Reviewerly/exHarmony huggingface dataset:
Internet Wizard for Enhancing Open-Domain Question-Answering Chatbot Knowledge Base in Education

Chatbots have gained widespread popularity for their task automation capabilities and consistent availability in various domains, including education. However, their ability to adapt to the continuously evolving and dynamic nature of knowledge is limited. This research investigates the implementation of an internet wizard to enhance the knowledge base of an open-domain question-answering chatbot. The proposed approach leverages search engines, particularly Google, and its features, including feature snippets, knowledge graph, and organic search, in conjunction with data science and natural language models. This mechanism empowers the chatbot to dynamically access the extensive and up-to-date knowledge available on the web, enabling the provision of real time and pertinent answers to user queries sourced from web documents. A pilot study in a higher education context evaluated the chatbot’s mechanism and features, confirming its proficiency in generating responses across a broad range of educational and non-educational topics. Positive feedback and high user satisfaction validate these findings. Notably, the chatbot’s dynamic feature of retrieving related or follow-up questions from search engines significantly enhances student engagement and facilitates exploration of supplementary information beyond the curriculum.
Deep-Reinforcement-Learning-Based Wireless IoT Device Identification Using Channel State Information

Internet of Things (IoT) technology has permeated into all aspects of today’s society and is playing an increasingly important role. Identity authentication is crucial for IoT devices to access the network, because the open wireless transmission environment of the IoT may suffer from various forms of network attacks. The asymmetry in the comprehensive capabilities of gateways and terminals in the IoT poses significant challenges to reliability and security. Traditional encryption-based identity authentication methods are difficult to apply to IoT terminals with limited capabilities due to high algorithm complexity and low computational efficiency. This paper explores physical layer identity identification based on channel state information (CSI) and proposes an intelligent identification method based on deep reinforcement learning (DRL). Specifically, by analyzing and extracting the features of the real received CSI information and a setting low-complexity state, as well as action and reward parameters for the deep neural network of deep reinforcement learning oriented to the scenario, we obtained an authentication method that can efficiently identify identities. The validation of the proposed method using collected CSI data demonstrates that it has good convergence properties. Compared with several existing machine-learning-based identity recognition methods, the proposed method has higher recognition accuracy.
Similarity-based parameter transferability in the quantum approximate optimization algorithm

The quantum approximate optimization algorithm (QAOA) is one of the most promising candidates for achieving quantum advantage through quantum-enhanced combinatorial optimization. A near-optimal solution to the combinatorial optimization problem is achieved by preparing a quantum state through the optimization of quantum circuit parameters. Optimal QAOA parameter concentration effects for special MaxCut problem instances have been observed, but a rigorous study of the subject is still lacking. In this work we show clustering of optimal QAOA parameters around specific values; consequently, successful transferability of parameters between different QAOA instances can be explained and predicted based on local properties of the graphs, including the type of subgraphs (lightcones) from which graphs are composed as well as the overall degree of nodes in the graph (parity). We apply this approach to several instances of random graphs with a varying number of nodes as well as parity and show that one can use optimal donor graph QAOA parameters as near-optimal parameters for larger acceptor graphs with comparable approximation ratios. This work presents a pathway to identifying classes of combinatorial optimization instances for which variational quantum algorithms such as QAOA can be substantially accelerated.
Relationships Among Reading Interest, Reading Self-Efficacy, And Reading Competency In The Junior High School

The objective of this study was to describe and relate the students’ reading interest, reading self-efficacy to the students reading competency in the Junior High School in Singaraja. This study applied quantitative research. There were 94 students as samples by using cluster quota sampling. The data were collected through a reading interest scale, a reading self-efficacy scale, and an objective reading competency test. The obtained data were analyzed descriptively and inferentially. The descriptive analysis consisted of central tendency measures and dispersion. While inferential analysis, the data were analyzed using pair-wise correlation and multiple correlation technique. The findings show that: 1) the students’ reading interest, reading self-efficacy, and reading competency on high-order-items proven to be at the moderate levels; 2) the relations pair-wisely between the students’ reading interest and reading self-efficacy, students’ reading interest and reading competency, the students’ reading self-efficacy and reading competency on high-order-items are positively and significantly correlated; and 3) the simultaneous relationships of the reading interest and reading self-efficacy to the students’ reading competency is proven to be significant. In order to develop high students’ reading interest, reading self-efficacy, and reading competency, the school and EFL teachers should provide literacy programs in reading. Previous researches show that literacy-rich environments tend to be effective ways to support the development of literacy in reading by sharing book readings. The EFL students should be trained millennial reading strategy, emphasizing the four skill dimensions, namely critical thinking skill in reading, creative effort in reading processes, collaborative endeavors in working on high-order-items, communicative skills in working out the reading indicators.
Lay Evaluations of Restraints and Prohibitions During the 1st, 2nd, and 4th Wave of the COVID-19 Pandemic in Lithuania

The article analyzes how, during the separate waves (the 1st, 2nd, and the 4th) of the coronavirus pandemic, participants of a study (overall n = 1356) assessed the government-imposed restrictions, prohibitions, liabilities and penalties for non-compliance with said restrictions, the perceived fairness of the behavior of other people during the pandemic, and the changes of their assessments during the coronavirus pandemic. Obtained evidence suggests that during the Covid-19 pandemic (from the 1st to the 4th wave) the participants of the study assessed the non-compliance with restrictions and prohibitions more and more forgivingly.
Development of solar radiation measurement sensor with added value to promote wide-area solar power prediction technology

In this study, we investigated a scenario where the prediction technology for the total output of distributed photovoltaic power generation over a wide area could be more efficiently disseminated by sharing the costs with society, rather than burdening only specific companies with the costs. To achieve this goal, we not only focused on measuring the amount of solar radiation but also incorporated additional parameters into the solar radiation sensor, which is essential for improving the accuracy of the prediction technology. The fundamental configuration of the developed sensor consists of an organic thin film solar cell (OPV), and the output is utilized to transmit the output data externally. Utilizing the surplus power from the OPV, we examined and produced three types of sensors: 1) a sensor with a CO2 measurement function, 2) a sensor with a mist spray function, and 3) a sensor with a photography function using a drive recorder. As a result, all sensors met the predetermined functions and target specifications.
The potential for the holistic development of research culture among technical university students based on generalized competencies

The aim of the study is to reveal the potential for the holistic development of research culture among technical university students based on the analysis of the existing educational standards of higher education. The paper substantiates the need for research culture formation among technical university students as a way to improve their professional competence in solving research and innovation tasks, presents the results of analysing the educational standards of higher education in areas of training related to engineering, technology and technical sciences, which reflect certain aspects of the development of students’ research culture in terms of the mastery of universal and general professional competencies. The scientific novelty of the study lies in identifying contradictions in the system of engineering and technical personnel training due to the lack of an integral system for research culture formation among students. As a result of the study, the generalized competencies reflecting aspects of research culture development among students in engineering and technical fields were formulated. It was found that the generalized competencies characterizing the holistic development of research culture among technical university students are presented fragmentarily. The paper outlined the directions for improving the system of engineering and technical personnel training based on research culture formation.
Like a sticker

Abstract This study explores a new type of grammaticalisation, namely, grammatical constructionalisation , based on an investigation of the use of a newly emerging construction, the [X. jpg ] construction, in online forums in Taiwan. JP (E)G stands for ‘Joint Photographic Experts Group’. As an abbreviation for the file extension of images, it was initially attached to image files in computers. However, in Taiwanese Mandarin, new usages for it have developed, whereby it can be attached to any phrase, including those without any source images, thereby simply pretending that the phrase has an attached image. Since the file extension .jpg is a technical term and a bound morpheme, when it extends to attenuating the force of the speech act, it functions as a pragmatic marker or hedge. This process of change from lexical to grammatical is known as grammatical constructionalisation and reveals the results of the interplay between popular Internet memes and user psychology. When using [X. jpg ], users tend to downtone the speaker’s attitude, increase solidarity among insiders and pursue vividness and a sense of humour. This usage initially emerged under the technical limitations of a text-only online environment. The findings of this study suggest that the constructionist approach is an efficient, unified theoretical framework for its explanatory adequacy in addressing issues concerning both synchronic lexical semantics and diachronic grammatical change.
The Influence of Locus of Control in the Choice of Coping Strategies for Teachers

Key words: strategy of coping and self-control, internal external processes, stress, coping behavior, coping resources, coping mechanisms The article discusses the theoretical approaches of coping, coping behavior, coping strategies and locus of control. A brief theoretical analysis of the theory of coping, the components of coping strategies, the definition and role of locus of control is presented. In the context of the modernization of education and the intensive search for new technologies in educational practice, the issue of maintaining the psychological health of a school teacher becomes a matter of extreme importance. There is a positive relationship between the presence of certain coping strategies and the degree of emotional burnout of teachers, namely, teachers with a formed phase of emotional burnout are dominated by non-adaptive coping strategies, while teachers with an unformed phase of emotional burnout are dominated by non-adaptive coping strategies. Also the article presents the data of our empirical study and their analysis based on a sample of teachers, in which the dependence of coping strategies on the locus of control was revealed. The nature and method of overcoming stressful situations is a special category of resources for stress resistance and coping techniques, which includes strategies and models of coping behavior or coping strategies. The preconditions for the formation of a burnout syndrome, requires the use of unproductive coping mechanisms, such as the non-adaptive mental processes and unproductive emotional and behavioral responses. We revealed significant relationships between coping strategies in problem solving and two scales of subjective control: internalization and general internalizing attitudes towards health and illness, as well as an inverse relationship between problem avoidance coping strategies and internalization of achievements. Based on the semantic meaning of the locus of control in the theory of J. Rotter and the coping strategy in the interpretation of D. Amirkhan, it can be assumed that the locus of control is a more fundamental personal characteristic than the strategy of coping behavior itself, and it is the locus of control that influences the choice of strategy. DOI։ https://doi.org/10.58726/27382915-2023.1-438
On Some Applications of the Method of Dimensional Analysis in the Course of Physics and Mathematics

Key words: problem, non-dimensional coefficient, quantity, exponent, dependence In the article, it was attempted to classify and represent the effective applications of the dimensional analysis method in the process of solving problems based on the principle of gradual complexity, which is the scientific and methodological novelty of the work, in order to highlight the role of the method in ensuring the informality and effectiveness of training. Particular attention is paid to the issues of the limits of the method’s applicability. In the first part of the work, the essence of the dimensional analysis method is briefly outlined, and then the simplest problems easily solved by its direct application are considered. The next section represents the cases when the desired physical expressions determined by this method can be uniquely determined with the accuracy of a constant dimensionless factor. As an example, the problem of determining the period of an oscillatory circuit is solved. The cycle of physical problems ends with a discussion of the problem of the Casimir phenomenon, for the solution of which, along with the method of dimensions, additional physical reasoning is used. When getting acquainted with the method of dimensional analysis, an initial erroneous impression may arise that the method is most applicable in physics, and is unlikely to have a possible effective application in mathematics. However, this is not true. No wonder the famous physicist, academician Migdal began his famous book on approximation and modeling of physical phenomena by proving the Pythagorean theorem using the dimensional analysis method. In the last section of the work, some tasks and test tasks of mathematics are considered, in the solution of which the dimensional analysis method is used.
Study and Case of Early Childhood Education and Elementary school-linked Programs and Yokohama City in Japan

본 연구는 2022년 문부과학성에서 3년간 운영을 목표로 본격적으로 시작한 유･초 연계 프로그램 정책을 중심으로 배경, 과제, 방향을 살펴보았다. 연구방법은 문헌연구이다. 자료는 문부과학성 보고서, ‘발달’ 연구지 등을 참고했다. 그 배경은 보육･교육과정 운영상, 무상화 지속과 보육과 교육의 질 향상, 사회 변화와 특별 아동 대응, 지속 가능한 사회를 위함이었다. 과제는 인식 공유 부족, 교육의 질을 확보하기 위한 수단 부족, 격차 없는 교육의 문제, 다양성 배려 및 교육의 질 보장의 문제, 교육 기회가 충분하지 않은 아동과 가정의 문제이다. 방향은 보육과 교육의 질에 관한 인식 공유, 유아가 갖출 능력과 각 기관 자원 및 특수성 고려, 모든 유아의 삶의 질 보장, 전국적 전개를 통한 교육의 질 보장과 전문성 향상, 기관의 역할 인식과 연계･협동이다. 문부과학성 프로그램과 요코하마시 사례를 통해 ‘아동이 배웠으면 하는 자질과 능력’을 어떻게 키워주고 길러주는가를 알 수 있었다. 시사점은 한국도 지속 가능한 사회를 고려, 교육부 차원에서 보다 적극적으로 유･초 연계 프로그램을 시행할 필요가 있다는 것이다.In this study, the background, tasks, and directions of early childhood education and elementary school-linked program policies, which were launched in earnest by the Ministry of Education and Science for three years in 2022, were first examined. The method of research is literature research. The data were referred to the Ministry of Education, Culture, Sports, Science and Technology report and the ‘development’ research paper. The background is for the continuation of free childcare and the improvement of the quality of childcare and education, social change and response to special children, and a sustainable society. The tasks include lack of awareness sharing, lack of means to secure quality of education, consideration of education and diversity without gaps, ensuring quality of education, and children and families with insufficient educational opportunities. The direction is to share awareness of the quality of childcare and education, consider the capabilities and resources and specificity of each institution, guarantee the quality of life of all infants, improve the quality of education and expertise through nationwide development, and link and cooperate with the role of institutions. Yokohama City, which has been examined as an example of the Ministry of Education, Culture, Sports, Science and Technology, seems to be how it develops and fosters “the qualities and abilities that children want to learn.” The implication is that Korea also needs to more actively implement early childhood education and elementary school linkage programs at the Ministry of Education level in consideration of a sustainable society.
Improving Students' Writing Skills Through Media Wall Magazines in Indonesian Language Learning

This study aims to increase learning achievement. Especially in Indonesian subjects. This is done because: (1) Indonesian academic achievement from year to year is unsatisfactory, (2) Many students are sleepy during Indonesian lessons, and (3) students are not very interested in Indonesian Language Lessons. This research uses a Classroom Action Research approach. (PTK) with a two-cycle system. The research subjects were fifth grade students at SD Negeri Tiron 01 Madiun Regency. Data collection techniques applied are tests and observations. Data analysis was carried out using a qualitative approach that focused on student achievement, student activity in learning, and learning implementation. The results of the study showed that the learning achievement of the Indonesian language students of class V at SD Negeri Tiron 01 Madiun Regency. Increasing the percentage of classical learning completeness from 83.3% (4 of 9 students) in Cycle I to 51.38% (7 of 9 students) in Cycle II. Student activity in learning also experienced an increase in the percentage of classical student activity from 50.00% (3 of 9 students) in Cycle I to 83.33% (6 of 9 students) in Cycle II. It can be concluded that using wall magazines can improve the learning achievement of fifth grade students. The findings in this study are wall magazines can provide inspiration for students to be able to express their ideas and creativity in written form. Through wall magazines, students can develop their writing potential so that they become better and better quality.
Blockchain and AI-assisted Onion Routing Protocol for Strengthening Anonymity in Beyond 5G IoMVs Networks

This paper overcomes the security and privacy issues of the Internet of military vehicles (IoMVs), wherein the attackers intercept and manipulate the IoMV communication to disrupt military operations. Moreover, IoMV communication uses the public Internet to route their sensitive data, which is open to several network-related attacks, such as data injection, session hijacking, privilege escalation, etc. To overcome the aforesaid security and privacy concerns, we proposed a blockchain and artificial intelligence (AI)-assisted onion routing framework to strengthen the security and anonymity of IoMVs participating in military operations. AI algorithms are amended to classify the malicious and non-malicious IoMVs so that only non-malicious IoMVs can participate in the data exchange via the onion routing network. In addition, each IoMV is uniquely identified by two identifiers, i.e., tag and verifying token, which is stored in the block of a blockchain. These identifiers authenticate and validate the participating IoMVs. Based on that, non-malicious IoMVs can participate in the onion routing network to securely transmit sensitive data. Further, each entity of the proposed framework utilized the indispensable characteristics of a 6G network to minimize the data loss and validated using the packet drop ratio parameter. Lastly, the proposed framework is evaluated using different evaluation metrics, such as statistical measures and blockchain processing time.
Opinion Mining with Interpretable Random Forests

This paper proposes an interpretable random forest for opinion mining on hotel reviews. This model performs the task of sentiment polarity about hotel as positive or negative. In addition, we constructed the criteria importance measures to explain and clarify the relationship and interactions of the hotel name, hotel aspect, hotel reviewer, and reviewer time affects the orientation of sentiment is negative or positive. An interpretable random forest was evaluated on three scenarios, which we built based on important features of the hotel reviews. The experimental results on the hotel reviews data set have shown the effectiveness of the proposed issues.
FGW-VnText: A Deep Learning-based System for Detecting and Recognizing Vietnamese Identity Cards and Citizen Identities

Electronic Know Your Customer (eKYC) technology is an online solution to identify and verify a customer’s identity, which is now widely used in the banking sector or public administrative services. One of the first critical steps in any eKYC process is extracting identity cards (ID Cards) or citizen identification (Citizen ID) information. These identity documents, however, are often varied in even each country. For example, in Vietnam, three valid but different types exist: 12-digit ID Card, 12-digit Citizen ID without a chip, and 12-digit Citizen ID with a chip. Intending to build an effective and robust end-to-end system for detecting and automatically extracting information from different types of ID Cards and Citizen IDs, this study proposes a system that integrates YOLOv5, CRAFT detection, and VietOCR in one deep learning pipeline. The experimental results on the collected data show that our proposed model brings more accurate performance than some recent related studies. The exact match results on the 12-digit ID card reached an average of 94.64%, the 12-digit citizen ID without a chip reached an average of 93.15%, and on the 12-digit citizen ID with a chip, an average of 90.57%.
Prediction method of photovoltaic power based on combination of CEEMDAN-SSA-DBN and LSTM

Aiming at the problem of high fluctuation and instability of photovoltaic power, a photovoltaic power prediction method combining two techniques has been proposed in this study. In this method, the fast correlation filtering algorithm has been used to extract the meteorological features having a strong correlation with photovoltaic power generation. The complete ensemble empirical mode decomposition with an adaptive noise model has been used to decompose the data into high and low-frequency components to reduce the data volatility. Then, the long short-term neural network and the deep confidence network were combined into a new prediction model to predict each component. Finally, the proposed combined photovoltaic power prediction method has been analyzed using an example and compared with the other prediction methods. The results show that the proposed combined prediction method has higher prediction accuracy.