Reviewerly/exHarmony huggingface dataset:
Exploring the Synergy of Prompt Engineering and Reinforcement Learning for Enhanced Control and Responsiveness in Chat GPT

Conversational AI systems, such as Chat GPT, have exhibited remarkable performance in generating human-like responses. However, achieving consistent control and responsiveness remains a challenge. This research paper explores the combined effects of prompt engineering and reinforcement learning techniques in enhancing control and responsiveness in Chat GPT. Our experiments demonstrate significant improvements in the model’s performance across diverse domains and tasks. We discuss the implications of these findings for various real-world applications, such as customer support, virtual assistants, content generation, and education, and provide insights into future research directions and ethical considerations in the development of more reliable, controllable, and effective conversational AI systems.
RESEARCH ON THE INNOVATION MODE OF INDUSTRY-EDUCATION INTEGRATION：A CASE STUDY OF AN INDUSTRY-EDUCATION PARK IN NORTHWEST CHINA

The integration of industry and education has attracted wide attention from all walks of life since it was proposed. Under the background of the integration of industry and education, some higher vocational colleges aim at training graduates with high comprehensive quality and strong practical ability, serve the local economic development as the orientation, and continuously provide high-skilled talents for various industries. An economic and technological development zone in Northwest China combines industrial characteristics, takes industry-education integration science and technology innovation park as the carrier, vigorously develops industry-education integration, innovates operation mode, collaborates education, and creates a new ecology of industry-education integration.
Individual training trajectory of future polygraph examiners as an effective pedagogical tool for the formation of professional competencies

The author in the presented work discusses the topical issues of using the individual trajectory for the students' learning in the educational process of the departmental education system, undergoing professional retraining according to the programs of additional professional education, as an effective pedagogical tool for the formation of the necessary professional competencies. A variable methodology for the formation of individual educational trajectories is proposed, based on the analysis of the needs and capabilities of each student according to vocational training programs in educational institutions of the Ministry of Internal Affairs of the Russian Federation. In the course of applying the possibilities of an individual learning trajectory, it is assumed that this will contribute to a more effective formation of the necessary knowledge. The novelty of the research lies in the fact that the individual learning trajectory, in turn, allows students in a creative format to choose topics that are important in their opinion and scientific and practical directions that most accurately correspond to their needs and interests, and at the same time, in cooperation with teachers, acquire serious practical experience in this field. The pedagogical idea, from the point of view of organizational aspects, is that each educational organization should have a regulatory, legal and pedagogical opportunity to implement individual learning trajectories of students as an effective way to improve the learning process, focused on obtaining fundamental knowledge by students in all areas of science and practice
A Study of the Significance of Mini Cement Plants in Building A Self-Reliant Economy

Nowadays, usage of cement is recognized as the most influential yardstick of urbanization vis-à-vis development of the economy. With the increasing demand for this wonder material, the mini cement plants are emerging as the counterpart of large plants in making the material available in the remotest of locality. In this process, they are remarkably fostering self-reliance while giving due consideration to environmental protection too. In this paper, attempts have been made to highlight the significance of mini cement plants in encouraging local entrepreneurship along with shaping a concrete economy for the region. The study will also try to analyze the performance, problems, and prospects of the mini cement plants along with the extent to which various factors influence their existence in the region of study.
Bayesian cognitive science

Bayesian cognitive science is a research programme that relies on modelling resources from Bayesian statistics for studying and understanding mind, brain, and behaviour. Conceiving of mental capacities as computing solutions to inductive problems, Bayesian cognitive scientists develop probabilistic models of mental capacities and evaluate their adequacy based on behavioural and neural data generated by humans (or other cognitive agents) performing a pertinent task. The overarching goal is to identify the mathematical principles, algorithmic procedures, and causal mechanisms that enable cognitive agents to take uncertainty into account and weigh it appropriately in producing adaptive behaviour. The appeal of Bayesian cognitive science derives from its transparency, normativity, and unifying power. Resources from Bayesian statistics allow cognitive scientists to characterise transparently, in terms of random variables and probabilistic dependencies between them, the inductive problems that many mental capacities are presumed to solve. Given this characterisation, researchers can define an upper bound on one’s performance on that problem and use it as a benchmark for interpreting experimental results, formulating hypotheses about why and when deviations from optimal performance should be expected, and seeking explanations of mental capacities within one encompassing theoretical framework. Although critics question the testability, explanatory power, and plausibility of Bayesian models of mental capacities, Bayesian cognitive science has proved itself to be an incredibly fruitful research programme. Fuelled by empirical and theoretical results from psychology, neuroscience, philosophy, computer science, artificial intelligence, and evolution, Bayesian cognitive science has: advanced our understanding of why cognitive systems should keep track of uncertainty and use it to facilitate adaptive behaviour; clarified how the brain might encode information about the uncertainty of its stimuli and perform computations with probability distributions; and crystallised the insight that cognitive agents’ management of uncertainty might be grounded in predictive processes aimed at avoiding surprising exchanges with the environment.
Formation of Research Skills of Future Teachers of Mathematics in Solving Olympiad Problems

This article addresses the critical need to enhance the professional training of teachers, specifically in the realm of teaching and research activities. The objective is to improve their cognitive and organizational skills to enhance the effectiveness of future educational endeavors. The article's primary focus is the development of a comprehensive model for instilling research skills in prospective mathematics educators. The study employs the "Diagnostics of Personal Creativity" test by E.E. Tunic as a principal assessment tool. This test aids in evaluating personal curiosity, analytical aptitude, the ability to think innovatively, and problem-solving capabilities, all of which are pivotal indicators of an individual's inclination towards research activities. The proposed model for cultivating research skills among future mathematics teachers hinges on a set of methodological parameters. These parameters are designed to elevate intellectual acumen by encouraging diverse cognitive comparisons within mental activities, forming the foundation for research-oriented thinking. The model underscores the gradual development of cognitive abilities across varying levels of depth, applied to solving complex Olympiad problems with intricate structures. In summary, this article presents a model that promises to significantly enhance the research skills of future mathematics teachers, thereby contributing to the advancement of the teaching profession and the holistic development of young learners.&#x0D; &#x0D; Received: 4 June 2023 / Accepted: 11 October 2023 / Published: 5 November 2023
STES Chatbot Using Flutter: STES Dialogic AI

STES Dialogic AI is a pioneering college-related chatbot designed to streamline the information and inquiry process for students interested in the Sinhgad Technical Education Society (STES). This innovative virtual assistant offers a userfriendly platform for students to access vital information about STES, such as admission procedures, course details, campus facilities, and other relevant queries. By harnessing natural language processing(NLP) and artificial intelligence, this chatbot serves as a responsive, round-the-clock information resource, ensuring that students can obtain answers to their questions promptly and efficiently. STES Dialogic AI not only enhances the student experience but also showcases STES's commitment to technological advancements and student-centric services
The Effect Of Jigsaw Teaching Technique To The Reading Comprehension Of Grade Eight Students Of Smp Negeri 2 Tapian Dolok On A Descriptive Text

The aim of this research is to describe and analyze reading comprehension teaching techniques using jigsaw teaching techniques for eighth grade students at SMP Negeri 2 Tapian Dolok. The aim of this research is to determine the effect. Jigsaw Teaching Technique on reading comprehension of eighth grade students of SMP Negeri 2 Tapian Dolok on descriptive text. This research uses a quantitative type of research with a quasi-experimental design. The sampling technique used in this research was purposive sampling, with a sample of 62 class VIII students at SMP Negeri 2 Tapian Dolok. Two classes were taken as subjects for this research, namely the experimental class and the control class. Data obtained from the experimental class and control class were analyzed using the t-test formula. Researchers found that the post-test average in the experimental group was 83 and the post-test average in the control group was 77. The calculation results showed that at the 5% significance level, the t-count value &gt; t-table (2.4 &gt; 1.671 ). From these results, it appears that there is a significant difference between student achievement in reading comprehension of descriptive texts that use jigsaw teaching techniques and those taught using traditional lecture-based teaching methods. Therefore, the researchers concluded that there was a significant influence of the Jigsaw teaching technique on reading comprehension.
Bandwidth-Aware Hadoop Scheduling Method for Enhanced Task Execution

This research presents a novel bandwidth-aware Hadoop scheduling method that addresses the challenge of task scheduling in Hadoop clusters while considering the real-time network conditions. The proposed method involves the establishment of a job time completion model and a mathematical model for a Hadoop scheduling system
Peningkatan Memahami Teks Persuasif Melalui Model Discovery Learning Siswa Kelas VIII SMP Muhammadiyah 02 Kota Malang

The purpose of this study is to describe the application of the discovery learning learning model to improve the understanding of persuasive text content of students of SMP Muhammadiyah 02 Malang City and to find out the increase in understanding of persuasive text content through the discovery learning model in grade VIII SMP Muhammadiyah 02 Malang City. This type of research is Classroom Action Research (PTK) with a qualitative approach. This class action research is carried out in two cycles. Each cycle consists of planning, execution, observation and reflection. The subjects of this study were grade VIII students of SMP Muhammadiyah 02 Malang City in the even semester of the 2022/2023 academic year, totaling 16 students. The data used include the results of cycle tests for each action, observations of learning activities, interview results, field notes. Data analysis used in this research is: data reduction, data presentation, conclusion drawing and verification. The success rate of learning in the classroom with learning achievement based on the implementation of the prestest and posttest of 16 students is categorized as quite active, evidenced by 56.10% in cycle I and 81.66% in cycle II, an increase in pretest by 25%. Furthermore, by 57.76% in cycle I and 90% in cycle II, there was an increase in posttest by 33%. Based on the results of the study, it can be concluded that discovery learning can improve the understanding of the concept of grade VIII students of SMP Muhammadiyah 02 Malang City.
Pengaruh Sustained Silent Reading Terhadap Motivasi Membaca, Pengetahuan Kosakata, dan Pemahaman Membaca Teks Bahasa Inggris Siswa Kelas 1E Sekolah Dasar Swasta X di Jakarta Barat [Effect of Sustained Silent Reading to Reading Motivation, Vocabulary Knowledge, and Reading Comprehension of Elementary School X Grade 1 Students in West Jakarta]

&lt;p&gt;Sustained Silent Reading (SSR) is a reading method with a purpose to increase enjoyment in reading. The enjoyment in reading will improve the reading skills which lead to increased reading motivation, vocabulary knowledge, and reading comprehension. This research was conducted to know the effect of SSR to grade 1 students’ reading motivation, vocabulary knowledge, and reading comprehension as young learners. The research design used a quantitative, pre-experimental one group pretest and posttest method. 24 students of 1E class of Elementary School X who received the SSR treatment are the subjects of this research. To collect the data, the researcher did a literature review and used instruments such as reading motivation questionnaire which is adapted from MRQ and RAI (Wigfield &amp;amp; Guthrie, 1997), vocabulary and reading comprehension tests. The data were analyzed using SPSS v. 21 software, with descriptive and inferential statistics (Paired Sample t-test and Wilcoxon Signed Ranks). After the treatments, there were increment in the students’ reading motivation (t = 4.881; ρ = 0.000), vocabulary knowledge (Z = -2.453; ρ = 0.014), and reading comprehension (Z = -3.539; ρ = 0.000). These analyses showed that the SSR method brought improvements to the students’ reading motivation, vocabulary knowledge, and reading comprehension.&lt;/p&gt;
Persepsi Siswa tentang Implementasi Media Literasi Digital di Pembelajaran Daring Geografi [Students' Perception about the Implementation of Digital Literacy in Geography Online Learning]

&lt;div&gt;&lt;p class="1eAbstract-text"&gt;The background of this research is the low literacy, participation, and collaboration ability of students. The COVID-19 pandemic has had an impact on the learning process. This study aims to determine student perceptions related to the implementation of digital literacy media on participation, collaboration skills, student satisfaction, and cognitive learning achievement in geography subjects. The subjects in this study were 162 students of class XI and XII social studies at XYZ private high school in South Tangerang. This research is a quantitative descriptive study using a simple regression test to measure. Data collection techniques using a questionnaire in the form of google form. The research instrument used is a variable to measure students' perceptions about the implementation of digital literacy, participation, collaboration skills, and student satisfaction. The results showed that students' perceptions about the implementation of digital literacy media affected the participation of 38.2%. Students' perceptions of digital literacy media also affect 50.2% of collaboration skills and 64.3% of student satisfaction. Participation and collaboration ability did not show any effect on cognitive learning achievement, it was seen from the sig value. &amp;gt; 0.05 and Fcount. &amp;lt; Ftable. Cognitive learning achievement is influenced by student satisfaction and perceptions regarding digital literacy media in geography online learning by 5.4% and 2.5%, respectively. So it can be concluded that students' perceptions of digital literacy media help students learn in geography online learning.&lt;/p&gt;&lt;/div&gt;
Prestasi Akademik Mahasiswa Saat Pandemi: Pengaruh Kompetensi Dosen dan Interaksi Mahasiswa Akuntansi Universitas Muara Bungo

The Covid-19 pandemic not only has an impact on public health, but also has an impact on the world of education. This research examines the factors that influence the academic achievement of accounting students. Accounting lectures, which contain mostly calculation material, even though they are taught boldly, must be mastered by the students. This researcher tested whether lecturer competency variables and student interaction had an effect on the academic achievement of accounting students. With a sample size of 70 people, and using Partial Least Square, using Smart PLS 4.0 it was concluded that Competency. Lecturer competency partially influences the academic achievement of brave learning during the Covid-19 pandemic. Meanwhile, student interaction has no partial effect on the academic achievement of brave learning during the Covid-19 pandemic.
Joining Battles with Mouse: Exploring Gaming Mice in the Virtual and Real Worlds

The gaming mouse is designed to be complex in response to the player’s body movements. Compared to the traditional or multi-touch mice with a smooth and flat appearance, their material and color combination, buttons with various special functions, and even a replaceable micro-switch and shell can drive game players to associate with other objects. The results show that there are many interesting correlations between plays’ gestures and game actions. The gaming mouse's advanced design allows it to react to players' motions more accurately. In addition, players create their own body techniques that adapt to the shape of the mouse and incorporate it into their imagined reality. In human-computer interfaces, various visual components and control mechanisms make up for the "cyber-netic loss" that occurs throughout the dematerialization process. The applica- tion of such compensation extends from plane graphics to gaming mice, and ranges from visual perception to the physical experience of controlling the mouse.
News Recommendation Systems: Impediments and Future Prospects

News publishers have reduced their usage of traditional newspapers in favour of digital various options such as webpages and specially constructed cell phone applications. In the present world, the internet has recreated information borders and, in addition to smartphone internet access, makes it the most vital medium content for everyone on earth. Users want personalized news recommendations in order to locate relevant news content and avoid information overload. With the growing number of media reports available on social media, tailored news suggestions have become more vital in assisting end users inside discovering relevant and engaging news stories. Traditional recommender systems, on the other hand, frequently fail to account for the constantly changing nature the users' preferences in addition to shifting patterns in news items. To solve this issue, this study offers a context-aware customized data system of recommendations that utilizes contextual information to improve news suggestion individualism. The method entails gathering, extracting, investigating, scrubbing, and arranging a big dataset from 22,657 English publications from 19 individual news outlets online. Four separate recommender frameworks were thought up using different methodologies, including content-based strategies like the TF-IDF Bag-of-Words, and Word2Vec, as well as a related not entirely set in stone by click demeanours. Since it’s been thoroughly explored over decades with noteworthy progress in enhancing user interaction, there encore many concerns and obstacles waiting to be researched further.
Prediksi Harga pada Trading Forex Pair USDCHF Menggunakan Regresi Linear

In the era of globalization, free trade grows rapidly and technology develops, affecting economic competition. Forex, foreign exchange trading, is one of the investments used to face this challenge. Technical and fundamental analysis is used to predict price movements in forex trading. Previous studies have used linear regression algorithms and other techniques for price prediction in forex. In this study, the linear regression algorithm is used to predict closing prices in forex trading because the linear regression algorithm is an algorithm that has been widely used in predictions, its strengths are in estimating simple model parameters and data based on time series. In addition, the linear regression algorithm can perform analysis using several independent variables so that the prediction results can be more accurate. The purpose of this study is to create a forex price prediction model, to make it easier for traders to make price predictions. A dataset of 2066 data was obtained through the metatrader software and processed through the preprocessing stage. The linear regression model was created using 5 scenarios, and the evaluation was carried out using the Mean Squared Error (MSE) and Root Mean Square Error (RMSE) values to select the best model. The results show that linear regression is able to predict the closing price of the USDCHF pair. The best linear regression model is obtained using the independent variable in scenario 1, namely the Open variable, with a linear regression equation of y=0.0145+0.9849x, the best MSE is 0.0000328509 and the best RMSE is 0.0057315705.
The Use of Contrast and Gradient Features to Categorize Texture Images

Image texture is an important part of many types of images, for example medical images. Texture Analysis is the technique that uses measurable features to categorize complex textures. The main goal is to extract discriminative features that are used in different pattern recognition applications and texture categorization. This paper investigates the extraction of most discriminative features for different texture images from the “Colored Brodatz” dataset using two types of image contrast measures, as well as using the statistical moments on five bands (red, green, blue, grey, and black). The Euclidean distance measure is used in the matching step to check the similarity degree. The proposed method was tested on 112 classes of textures. The achieved results showed that the proposed method is accurate and fast concerning classification accuracy with low computational complexity. The achieved Recognition Rate (RR) was 100%.
The Defensive Methods Against Deepfake: Review

Due to the spread of “Deepfake” in our society and the impact of this phenomenon on politicians, celebrities, and the privacy of individuals in particular, as well as, on the other hand, its impact on the electoral process as well as financial fraud, all these reasons prompted us to present a research paper dealing with this phenomenon. This paper presents a comprehensive review of Deepfake, how it is created, and who has produced it. This paper can be used as a reference and information source for the methods used to limit deepfake by detecting forgeries and minimizing its impact on society by preventing it. This paper reviews the results of much research in the field of deepfake, as well as the advantages of each method, as well as finding points of weakness such as complexity, time consumption, and the environment that is applied to it. Methods to avoid or reduce these obstacles are also suggested.