calculation of semantic similarity which is the most important part of their global similarity measure. This function is implemented into their new P2P heterogeneous and distributed data integration system MedPeer.
A Review of Answering Queries Over Ontologies Based on Databases
Authors: Zhang Fu , Ma Z. M. , Cheng Haitao
Published: February 2018

Ontologies, as a standard (W3C recommendation) for representing knowledge in the Semantic Web, have been employed in many application domains. Currently, real ontologies tend to become very large to huge. Thus, one problem is considered that has arisen from practical needs: namely, efficient querying of ontologies. To this end, there are today many proposals for answering queries over ontologies, and until now the literature on querying of ontologies has been flourishing. In particular, on the basis of the efficient and mature techniques of databases, which are useful for querying ontologies. To investigate querying of ontologies and more importantly identifying the direction of querying of ontologies based on databases, in this chapter, we aim at providing a brief review of answering queries over ontologies based on databases. Some query techniques, their classifications and the directions for future research, are introduced. Other query formalisms over ontologies that are not related to databases are not covered here.
A Study on the Impact of Learning Analytics to Evaluate Students' Performance in Higher Education
Authors: Singh Neerja
Published: February 2018

Learning analytics is receiving increased awareness because it helps educational institutions in growing student retention, enhancing student fulfillment, and easing the burden of accountability. Although those massive-scale issues are worthy of attention, schools may additionally be inquisitive about how they can use learning analytics in their personal guides to assist their students. In this chapter, the authors define learning analytics, the way it has been used in educational establishments, what learning analytics tools are available, and how college can make use of facts in their publications to reveal scholar overall performance. Finally, the authors articulate several problems and uncertainties with the usage of learning analytics in higher education.
Impact of Learning Analytics on the Assessment of a Curriculum-Based Test
Authors: Singh Neerja
Published: February 2018

The assessment is not limited to only the measurement of memorized awareness; all the way through it, the various abilities of the individual are considered. Such evaluation of abilities is of great significance in obtaining knowledge about the individual's aptitude, interest, capability, and capacity. The evaluation of ability is now done with the help of psychological tests. The different types of psychological tests that are used in measuring intelligence and different types of abilities. It is worth consideration that the psychological tests are constructed on certain general principles and in this connection some specific conditions and characteristics are always kept in mind. In this chapter, the author's aim is to describe these principles and the specific conditions as well as to assess the importance of learning analytics on this platform.
Implementation and Impact of Learning Analytics on Multifarious Educational Systems
Authors: Singh Manoj Kumar
Published: February 2018

The understanding of approaches on theory and practices is to move “from clicks to constructs” in a principled way. Learning analytics are a particular living form of the larger shift to an algorithmically pervaded society, and their wider impact on education desires careful consideration. In this chapter, the author argues that by using design in any other case the usage of a mastering analytics device is continually aligned with evaluation regimes, which are flip grounded in assumptions and pedagogical practices. Fundamentally then, the author argues that deploying a given getting to know analytics device expresses a dedication to a specific academic worldview designed to nurture unique varieties of new researchers and improvement of learning analytic strategies as well as to use the evaluation process for analysis of the implicit or specific stances taken in the design and deployment of technology to address those key questions and clearly shape the impact of learning analytics on mixed educational systems.
An Efficient and Congestion Aware Fuzzy Based Output Selection Strategy for On-Chip Routers
Authors: Arora Ashima , Shukla Neeraj Kr.
Published: February 2018

The network performance of an adaptive router largely depends on well designed selection strategy. The selection function selects one of the accepted output directions returned by the routing function. The effectiveness of any selection strategy relies on its congestion free traffic distribution mechanism for each incoming packet. This article proposes a fuzzy based output selection strategy that considers the congestion information from both neighboring routers as well as routers on global path. The strategy efficiently balances the traffic load by using the knowledge base of fuzzy controllers. Performance evaluation is carried out using a cycle accurate simulator under synthetic traffic conditions. The experimental results show that the fuzzy based selection strategy improves the performance by increased throughput and reduced packet latency when compared with other traditional selection strategies.
Chaotic Tornadogenesis Optimization Algorithm for Data Clustering Problems
Authors: Saidala Ravi Kumar , Devarakonda Nagaraju
Published: February 2018

This article describes how clustering is an attractive and major task in data mining in which particular set of objects are grouped according to their similarities based on some criteria. Among the numerous algorithms, k-Means is the best and efficient in address clustering problems. Any expert system is said to be good, only if it returns the optimal data clusters. The challenge of optimal clustering lies in finding the optimal number of clusters and identifying all the data groups correctly which is a NP-hard problem. Recently a new optimization algorithm TOA was developed to address these problems. However, the standard TOA is too often trapped at the local optima and premature convergence. To overcome this, this article proposes CTOA. The main objective of embedding chaotic maps into standard TOA is to compute and automatically adapt the internal parameters. The proposed CTOA is first benchmarked on standard mathematical functions and later applied to 10 data clustering problems. The obtained graphical and statistical results along with comparisons illustrate the capabilities of CTOA regarding accuracy and robustness
Use and Misuse of Technology in Marketing
Authors: Fatma Sabeeha
Published: February 2018

This article describes how the recent breakthrough in information technology has changed in day-to-day life. The smart phone rules the minds and hearts of a major chunk of the population. Internet has become a basic requirement of many a people. Although technology has affected all functional area of business, marketing is feeling the heat even more. The leap in the information technology replaced mass marketing with one-to-one marketing. Customer relationship, knowledge management, database marketing became the buzz words during 1990s. Search services, biometrics and smart cards, enhanced computational speed, M-commerce, and GPS tracking have changed the way marketing is done. However, technology is often misused by marketers to lure customers on wrong premises. Marketers may at times misuse technology for their vested interest. The article discusses the various cases where technology has been misused by the marketers. The article explores the technological innovations in marketing and the potential misuse of technology with special focus on cases from India.
Applying Metaheuristics to Minimize Work-Related Musculoskeletal Disorders
Authors: Pata Arminda , Moura Ana
Published: February 2018

This article covers the topic of planning and organization of work, which is one of the biggest problems is to establish the most appropriate allocations between human and technical resources, according to the characteristics that define and characterize each individual. These adjustments to decision-making regarding the characteristics of a new larger workforce is a challenge for human resource managers and researchers working to provide well-being and quality of life improvements for employees. The problem of work-related musculoskeletal disorders, coupled with the aging of the active population, may increase the number of citizens with permanent disabilities. Given the complexity and uniqueness of the problems, a decision support system that uses some metaheuristic approaches is presented. The result is a hybrid approach that gives the best solution according to several parameters defined by the decision-maker. Computational results of real problem instances are presented, proving that in most cases, the optimal solution is achieved.
Phenetic and genetic characterization of selected economically important species in the family Zingiberaceae
Authors: Silva A. B. W. R. , Herath H. , Senanayake S. P. , Swarnathilaka D. B. R.
Published: February 2018

Zingiberaceae, includes medicinally and economically important monocotyledons mostly distributed in South and South East Asia. A complete taxonomic knowledge of this plant group in Sri Lanka is lacking hence the present study was carried out to characterize and infer phenetic and genetic relationships of eight economically important zingibers. Morphological and anatomical characters of leaves, rhizomes and adventitious roots and phenolic characters of leaves were cluster analysed using MINITAB 17 to derive relationships. A phylogram was obtained from MEGA software using rDNA ITS sequences amplified by PCR from leaf genomic DNA. Costus speciosus was used as the out group in the phylogenetic study. As per the principal component analysis plant height, rhizome diameter, length of rhizome internodes, leaf length, leaf width and length of leaf petiole can be recommended as suitable for characterization of these taxa. rDNA ITS regions may well be used for Zingiber and Curcuma species identification. Combination of morphological, anatomical and phenolic characters can be used in delimiting commonly used Z. officinale cultivars and Curcuma species in Sri Lanka. Further, derived genetic relationships of these taxa would provide better information in characterization of commonly used Zingiber cultivars, Curcuma and Alpinia species in Sri Lanka at the initial developmental stages and would support in quality improvement breeding programs.
A preliminary study on effect of buddhist pirith chanting and pop music on the growth and yield performance in rice (Oryza sativa L.)
Authors: Munasinghe D. S. P. , Liyanage K. C. M. , Weerakoon S. R. , Somaratne S. , Dissanayake D. M. L. C.
Published: February 2018

Music influences the growth of plants through either promoting or restricting the growth of plants. The effects of Pirith chanting and pop music were focused in the present study. Seeds of Two (02) rice varieties (Bg300 and Kaluheenati) were subjected to dormancy break treatment, kept in a soundproof confined chamber and arranged in Completely Randomized Design (CRD) with two (02) replicates and 10 seeds per replicate. Seeds were allowed to germinate under the sound rhythms; pop music, Pirith chanting and silence separately in sound proof chamber. A set of pop songs and Thunsuthra in Pirith chanting were chosen as the two (02) sound rhythms. Seeds were kept under silence served as the control. Music and Pirith were played separately for an hour, at 30cm distance away from the seeds with an intensity of 55-60 dB for seven (07) days continuously, maintaining equal environmental conditions. Following seven (07) days, the percent germination was recorded. The same germinated seeds were planted in plastic pots filled with paddy soil, up to ¾ of the total depth and pots were arranged in Completely Randomized Design (CRD) with two (02) replicates and five (05) plants per replicate. Following one week, plants were subjected to the sound rhythm treatments and silence separately for three (03) months continuously. Measurement on growth and yield performance were recorded every fortnight. Significantly different (p < 0.05) in growth and yield performances were observed under Pirith and pop music. Considerably higher rates of growth and yield were observed for varieties exposed to Pirith and comparatively, the effect of Pirith on growth and yield performance was higher with respect to pop music thus implying that the rhythmic chanting of Pirith is the most appropriate type music that improved the growth performance of Oryza sativa.
Athletic Training Students' and Preceptors' Perceptions of Active Learning Time and Bug-In-Ear Technology During Clinical Education Experiences
Authors: Nottingham Sara L. , Kasamatsu Tricia M. , Montgomery Melissa M.
Published: February 2018

Context:

Engaging clinical experiences that allow extensive active learning and patient care interactions are important for the professional development of athletic training students. Understanding students' use of clinical time is important when attempting to improve these experiences.

Objective:

To gain participants' perspectives on active learning during clinical education both with and without the use of bug-in-ear technology.

Design:

Qualitative.

Setting:

Three high schools, 2 rehabilitation clinics, 1 university, and 1 community college clinical sites within 3 Commission on Accreditation of Athletic Training Education–accredited undergraduate athletic training programs.

Patients or Other Participants:

Thirteen athletic training students (11 female, 2 male; 22 ± 2 years old, 2 ± 1 years enrolled in the current accredited athletic training program) and 8 preceptors (5 female, 3 male; 35 ± 10 years old, 3 ± 3 years of experience as a preceptor) volunteered for this study.

Main Outcome Measure(s):

After observation of the participants' clinical education experiences, individual in-person interviews were audiorecorded and transcribed verbatim. We used an inductive process of open, axial, and selective coding to identify themes. Trustworthiness was established with member checking, multiple-analyst triangulation, and data source triangulation.

Results:

Three themes emerged from the data. Participants recognize that students spend much of their clinical time interacting with patients, completing administrative tasks, and doing custodial work. Participants noted their awareness of student activities increased after using the active learning assessment instrument. Lastly, participants perceived that bug-in-ear technology improved the efficiency of task completion but not the actual tasks completed.

Conclusions:

Since several factors influence the amount of active learning time spent during students' clinical education, athletic training programs may benefit from looking at their own students' time spent during clinical education. Asking students and preceptors to assess active learning time may help them and clinical education coordinators identify ways to increase active learning and decrease unengaged and managerial time.
Roles of Mentoring for Novice Athletic Training Faculty Members
Authors: Nottingham Sara L. , Mazerolle Stephanie M. , Barrett Jessica L.
Published: February 2018

Context:

Mentorship is a valuable resource for athletic trainers who are transitioning to new roles such as a student, preceptor, or autonomous clinician. While mentorship has been identified as an important component of education, little is known about the role of mentorship during the transition from doctoral student to faculty member during the first several years in academia.

Objective:

Obtain faculty members' perspectives on the role of mentorship as it relates to their experiences as a tenure-track faculty member.

Design:

Qualitative, phenomenological research.

Setting:

Higher education institutions with Commission on Accreditation of Athletic Training Education-accredited programs.

Patients or Other Participants:

Twelve novice faculty members (9 female, 3 male) and 12 experienced faculty members (3 female, 9 male) participated in this study.

Main Outcome Measure(s):

We developed and piloted an interview guide designed to gain participants' perspectives on their experiences with and perceptions of mentorship in relation to their faculty roles and responsibilities. Semistructured telephone interviews were completed with each individual and transcribed verbatim. Data were analyzed using a phenomenological approach, and saturation was obtained. Trustworthiness was established with the use of member checking, multiple-analysts triangulation, and data source triangulation.

Results:

Two themes emerged regarding roles of mentorship: (1) support and guidance and (2) navigating institutional politics and expectations. Mentors supported novice faculty members in their responsibilities of teaching, research, and service, particularly when mentees perceived a weakness in 1 area. Mentors also helped novice faculty members navigate the tenure and promotion process and politics of their institution.

Conclusions:

Mentorship appears to be an important mechanism of support for novice faculty members as they transition to their tenure-track faculty roles. Mentorship appears to be particularly valuable when there is a perceived lack of preparation for 1 aspect of a faculty position. Novice faculty members should seek out mentors within and beyond their institution for support.
Right-handed Hopf algebras and the preLie forest formula
Authors: Menous Frédéric , Patras Frédéric
Published: February 2018

Three equivalent methods allow to compute the antipode of the Hopf algebras of Feynman diagrams in perturbative quantum field theory (QFT): the Dyson–Salam formula, the Bogoliubov formula, and the Zimmermann forest formula. Whereas the first two hold generally for arbitrary connected graded Hopf algebras, the third one requires extra structure properties of the underlying Hopf algebra but has the nice property to reduce drastically the number of terms in the expression of the antipode (it is optimal in that sense).

The present article is concerned with the forest formula: we show that it generalizes to arbitrary right-handed polynomial Hopf algebras. These Hopf algebras are dual to the enveloping algebras of preLie algebras – a structure common to many combinatorial Hopf algebras which is carried in particular by the Hopf algebras of Feynman diagrams.
Low Speed Continuous Slip SAE No. 2 µPVT Procedure
Authors:   Automatic Transmission and Transaxle Committee
Published: February 2018

This SAE document is intended as the definition of a standard test, which may be subject to frequent change to keep pace with experience and technical advances. This should be kept in mind when considering its use.

The SAE No. 2 friction test is used to evaluate the friction characteristics of automatic transmission plate clutches with automotive transmission fluid combinations.

The specific purpose of this document is to define a µPVT test for the evaluation of the variation of wet friction system low speed slip characteristics as a function of speed, temperature, and pressure. This procedure is intended as a suggested method for both suppliers and end users.

The only variables selected by the supplier or user of the friction system are:

Friction material

Fluid

Reaction plates

Oil flow (optional)

These four variables must be clearly identified when reporting the results of this test. If any of the test parameters or system hardware as described in this document are changed, other than the friction material, test fluid, or reaction plates, the data may not be reported as being obtained using this document.

This procedure is intended to evaluate ramped speed friction characteristics, also called sweeps, and can be used to demonstrate capacity changes that occur between the different levels of slip speed, applied pressure, and fluid temperature. The level of coefficient of friction, as well as the trends in torque capacity with speed, can be used to compare candidate materials or fluids.