bluuebunny/crossref_metadata_2025 huggingface dataset:
Enabling Rapid Classification of Social Media Communications During Crises
Authors: Imran Muhammad , Mitra Prasenjit , Srivastava Jaideep
Published: March 2020

The use of social media platforms such as Twitter by affected people during crises is considered a vital source of information for crisis response. However, rapid crisis response requires real-time analysis of online information. When a disaster happens, among other data processing techniques, supervised machine learning can help classify online information in real-time. However, scarcity of labeled data causes poor performance in machine training. Often labeled data from past event is available. Can past labeled data be reused to train classifiers? We study the usefulness of labeled data of past events. We observe the performance of our classifiers trained using different combinations of training sets obtained from past disasters. Moreover, we propose two approaches (target labeling and active learning) to boost classification performance of a learning scheme. We perform extensive experimentation on real crisis datasets and show the utility of past-labeled data to train machine learning classifiers to process sudden-onset crisis-related data in real-time.
Empirical Evaluations of Interactive Systems in Cultural Heritage
Authors: Koutsabasis Panayiotis
Published: March 2020

An increasing number of interactive systems aim to enhance the user experience (UX) of visitors at museums, archaeological places and cultural sites. This paper presents a review of empirical evaluations of interactive systems in cultural heritage (CH) based on a systematically selected sample of 53 publications from 2012-2016. Empirical evaluations examine the degree an interactive system satisfies user goals and expectations and are inherently complex activities that require careful planning and selection of methods. The review reports on (a) interactive systems of CH in terms of: purpose, technology, cultural content and location of interaction and (b) methods of empirical evaluation in terms of: dimensions of UX, general approach, data collection and participants. The paper provides discussion, critique and outlook on issues including: extending the evaluation dimensions towards the cultural value and the essence of interactivity; placing more consideration on CH professionals; identifying new evaluation methods that balance qualitative results to evidence-based approaches.
Generating Efficient Techniques for Information Extraction and Processing Using Cellular Automata
Authors: Paul Subrata , Mitra Anirban
Published: March 2020

The evolution of Cellular automaton has proved to be very efficient in carrying out arbitrary information processing. A significant application lies in the theory and practice of finding a technique for unifying the information processing. But, in this case the structures used in conventional computer languages are largely inappropriate. The definite organization of computer memory into named areas, stacks, and so on, is not suitable for cellular automata in which processing elements are not distinguished from memory elements. Rather it can be assumed that the data could be represented by an object like a graph, on which transformations can be performed in parallel. This chapter initiate with basic literature on cellular automata, related definitions and notations and focuses on its applications in information processing.
Real-Time Streaming Data Analysis Using a Three-Way Classification Method for Sentimental Analysis
Authors: Hiriyannaiah Srinidhi , Siddesh G.M. , Srinivasa K.G.
Published: March 2020

This article describes how recent advances in computing have led to an increase in the generation of data in fields such as social media, medical, power and others. With the rapid increase in internet users, social media has given power for sentiment analysis or opinion mining. It is a highly challenging task for storing, querying and analyzing such types of data. This article aims at providing a solution to store, query and analyze streaming data using Apache Kafka as the platform and twitter data as an example for analysis. A three-way classification method is proposed for sentimental analysis of twitter data that combines both the approaches for knowledge-based and machine-learning using three stages namely emotion classification, word classification and sentiment classification. The hybrid three-way classification approach was evaluated using a sample of five query strings on twitter and compared with existing emotion classifier, polarity classifier and Naïve Bayes classifier for sentimental analysis. The accuracy of the results of the proposed approach is superior when compared to existing approaches.
Political Sentiment Mining
Authors: Bele Nishikant , Panigrahi Prabin Kumar , Srivastava Shashi Kant
Published: March 2020

Investigations on sentiment mining are mostly ensued in the English language. Due to the characteristics of the Indian languages tools and techniques used for sentiment mining in the English language cannot be applied directly to text in Hindi languages. The objective of this paper is to extract the political sentiment at the document-level from Hindi blogs. The authors could not find any literature about extracting sentiments at the document-level from Hindi blogs. They extracted opinion about one of India's very famous leaders who was a prominent face in the national election of 2014. They prepared the datasets from Hindi blogs reviews. They purposed the lexicon and machine learning technique to classify the sentiment. Their purposed method used four steps: (1) Crawling and preprocessing the blog reviews; (2) Extracting reviews relevant to the query using the Vector Space Model (VSM); (3) Identifying sentiment at the document level using the Lexicon method, and (4) Measuring the result using the Machine learning technique. Their experimental result demonstrates the effectiveness of our algorithms.
Subjective Text Mining for Arabic Social Media
Authors: Hathlian Nourah F. Bin , Hafez Alaaeldin M.
Published: March 2020

The need for designing Arabic text mining systems for the use on social media posts is increasingly becoming a significant and attractive research area. It serves and enhances the knowledge needed in various domains. The main focus of this paper is to propose a novel framework combining sentiment analysis with subjective analysis on Arabic social media posts to determine whether people are interested or not interested in a defined subject. For those purposes, text classification methods—including preprocessing and machine learning mechanisms—are applied. Essentially, the performance of the framework is tested using Twitter as a data source, where possible volunteers on a certain subject are identified based on their posted tweets along with their subject-related information. Twitter is considered because of its popularity and its rich content from online microblogging services. The results obtained are very promising with an accuracy of 89%, thereby encouraging further research.
Data Accuracy Considerations with mHealth
Authors: Sako Zaid Zekiria , Karpathiou Vass , Adibi Sasan , Wickramasinghe Nilmini
Published: March 2020

With the plethora of mHealth solutions developed being digital, this necessitates the need for accurate data and information integrity. Lack of data accuracy and information integrity in mHealth can cause serious harm to patients and limit the benefits of such promising technology. Thus, this exploratory study investigates data accuracy and information integrity in mHealth by examining a mobile health solution for diabetes, with the aim of incorporating Machine Learning to detect sources of inaccurate data and deliver quality information.
Machine Learning Applications in Cancer Therapy Assessment and Implications on Clinical Practice
Authors: Gangeh Mehrdad J. , Tadayyon Hadi , Tran William T. , Czarnota Gregory Jan
Published: March 2020

Precision medicine is an emerging medical model based on the customization of medical decisions and treatments to individuals. In personalized cancer therapy, tailored optimal therapies are selected depending on patient response to treatment rather than just using a one-size-fits-all approach. To this end, the field has witnessed significant advances in cancer response monitoring early after the start of therapy administration by using functional medical imaging modalities, particularly quantitative ultrasound (QUS) methods to monitor cell death at microscopic levels. This motivates the design of computer-assisted technologies for cancer therapy assessment, or computer-aided-theragnosis (CAT) systems. This chapter elaborates recent advances in the design and development of CAT systems based on QUS technologies in conjunction with advanced texture analysis and machine learning techniques with the aim of providing a framework for the early assessment of cancer responses that can potentially facilitate switching to more efficacious treatments in refractory patients.
Advancing Malware Classification With an Evolving Clustering Method
Authors: Chen Chia-Mei , Wang Shi-Hao
Published: March 2020

This article describes how honeypots and intrusion detection systems serve as major mechanisms for security administrators to collect a variety of sample viruses and malware for further analysis, classification, and system protection. However, increased variety and complexity of malware makes the analysis and classification challenging, especially when efficiency and timely response are two contradictory yet equally significant criteria in malware classification. Besides, similarity-based classifications exhibit insufficiency because the mutation and fuzzification of malware exacerbate classification difficulties. In order to improve malware classification speed and attend to mutation, this research proposes the ameliorated progressive classification that integrates static analysis and improved k-means algorithm. This proposed classification aims at assisting network administrators to have a malware classification preprocess and make efficient malware classifications upon the capture of new malware, thus enhancing the defense against malware.
Intelligent Transportation System
Authors: Agarwal Parul , Hassan Syed Imtiyaz , Ahmed Jawed
Published: March 2020

Today, the technology is moving at a fast pace and has also changed the pace at which the commuter is moving. No longer is the commuter ready to waste time and resources while travelling. This has led to a revolution in the transport sector. ICT, smart devices, and different enabling technologies make intelligent transport systems (ITS) a reality. If well implemented, they can save time and money, help to reduce the environmental threats, and also create business opportunities for many. Today's era is an era of revolution, technological advances, Internet, digitalization, mobile communications, big data, and an era of harnessing the potentials of Cloud Computing. Realizing the benefits of each of these and their utilization and need, a global potential for a powerful and less costly ITS has to be created. This chapter shall give a complete insight into the ITS: its history, components, benefits, issues, and challenges. It would also discuss the future that is in store for ITS but with a realization that the environment is not at stake.
Novel Congestion Control Model for Maintaining Quality of Service in MANET
Authors: Rashid Mamoon , Rashid Aabid , Gupta Sachin Kumar
Published: March 2020

This chapter is related to quality of service in the network. The congestion is the factor which affects quality of service in the network. The AODV is the routing protocol used to establish path from source to destination. To maintain quality of the service, novel approach is proposed. The technique of back propagation is proposed in this work for the congestion avoidance in the network. The back propagation algorithm calculates changes of congestion on each node in network. The node with the least chances of congestion is selected for path establish from source to destination. The proposed approach is implemented in network simulator version 2 and results are analyzed in terms of throughput, packet-loss, delay, and load. It is analyzed that network throughput is increased, packet-loss, delay, and load is reduced in the proposed methodology as compared to state-of-art.
Open Threads-Enabled Mesh Networks in Vehicles for Real-Time Traffic Monitoring
Authors: Choudhary Parul , Dwivedi Rakesh kumar , Singh Umang
Published: March 2020

The exponential increase of traffic on roads has led to numerous disastrous consequences. These issues demand an adaptive solution that ensures road safety and decreases the traffic congestion on roads. New paradigms such as Cloud computing and internet of things are aiding in achievement of the inter-communication among the vehicles on road. VANETs are designed to provide effective and efficient communication systems to develop innovative solutions but are restricted due to mobility constraints. This chapter proposes an IP-based novel framework composed of open threads integrated with VANETs exchanging information to create a mesh network among vehicles. This novel Open Threads-based infrastructure can help in achieving a more economical, efficient, safer, and sustainable world of transportation which is safer and greener. This chapter also discusses and compares various thread-enabled microcontrollers by different vendors that can be utilized to create a mesh network.
Vehicular Cloud and Fog Computing Architecture, Applications, Services, and Challenges
Authors: Gaba Priyanka , Raw Ram Shringar
Published: March 2020

VANET, a type of MANET, connects vehicles to provide safety and non-safety features to the drivers and passengers by exchanging valuable data. As vehicles on road are increasing to handle such data cloud computing, functionality is merged with vehicles known as Vehicular Cloud Computing(VCC) to serve VANET with computation, storage, and networking functionalities. But Cloud, a centralized server, does not fit well for vehicles needing high-speed processing, low latency, and more security. To overcome these limitations of Cloud, Fog computing was evolved, extending the functionality of cloud computing model to the edge of the network. This works well for real time applications that need fast response, saves network bandwidth, and is a reliable, secure solution. An application of Fog is with vehicles known as Vehicular Fog Computing (VFC). This chapter discusses cloud computing technique and its benefits and drawbacks, detailed comparison between VCC and VFC, applications of Fog Computing, its security, and forensic challenges.
The Effect of Artificial Intelligence on Management Process
Authors: Sundu Mustafa , Ozdemir Sebnem
Published: March 2020

Artificial intelligence has started to dominantly affect every sector in Industry 4.0. However, the adaptation of the concept to managerial processes are closely related to the concepts of data science and digital transformation. Because artificial intelligence applications being developed are within the scope of artificial narrow intelligence (ANI), that situation requires the company to have a digital transformation policy in order to use artificial intelligence in managerial processes. In addition, to avoid biased artificial intelligence applications, the learning set of artificial intelligence requires a highly rigorous design. This necessitates the establishment of a data science department within the company. In this chapter, digital transformation processes in managerial perspective and the surrounded effect of artificial narrow intelligence on management are discussed.
Sustainability of SMEs and Health Sector in a Dynamic Capabilities Perspective
Authors: Akkaya Bülent , Üstgörül Sema
Published: March 2020

In Industry 4.0, enterprises have economic, social, and environmentally sustainable policies, and the implementation of these policies may lead to raising the national economy and society welfare. It can be achieved by firms' dynamic capabilities. Therefore, structuring of the activities of enterprises, especially SMEs and health sector organizations within the framework of sustainability and establishing standards by establishing control mechanisms, plays an important role in the development of the country. One of the most important responsibilities of managers in these sectors in implementing sustainable policies is to utilize the dynamic capabilities of the organization. In this context, it is necessary to have knowledge about what dynamic capabilities are and their relationship with sustainability. This study discusses the relationship between dynamic capabilities and sustainability of SMEs and the firms in health sector.
Health 4.0
Authors: Ahmad Sahrish , Halim Hasliza Abdul , Khan Mohammad Jamal , Ahmad Noor Hazlina
Published: March 2020

In the new era of Industry 4.0 and on the basis of current knowledge about innovation in Industry 4.0, it has become a pretty clear that Industry 4.0 had a major impact on the manufacturing sector. At its origin, this industry is evolving from manufacturing to service providers. This chapter explains how innovation of new digital services such as Industry 4.0 integrates towards the healthcare system such as Health 4.0 in India. Although innovation is significant among the manufacturing sector, the practice of this concept is still lacking among the service sector such as hospitals. This study will investigate the impact of organizational learning on horizontal technology collaboration and vertical technology collaboration. The study is designed as a quantitative study and the non-probability purposive sampling technique was used. The data was collected from the doctors of small and medium private hospitals. The findings of data analysis reveal that organizational learning has significant positive impact on horizontal technology collaboration and vertical technology collaboration.
Cultural Elements in Spanish SME Websites and Social Media
Authors: Castillo Rodríguez Celia , Olvera-Lobo María Dolores , Moya-Molina Elena
Published: March 2020

The establishment of a professional online corporate presence is an indispensable step for most companies. However, this online presence must consider linguistic, cultural, and technical differences, as well as variations in user expectations across markets. The language industry has responded to these needs by offering two services, namely localization and transcreation, which may act as valuable tools for the adaptation of corporate communications and whose benefits may be particularly advantageous for smaller companies. This study analyzes the application of localization and transcreation processes and strategies in the corporate context, with a focus on Spanish SMEs and English-speaking markets. Results suggest that the signs of the application of these activities in the corporate online field are still scarce. Furthermore, the online presence of both Spanish SMEs and large US corporations show numerous deficiencies, such as partial translations, typos, a non-updated use of social media, and little adaptation to the addressed markets.
NARX Neural Networks Model for Forecasting Daily Patient Arrivals in the Emergency Department
Authors: Yucesan Melih , Mete Suleyman , Serin Faruk , Celik Erkan , Gul Muhammet
Published: March 2020

Regarding measuring of service quality at the emergency departments (ED), essential parameters are length of stay (LOS) and waiting times. Patient arrivals, which is related to LOS and waiting times, is hard to forecast and is affected by many parameters. Therefore, authors employed a Nonlinear Autoregressive Exogenous (NARX) model for forecasting of ED arrivals. NARX models are used extensively in many applications that show non-linear and dynamic behavior, but as far as authors know, the NARX method has not yet been used in the forecast of ED arrivals before. In this study, calendar and climatic variables are defined as input parameters. Patient Arrivals is defined as output parameter. A commercial software, MATLAB, was used to train and test the data set. To find the best network architecture Levenberg-Marquardt (LM) and Bayesian Regularization (BR) algorithms, different lags, and number of neurons were tested. R-squared and mean square error (MSE) are used to evaluate the accuracy of the tested networks.
Computational Intelligence Approach for Classification of Diabetes Mellitus Using Decision Tree
Authors: Pekel Engin , Özmen Ebru Pekel
Published: March 2020

Diabetes mellitus (DM) is a group of metabolic disorders with one common manifestation: elevated blood sugar or hyperglycemia. The diagnosis of diabetes is the most crucial point due to chronic hyperglycemia. This chapter improves the performance of the Classification and Regression Trees (CART) algorithm because the accurate classification of diabetes depends on the algorithm efficiency. Authors use the accuracy rate for the objective function in the prediction process by Genetic Algorithm (GA). The proposed GA-CART algorithm provides the best performance at 96.05%.
Interval Type II Fuzzy Number Generation From Data Set Applied to Sedation Stage Classification
Authors: Nasibov Efendi , Peker Sinem
Published: March 2020

There are several ways to summarize the data set by using measures of locations, dispersions, charts, and so on. But how can the data set be represented or shown when uncertainty exists in the environment process? Usage of the fuzzy number can be a way to handle the uncertainty in the representation of the data set. This chapter focuses on the membership function construction from the data set and introduces the formulas for the interval Type-2 generalized bell-shaped fuzzy number generation based on the data set. The bispectral index scores (BIS) are processed to see the ability of the offered methods in the construction of the interval Type -2 generalized bell-shaped membership function in the real data set. The obtained membership functions are used for a classification problem of sedation stages according to BIS data sets. Classification accuracies are calculated.
Smart Cataract Detector
Authors: Manikandakumar M.
Published: March 2020

Eyes react to light. Cataract, a common eye disease, clouds the lens of the eye, which decreases vision and can cause blindness. It can be in one or both eyes. The most major cause of cataract is ageing. Cataract also can be found in children and can occur due to eye injuries and inflammation. As mobile technology emerges to a greater extent, designing an application would help people perform a self check-up without meeting the doctors in person, thus saving time and cost. The pre-diagnosis of cataracts is costly for poor people. Time taken by the machine to detect cataract is greater, so the doctor can't attend as many patients. A cheap, reliable mobile application that helps diagnose cataract would cut cost and simplify diagnosis. This chapter proposes the development of smart phone application to detect the presence of cataract using image processing techniques.
A Survey and Analysis to Find Dental Implant Issues in India
Authors: Satapathy Suchismita
Published: March 2020

Presently, dental implantations are the ideal solution and best substitute option for missing teeth. Dental implants determined the replacements of root and non-working teeth after the loss of natural teeth. Strengthening dental materials helps to fix the loss teeth. For teeth with root disease and fault in bone density, dental implantation is very essential. While bridge work and dentures decline to reclaim the suitable chewing condition and turn the problem of missing teeth, dental implants trace the solution of missing teeth. For more progress in dental-concerned technology, an extensive growth in dental implants has been noticed during the last several years. So there is a large need of excellent, quality dental materials. The selection of the implant materials, their generation system, manufacturing method, age-long durability, bio compatibility with medical principle, and professional dental field of study are therefore essential.
Intelligent Manufacturing Systems Driven by Artificial Intelligence in Industry 4.0
Authors: Banjanović-Mehmedović Lejla , Mehmedović Fahrudin
Published: March 2020

Intelligent manufacturing plays an important role in Industry 4.0. Key technologies such as artificial intelligence (AI), big data analytics (BDA), the internet of things (IoT), cyber-physical systems (CPSs), and cloud computing enable intelligent manufacturing systems (IMS). Artificial intelligence (AI) plays an essential role in IMS by providing typical features such as learning, reasoning, acting, modeling, intelligent interconnecting, and intelligent decision making. Artificial intelligence's impact on manufacturing is involved in Industry 4.0 through big data analytics, predictive maintenance, data-driven system modeling, control and optimization, human-robot collaboration, and smart machine communication. The recent advances in machine and deep learning algorithms combined with powerful computational hardware have opened new possibilities for technological progress in manufacturing, which led to improving and optimizing any business model.
Design of Facility Layout for Industry 4.0
Authors: Ficko Mirko , Berus Lucijano , Palčič Iztok , Klančnik Simon
Published: March 2020

The concept of Industry 4.0 combines a large number of fully or partly autonomous devices and humans into a system, which is, due to synergies, more flexible and effective than a fully automated system. To reach this objective we have to ensure such facility layout that ensures an efficient transport system which takes into account the large number of participants. The most important design goal is to minimise the path travelled by transport devices. In the case of Industry 4.0 we have two altered conditions: the number of devices (machines, workplaces, storages) connected in one system is substantially larger, and autonomous transport devices and humans have different organisational needs regarding the facility layout. This chapter presents a highly efficient method for preparation of layouts that is based on simplified space and the physical appearance of the system. The design of transportation paths will be subjected to finding the optimum layout of devices to lower transportation costs.
Smart Sensors
Authors: Karabegović Isak , Karabegović Edina
Published: March 2020

All companies in the world are facing global competition. In order to keep up with the competition and meet the increasing demands of the market, it is essential that they use new technologies in the production processes (i.e., to implement Industry 4.0). The chapter presents smart sensors that automatically detect errors during the production process. Smart sensors communicate via IO-Link in stable communication, whereas the technology itself offers numerous practical benefits in everyday industrial work. Sensors are excellent data collectors and highly intelligent analysts that share their knowledge with their environment through an integrated real-time IO-Link interface. With the implementation of smart sensors in production systems, they become flexible production systems, contribute to the rapid start-up of the process, are automatically adjusted, enable digital data transmission, and can verify the device and the records.
Distributed Energy Resource Management System Based on Discrete Event Simulation
Authors: Šinko Simona , Kragelj Dušan , Radić Ivana , Gajšek Brigita , Kramberger Tomaž , Rupnik Bojan
Published: March 2020

Nowadays, there is more and more discussion about Industry 4.0. The introduction of which could result into growing larger power consumption in a world. On the other side, some parts of Industry 4.0 can help to reduce energy consumption with the use of smart grid, internet of things, renewable energy, etc. The future of energy seems to be in the distributed energy resources (DER). The chapter presents the use of DER on the example of hospital, which are considered as the biggest consumer of energy in commercial sector. Because of important role of understanding the energy consumption, there is an emphasis on the energy modeling and analysis. The chapter provides a new approach in the modelling of energy with the discrete even simulation in which energy is presented by logistics packages, where every package presents a unit of energy. Basic analyses that can be made with the model are presented.
Investigation of Operational Characteristics of Mechatronic Systems in Industry 4.0
Authors: Turmanidze Raul , Dašić Predrag V. , Popkhadze Giorgi
Published: March 2020

This work presents the results of an analysis of the main expected potential problems that may occur in the implementation of the Industry 4.0 reform. It is proved that the pace and level of development of this reform will largely be determined by the effectiveness of the used mechatronic systems. It has also been established that as a result of systematic miniaturization of the nodes of radio-electronic equipment and microelectronic equipment and microelectronic technology, the main problem of these reforms and the implementation of complex technological processes is instrumental support, especially cutting micro-tools. Therefore, the examples of these micro-tools show methods for improving their performance characteristics.
Implementation of Industry 4.0 in Transformation of Medical Device Maintenance Systems
Authors: Gurbeta Pokvic Lejla , Spahic Lemana , Badnjevic Almir
Published: March 2020

Due to the development of information communication technologies (ICT), the number of medical devices (MDs) with telemetric possibilities is rising, so the concept of homecare is gaining importance. Also, new generation medical devices are equipped with artificial intelligence that is able to perform real-time analysis of measurement result and provide diagnosis prediction. This is the Industry 4.0 happening now. However, there is still traditional approach in management of medical devices. As medical devices have been sophisticated, management systems should improve so they can encompass all the important aspects regarding safety of patients and quality of care. This chapter presents how the technology of Industry 4.0 can be used to improve medical device maintenance systems by application of artificial intelligence (AI). Clinical engineering and health technology management departments benefit from such systems in terms of increase of safety and quality of patient diagnosis and treatments, and cost optimization in medical device management.
Creativity and Innovation in Educating Engineers and Product Designers of the 21st Century for the Fourth Industrial Revolution
Authors: Kovačević Ahmed
Published: March 2020

Industry 4.0 is the trend towards automation and data exchange in manufacturing technologies and processes. It requires engineers and product designers trained for the challenge. Collaborative design in virtual environment (CODEVE) is a teaching methodology developed for this within the European Global Product Realization (EGPR) course since early 2000. Each year, an academic virtual enterprise of participating European universities and an industrial partner is formed, and students distributed in international teams. Educational and project tasks are performed through virtual communication tools. The CODEVE methodology was tested on design of consumer products, service-driven products, and industrial machinery. Its evaluation was supported by the Erasmus+ funded project called Networked Activities for Realization of Innovative Products (NARIP) from 2015-2017. As explained in this chapter, it enables students to work for industry, encourages them to understand and explore methods related to Industry 4.0, and helps them to overcome barriers of distributed environment.
Prejudice, Discrimination, and Alienation in Educational Environments
Authors: Yılmaz Didem Çelik , Argon Türkan
Published: March 2020

In today's societies where cultural singularity is almost destroyed, diversity can be an important richness, thanks to individuals displaying peace-based approaches. Schools are affected by this diversity and will continue to be cultivated as small but highly effective stakeholders of the social structure. It can be said that it is important for educational organizations to gain human values before teaching theoretical lessons to their students and that the necessary studies should be carried out both for school administrators and teachers and for students. First of all, raising awareness on this issue is a great need during the construction of the peace society. Therefore, in addition to contributing to the literature with this study, it is aimed to present different and diverse perspectives of prejudice, discrimination, and alienation of students and teachers, giving examples of cause and effect relationships. It is also aimed to make suggestions to reduce negative impacts and thus to raise awareness on the subject.
What Do Teachers Need to Become a Peace Educator?
Authors: Günçavdı Gizem
Published: March 2020

In the recent era, the borders among countries have become more accessible. This fact makes cultural differences an important issue to be taken into consideration. It is a well-known fact that all of these differences can easily be seen in many communities. Thus, building and keeping peace are very important for any type of communities. In order to manage that, individuals should learn how to be peacemakers. This process is called peace education. This fact brings the importance of the factor of “teacher” to the forefront. Considering these, the qualities of teachers who are peace educators have become an important issue to be discussed. Thus, the aim of this chapter will be identifying what kind of characteristics a teacher should have during peace education process. The “White Pigeon Model” is presented for a peace educator's characteristics. This model includes knowledge, skills, and personal characteristics of a peace educator. They are discussed in detail.
eService-Learning
Authors: Laurie Mandi M.
Published: March 2020

The service-learning pedagogy has flourished in popularity and student outcomes, and with the online student population expanding, institutions of higher learning must develop programs with similar content across both face-to-face and distance-learning applications. Institutions are using eService-Learning (eS-L) programs to address this divide. Commonly reported service-learning outcomes include student's sense of belonging and community engagement, and this chapter aims to present a case with similar outcomes for graduate-level students enrolled in a distance learning course with a substantive service-learning component.
Do Loneliness and Social Connectedness Improve in Older Adults Through Mobile Technology?
Authors: McWhorter Rochell R. , Delello Julie A. , Gipson Christine S. , Mastel-Smith Beth , Caruso Kleanthe
Published: March 2020

About one-fifth of the population in the United States in 2015 will be age 65 or older in 2050 and loneliness may be a contributing factor that inhibits their well-being and overall health. As the number of older adults continues to escalate, information and communication technologies such as smartphones and computers may create an increase in social connectedness leading to a decline in loneliness and social isolation. Results from this pilot study suggest that the older adult participants demonstrated some degree of loneliness. As the older adults used social media to connect with friends, family, and other information of interest, there was an increase in social connectedness for many of the participants, but the intensive iPad intervention was not significant in terms of reducing loneliness for either group over time.
In the Pursuit of Happiness
Authors: Kell Jaclyn Terese
Published: March 2020

How can we foster happiness in a child and what happens if it is not done properly? Newborns have to rely on their parents and others to teach them this emotion from the beginning, and there are some that fail to do so. This chapter discusses the theories and methods used in fostering happiness in children from a young age as well as understanding other challenges. Positive psychology, discovered by Martin Seligman, is currently a new industrialized way of catalyzing a more focused view on infusing life with positive qualities. Other topics concerning happiness stem from positive psychology. It is imperative to understand them and consider them throughout a child's life. Children's minds are constantly developing to understand new things around them. Children aren't going to be happy at all times, and there will be moments when they throw tantrums or have other issues. When these moments occur, it is important for parents, teachers, and other adults to handle them the right way.
How Children Fail
Authors: Hotez Emily
Published: March 2020

In recent years, there has been widespread interest across both the research and public sectors in understanding how to promote children's lifelong success in a range of domains. While a focus on promoting success in children remains salient, equally salient in the research is how children fail—specifically, how children prevail in the face of failure, adversity, and other challenges over time. The chapter explores parenting and family factors that predict grit. This chapter investigates a range of parenting and family factors, including demographic characteristics, parenting behaviors and styles, and family cultural and environmental factors. Based on this research, the chapter provides overarching recommendations to researchers seeking to understand grit in a family context.
The Art of Consumption
Authors: Ashbrook Lauren G.
Published: March 2020

This chapter addresses the many different ways children consume both food and media, and the diverse effects these consumption habits have. This chapter also addresses how the consumption of these two variables are related and have reciprocal effects, which can be damaging, to one another. The negative effects of certain consumption habits can be detrimental for the child and family as a whole. Furthermore, the author discusses the most beneficial practices for children to cultivate in order to develop an overall healthy food and media diet.
The History and Evolution of Infant-Parental Attachment Security
Authors: Nolan Erika
Published: March 2020

From an ethological viewpoint, the term “attachment” refers to the affectional tie developed between two animals that creates a lasting bond. While the term generally refers to animals, for the purpose of this chapter, this term will be used to describe bonds among humans. Mainly, the word attachment will be used to analyze and describe the bond between an infant and his/her primary caregiver. One of the primary characteristics of attachment is the desire to maintain close proximity. This is accomplished through attachment behaviors, which are behaviors that support proximity to the attachment figure.
The Innovation Potential of Communities of Practice in Higher Education
Authors: Bracewell Margot , Cordua-von Specht Isabel , Wilson-Mah Rebecca
Published: March 2020

This chapter applies scholarly reflection to discuss the experiences of faculty and staff who convene, facilitate, and maintain two active but different communities of practice (CoP) in the same university. With a focus on innovation, the authors explore how practice-based, social learning in two different CoPs have supported local change in the organization and contributed to positive outcomes and improved processes. Taking a comparative approach, this chapter explores the practical process aspects associated with convening, facilitating, and maintaining two CoPs, including the varying influences of: scope, structure, leadership and convening, and engagement and participation. The authors discuss and compare how the innovation potential of a CoP is shaped by, and must adapt to, its specific context within the university.
Innovation for Technology-Supported Student Services Delivery
Authors: Andrews-Brown Adrianna
Published: March 2020

Student services are delivered in person, online, synchronously, and asynchronously in order to meet students' varied needs and preferences. Through a critical analysis of relevant literature, this chapter explores how student services units can incorporate technological solutions to ensure students are aware of services and can access them when needed. Technology-enhanced student services are explored through examples in the literature of innovative technological solutions for student services delivery, including leveraging existing institutional systems (learning management systems and customer relationship management systems) to support services for students. The chapter concludes with recommendations for administrators and student services providers.
Changing the DNA of Higher Education Through Innovative Approaches
Authors: Singh Yuvika , Atwal Heena
Published: March 2020

Research shows that despite numerous advantages of creativity for any nation, the higher education system lags in creativity and innovation. Today, the aim is not just to impart knowledge to students, but current time demands that higher educational environments foster innovative cultures to enable creativity and innovation. This chapter provides relevant examples to support the argument that the application of innovative teaching methods has the potential to change the “DNA “of higher education. The author argues that innovation must be an amalgamation of effective teaching and effective learning elements and that innovative education can nurture an “inventive society” by developing and encouraging opportunities for creative actions that promote self-sufficiency.
Real Time Motion Detection for Traffic Analysis Using Computer Vision
Authors: Ashwin Sai C.  , Karthik Srinivas K.  , Allwyn Raja P.
Published: March 2020

Nowadays, as the digital era proliferates, there are a number of traffic violation detection systems built using hardware and software to detect violation of traffic rules. This article proposes an integrated method for traffic analysis by detecting vehicles in the video and tracking their motion for multiple violation detection. The purpose of this integrated system is to provide a method to identify different types of traffic violations and to reduce the number of systems used to record violations. This method receives input from traffic surveillance camera and uses DNN to classify the vehicles to reduce the number of personnel needed to do this manually. The authors have implemented modules which are used to track vehicles and detect violations such as line crossing, lane changing, signal jumping, over-speeding and find illegally parked vehicles. The main purpose of this project is to convert manual traffic analysis into a smart traffic management system.
Sift and Deep Convolutional Features for Closeness-Based Leaf Image Recognition
Authors: Sucithra B.  , Gladston Angelin
Published: March 2020

Plant leaf recognition has been carried out widely using low level features. Scale invariant feature transform techniques have been used to extract the low level features. Leaves that match based on low level features but do not do so in the semantic perspective cannot not be recognized. To address that, global features have been extracted and used using convolutional neural networks. Even then there are issues like leaf images in various illuminations, rotations, taken in different angles, and so on. To address such issues, the closeness among low level features and global features are computed using multiple distance measures and a leaf recognition framework has been proposed. The matched patches are evaluated both quantitatively and qualitatively. Experimental results obtained are promising for the proposed closeness-based leaf recognition framework.
Competition in Monopoly
Authors: Vijayakumar Bharathi S.  , Kulkarni Mugdha Shailendra
Published: March 2020

This research article investigates the impact of using a Monopoly Board Game (MBG) in the teaching-learning process of financial statement analysis (FSA) to information technology management students, who earlier had little or no finance or accounting prior educational background. The subjects were students (N=159) in an Indian University. The study; first, narrated the process of administering MBG; second, quantitatively analyzed the learning experience through a structured questionnaire to validate the research objectives. The study resulted in the creation of three factor-clusters namely cognizance, collaboration, and enthusiasm which impacted students' MBG learning experience over the traditional teaching-learning methods. Results showed that factors relating to cognizance are more impacting than collaboration and enthusiasm. In the future, this research can be extended to advanced finance courses and can be integrated with relevant educational theories that underpin teaching-learning processes in higher education to other disciplines.
Enhancing Student Achievement, Engagement, and Satisfaction Using Animated Instructional Videos
Authors: Cookson April , Kim Daesang , Hartsell Taralynn
Published: March 2020

The purpose of this project was to increase student achievement, engagement, and satisfaction using animated instructional videos in an online general psychology course at a community college. This project not only considered the data collected from student activity tracking, but also examined students' perception of how the videos engaged and helped them remember course material. Collection of data was conducted using a pre-intervention and post-intervention survey, a pre-test, a post-test (mid-term exam), and an online behavior evaluation rubric. A statistically significant increase in scores from pre-test to post-test occurred. Students reported that they preferred the animated instructional videos over the textbook and believed videos helped them remember the material. Overall, the project showed that students enjoyed the videos and many recommended that additional ones be created for the rest of the course. Although time-consuming, instructional videos were worth the effort to keep students engaged and learn course material.
The Environmental Awareness Influence Urban Female's Purchasing Intention of Organic Agricultural Products
Authors: Lai Jing-Jing , Pai Nai-Yuan , Wang Wen-Cheng
Published: March 2020

In 2018, the number of internet users in Taiwan reached 18.66 million. The online rate was 79.2%, which was 0.4% higher than that in 2017. Moreover, the annual growth rate of Taiwan's online shopping market is double digits, suggesting the rapid expansion of online shops and the popular trend in online shopping. Managing a store on the internet platform offers many advantages, such as low operating cost, cheaper fees, greater sources of customers, and keyword marketing. As online shopping becomes prevalent in Taiwan, online shops are considered effective sales channels. Among the online shops, there are many small organic shops operated by farmers, as well as chain organic stores. However, researches on Taiwan's online purchase and sales of organic agricultural products (vegetables and fruits) are very sparse. The subjects were mostly urban women, who are white-collar workers, have middle to upper income levels, a high level of education, and are highly frequent internet shoppers. The findings indicate that in the booming online shopping market, urban women's attitude and perceived behavioral control positively, affect their intention to buy organic agricultural products (vegetables and fruits) online. Chain stores and farmers should consider internet marketing as an important sales channel targeting urban women.