bluuebunny/crossref_metadata_2025 huggingface dataset:
Loss Minimization in Active Distribution Network
Authors: Simachew Bawoke
Published: December 2019

Power loss reduction is an important problem that needs to be addressed with respect to generating electrical power. It is important to reduce power loss using locally generated power sources and/or compensations. This chapter brings a method of presents a method of maximizing energy utilization, feeder loss reduction, and voltage profile improvement for radial distribution network using the active and reactive power sources. Distributed Generation (DG) (wind and solar with backup by biomass generation) and shunt capacitor (QG) for reactive power demand are used. Integrating DG and QG at each bus might reduce the loss but it is economically unaffordable, especially for developing countries. Therefore, the utilization optimization method is required for finding an optimal size and location to feeders for placing QG and DG to minimize feeder loss.
Reliability Assessment of Microgrid-Integrated Electrical Distribution System
Authors: Khan Baseem , Fanuel Mesfin
Published: December 2019

Due to the transition of traditional power system to smart structure, integration of renewable energy sources is of great importance. It is performed by using distributed generators and Micro grid. Integration of renewable sources is very useful for the reliability enhancement of distribution system as energy can be supplied locally at distributed level. Therefore, this chapter provides an overview of various reliability methods which are utilized for finding the impact of renewable energy generation on distribution system reliability assessment. These renewable energy sources are integrated in the distribution system at distributed and Micro grid level. Various characteristics of renewable energy sources are discussed to model them. A general problem of reliability assessment in terms of reliability indices is also discussed.
Reliability Enhancement of Smart Distribution Network Using Reconfiguration
Authors: Anteneh Degarege
Published: December 2019

Electric power should deliver a predicable per condition for the technological, economic, and political development of any countries and it is vital for each individual. Power outage is series problem in Ethiopia at the hole of distribution network. This is due to frequent interruptions and much time service restoration. That is why most customers of Ethiopia have their day-to-day activities highly affected and they are strongly complaining to Ethiopia electric utility daily. But this power outage affected customer cost and the Ethiopian utility. In most developing countries including Ethiopia, distribution systems have received considerably less of the attention to reliability modeling and evaluation than have generating and transmitting systems. Life is directly or indirectly dependent on electric power so a utility should deliver reliable power every day for 24 hours and each year for 8,760 hours to satisfy human needs and to perform their works as much as possible with less economy.
Management of Electrical Maintenance of University Buildings Using Deterioration Models
Authors: Alhassan Bassel Mohamed
Published: December 2019

Buildings maintenance has received increasing international attention in various fields of scientific research. As a result, the maintenance of buildings has changed from the preventive to the predictive approach. This is done through an evaluation model to support and assist the management of the facility in selecting alternatives and making appropriate decisions in maintenance according to building status and maintenance budget. This chapter investigated the reasons for the electrical maintenance of the university buildings and the degree of importance of each element of electrical maintenance through the design of a questionnaire in which the electrical components were divided into elements and then each element was linked to all maintenance items that related to it. At the end of the research, mathematical models were developed, and they help to forecast the electrical maintenance items and distribution of the maintenance budget, and to verify the validity of these models. The models have been applied to study the case of dorm buildings in Tishreen University.
Applied Power Electronics
Authors: Makdisie Carlo Joseph , Mariam Marah Fadl
Published: December 2019

Power Electronics is the study of switching electronic devices and circuits to convert and control the flow of electrical energy. Power Electronics is the basic technology of switching power supplies, power converters, power inverters, motor drives, and motor soft starters. Inverters are devices that transform DC input into fixed AC output through changing the trigger angle, in the ideal statues the output wave form is perfect sine wave, however in the practical case it has some higher harmonics that need to be reduced. Inverters are an important part of UPS systems, fully explained in this chapter, where UPSs are uninterruptible Power Supply in which the inverters are included as an essential part, that can provide emergency power to a load when the input power source or main power source fails.
Design of Experiments to Optimize Soxhlet-HTP Method to Establish Environmental Diagnostics of Polluted Soil
Authors: Morales-Bautista Carlos Mario , Méndez-Olán Candelario , López-Martínez Sugey , Ojeda-Morales Marcia E.
Published: December 2019

One of the great challenges of the environmental diagnoses of soils contaminated with hydrocarbons is the optimization of analytical determinations. For this reason, this chapter evaluates the extraction of hydrocarbons by the Soxhlet method through the design of experiments (DOE), variating three different solvents, three soils, and three extraction times. Soil was experimentally contaminated at different concentrations, and hydrocarbons totals relying on conditions organic matter, electrical conductivity, pH and textures, amount of sample, solvents, and NaSO4, were studied. The variables were evaluated by means of an analysis of the Taguchi design and a factorial design, with the results the significant and optimal parameters of the process were determined, which were solvent type and time (10 hours and dielectric constant of 9). Also, the model discards the soil properties. These results will save time and resources, and they reduce errors.
Application of Design of Experiments in Biofuel Production
Authors: Tavizón-Pozos Jesús Andrés , Ibarra Israel S. , Guevara-Lara Alfredo , Galán-Vidal Carlos Andrés
Published: December 2019

Biofuels emerge as an alternative to mitigate climate change. In this sense, four biofuels generations have been proposed to produce clean and renewable fuels. To achieve this, the development of these fuels requires an extensive and rigorous experimental work that will bring optimal results in short time periods. Hence, to accelerate the development of clean fuels, the Design of Experiments (DoE) methodologies are a useful tool to improve the operational conditions such as temperature, time, pressure, and molar ratios. Several authors have studied and optimized the different biofuel production systems using Factorial Designs and Response Surface Design methods and statistical analysis with reliable results. This chapter reviews and classifies the results obtained by these investigations and demonstrates the scopes and limitations of the application of DoE.
The Role of Multivariant Analysis on the Interpretation of FTIR and Raman Spectra
Authors: Celik Sefa , Albayrak Ali Tugrul , Akyuz Sevim , E. Ozel Aysen
Published: December 2019

FTIR and Raman spectroscopy are complementary spectroscopic techniques that play an important role in the analysis of molecular structure and the determination of characteristic vibrational bands. Vibrational spectroscopy has a wide range of applications including mainly in physics and biology. Its applications have gained tremendous speed in the field of biological macromolecules and biological systems, such as tissue, blood, and cells. However, the vibrational spectra obtained from the biological systems contain a large number of data and information that make the interpretation difficult. To facilitate the analysis, multivariant analysis comprising the reduction of the dimension of spectrum data and classification of them by eliminating redundancy data, which are obtained from the spectra and does not have any role, becomes critical. In this chapter, the applications of Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and their combination PCA-LDA, which are widely used among multivariant techniques on biological systems will be disclosed.
Temperature Effects on the Physicochemical Properties and Composition of Fatty Acids in the Oil of Chia Seeds
Authors: Vargas Martínez María Gabriela , Pascual-Bustamante Selene , Beltrán-Orozco María del Carmen
Published: December 2019

Chia seeds have a high content of omega 3, 6, and 9 fatty acids, so their consumption has become popular, often added to products subjected to heat treatments. This chapter evaluated the effect of temperature and time on the physicochemical properties and fatty acid composition of chia seed oil. The seeds, either whole or ground, were subjected to several treatments using a full factorial experimental design 32 where the factors were: the temperature (150, 187, and 225 °C) and treatment time (10, 25 and 40 min), while the studied responses were: iodine, acid, peroxide, and saponification values, Kreis test, and the content of omega 3, 6, and 9, the latter evaluated by gas chromatography. The use of moderate temperatures and short baking times is recommended (150 to 155 °C, less than 14 min) to avoid the loss in essential fatty acids and thus preserve the nutritional value of chia added in functional foods.
Kazakhstani E-Learning Practice in Higher Education
Authors: Yessenova Kamchat , Parker Judith , Sadvakasova Zuhra , Syrgakbaeva Akmaral , Tazhina Gainiya
Published: December 2019

The purpose of the study was to analyze the experience provided by e-learning in a higher education setting in Kazakhstan as viewed by university administrators and graduate school e-learners. Surveys revealed that the e-learners expressed a high interest in study at remote universities. From the standpoint of the administrators, the main challenges of distance education development are the considerable implementation costs, a lack of technical support, the need to train qualified teachers, and a need for the full-fledged development of new courses. Clarifying the implication of these challenges can help administrators develop e-learning classes in universities nationwide. The research results can be applied towards identifying the resources needed for further developing e-learning initiatives for higher education, with the goal of giving universities a competitive advantage.
Introducing Information and Communication Technology Training for Rural Women in South Africa
Authors: Tawiah Sampson , Setlhodi Itumeleng I
Published: December 2019

In a contemporary world, ICT training is vital for socio-economic advancement, which is why it should be included in the curriculum that seeks to empower rural women with computer skills to enhance their livelihoods. Rural women lack access to ICTs and they do not know how to use them. A lack of knowledge and skills in ICTs can result in unemployment, poverty and societal discrimination. Through the lens of the human capital theory, this article investigates and reports on the strategies for introducing ICT in the teaching and learning of rural women. Document analysis approach was used to investigate journals, government policy documents and reports from studies to arrive at the findings which include, among others, the employment of computer experts to teach rural women in disadvantaged communities. The study concludes that the introduction of ICT in the curriculum of rural women especially can ensure their socio-economic transformation.
Latency and Energy Optimization Using MAC-Aware Routing for WSNs
Authors: Hebal Sara , Louail Lemia , Harous Saad
Published: December 2019

Protocols for wireless sensor networks are generally designed following the layered protocol stack where layers are independent. Uncorrelated decisions coming from different layers may affect certain metrics such as the latency of communications, the energy consumption, etc. Cross-layer approaches overcome this problem by exploiting the dependencies between the layers. In this article, the authors propose latency and energy mac-aware routing for wireless sensor networks (LEMAR-WSN), a new cross-layer routing approach using information of the TDMA schedule and exploiting the information of the energy consumed by each node in order to optimize the latency of communications and the energy consumption when relaying information to the sink in a wireless sensor network. Simulation results show that the proposed approach improves the average latency of communications up to 20% and the average.
Enhancing Modeling for Network Selection Using Graph Theory in Beyond 4G Networks
Authors: Lahby Mohamed
Published: December 2019

In recent years, the development and the deployment of different generation systems such as 3G (UMTS, Wi-Fi), 4G (LTE, WIMAX), and 5G have become a reality for different telecommunication operators. At the same time, the development of new mobile devices with multiple interfaces have shifted the behavior of users concerning the utilization of the internet. Additionally, several streaming servers are available to provide real time applications such as e-commerce transactions, video streaming, online gaming, etc. As a result, the users have the privilege to use different multimedia applications at anytime and anywhere. The major trend in Beyond 4G networks is determining the best access network for the end user in terms of quality of service (QoS) during the network selection decision. Thus, in this article, the authors investigate graph theory and the AHP approach to deal with the network selection issue. The experimental results show that the proposed policy can achieve a significant performance in terms of QoS metrics for real-time streaming than conventional algorithms.
The Role of Strategy Implementation in the Relationship Between Strategic Planning Systems and Performance
Authors: Namada Juliana Mulaa
Published: December 2019

While substantial research has been done on strategic planning and performance, there is little research on the moderating role of strategy implementation. This study attempts to bridge this gap. The study adopted a descriptive cross-sectional survey with the firm as the unit of analysis. The findings indicate that strategy implementation moderates the relationship between strategic planning systems and market performance as well as internal business process performance but not on return on investment performance. In conclusion, the configuration of planning systems with its theoretical underpinning as resource bundles explain performance variations among firms. The study's implication for practice is that strategic planning systems should be emphasized by business firms as a configuration and not by its domains.
Marketing in an Economic Downturn – Challenges and Opportunities
Authors: Mandal Pratap Chandra
Published: December 2019

The business environment is uncertain. It becomes even more turbulent during recession. This uncertainty directly affects the investments made by firms. Firms hesitate to invest during a recession because of the belief that the returns will not be commensurate with the investment made. Nevertheless, there are firms which develop strategies and invest during recession. The article discusses various strategies which firms may adopt to survive and also excel during recession. The advantages and the disadvantages of the following those strategies are discussed. The article also focuses on firms which implemented strategies to overcome recession and established themselves in the minds of customers. This article might help firms and practitioners in identifying the most effective strategies to be adopted for excellence during an economic downturn.
Continued Usage and Dependency of Smartphones
Authors: Rosaline Salini , Johnson Samuel
Published: December 2019

Smartphones have become an integral part of everyone's life. Being a powerful communication device, the number of subscribers is persistently increasing every year. Younger generation are often the early adopters of smartphones. Because of its educational and entertaining options students have adopted them easily. This study aims to identify the factors that lead to student dependency on smartphones and thus leading to continued usage. The data was collected from undergraduate students and was analysed using structural equation modelling (SEM). The results of the study show that performance expectancy, social needs, social influence, convenience has a positive relationship on dependency on smartphones and dependency on smartphones has a positive relationship on continued usage of smartphones. The findings have led to theoretical and practical implications and future researches are suggested.
Empathizing With the Criminally Insane
Authors: Sabourin Randy , Ahmed Rukhsana
Published: December 2019

Arkham Asylum is home to some of popular culture's most notorious super villains. The neglect and inadequate care these villains receive mirrors a real-world context where mental illness is surrounded by stigma, misunderstanding, and poor rehabilitation rates. This study explores the less glossy niches between the action-packed button-mashing on the surface of a popular Batman video game Batman: Arkham Asylum. By pulling back the curtain over the routine treatment of Arkham Asylum's patients (also known as inmates), it presents a set of good practices for improving their care through more effective communication. Recorded audio interviews from the video game constitutes the foundation for this set of good practices tailored to the needs of the fictional facility. Narrative inquiry is used to pull these recommendations from the data. Based on narrative elements found in the data, this study recommends an empathy-driven and preventative approach to treating Gotham's criminally insane population.
Multimedia Image Retrieval System by Combining CNN With Handcraft Features in Three Different Similarity Measures
Authors: Alrahhal Maher , Supreethi K.P.
Published: December 2019

The authors propose WNAHVF, a combined weighted and normalized AlexNet with handcrafted visual features for extracting features from images and using those vectors for image retrieval and classification. The authors test the WNAHVF method on two general datasets, Corel-1k and Corel-10k, and one medical dataset. The outcomes demonstrate combining Bag of Features and Local Neighbor patterns with AlexNet enhances the accuracy and gives better results in general and medical image datasets in retrieval and classification problems. This algorithm gives results that are superior to existing strategies.
Intelligence and Adaptive Global Algorithm Detection of Crowd Behavior
Authors: Chebi Hocine , Tabet-Derraz Hind , Sayah Rafik , Benaissa Abdelkader , Meroufel Abdelkader , Acheli Dalila , Meraihi Yassine
Published: December 2019

The recognition and prediction of people's activities from videos are major concerns in the field of computer vision. The main objective of this article is to propose an adaptive global algorithm that analyzes human behavior from video. This problem is also called video content analysis or VCA. This analysis is performed in outdoor or indoor environments. The video scene can be depending on the number of people present, is characterized by the presence of only one person at a time in the video. We are interested in scenes containing a large number of people. This is called crowd scenes where we will address the problems of motion pattern extraction in crowd event detection. To achieve our goals, we propose an approach based on scheme analysis of a new adaptive architecture and hybrid technique detection movement. The first stage consists of acquiring the image from camera recordings. After several successive stages are applied, the active detection of movement by a hybrid technique, until classification by fuzzy logic is preformed, which is the last phase intervening in the process of detection of anomalies based on the increase in the speed of the reaction of safety services in order to carry out a precise analysis and detect events in real time. In order to provide the users with concrete results on the analysis of human behavior, result experimentation on datasets have validated our approaches, with very satisfying results compared to the other state-of-the-art approaches.
Effective Technique to Reduce the Dimension of Text Data
Authors: Guru D.S. , Swarnalatha K. , Kumar N. Vinay , Anami Basavaraj S.
Published: December 2019

In this article, features are selected using feature clustering and ranking of features for imbalanced text data. Initially the text documents are represented in lower dimension using the term class relevance (TCR) method. The class wise clustering is recommended to balance the documents in each class. Subsequently, the clusters are treated as classes and the documents of each cluster are represented in the lower dimensional form using the TCR again. The features are clustered and for each feature cluster the cluster representative is selected and these representatives are used as selected features of the documents. Hence, this proposed model reduces the dimension to a smaller number of features. For selecting the cluster representative, four feature evaluation methods are used and classification is done by using SVM classifier. The performance of the method is compared with the global feature ranking method. The experiment is conducted on two benchmark datasets the Reuters-21578 and the TDT2 dataset. The experimental results show that this method performs well when compared to the other existing works.
Long-Short Term Neural Network Analysis of Center of Pressure of Gait
Authors: Khan Arshia , Madden Janna
Published: December 2019

Detection of vascular dementia in early stages of cognitive impairment is difficult to do in a clinical setting since the earliest changes are often discrete and physiological in nature. One major aspect of this is gait patterns. This project utilizes force-sensing platforms, motion capture, and EMG sensors to unobtrusively collect biometric data from an individual's walking gait patterns. The data parameters gathered were center of pressure, gait phase and end of unloading/toe-ff events. By quantifying and analyzing machine learning algorithms, specifically deep learning time-series based models, onset patterns of vascular dementia are explored with an overarching goal of creating a system that will assist in understanding and diagnosing cases of vascular dementia. The proposed system provides a tool for which gait can be analyzed and compared over a long period of time and opens opportunity to increased personalization in health monitoring and disease diagnosis and provides an avenue to increase patient-centricity of medical care. Since gait is one of the early predictors of vascular dementia, we developed a long short-term neural network to predict the gait variations from which we can predict the onset of vascular dementia.
An Electronic Medical Record System
Authors: Sarfraz Muhammad , Al-Hussainan Anwar F. , Mohammad Farah , Al-Azmi Hanouf
Published: December 2019

This research proposes, designs, and implements a new online system for electronic medical records (EMR) for assisting the current processes of labs and hospitals. Specific consideration is given to the records of blood donors. It provides an online automated alternate to the traditional manual processes adopted for various medical labs. The proposed system provides an easy way to communicate with the world. The article presents use case diagrams that model the logics of the system. It also proposes schema for supporting databases in the system. The system is prototyped, and ready to be used. To achieve the targeted system, in addition to investigating the latest studies in this area, the needed data was collected through a questionnaire survey with the community. The system, as a special case, has been oriented for the communities of the state of Kuwait to improve its healthcare sector. However, this design can be easily ported to other countries platforms due to its generic formulation.
RETRACTED: AIR POLLUTANTS CONCENTRATION PREDICTION BASED ON TRANSFER LEARNING AND RECURRENT NEURAL NETWORK
Authors: Hang Fong Iat , Fong Simon
Published: December 2019

Air pollution poses a great threat to human health, and people are paying more and more attention to the prediction of air pollution. Prediction of air pollution helps people plan for their outdoor activities and helps protect human health. In this article, long-short term memory recurrent neural networks were used to predict the future concentration of air pollutants in Macau. In addition, meteorological data and data on the concentration of air pollutants were used. Moreover, in Macau, some air quality monitoring stations have less observed data, and some AQMSs less observed data of certain types of air pollutants. Therefore, the transfer learning and pre-trained neural networks were used to assist AQMSs with less observed data to generate neural network with high prediction accuracy. In this thesis, in most cases, LSTM RNNs initialized with transfer learning methods have higher prediction accuracy, used less training time than randomly initialized recurrent neural networks.
MEASURING SIMILARITY BETWEEN BIOMEDICAL DATA BY USING FURIA ENSEMBLES RULE-BASED CLASSIFICATION
Authors: Fong Simon
Published: December 2019

Similarity measures are essential to solve many pattern recognition problems such as classification, clustering, and retrieval problems. Various distance/similarity measures that is applicable to compare two probability density functions. Data comparison is widely used field in our society nowadays, and it is a very import part. To compare two objects is a common task that people from all walks of life would do. People always want or need to find the similarity between two different objects or the difference between two similar objects. Some different data may share some similarity in some given attribute(s). To compare with two datasets based on attributes by classification algorithms, for the attributes, we need to select them out by rules and the system is known as rule-based reasoning system or expert system which classifies a given test instance into a particular outcome from the learned rules. The test instance carries multiple attributes, which are usually the values of diagnostic tests. In this article, we are proposing a classifier ensemble-based method for comparison of two datasets or one dataset with different features. The ensemble data mining learning methods are applied for rule generation, and a multi-criterion evaluation approach is used for selecting reliable rules over the results of the ensemble methods. The efficacy of the proposed methodology is illustrated via an example of two disease datasets; it is a combined dataset with the same instances and normal attributes but the class in strictly speaking. This article introduces a fuzzy rule-based classification method called FURIA, to get the relationship between two datasets by FURIA rules. And find the similarity between these two datasets.
Engaging the Crowd
Authors: Mueller Johannes , Asada Shiho , Tomarchio Ludovica
Published: December 2019

In this article, the challenges of realising e-participatory projects in urban planning are described. A participatory case study in Singapore serves as the basis for their presented conclusions. The researchers used a map-based e-participation tool to collect design proposals from participants for the planning site. The user feedback for the tool interface and the study campaign's website together with designer expertise on user interfaces (UI) was incorporated into the redesign of the website and interface of the participatory design tool. From there, some general guidelines for conducting engagement studies and for designing participatory design tool interfaces for non-expert users were formulated. One key finding is that the information presented to the non-expert user must be concise, and the UI must be adapted to the user's habits and focus the user's attention towards completing the study.
A Review of Quality of Service in Fog Computing for the Internet of Things
Authors: Vambe William Tichaona , Chang Chii , Sibanda Khulumani
Published: December 2019

With the advent of the paradigm of the Internet of Things, many computing elements need many modifications to promote Quality of Service (QoS). Quality of Service is a pillar that promotes real-time reaction to time-critical tasks. Any impediments to QoS should be resolved and handled. In 2012, fog computing was implemented to enhance QoS in current systems in a bid to tackle QoS problems encountered by using cloud computing alone. Currently, the primary focus in fog computing is now on enhancing QoS. The primary goal of this study is, therefore, to critically review and evaluate the literature on the work done to improve elements of QoS in fog computing. This study begins by examining the roots of history, characteristics, and advantages of fog computing. Secondly, it discusses the important elements of QoS parameters. Finally, open problems that still affect fog computing are identified and discussed in order to achieve enhanced QoS.
Improving Career Decision-Making for High School Students Through a Web-Based Expert System
Authors: Asabere Nana Yaw , Amoako Eric
Published: December 2019

Globally, the right and appropriate selection of tertiary programmes by potential students in education corroborates every nation's development progress. In order to explore the effect of career counseling and development in high schools in Ghana with a focus on some selected senior high school (SHS) students, this paper utilized a quantitative (questionnaire) research instrument to corroborate the development a web-based expert system for tertiary programme selection. An analytical summary of questionnaire responses received from the selected SHS students showed that due to limited career assessment processes, SHS students in Accra, Ghana arbitrary select tertiary programmes without realizing how such selections can affect their future careers. In terms of user acceptance testing (UAT), 80% of the selected SHS students (100) found our proposed system to be very useful. Such a system will therefore solve and improve career guidance, counselling, and development problems of SHS students in Ghana.
Challenges and Opportunities in Building a Successful Digital Library in Developing Countries
Authors: Dongardive Prakash Bhagwan
Published: December 2019

The present research work describes the use of the electronic resources by the teaching community at Mekelle University, Ethiopia. The survey was conducted by using questionnaires to collect the data. The questionnaires were administrated to total 1516 on duty teaching faculties of seven colleges. Including the College of Natural and Computational Sciences, the College of Veterinary Medicine, the College of Health Science, the College of Law and Governance, the College of Business and Economics, the College of Language and Social Sciences, College Dry Land Agriculture and Natural Resources as well as nine regular institutes including; the Ethiopian Institute of Technology, the Mekelle Institute of Technology, the Institute of Paleo Environment and Heritage Conservation, the Institute of Pedagogical Sciences, the Institute of Geo-Information and Earth Observation Sciences, the Institute of Environment and Gender Development Studies, the Institute of Population Studies, the Institute for Climate and Society, and the Institute for Water and Environment at Mekelle University. The survey also examines the purpose of use, frequency, difficulties, and availability of electronic information resources subscribed by the Mekelle University Digital Library. Finally, the data was interpreted, concluded, and suggestions have been given for improvement of electronic information resources at library web portal.
Teaching Graduate Technology Management Students With Innovative Learning Approaches Around Cybersecurity
Authors: Burrell Darrell Norman
Published: December 2019

Every year in the U.S., 40,000 jobs for information security analysts go unfilled, and employers are struggling to fill 200,000 other cybersecurity related roles. Colleges and universities have created certificates, undergraduate, and graduate programs to train professionals in these job roles. This issue becomes more complicated when you explore the that competent workers in this field need more than just book knowledge to be effective. Engaged and experiential learning approaches encourages experimentation and expanding teaching cybersecurity beyond the use of just classroom lectures, textbooks, and PowerPoint slides. The use of experiential and scenario-based learning approaches helps students to develop real-world problem solving and critical thinking skills that demonstrate expertise beyond course grades and degrees. Developing the ability to strategic and adaptive is vital to be effective. This case study research intends not to reconstitute theory but to influence the practice of cybersecurity education through the use of innovative applied and engaged learning approaches.
Faculty Videos of Resilience Narratives at Two Institutions
Authors: Wald Hedy S. , Bursch Brenda
Published: December 2019

Burnout and mental health issues among residents are associated with adverse health consequences and suboptimal job performance, e.g. increased medical error. Given role models as key to cultivating resilience, we created faculty resilience narrative videos within resilience skill training programs, hypothesizing such videos would provide new perspectives/insights on resiliency and humanize attendings in a useful way. Child and adult neurology residents at two institutions positively rated the impact of these faculty videos. Such videos are an innovative and practical way to: 1) provide exemplar role models for learning about coping with physician challenges and gaining insights on resilience; 2) access stories of triumph over challenge for inspiration; and 3) work to achieve local culture change by reducing stigma and increase empathy/connection during training. Successful implementation of this video innovation provides good rationale for further evaluation of impact on local culture, faculty experience, and resident attitudes and behavior.
Integrating Service-Learning Pedagogy Into Community College Coursework
Authors: Leonard Timothy , Flink Patrick J.
Published: December 2019

Developmental students face significant academic and life challenges as they pursue a college degree. As students in developmental studies often struggle to complete their courses, research focused on innovative pedagogy that engages students while developing skills is needed. This project sought to investigate implementing an on-campus, service-learning (SL) component into developmental reading courses. Students participated in SL by reading to children at the on-campus Early Childhood Center (ECC) one time per week, during scheduled class, with time provided for structured metacognition through reflective journals. A phenomenological approach was used for this study, and Interpretive Phenomenological Analysis (IPA) was used to examine responses and note trends in data. It was found that students who participated in SL as part of their developmental reading course reported multiple positive effects such as developing a positive academic mindset, improving self-efficacy, and increasing motivation to read.
Another AI? Artificial Imagination for Artistic Mind Map Generation
Authors: Liu Ruixue , Chen Baoyang , Guo Xiaoyu , Chen Meng , Qiu Zhijie , He Xiaodong
Published: December 2019

This article presents a novel real-time, collaborative, and interactive AI painting system, Mappa Mundi, for artistic Mind Map creation. The system consists of a voice-based input interface, an automatic topic expansion module, and an image projection module. Imagination is one of the most important factors which makes an artistic painting unique and impressive. With the rapid development of artificial intelligence, more and more researchers try to create painting with AI technology. However, lacking imagination is still a main problem for AI painting. This research proposes a novel approach to inject rich imagination into a special kind of painting- Mind Map. Lexical and phonological similarities of respective seed words are first considered, then the system learns and inherits the artist's original painting style, and further applies Dadaism and impossibility of improvisation principles into the process. Several metrics for imagination evaluation are then developed later in the article. The result show that this proposed method can increase the imagination of painting and also improve its overall quality.
Corporate Governance and Corporate Social Responsibility Disclosure
Authors: Nour Abdulnaser Ibrahim , Sharabati Abdel-Aziz Ahmad , Hammad Khitam Mahmoud
Published: December 2019

Developed countries are increasingly concerned about the relationship between corporate governance and corporate social responsibility disclosure while developing countries recently started to take care of this issue. Therefore, the main objective of the study is to examine the effect of the board mechanisms of corporate governance on the extent of social responsibility disclosure of Jordanian public industrial companies during the period (2010 to 2014). In this research, descriptive statistics are used to study variables, both correlation matrix and collinearity diagnostic are used to test whether multicollinearity problem exists. Finally, OLS regression analysis is used to test the hypotheses of the study. The results show that the extent of social responsibility disclosure is positively affected by board size and percentage of women on board, negatively affected by duality and board average age. Board meetings and board composition are insignificant to social responsibility disclosure. The study faces several limitations where the measurement of corporate social responsibility requires human judgment, which is subjective and ambiguous. Furthermore, the study sample was limited to industrial companies. Understanding the relationship between CG and CSR is very important because the CG mechanism is an obligation to protect and improve social, economic, and environment, as well as the welfare of society. CSR elements should be included within the companies' vision, mission, strategies and daily practices to maximize the shareholder value.
Disclosure of Environmental Compliance Management on Corporate Websites
Authors: Thimm Heiko Henning , Rasmussen Karsten Boye
Published: December 2019

Environmental disclosure in business has been researched. However, only a few projects have addressed disclosures in connection to the companies' obligations to follow environmental laws, standards, and regulations which is the main objective of the field of corporate environmental compliance management (CECM). This article describes the basis of a systematic literature review and the current state of knowledge about CECM website disclosure. Furthermore, major conceptual and methodological aspects for future disclosure studies are presented. The authors also propose a global CECM data collection and further research directions in order to close today's knowledge gap concerning determining factors and major characteristics of CECM disclosure. The research directions are exemplified by a set of novel questions. Future investigations of these questions through corresponding data analysis on the basis of the proposed CECM data collection will yield new insights that are relevant for researchers, practitioners, and governmental agencies.
Knowledge-Based Service (KBS) Opportunities to Contour Startup Into a Scalable Enterprise
Authors: Yadav Deepak , Das Niladari , Tripathi Paritosh
Published: December 2019

The essential transition step from a startup to a sustainable organization in early-stage entrepreneurs is very crucial. The four stages in the life cycle of an entrepreneurial venture consists of ideation, transition, scaling-up, and growth/exit and is efficiently done by knowledge-based services (KBS). The founding team faced the key challenges which emphasize assessment, validation, and enhancement of the business concept. KBS is a large and fast-growing economy based on businesses and professions which lays a concrete foundation to build a scalable business. KBS are highly recommended opportunities for new venture investment and growth and have created more than 79% out of all nonfarm US jobs. This area has been paid very little attention to entrepreneurship research and education which hampers national economic expansion. This article discusses entrepreneurship education, research and investment in KBS. KBS research work explores exclusive features, opportunities, and challenges in new venture development to a scalable enterprise.
Analysis on Opinion Words Extraction in Electronic Product Reviews
Authors: Aung Sint Sint
Published: December 2019

Online user reviews are increasingly becoming important for measuring the quality of different products and services. Sentiment classification or opinion mining involves studying and building a system that collects data from online and examines the opinions. Sentiment classification is also defined as opinion extraction as the computational research area of subjective information towards different products. Opinion mining or sentiment classification has attracted in many research areas because of its usefulness in natural language processing and other area of applications. Extracting opinion words and product features are also important tasks in opinion mining. In this work an unsupervised approach was proposed to extract opinions and product features without training examples. To obtain the dependency relation between the product aspects and opinions, this work used StanfordCoreNLP dependency parser. From these relations, rules are predified to extract product and opinions. The main advantage of this approach is that there is no need for training data and it has domain independence. Acoording to the experimental results, the modified algorithm gets better results than the double propagation algorithm.
An Exploration of the Relationships Between Different Reading Strategies and IELTS Test Performance
Authors: Marjerison Rob Kim , Liu Pengfei , Duffy Liam P. , Chen Rongjuan
Published: December 2019

This study explores which types of IELTS Academic Reading strategies are used, and the impact of these strategies on test outcomes. The study was a quantitative research, using descriptive-correlational design based on data collected from students at Sino-US University in China. Descriptive and inferential statistics were used to analyze the data. The method used in this study was a partial replication the work of a previous researcher's exploration of the reading processes learners engage in when taking IELTS Reading tests. Participants first finished an IELTS reading test, and then completed a written retrospective protocol. The analysis reveals that there is a moderately positive relationship between the choice of text preview strategy (from 1 to 5) and the outcome. A pattern was identified that using expeditious reading strategies to initially locate information, and more careful reading strategies to identify answers to the question tasks was common among high-scoring participants.
Analysis of Speeches by the Former President of the US, Barack Hussein Obama, Regarding the Middle East and Northern Africa
Authors: Wudie Alelign Aschale
Published: December 2019

The main intention in this article is to critically analyze the ex-president Barack Obama's speeches regarding the Middle East and (North) Africa and see how US-America, Middle East, and Africa are framed in political ideologies. Data is collected from the four speeches delivered by the ex-president of the USA in different places and settings. The data is analyzed using critical discourse analysis (CDA). The findings revealed that political ideology sleeplessly aspires to safeguard the interests of America and her “true” allies to sustain their world power and to suppress the “others” in the counterfeit names of tolerance, engagement, aid and support, democracy and freedom, knowledge-driven economy, peace and security, etc., that targets the younger generation. Contemporary pretexts and extensions have been done with discourse manipulations and real-life interventions.
A Novel Sequence Graph-Based Approach to Find Academic Research Trends
Authors: George Soumya , Elayidom M. Sudheep , Santhanakrishnan T.
Published: December 2019

Research trends are dynamic, changing from time to time. It is an indicator of the latest innovations in each field of research, current areas of research, the latest technologies, and developments in each field of research. It also helps with future innovations and developments by providing current challenges and opportunities. This article proposes an efficient method to find research trends in each field of research of any subject area by using the graph-based subject classification of published papers. This methodology can be efficiently used to find research trends at any point of time, based on the published year of academic publications. A study of change in research trends in three subject areas - physics, mathematics, and computer science have been successfully conducted based on a total of 4500 publications since 2004.
Tuning Subunit Vaccines with Novel TLR Triagonist Adjuvants to Generate Protective Immune Responses against Coxiella burnetii
Authors: Gilkes Adrienne P. , Albin Tyler J. , Manna Saikat , Supnet Medalyn , Ruiz Sara , Tom Janine , Badten Alexander J. , Jain Aarti , Nakajima Rie , Felgner Jiin , Davies D. Huw , Stetkevich Samuel A. , Zlotnik Albert , Pearlman Eric , Nalca Aysegul , Felgner Philip L. , Esser-Kahn Aaron P. , Burkhardt Amanda M.
Published: December 2019

Coxiella burnetii is an obligate intracellular bacterium and the causative agent of Q fever. C. burnetii is considered a potential bioterrorism agent because of its low infectious dose; resistance to heat, drying, and common disinfectants; and lack of prophylactic therapies. Q-Vax, a formalin-inactivated whole-bacteria vaccine, is currently the only prophylactic measure that is protective against C. burnetii infections but is not U.S. Food and Drug Administration approved. To overcome the safety concerns associated with the whole-bacteria vaccine, we sought to generate and evaluate recombinant protein subunit vaccines against C. burnetii. To accomplish this, we formulated C. burnetii Ags with a novel TLR triagonist adjuvant platform, which used combinatorial chemistry to link three different TLR agonists together to form one adjuvanting complex. We evaluated the immunomodulatory activity of a panel of TLR triagonist adjuvants and found that they elicited unique Ag-specific immune responses both in vitro and in vivo. We evaluated our top candidates in a live C. burnetii aerosol challenge model in C56BL/6 mice and found that several of our novel vaccine formulations conferred varying levels of protection to the challenged animals compared with sham immunized mice, although none of our candidates were as protective as the commercial vaccine across all protection criteria that were analyzed. Our findings characterize a novel adjuvant platform and offer an alternative approach to generating protective and effective vaccines against C. burnetii.