bluuebunny/crossref_metadata_2025 huggingface dataset:
On Rogosinski-type approximation processes in Banach space using the framework of the cosine operator function
Authors: Kivinukk Andi , Saksa Anna
Published: November 2021

In this article, we investigate the approximation properties of general cosine-type operators, especially Rogosinski-type operators, in Banach space when there is a cosine operator function. We apply our approach to both trigonometric Rogosinski operators and Shannon sampling operators. Moreover, for some operators, we derived orders of approximation that include numerical estimates of the constants contained in it. We announced a new direction for approximation issues in the Mellin framework.
Learning With Heterogeneous Misspecified Models: Characterization and Robustness
Authors: Bohren J. Aislinn , Hauser Daniel N.
Published: November 2021

This paper develops a general framework to study how misinterpreting information impacts learning. Our main result is a simple criterion to characterize long‐run beliefs based on the underlying form of misspecification. We present this characterization in the context of social learning, then highlight how it applies to other learning environments, including individual learning. A key contribution is that our characterization applies to settings with model heterogeneity and provides conditions for entrenched disagreement. Our characterization can be used to determine whether a representative agent approach is valid in the face of heterogeneity, study how differing levels of bias or unawareness of others' biases impact learning, and explore whether the impact of a bias is sensitive to parametric specification or the source of information. This unified framework synthesizes insights gleaned from previously studied forms of misspecification and provides novel insights in specific applications, as we demonstrate in settings with partisan bias, overreaction, naive learning, and level‐k reasoning.
When Moving‐Average Models Meet High‐Frequency Data: Uniform Inference on Volatility
Authors: Da Rui , Xiu Dacheng
Published: November 2021

We conduct inference on volatility with noisy high‐frequency data. We assume the observed transaction price follows a continuous‐time Itô‐semimartingale, contaminated by a discrete‐time moving‐average noise process associated with the arrival of trades. We estimate volatility, defined as the quadratic variation of the semimartingale, by maximizing the likelihood of a misspecified moving‐average model, with its order selected based on an information criterion. Our inference is uniformly valid over a large class of noise processes whose magnitude and dependence structure vary with sample size. We show that the convergence rate of our estimator dominatesn1/4as noise vanishes, and is determined by the selected order of noise dependence when noise is sufficiently small. Our implementation guarantees positive estimates in finite samples.
Cyber Security Competency Model Based on Learning Theories and Learning Continuum Hierarchy
Authors: Yaokumah Winfred
Published: November 2021

There is an urgent need for transformative changes in cyber security awareness and training programs to produce individuals and the workforce that can deal with business risks emanating from the prevailing and emerging cyber-attacks. This chapter proposes a cyber security competency model that integrates learning theories (cognitive, affective, and psychomotor), learning continuum hierarchy (awareness and training), and cyber security domain knowledge. Employing literature search of scholarly and practitioner works, together with cyber security standards from governmental and non-governmental organizations, the chapter integrates cyber security domain knowledge, learning theories, and learning continuum hierarchy to design a model of cyber security competencies suitable for use in educating individuals and the general workforce. This theoretical-based approach to designing cyber security awareness and training programs will produce skillful individuals and workforce that can mitigate cyber-attacks in the global business environment.
A Cybersecurity Skills Framework
Authors: Fischer Peter James
Published: November 2021

This chapter traces the evolution of cybersecurity skills requirements and development over the past 40 years, from the early days of computer security (Compusec) to the present day. The development of cybersecurity skills is traced from an initial focus upon national security and confidentiality through to the current recognition as business driver. The main part of the chapter concentrates on the development of a specific skills framework from the Institute of Information Security Professionals. Originally conceived in 2006 and initially used for purposes of membership accreditation, the IISP Skills Framework has since been used extensively by commerce, industry, government and academia in the UK and more widely. Version 2 of the framework was published in 2016, and the chapter discussion outlines both the original structure and the notable changes in the later release. These developments collectively illustrate the ongoing recognition of cybersecurity skills, as well as the evolution of the skills themselves.
Exposing Mental Models to Accelerate Distance Learning Environments
Authors: Andrade Mario
Published: November 2021

This chapter forms one part in a series of chapters offering recommendations to design effective distance and blended learning. The COVID-19 pandemic has been an unintended catalyst for change in schools. Due to the closing of school buildings in the spring of 2020, school districts were forced to quickly transition to distance learning or blended learning. Even before COVID-19, many districts failed to successfully and systematically implement the new knowledge and skills acquired in these sessions. So, the question is, why has blended and distance learning practices continued to function in pockets throughout a school district and not systematically throughout the school organization? One can argue that full implementation was impeded by the lack of budgetary resources and infrastructure or unaligned curriculum, instruction, and assessments.
SecBrain
Authors: Martínez Beltrán Enrique Tomás , Quiles Pérez Mario , López Bernal Sergio , Huertas Celdrán Alberto , Martínez Pérez Gregorio
Published: November 2021

In recent years, the growth of brain-computer interfaces (BCIs) has been remarkable in specific application fields, such as the medical sector or the entertainment industry. Most of these fields use evoked potentials, like P300, to obtain neural data able to handle prostheses or achieve greater immersion experience in videogames. The natural use of BCI involves the management of sensitive users' information as behaviors, emotions, or thoughts. In this context, new security breaches in BCI are offering cybercriminals the possibility of collecting sensitive data and affecting subjects' physical integrity, which are critical issues. For all these reasons, the fact of applying efficient cybersecurity mechanisms has become a main challenge. To improve this challenge, this chapter proposes a framework able to detect cyberattacks affecting one of the most typical scenarios of BCI, the generation of P300 through visual stimuli. A pool of experiments demonstrates the performance of the proposed framework.
Safety Management System and Business Continuity Planning Considering COVID-19
Authors: Gunes Cagin Nihan , Senvar Ozlem
Published: November 2021

The COVID-19 pandemic revealed the fragility of individuals, businesses, and societies against the environmental risks. In particular, businesses have been caught flat-footed since it was an unanticipated and unprecedented crisis that impacted the most valuable asset of an organization: human resources. While incorporating the retrospective views on safety and risk management, this chapter tries to explain the significance of establishing a safety management system and developing business continuity planning from a contemporary perspective to protect occupational health and safety and attain organizational resilience in case of a pandemic or disaster. This chapter provides a conceptual overview and better understanding of safety management and business continuity practices to ensure survival and sustainability of organizations. To obtain insight and intersectoral learning, examples are given from the civil aviation sector that has been one of the most vulnerable industries during the pandemic.
Integrated Systems in Distance Education
Authors: Durak Gurhan , Cankaya Serkan , Demir Omer Anil , Cevre Cagri
Published: November 2021

During the COVID-19 pandemic, platforms that support remote working and distance education have gained great importance. Video conferencing features became crucial. In these platforms, it is possible to hold meetings and do collaborations without having to go to a physical milieu. These platforms include various features such as online meetings, group conferences, file sharing, and office integration. Systems such as Google Classroom and Microsoft Teams, which include both a learning management system and a video conference application in distance education, have gained equal importance. Video conference applications have become important tools for students to feel themselves in a social environment, as they were isolated at homes for a long time due to pandemic. In this chapter, features of integrated systems in distance education will be investigated with related literature, and the popular integrated systems will be introduced and compared.
Effective, Efficient, and Attractive Instructional Design for Online Learning
Authors: Taskiran Ayse
Published: November 2021

The worldwide school closures due to the COVID-19 pandemic have caused a rapid transition from traditional to emergency remote teaching. On the other hand, during this emergency, remote teaching, deliberate planning, and design of distance learning processes had to be overlooked to provide a quick solution for the disruption of face-to-face education globally. The aim of this chapter is to shed light on what could be done to make online courses effective, efficient, and attractive by embodying the elements that can be included in the instructional design of online courses for future online distance education practices that might be applied during emergency remote teaching. The elements that will be discussed in the chapter will be elaborated in relation to general principles of instructional design, teaching methods and techniques, instructional technologies, teaching materials and media, learner-teacher-content interaction, and feedback.
The Collaborative Digital Content Library Fostering Faculty Members' Collaboratively Building Learning Sources
Authors: Karagöz Emre , Güney Lütfiye Özge , Baran Bahar
Published: November 2021

The daily life conditions, which are affected by the COVID-19 pandemic process, have caused restrictions in many important areas of life, such as education, and these restrictions have been eliminated through technology. In teaching and learning processes, the instructors who do not have digital literacy encountered problems in creating digital content by using online education tools. This study aims to design and develop an online digital content library, content distribution screen, and forum system based on the community of practice theory to the readers. The system is expected to increase the knowledge and skills of the instructors in a teacher community, who may be unfamiliar with technology in the content preparation processes and contribute to the development of quality content and higher education.
Emotional Presence in Online Learning
Authors: Telli Esra , Sarsar Fırat , Cleveland-Innes Martha
Published: November 2021

This chapter presents a theoretical understanding of emotional presence in online learning. Research findings show that emotions have a crucial influence on successful online learning. The increasing rate of online courses, especially in higher education, makes us reconsider how necessary emotional presence is to participate in the learning process. Learning is not only a teaching or assessment process, but also a social and emotional process. It is therefore crucial to understand how students engage in online learning, and how lecturers and students perceive their emotional presence. This chapter also highlights the importance of emotions expressed by both students and lecturers in online learning.
Development and Validation of an Instrument for Online Learning Fatigue in Higher Education
Authors: Tugtekin Ufuk
Published: November 2021

The rapid and relatively compulsory integration of learning management systems (LMS) in educational settings has triggered the everchanging needs once again to assess the potential negative outcomes of online learning environments amid the COVID-19 pandemic. This study presents the rationale for developing an instrument for doing such an assessment, and the research demonstrates evidence of reliability and validity qualifications in assessing the fatigue resulting from the excessive online learning experience in higher education. The instrument consists of 28 items and seven factors. The data were collected via learning management systems from a sample of 884 online learning experienced students in higher education. Results of factor analyses revealed that the scale demonstrated no indication of deficiency in reliability or validity when evaluating the fatigue levels resulting from the excessive online learning experience. Consequently, the scale could be used to assess and improve the fatigue levels of individuals who experienced excessive online learning in higher education.
A Light Into the Current COVID-19 Pandemic in the Context of the Ancient Indian Science
Authors: Siddiqua Fatima , Rahman Rashmi Husniwara
Published: November 2021

Ancient science relating to plants has always been a source of drug discovery, and in ancient times, people used medicinal plants to fight against pandemics. Researchers suggest ancient medical practices like Ayurveda, Unani, and traditional herbal medicine as a potential source to cure or prevent diseases like COVID-19. The internet of things (IoT) aims to help solve real-world problems by connecting all modern-day devices. An internet of healthcare things (IoHT), a branch of IoT, is creating a revolution in medicine. We can incorporate ancient knowledge into the IoT system and help people worldwide fight this pandemic by spreading the knowledge of Ancient Indian medicinal practice.
Graduate Development Program as an Interventional Strategy for Talent Management
Authors: Baporikar Neeta , Randa Isaac O.
Published: November 2021

Organizations have recognized the need to have a workforce that can give the company direction and help it adapt to continuous market changes. Many organizations have taken note of this ever-changing competitive market and implemented the Graduate Development Program (GDP) to ensure the development and consistent supply of its talent pool. Adopting a qualitative research design with research instruments that allow interaction with all key stakeholders, the objective of this paper is to assess GDP as an interventional strategy for talent management, in the context of Namibia. The study findings are mixed as it shows that current and past employees feel that the GDP implementation is not effective due to their negative perceptions about the identification of outside talent and yet the findings did reveal that the GDP has resulted in improved talent sets and an enabling environment to recruit, develop and retain staff in critical positions.
Network Slice Provisioning Approaches for Industry Verticals
Authors: Walia Jaspreet Singh , Hämmäinen Heikki , Kilkki Kalevi , Flinck Hannu , Matinmikko-Blue Marja , Yrjölä Seppo
Published: November 2021

Network slicing is widely studied as an essential technological enabler for supporting diverse use case specific services through network virtualization. Industry verticals, consisting of diverse use cases requiring different network resources, are considered key customers for network slices. However, different approaches for network slice provisioning to industry verticals and required business models are still largely unexplored and require further work. Focusing on technical and business aspects of network slicing, this article develops three new business models, enabled by different distributions of business roles and management exposure between business actors. The feasibility of the business models is studied in terms of; the costs and benefits to business actors, mapping to use cases in various industry verticals, and the infrastructure costs of common and dedicated virtualization infrastructures. Finally, a strategic approach and relevant recommendations are proposed for major business actors, national regulatory authorities, and standards developing organizations.
Student ICT Use Motives
Authors: Dar Wahid Ahmad , Jan Kounsar
Published: November 2021

Research on the second-level digital divide suggests that motivational factors are crucial for its comprehensive understanding. However, the literature survey indicates a lack of research on ICT usage motives and their relation with student alienation. Using data from an offline survey on university students, this study establishes psychometric properties of student's ICT usage motive scale in the Kashmiri context. Based on SCT theory, the scale distinguishes between three underlying ICT usage motives—socialising, instrumental, and mood management—with the latter two motives negatively correlated with each other. Further analysis shows that instrumental motive reflected a moderate negative correlation with learned helplessness (LH), learning disinterest (LD), and learning discouragement (LDC) dimensions of student alienation. Socialising motive showed a moderate positive correlation with classroom isolation (CIS). CFA (n=575) model showed the least metric invariance with regard to gender and residential background.
A Transition to a Circular Economic Environment
Authors: Seetharaman A. , Shah Manthan , Patwa Nitin
Published: November 2021

The circular economy is progressively a way towards a sustainable society. The shift from linear to circular business models concerns the entrepreneurs to adopt new practices. The purpose of this research is to propose circular business models to make the worlds three of the most wasteful industries food, plastic, and fashion more sustainable. This paper is developed based on an extensive literature review and case studies. The proposed framework analyses the challenges of these three industries and prescribes relevant business models and sustainable practices. The findings in circular economy business models suggest elements of businesses that can be adopted by entrepreneurs in any industry to create a circular activity. This research paper gives the entrepreneurial spirit with business tools to achieve sustainability ambition.
Impact of the Global Financial Crisis on the IT Sector
Authors: Chytis Evangelos , Liota Vasilia , Goumas Spiridon , Papagregoriou Aristidis
Published: November 2021

The impact of the Information and Technology (IT) sector on the countries’ innovation development has been recognized as crucial in prior and recent research studies. Moreover, firms’ innovativeness affects positively countries’ economies. Nevertheless, the global economic crisis of the last decade constituted a significant barrier to the development of country economies and had a negative effect on firms’ performance. Specifically, the negative consequences of the global crisis became harder for Southern Europe Countries. More specifically the Greek economy was suffered by an extended period of crisis with harder consequences than those of other European countries. The main purpose of this study was to examine the financial performance of Greek IT firms in the early years of crisis. Our findings have been relevant to those of previous studies which observed negative effects of the financial recession on firms profitability.
The Three-Iterative Design and Implementation of a Student-Facing Social Learning Analytics Tool
Authors: Ouyang Fan , Li Xu , Jiao Pengcheng , Peng Xian , Chen Wenzhi
Published: November 2021

The design of social learning analytics (SLA) tools has become a practical means to make available learning information with a goal to improve students' regulation, reflection, and engagement in online learning. This design-based research uses the multi-method analytics to iteratively design, implement, and modify the SLA tool that makes available social, topic, and cognitive information to students in online discussions. This tool demonstrates students' online discussions from social, sematic, and cognitive aspects. This research further uses online questionnaire and interview methods to investigate students' perceptions about the tool's usefulness and usability. After experiencing this tool, students proposed critical feedback for tool improvement from the network visualization, peer reference, and explanation support perspectives. Overall, the SLA tool is a beneficial tool to foster students' awareness of their own learning and peer learning process to improve students' regulation and reflection of learning and eventually improve student engagement in online discussions.
Decision-Making Model to Assess the Organizational Climate in Healthcare Organizations
Authors: Rodrigues Kassia Tonheiro , Martins Carolina Lino , Neto João Batista Sarmento dos Santos , Fogaça Diego Rorato , Ensslin Sandra Rolim
Published: November 2021

Organizational climate impacts on the employee’s well-being, commitment and positive behavior. Most studies to assess climate in healthcare organizations use qualitative and/or statistical methods. Here, we propose a general framework, based on a multiple criteria decision making/aid (MCDM / A) method, which considers different objectives in a single problem. Such framework includes internal and external factors to assess organizational climate and presented adequate results when tested in a particular case. To assess the organizational climate, we use the ELECTRE TRI method, an outranking method that combine the decision-maker (DM) preferences and his value judgments. We conclude that MCDM methods can improve agility, provide a systemic vision on organizational climate assessment and contribute to the decision-making process
Decision Support System in Thailand's Dam Safety With a Mobile Application for Public Relations
Authors: Dowrueng Apinat , Thongthamchart Chinoros , Raphitphan Nanthiya , Brohmsubha Potcharapol , Laungnarutai Wanlaya , Supakchukul Unpong , Dowrueng Arnuphap
Published: November 2021

This paper describes the decision-making based on civil engineering expertise of the Dam Safety Remote Monitoring System: DS-RMS, which decides on action-based advice depending on every-day scenarios and special occurrences such as earthquakes and floods. The system has been in full operation since 2016 and automatically evaluates 35 failure modes for 3 major dam types 24 hours a day. Key benefits include quick and reliable access to current information about the dams and being a reliever to dam executives in critical situations. In further development, parts of the real-time dam information were selected and made available to the public together with dam safety evaluation results automatically and continuously via a mobile application.
Comparison of Normalization Techniques on Data Sets With Outliers
Authors: Vafaei Nazanin , Ribeiro Rita A. , Camarinha-Matos Luis M.
Published: November 2021

With the fast growing of data-rich systems, dealing with complex decision problems with skewed input data sets and respective outliers is unavoidable. Generally, data skewness refers to a non-uniform distribution in a dataset, i.e. a dataset which contains asymmetries and/or outliers. Normalization is the first step of most multi-criteria decision making (MCDM) problems to obtain dimensionless data, from heterogeneous input data sets, that enable aggregation of criteria and thereby ranking of alternatives. Therefore, when in presence of outliers in criteria datasets, finding a suitable normalization technique is of utmost importance. As such, in this work, we compare seven normalization techniques (Max, Max-Min, Vector, Sum, Logarithmic, Target-based, and Fuzzification) on criteria datasets, which contain outliers to analyse their results for MCDM problems. A numerical example illustrates the behaviour of the chosen normalization techniques and an (ongoing) evaluation assessment framework is used to recommend the best normalization technique for this type of criteria.
Machine Learning on Soccer Player Positions
Authors: Di Giacomo Umberto , Mercaldo Francesco , Santone Antonella , Capobianco Giovanni
Published: November 2021

During the last few years, sports analytics has been growing rapidly. The main usage of this discipline is the prediction of soccer match results, even if it can be applied with interesting results in different areas, such as analysis based on the player position information. In this paper, we propose an approach aimed to recognize the player position in a soccer match, predicting the specific zone in which the player is located in a specific moment. Similar objectives have never been considered yet with our best knowledge. We consider supervised machine learning techniques by considering a dataset obtained through video capturing and tracking system. The data analyzed refer to several professional soccer games captured at the Alfheim Stadium in Tromso, Norway. The approach can be used in real-time, in order to verify if a player is playing according to the guidelines of the coach. In the experimental analysis, three different types of classification have been performed, i.e., three different divisions of the field, reaching the best results with Random Tree Algorithm.
Development of System Typology and Choice of Preferred Simulation Modelling Methods for DSS-Toolkit
Authors: Dmitriev Oleg Nikolaevich
Published: November 2021

Formulated a position on the feasibility of developing and applying a highly developed simulation models of complex object within scope of justifying of managerial decisions. Selected set of classification factors that determine the performance of a typology of simulation methods. The article reveals the content of the applicable methods of simulation in relation to the procedure of organization of promotion in the model time. The existence of the problem of forming of the simulation method and its principal conceptual solvability by preparation and implementation of research optimization (analysis and/or synthesis of this method) is shown. An innovative extension of the set of these methods is introduced. The considerations concerning the preferred method for application for a certain category of object of modellings - the method of key model events are formulated. The problem of synthesis of a method of combination of group of methods of simulation is allocated.
Cloud Provider Selection Based on Accountability and Security Using Interval-Valued Fuzzy TOPSIS
Authors: Thasni T.  , Kalaiarasan C. , Venkatesh K. A.
Published: November 2021

Cloud computing enables on-demand access to a public resource pool. Many businesses are migrating to the cloud due to its popularity and financial benefits. As a result, finding a suitable and best Cloud Service Provider is a difficult task for all cloud users. Many ranking systems, such as ANP, AHP and TOPSIS, have been proposed in the literature .However, many of the studies concentrated on quantitative data. But qualitative attributes are equally significant in many applications where the user is more concerned with the qualitative features.The implementation of MCDM approach for the ranking and the selection of the best player in the market as per the qualitative need of the cloud users like business organization or cloud brokers is the aim of this article. An ISO approved standard SMI framework is available for the evaluation of the CSPs.The authors have considered SMI attributes like accountability and security as the criteria for evaluation of the CSPs. The MCDM approach called IVF-TOPSIS that can handle the inherent vagueness in the cloud dataset is implemented in this work
Regional Leading Industry Selection Based on an Extended Fuzzy VIKOR Approach
Authors: Zhou Fuli , Wang Guiyan , Chen Tianfu , Ma Panpan , Pratap Saurabh
Published: November 2021

To improve the deployment and optimization of the industrial structure, researchers and practitioners have performed a variety of researches in terms of regional leading industry selection based on AO Hirschman, Rostow and Miyohei’s principles. The criteria and methods employed in previous studies are mainly based on the mass industrial development data, leading to the limitation of study on the application in new high-tech district and underdeveloped regions. Due to lack of industrial data and detail industry information, it is difficult to employ the deterministic regional industry selection model. Therefore, an extended fuzzy-VIKOR approach that the expert-based and trapezoidal fuzzy number decision-making techniques, embedded into the VIKOR steps is proposed. It is developed to solve the regional leading industry selection problems concerning industrial, economic, social and environmental dimensions. Finally, a case study for the industrial planning of a high-tech zone is applied to verify the proposed decision-making approach.
SARCP
Authors: Asabere Nana Yaw , Fiamavle Elikem , Agyiri Joseph , Torgby Wisdom Kwawu , Dzata Joseph Eyram , Doe Nina Pearl
Published: November 2021

In the domain of cyber security, the defence mechanisms of networks has traditionally been placed in a reactionary role. Cyber security professionals are therefore disadvantaged in a cyber-attack situation due to the fact that it is vital that they maneuver such attacks before the network is totally compromised. In this paper, we utilize the Betweenness Centrality network measure (social property) to discover possible cyber-attack paths and then employ computation of similar personality of nodes/users to generate predictions about possible attacks within the network. Our method proposes a social recommender algorithm called socially-aware recommendation of cyber-attack paths (SARCP), as an attack predictor in the cyber security defence domain. In a social network, SARCP exploits and delivers all possible paths which can result in cyber-attacks. Using a real-world dataset and relevant evaluation metrics, experimental results in the paper show that our proposed method is favorable and effective.
Prediction of Chronic Obstructive Pulmonary Disease Stages Using Machine Learning Algorithms
Authors: Mohamed Israa
Published: November 2021

Identifying chronic obstructive pulmonary disease (COPD) severity stages is of great importance to control the related mortality rates and reduce the associated costs. This study aims to build prediction models for COPD stages and, to compare the relative performance of five machine learning algorithms to determine the optimal prediction algorithm. This research is based on data collected from a private hospital in Egypt for the two calendar years 2018 and 2019. Five machine learning algorithms were used for the comparison. The F1 score, specificity, sensitivity, accuracy, positive predictive value and negative predictive value were the performance measures used for algorithms comparison. Analysis included 211 patients’ records. Our results show that the best performing algorithm in most of the disease stages is the PNN with the optimal prediction accuracy and hence it can be considered as a powerful prediction tool used by decision makers in predicting severity stages of COPD.
A Novel Approach for the Recruitment Process in Human Resources Management
Authors: Bal Mert , Bal Yasemin
Published: November 2021

Discovering and using valuable and meaningful data which is hidden in large databases can have strategic importance in the managerial decision-making process for organizations to gain competitive advantage. With the increasing data flow, it has become more difficult for organizations to store this data and gain useful knowledge to manage their business operations and functions. A knowledge discovery process that is based on data mining methods has widely been used in business operations and management functions. This paper investigates formal concept analysis which is a powerful tool in knowledge representation and discovery and explains association rule mining based on formal concept analysis. An experimental study is given for employee selection function of HRM by using formal concept analysis method to model the qualifications of candidates which are needed for the job position. The qualifications of the candidates are modelled with concept lattices, and the qualifications of the candidates are matched with the ones determined in the job specification.
Non-Contact Abnormal Physiological Status Detection During Sport and Training
Authors: Yang Jinlin
Published: November 2021

In sport and training, it is necessary to continue monitoring the physiological parameters of athletes to ensure that they can maintain a high level of competition. The previous monitoring physiological status methods mainly are contactable by sensors that are worn on the body. This paper adopts a non-contact physiological parameter monitoring method by using imaging photoplethysmography (iPPG). In order to eliminate the noises in iPPG signals, the correlation energy entropy threshold adaptive denoising and variance characterization series are introduced to resist the noises from external conditions. The noises are removed by a threshold which is estimated by noise energy entropy. The constructed signals after denoising are used to estimate physiological parameters, such as heart rate and respiratory rate. The experimental results demonstrate that it estimates the physiological parameters better by using iPPG-based physiological parameter monitoring method than previous methods.
Effectiveness Evaluation of Replacement Policies for On-Chip Caches in Multiprocessors
Authors: Jose Jobin , Begum Shameedha , Ramasubrmanian N.
Published: November 2021

A Cache plays a vital role in improving performance in the multicore environment, especially the Last Level Cache (LLC). The improvements in performance are based on the block size, associativity, and replacement policies. Most of the papers concentrate on traditional Least Recently Used (LRU) based replacement policies for their replacement decisions. Unfortunately, the replacement decisions do not enhance performance of the cache as expected. An enhanced modified Pseudo LRU policy is proposed, which is an approximation of LRU. The proposed methodology uses counters to enhance the confidence of replacement decisions based on the history of the replaceable blocks in cache. It is very clear from the Simulation results that the replacement scheme proposed exhibits better performance improvement in terms of miss ratio of about 3% and energy efficiency of about 2% on an average.
The Quest for Motivation
Authors: Bawa Arpit
Published: November 2021

Studies have shown Tabletop Role Playing Games (TRPGs) to be effective motivational learning tools that can be utilized in various subject matters. However, limited research has analyzed the elements within TRPGs that enable them to provide motivation to the users. As such, this study conducted an in-depth examination of the elements of TRPGs through the perception of players. Self-determination theory helped frame the study, while the Generic Qualitative Inquiry approach was used for the methodology. Semi structured interviews were conducted with six participants. Data revealed several themes that aligned with the motivational frame related to competency, relatedness, and autonomy. The findings indicate the importance of the roleplaying element and the connection between the player and their in-game character, as well as the effect choices within the game have on the players and other elements of TRPGs. Implications regarding design of TRPGs as learning tools are discussed.
The Gap Between Korean Esports and Educational Gaming
Authors: DeArmond Marc C. , Shelton Brett E. , Hsu Yu-Chang
Published: November 2021

While some research suggests South Korea has fallen behind other developed nations with regard to publishing and using serious games in the classroom, Korean interest in video games remains extremely high. Due to a number of cultural, social, and technological factors, esports was primed to become a significant force in Korean culture and received significant support from the Ministry of Culture. The Korean Ministry of Education, meanwhile, is resistant to adopting educational games as a part of its accepted pedagogy. This resistance has created a significant gap between the interest in video games as a learning tool and that of video games as an industry and career path in Korea. While a number of factors play a role in the languishing serious games market, based on evidence analyzed through educational gaming literature it is unlikely educational gaming will be able to significantly advance without the support of the primary governing body controlling educational policy.
Implementation of Enterprise Resource Planning (ERP) Systems in the Gig Economy
Authors: Behl Aastha , Rajagopal K. , Sheorey Pratima
Published: November 2021

The gig economy has played a significant role in the country's economic development and has led to the growth in the employment of the people worldwide by supplementing the primary income of the people. With the security and autonomy that the gig sector promises, people choose to work as gig workers rather than traditional workers. Almost every company uses an enterprise resource planning system (ERPs) to some extent to improve its performance and competitiveness. This paper devises a conceptual model describing how ERP systems help improve the human resource management of the gig workers, maintain customer relations, and bring digital transformation to its business. The research model would provide an understanding of diagnosing how the ERP system can help improve the conditions of the gig workers and the potential problems faced by them in the areas where the ERP system is not working efficiently. The framework would provide insights in simplifying the implementation of ERP in the gig sector that would be useful in the future.
Estimate Risks Eate for Android Applications Using Android Permissions
Authors: Er-Rajy Latifa , El Kiram My Ahmed , El Ghazouani Mohamed
Published: November 2021

In recent years, Android became the first target for hackers and malware developers due to its inefficient permission model. In this article, the authors introduce a tool called PerUpSecure to manage permissions requested by Android applications, calculate the risk rates, and display the results to the user in order to help him to make a better decision. Thanks to our PerUpSecure, the user will be able to install only the trusted applications. As far as the authors know, the other existing tools focus only on measuring app risk after being installed and not before as this tool does. Therefore, to evaluate the tool, they selected two different applications sets. The results show that the tool can produce the most trustworthy risk rate to prevent and detect potential malicious activities performed by malware.
DNA Cryptography Using DNA Fragment Assembly and Fragment Key Expansion for Genomic Data
Authors: Adithya B.  , Santhi G.
Published: November 2021

This research proposes a tweaked scheme based on DNA fragment assembly to improve protection over insecure channel. The proposed procedure utilizes binary coding to change over an underlying plaintext into a reference DNA arrangement to deal with the fragmentation. DNA fragment key expansion is applied over the reference DNA sequence to make the short-chain fragments. The redundancy in the long-chain of reference DNA is removed using DNA fragment assembly. A look-up table is generated to store the binary values of overlapped fragments to be reassembled during the encryption and decryption processes to prevent artefacts. Also, it is used in an overlapped sequence to counteract cipher decomposition. The results and comparisons demonstrate that the proposed scheme can balance the three most important characteristics of any DNA masking scheme: payload, capacity, and BPN. Moreover, the potential for cracking the proposed tweaked method is more complex than the current strategies.
Impact of Information Communication Technology Strategies on Learning Effectiveness
Authors: Vajjhala Narasimha Rao , Vajjhala Narasimha Rao , Strang Kenneth David
Published: November 2021

Transnational higher education is a multinational growth strategy requiring a foreign direct investment to establish a university or a campus in a new country and, if possible, to use articulation agreements with credible partners to increase domestic enrolment. Due to the potential international student learning style differences, we hypothesized there may be difficulties teaching Information Communication Technology (ICT) courses in transnational strategies due to the student origin or domestic campus location. The purpose of this study was to examine if student learning was effective within ICT graduate courses at an accredited sub-Saharan Africa-based university implementing the transnational education strategy. We found student learning was effective, but paradoxically, some factors indicated unusual results. Learning impact was higher when students disregarded the learning objectives, which we were able to explain theoretically. Conversely, learning impact was higher for many students who avoided tutoring, which we also rationalized.
Safety and Attention of Passengers With Disabilities Who Travel by Train
Authors: José G. Hernández R.  , María J. García G.  , Gilberto J. Hernández G.
Published: November 2021

In this work, within the business world, two fields of great social interest are related. In particular, it will talk about corporate Safety & Security (S&S) and Corporate Social Responsibility (CSR). The importance of S&S in a service company will be analyzed, while some of the actions that these companies can take to increase their CSR will be studied. Specifically, the study will focus on trying to offer some recommendations, to help ensure that train travel is safer and more enjoyable for passengers who suffer from a disability. From what has been said previously, the objective of this work can be stated as: present some actions, so that the trip by train, of passengers with some disability, is safer and more pleasant. To achieve this objective and the secondary objectives that may be generated, the Integrated-Adaptable Methodology for the development of Decision Support System will be followed, which, it has been shown, is very useful in investigations similar to this.
The Present Context of Sustainable Develpoment in Romania
Authors: Ilie Marinela
Published: November 2021

Sustainable development promotes the concept of reconciling economic and social progress without endangering the naturally balanced balance on the planet. The idea behind this concept is to ensure a better quality of life for all the inhabitants of the planet, for the present generations and for the future generations. In Romania, as a member state of the European Union, in 1997 the National Center for Sustainable Development was created under the auspices of the Romanian Academy, which over time managed to become the most authorized voice in civil society in the field of developing proposals and strategies for sustainable development of Romania. The purpose of the National Center for Sustainable Development is to identify Romania's sustainable development priorities and achieve them through concrete projects at the national and local levels. The purpose of this paper is to identify and analyze the opinion of the Romanian citizens regarding sustainable development's current context and situation.
An Improvement of Yield Production Rate for Crops by Predicting Disease Rate Using Intelligent Decision Systems
Authors: Usha Rani M.  , Saravana Selvam N.  , Jegatha Deborah L.
Published: November 2021

Agriculture is the country's mainstay. Plant diseases reduce production and thus product prices. Clearly, prices of edible and non-edible goods rose dramatically after the outbreak. We can save plants and correct pricing inconsistencies using automated disease detection. Using light detection and range (LIDAR) to identify plant diseases lets farmers handle dense volumes with minimal human intervention. To address the limitations of passive systems like climate, light variations, viewing angle, and canopy architecture, LIDAR sensors are used. The DSRC was used to receive an alert signal from the cloud server and convey it to farmers in real-time via cluster heads. For each concept, we evaluate its strengths and weaknesses, as well as the potential for future research. This research work aims to improve the way deep neural networks identify plant diseases. Google Net, Inceptionv3, Res Net 50, and Improved Vgg19 are evaluated before Biased CNN. Finally, our proposed Biased CNN (B-CNN) methodology boosted farmers' production by 93% per area.
The Impact of Website Design on Online Customer Buying Satisfaction and Loyalty to E-Tailers
Authors: Chakraborty Debarun , Banerjee Jayanta , Mehta Prashant , Singh Netra Pal
Published: November 2021

The popularity of e-tailers has distorted the retail industry in India. Websites are becoming an important means through which customers get product information and purchase items for their needs. This research paper focuses on four dimensions, i.e. user interface, convenience, personalized recommendations, and perceived security of the website, to assess their impact on online customer satisfaction with and loyalty towards E-tailers. The study questionnaire used established measures. The data was collected from four large cities in India, namely Chennai, Mumbai, Kolkata and Delhi. Analysis of the survey results suggests that perceived website security is the most important dimension for customer loyalty. E-tailers have to ensure adequate security provisions in their websites to build up consumer perceptions of trust and so repeat business loyalty.
Examining Online Health Community Users' Information Adoption Intention
Authors: Zhou Tao
Published: November 2021

Due to the doubt on information credibility, users often hesitate to adopt the health information posted on online health communities (OHC). This may undermine the sustainable development of OHC. The purpose of this research is to identify the determinants of OHC users’ information adoption intention. The results indicated that both information factors and social interaction affect the adoption intention. Information factors include argument quality and source credibility, whereas social interaction includes perceived similarity and familiarity. The results imply that OHC need to ensure information quality and support users’ interaction in order to facilitate their information adoption.
An Artificial Neural Network Examination of the Intention to Implement Blockchain in the Supply Chains of SMEs in Tonga
Authors: Faasolo Malia Benedine , Sumarliah Eli
Published: November 2021

The research intends to examine the impacts of the technology, organization, and environmental factors on the implementation of blockchain in the supply chains of SMEs in the Kingdom of Tonga. These include regulatory support, competitive pressure, cost, upper management support, complexity, and relative advantage. The research uses SEM-PLS to test the hypotheses and the Artificial Neural Network method to analyze and classify survey data from 201 SMEs. Findings show that relative advantage, cost, complexity, and competitive pressure significantly affect implementing blockchain in the supply chains. As SMEs frequently have limited capital to invest in technology but meets the same obligations to streamline business operations to optimize profits, blockchain provides a feasible choice for the firms’ sustainability with its characteristics of security, transparency, and immutability that are prospective to develop SMEs’ performance. Thus, the paper provides novel insight regarding the determinants of SMEs' intention to implement blockchain in their supply chains.