Reviewerly/exHarmony huggingface dataset:
THE DISCOURSE OF SPIRITUAL AND EXISTENTIAL FORMATION OF IVAN FRANKO: THE CONCEPT OF PERSONALITY

The review of the monograph by Y. Nakhlik “Virazhi Frankovoho Dukhu Svitohliad. Ideolohiia. Literatura” examines the system of innovative changes in the field of contemporary Franco`s studies through the widening of different discourses (cultural studies, philosophy, literature, education, and upbringing). It is proved that the basis of the study is a straight-through model of the spiritual-existential formation of the evolutionary progress of Ivan Franko, which is human-centric, national-centric. The problems, which are revealed in the monograph as the basis of spiritual and moral development and self-development, are investigated and analyzed. The guidelines for reflection of the formation of the self-challenge component in the system of formation of spiritual and moral values in the system of personality`s and society`s interaction are emphasized. The role of artwork as a system of aesthetic, philosophical, psycholinguistic values is examined on the sample of the analysis of the main thematic layers of the monograph. The analysis of peer-reviewed monograph argues that the text as a basis for cultural studies is an all-encompassing phenomenon. SynergeticsFranko`s texts covers all areas of human activity. In their system archetypes codes generated significant era. The set of ideals and symbols, norms and principles, achievements, and values influences on the organization life, and how human activity both in material and in spiritual spheres. Based on the analysis of the artistic heritage of Ivan Franko is a redefining primitive interpretation of artistic phenomena. These processes are the basis for the formation of a new system of thinking, a new human individuality, and new, high-quality human relations. Ivan Franko`s creative work shows that humanity's means of cultural influence is moving from one era to another era of technocracy to assert religious moral values. In the past pragmatism and away technocrats, the humancentric model is a cross-cutting social life of mankind. By analyzing the Ivan Franko`s works we see expanding intellectual horizons of literature and social life. A literary text is a basic for foundation of the person's world. Tradition of Franco's words have continued through time and space. The World cultural system is currently undergoing a major transformation in the party establishment moral values of our time. In contrast, selfishness, greed, callousness, indifference practice life brings to life the circulation of qualitatively new values: sacrifice, forgiveness, understanding the world, another human civilization. The presented monograph is analyzed in light of the system of axiological values of the cultural paradigm. The study of Ivan Franko's spiritual evolution provides a systematic analysis of the importance of the text in the philosophical and existential rendition of the epoch.
AN IMPORTANT ELEMENTS IN PROMOTING READING COMPREHENSION

Reading is a strong foundation that must be instilled in the early grades and is the key to successful learning in subsequent classes. The essence of reading is to understand what is being read. This study aims to analyze important elements in improving the teaching of reading for comprehension. This research is qualitative research with a descriptive approach. The stages passed in this research begin with planning, research, implementation, data analysis, and then writing reports. The subjects in the study were two supervisors, two literacy coaches, two principals and six early-grade teachers. The results of interviews and observations explain that there are nine important elements in improving the teaching of reading for understanding. Some of those things are getting into the habit of making connections between the book and the outside world.
ENHANCING STUDENTS' LISTENING SKILL: LEVERAGING EXTENSIVE LISTENING ACTIVITY IN AN EFL CLASSROOM

This research aims to explore the best implementation of Extensive Listening in improving students' listening skill at grade eleven of SMK PGRI 3 Badung. The subject of this research is XI MM 2 class that consisted of 31 students. This Classroom Action Research (CAR) cyclic procedure consist of four stages, namely: planning, action, observation, and reflection. Observation and interview was done focusing on how the students respond to the implementation of the extensive listening method, while the test was administered in the end of class to check whether the applied method is effective. The result showed that the best implementation of Extensive Listening was found in the second cycle where drilling vocabulary was applied during pre-listening, practice and adaptation of speech rate were applied in whilst-listening, and exercises were emphasized in post-listening. This syntax was proven to successfully help the students to achieve the learning goal where 96,77% passed the minimum mastery criteria or KKM (75) with the class mean score of 89,67. Besides, students stated that they liked the teaching method and were more motivated in learning listening. Students confirmed that vocabulary and pronunciation drilling was considered effective and influential for their ability in doing the listening test. So, It could be concluded that: 1. drilling vocabulary should be implemented prior to the Extensive Listening main activities to ensure that the students have sufficient vocabulary, 2. teacher should justify the speech rate of the listening material during the Extensive Listening main activities to suit the students' ability.
Tingkat Pemahaman Peserta Didik Kelas VI Sd Terhadap Bahaya Merokok

The smoking habit among students and teenagers is currently increasingly common. Students at the age of 10 years are already smoking, even though this age is the final stage of child development. This article discusses the level of students' understanding of the dangers of smoking with the aim of finding out the level of understanding of grade VI elementary school students about the dangers of smoking. This research was conducted at 10 schools consisting of 5 state elementary schools and 5 private elementary schools with A accreditation and having parallel classes. The research used a qualitative descriptive method in the form of a survey with data collection via questionnaires from 992 students at 10 schools. The data collection process was carried out during the research using the Miles and Hubermen model which includes four activities, namely data collection, data reduction, data presentation, conclusion drawing and verification. After data collection and data reduction, the data is then presented using a scoring technique which is divided into three levels, namely low, medium and high. The conclusion obtained is that students' understanding of the dangers of smoking is at a moderate level of understanding. Students' understanding can be proven by answers that are often answered correctly in multiple choice and essay questions. Students have the ability to describe their understanding of the dangers of smoking.
Pengaruh Model Pembelajaran RADEC berbasis STEAM terhadap Literasi Sains Siswa Kelas IV Sekolah Dasar

The low level of science literacy among students encourages this research because there is a need for learning that can relate science to everyday phenomena. This study aims to determine the effect of the STEAM-based RADEC learning model on the science literacy of fourth grade elementary school students. This study used a quasi-experimental design with a post-test only control group design. A random sampling technique was used to take a sample consisting of 51 students: 27 students in the experimental class and 24 students in the control class. A multiple choice test with 20 items is used to measure students' science literacy abilities. The results of the test data collection were then calculated and analyzed using the t-test formula with the help of the SPSS version 26 program. The results of the hypothesis test showed a significance value of 0.000 &lt;0.05, so H1 was accepted, which means that there was a significant influence between students who were taught with the STEAM-based RADEC learning model and students who were not taught with the STEAM-based RADEC learning model. The mean post-test for science literacy in the experimental class was 88, which was 78 for the control class. This means that the STEAM-based RADEC learning model has a significant effect on the science literacy of fourth grade elementary school students.
Pengaruh Penerapan Model Eliciting Activities (MEAs) terhadap Kemampuan Komunikasi pada Pembelajaran IPS Siswa Kelas 6 Sekolah Pioneer Depok

This research was motivated by the aim of knowing the social studies learning of students in Grade 6 of Depok Pioneer School that has not been achieved, one of which is communication skills. One of the factors for students' lack of communication skills is simply listening to the teacher's explanation, then taking notes and solving practice questions. This can result in students' knowledge and understanding being limited to the information provided by the teacher. So that a learning model is needed that is applied, namely by applying Model Eliciting Activities (MEAs). The purpose of this study is to determine whether the application of Model Eliciting Activities (MEAs) affects communication skills in social studies learning in grade 6 of Depok Pioneer School better than student communication skills using conventional learning in grade 6 of Depok Pioneer School. This type of research is quasi-experimental research. Sampling was carried out using pre-test post-test control group design. The population in this study amounted to 24 grade 6 students of Depok Pioneer School. Social studies learning activities use Model-Eliciting Activities for experimental classes, while in control classes social studies learning activities use Conventional learning. Data analysis using an independent sample T-Test test on post-test values of the experimental group and control group results showed changes in communication in social studies learning after using Model Eliciting Activities (MEAs). Based on the results of the study, it can be concluded that students' mathematical communication skills using Model Eliciting Activities (MEAs) are better than students' communication skills using conventional learning in Grade 6 of Depok Pioneer School.
Design and Analysis of Wideband PNP Sziklai Common Collector Amplifier with High Current Gain

Objective: Objective of the manuscript is to introduce a novel idea of designing a small-signal common collector (emitter follower) amplifier with user-defined PSpice model of PNP Sziklai pair. Method: A circuit simulation program is developed on the PSpice simulation platform to design and study the proposed amplifier circuit. Small-signal AC equivalent circuit analysis authenticates the proposed amplifier design and selection of biasing components. The proposed amplifier is also implemented on Cadence Virtuoso Simulation software at 180nm technology to validate the design by performing its layout and post-layout simulation. Findings: The proposed circuit gives high current gain and smaller gain fluctuations (β) due to environmental parameter variations. The effect of variation in stage current gain of Sziklai pair components is observed under different operating conditions. Equivalent circuit analysis, noise performance, and the effect of temperature on the performance of the proposed circuit are widely discussed. Other possible circuit structures with a similar concept of design are also discussed as special cases. Highly stable amplifier current gain as well as device current gain, high amplifier voltage gain, device voltage gains below unity, and low harmonic distortion are prime features of proposed circuit. The problem of finding a matched pair of BJTs for the Sziklai pair is also addressed in the proposed design. The linear distortion-less operation of this circuit, combined with its very high current gain, makes it a suitable candidate for instrumentation amplifiers with wide operating frequency range. The proposed amplifier takes up (10.105 x 10.055) μm2 of area at 180nm technology. The results of pre-layout and post-layout AC responses show that there is a close resemblance between the parameters before and after the layout, which promotes the usability and design of the proposed amplifier. Novelty: The idea explored in the manuscript is entirely new and first time announced by authors. Keywords: PNP Sziklai Pair, Common Collector Amplifier, Current Gain, Small Signal Amplifier, Cadence Virtuoso
Structural relationship among Grit, Exercise Passion, Exercise Satisfaction and Exercise Adherence of Life Sports Participants

This study has a main purpose that closely examines the structural relationship among grit, exercise passion, exercise satisfaction and exercise adherence of life sports participants In order to achieve it, the sample from participants of life sports were accumulated by using convenience sampling that chose sports centers city in seoul and gyeonggi-do. The samples were 300 people. and we excluded unsuitable sheet like that were decided as untruthful one and an omission and unclear. So the final samples were 243 people. On the basis of that, The statistical techniques, spss 24.0 and amos 24.0 program have been used for the analysis as per research purpose. The statistical analysis used in the research for a data analysis includes frequency analysis, confirmatory factor analysis, reliability analysis, correlation analysis, and structure equation model analysis. The research has drawn the following conclusions, based on the above mentioned research method and its procedures: First, The grit influences the exercise passion. Second, The exercise passion influences the exercise satisfaction Third, The exercise passion influences the exercise adherence. Fourth, The exercise satisfaction influences the exercise adherence.
Campus Management System with ID Card using Face Recognition with LBPH Algorithm

The Face recognition system mentioned is a computer vision and image processing application designed to carry out two primary functions: identifying and verifying a person from an image or a video database. The objective of this research is to provide a more efficient and effective alternative to traditional manual management systems. It can be used in offices, schools, and organizations where security is critical. In the proposed system, initially, all students enrolled in the Academic Year whose information is stored in a database server and released a unique ID Card with their facial image to be a smart campus. The main objective of the proposed system is to automate the time-in, and time-out of students, teachers, staff, and anyone who enters and leaves the campus of the University of Computer Studies, Hinthada (UCSH). This system is implemented with the 405 students in the 2022-2023 Academic Year, 86 permanent staff including the principal whose ID card (Name, Year, Roll No, NRC, Father Name: for students, Name, Rank, Department, NRC, Address: for teachers and staffs). As soon as someone enters the campus of a university, the ID card is scanned, the images of the ID card are captured and the face onthe card will be matched with the faces in the trained dataset to detect by using the Haar cascade classifier, and recognize the face using Local Binary Pattern LBPH algorithm. The proposed system demonstrates strong performance, achieving an accuracy rate of over 90% for everyone entering the campus. It is both effective and efficient, providing a smart solution for identification.
Applications of AI in Computer Vision and NLP

Computer vision and language AI (or speech AI) are two rapidly growing fields that have the potential to revolutionize the way when interacted with technology. When it comes to artificial intelligence, there are two main branches: computer vision, which focuses on visual data, and language AI (or voice AI), which focuses on both written and spoken language. The purpose of this research is to offer a snapshot of where things stand in this area right now, highlighting recent research and key findings in both computer vision and language AI (or speech AI). The literature review will focus on the most recent advancements and trends in these fields, as well as identify gaps in the literature that need further research.
Literature Review: Recent Advances in Computer Vision and Language AI

This comprehensive literature review examines the latest breakthroughs in computer vision and natural language processing (NLP), two rapidly evolving fields with applications across search, human-computer interaction, robotics, and more. It synthesizes key findings, trends, limitations, and open challenges from cutting-edge research at their intersection. The dramatic progress driven by deep neural networks is analysed in depth, along with issues like generalization, context handling, reasoning, uncertainty, and human-centric evaluation. Although remarkable advances have been made, especially in computer vision, core problems remain to be addressed. This review provides a thorough overview of the state-of-the-art, reflecting the most recent innovations, and promising future directions in this dynamic research domain.
Unveiling the Teaching Methods Adopted in DevOps Courses

DevOps practices arose to coordinate development and operation teams and ensure rapid and reliable new software releases. Although there is a considerable demand for preparing new professionals in these practices, fewer studies investigate teaching methods in DevOps Education. Our dissertation investigates the teaching methods reported in the literature and in interviews with DevOps educators. We also studied their connection with DevOps educational challenges. Our results indicate teaching DevOps by adopting practical teaching methods in a collaborative learning environment.
Criminal Law And Artificial Intelligence: Perspective From Italian And European Experience

An offence committed by artificial intelligence seems like an oxymoron, at least in a legal system in which criminal offence is literally an expression of the personality of a human being. However, reality knocks on the door of the criminalist, evoking the possibility that a non-human agent may commit harmful acts for which the community expresses a need for punishment. This paper examines the perspective of a rational criminal control with respect to acts performed by or by means of machines and software that learn and evolve through a comparison with the environment in which they operate.
Analysis and Prediction of Earthquake Impact using Convolutional Neural Networks

Abstract: Earthquake prediction is a complex yet crucial area of study, holding the potential to safeguard lives and minimize the catastrophic impact of seismic events. Convolutional Neural Networks (CNNs), originally designed for image analysis, have demonstrated their adaptability in geoscience, particularly in the domain of earthquake prediction. Leveraging CNNs in earthquake prediction entails the examination of extensive seismic datasets, encompassing waveform records, sensor data, and geospatial information. CNNs excel in automatically detecting intricate patterns and associations within these datasets, rendering them a suitable choice for identifying early seismic indicators and anomalies. The process of employing CNNs for earthquake prediction comprises several essential stages, including data preprocessing, feature extraction, and model training. Researchers often initiate data preprocessing to eliminate noise and enhance data integrity. Subsequently, CNNs are deployed to extract pertinent features from the data, capturing nuanced patterns that may suggest impending seismic activity. These features can encompass spectral attributes, temporal fluctuations, or spatial dependencies, all of which are then incorporated into a CNN-based model. Convolutional Neural Networks have emerged as a promising tool in the realm of earthquake prediction. Their proficiency in scrutinizing seismic data and uncovering subtle patterns holds great potential for enhancing early warning systems and earthquake risk assessment. This, in turn, can significantly contribute to disaster preparedness and mitigation efforts.
Project EngiBot: Engineering Insights through NLP- driven Chatbot

Abstract: A chatbot is an automated system designed to engage with users, offering human-like conversations and promptly responding to their queries based on the input provided. This technology creates a seamless illusion of interacting with a human interlocutor. This chatbot empowers students with the ability to access information about college activities from anywhere with an internet connection. Furthermore, it extends its capabilities to guide engineering students on various aspects, including identifying colleges with the highest salary packages, exploring trending domains within the field, and providing a roadmap for mastering these domains. The development of the college inquiry chatbot involved the utilization of a Natural Language Processing (NLP) system that assesses and understands user questions and messages. Understanding that people interact with varying emotional states and attitudes, chatbots adhere to defined rules, ensuring polite and accurate communication with customers, mirroring human interaction. Additionally, the chatbot offers invaluable insights on the technologies essential for achieving expertise in a specific engineering domain, serving as a comprehensive resource for students in their educational journey. They significantly reduce response times, allowing students to receive prompt and accurate answers.
Streamlining Attendance Management in Education: A Web-Based System Combining Facial Recognition and QR Code Technology

Attendance tracking has long posed challenges in educational institutions due to the inefficiency and error-prone nature of traditional paper-based methods. In response, many institutions have embraced web technologies and automated attendance systems, incorporating biometrics, QR codes, barcodes, and RFID-based technologies. However, the applicability of these systems may vary across different educational settings. This paper introduces a web-based student attendance management system that combines facial recognition technology and QR codes to address the challenges associated with manual attendance tracking in a university college. The system leverages a centralized database for streamlined monitoring and auditing of attendance records, offering the flexibility to choose between face recognition and QR code attendance marking options. User acceptance tests were conducted to evaluate the system's effectiveness, and the results indicate that the proposed system greatly improves attendance tracking transparency and demonstrates high usability based on positive user ratings. Additionally, the preference for face recognition over QR code scanning was evident. Incorporating these technologies into the automated attendance system represents a substantial advancement in educational technology, offering an accurate and efficient way of recording attendance.