Reviewerly/exHarmony huggingface dataset:
Impact of Individual Belief, Facilitating Condition, and Habits on the Acceptance and Support to Use Mobile Training

Implementation and adoption of mobile training are still nascent in the public sector in the UAE. A successful migration model for a mobile trainingsystem relies on user support and acceptance as well as the decision to migrate to mobile training. The study aims to investigate a comprehensive rangeof the factors that influence the intention to use and support to change to mobile training in the Sharjah police general command – UAE. The proposedconceptual framework includes Individual Beliefs (attitude) (IB), Facilities Condition (FC), Habits (HA), Intention to Use Mobile Training (IUMT),and support to change to mobile training (SCMT). The study's target population is all the staff members of the General Department of Sharjah Policein the Emirate of Sharjah, which has a total of 7,715 employees and a sample size of 367. The final dataset includes 373 respondents collected from 19different departments by using the quota sampling technique. Results of intention to use mobile training (IUMT), illustrate a satisfactory predictivepower; the three variables; IB, FC, and HA can explain 44.6% of the variance. The precedence of the impacts based on the path coefficient is individualbelief, facilitating conditions, then habit. Results of support to change to mobile training (SCMT), illustrate a moderate predictive power; the fourvariables; IUMT, IB, FC, and HA can explain 63.6% of the variance. The precedence of the impacts based on the path coefficient is the intention to usemobile training, then individual belief. The three main predictors have impacts on the support to change to mobile training (SCMT) either directly orindirectly. Based on the total effect, the precedence of the three main variables is individual belief, facilitating conditions, then habit.
Blockchain for Authorized Access of Health Insurance IoT System

Today's insurance industry plays a significant role in a variety of fields, particularly in health insurance. As IoT technology advances, health insurers in IoT networks can obtain real-time medical data for individuals and issue individual insurance policies based on a person's lifestyle. However, sharing personal data requires a guarantee of privacy and security. This paper suggests a Blockchain technology to solve this problem. The work presents a novel framework that integrates health insurers, IoT-based networks, and Blockchain technology to implement access control protocol using a smart contract for sharing the financial premium of insureds with the stakeholders as non-participants/authorized parties. The evaluation of the proposal results in authorized access within less time compared to traditional data-sharing systems, and the security analysis shows that proposal can protect data from potential threats. Index Terms— IoT, Blockchain, health insurance, insurer, Smart Contract, PBFT.
Classification of Tiles using Convolutional Neural Network

Tiles are one of the building materials with various types that can make a residence more elegant, attractive, and colorful. However, not all people know about the types of tiles and their advantages. Therefore, a Convolutional Neural Networks (CNN) based method is proposed to make it easier for people to accurately recognize tiles based on their types and know their advantages. The purpose of this paper is to classify the types of tiles using CNN which is based on VGG16 model. The proposed method classifies tiles into 6 classes, namely granite, limestone, marble, motifs, mosaics, and terrazzo. This research uses 186 training data, 96 validation data and 60 test data with image resolution of 224x224. Based on the experiments, the training process produces 100% of training accuracy and 94% of validation accuracy. The testing process achieves 98.33% accuracy which can be concluded that the proposed CNN model able to classify the types of tiles well.
Head Gesture Recognition Based on Capacitive Sensors Using Deep Learning Algorithms

Abstract The current paper proposed and investigated the head motion recognition idea based on four capacitive sensors and deep learning models. The proposed system was designed to empower a tetraplegic person to control a remote device or an intelligent wheelchair. The capacitive sensors were placed around the neck using a necktie, which each volunteer who participated in this experiment was easy to use. The results show that the best-proposed deep learning model can determine each activity with a classification rate equal to 89.29% using capacitive raw data. During the experiments the deep learning models provided accuracy values in the range of 56.25% to 89.29%.
E-Jacket with Health Monitoring System Using Renewable Source of Energy

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Random Number Generator with Long Cycle Based on Memory Cells

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Spammer Detection and Fake User Identification in E-Commerce Site

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Review on Common Techniques for Urban Environment Video Analytics

This work compiles the different computer vision-based approaches from the state-of-the-art intended for video analytics in urban environments. The manuscript groups the different approaches according to the typical modules present in video analysis, including image preprocessing, object detection, classification, and tracking. This proposed pipeline serves as a basic guide to representing these most representative approaches in this topic of video analysis that will be addressed in this work. Furthermore, the manuscript is not intended to be an exhaustive review of the most advanced approaches, but only a list of common techniques proposed to address recurring problems in this field.
BERT- and FastText-Based Research Paper Recommender System

With the advent of digital libraries, researchers can now access a plethora of publications and journals from any part of the world. These research papers play an instrumental role in acquainting researchers with the latest technological advancements taking place all over the world. Students who wish to know about the latest technologies also peruse these research papers. But currently, there is a dearth of satisfactory approaches for getting relevant recommendations. In the era of digital libraries, the importance of research paper recommendations is increasing day by day. However, there is a paucity of recommendation systems that allows us to leverage these information sources effectively. This places some limitations on an application that has great potential. So, a research paper recommendation system that allows us to generate accurate predictions is exigent. As abstracts are representative of the whole research paper, a research paper recommendation system that generates relevant keywords out of the abstract using BERT and provides recommendations would be both quick as well as accurate. BERT embeddings for keyword extraction from the abstracts and FastText for classification of the words and sentences are used for better evaluation and recommendations of the research papers. This method will fetch better results in comparison to the traditional approaches used for keyword extraction as well as research paper recommendation.
English Language Writing Anxiety among Diploma Engineering Students in Uitm

Over the past decades, researchers are becoming increasingly interested in the writing skills of second language (L2) learners. Although writing has been recognised as a complex skill, it is a crucial skill that (L1) and (L2) learners must master due to its widespread use in academic studies. Numerous scholars (Jennifer and Ponniah,2017; Altukruni,2019) believe that the writing process is influenced by cognitive, cultural, and social aspects, making it a difficult endeavour. All of this may cause the students to feel a great deal of concern and anxiety. In Malaysia, many studies were conducted in order to investigate anxiety in L2 classrooms, with the majority of them focusing on speaking skill (Sim et.al., 2020; Kamal et.al., 2020; Nurul Fatinah et.al., 2020). There are also studies on writing anxiety in first and second language but more detailed investigation and in-depth research on this needs to be done so both instructors and learners will be more aware of the perturbing issues involving writing anxiety in L2 classroom. Due to the complexity and multidimensional phenomenon of writing anxiety, a sequential explanatory mixed-method approach will be used in this investigation (Creswell, 1998). The outcomes from this research project are expected to assist L2 educators better understand how to teach writing. Next, it may aid the researcher in developing a mediated learning environment in the classroom, allowing learners to feel more at comfortable in approximating basic knowledge to create good essays and become less worried while writing essays autonomously.
A biographical experience concerning the role of ICT in Mathematics education

The article starts with the theoretical and empirical introduction, mentioning the role of ICT in teacher training, and proceeds with the methodological presentation of the general research and its design. The next section presents the results obtained, divided in two subsections - the biographical synopsis and the status and use of ICT in Teresa’s teaching and training practice. The conclusion, as allowed by Teresa’s narrative, closes the text.&#x0D; Objectives: The article belongs to a qualitative biographical-narrative research, which involves obtaining biographical testimonials from teachers/ researchers who train teachers with the help of Information and Communication Technologies (ICT), to promote skills such as critical thinking, creativity, collaboration, cooperation, and communication, understood as essential for the development of comprehensive education, curricular sustainability, and participatory citizenship.&#x0D; Methodology: The research problem involves the determination of the importance and status associated to the use of ICT in the professional understanding and practice of the participants, according to biographical narratives: What importance and status do the participants associate to the use of ICT, in their understanding and practice of the teaching profession? The teachers’ professional biographies were reconstructed from the collected opinions and perceptions, providing answers to the research question.&#x0D; Results: Here, we report the biographical narrative of a university teacher/ researcher, under the pseudonym “Teresa”, who is dedicated to Mathematics education in teacher training. From her reconstructed biographical experience, we will highlight a close relationship to the theoretical and empirical contributions presented in the introduction, and to results previously obtained through our research.
Particle Swarm Optimization Algorithm with Mirror-image Inertia Weight

So far, no matter what kind of inertia weighting algorithm, its value changes within the positive range (0, 1.2). To further improve the optimization performance of particles, this paper proposes a mirror-image inertia weight (miIW) strategy, which extends the value range of inertia weight from the positive domain (0, 1.2) to the negative domain (-1.2, 0). The CEC2014 function was used to test the optimization performance of different inertia weight algorithms in the PSO algorithm using three strategies of positive inertia weight (PIW), negative inertia weight (NIW), and mirror-image inertia weight (miIW), The results show that the optimization performance of miIW is better than PIW and NIW. To verify the actual optimization ability of the mirror-image inertial weight (miIW), we compared the effects of PSO with miIW, PSO with PIW, and PSO with NIW in the optimization of the classification model parameters. The results show that the PSO with miIW optimization result is the best. These research results show that the miIW strategy increases the flight distance of the particles, which expands the search range of the particles, improves the overall development capabilities of the particles, and increases the search density of the particles. The expansion of the search range and the increase of the search density work together to promote a significant improvement in the optimization performance of the PSO algorithm.
The Clustering Algorithm Based on Improved Antlion Optimization Algorithm with K-Means Concepts

K-means clustering algorithm has the advantages of its simple and fast mechanism adapted to different applications. Nevertheless, there is room for improvement such as its results easily affected by the assigned initial values and prone to fall into a local optimum. In this paper, a clustering algorithm based on an improved Antlion optimization algorithm with K-means concepts (IALO-K) is proposed. First, the elite strategy of the Antlion Optimization Algorithm (ALO) is proposed to preserve the elite individuals of each generation for in-depth exploration. Secondly, a formula for updating the individual to avoid falling into local is also implemented. Finally, the concepts of K-means are added to the clustering process to accelerate the convergence speed. There are five common datasets selected to test the IALO-K algorithm and compared with the traditional K-means and other algorithms. The test results show that the clustering performance of IALO-K algorithm is better than other algorithms.
Multi-strategy Parallel Phasmatodea Population Evolution Algorithm for Public Transport Scheduling

The phasmatodea population evolution algorithm (PPE) is a novel algorithm to simulate population evolution. In this paper, a multi-strategy parallel phasmatodea population evolution algorithm (MPPPE) is proposed to further improve the comprehensive performance of PPE. The step factor of the flower pollination algorithm is introduced to maintain the diversity of population. In terms of communication, two communication strategies are adopted, which not only speeds up the convergence rate but also improves the exploration ability of the algorithm. We compared this algorithm with the other three optimization algorithms in the CEC2013 test function and proved the excellent performance of this algorithm. Finally, this algorithm is applied to the bus scheduling problem in traffic transportation, and satisfactory optimization results are obtained.
Digital Science Art as an Ontological Metaphor

The article considers the possibility of using digital scientific art as a tool for philosophical and aesthetic cognition. On the example of games of cellular automata and from the point of view of the paradigm of synergetics, a large-scale analogy of the dynamics of multi-element distributed systems of various natures is revealed. The question is raised about the nature of beauty, which is interpreted as a fundamental cosmic phenomenon. The concept of protoconstruct is viewed as a mental (mathematical, digital) object, the properties of which are transferred to the objects and phenomena under study. As an example of digital protoconstructs, the article discusses the so-called cellular symmetroids. Cellular symmetroids can be considered from the point of view of scientific art as art objects. At the same time, they represent a deep ontological metaphor. A unique property of cellular symmetroids is spontaneous destruction and transition to quasi-chaotic dynamics. This feature can be linked to the idea of historical time, which is very unusual for mathematical objects. Mathematical structures that arise as a result of calculations according to this model are completely unique and inimitable, like the internal states of the soul or psyche of a thinking subject. At the same time, they are to the same extent determined (even involuntary) by the previous state. Integrity, internal unity are inherent not only in symmetric structures but also in the chaos that is born after them, which, in contrast to stereotypical statistical intuitive ideas, is deterministic. However, such an abstract digital art, based on the unconventional mathematics of dynamic chaos, is an accurate ontological metaphor, a visualization of the eidos of the beauty in their relationship with the cosmic logos and the nature of the original creative chaos.
Development of framework to support software requirement elicitation using a domain ontology

One of the main goals of Software Requirements Engineering is to understand customers' needs and to put their customer needs in requirement. The requirement engineering has several processes one of them are requirement elicitation the requirement elicitation considered as one process of requirement engineering and also considered as important process so the process of elicit the requirement has difficult, due to the incompleteness problem, ontology has player important rule to helps the requirement elicitation by adding more information about the words. in this paper implementing framework by using domain ontology, the frame work implement using java and ontology using protégé, the framework evaluated using requirement in in banking domain, and show the results helps the software developer to choose the requirement.
THE EFFECTIVENESS OF PHONIC BASED APPROACH IN YOUNG ESL LEARNERS

In Pakistan, English is taught as a second language. Phonics based approach is considered as basic constituent of reading for English as second language learners.This study aimed to find the effectiveness of phonics-based approach at primary level andto check the accuracy of spellings and oral reading in young ESL learners. The participants of the study were exposed to oral reading of texts and a spelling test was adapted for data collection. The reading and spelling accuracy were measured from the data collected from the primary sources. The results showed that the phonics-based approach is 97.6% and 92.1% effective for reading and spelling accuracy, respectively, in young ESL learners. The phonics-based approach is effective to be applied to the primary schools of ESL context.
The Binary Lesson as a Means of Upgrading the Compulsory Minimum in Mathematics in the Second Grade

The binary (also called integrated or synthesized) lesson is considered as a non-traditional form of organization of learning. This type of lessons is applied both in vocational education and in general education school. In binary lessons, theoretical knowledge and practical skills are formed inseparably. They can unite two teachers from different subjects and fields. Binary lessons have a more specific technology of preparation and conduct than traditional lessons. Their structure is very dynamic and flexible depending on the type of lesson (lesson-lecture, lessonseminar, lesson-talk, lesson-discussion, lesson-conference, summary lesson, etc.). Such lessons are usually difficult to fit into a lesson. It is good for such lessons to be paired, because they favor the development of dialogic communication and interaction of teachers with each other, as well as between each of them and the students. The availability of two sources of information stimulates students to be actively involved in the learning environment, to compare different points of view, to express their opinions and attitudes. During such a lesson, they have the opportunity not only to master a much larger amount of information than traditional, but also to develop and improve their communication skills, to show initiative and creativity.
ACTIVE FORMS AND METHODS OF LEARNING IN THE FORMATION OF UNIVERSAL COMPETENCES OF STUDENTS

The use of the competence-based approach in higher education presupposes the formation of a structure of universal competencies among students. Formed competencies make it possible to apply the acquired knowledge in practice, solving various kinds of professional, social and civic tasks. The system of active forms and methods of teaching should become the guiding principle of the formation of the structure of universal competences. It is necessary to introduce such forms of the educational process, innovative pedagogical systems and technologies, methods of active learning, methods of diagnosing the level of formation of competencies, which contribute to the combination of theoretical knowledge with practical skills.