Reviewerly/exHarmony huggingface dataset:
Self-Development as a Factor in the Professional Growth of Future Teachers

The study aimed to substantiate the concept of "self-development as a factor in the professional growth of future teachers" and to empirically research the effectiveness of technological tools that affect the development of its components. Self-development as a factor in the professional growth of future teachers in the context of the article is considered as a motivated self-progress of applicants for higher education in pedagogical specialties, which is based on personal senses and aimed at developing their professional potential. To achieve this goal at different stages of the study, we applied: author questionnaires using Google service (Google Forms tool), individual protocols for self-assessment, diagnostic technologies of self-awareness and self-development - the flower of my research skills, a cascade of sequences, a basket of ideas, personal projects technologies - pedagogical portfolios, cases, Self-book, projects, business (imitation) games, maps of professional self-development. The generalization of the data of the empirical study took place using the methods of mathematical statistics – the Pearson's correlation coefficient using MS Excel (application of the "CORREL" function). The results of the study confirm the quantitative and qualitative indicators of the positive component dynamics of the formation of self-development for the professional growth of future teachers. It is proved that the use of a set of personal-projective tools contributes to the formation of professional self-development of the teacher, which is expressed by the components disclosed in the article. The application of our research: its results will help applicants for higher education (future teachers and lecturers of higher educational institutions of pedagogical specialties) consciously apply diagnostic, personal-projective technologies for the teacher’s self-development at the beginning of their activity. The study for the first time substantiates the essence of the concept and the components of self-development as a factor in the professional growth of future teachers; suggests a set of effective methods that have not been widely explained.
Makers against Covid-19: Face shields as the international solidarity KPI

At the first signs of the Covid-19 pandemic, the uncertainty around the global stock of medical supplies sparked a response in the DIY communities around the world. In the case of Spain, a community called Coronavirus Makers (CVM) emerged to supply ventilators and personal protection equipment (PPE) to hospitals and people in need. This paper explores the evolution of this community-driven development, detailing the patterns proposed by members of the group acting as design experts to tackle different problems. More specifically the paper uses face shields, the most produced PPE in Spain, as a boundary object to highlight the relationships amongst individuals, institutions, and companies. The objects of design, since they fall in the specific category of devices for medical use, have to overcome validation at the technical level. Authors will also explore some of the controversies surrounding the transfer of these products from horizontal innovation networks to traditional production companies.
Quelling the Boredom with Alternative Instruction: Augmented Reality, Escape Kits, and Scavenger Hunts

From 2016-2019, Jacksonville State University (JSU) librarians embraced the call to incorporate increased active learning into traditional library information instruction. Librarians began this process by integrating the use of a scavenger hunt into the Houston Cole Library’s new orientation tailgate event. Breakout EDU Escape Room kits with a custom-built storyline were added to teach basic research skills and help lessen library anxiety in First Year Freshman Experience courses. Augmented reality (AR) was incorporated into Business Orientation classes to increase student understanding of specialized business information resources. These activities helped librarians fulfill Houston Cole Library’s mission of creating a student-driven learning environment focusing on the Association of College Research Libraries (ACRL) information literacy framework. The research, planning, and implementation processes involved in the initiation of scavenger hunts, escape activities, and AR interactive stories at JSU have numerous applications across all educational levels and disciplinary focuses.
Multi Modal RGB D Action Recognition with CNN LSTM Ensemble Deep Network

Human action recognition has transformed from a video processing problem into multi modal machine learning problem.The objective of this work is to perform multi modal human action recognition on an ensemble hybrid network of CNN and LSTM layers.The proposed CNN -LSTM ensemble network is a 2 -stream framework with one ensemble stream learning RGB sequences and the other depth.This proposed framework can learn both temporal and spatial dynamics in both RGB and depth modal action data.The hybrid network is found to be receptive towards both spatial and temporal fields because of the hierarchical structure of CNNs and LSTMs.Finally, to test our proposed model, we used our own BVCAction3D and three RGB D benchmark action datasets.The experiments were conducted on all the datasets using the proposed framework and was found to be effective when compared to similar deep learning architectures.
INCREASING ABILITY TO READ UNDERSTANDING THROUGH PQ4R METHOD IN CLASS IV STUDENTS SDI ARRAYAAHIIN BEKASI DISTRICT

The purpose of this study is to make improvements in the learning process and improve learning outcomes Indonesian fourth grade student at Arrayaahiin Elementary Islamic School west C ikarang Bekasi District using the PQ4R method (Preview, Question, Read, Recite, Reflect and Review.) This research was conducted in SDI Arrayaahiin Bekasi Regency. This research method is a class action research that uses a spiral or cycle model from Kemmis and Taggart. The cycle is carried out twice with four rounds of each cycle, namely planning, implementation, action, observation and reflection. That is, in the first cycle, the percentage of reading comprehension reached 67%, with a teacher observation size of 93%. In the second cycle, the percentage of reading comprehension reached 80%, and observation measured 94% of teachers. Once discovered, there is a gradual increase in learning after the action. The PQ4R method not only helps students in the skills expected in the learning process at school. However, it is very important to equip students with a systematic learning method. The method of use for the benefit of the studio will produce supported understanding, not memory. Understanding that discuss relative will last longer in the brain, than just remembering the facts.
The Influence of Reference Material for Sketching Strategies and Form Establishment at the Embodiment Design Level

This paper purposely to understand the relationship between reference materials and form the embodiment process illustrated in the design drawing sketch. To review the respondent’s design thinking characteristic and to surmise the scenario of the product development issue, a design protocol analysis put in place as a core method. Respondent behaviour throughout the design activities was recorded and analyzed through interaction design embodiment process. Analysing design activities and drawing sketch has produced some pattern which states the meaning of average design element, selected reference material, interaction behaviour, and the design process in a control situation. Keywords: Interaction, Form Embodiment, Design Thinking Process, Design Elements eISSN: 2398-4287© 2020. The Authors. Published for AMER ABRA cE-Bsby e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning &amp; Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v5iSI3.2546
Learning from Weakly-Labeled Web Videos via Exploring Sub-concepts

Learning visual knowledge from massive weakly-labeled web videos has attracted growing research interests thanks to the large corpus of easily accessible video data on the Internet. However, for video action recognition, the action of interest might only exist in arbitrary clips of untrimmed web videos, resulting in high label noises in the temporal space. To address this challenge, we introduce a new method for pre-training video action recognition models using queried web videos. Instead of trying to filter out potential noises, we propose to provide fine-grained supervision signals by defining the concept of Sub-Pseudo Label (SPL). Specifically, SPL spans out a new set of meaningful "middle ground" label space constructed by extrapolating the original weak labels during video querying and the prior knowledge distilled from a teacher model. Consequently, SPL provides enriched supervision for video models to learn better representations and improves data utilization efficiency of untrimmed videos. We validate the effectiveness of our method on four video action recognition datasets and a weakly-labeled image dataset. Experiments show that SPL outperforms several existing pre-training strategies and the learned representations lead to competitive results on several benchmarks.
Opportunities for Higher Education of Artificial Intelligence in Korea

In the recent years, the business environments in Korea, as in most other industrialized countries, have been going under revolutionary changes by adopting artificial intelligence (AI) technology.Since the technology gets popular widely in a short period, there are surging demands of AI manpower not only in the experienced level but also in the entry level.Specifically, we observed by analysing software (SW) job announcements that in about half the cases they require more than 4-year education in college for their new employees without previous job experiences in big data/AI job positions.With the increasing industrial demands in the new technology, there are on-going efforts in higher educational institutes to provide qualified graduates in the AI fields.We surveyed what skills are required in which application fields.
The Impact of Human Capital on Economic Growth in Ethiopia: Evidence from Time Series Analysis

The general objective of the study was to analyze the impact of human capital development on economic growth in Ethiopia over the period 1974/5 -2018/9. The econometric models of Johnesan cointegration, VECM and causality tests were applied to analysis short-run and long-run impact of Human capital on Economic growth. The result of the error correction model shows that the model is adjusting at a relatively stable rate of 74.3% towards the long-run equilibrium. Furthermore, the result shows that human capital proxied of (primary and secondary school enrolments) and active labour force have a positive statistical significant long run and short-run effect on economic growth in Ethiopia. Such findings are consistent with the endogenous growth theories which argue that an improvement in human capital (skilled workers) improves productivity. In addition, results reveal that education expenditure and life expectancy at birth have a positive and statistically significant long-run effect on economic growth. However, the expenditure on health, secondary school enrolment and official development assistance are statically significant and have an unexpected negative impact on long-run economic growth. Furthermore, the short-run causality tests results reveal that public expenditure on education, primary school enrolment, secondary school enrolment and RGDP have unidirectional causal effects. Hence policymakers and/or the government give prioritize to create institutional capacity that increase school enrolment and strengthening the infrastructure or investment of educational and health institutions that produce quality of manpower to increase productivity.
Extended Belief Rule-Base Optimization Base on Clustering Tree and Parameter Optimization

Extended belief rule-based (EBRB) system has a better ability to model complex problems than belief rule-based (BRB) system. However, the storage of rules in EBRB system is out of order, which leads to the low efficiency of rule retrieval during the reasoning process. Therefore, to improve the efficiency of rule retrieval, this study introduces K-means clustering tree algorithm into the construction of rule base, then proposes a multi-layer weighted reasoning approach based on K-means clustering tree. The proposed approach seeks out a path on the tree during the rule retrieval process, and then figures out several reasoning results according to the nodes on the path. These results are weighted and aggregated to obtain the final conclusion of the system, thus ensure both the efficiency of reasoning and the sufficient utilization of information. In addition, the differential evolution (DE) algorithm is used to train the parameters of EBRB system in this study. Several experiments are conducted on commonly used classification datasets from UCI, and the results are compared with some existing works of EBRB system and conventional machine learning methods. The comparison results illustrate that the proposed method can make an obvious improvement in the performance of EBRB system.
Development of Business Model Digital Fraction Property Investment

Investing a property or real estate could be a challenge for Millennials generation. The increase in property prices is not in line with the increased of minimum wage that makes Millennials only afford to rent the property. To having an investment in property need more time in legal procedure, sometime need more than months. Fraction Property investment is a concept of investing property together. Separate the property in other format of digital assets distributed it to all more than one party. To implement this concept need to has a suitable business model and technology. Rising of industrial revolution 4.0, introduce the world with Blockchain Technology. The research is aiming to give better picture of new business model of investing on a property based on blockchain technology. With right business models, millennials generation will have another methods of investment on a property, that secure, easy and digital.
A Technique and Architectural Design for Criminal Detection based on Lombroso Theory Using Deep Learning

Crimes and criminal activities are increasing day by day and there are no proper criteria to search, detect, identify, and predict these criminals. Despite various surveillance cameras in different areas still, crimes are at a peak. The police investigation department cannot efficiently detect the criminals in time. However, in many countries for the sake of public and private security, the initiation of security technologies has been employed for criminal identification or recognition with the help of footprint identification, fingerprint identification, facial recognition, or based on other suspicious activity detections through surveillance cameras. However, there are limited automated systems that can identify the criminals precisely and get the accurate or precise similarity between the recorded footage images with the criminals that already are available in the police criminal records. To make the police investigation department more effective, this research work presents the design of an automated criminal detection system for the prediction of criminals. The proposed system can predict criminals or possibilities of being criminal based on Lombrosso's Theory of Criminology about born criminals or the persons who look like criminals. A deep learning-based facial recognition approach was used that can detect or predict any person whether he is criminal, or not and that can also give the possibility of being criminal. For training, the ResNet50 model was used, which is based on CNN and SVM Classifiers for feature extracting from the dataset. Two different labeled based datasets were used, having different criminals and noncriminals images in the database. The proposed system could efficiently help the investigating officers in narrowing down the suspects' pool.
Blended learning technologies for a foreign language teaching the students of non-philological majors

Modern theories of foreign language teaching are getting developed. The constant society digitalization influences it. Generation Z students closely associate their lives with technology. Moreover, teachers must find ways to apply effectively information and communication technologies in the learning process. In our opinion, one of the ways is the concept of blended learning. It implies the optimal combination of traditional pedagogical technologies and distance, online learning. The purpose of our research is to examine the effectiveness of the concept of blended learning in the process of learning a foreign language for students of non-philological majors. For this purpose, we conducted a pedagogical experiment. It assumes the introduction of the concept of blended learning in the educational process of higher education. The research was carried out with Ukrainian students of non-philological majors during the study of English (offline and online). Also, international students who are studying Ukrainian as a foreign language were involved. Comparative analysis of students' readiness to learn using different blended learning tools was used. Methods of mathematical statistics (nonparametric Kruskal-Wallis and Mann-Whitney criteria) were utilized to analyse and process the experimental data. The results of the study indicate the effectiveness of blended learning technology usage in the process of foreign language teaching. Nevertheless, they show that the proposed tools help students better master a foreign language. Besides, students are both in active learning and passively reinforcing their knowledge using digital technologies during education. The authors consider it indisputable that blended learning tools should be used to some extent for students of all majors. The authors understand that the proposed tools are not exhaustive and definitive. Their list should be extended, and the use of specific tools depends on the teacher, students, the course, and other factors.
2D Optimal Trajectory Planning Problem in Threat Environment for UUV with Non-Uniform Radiation Pattern

Path planning is necessary in many applications using unmanned underwater vehicles (UUVs). The main class of tasks is the planning of safe routes with minimal energy costs and/or minimal levels of emitted physical and information signals. Since the action planner is on board the UUV, the main focus is on methods and algorithms that allow it to build reference trajectories while minimizing the number of calculations. The study is devoted to the problem of the optimal route planning for a UUV with a non-uniform radiation pattern. The problem is stated in the form of two point variational problem for which necessary and sufficient optimality conditions are proved. Particular attention is paid to cases where optimality conditions are not met. These cases are directly related to found specific forms of a radiation pattern. Sufficient optimality conditions are extended on the class of two-link and multi-link motion paths. Software tools have been developed and computer simulations have been performed for various types of radiation patterns.
MOBILE LEARNING: TOOLS AND SERVICES, FUNCTIONS AND OPPORTUNITIES

The relevance of the research is conditioned by the increasing role of the use of mobile learning technologies and services in the educational process of higher educational institutions.The article discusses the issues related to the role of mobile learning in the formation of a new educational environment.It presents the analysis of the main formation and development stages for the mobile learning system, its legislative form and development prospects.The research identifies the reasons that hinder the development of mobile learning in Russia and the factors contributing to its spread.The authors consider tools and services of mobile learning from the point of view of target and functional purpose.They describe the advantages and disadvantages of the use of these tools and services in teaching students.
Implementasi Sistem Pakar untuk Mendeteksi Virus Covid-19 dengan Perbandingan Metode Naïve Bayes dan Certainty Factor

The Covid -19 virus spread in the world, especially in Indonesia, very fast. This epidemic is of concern around the world because it has a quite bad impact in various sectors. With existing technological advances, the Expert System can assist medical personnel in detecting the Covid -19 Virus. The purpose of the author in conducting the study was to detect the Covid-19 virus as easily as possible with symptom data obtained from patients who had consultations. The Naïve Bayes method is a method that uses probability and statistics that can predict a person's chance of being exposed to Covid-19 in the future based on symptoms experienced in the previous period packed with a web-based program. For comparison, the author uses the Certainty Factor Method. Certainty Factor is a method that aims to determine the certainty value which is based on the previous calculation of CF value by manual calculation. The Naïve Bayes method can group the symptoms obtained from the official WHO website which has been given an indicator of the percentage of someone exposed to the Covid-19 Virus based on the symptom data experienced to determine a person exposed to the Covid-19 Virus. While the Certainty Factor method gets the confidence of someone exposed to the symptoms of the Covid-19 virus by using the calculation indicator on the CF value that has been consulted by the user, which can provide a percentage level of confidence that is 86%.Keywords:Expert System, Covid-19, Naive Bayes, Certainty Factor.
Quantum Markov Chains Associated with Unitary Quantum Walks

In this paper we discuss the quantum Markov chains of unitary quantum walks.The construction of the quantum Markov chain associated with a unitary quantum walk serves as a good example in the view point of quantum Markov chains.On the other hand, the method of quantum Markov chain provides a tool for the investigation of dynamical properties of the unitary quantum walks.We discuss the reducibility/irreducibility and the recurrence/transience properties.Comparing with the results known in other literature and in classical random walks, we will see some similarity as well as some differences.