bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract Intelligence
Authors: Wang Yingxu , Zadeh Lotfi A. , Widrow Bernard , Howard Newton , Beaufays Françoise , Baciu George , Hsu D. Frank , Luo Guiming , Mizoguchi Fumio , Patel Shushma , Raskin Victor , Tsumoto Shusaku , Wei Wei , Zhang Du
Published: March 2020

Basic studies in denotational mathematics and mathematical engineering have led to the theory of abstract intelligence (aI), which is a set of mathematical models of natural and computational intelligence in cognitive informatics (CI) and cognitive computing (CC). Abstract intelligence triggers the recent breakthroughs in cognitive systems such as cognitive computers, cognitive robots, cognitive neural networks, and cognitive learning. This paper reports a set of position statements presented in the plenary panel (Part II) of IEEE ICCI*CC'16 on Cognitive Informatics and Cognitive Computing at Stanford University. The summary is contributed by invited panelists who are part of the world's renowned scholars in the transdisciplinary field of CI and CC.
Graph-Based Semi-Supervised Learning With Big Data
Authors: Banerjee Prithish , Culp Mark Vere , Ryan Kenneth Jospeh , Michailidis George
Published: March 2020

This chapter presents some popular graph-based semi-supervised approaches. These techniques apply to classification and regression problems and can be extended to big data problems using recently developed anchor graph enhancements. The background necessary for understanding this Chapter includes linear algebra and optimization. No prior knowledge in methods of machine learning is necessary. An empirical demonstration of the techniques for these methods is also provided on real data set benchmarks.
Speaker Recognition With Normal and Telephonic Assamese Speech Using I-Vector and Learning-Based Classifier
Authors: Sharma Mridusmita , Kaushik Rituraj , Sarma Kandarpa Kumar
Published: March 2020

Speaker recognition is the task of identifying a person by his/her unique identification features or behavioural characteristics that are included in the speech uttered by the person. Speaker recognition deals with the identity of the speaker. It is a biometric modality which uses the features of the speaker that is influenced by one's individual behaviour as well as the characteristics of the vocal cord. The issue becomes more complex when regional languages are considered. Here, the authors report the design of a speaker recognition system using normal and telephonic Assamese speech for their case study. In their work, the authors have implemented i-vectors as features to generate an optimal feature set and have used the Feed Forward Neural Network for the recognition purpose which gives a fairly high recognition rate.
An Online Intrusion Detection System to Cloud Computing Based on Neucube Algorithms
Authors: Almomani Ammar , Alauthman Mohammad , Albalas Firas , Dorgham O. , Obeidat Atef
Published: March 2020

This article describes how as network traffic grows, attacks on traffic become more complicated and harder to detect. Recently, researchers have begun to explore machine learning techniques with cloud computing technologies to classify network threats. So, new and creative ways are needed to enhance intrusion detection system. This article addresses the source of the above issues through detecting an intrusion in cloud computing before it further disrupts normal network operations, because the complexity of malicious attack techniques have evolved from traditional malicious attack technologies (direct malicious attack), which include different malicious attack classes, such as DoS, Probe, R2L, and U2R malicious attacks, especially the zero-day attack in online mode. The proposed online intrusion detection cloud system (OIDCS) adopts the principles of the new spiking neural network architecture called NeuCube algorithm. It is proposed that this system is the first filtering system approach that utilizes the NeuCube algorithm. The OIDCS inherits the hybrid (supervised/unsupervised) learning feature of the NeuCube algorithm and uses this algorithm in an online system with lifelong learning to classify input while learning the system. The system is accurate, especially when working with a zero-day attack, reaching approximately 97% accuracy based on the to-be-remembered (TBR) encoding algorithm.
Applications of Longitudinal Research to Advance Organizational Theory
Authors: Newman David , Newman Isadore , Hitchcock John H.
Published: March 2020

The purpose of this article is to inform researchers about and encourage the use of longitudinal designs to further understanding of human resource development and organizational theory. This article presents information about a variety of longitudinal research designs, related statistical procedures, and an overview of general data collecting approaches, covering their strengths and weaknesses. The article also serves as a reminder of the importance of alignment between the research purpose, questions and methodology while highlighting the benefits of using multiple methods. Finally, importance of research replicability in the context of longitudinal inquiry is stressed.
Quantum-Behaved Particle Swarm Optimization Based Radial Basis Function Network for Classification of Clinical Datasets
Authors: Leema N. , Nehemiah H. Khanna , Kannan A.
Published: March 2020

In this article, a classification framework that uses quantum-behaved particle swarm optimization neural network (QPSONN) classifiers for diagnosing a disease is discussed. The neural network used for classification is radial basis function neural network (RBFNN). For training the RBFNN K-means clustering algorithm and quantum-behaved particle swarm optimization (QPSO) algorithm has been used. The K-means clustering algorithm is used to find the optimal number of clusters which determines the number of neurons in the hidden layer. The cluster approximation error is used to find the optimal clusters. The weights between the hidden and the output layer is determined using QPSO algorithm based on the mean squared error (MSE). The performance of the developed classifier model has been tested with five clinical datasets, namely Pima Indian Diabetes, Hepatitis, Bupa Liver Disease, Wisconsin Breast Cancer and Cleveland Heart Disease were obtained from the University of California, Irvine (UCI) machine learning repository.
Sentiment Predictions Using Deep Belief Networks Model for Odd-Even Policy in Delhi
Authors: Sharma Sudhir Kumar , Hoque Ximi , Chandra Pravin
Published: March 2020

This paper analyzes the odd-even policy in Delhi using tweets posted on Twitter from December 2015 to August 2016. Twitter is a social network where users post their feelings, opinions and sentiments for any event. This paper transforms the unstructured tweets into structured information using open source libraries. Further objective is to build a model using Deep Belief Networks classification (DBN) to classify unseen tweets on the same context. This paper collects tweets on this event under six hashtags. This study explores three freely available resources / Application Programming Interfaces (APIs) for labeling of tweets for academic research. This paper proposes three sentiment prediction models using the sentiment predictions provided by three APIs. DBN classifier is used to build six models. The performances of these six models are evaluated through standard evaluation metrics. The experimental results reveal that the TextBlob API and proposed Preference Model outperformed than the other four sentiment prediction models.
Detection of Drive-by Download Attacks Using Machine Learning Approach
Authors: Aldwairi Monther , Hasan Musaab , Balbahaith Zayed
Published: March 2020

Drive-by download refers to attacks that automatically download malwares to user's computer without his knowledge or consent. This type of attack is accomplished by exploiting web browsers and plugins vulnerabilities. The damage may include data leakage leading to financial loss. Traditional antivirus and intrusion detection systems are not efficient against such attacks. Researchers proposed plenty of detection approaches mostly passive blacklisting. However, a few proposed dynamic classification techniques, which suffer from clear shortcomings. In this paper, we propose a novel approach to detect drive-by download infected web pages based on extracted features from their source code. We test 23 different machine learning classifiers using data set of 5435 webpages and based on the detection accuracy we selected the top five to build our detection model. The approach is expected to serve as a base for implementing and developing anti drive-by download programs. We develop a graphical user interface program to allow the end user to examine the URL before visiting the website. The Bagged Trees classifier exhibited the highest accuracy of 90.1% and reported 96.24% true positive and 26.07% false positive rate.
Research Strategy for Studying User's Acceptance of Tourism-Related ITs
Authors: Siang Tan Gek , Aziz Kamarulzaman Ab. , Ahmad Zauwiyah
Published: March 2020

This paper aims to guide future researchers on research strategy for studying user's acceptance of tourism-related Information Technologies (ITs). In a study on user's acceptance of the technological-combination of virtual reality and augmented reality application in the UNESCO World Heritage Site of Melaka, the author proposes 11 steps of research strategy which begin with developing the research framework (Step 1), proposing the research hypotheses (Step 2), determining research design (Step 3), designing sampling processes (Step 4), designing questionnaire (Step 5), conducting face validity (Step 6), developing the prototypes (Step 7), conducting pilot testing (Step 8), collecting data (Step 9), analyzing data (Step 10), as well as providing conclusion (Step 11).
ISOPM
Authors: Fraga Maria da Glória , Varajão João , Oliveira Paula Cristina
Published: March 2020

Information Systems (IS) and Information Technologies (IT) are fundamental elements for the competitiveness of organizations. Thus, an efficient development of IT/IS projects is a key factor for business success. Nowadays companies are increasingly outsourcing their activities, including the development of IT/IS projects. However, the results of investments often lead to frustration and are far from meeting the expectations. Bearing this in mind, this paper proposes a new framework – ISOPM – that identifies the most relevant activities for the IT/IS outsourcing projects management, aiming to contribute to the study and development of this specific area of project management.
A Taxonomy of Sybil Attacks in Vehicular Ad-Hoc Network (VANET)
Authors: Chaubey Nirbhay Kumar , Yadav Dhananjay
Published: March 2020

Vehicular ad hoc networks (VANETs) are a class of ad hoc networks in which vehicle communicate with each other to show the traffic situation and any mishappening on the road. VANET is vulnerable to a number of attacks due to its infrastructure-less nature. One of these attacks is the Sybil attack. Security of data dissemination in VANET is very crucial, otherwise any mishappening can occur on road. Sybil attack is very difficult to be defended and detected, especially when it is launched by some conspired attackers using their legitimate identities, and this has become a growing research interest in VANETs in past few years. This chapter studies various dimension of VANETs including its structure, communication architecture, security issues, and critical review of technique to detect Sybil attacks.
Sustainable Performance of Tunisian SMEs in Industry 4.0
Authors: Abdulaziz Alhumaidan Abdullah , Ahmad Noor Hazlina
Published: March 2020

The research aims to know the impact of sustainability orientation on sustainable performance. The data has been collected through a survey and the probability-random sampling technique has been employed. The study sample is micro and small enterprises in Tunisia. The organizational level is the unit of analysis, which are the owners of these enterprises. It has been concluded that managers' orientations have an influence on environmental and social performance, but their orientations towards sustainability did not impact economic performance. The study has suggested that future research could investigate different organizations irrespective of their size and industry that would make it easy to generalize results.
Employer's Role Performance Towards Employees' Satisfaction
Authors: Abd Halim Siti Noorjannah , Abd Halim Siti Noorhaslina
Published: March 2020

The wave of the Fourth Industrial Revolution (IR4.0) is a phenomenon in which one or more technologies are replaced by another technology in a short amount of time. In small and medium-sized enterprises (SMEs), some internal and external problem are occurring that suggest change from classical to technological approach. Thus, this chapter aims to establish the relationship between the employees' satisfaction toward their employer's role performance. Based on the power-dependence and agency theories, this study contributes to the SMEs industry in Malaysia and will involve IR4.0 by offering a much more comprehensive theoretical perspective to aid understanding and prepare for the revolution internally. The sample of this study comprises of employees who are working in various sectors of the SMEs industry. G-power technique was employed to find the minimum sample size in this study. Meanwhile, the SPSS and PLS will be used to analyse the data. The practical implication of this research concerns the factors that can enhance employee satisfaction if their company jumps into the IR4.0. Thus, the employer should play the right role to make sure the employees are ready and well prepared for the revolution despite there being environmental uncertainty happening in the process.
Strategic Management in SMEs in the Context of Clustering
Authors: Arıcıoğlu Mustafa Atilla , Yiğitol Büşra
Published: March 2020

Nowadays, the effects of global dynamics are directive on enterprises. Competitiveness is triggered by these dynamics and determine the efficiency of enterprises. Therefore, not only the local and national dimension, but also the global actors have a say on the viability of enterprises and their competitiveness. In such an ecological environment, it is possible to come across many strategies for gaining competitiveness and skills. Porter points out that the national resources should be used optimally and that each country should specialize in specific areas and build clusters through these areas and thus use the resources effectively. Therefore, it draws attention to “the importance of clustering,” which is one of the instruments effective in competitiveness with global dynamics. In this study, strategic management processes of small and medium-sized enterprises in the context of clustering will be discussed. In addition, the contribution of cluster studies to SMEs in Industry 4.0 digitalization process will be briefly mentioned.
A Maximal Covering Location Model for the Organ Transplant Organization in Turkey
Authors: Özkan Barış , Özceylan Eren
Published: March 2020

Transplantation of the organs is one of the principal treatment techniques for the people who have critical organ issues. One of the main steps of this treatment is getting the organ as quickly as possible to its recipient from a potential donor. To provide the aforementioned treatment, the spatial distributions of the organ transplant centers which maximize the donors/patients coverage become essential. In this chapter, the organ transplant process of Turkey which has 99 transplant centers (hospitals) in 81 cities is considered. The main goal of this study is to maximize the donor/patient coverage within the system constraints. As a potential demand source, 923 districts are determined using geographic information system (GIS). With the application of maximal covering location model, the number of covered donors/patients is maximized considering the cold ischemia time of organs. Optimal results are obtained for different scenarios based on heart, liver, and kidney.
Machine Learning Applications for Classification Emergency and Non-Emergency Patients
Authors: Çil Zeynel Abidin , Caliskan Abdullah
Published: March 2020

Emergency departments of hospitals are busy. In recent years, patient arrivals have significantly risen at emergency departments in Turkey like other countries in the world. The main important features of emergency services are uninterrupted service, providing services in a short time, and priority to emergency patients. However, patients who do not need immediate treatment can sometimes apply to this department due to several reasons like working time and short waiting time. This situation can reduce efficiency and effectiveness at emergency departments. On the other hand, computers solve complex classification problems by using machine learning methods. The methods have a wide range of applications, such as computational biology and computer vision. Therefore, classification of emergency and non-emergency patients is vital to increase productivity of the department. This chapter tries to find the best classifier for detection of emergency patients by utilizing a data set.
Detection of Chronic Disease in Primary Care Using Artificial Intelligence Techniques
Authors: Gulmez Hakan
Published: March 2020

Chronic diseases are the leading causes of death and disability worldwide. By 2020, it is expected to increase to 73% of all deaths and 60% of global burden of disease associated with chronic diseases. For all these reasons, early diagnosis and treatment of chronic diseases is very important. Machine learning is an application of artificial intelligence that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning is the development of computer programs that can access data and use it to learn for themselves. The learning process starts by searching for patterns in the examples, experiences, or observations. It will make faster and better decisions in the future based on all these. The primary purpose in machine learning is to allow computers to learn automatically without human help and affect. Considering all the reasons above, this chapter finds the most appropriate artificial intelligence technique for the early detection of chronic diseases.
An Ontology-Based Approach for Production Planning and Control of Cyber-Physical Production Systems
Authors: Hozdić Elvis
Published: March 2020

The objective of this research is to develop a new ontology-based approach for the management and control of cyber-physical production systems (CPPSs). In the CPPSs, the management and control functions are integrated with a physical part of manufacturing system. The function of production planning and control of manufacturing systems (PPC) is an important part of the management and control of the CPPSs. The elements of the cyber system structure enable the dynamic management and control of manufacturing systems in real time, through the realization of the digitalized and cybernated functions of PPC. The proposed approach to management and control of the CPPSs is based on the foundational ontology of manufacturing systems. The digitalized production planning, scheduling, and control functions are implemented as a multi-agent system (MAS). The communication between agents was addressed to support the autonomic decision for each individual agent. A case study demonstrates feasibility of the approach through the use of simulation experiments.
New Solar Photocatalytic Technologies for Water Purification as Support for the Implementation of Industry 4.0
Authors: Bratovcic Amra
Published: March 2020

The main urgent problem of humanity is related to clean water availability. Shortage of drinking water in most parts of the world has been a growing concern in recent times. This chapter will consider emerging contaminants present in the aquatic environment. The commonly present concentrations are in the range from mg/L to ng/L in wastewater, surface water, ground water, and drinking water. The challenges in wastewater and drinking water purification are dependent on the origin of the water. Solar photocatalysis is a new promising technology for the water purification. With solar, photocatalysis is possible to reduce organic contaminants present in water by using the sunlight. This chapter addresses the fundamental reaction mechanism, different type of photocatalytic nanomaterials based on TiO2, and recent developments in the reactor design for solar photocatalytic water purification from lab scale-up to large-scale application.
Innovative Technologies in Lapping and Electrospark Alloying of Metal Surfaces as the Basis for Industry 4.0
Authors: Avdeenko Anatoly P. , Konovalova Svetlana A. , Dašić Predrag V. , Turmanidze Raul
Published: March 2020

The various active chemical additives along with abrasive materials are used to intensify processes in lapping of metal surfaces. The authors developed new lapping compositions based on inexpensive components with the addition of various chemical agents. The chemical additives help to improve metal removal, to decrease surface roughness, and to get a more stable metal surface. New lapping pastes do not cause the corrosion of equipment and do not require their replacement in further operations of the mechanism, for example, large-sized reducer. The chemical additives can be used in electrospark alloying too. They improve both the alloying process and the subsequent operation of alloyed surfaces. New technologies reduce the number of operations that require human involvement. That contributes to the introduction of full machine control over technological process and is the basis for Industry 4.0 that offers the opportunity for manufacturers to optimize their operations quickly and efficiently by knowing what needs attention.
Peaceful Solution of Conflicts in Schools
Authors: Uğurlu Celal Teyyar , Şemin Fatma Köybaşı
Published: March 2020

Conflicts in schools can be settled amicably if certain variables become known such as probable circumstances under which schools might face conflicts, factors causing conflicts, and ways of effective conflict management. This chapter first introduces basic concepts related to conflict. The sections about interpersonal relations, communication, interpersonal relations, and listening as a part of communication are dedicated to communication and interpersonal relations as the root of conflict. The following sections of this chapter elaborate conflict as well as terms regarding reasons of conflict including what conflict is, the conflict theory, types of conflict, factors causing interpersonal conflicts, interpersonal conflicts in schools, and reasons of student-student conflicts in schools. In this scope, effective ways of conflict management are discussed. The sections about conflict management emphasize that conflicts can be overcome in a constructive manner.
Teaching in a Makerspace
Authors: Otieno Catherine
Published: March 2020

This chapter provides an in-depth study of the teaching practices of instructors who primarily guide and facilitate learning in a makespace. With a close look at the pedagogical practices that govern teaching and learning in the maker classroom, this study presents instructors who modeled these frameworks. In addition to their own knowledge base and expertise, they were able to efficiently and effectively integrate multi-resources in a unique learning environment while helping learners succeed and adopt the maker mindset. Makerspaces are changing how we perceive learning and teaching. Instructors highlighted in this chapter put forth activities and learning goals that were learner centered and interesting to various learning needs. They designed and created a learning environment that safeguarded learners and allowed them to experiment with ideas and materials, creating different iterations of learning and redefining what success and failure means.
Educator Perceptions of Digital Devices
Authors: Delello Julie A. , Kiekel Jean , Poyo Susan R. , Williams Mia Kim , Kerby Deborah
Published: March 2020

There is a growing concern regarding student use of digital devices such as smartphones during classroom instruction. This pilot study used a mixed-method survey to collect data from 146 K-16 educators. Eighty percent of the participants said that students multitask, and 50% said they multitask a lot. Many of the instructors reported they are distracted by students' use of phones while more than half of the participants indicated they felt doing multiple tasks at the same time disrupts class time and may impact a students' ability to learn. These findings have important implications because classroom instructors may need to modify instructional strategies to keep students on task, have clear policies on the use of electronic devices, and ensure that students understand instructor expectations.
Creepy Technologies and the Privacy Issues of Invasive Technologies
Authors: McWhorter Rochell R. , Bennett Elisabeth E.
Published: March 2020

Technology has become increasingly invasive and corporate networks are expanding into public and private spaces to collect unprecedented data and provide new services such as artificial intelligence and through unsettling human-like personas. The term “creepy technology” is appearing in the literature along with concerns for privacy, ethical boundaries, cybersecurity, and mistaken identity but is also in news articles to inform the public about technology advances that affect consumer privacy. Invasive technology provides the impetus for external adaptation for many organizations and current trends require rapid adaption to potential threats to security. Also, usability addresses how users respond and adapt to new technology. This chapter includes the presentation of an exploratory study of how the public responded to various technology announcements (N=689 responses) and results indicated a significant response to invasive technologies and some sense of freedom to opine. This chapter also provides discussion of interventions that are critical to both public and private sectors.
Grit, Goal Setting, and Social Support as It Pertains to Family Dynamics and Romantic Relationships
Authors: Blanchard-McGehee Valerie Lynn
Published: March 2020

This chapter explores interpersonal relationships in family dynamics and romantic relationships as they pertain to grit, goal setting, and social support. Individuals in various types of relationships will be explored, such as married and non-married couples, couples with children, and couples without children. In addition, this chapter will examine the influence that partners and family members have on one another and the several outcomes that result in different kinds of family and relational supports. The chapter will also explore the importance of using all three methods (grit, goal setting, social support) in conjunction with one another, since the three are vital to long-term success in interpersonal relationships and positive family dynamics, regardless of environmental or socio-economic differences in each case. Examples with evidentiary and anecdotal support will be used to explain the benefits or detriments of having or not having these traits in interpersonal relationships and family dynamics. These examples were selected to be inclusive and to relate to family, parental, and spousal relationship structures.
Beyond Novelty
Authors: Fovet Frederic
Published: March 2020

This chapter examines how fully accessible teaching and learning, and particularly Universal Design for Learning (UDL), currently attracts much attention in higher education (HE) as an innovative pedagogical approach. Having highlighted all the dimensions of UDL that currently qualify it as “innovative”, the chapter further examines the concept of pedagogical innovation and what constitutes such a perception within the field. It is argued that far from being new, the notion of accessible teaching and learning draws from other pedagogical concepts and schools of thought that are well established in the literature and very much traditional and readily accepted. The chapter discusses that despite this recent “framing” or branding, UDL is not so much a novelty as a return to a fundamental questioning on the part of educators and instructional designers around engagement and social justice and their place in pedagogy.
Disruptive Methodologies and Cross-Curricular Competencies for a Training Adapted to New Professional Profiles
Authors: Díaz-Millón Mar , Rivera-Trigueros Irene , Olvera-Lobo María Dolores , Gutiérrez-Artacho Juncal
Published: March 2020

Recently, in the translation sector, new multifaceted profiles requiring a great domain of new technologies have emerged: localization, post-editing, and transcreation. To train future professionals, it is necessary to define the cross-curricular competencies they require. Cross-curricular competencies involve gaining cross-disciplinary skills in the teaching-learning process. However, cross-curricular competencies are often relegated to a second place. The main objective of this chapter is to explore how disruptive methodologies can be applied to studies in translation and interpreting to foster cross-curricular competencies. After defining innovation in higher education, this work outlines which are the most suitable disruptive methodologies that foster cross-curricular competencies in the undergraduate program in translation and interpreting.
Case Study
Authors: Lambert Jacqueline M.
Published: March 2020

Focusing on the challenges faced by polytechnic institutions in Alberta, Canada, this chapter explores the rationales, challenges, and solutions encountered in choosing between investment credit and non-credit program offerings to meet the needs of adult learners and industry partners. Drawing on inter-provincial and international perspectives, this chapter discusses ways to provide the benefits of credential education access, alongside the flexibility and responsiveness of non-credit learning design.
Foreign Body Shape Classification Using Intuitionistic Fuzzy Rule Based Approach on Pediatric Radiography Images
Authors: Vasumathy M.  , Mythili T.
Published: March 2020

Segmentation is the significant key stage in image analysis towards partitioning an image into different regions which have homogeneous features such as color, shape, and texture which is very important in classifying different region shapes in an image. In general, images are considered fuzzy due to the uncertainty present in terms of vagueness. The regions contain imprecise gray levels and uncertain data values which makes the task of defining the membership function difficult due to lack of precise knowledge. The intuitionistic fuzzy rule-based shape classification approach is used to classify the different shapes, such as circular, polygon, sharp, and irregular of the aspired foreign body on pediatric radiography images. Experimental results show the effectiveness of the proposed method in contrast to conventional fuzzy rule base algorithm.
Using Virtual Rehearsal in a Simulator to Impact the Performance of Science Teachers
Authors: Dieker Lisa A. , Straub Carrie , Hynes Michael , Hughes Charles E , Bukathy Caitlyn , Bousfield Taylor , Mrstik Samantha
Published: March 2020

This study investigated the use of a virtual learning environment, TeachLivE, using pre-post group design to examine the effects of repeated virtual rehearsal sessions. Based upon past findings on the effectiveness of four 10-minutes sessions, the research team used refined methods to examine the effects of these sessions on 102 secondary science teachers. Teachers who took part in the simulated activities significantly increased their targeted behaviors compared to colleagues who had not taken part in the simulation activities. These results of behavior changes that occurred in the simulation were found to transfer back to the real classroom settings for the experimental group (simulation use). Results from this study further validates the impact of simulation in teacher education, showing professional learning in virtual-reality simulated classrooms can positively impact targeted teaching practices in a concentrated amount of time.
A Conceptual Study on Employer Perception towards Hiring Employee with Online Degree/Certification
Authors: Naresh B.  , Rajalakshmi M.
Published: March 2020

Higher education is enduring a transition across the world. This transition leads to the introduction of technology into the education system and provides opportunities to pursue a degree through online participation. According to Bramble and Panda, globalization plays a vital role in recognizing the necessity of providing online learning opportunities in higher education. The stakeholders and education institutions are very much concerned about the massive potential of online learning models. In the span of a decade, the demand for online courses has increased due to change in technology, lifestyle, economics, concerns of employees to develop knowledge, new competency skills and thinning out the geographical differences, etc. The innovative archetype of the online education is significant in quality, course content, satisfaction, and the perception of the users from various levels when compared to traditional face-to-face classroom systems. As a result, online education is more effective and efficient than the model of face-to-face education. The main objective of this research is to analyse and measure the various factors that affect employer perception towards online education systems in their recruitment process and cycle. 549 articles have been examined in terms of integrated literature review system to measure the impact. The result indicates, awareness, readiness, credentials and reputation are the major factors that affect employer perception on hiring decision.
The Math Model of Drone Behavior in the Hive, Providing Algorithmic Architecture
Authors: Galiautdinov Rinat
Published: March 2020

Nowadays, drones play a significant role not only in civil ventures, but also in the military sphere. Planning the trajectories of the hives of the drones is not a trivial task and requires deep research. In this research, the author considers different strategies of biological creatures and then extrapolated on the drones. The author's research demonstrates the math model of the drones behavior in the hive, provides algorithmic architecture. The author describes in the detail the layers of the system for management of the drones and their responsibilities and architecture. The author also provides a software algorithm which demonstrates effective grouping of the drones (creating a swarm) which is later on used in the movement of the swarm.
Understanding the Continuance of Mobile Financial Services in Kenya
Authors: Omigie Newman O. , Zo Hangjung , Ciganek Andrew P. , Jarupathirun Suprasith
Published: March 2020

This study develops an integrated model that extends the means-end theory with customer value research and examines continuance intention towards using mobile financial services. A large-scale online questionnaire targeting M-PESA customers in Kenya was employed to analyze the research model. The results indicate that utilitarian and hedonic values affect continuance intention. Hedonic and personal values impact customer satisfaction, while customer satisfaction influences continuance intention. Customer satisfaction mediates the indirect effects of hedonic and personal values on continuance intention. This study presents a value-based framework to examine the hierarchical influences of customer value on attitudes and outcome behaviors. This study offers several research contributions as well as insights for practitioners to enhance mobile financial services for sustained adoption, use, economic and developmental success.
Social Media in Micro-Enterprises
Authors: Vatanasakdakul Savanid , Aoun Chadi , Putra Yuniarti Hidayah Suyoso
Published: March 2020

Social media is increasingly gaining traction as a valuable tool for small business. This is particularly the case in micro enterprises in the Indonesian retail industry, where adoption is anecdotally increasing, but with little understanding of the factors enabling such adoption. Consequently, this study proposes a research model derived from the Unified Theory of Acceptance and the Use of Technology and extended by integrating the task-technology-fit framework, along with price value propositions. Online surveys were sent to micro enterprises operating in the Indonesian retail industry with 153 valid responses received. Data analysis used structural equation modelling with SmartPLS 3. The results show that price value and task-technology-fit are perceived as significant factors for influencing positive attitudes towards the adoption of social media among micro enterprises. In addition, attitude and facilitating conditions were found to have a significant influence on intention to adopt social media. These findings hold import implications to theory and practice in this nascent field of research.
Mirror Mold Reuse Techniques in Ancient East Asia
Authors: Shimizu Yasuji , Uno Takashi , Sugaya Fuminori , Toyooka Takushi , Shimizu Katsuro
Published: March 2020

Re-using technique of casting molds for “bronze mirrors with triangular rims and designs of divinities and animals” have been considered. Presence of the same carving decorative patterns have recognized because crack marks of the surface of mirror are comparable. Although this technique was applied for casting of bronze mirrors in ancient Japan, it was presence in the Linzi site in Early Han Dynasty in China.
Samurai’s Swords, a Non-Invasive Investigation by Neutron Techniques
Authors: Salvemini Filomena , Luzin Vladimir , Avdeev Maxim , Tremsin Anton , Sokolova Anna , Gregg Alexander , Wensrich Chris M. , Gatenby Sue , Kim Min Jung , Grazzi Francesco
Published: March 2020

A synergic combination of neutron techniques was applied to characterize non-invasively the laminated structure of a set of ancient katana, part of the East Asian Collection of the Museum of Applied Arts and Sciences (MAAS) in Sydney. Neutron tomography, diffraction, residual stress and Bragg-edge transmission analyses were undertaken on samples of well-known origin, time period and authorship to create a reference database on the main manufacturing methods developed by Japanese swordsmiths. In the attempt to attributemumei(no-signature) blades basing on a scientific analytical method rather than a stylistic analysis, data from the reference samples were benchmarked against the results obtained from the unknown blade to identify differences and commonalities in the production process.
A Scientific Study of Eastern Zhou Bronze Weapons with Tin-Rich Surface Decoration
Authors: Wang Quan Yu , Chen Yi , O'Flynn Daniel
Published: March 2020

In this paper we examined three bronze weapons with tin-rich surface decoration from the Eastern Zhou period: a sword (1966,0222.1) with a trellis pattern, a spearhead (1947,0712.426) with a hexagonal star pattern in the British Museum collections, and a sword (GT698) with a trellis pattern from a private collection. These weapons may have come from south eastern China, a region renowned for its weaponry production in the Eastern Zhou period, as both their styles and decorations are comparable to the sword of the Yue King Goujian and the spearhead of Wu King Fuchai, two of the most typical objects of this type. The manufacturing and surface tin-rich decoration techniques were investigated using microscopy, X-ray CT imaging, X-ray fluorescence spectrometry, scanning electron microscopy equipped with energy dispersive X-ray spectroscopy, and X-ray diffraction. The results showed that all the objects were made of high tin bronzes. The swords were made by casting a grip around the pre-cast blade and the pommel. The spearhead was an integral casting. The trellis pattern on the swords was probably produced by heating up a tin-rich paste applied to the surface and the thin hexagonal star decoration pattern on the spearhead was probably produced by brush painting with a mercury-tin amalgam followed by heating.
The Many and Various Roles of Manganese in Iron and Steel Production
Authors: Craddock Paul T.
Published: March 2020

Manganese oxide and metallic manganese have made a long and varied contribution to the production of iron and steel through the centuries, long before Sir Robert Hadfield’s alloy manganese steel first produced in 1882. Although quite well known empirically, this contribution has sometimes been misunderstood or misrepresented.The success of some of the early so-called ‘natural steels’ was the presence of manganese oxides in the iron ores used.Manganese oxide was already used as a flux from the early days of the production of crucible steel in Asia and it now appears that it was used as a flux from the inception of the otherwise very different later European crucible steel technologies. After the introduction of crucible steel making in Britain in the 18th century, foreign competitors believed that the reason for the success of the processes used at Sheffield was a secret flux and studies on recently discovered 18th century crucibles in Sheffield have shown that process was indeed fluxed with manganese oxide.The function of manganese in the later European crucible steel industry has been rather overshadowed and confused historically by the very different ‘Carburet of manganese’, a strange concoction, patented by Josiah Heath in 1839 added to iron or steel to purify the metal. At the time the chemistry of the process was misunderstood and many acrimonious and inaccurate claims were made, crucially confusing the very different functions of manganese oxide and manganese metal, overshadowing the part already played by manganese oxide for almost a century previously..Finally manganese and its salts played a crucial role in the Bessemer process of steel making.
Effectiveness and tolerability of focal versus radial extracorporeal shock wave therapy in patients affected by plantar fascia enthesopathy
Authors: Pisani Edoardo , Curci Claudio , Moretti Antimo , Mazzola Anna , Paoletta Marco , Liguori Sara , Iolascon Giovanni
Published: March 2020

Plantar fascia enthesopathy is the most common cause of heel pain. Extracorporeal shock wave therapy (ESWT) is widely used in patients affected by this condition. The aim of this study was to compare efficacy and tolerability of ESWT modalities in the treatment of plantar fasciitis. We included 42 patients receiving 1 session of focused ESWT (f-ESWT group) or radial ESWT (r-ESWT group) per week for 3 weeks. Pain assessment was performed at baseline, before each session, and 1 month after the last session using brief pain inventory (BPI) severity index, and interference index (II). Tolerability was defined in terms of patient discomfort after treatment assessed by numeric rating scale at baseline and after each session. Plantar fascia changes in ultrasonography were further investigated. A significant reduction of BPI-II (P<0.001) was reported in both groups, although no between-group differences were found. Plantar fascia thickness showed significant reduction only in the f- ESWT group (P=0.028). Patient’s tolerability was significantly better in the r-ESWT group (P<0.05). Our study confirms that ESWT is effective for reducing pain and disability in patients affected by plantar fasciitis, although r- ESWT seems to be better tolerated.
The predictive efficacy of multidimensional prognostic index in the elderly with heart failure and reduced ejection fraction in a real world sample: the Post-Acute Long-Term Care setting
Authors: Pittui Eleonora , Dore Caterina , Mameli Irene , Scuteri Angelo , Dettori Marco , Uneddu Antonio
Published: March 2020

The multidimensional prognostic index (MPI) is an accurate predictor of mortality validated in hospitalized older patients. Aim of this study was to evaluate the reliability of the MPI in predicting shortand long-term mortality in patients with heart failure (HF), particularly in those with reduced left ventricular ejection fraction (HFrEF). The study population included all patients older than 65 years admitted in a Post-Acute Long-Care Unit from 2013 to 2018. Patients were divided into two groups: patients with HF (N=143) and patients without HF as controls (N=1254). Furthermore, patients affected by HF were subdivided according to echocardiographic left ventricular ejection fraction (LVEF), i.e. reduced, mid-range and preserved LVEF (respectively HFrEF, HFmrEF, HFpEF). All patients underwent a comprehensive geriatric assessment (CGA) to calculate the MPI based on information on functional, cognitive, nutritional and mobility status, comorbidity, poli-pharmacy and co-habitation. Mortality rates in the HF group was 46% in patients MPI-1 or MPI-2 groups versus 59% in patients included in the MPI- 3 group. In particular, of 32 HF patients with HFrEF 67.7% were in the MPI-3 class compared to 43% of 14 patients with HFmrEF group and to 41% of 63 patients with HFpEF. These findings suggest that MPI is a reliable predictor of mortality in HF patients and that it was particularly useful in the subgroup of patients with HFrEF.
Devising a Pace-Based Definition for “The Wall”: An Observational Analysis of Marathoners' Subjective Experiences of Fatigue
Authors: Doherty Cailbhe , Keogh Alison , Smyth Barry , Megyesi Peter , Caulfield Brian
Published: March 2020

Context

Many runners report “hitting The Wall” (HTW) during a marathon (42.2 km). However, the performance manifestation of this subjectively experienced phenomenon remains unclear.

Objective

To identify a pace-based classification for HTW by integrating subjective reports of fatigue and runners' pacing profiles during a marathon.

Design

Cross-sectional study.

Setting

Public race event (2018 Dublin Marathon).

Patients or Other Participants

Eighty-three runners (28 [34%] women, 55 [66%] men, age = 41.5 ± 9.1 years, height = 1.73 ± 0.09 m, mass = 70.2 ± 10.1 kg).

Main Outcome Measure(s)

The pacing profiles for respondents to our postrace questionnaire that concerned the phenomenon of HTW were evaluated. Receiver operating characteristic analyses were performed on discretized outcomes of the time series of marathoners' paces during the race.

Results

Using the receiver operating characteristic analyses, we observed that runners could be classified as having experienced HTW if they ran any 1-km segment 11% slower than the average of the remaining segments of the race (accuracy = 84.6%, sensitivity = 1, specificity = 0.6) or if the standard deviation of the normalized 1-km split times exceeded 0.0532 (accuracy = 83%, sensitivity = 0.818, specificity = 0.8). Similarly, runners could be classified as having experienced HTW if they ran any 5-km segment 7.3% slower than the average of the remaining 5-km segments of the race (accuracy = 84.6%, sensitivity = 1, specificity = 0.644) or if the standard deviation of the normalized 5-km split times exceeded 0.0346 (accuracy = 82%, sensitivity = 0.909, specificity = 0.622).

Conclusions

These pace-based criteria could be valuable to researchers evaluating HTW prevalence in cohorts for whom they lack subjective questionnaire data.