bluuebunny/crossref_metadata_2025 huggingface dataset:
Electron and Proton Heating in Transrelativistic Guide Field Reconnection
Authors: Rowan Michael E. , Sironi Lorenzo , Narayan Ramesh
Published: February 2019

The plasma in low-luminosity accretion flows, such as the one around the black hole at the center of M87 or Sgr A* at our Galactic Center, is expected to be collisioness and of two temperatures, with protons hotter than electrons. Here, particle heating is expected to be controlled by magnetic reconnection in the transrelativistic regime

, where the magnetization

is the ratio of magnetic energy density to plasma enthalpy density. Using large-scale 2D particle-in-cell simulations, we explore for a fiducial

how the dissipated magnetic energy is partitioned between electrons and protons as a function of

(the ratio of proton thermal pressure to magnetic pressure) and of the strength of a guide field

perpendicular to the reversing field B
0. At low

, we find that the fraction of initial magnetic energy per particle converted into electron irreversible heat is nearly independent of

, whereas protons are heated much less with increasing

. As a result, for large

, electrons receive the overwhelming majority of irreversible particle heating (∼93% for

). This is significantly different than the antiparallel case

, in which irreversible electron heating accounts for only ∼18% of the total particle heating (Rowan et al. 2017). At

, when both species start already relativistically hot (for our fiducial

), electrons and protons each receive ∼50% of the irreversible particle heating, regardless of the guide field strength. Our results provide important insights into the plasma physics of electron and proton heating in hot accretion flows around supermassive black holes.
Origin of Radio-quiet Coronal Mass Ejections in Flare Stars
Authors: Mullan D. J. , Paudel R. R.
Published: February 2019

Type II radio bursts are observed in the Sun in association with many coronal mass ejections (CMEs). In view of this association, there has been an expectation that, by scaling from solar flares to the flares that are observed on M dwarfs, radio emission analogous to solar type II bursts should be detectable in association with M dwarf flares. However, several surveys have revealed that this expectation does not seem to be fulfilled. Here we hypothesize that the presence of larger global field strengths in low-mass stars, suggested by recent magnetoconvective modeling, gives rise to such large Alfvén speeds in the corona that it becomes difficult to satisfy the conditions for the generation of type II radio bursts. As a result, CMEs propagating in the corona/wind of flare stars are expected to be “radio-quiet” as regards type II bursts. In view of this, we suggest that, in the context of type II bursts, scaling from solar to stellar flares is of limited effectiveness.
Identifying the 3FHL Catalog. III. Results of the CTIO-COSMOS Optical Spectroscopy Campaign
Authors: Desai A. , Marchesi S. , Rajagopal M. , Ajello M.
Published: February 2019

Active galactic nuclei (AGNs) with their relativistic jets pointed toward the observer form a subclass of luminous γ-ray sources commonly known as blazars. The study of blazars is essential to improve our understanding of the AGNs emission mechanisms and evolution, as well as to map the extragalactic background light. To do so, however, one needs to classify and measure a redshift for a large sample of these sources correctly. The Third Fermi-LAT Catalog of High-Energy Sources (3FHL) contains ≈1160 blazars reported at energies greater than 10 GeV. However, ∼25% of these sources are unclassified and ∼50% lack redshift information. To increase the spectral completeness of the 3FHL catalog, we are working on an optical spectroscopic follow-up campaign using 4 m and 8 m telescopes. In this paper, we present the results of the second part of this campaign, where we observed 23 blazars using the 4 m telescope at Cerro Tololo Interamerican Observatory in Chile. We report that all the 23 sources are classified as BL Lacs, a confirmed redshift measurement for three sources, a redshift lower limit for two sources, and a tentative redshift measurement for three sources.
Strongly Bipolar Inner Ejecta of the Normal Type IIP Supernova ASASSN-16at
Authors: Bose Subhash , Dong Subo , Elias-Rosa N. , Shappee B. J. , Bersier David , Benetti Stefano , Stritzinger M. D. , Grupe D. , Kochanek C. S. , Prieto J. L. , Chen Ping , Kuncarayakti H. , Mattila Seppo , Morales-Garoffolo Antonia , Morrell Nidia , Onori F. , Reynolds Thomas M , Siviero A. , Somero Auni , Stanek K. Z. , Terreran Giacomo , Thompson Todd A. , Tomasella L. , Ashall C. , Gall Christa , Gromadzki M. , Holoien T. W.-S.
Published: February 2019

We report distinctly double-peaked Hα and Hβ emission lines in the late-time, nebular-phase spectra (≳200 days) of the otherwise normal at early phases (≲100 days) type IIP supernova ASASSN-16at (SN 2016X). Such distinctly double-peaked nebular Balmer lines have never been observed for a type II SN. The nebular-phase Balmer emission is driven by the radioactive 56Co decay, so the observed line profile bifurcation suggests a strong bipolarity in the 56Ni distribution or in the line-forming region of the inner ejecta. The strongly bifurcated blueshifted and redshifted peaks are separated by ∼3 × 103 km s−1 and are roughly symmetrically positioned with respect to the host-galaxy rest frame, implying that the inner ejecta are composed of two almost-detached blobs. The red peak progressively weakens relative to the blue peak, and disappears in the 740 days spectrum. One possible reason for the line-ratio evolution is increasing differential extinction from continuous formation of dust within the envelope, which is also supported by the near-infrared flux excess that develops after ∼100 days.
Cytological markers used for identification and transfer of Aegilops spp. chromatin carrying valuable genes into cultivated forms of Triticum
Authors: Kwiatek Michał T. , Kurasiak-Popowska Danuta , Mikołajczyk Sylwia , Niemann Janetta , Tomkowiak Agnieszka , Weigt Dorota , Nawracała Jerzy
Published: February 2019

There are many reports describing chromosome structure, organization and evolution within goatgrasses (Aegilopsspp.). Chromosome banding and fluorescencein situhybridization techniques are main methods used to identifyAegilopsLinnaeus, 1753 chromosomes. These data have essential value considering the close genetic and genomic relationship of goatgrasses with wheat (TriticumaestivumLinnaeus, 1753) and triticale (×TriticosecaleWittmack, 1899). A key question is whether those protocols are useful and effective for trackingAegilopschromosomes or chromosome segments in genetic background of cultivated cereals. This article is a review of scientific reports describing chromosome identification methods, which were applied for development of prebreeding plant material and for transfer of desirable traits intoTriticumLinnaeus, 1753 cultivated species. Moreover, this paper is a resume of the most efficient cytomolecular markers, which can be used to follow the introgression ofAegilopschromatin during the breeding process.
Sample size for inspection intended to manage risk within mixed consignments
Authors: Lane Stephen E. , Cannon Rob M. , Arthur Anthony D. , Robinson Andrew P.
Published: February 2019

The identification of a lot, and the size of the random sample taken for plant products, is justified by appeal to International Standards for Phytosanitary Measures No. 31, “Methodologies for Sampling of Consignments”. ISPM 31 notes that “A lot to be sampled should be a number of units of a single commodity identifiable by its homogeneity [...]” and “Treating multiple commodities as a single lot for convenience may mean that statistical inferences cannot be drawn from the results of the sampling.”

However, consignments are frequently heterogeneous, either because the same commodities have multiple sources or because there are several different commodities. The ISPM 31 prescription creates a substantial burden on border inspection because it suggests that heterogeneous populations must be split into homogeneous sub-populations from which separate samples of nominal size must be taken.

We demonstrate that if consignments with known heterogeneity are treated as stratified populations and the random sample of units is allocated proportionally based on the number of units in each stratum, then the nominal sensitivity at the consignment level is achieved if our concern is the level of contamination in the entire consignment taken as a whole. We argue that unknown heterogeneity is no impediment to appropriate statistical inference. We conclude that the international standard is unnecessarily restrictive.
Solanum medusae (Solanaceae), a new wolf-fruit from Brazil, and a key to the extra-Amazonian Brazilian Androceras/Crinitum Clade species
Authors: Gouvêa Yuri Fernandes , Stehmann João Renato , Knapp Sandra
Published: February 2019

Solanummedusaesp. nov. is described from the Cerrado biome in the Serra da Canastra region, southwestern Minas Gerais State, Brazil. The new species is morphologically similar to the common S.lycocarpum A.St.-Hil. (known as lobeira or wolf-fruit), but differs from it in habit and pubescence characters. We here describe this new taxon and discuss its morphology, some aspects of its ecology, affinities and distribution. Full specimen citations are provided, as well as illustrations, distribution map and a preliminary conservation assessment of the species. A key to all of the known extra-Amazonian Brazilian species of the Androceras/Crinitum clade is also provided to aid in their identification.
Innovative Applications Mode of Network Learning Space in Exercise Physiology Based on Ubiquitous Learning
Authors: Kong Jie
Published: February 2019

With continuous development of internet technology, the concept of ubiquitous learning and network learning space have received more and more attention from scholars, and gradually become the research focuses. College classroom has turned to network teaching from traditional teaching. In this study, literature review and case study were combined with ubiquitous learning and network learning space construction to systematically discuss classification and concept models of network learning space under the perspective of ubiquitous learning. Meanwhile, four models based on network learning space were proposed, and flipped classroom network teaching model was applied in the course of Exercise Physiology. The study showed that, the model has the good teaching effect in course teaching. It not just improves students’ interest, but also lays a foundation for popularizing the teaching mode.
A Distributed Distribution and Scheduling Algorithm of Educational Resources Based on Vector Space Model
Authors: Zan Chen
Published: February 2019

To explore the distributed dispatching and scheduling algorithm of educational resources, based on the vector space model, the user and resource description model is built. In addition, the user interest representation method based on the background and tense vector space model (BTVSM) is proposed, and the distributed architecture based on the scheduling server is used to provide the personalized distribution service to the resource users. At the same time, the task scheduling model and algorithm are analyzed. The task scheduling optimization based on ant colony algorithm is mainly used in the scheduling server, and the simulation experiment is designed to verify the effectiveness of distributed dispatching and task scheduling algorithm for educational resources. The experimental results prove the validity of the application of distributed dispatching and scheduling algorithm based on VSM in specific systems, and it can effectively solve the allocation problem between the resource user group and the distributed dispatching center.
Technological Competences: A Systematic Review of the Literature in 22 Years of Study
Authors: Candolfi Arballo Norma , Chan Nuñez Maria Elena , Rodriguez Tapia Bernabé
Published: February 2019

In this Systematic Review of the Literature (SRL) the term “technological competence” is analyzed. The analysis is conducted within the areas of knowledge in which the term has been studied, considering the definitions that have been associated to the term, the approaches proposed by the authors that make use of the term, the transformation of the concept throughout the time, and the boundaries of application with other similar terms, such as technological capability and technological skill. A total of 140 publications focused on technological competences are analyzed. The publications correspond to a time span ranging from 1994 to 2016, and include research articles from recognized databases and, to a lesser extent, gray literature articles. Finally, the term technological competence applied in the productive sector is redefined such as it allows focusing on projects for technological absorption or training in industry.
Measuring Students Satisfaction in Using Learning Management System
Authors: Ohliati Jenny , Abbas Bahtiar Saleh
Published: February 2019

The purpose of this study to determine what are the influenced factors for student satisfaction on learning management system at a private university that operates online learning system. The research was conducted to find out whether there is influence of information quality, system quality, service quality, perceived usefulness, perceived ease of use, and communication quality to student satisfaction toward learning management system. This study took a sample of 100 student respondents at the university. The used analytical method to test the effect is partial least square. The results show that information quality, service quality, and perceived ease of use have a significant effect on student satisfaction. Service quality is the most dominant factor that affects the satisfaction of students to learning management system.
Multimedia-Based Teaching Platform for English Listening in Universities
Authors: Zhao Xin , Wang Yan , Liu Yanli , Xu Yunan , Meng Yuanning , Guo Lan
Published: February 2019

Abstract—This paper aims to optimize the application of multimedia tech-nologies in the teaching of English listening. For this purpose, the author car-ried out a comprehensive analysis on the theoretical bases, principles and de-sign of multimedia-based English teaching, and designed a multimedia-based teaching platform for English listening in universities. Specifically, a question-naire survey was conducted to qualitatively measure the demand of listening teaching, clarify the current situation of the teaching of English listening, and improve the acceptance of multimedia-based technology. Moreover, the effect of the proposed platform was verified through a teaching experiment. The re-search findings shed new light on the understanding and application of multi-media-based teaching of English listening.
Development of Metal Polishing Dust Monitoring System using the Internet of Things and Cloud Server
Authors: Fan Zhiyao , Pan Tianhong , Ma Li
Published: February 2019

In order to increase the management efficiency and decrease the maintenance costs in the traditional dust monitoring system, a novel real-time remote monitoring system using the Internet of Things and cloud server is proposed in this paper. The system includes several sensor nodes, a sink node and Cloud Server. The high-precision dust probe, temperature and humidity sensors, water flow sensors and hydrogen transmitters are integrated together into a sensor node to access the metal polished environmental information. Then, the collected information is transmitted to sink-node using the 2.4G wireless network. The sink-node uploads data to the Cloud Server through the 4G network and TCP Socket. Based on the Browser/Server (B/S) model, a remote monitoring system is developed by using Tencent Cloud Server, C# language, and SQL database. As a result, the on-site metal polishing environmental information is obtained via the App and Web page.
Implementing Teachers’ Training Technologies at a Federal University: E-portfolio, Digital Laboratory, PROLog Module System
Authors: Smolyaninova Olga , Bezyzvestnykh Ekaterina
Published: February 2019

Students' training quality directly depends on the modern digital environment resources in the federal university. Rich digital environment of the university provides effective learning and allows students to use innovative learning technologies (e-portfolio, digital laboratories, MOOC, etc.) in professional activities for projecting and realization of individual educational paths. E-learning, distant learning technologies implementation and other digital environment resources for potential teachers’ training at the federal university make the learning process more effective. The article describes the practice at Institute of Education, Psychology and Sociology of Siberian Federal University in creating modern digital environment for teachers’ training by the means of e-portfolio technologies, digital laboratory, PROLog module system of experiments, learning management system (LMS) Moodle.
Les adolescents face aux violences numériques
Authors: Jehel Sophie
Published: February 2019

La circulation des images violentes est favorisée par les stratégies des plateformes numériques visant l’ « addiction » à leurs dispositifs et la circulation des affects : elle stimule les interactions, permettant la collecte de données personnelles par leurs algorithmes. Faire face aux violences numériques requiert pour les adolescents un double travail auquel se consacre cet article : conjointement au « travail du clic » que représentent les activités de partage, de recommandations, de commentaires qu’elles suscitent, s’ajoute un travail en profondeur sur les émotions ressenties face aux images violentes, sexuelles et haineuses, et leur expression sur les plateformes. Le travail émotionnel des adolescents consiste à gérer les écarts entre les différentes règles de sentiment auxquels ils se réfèrent, celles de la plateforme, celles des pairs, celles des parents. Ils ne sont pas dotés également des capacités pour accomplir ce travail et construire des postures autonomes, résistant aux logiques de violence qui affectent leurs circulations numériques. Certains développent des attitudes d’adhésion aux logiques de violence et perdent la capacité à écouter leurs propres sentiments, à protéger leur subjectivité. L’instrumentalisation commerciale des émotions comprend un risque de réification auquel les adolescents sont particulièrement exposés et qui renforce le cycle des violences numériques. L’article s’appuie notamment sur une enquête qualitative menée auprès de 200 adolescents de milieux sociaux et scolaires différenciés entre 2015 et 2017 par entretiens semi-directifs.
The Space Generation Advisory Council
Authors: Decoopman Clémentine , Napier Jennifer Lauren
Published: February 2019

The Space Generation Advisory Council (SGAC) in support of the United Nations Programme on Space Applications is a global non-governmental, non-profit organization and network which aims to represent university students and young space professionals ages 18-35 to the United Nations, space agencies, industry, and academia. The organisation was created in 1999 at the United Nations Conference on Exploration and Peaceful Uses of Outer Space (UNISPACE III), and its members include university students and young professionals with very diverse educational and professional backgrounds, collaborating together on various projects and activities. This chapter provides a detailed description of the organization, including its mandate and scope. In particular, it outlines the benefits and importance of cross-sectorial and multi-disciplinary cooperation in the space sector, and beyond.
Mega-Constellations
Authors: Lacombe Arthur K.
Published: February 2019

This chapter focuses on satellite mega-constellations, as mega-constellations raise several technical issues from telecommunication to launching these huge sets of satellites. Through an overview of basic signal science (periodic waves, types of modulation) and a discussion about telecommunication systems, actual 4G and future 5G networks, the chapter aims at giving without prior scientific background, sufficient material to better understand mega-constellation from its basic functioning to sophisticated satellites systems on orbit providing wide communication services all around the Earth. Major topics are evoked about such constellations be it on launching, space debris, challenges, and technologies used from a technical point of view.
The Strategic Adoption of Big Data in Organizations
Authors: Al-Qirim Nabeel , Rouibah Kamel , Serhani Mohamad Adel , Tarhini Ali , Khalil Ashraf , Maqableh Mahmoud , Gergely Marton
Published: February 2019

This chapter investigates the strategic adoption of big data (BD) and analytics (BDA) in organizations. BD represents a large and complex phenomenon which spans different disciplines. BD research is fraught with many challenges. This research develops BD adoption model that could aid organizations in assessing the strategic importance of BD to gain different advantages including gaining a competitive advantage. BD is considered a radical technology and realizing its advantages in organizations is challenged with many factors. The research attempts to outline the different aspects of BD highlighting different contributions, implications and recommendations.
Analysis of Cutting-Edge Regression Algorithms Used for Data Analysis
Authors: Mishra Indivar , Bandyopadhyay Ritwik , Ghosh Sourish , Swetapadma Aleena
Published: February 2019

Considering the growing applications of big data analytics in the various fields such as healthcare, finance, e-commerce, and web services, it is essential to continuously develop techniques useful for big data. Among various techniques used for big data analytics, regression analysis is very important. In this chapter, an attempt is made to take a detailed look into some of the main regression algorithms and their origin that are used for big data analytics. In this study, some of very famous works related to regression along with some latest research are analyzed. Regression is the process of deducing a predictive model for real-world information based on verified information that is already received. It is used for making predictions, optimizing solutions to complex problems, and understands trends in large and big data analytics. The goal of this study is to promote and facilitate a better understanding of regression algorithms that are in use in the real world for big data analytics.
Applications of Big Data and Green IoT-Enabling Technologies for Smart Cities
Authors: Dogan Onur , Gurcan Omer Faruk
Published: February 2019

In recent years, enormous amounts of digital data have been generated. In parallel, data collection, storage, and analysis technologies have developed. Recently, there has been an increasing trend of people moving towards urban areas. By 2030 more than 60% of the world's population will live in an urban environment. Urban areas are big data resource because they include millions of citizens, technological devices, and vehicles which generate data continuously. Besides, rapid urbanization brings many challenges, such as environmental pollution, traffic congestion, health problems, energy management, etc. Some policies for countries are required to cope with urbanization problems. One of these policies is to build smart cities. Smart cities integrate information and communication technology and various physical devices connected to the network (the internet of things or IoT) to both improve the quality of government services and citizen welfare. This chapter presents a literature review of big data, smart cities, IoT, green-IoT concepts, using technology and methods, and applications worldwide.
Challenges and Solutions of Big Data and IoT
Authors: K. Jayashree , R. Abirami , P. Rajeswari
Published: February 2019

The successful development of big data and the internet of things (IoT) is increasing and influencing all areas of technologies and businesses. The rapid increase of more devices that are connected to IoT from which enormous amount of data are consumed indicates the way how big data is related with IoT. Since huge amount of data are obtained from different sources, analysis of these data involves much of processing at each and every level to extract knowledge for decision making process. To manage big data in a continuous network that keeps expanding leads to few issues related to data collection, data processing, analytics, and security. To address these issues, certain solution using bigdata approach in IoT are examined. Combining these two areas provides several opportunities developing new systems and identify advanced techniques to solve challenges on big data and IoT.
Lecturers' Perceptions of Learning Management Systems Within a Previously Disadvantaged University
Authors: Sackstein Suzanne , Coleman Emma , Ndobe Tsakani Violet
Published: February 2019

The integration of learning management systems into an educational context can prepare students to cope with the current information society, as well as enhance pedagogical practices and knowledge transmission. In order to realize these potential benefits, it is important to understand lecturers' reasons for use and non-use of LMS. This chapter argues that when introducing digital technologies into education in developing economies, contextual issues need to be taken into account, as users have to grapple with issues that may prevent use such as low technical literacy, poor technical support, and limited internet access. For education to be truly inclusive in developing economies, these contextual issues need to be addressed so that students from such contexts are able to reap the same benefits of technology as their contemporaries worldwide, such as improved education in terms of content, and improving the future potential of students in the workplace, with its ever-increasing reliance on technical skills and global connection to the digital economy.
Learning Analytics
Authors: Juhaňák Libor , Zounek Jiří
Published: February 2019

The goal of this chapter is to present and describe a relatively new research field, known as learning analytics, which focuses on use of a wide spectrum of analytical methods and techniques to analyze data coming from educational contexts. The first part of the chapter focuses on the historical context of analytics in education and introduces several research fields that participated in the creation and formation of learning analytics. At the same time, the development of learning analytics and basic related concepts are described in more detail. In the second part, the authors provide an overview of the main research fields and topics within learning analytics, including an overview of commonly used analytical instruments and systems. The final part of the chapter then focuses on challenges currently faced by the field of learning analytics, as well as on opportunities for further development and research within learning analytics in the upcoming years, which are now under development.
A Systematic Exploration of Language Learning Technologies
Authors: Cherner Todd Sloan , Wu Diming , Fegely Alex G.
Published: February 2019

There is an ever-growing number of language learning technologies designed for teaching English, and they commonly take the form of applications for mobile devices and websites. Because learning a language provides personal and professional opportunities, this chapter's researchers conducted a case study that examined the functionality and quality of websites designed to teach English using Puentadura's substitution, augmentation, modification, and redefinition (SAMR) scale. This case study opens with an overview of the edtech marketplace before explaining how the researchers used SAMR to analyze websites designed for teaching English. The researchers found that the majority of websites functioned at SAMR's lower levels and that their design presented challenges when navigating through their content. This chapter concludes with multiple recommendations for both developers and researchers regarding ways to increase the websites' functionalities and improve their design.
A Photo-Narrative of the Sociolinguistic and Sociocultural Identities of a Refugee Adolescent
Authors: Davies Alex P.
Published: February 2019

One's linguistic discourse is directly linked to his or her identity construction. The author conducted a qualitative study that investigated the sociolinguistic and sociocultural identities, both current and imagined, of a newly arrived adolescent of refugee status, named Yerodin, through a photo-narrative approach. Yerodin was unique in that he was 11 years old when he arrived to the United States but did not have any prior formalized schooling. Therefore, he was illiterate in both his first language of Swahili and second language of English. This study took place during a summer school program that sought to develop Yerodin and his siblings' literacy skills before the upcoming school year. Findings illustrated Yerodin's current identity as one who appreciated his experiences in the refugee camp prior to resettlement and as an English learner. Furthermore, Yerodin realized that English, his second language, and academics were key to accessing his desired communities of identity, including aspects of American culture and friendships with “American peers.”
The Entrepreneurial Intention in University Level Students
Authors: González Martínez Rocío , Ríos-Manríquez Martha , Arteaga Cervantes Ana Laura
Published: February 2019

Universities impact in the entrepreneurship ecosystem, they emanate a large number of talents, using their resources to support entrepreneurship. From this situation, arrives the importance of generating and validating measurement instruments to contribute to the identification of level of entrepreneurial intention with which students, of higher education level, have. The Exploratory Factor Analysis technique, uses the Varimax Orthogonal Rotation method, with principal component extraction factors, with a sample of 235 students in public universities of the state of Guanajuato in Mexico, considering 6 dimensions as variables. The results of this research consider as relevant only 3 dimensions from the 6 studied, considering that the entrepreneurial intention in the higher education student is a product of creativity, innovation and need for achievement. While the three dimensions: self-esteem, assumption of risk and problem solving, does not reach a relevant importance; showing a robust instrument for the Mexican context.
Entrepreneurship Program at Secondary School
Authors: Madeira Maria Jose , Rocha Andreia
Published: February 2019

The aim of this study is the analysis of the effect that the entrepreneurship activities have in the development of an entrepreneurial profile of the students of a secondary level and their future entrepreneurial intentions. To empirically test the formulated hypothesis, a questionnaire was developed. By the application of methods of factorial analysis and a logistic regression model, it was concluded that variables like the incentive given by school agents, the participation of students in extracurricular activities and the desire to continue studying, influenced the entrepreneurial intentions of the students. Concerning the entrepreneurial profile, it was concluded that the students who have higher capacity of creation and concretization of entrepreneurial projects and a winning will, have a higher propensity to create their own business. This research analysed the impact of entrepreneurship activities on the development of the secondary school students' entrepreneurial profile, and understand whether these same activities influence their future intentions.
Crossing the Chasm
Authors: Bulger Stephanie R. , Correa Alma , Perman Amertah E. , Rivaldi Matthew
Published: February 2019

Due to the ongoing trend of increased higher education costs, state and federal strategies have been implemented in an effort to lower students' cost of college. One such strategy gaining nationwide attention is the implementation of open educational resources (OER) to lower the cost of textbooks. This chapter describes how a higher education institution can support and scale the diffusion of OER adoption by presenting a framework based on Everett Rogers's diffusion of innovation theory, with a focus on engaging the “early majority” in this process to sustain the innovation. The development of the framework and a case study of its implementation and evaluation within a community college district are presented to guide other higher education institutions in the scaling of OER adoption. The chapter also considers influences on the framework that constrain, accelerate, or support OER adoption, and presents implications and recommendations based on lessons learned.
Gamification Meets Mobile Learning
Authors: Apandi Affah Mohd
Published: February 2019

Higher education in the era of Industrial Revolution 4.0 (IR 4.0) has given a brand new drive on Malaysian educational transformation. The impact of a numerous technology innovations in ICT towards Malaysian education is noticeable. Some existing jobs will be eliminated in this era, but more new jobs that require digital literacy are going to be created. Therefore, Education 4.0 must be able to produce graduates with excellent communication and collaborative skills. However, Malaysian Digest states that fresh graduates lack soft skills. Several approaches have been proposed by the Ministry of Higher Education for the purpose of enhancing students' soft skills. Therefore, by having technologies to help overcome this problem is sought after. This chapter describes the utilization of mobile learning and gamification in enhancing learner's soft skills. It elaborates the effectiveness of using gamification in mobile learning technique to develop learners' higher order thinking skills to help them succeed in a global economy.
Active Use of Digital Technologies in Mathematical Problem Solving
Authors: Symons Duncan , Pierce Robyn
Published: February 2019

The need for students to engage in critical thinking, collaboration, communication, and creativity when utilizing digital technologies is well established given the current push to prepare our students for future work expectations, often referred to as Industry 4.0. In this chapter, 54 Grade 5 students participated in online collaborative mathematical problem solving over a period of 9 weeks. Text-based discussion and software derived artefacts were investigated in an effort to understand how this approach aligns with these expectations. An examination of the frequency/density of technical mathematical vocabulary use and identified examples, Talk Types is used as a means to understand how often students within the online environment are likely to be engaged in work that might be considered productive. The findings of this study suggest that utilizing online synchronous and asynchronous collaborative learning platforms for the purposes of mathematical problem solving is a small but important approach to preparing students for the era of Industry 4.0.
Redesigning Continuing Professional Development Training (CPDT) in Higher Education
Authors: Mohamed Abdul Halim , Ahmad Azlida
Published: February 2019

This chapter discusses the impacts of Industrial Revolution (IR) 4.0 on the continuing professional development training (CPDT), demanding lecturers/teachers to acquire knowledge of instructional design and information and communications technology (ICT). IR 4.0, often referred to as Education 4.0, requires universities to upgrade their CPDT that can enhance ICT skills of lecturers/teachers as well as students. The Ministries of Education (MOEs) and Ministries of Higher Education (MOHE) among ASEAN countries need to share their initiatives to help produce effective digital citizens. The quality of students depends on the quality of lecturers/teachers trained in CPDT. CPDT should be carefully redesigned to encourage more lecturers to enhance their student learning as well as engagement through ICT integration. Guidelines of redesigning CPDT are provided to redesign better and effective CPDT in the future. It is hoped that lecturers can increase their teaching effectiveness, efficiency, and productivity through continuous successful exposure of ID knowledge, skills, and ICT integration.
Protection of the Communication and Digital Security of Mobile Phones as a Fundamental Right to Privacy
Authors: Santiago Nestor Eduardo Araruna , Amorim Ana Monica Anselmo
Published: February 2019

The central idea of this chapter is to discuss the notion of privacy arising from the use and exchange of messages through the use of mobile phones and whether police officers in charge of patrolling and public security may have access to the messages contained therein without proper judicial authorization. The authors focused on the position of the Brazilian Superior Court of Justice (STJ) on the subject, based on the decision rendered in the Appeal in Habeas Corpus (RHC) n. 51.531/RO. At this trial, protection was given to the new forms of communication and data contained in mobile phones under the constitutional terms of protection of privacy and non-unlawful obtaining of evidence, so that it will be necessary to issue a court order to get any informational elements found in messaging applications installed on a smartphone.
Assisted Human Reproduction by Medical Techniques and the Respect of the Fundamental Rights and the Dignity of the Parts Involved
Authors: Wider Roberto
Published: February 2019

Dealing with the subject of the fundamental rights of people involved in medically assisted reproduction, this chapter focuses on the issues surrounding the LGBTI+ population (lesbians, gays, bisexuals, transsexuals, intersexuals, and new genders that are being recognized). Within this group, the importance of biological children, even amongst those who cannot naturally reproduce, is also highlighted. Firstly, the author points out the laws that determine the child's protection, then compares them to real-life examples of actual situations of homophobia including physical and psychological abuse, understanding that children are also subject to the same abuse, not only due to sexual orientation discrimination and gender identity but also from having to grow up in a so-called unusual family structure. The author looks for an answer that will help strengthen the child's fundamental rights both before and after birth.
Moral Disengagement Strategies in Videogame Players and Sports Players
Authors: McLean Lavinia , Griffiths Mark D.
Published: February 2019

Research in the area of video game play and sports psychology has suggested that specific strategies are often employed by players to justify aggressive behaviour used during gameplay. The present study investigates the relationship between game play and moral disengagement strategies in a group of 605 adults who played violent videogames or regularly played competitive sports. The results suggest that sports players were more likely than violent game players to endorse moral disengagement strategies. The video gamers were more likely to use a specific set of moral disengagement strategies (i.e., cognitive restructuring) than the other groups and this may be related to the structural characteristics of videogames. The findings add to recent research exploring the mechanisms by which individuals engage in aggressive acts both virtually and in real-life situations. The results are discussed in relation to similar relevant research in the area, along with recommendations for future research.
Evaluation of Driver's Cognitive Distracted State Considering the Ambient State of a Car
Authors: Koma Hiroaki , Harada Taku , Yoshizawa Akira , Iwasaki Hirotoshi
Published: February 2019

The effectiveness of considering the ambient state of a driving car for evaluating the driver's cognitive distracted state is evaluated. In this article, Support Vector Machines and Random Forest, which are representative machine learning models, are applied. As input data for the machine learning model, in addition to a driver's biometric data and car driving data, an ambient state data of a driving car are used. The ambient state data of a driving car considered in this study are that of the preceding car and the shape of the road. Experiments using a driving simulator are conducted to evaluate the effectiveness of considering the ambient state of a driving car.
Chaotic System Design Based on Recurrent Artificial Neural Network for the Simulation of EEG Time Series
Authors: Zhang Lei
Published: February 2019

Electroencephalogram (EEG) signals captured from brain activities demonstrate chaotic features, and can be simulated by nonlinear dynamic time series outputs of chaotic systems. This article presents the research work of chaotic system generator design based on artificial neural network (ANN), for studying the chaotic features of human brain dynamics. The ANN training performances of Nonlinear Auto-Regressive (NAR) model are evaluated for the generation and prediction of chaotic system time series outputs, based on varying the ANN architecture and the precision of the generated training data. The NAR model is trained in open loop form with 1,000 training samples generated using Lorenz system equations and the forward Euler method. The close loop NAR model is used for the generation and prediction of Lorenz chaotic time series outputs. The training results show that better training performance can be achieved by increasing the number of feedback delays and the number of hidden neurons, at the cost of increasing the computational load.
Performance Analyses of Differential Evolution Algorithm Based on Dynamic Fitness Landscape
Authors: Li Kangshun , Liang Zhuozhi , Yang Shuling , Chen Zhangxing , Wang Hui , Lin Zhiyi
Published: February 2019

Dynamic fitness landscape analyses contain different metrics to attempt to analyze optimization problems. In this article, some of dynamic fitness landscape metrics are selected to discuss differential evolution (DE) algorithm properties and performance. Based on traditional differential evolution algorithm, benchmark functions and dynamic fitness landscape measures such as fitness distance correlation for calculating the distance to the nearest global optimum, ruggedness based on entropy, dynamic severity for estimating dynamic properties, a fitness cloud for getting a visual rendering of evolvability and a gradient for analyzing micro changes of benchmark functions in differential evolution algorithm, the authors obtain useful results and try to apply effective data, figures and graphs to analyze the performance differential evolution algorithm and make conclusions. Those metrics have great value and more details as DE performance.
A Novel Performance Enhancing Task Scheduling Algorithm for Cloud-Based E-Health Environment
Authors: Pandi Vijayakumar , Perumal Pandiaraja , Balusamy Balamurugan , Karuppiah Marimuthu
Published: February 2019

The fast-growing internet services have led to the rapid development of storing, retrieving and processing health-related documents from a public cloud. In such a scenario, the performance of cloud services offered is not guaranteed, since it depends on efficient resource scheduling, network bandwidth, etc. The trade-off which lies between the cost and the QoS is that the cost should be variably low on achieving high QoS. This can be done by performance optimization. In order to optimize the performance, a novel task scheduling algorithm is proposed in this article. The main advantage of this proposed scheduling algorithm is to improve the QoS parameters which comprises of metrics such as response time, computation time, availability and cost. The proposed work is simulated in Aneka and shows better performance compared to existing paradigms.
Two-Stage Adaptive Classification Cloud Workload Prediction Based on Neural Networks
Authors: Li Lei , Wang Yilin , Jin Lianwen , Zhang Xin , Qin Huiping
Published: February 2019

Workload prediction is important for automatic scaling of resource management, and a high accuracy of workload prediction can reduce the cost and improve the resource utilization in the cloud. But, the task request is usually random mutation, so it is difficult to achieve more accurate prediction result for single models. Thus, to improve the prediction result, the authors proposed a novel two-stage workload prediction model based on artificial neural networks (ANNs), which is composed of one classification model and two prediction models. On the basis of the first-order gradient feature, the model can categorize the workload into two classes adaptively. Then, it can predict the workload by using the corresponding prediction neural network models according to the classification results. The experiment results demonstrate that the suggested model can achieve more accurate workload prediction compared with other models.
The Television Viewer and the Television News
Authors: Nguri Evans Matu
Published: February 2019

Television news has been studied from a number of perspectives. Few studies have focused on the moment of the encounter between the television viewer and the news. This research focused on what takes place at the encounter as described by the viewer. Its specific research questions were: what viewer typology constructs? What key news aesthetic emerges? And what is the nature of the encounter process? These were examined in a qualitative study mainly using a phenomenological approach involving 58 participants. The study had three key findings: that the television viewer is a disturbed, reflective, and dominating person at the encounter; that an epic news genre dominates the site and process; and lastly, that the key process at the encounter is one of intertextuality through a combative, combustive fusion and filter procedure. The research argues for a new area of encounter studies.
Comparative Analysis of Various Parameters of Tri-Gate MOSFET with High-K Spacer
Authors: Vimala P. , Nithin Kumar N.R.
Published: February 2019

In this paper, a comparative analysis of the Tri-gate MOSFET device structure with respect to Single Material Gate (SMG) Tri-gate MOSFET, Double Material Gate (DMG) Tri-gate MOSFET and Triple Material Gate (TMG) Tri-gate MOSFET with & without Hafnium dioxide as high-K dielectric material is employed using Silvaco TCAD Atlas Tool. It shows a compact model and better DC, AC performance for triple material gate structures and yields a high drive current of the device for TMG Tri-gate MOSFET with high-k dielectrics and shows a better electrical characteristics in comparison with other device structures.
Size Controlled Preparation of Starch Nanoparticles from Wheat through Precipitation at Low Temperature
Authors: Momenpoor Behnaz , Danafar Firoozeh , Bakhtiari Fereshteh
Published: February 2019

This study developed an energy efficient procedure to produce size-controlled starch nanoparticles (SNPs) via precipitation. A 0.06 g/ml aqueous starch suspension was solubilized in a solvents system including NaOH and urea at temperature of 35 °C. Applying only 3 minutes ultrasonic treatment leads to formation of SNPs in a narrow size range of 50-70 nm with production yield of 92±5%. TEM and FESEM revealed formation of uniform short nanofibers. Unlike starch/water suspension, the nanoparticles/water suspension remained stable for 48 hours.
Synthesis and Characterization of Stabilized Tetragonal Nano Zirconia by Precipitation Method
Authors: Shokry Hassan , El-Kady Marwa Farouk , Hamad Hesham
Published: February 2019

Nano sized ZrO2 nanopowder was synthesized by precipitation method. Phase transformation was investigated as a function of calcination temperature by XRD, SEM , and FT-IR. It is indicated that the thermal anneling from 400 to 800 °C resulted in increasing the average crystallite size from 12 to 20 nm. As the calcination temperature increased, the crystallite size and the agglomeration were increased. The increase in the monoclinic content and grain growth are caused by the calcination temperatures even calcination at 800 °C.