Reviewerly/exHarmony huggingface dataset:
CONDITIONS FOR IMPROVING THE PROFESSIONAL COMPETENCE OF A TEACHER OF ENERGY DISCIPLINES BASED ON MODERN INFORMATION TECHNOLOGIES

The article examines the existing experience of using modern information technologies in the educational process, considers the possibilities of their application to increase the professional competence of the teacher of energy disciplines in the conditions of distance education. The method of organizing the professional training of teachers for the effective use of modern information technologies in pedagogical activities is proposed. The range of issues related to the substantiation of requirements for the use of modern information technologies in the educational process, which has a powerful impact on the results and quality of work of the higher education institution, is outlined. An overview of the existing experience of using modern information technologies to improve the professional competence of the teacher of energy disciplines is considered. The professionalism of a modern teacher of energy disciplines in the conditions of distance education consists not only in the knowledge of his subject and the methodology of its teaching, but also in the need to possess modern information technologies - competence and the desire to possess information culture. Attention is paid to the issue of formation and development of the informational and pedagogical competence of the teacher of energy disciplines. The informational and pedagogical competence of a teacher of energy disciplines is defined as his readiness and ability to independently use MIT in pedagogical activities to solve a wide range of educational tasks and to design ways of improving qualifications in this field. In the new conditions, the professional career of any teacher depends on how well he is able to find and receive, perceive and use new information in the educational process in the conditions of distance education in a timely manner. And for this, a modern teacher must develop the ability to manage the educational process and self-evaluate the information received. It is also considered how the use of modern information technologies facilitates the activities of the teacher of energy disciplines in conducting classes. Possibilities of using modern information technologies at all stages of conducting modern classes in the conditions of distance education. Key words: professional competence, informational and pedagogical competence, teacher of energy disciplines, modern information technologies, educational process.
FORMATION OF THE ABILITIES AND SKILLS OF WORKING WITH SCIENTIFIC TEXTS IN THE LANGUAGE TRAINING PROCESS FOR HIGHER EDUCATION STUDENTS IN THE CLASSES OF THE COURSE «UKRAINIAN LANGUAGE (BY PROFESSIONAL DIRECTION)»

The formation of abilities and skills of work with scientific texts in the process of language training for higher education students is an actual problem of modern pedagogy, as bachelor’s mastering of technologies to work with these texts allows to develop the scientific competence of the future specialist. At the classes on the educational discipline «Ukrainian language by professional direction» the main attention is paid to the formation of abilities and skills of higher education graduates to interact freely in the sphere of professional communication, and to create primary and secondary scientific texts on a specialty profile. The purpose of this article is to describe the technology of drawing up the secondary scientific texts (plan, theses, abstract) to form the abilities and skills of higher education graduates in the analytical-synthetic processing of original text. Research methods applied: analysis and synthesis of scientific literature (to clarify the key concepts of the study), systematization (in order to identify existing scientific approaches to solving the problem), theoretical generalization (to formulate the final provisions and conclusions). The article considers the signs of scientific text (integrity; connectivity; consistency; information-format, logical, estimated saturation), which is important in the process of compression of the primary text, i.e. reduction of the volume of written without loss for its content. The compression of scientific text provides maximum reproduction of the content with a smaller number of language means. The article analyzes the peculiarities of the compression stages of secondary scientific texts. The appointment of different types of plan (expanded, interrogative, nominal and quote) is outlined. The types of theses (chosen by the quote author from the first place and handed over by his own words the most important of his provisions) were considered, the difference between the plan and theses was confirmed. Specific features of different types of abstract (informative, indicative, overview) are described. The text creation of these genres in scientific style according to the technology mentioned in the article helps to form the necessary abilities and skills of scientific and research activity in the higher education graduates.
Pengujian Long-Short Term Memory (LSTM) Pada Prediksi Trafik Lalu Lintas Menggunakan Multi Server

This study presents a test of the long short term memory (LSTM) algorithm on traffic prediction with multi edge server and cloud server architectures. IoT sensors located on the roadside such as cameras and location data on each driver are used and stored in the data center. When a driver sends a travel time request to a nearby edge server, traffic predictions will be made on the edge server or cloud server. Server selection is made based on the destination location of the driver's request. If the destination is in the edge server area, traffic predictions are made on the edge server. However, if the destination is in the cloud server area, traffic predictions are made on the cloud server. Then to predict traffic traffic is done with LSTM. following modeling is made with a density of 128 and a density of 256. By learning from previous traffic, LSTM with a greater density gets a proportion of errors, namely RMSE 10.78%, MAE 8.24%, and MAPE 19.87%.
Enabling High-Quality Machine Learning Model Trading on Blockchain-Based Marketplace

Machine learning model sharing markets have emerged as a popular platform for individuals and companies to share and access machine learning models. These markets enable more people to benefit from the field of artificial intelligence and to leverage its advantages on a broader scale. However, these markets face challenges in designing effective incentives for model owners to share their models, and for model users to provide honest feedback on model quality. This paper proposes a novel game theoretic framework for machine learning model sharing markets that addresses these challenges. Our framework includes two main components: a mechanism for incentivizing model owners to share their models, and a mechanism for encouraging the honest evaluation of model quality by the model users. To evaluate the effectiveness of our framework, we conducted experiments and the results demonstrate that our mechanism for incentivizing model owners is effective at encouraging high-quality model sharing, and our reputation system encourages the honest evaluation of model quality.
INTRODUCING A BIOMETRIC AGE-VERIFICATION SYSTEM: A NEW APPROACH TO CURBING AGE CHEATING IN CIVIL-SERVICE AND OTHER PROFESSIONS IN GHANA

Age cheating is a widespread problem in many professions in Ghana, including civil-service, sports, and entertainment. This practice compromises the integrity of the affected professions and denies deserving candidates of opportunities. This paper proposes the introduction of a biometric age-verification system as a new approach to curbing age cheating. The proposed system will leverage biometric data such as fingerprints, facial recognition, and iris scans to verify the age of candidates. This paper presents the benefits of a biometric age-verification system, including increased accuracy, efficiency, and transparency. Furthermore, the paper discusses the potential challenges of implementing such a system and suggests ways to address them. Overall, the proposed biometric age-verification system is a promising solution to curb age cheating in civil-service and other professions in Ghana.
CORRUPTION CRIME AND ITS SITUATION IN MODERN SOCIETY

In this article, the author made some comments on some issues of corruption crime and its situation in modern society in accordance with the criminal legislation of the Republic of Uzbekistan. Also, this article examines the concept and features of the corruption crime and its situation in modern society, analyzes the opinions of scientists. The relevant proposals and recommendations for improving the norms of the criminal law related to the corruption crimes are also given.
A Practical Significant Technic in Solving Overfitting: Regularization

The passage mainly discusses the solution to overfitting. Overfitting usually happens when people are training their machine learning models. When a model is overfitted, it only fits one particular dataset and misses most of the data points from another dataset. This problem affects the model's performance and makes it unable to use for its purpose. So how to solve this problem with significance and practical meaning? At the beginning of the passage, I will introduce some theoretical foundations for overfitting. Then I will define the concept of overfitting and show an example of overfitting in the machine learning model. After that, I will tell you how to pick the correct model with the testing set. Then, the passage focuses on the discussion of regularization, which is a helpful technique for solving overfitting. And I will compare the L1 and l2 regularization to help you find the suitable one.
Research on Quantum Computers Characteristic

Quantum computing is the engineering of utilizing the properties of a quantum, as so could be understood as the using the rules of nature at the scale of an atom, to calculate faster and more complicated problems than traditional computers. These new inventions are not merely a device that calculates faster than the speed convention computers, the only similarity between them might only be some essential hardware and their names, because unlike conventional computers that uses classical physics to transmit electronic information, quantum computers utilize quantum physics to perform calculations. Quantum computing has the potential to replace conventional computers in solving important problems in fields such as chemistry, cryptography, materials science, medicine, and artificial intelligence, which are all task that are uneasy and sometimes devastating for conventional computers to do. Quantum computers characteristics includes but are not limited to: stronger information processing abilities and a faster calculation speed. Compared with traditional computers, the greater the amount of information it processes, the better a quantum computer can calculate a more accurate result. This paper is focused on researching and explaing the characteristics of quantum computers and their possible contributions to the human society.
UTILIZATION OF INFORMATION AND COMMUNICATION TECHNOLOGY MEDIA IN DISTANCE LEARNING IN THE UPPER GRADE OF ELEMENTARY SCHOOL

Along with the Covid-19 pandemic and the issuance of a Circular Letter from the Minister of Education and Culture regarding the Implementation of Education in an Emergency Period, the Indonesian education system has also adapted by implementing distance learning. This distance learning forces teachers and students to change the concept of learning in class to learning in cyberspace using existing information and communication technology media. This study aims to identify and explain what information and communication technology media are used in distance learning in the upper grades of elementary schools, and how to implement their use. The collection of research data uses the library study method and uses secondary data collected from articles, and journals. The criteria for the selected data are regarding the utilization of information and communication technology media in the upper grades of elementary schools during distance learning From several sources obtained, finally the most relevant was selected and 13 articles were obtained. The results of this literature study research are information and communication technology media used during distance learning in upper grades in several elementary schools are Zoom, Google Classroom, gadgets, animated videos, Google Forms, Google Sites, Quizizz, MS 365, WhatsApp, WPS, Youtube and the Rumah Belajar portal. Blended learning and e-learning systems are also worth trying to use in distance learning.
The Impact of Puppet Show Media on Grade 3 Students' Listening Skills at SDN 1 Syamtalira Bayu

The low creativity of teachers in determining learning media makes students experience difficulties in listening. One of the things that underlies the achievement of learning is the availability of media in the teaching and learning process. Therefore, the researcher formulated this study with the title "The Influence of Puppet Show Media on Students' Listening Skills in Theme 2 Class 3 SDN 1 Syamtalira Bayu". The purpose of this study was to determine whether or not there was an effect of the use of puppet show media on listening skills in grade III elementary school students. The method used is quantitative with a quasi-experimental approach. Sources of research data were all grade III of SDN 1 Syamtalira Bayu, totaling 21 students in the experimental class and 21 students in the control class. The data collection technique in this study was a test with the results of the research that there was an influence by using Puppet Show media on the listening ability of class III students. In testing the hypothesis, the price of tcount is 2,164 and ttable is 1,683 after testing at a significant level α = 0.05/2 and df = 40 based on the criteria for testing the hypothesis, then reject H0, because tcount &gt; table, namely 2,164 &gt; 1,683, then Ho is rejected, Ha is accepted, which means there is an influence in the use of puppet show media on students' listening skills on the theme of class 2 class III SDN 1 Syamtalira Bayu.
Fuzziness Based Semi-supervised Deep Learning for Multimodal Image Classification

Predicting a class or label of text-aided image has practical application in a range of domains including social media, machine learning and medical domain. Usually, supervised learning model is used to make such predictions where labeled data is mandatory, which is time consuming and required manual help. Classification of images are accomplished on visual features only by utilizing deep learning. Employing semi-supervised learning is a viable answer to these issues that needs a few label sample to classify huge unlabeled samples. The paper suggests a novel semi-supervised deep learning method based on fuzziness, called (FSSDL-MIC) for multimodal image classification to tackle the challenge of web image classification. For the first time in this scenario, we integrate Multilayer perceptron for textual features and MobileNetV2 for visual features to create a multimodal paradigm. Using data from PASCAL VOC’07, experiments have revealed that the proposed framework achieves significant improvement and outperforms modern techniques for multimodal image categorization. We also see a positive impact of low fuzzy sample when final model trained with visual features only.
Research on the Smart Teaching Mode of College English from the Perspective of Internet+

With the continuous development of information technology in recent years, it has begun to be applied in higher education.Smart teaching mode can be applied in College English teaching.It helps to improve college English teaching quality to a certain extent.This paper mainly explores the strategies of applying smart teaching mode in college English from the perspective of Internet +.
Development of Android-Based BIPAS Learning Media in MI/SD

Learning media is something that has an important role in the learning process, with the presence of learning media material that was previously difficult for students to understand or even abstract will become concrete with the help of learning media. The purpose of this study was to produce android-based BIPAS learning media on the theme "Beautiful Togetherness" subtheme "Togetherness in Diversity" Learning 1 which contains Indonesian language, science, and social studies (BIPAS) material. This development research uses the Research and Development (R&amp;D) method with the 4D development model, this model uses 4 stages including Define, Design, Develop and Disseminate. The results of this study produced that the android-based BIPAS learning media is of good quality. Proven by the results of validation by material experts obtained a percentage of 80.68%, while validation by media experts obtained a percentage of 93.33%. so that this product can be said to be valid material experts and media experts. The results of students' responses obtained a percentage of 88.97% in the Very Good category.
An Efficient Feature Subset Selection with Fuzzy Wavelet Neural Network for Data Mining in Big Data Environment

Big data refers to the massive quality of data being generated at a drastic speed from various heterogeneous sources namely social media, mobile devices, internet transactions, networked devices, and sensors. Several data mining (DM) and machine learning (ML) models have been presented for the extraction of knowledge from Big Data. Since the big datasets include numerous features, feature selection techniques are essential to eliminate unwanted and unrelated features which degrade the classification efficiency. The adoption of DM tools for big data environments necessitates remodeling the algorithm. In this aspect, this paper presents an intelligent feature subset selection with fuzzy wavelet neural network (FSS-FWNN) for big data classification. The FSS-FWNN technique incorporates Hadoop Ecosystem tool for handling big data in an effectual way. Besides, the FSS-FWNN technique involves three processes namely preprocessing, feature selection, and classification. In addition, quasi-oppositional chicken swarm optimization (QOCSO) technique is employed for the feature selection process and the FWNN technique is applied for the classification process. The design of QOCSO algorithm as an FS technique for big data classification shows the novelty of the work and the feature subset selection process considerably enhances the classification performance. An extensive set of simulations is carried out and the results are reviewed in terms of several evaluation factors in order to analyse the improvement of the FSS-FWNN approach. The experimental findings demonstrated that the FSS-FWNN approach outperformed the most current algorithms.
Analisis Strategi Guru Dalam Meningkatkan Keterampilan Berbicara Siswa Dalam Proses Pembelajaran Kelas IV di SDN 7 Kesu’

The purpose of this study was to describe the teacher's strategy in improving students' speaking skills in the fourth grade learning process at SDN 7 Kesu'. This type of research is descriptive qualitative research. The source of this research is the fourth grade teacher at SDN 7 Kesu. Data collection techniques used are observation, interviews, and documentation. Data analysis technique with data reduction stages, data study, and drawing conclusions. The results of the study concluded that strategies that can improve students' speaking skills are by conducting simulation activities (simulation games), storytelling and telling stories, inviting students to play characters in a story, and inviting students to have conversations.
Discovery of crime event sequences with constricted spatio-temporal sequential patterns

Abstract In this article, we introduce a novel type of spatio-temporal sequential patterns called Constricted Spatio-Temporal Sequential (CSTS) patterns and thoroughly analyze their properties. We demonstrate that the set of CSTS patterns is a concise representation of all spatio-temporal sequential patterns that can be discovered in a given dataset. To measure significance of the discovered CSTS patterns we adapt the participation index measure. We also provide CSTS-Miner : an algorithm that discovers all participation index strong CSTS patterns in event data. We experimentally evaluate the proposed algorithms using two crime-related datasets: Pittsburgh Police Incident Blotter Dataset and Boston Crime Incident Reports Dataset. In the experiments, the CSTS-Miner algorithm is compared with the other four state-of-the-art algorithms: STS-Miner, CSTPM, STBFM and CST-SPMiner. As the results of the experiments suggest, the proposed algorithm discovers much fewer patterns than the other selected algorithms. Finally, we provide the examples of interesting crime-related patterns discovered by the proposed CSTS-Miner algorithm.
LINGUISTIC REALIZATIONS OF THE ABSTRACTS IN INFORMATICS, COMPUTER SCIENCE &amp; ENGINEERING, AND INFORMATION SYSTEMS JOURNALS

&lt;p&gt;&lt;em&gt;The abstract is now a required part of a Research Article (RA) for most scientific publications. It is recognized that the functions, linguistic realizations, and rhetorical structures of abstracts and RAs vary (Lores 2004). The study aims to examine how each step in RA abstracts is expressed linguistically. The data come from &lt;/em&gt;&lt;em&gt;30 RA abstracts taken from two Informatics, Computer Science &amp;amp; Engineering, and Information Systems in COMMIT (Communication and Information Technology) Journal and Khazanah Informatika, Jurnal Ilmu Komputer dan Informatika published in 2021-2022&lt;/em&gt;&lt;em&gt;. According to Hyland's theory, the writers enumerated each move frequency of the rhetorical structure: Introduction (M1), Purpose (M2), Method (M3), Results (M4), and Conclusion (M5). The writers then examined each move's linguistic realizations, paying particular attention to the word tense and lexis. It was discovered that the category of "innovation in a field" was the most frequently used one in Move 1; "this" predominates in the category of deictic item in Move 2; and "use" and "show" are the most frequently used verbs in Move 3. Move 4 contains 25 that-complement phrases; At move 5, mixed results were found for each cohort. In Moves 1, 2, 4, and 5, the Present tense was used the most. In all the movements, the active voice predominated, and the passive voice was applied more in Move 3. The findings are a practical guide for beginning researchers conducting comparable studies.&lt;/em&gt;&lt;/p&gt;
The Reducibility of Modal Syllogisms Based on the Syllogism EI◇O-2

Syllogistic reasoning plays a crucial part in natural language information processing.For the purpose of providing a consistent interpretation for Aristotelian modal syllogistic, this paper firstly proves the validity of the syllogism EI◇O-2, and then takes it as the basic axiom to derive the other 38 valid modal syllogisms by taking advantage of some reasoning rules in classical propositional logic, the symmetry of two Aristotelian quantifiers (i.e.some and no), the transformation between any one of Aristotelian quantifiers and its three negative quantifiers, as well as some facts in first order logic.In other words, there are reducible relations between the modal syllogism EI◇O-2 and the other 38 valid modal syllogisms.There are infinitely many instances in natural language corresponding to any valid modal syllogism.Therefore, this study has theoretical value and practical significance for natural language information processing in computer science.