bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhanced F-Perceptory Approach for Dealing With Geographic Data Imprecision From the Conceptual Modeling to the Fuzzy Geographical Database Building
Authors: Khalfi Besma , De Runz Cyril , Akdag Herman
Published: August 2018

When analyzing spatial issues, it is often that the geographer is confronted with many problems concerning the uncertainty of the available information. These problems may appear on the geometric or semantic quality of objects and as a result, a low precision is considered. So, it is necessary to develop representation and modeling methods that are suited to the imprecise nature of geographic data. This leads proposing recently F-Perceptory to manage fuzzy geographic data modeling. From the model described in Zoghlami, et al, (2011) some limits are relieved. F-Perceptory does not manage fuzzy composite geographic objects. The paper shows proposition to enhance the approach by the managing this type of objects in modeling and its transformation to the UML. On the technical level, the object modeling tools commonly used do not take into account fuzzy data. The authors propose new functional modules integrated under an existing CASE tool.
Forest Fire Information System Using Wireless Sensor Network
Authors: Devadevan V.  , Sankaranarayanan Suresh
Published: August 2018

Forest fire is the most common hazard which is a great threat to the ecosystem. Remote Sensing and GIS are widely used for forest fire detection. Wireless Sensor Network (WSN) is an emerging technology which is used to monitor environmental parameters towards alerting forest department officers for prevention or control. In this research, the authors developed Forest Fire Information System (FFIS) that provides interface to monitor, assess and analyze the forest fire data emanating from WSN which is a part of Intelligent Forest Fire Detection System. The information system also maintains necessary details of forest fire incidents that can be used for analysis and report generation. It also has a Decision Support System (DSS) integrated into it that can be used by forest officials for strategic planning. This has been developed using PHP and MySQL. This paper is an extension of research work carried about Intelligent Forest Fire Detection System using WSN.
Digital Surveying in Cultural Heritage
Authors: Stylianidis Efstratios , Georgopoulos Andreas
Published: August 2018

Cultural Heritage is recognized as a priceless asset of human being, which exposes the humanity's achievements over centuries. The need for documentation and preservation of cultural heritage is well known worldwide. Digital surveying techniques are playing a catalytic role towards recording and documentation of cultural heritage. This chapter describes the methodological and technological aspects of image-based recording and documentation approaches acting as the vehicle for the digital surveying of cultural heritage. The chapter not only describes the different technologies and techniques used but also goes to the extent of clarifying several applied implementation issues. Three different examples and application case studies from a small, a medium and a large-scale cultural heritage objects are provided to demonstrate the developments.
Improving the Efficiency of Image Interpretation Using Ground Truth Terrestrial Photographs
Authors: Gienko Gennady , Govorov Michael
Published: August 2018

Researchers worldwide use remotely sensed imagery in their projects, in both the social and natural sciences. However, users often encounter difficulties working with satellite images and aerial photographs, as image interpretation requires specific experience and skills. The best way to acquire these skills is to go into the field, identify your location in an overhead image, observe the landscape, and find corresponding features in the overhead image. In many cases, personal observations could be substituted by using terrestrial photographs taken from the ground with conventional cameras. This chapter discusses the value of terrestrial photographs as a substitute for field observations, elaborates on issues of data collection, and presents results of experimental estimation of the effectiveness of the use of terrestrial ground truth photographs for interpretation of remotely sensed imagery. The chapter introduces the concept of GeoTruth – a web-based collaborative framework for collection, storing and distribution of ground truth terrestrial photographs and corresponding metadata.
Sugeno Fuzzy-Inference-System-Based Land Cover Classification of Remotely Sensed Images
Authors: Jenicka S.
Published: August 2018

Accuracy of land cover classification in remotely sensed images relies on the features extracted and the classifier used. Texture features are significant in land cover classification. Traditional texture models capture only patterns with discrete boundaries whereas fuzzy patterns need to be classified by assigning due weightage to uncertainty. When remotely sensed image contains noise, the image may have fuzzy patterns characterizing land covers and fuzzy boundaries separating land covers. So a fuzzy texture model is proposed for effective classification of land covers in remotely sensed images and the model uses Sugeno Fuzzy Inference System (FIS). Support Vector Machine (SVM) is used for precise and fast classification of image pixels. Hence it is proposed to use a hybrid of fuzzy texture model and SVM for land cover classification of remotely sensed images. In this chapter, land cover classification of IRS-P6, LISS-IV remotely sensed image is performed using multivariate version of the proposed texture model.
Automatic Estimation of Soil Biochar Quantity via Hyperspectral Imaging
Authors: Tong Lei , Zhou Jun , Bai Shahla Hosseini , Xu Chengyuan , Qian Yuntao , Gao Yongsheng , Xu Zhihong
Published: August 2018

Biochar soil amendment is globally recognized as an emerging approach to mitigate CO2 emissions and increase crop yield. Because the durability and changes of biochar may affect its long term functions, it is important to quantify biochar in soil after application. In this chapter, an automatic soil biochar estimation method is proposed by analysis of hyperspectral images captured by cameras that cover both visible and infrared light wavelengths. The soil image is considered as a mixture of soil and biochar signals, and then hyperspectral unmixing methods are applied to estimate the biochar proportion at each pixel. The final percentage of biochar can be calculated by taking the mean of the proportion of hyperspectral pixels. Three different models of unmixing are described in this chapter. Their experimental results are evaluated by polynomial regression and root mean square errors against the ground truth data collected in the environmental labs. The results show that hyperspectral unmixing is a promising method to measure the percentage of biochar in the soil.
Factors Contributing to the Effectiveness of Online Students and Instructors
Authors: Kilburn Michelle , Henckell Martha , Starrett David
Published: August 2018

Identifying the positive attributes of students and instructors in the online environment will contribute to the understanding of how we can enhance the learning experience for the student and the teaching experience for the instructor. This chapter will assist students and instructors in understanding the differences that may be experienced in the online environment versus the face-to-face environment and provide the opportunity to consider whether online learning and/or teaching is a “good fit” for them. Understanding why students and/or instructors might choose the online environment will also assist administrators in developing successful, quality online programs that enrich the experiences for both students and instructors.
Multimodal Literacy
Authors: Tobin Maryann Tatum
Published: August 2018

Millennial readers are learning to navigate an increasingly robust system of symbols and patterns in order to become literate. This phenomenon, known as multimodal literacy, is providing for new and rich ways of teaching reading to address the complex thinking patterns of young students. However, the rapid pace of technological growth has created a confluence of basic literacy skills and the reading requirements of a multimodal world. Literacy educators must adapt their instruction to this new reality to prepare today's students for the challenges of this century and beyond.
Importance of Information Literacy
Authors: Sanchez-Ruiz Lidia , Blanco Beatriz
Published: August 2018

It is said that we live in an information society. In this scenario, information becomes a key aspect in everybody's professional and personal lives. Thus, a new concept appears: information literacy. Even though information literacy is not always considered a core competency, many organizations require information literacy skills on their job offers. Therefore, every university student should acquire and develop information literacy skills during their undergraduate studies. Taking this into consideration, as a first step, students should be aware of the relevance of information literacy skills. Once they are aware of its importance, they are able to improve and develop it. Thus, the aim of this study is to analyze whether university students are aware of the importance of information literacy. Additionally, the authors analyze whether students' awareness varies after attending an information training course. In order to fulfil this objective, the IL-HUMASS survey is used.
Quality Online Learning in Higher Education
Authors: Wooldridge Deborah G. , Poirier Sandra , Matuga Julia M.
Published: August 2018

Traditional education systems alone, despite the essential role they have played and will continue to play in learning, are simply not capable of serving the world's growing and changing needs. The knowledge explosion, driven by the power of the network to connect people and spread ideas, has changed the very nature of learning. We must innovate and develop new modes of learning, both formal and informal, that meet the demands of the knowledge-driven economy in this information age. This chapter begins by identifying the technological changes that are affecting all societies and how these changes will specifically impact postsecondary education. The topic of course delivery within this chapter is viewed as a cultural issue that permeates processes from the design of an online course to the evaluation of an online course.
The University-Industry Collaboration
Authors: Chedid Marcello Fernandes , Teixeira Leonor
Published: August 2018

The collaboration between academia and industry—university-industry collaboration (UIC)—may occur according to different formats (multiple types) and recently has increased based on the third mission of the universities. This relationship offers advantages to both entities, addressing global challenges to their mutual benefit as well as benefits to society. Nevertheless, this relationship is complex and often appears threatening to both the university and industry through value and goals conflicts. In order to achieve success in this relationship, it is important to understand the three drivers that are part of UIC (i.e., the motivation for collaboration, the channel of interaction and outcome, and benefits of collaboration). Their understanding allows one to mitigate barriers, overcome differences, create an environment of trust and commitment, and consequently, achieve success of the UIC. This chapter aims to address these three main drivers of this relationship based on literature review.
Mobile Game-Based Learning
Authors: DaCosta Boaventura , Seok Soonhwa , Kinsell Carolyn
Published: August 2018

The massive spread of mobile computing is undeniable with the draw of mobile games reaching epic proportions. This popularity, along with the anytime, anywhere, and on-any-device characteristics of mobile computing has ignited mounting interest in the use of mobile games in educational contexts, as illustrated by a growing number of articles on this topic. This chapter offers a review of the research on mobile game-based learning (mGBL), citing mobile games that have been experimented with and/or used to explore learning. Although many of the studies to date have emphasized the location-based capabilities of mobile devices, the emerging research focused on mGBL is promising, showing that learning can take place through the use of these games. Future research, however, should look beyond individual devices and functionality, and place greater importance on pedagogy.
Automatic Emotion Recognition Based on Non-Contact Gaits Information
Authors: Wang Jingying , Li Baobin , Zhu Changye , Li Shun , Zhu Tingshao
Published: August 2018

Automatic emotion recognition was of great value in many applications; however, to fully display the application value of emotion recognition, more portable, non-intrusive, inexpensive technologies need to be developed. Except face expression and voices, human gaits could reflect the walker's emotional state too. By utilizing 59 participants' gaits data with emotion labels, the authors train machine learning models that are able to “sense” individual emotion. Experimental results show these models work very well and prove that gait features are effective in characterizing and recognizing emotions.
The Summers and Winters of Artificial Intelligence
Authors: Gonsalves Tad
Published: August 2018

Artificial intelligence (AI) is a branch of computer science whose aim is to make computers intelligent. These “intelligent” activities include thinking, reasoning, receiving stimuli from the environment and responding to them, solving puzzles, speaking and understanding language, etc. It was John McCarthy who coined the word artificial intelligence at the conference on computers in Dartmouth in 1954, indicating that its goal was to achieve a digital equivalent of human-level intelligence. In the 1970s, AI entered a low-productive period known as the AI winter. During this period, scientific and notably commercial activities in AI dropped dramatically. The victory of IBM's Deep Blue AI program over the reigning world chess champion in 1997 is probably hailed as the biggest achievement of AI. Yet another great AI achievement is the victory of IBM's Watson over the world Jeopardy champions in 2011. This chapter is a brief outline of how, through numerous ups and downs, AI has come to be where it currently is, and where we might expect it to be heading in the next couple of decades.
Affect-Sensitive Computer Systems
Authors: Thompson Nik , McGill Tanya , Murray David
Published: August 2018

Affective computing is the broad domain encompassing all of the hardware, software, and underlying theoretical models underpinning the development of affect sensitive computer systems. Such systems facilitate more intuitive, natural computer interfaces by enabling the communication of the user's emotional state. Despite rapid growth in recent years, affective computing is still an underexplored field, which holds promise to be a valuable direction for future software development. Human-computer interaction has traditionally been dominated by the information processing metaphor, and as a result, interaction between the computer and the user is generally unidirectional and asymmetric. The next generation of computer interfaces aim to address this gap in communication and create interaction environments that support the motivational and affective goals of the user.
Developing Creativity and Learning Design by Information and Communication Technology (ICT) in Developing Contexts
Authors: Zhou Chunfang , Purushothaman Aparna
Published: August 2018

This chapter has two aims: 1) to bridge the link between creativity, learning, information ecology, and community of practice that underpins the theoretical necessity of contextual user-centered approach to learning design by ICT in developing contexts; and 2) to specifically discuss how a human-computer interaction for development (HCI4D) based on learning design can be applied to provide the practical instrument for building creative learning environment in developing contexts. Theoretically, the chapter will build a new framework by using three prominent theories: creativity theories, information ecology, and theory of communities of practice. This chapter also has practical contributions to offer developmental scholars and project managers a vocabulary to address the process and learning issues in both formal and informal learning environments and opening up new ways for understanding creativity, learning, and usages of ICT in a developmental context.
Exploring New Handwriting Parameters for Writer Identification
Authors: Aubin Verónica Inés , Doorn Jorge Horacio
Published: August 2018

The automatic processing of handwriting samples is part of the computational biometric. It applies qualitative and quantitative techniques by means of capturing, visualizing, and analyzing handwriting. The main applications are writer identification and text understanding. Two significantly different situations appear: online and offline data capturing. In the former, the samples are obtained in a dedicated framework, where the writing instrument and the surface have several sensors. In the latter, the unique information available comes from the residues left on paper. This chapter deals with the second situation. Width, grey value, direction, and other parameters of the residual manuscript text are influenced by the psychomotor characteristics of the writer. Some of these personal parameters may be estimated from the observable properties of the written text.
A Trust Case-Based Model Applied to Agents Collaboration
Authors: Boff Felipe , Lorenzi Fabiana
Published: August 2018

This chapter shows an approach for developing a method that uses case-based reasoning (CBR) for calculating trust levels in agents' collaboration. The proposed development foresees all interactions between agents are considered in the updating process of general trust level. These collaborations are also stored in a CBR database. Each new interaction calculates a situational trust level based on similar cases. This trust level will be weighed against the global trust level, creating an indicator based on the requested collaboration without excluding the collaboration history.
Applications of Artificial Neural Networks in Economics and Finance
Authors: Mihaylova Iva
Published: August 2018

Artificial neural networks (ANNs) are a powerful technique for multivariate dependence analysis. Originally inspired by neuroscience, ANNs are becoming an increasingly attractive analytic tool for applications in the area of economics and finance due to the flexible solutions they offer. The purpose of this chapter is to present such important applications with an emphasis on recent research trends. The contributions are grouped as follows: ANNs (1) for prediction, (2) for classification, and (3) for modelling. The chapter concludes with the future trends in the ANNs research in economics and finance.
Social Computing
Authors: Hemmatazad Nolan
Published: August 2018

Broadly speaking, social computing encapsulates the idea of making technologies more aware of, and more in alignment with, the social needs of their users. This allows for the introduction of new modes of communication and collaboration among users, the ability to establish and grow communities of various constitutions, as well as for more dynamic and large-scale content creation, dissemination, and evaluation. This chapter serves the ternary purpose of establishing a broad definition of social computing as it stands today and as it is expected to evolve in the near future, providing an overview of the practical applications of social computing, and examining the present and historic research themes that have made an impression on social computing as an area of academic intrigue. The chapter is intended to be accessible to casual readers, practitioners, and academicians alike, with little technical depth and broad focus throughout, for the purpose of establishing an initial acquaintance with the field.
Leveraging Internet of Things to Revolutionize Waste Management
Authors: Maksimovic Mirjana
Published: August 2018

A continuously growing population and their migration to urban centers consequently leads to waste expansion. The rapidly increasing quantities of waste generated in the cities affect way of human life, environment and planet. Hence, the necessity for smarter, safer, and greener places have never been more urgent. The novel technologies, Internet of Things (IoT) particularly, holds the potential to better manage waste and recycling. The IoT-driven waste management systems positively influence achieving the vision of smart green cities. This article analyzes the role of smart and safe IoT-powered waste management system, highlights its benefits, and possibilities of implementation and evaluation. It is expected that the IoT-based waste management system will deal successfully with an increasing amount of diverse types of waste and through the realization of a smart green city vision will resolve numerous problems related to human health and environmental contamination.
Assessing the Hydrological Effect of Climate Change on Water Balance of a River Basin in Northern Greece
Authors: Koukouli Panagiota G. , Georgiou Pantazis E. , Karpouzos Dimitrios K.
Published: August 2018

In this work, the impacts of climate change on the water resources of the Olynthios River Basin in Northern Greece, were assessed. For this purpose, the climate change scenarios SRES and RCPs were used (SRES A1B, Α2 and RCP4.5, 8.5) - which were taken from two climate models, CGCM3.1/T63 and CanESM2, respectively - for two time periods (2031-2050 and 2081-2100) and for the baseline period (1981-2000). The downscaling was performed using the weather generator ClimGen. The monthly water balance of the Olynthios River Basin was estimated with the use of a conceptual water balance model. Results showed that the annual runoff of the river basin of Olynthios will decrease in response to climate change under all scenarios for both time periods. The results highlight the necessity for adequate adaptation strategies which could improve agricultural water management and reduce the impacts of climate change on agriculture.
Applying Multiple Linear Regression and Neural Network to Predict Business Performance Using the Reliability of Accounting Information System
Authors: Al-Dmour Ahmed H. , Al-Dmour Rand H.
Published: August 2018

This article aims to predict business performance using multiple linear regression and neural network. It compares the accuracy power of ANN and multiple linear regression (MLR) using the reliability of accounting information system as independent variables, and business performance as a dependent variable. It is based on primary data collected through a structured questionnaire from 162 out 202 of public listed companies in financial service sector in Jordan. The data were analysed using ANN and MLR. Testing results of the two methods ANN and MLR confirmed that the business performance indicators (financial, non-financial and combined) were significantly could be predicted by the reliability of AIS and they also revealed that in terms of predictive accuracy test, the ANN has a higher accuracy than regression analysis.
Audit Committee Effectiveness and Accounting Conservatism a Test of Lagged Effect
Authors: Khan Saif Ur-Rehman , Khan Faisal , Elshareif Elgilani
Published: August 2018

This article examines the effect of audit committee effectiveness on two measures of accounting conservatism. In addition, this article also investigates the interaction effect of four endogenous variables (i.e. firm's operating risks, leverage, managerial influence, firm's size) and three exogenous variables on relationship between audit committee effectiveness and two measures of accounting conservatism. A total of 543 sample firms are selected from the Bursa Malaysia for the period from 2004 to 2013. In addition, some information relating to audit committee and auditor quality are collected from firms' annual reports. For data analysis, panel data methodology is employed, and multiple regression analysis technique is used to test the developed hypotheses of this study. Results show that interaction effect of firm's operating risks, managerial influence, external auditor quality and capital market uncertainty found to be significant with two-year-lagged effect on both measures of conservatism. Whereas, the interaction effect of firm's leverage, firm's size and product market completion are found to be insignificant. The findings of this study contribute to the signaling theory, agency theory, reputation theory and accounting conservatism literature with lagged effect in emerging economies settings.
Epistemology of Relationship Marketing Strategies
Authors: Saraswati Arvind Kumar , Syed Asif Ali , Singh Shamsher
Published: August 2018

Relationship marketing strategies are designed to building customer loyalty by providing value to all the parties involved in the relational exchanges. The chosen field for this article was the online travel industry. The Indian online travel industry growing at a steady rate. However, the success of the online travel industry is not guaranteed despite of its significant growth potential in India. Rather, it is contingent upon understanding complex consumer shopping behavior. This article is aimed at exploring the epistemology of relationship marketing strategies, and to assess the extent to which these strategies would benefit online travel industry in retaining their customers. This article is exploratory in nature and is built upon the thorough review of past literature documented in earlier research papers, media articles, news items, and website information. The outcome of the article reveals various strategies that the players of online travel industry may employ to develop long term relationships with their customer.
Customer Empowerment and Satisfaction through the Consultative Selling Process in the Retail Industry
Authors: Castillo Javier , George Babu
Published: August 2018

This article draws insight from the literature to propose a model interlinking key stages in the consultative selling process, customer engagement, and customer satisfaction. It is argued that customer journey should be designed as a process of empowering customers to make the right choices and the role of businesses should be to design and deliver products that meet with needs realized in the consultative process between the business and the customer. Even though this discussion is situated within the context of the retail industry, the findings could possibly be applied in various other customer relationship contexts as well.
Information Technology Impact on Productivity
Authors: Appiahene Peter , Ussiph Najim , Missah Yaw M
Published: August 2018

The notion that an increase in information technology investments will result in a positive impact on productivity has been deliberated comprehensively at various levels. Initial studies have established that, there was no link between investment in IT and productivity while others suggested otherwise. Even though there is a growing number of an academic studies on this topic, most of them has been centered on America, Asia and Europe. This current article reviews and analyzes literatures on the topic and presents a quantitative analysis of the literatures on continental bases. The study uses PRISMA Flow diagram and examined 141 studies that have been published between 1990 and 2017. The results suggested that Europe led with 36.88%, whilst Africa has not contributed much to IT and productivity literature with just 8.51%. The study therefore concluded that more studies on the topic should be done using data from Africa.
Promoting Situation Awareness
Authors: Backholm Klas , Högväg Joachim , Lindholm Jenny , Knutsen Jørn , Westvang Even
Published: August 2018

Crisis communicators and journalists need stable structures to handle social media content in emergencies, but struggle with information overload. The usability of a tool intended to support information gathering was investigated by conducting two usability tests (low- and high-fidelity prototypes) with journalists. The aims were to investigate how well the design reflected users' general mental models of emergency work, and how it responded to the specific requirements set by work in high-stress surroundings. Tests were conducted in a laboratory. Participants understood the main prototype concepts, but struggled with time-consuming tasks, for instance, those related to saving content or evaluating information quality. To provide good situation awareness - and to fit in with user expectations - a system should gather information from several social media outlets and allow for varying possible user modes. However, system designers need to carefully balance between including necessary features and avoiding tasks that require complex manual actions.
Automatic Selector Between Cardiogenic Oscillation and Airway Secretion in Mechanical Ventilation Flow Signals Using Artificial Immune System
Authors: Sobral dos Santos Samuel , Wanderley Hatus Vianna , Neto Fernando Buarque de Lima
Published: August 2018

The accumulation of secretions in the airways of ventilator-dependent patients is a common problem, and if not detected and treated in due time, it greatly increases the risk of infections and asynchrony. Unfortunately, cardiogenic oscillation modifies the flow signal shape that can confuse clinical staff and modern lung ventilators. In this article, the authors use an artificial immune system algorithm in a pre-processed flow signal. The authors' approach was able to automatically detect the presence or absence of airway secretions, even if the sample contains the influence of cardiogenic oscillation. The training and validation of the algorithm was carried out using a database containing flow signals of 457 respiratory cycles, obtained from three patients in different ventilation modes. The algorithm trained with 60% of the base cycles, was able to achieve specificity and sensitivity above 0.96 in the classification of the remaining cycles of the base.
Automated Quantification of Eye Blink Rate Using VIOLA–JONES Algorithm
Authors: Hamdan Mohammad , Shehadeh Hisham A.
Published: August 2018

In this article, we have proposed a novel tool that helps to objectively quantify eye blink rate. Using the proposed algorithm, a threshold for normal blink rate can be set to test those who have to reduce eye blink rate and are prone to ocular surface dryness. The statistical results show excellent agreement between software-detected number of blinks and visually measured with 90% accuracy for the participants. In addition, the comparison between our tool and other approaches of eye blink monitoring shows that our tool is competitive with only 5% wasted blinks.
Generic Access Control Model and Semantic Mapping Between Heterogeneous Policies
Authors: Haguouche Samira , Jarir Zahi
Published: August 2018

This article aims to ensure a dynamic set up of access control policies across collaborating organizations where these organizations adopt heterogeneous access control models. To attain this objective, this contribution started with a survey on existing access control models, and their specificities on collaboration. Based on this survey, it remains that the topic on access control collaboration still open despite the efforts made. Therefore, in this article a generic representation of access control concepts is proposed. This generic representation considers the process of semantic mapping between policies of heterogeneous access control systems. In this fact an ontology-based semantic mapping is proposed. This mapping has the advantage to optimize the administrators' involvement by combining linguistic-based and upper-ontology based matching techniques with a user-based constraint strategy for ontology matching.
Entropy Based Identification of Fake Profiles in Social Network
Authors: Sarna Geetika , Bhatia M.P.S.
Published: August 2018

Cyberbullying is a felonious act carried out against the victim by sending harassing/ embarrassing/ abusing information online. Normally offenders create fake profiles in order to hide their identity for unscrupulous activities. Assuming a fake identity is very harmful as the real picture of the offender is not visible, and also it can become difficult to entrap them. Sometimes, some trustworthy friends can also take advantage of the fake identity in order to harm the victim. Culprits can reveal victim's personal information like financial details, personal history, family, etc., and along with it, he can harass, threaten or blackmail the victim using fake profiles and permeates that information on the social network. So, it is necessary to resolve this issue. In this article, the authors used the concept of entropy and cross entropy to identify fake profiles as entropy works on the degree of uncertainty. Also, this article shows the comparison of proposed method with the existing classifiers.
Understanding the Determinants of Big Data Adoption in India
Authors: Gangwar Hemlata
Published: August 2018

This article sought to identify the drivers of Big Data adoption within the manufacturing and services sectors in India. A questionnaire-based survey was used to collect data from manufacturing and service sector organizations in India. The data was analyzed using exploratory and confirmatory factor analyses. Relevant hypotheses were then derived and tested by SEM analysis. The findings revealed that the following factors are important for both sectors: relative advantage, compatibility, complexity, organizational size, top management support, competitive pressure, vendor support, data management and data privacy. Statistically significant differences between the service and the manufacturing sectors were found. In other words, the relative importance of the factors for Big Data adoption differs between the sectors. The only exception was complexity, which was found to be insignificant in regard to the manufacturing sector. The factors identified can be used to facilitate Big Data adoption outcomes in organizations.
Contribuições de Paul Feyerabend para a Filosofia da Tecnologia: democratização e governança da ciência e tecnologia
Authors: Abrahão Luiz
Published: August 2018

O texto reflete sobre as contribuições de Paul Feyerabend para a filosofia da tecnologia, com ênfase na discussão sobre democratização e governança da ciência e tecnologia. Inicialmente, apresentamos aspectos centrais da filosofia política de Feyerabend, especialmente a crítica do autor à hegemonia dos especialistas. Em seguida, recuperamos debates contemporâneos sobre a autoridade científica que dialogam com a filosofia de Feyerabend. Concluímos que o valor da filosofia pluralista de Feyerabend para a filosofia da tecnologia não se restringe à crítica da superioridade teórica da ciência.
Effect of Heat Treatments on 302 Austenitic Stainless Steel Spot Weld
Authors: Al-Mukhtar A.M. , Al-Jumaili Shaymaa Abdul Khader , Al-Jlehawy Ali Hussein Fahem
Published: August 2018

The shear strength of 302 austenitic stainless steel spot welds has been studied. Thewelding current in resistance spot welding process (RSW) plays a significant role. However,this item's effect is well known and extensively studied in the previous literature. This work aims toshow the heat treatment’s effect on different joints that welded at various current. The experimentalresults show that the tensile shear strength is increased with increasing the current. Annealingtreatment improves the tensile shear strength due to the reformation of the grain size and removesthe residual stresses. Grain refinement is an effective technique for improving the strength.Therefore, the tensile shear strength is increased by annealing treatment temperature up to 750 °C.However, at 850°C, the tensile shear strength is dropped down.
Porcine Reproductive and Respiratory Syndrome Virus Nonstructural Protein 4 Cleaves Porcine DCP1a To Attenuate Its Antiviral Activity
Authors: Tao Ran , Fang Liurong , Bai Dongcheng , Ke Wenting , Zhou Yanrong , Wang Dang , Xiao Shaobo
Published: August 2018

As one of the most significant etiological agents in pigs, porcine reproductive and respiratory syndrome virus (PRRSV) has adversely impacted the global swine industry since it was discovered in the 1980s. The mRNA-decapping enzyme 1a (DCP1a), a regulatory factor involved in removing the 5′-methylguanosine cap from eukaryotic mRNA, has recently been identified as an IFN-stimulated gene. However, the role of DCP1a in PRRSV infection is not well understood. In this study, overexpression and knockdown of porcine DCP1a (pDCP1a) showed that pDCP1a affected PRRSV infection. Interestingly, we found that PRRSV infection significantly downregulated pDCP1a expression at the protein level by cleaving pDCP1a. Furthermore, we demonstrated that PRRSV nonstructural protein 4 (nsp4), a 3C-like proteinase, is responsible for pDCP1a cleavage, and the cleaved site is at glutamic acid 238 (E238) of pDCP1a. The mutant pDCP1a-E238A, which cannot be cleaved by nsp4, showed higher anti-PRRSV activity, and the antiviral effects of two cleavage products (pDCP1a1–238 and pDCP1a239–580) were significantly decreased compared with wild type pDCP1a. Unexpectedly, PRRSV infection or overexpression of nsp4 did not cleave monkey DCP1a, and monkey DCP1a showed a higher anti-PRRSV activity than pDCP1a. Taken together, this study reveals a new strategy evolved by PRRSV to dampen the host defense, complementing the known PRRSV-mediated immune evasion mechanisms.
The Atypical Chemokine Receptor Ackr2 Constrains NK Cell Migratory Activity and Promotes Metastasis
Authors: Hansell Christopher A. H. , Fraser Alasdair R. , Hayes Alan J. , Pingen Marieke , Burt Claire L. , Lee Kit Ming , Medina-Ruiz Laura , Brownlie Demi , Macleod Megan K. L. , Burgoyne Paul , Wilson Gillian J. , Nibbs Robert J. B. , Graham Gerard J.
Published: August 2018

Chemokines have been shown to be essential players in a range of cancer contexts. In this study, we demonstrate that mice deficient in the atypical chemokine receptor Ackr2 display impaired development of metastasis in vivo in both cell line and spontaneous models. Further analysis reveals that this relates to increased expression of the chemokine receptor CCR2, specifically by KLRG1+ NK cells from the Ackr2−/− mice. This leads to increased recruitment of KLRG1+ NK cells to CCL2-expressing tumors and enhanced tumor killing. Together, these data indicate that Ackr2 limits the expression of CCR2 on NK cells and restricts their tumoricidal activity. Our data have important implications for our understanding of the roles for chemokines in the metastatic process and highlight Ackr2 and CCR2 as potentially manipulable therapeutic targets in metastasis.
The perceived fairness of turnover tax
Authors: Gluckman Adam , Turner Magda
Published: August 2018

The South Africa Turnover Tax system, implemented on 01 March 2009 to simplify tax for microbusinesses and to improve tax compliance had an insignificant number of registrations and research indicated that a possible reason is the fairness of the tax. The aim of this study is to explore the perceived fairness of the Turnover Tax system. By way of a literature review, criticisms and provisions of the Sixth Schedule to the Income Tax Act No. 58 of 1962 were identified and used as statements on a survey questionnaire. Using the principles of a fair tax system as advanced by Adam Smith a correspondence survey which included two open-ended questions was issued to participants with knowledge of Turnover Tax to establish whether the statements corresponded to any of Adam Smith’s Maxims. The results reveal that the Turnover Tax system is not perceived as completely fair and encourage Government to relook at the legislation with the intend to simplify it further, to removing ambiguity and add detailed lists of excluded services. Education and training of taxpayers is important. A repetition of this study on taxpayers registered on the Turnover Tax system will make further contribution and add to the insight into the fairness of the Turnover Tax system provided by this article.
Innovation, learning and performance in a resource-rich emerging economy
Authors: Scott Gregory J. , Chaston Ian
Published: August 2018

Background: This article compares the performance of firms in resource-rich sectors of the Peruvian economy with that of businesses operating in service sectors. Objectives: In so doing, the research seeks to examine whether innovation is managed differently by firms operating in different sectors of a developing-country economy and whether the performance of firms in an emerging economy may be influenced by innovation and learning practices at the sectoral level. Method: Data were acquired through a survey of overwhelmingly middle managers working in Peru. Results: According to the survey findings, the performance of firms in the resource-rich sectors appeared to be uninfluenced by innovation or involvement in organisational learning. In contrast, firms in the service sectors not only exhibited an innovation orientation and involvement in learning but also reported higher sales growth. Conclusion: The study concludes that firms operating in the resource-rich sectors of Peru’s economy do not appear to benefit from engaging in innovation or learning at this point in time, whereas such activities are advantageous for service sector businesses. Therefore, the relationship between innovation, learning and performance may be influenced not just by the type of economy but also by the sector in which the firms are operating.
Разделение переменных в анизотропной модели Шотки-Фрама
Authors: Skrypnik Taras Vladimirovich
Published: August 2018

Сконструированы разделенные переменные для полностью анизотропной\linebreak классической модели Шотки-Фрама на произвольной коприсоединенной орбите группы $SO(4)$. В явном виде найдены формулы реконструкции, выражающие динамические переменные через координаты разделения, и записаны уравнения движения в форме типа Абеля.
Direct Injection Gasoline Fuel Injector Characterization
Authors:   Gasoline Fuel Injection Standards Committee
Published: August 2018

This SAE Recommended Practice promotes uniformity in the evaluation and qualification tests conducted on GDI fuel injectors used in gasoline engine applications, where fuel pressures are typically well above 1 MPa. The document scope is limited to electrically-actuated fuel injection devices used in automotive GDI systems and is primarily restricted to bench tests.
Simulation of Quarter-Car Model with Magnetorheological Dampers for Ride Quality Improvement
Authors: Sharma Sunil Kumar , Sharma Rakesh Chandmal
Published: August 2018

A semi-active suspension system using Magnetorheological (MR) damper overcomes all the inherent limits of passive and active suspension systems and combines the advantages of both. This paper gives a concise introduction to the suspension system of a passenger vehicle which is presented along with the analysis of semi-active suspension system using MR fluid dampers based on Bingham model. MR dampers are filled with MR fluids whose properties can be controlled by applying voltage signal. To further prove the statement, a quarter car model with two degrees of freedom has been used for modeling the suspension system the sprung mass acceleration of passive suspension system has been compared with the semi-active suspension system using the Bingham model for MRF damper. Simulink/MATLAB is used to carry out the simulation. The results drawn show that the semi-active suspension system performed better than the passive suspension system in terms of vehicle stability.
Microstructural and Mechanical Investigations of Mg-based Alloys
Authors: Singla Amit , Sharma Neeraj , Kumar Sushil
Published: August 2018

In the present work, an attempt has been made to study the microstructural and mechanical behaviour of Mg-alloy prepared by powder metallurgy process. Highly pure Mg powder is used for the fabrication of Mg-alloy at different additive percentages. The investigation of constituent phases was successfully completed for the Mg-alloy using standard X-ray diffractometers. Scanning electron microscopy was used for the morphological studies. Tensile strength and percentage elongation of Mg-alloys were also evaluated at room temperature. The minimum and maximum ultimate stress varies from 67 to 108MPa. The percentage elongation also increased 1.03 to 1.57%.
Television and Totalitarianism in Czechoslovakia From the First Democratic Republic to the Fall of Communism
Authors: Štoll Martin
Published: August 2018

The story of Czechoslovak television is in many respects typical of the cultural and political developments in Central Europe, behind the Iron Curtain. Martin Štoll, with unprecedented access to the Military Historical Archives in Prague, provides contextual insights into the issues of introducing television in the whole Socialist Bloc (save China, Mongolia and Cuba), from the introduction of television broadcasting in Czechoslovakia in 1921 through to the 1968 occupation and the Velvet revolution in 1989 – encapsulating an important point in media history within two totalitarian states.

Television and Totalitarianism in Czechoslovakia examines the variability of political interests as reflected on television in interwar Czechoslovakia, including Nazi research on television technology in the Czech borderlands (Sudetenland), the quarrel over the outcomes of this research as war booty with the Red Army, the beginning of the Czechoslovak technological journey, and, finally, the institutionalized foundation of Czechoslovak television, including the first years of its broadcasting as a manifestation of Communist propaganda.
Remote sensing of Trichodesmium spp. mats in the western tropical South Pacific
Authors: Rousset Guillaume , De Boissieu Florian , Menkes Christophe E. , Lefèvre Jérôme , Frouin Robert , Rodier Martine , Ridoux Vincent , Laran Sophie , Bonnet Sophie , Dupouy Cécile
Published: August 2018

Abstract. Trichodesmium is the major nitrogen-fixing species in the western
tropical South Pacific (WTSP) region, a hot spot of diazotrophy. Due to the
paucity of in situ observations, remote-sensing methods for detecting
Trichodesmium presence on a large scale have been investigated to
assess the regional-to-global impact of this organism on primary production
and carbon cycling. A number of algorithms have been developed to identify
Trichodesmium surface blooms from space, but determining with
confidence their accuracy has been difficult, chiefly because of the scarcity
of sea-truth information at the time of satellite overpass. Here, we use a series
of new cruises as well as airborne surveys over the WTSP to evaluate their
ability to detect Trichodesmium surface blooms in the satellite
imagery. The evaluation, performed on MODIS data at 250 m and 1 km resolution
acquired over the region, shows limitations due to spatial resolution, clouds,
and atmospheric correction. A new satellite-based algorithm is designed to
alleviate some of these limitations, by exploiting optimally spectral
features in the atmospherically corrected reflectance at 531, 645, 678, 748,
and 869 nm. This algorithm outperforms former ones near clouds, limiting
false positive detection and allowing regional-scale automation. Compared
with observations, 80 % of the detected mats are within a 2 km range,
demonstrating the good statistical skill of the new algorithm. Application to
MODIS imagery acquired during the February-March 2015 OUTPACE campaign
reveals the presence of surface blooms northwest and east of New Caledonia
and near 20∘ S–172∘ W in qualitative agreement with measured nitrogen
fixation rates. Improving Trichodesmium detection requires measuring
ocean color at higher spectral and spatial (<250 m) resolution than MODIS,
taking into account environment properties (e.g., wind, sea surface
temperature), fluorescence, and spatial structure of filaments, and a better
understanding of Trichodesmium dynamics, including aggregation
processes to generate surface mats. Such sub-mesoscale aggregation processes
for Trichodesmium are yet to be understood.