Reviewerly/exHarmony huggingface dataset:
Methods of Analysis of Amazon Product Reviews and Rating Prediction

Online shopping reviews have become an important data source for merchants to make smarter decisions in product development, operations, and marketing. In this paper, we propose a modeling strategy to optimize data analysis and processing of online shopping review data. We address four main problems: identifying commonly used words in positive, negative, and helpful reviews, predicting the products to which the comments refer using semantic analysis, predicting the product rating based on the comments using sentiment analysis, and proposing ways to distinguish human comments from machine-generated ones. Additionally, we provide a recommendation letter to customers on how to read product reviews.
Mathematical Analysis of the Relationship between College Entrance Exam Scores and Information and Computing Science Discipline Performance in a Chinese University

This article uses multiple regression analysis methods and canonical correlation analysis, combined with the college entrance examination scores and partial discipline scores in the first three years of university for students majoring in Information and Computing Science in a certain university. We separately analyze the connection between the college entrance examination and university discipline scores, and compare the advantages and disadvantages of the two methods. We hope to quantitatively analyze the transmission and extension of subject knowledge at different stages from a mathematical perspective, and also promote the practical application value of mathematics, providing more people with inspiration and thought on mathematics.
The Interpretation of QR Codes from the Perspective of Pierce's Semiotics

As a new favourite in the digital age, the emergence of QR codes has brought great convenience to human life. The QR codes symbols composed of geometric figures have the ability to carry meaning. Based on Peirce's semiotics, this study explores the relationship between the referents of QR codes, the derivation of signifier process and the communication process. The research finds that: (1) Icon, index and symbol are in a dynamic relationship; (2) The derivation of of signifier process of QR codes depends on the "interpretant"; (3) The communication process of QR codes is mostly culture-based. Through the interpretation of QR codes, this study aims to deepen people's understanding of QR codes and to help them better interpret the meanings implied by QR codes.
Emerging Frontiers of Public Safety: Synergizing AI and Bioengineering for Crime Prevention

The convergence of artificial intelligence (AI) and biological engineering technology (BET) can potentially revolutionize public safety efforts. However, the responsible use of these technologies requires crucial considerations. This study employed an exploratory sequential mixed-method to examine the governance mechanisms apropos AI and BET in the context of crime prevention in the Philippines. It identifies several key components that contribute to establishing governance mechanisms, including multisectoral agencies, legislative initiatives, and regulatory frameworks. The study also identifies a 3-factor model for the governance convergence of AI and BET in public safety. These factors include empowerment and sufficiency, ethical considerations, and laws and regulations. The findings underscore the notable implications of integrating AI and BET into public safety efforts, such as improving surveillance systems, proactively preventing public health crises, and optimizing emergency response capabilities. However, ethical considerations and regulatory guidelines must be in place to address privacy concerns and mitigate potential risks associated with these technologies. The convergence of AI and BET also presents opportunities for sustainability. Nevertheless, concerns arise regarding its improper utilization. Based on the study's findings, policy recommendations are directed at ethical considerations, governance and regulation, and sustainability. These policy actions aim to address the opportunities and challenges associated with the convergence of AI and BET in public safety, ensuring responsible and beneficial use within the framework of Public Safety 4.0.
Motion Planning of Redundant Mobile Manipulators with a Barycentric Constraint

Stability and safety are significant for mobile manipulators. In this paper, we use the barycentric position as one of the constraints in the redundant mobile manipulators' motion planning to stabilize manipulators. To quantify the extent of the barycentric constraint, we propose the concept of a valid safety region of the barycenter, which is formulated as an optimization problem. Because of the problem's non-convexity, the particle swarm optimization algorithm is used to solve it. The simulation results show the effectiveness of considering the barycentric constraint of the mobile manipulator during task execution.
Unified blended learning management system

The article is devoted to the managerial aspects of blended learning, and considers the possibilities of integrating digital educational resources and tools to build a unified system for organizing and managing the process of blended learning. It has been revealed that today many different educational platforms have been developed and used, the functions and roles of learning activity management systems, learning management, content management, and other resources, which have different formats of organizational solutions, have been analyzed, and ways of their integration have been identified. An adaptive model for the integration of learning management and support systems in a mixed format, allowing students to interact with the learning environment in digital ways and self-regulate learning, was proposed. Scientific novelty is the theoretical justification and definition of the role of digital technology integration in academic, institutional and technological support of blended learning, development of structural and content model based on the integration of digital educational technologies and value-target, didactic, communicative and technological, institutional, evaluative-results and system-forming components of blended learning management system. The practical significance is the development of the platform as a unified adaptive environment, outlining the functions of management managers, teachers and students in the process of implementing blended learning in higher education. The main functions of blended learning technology, modern methods and tools for online learning are described, the features of mixing online and offline, synchronous and asynchronous learning are revealed. During the study, a survey of students, undergraduates and faculty was carried out, the educational platforms of higher education, the possibility of integrating digital learning resources in the implementation of blended learning. The results of the experiment are summarised and processed.
Social psychology: Spotting social faux pas with AI

New research demonstrates AI, in the form of natural language models, can identify social norm violations in text and correctly distinguish the specific violated norm. This shows AI’s potential to recognize tricky social faux pas and support cross-cultural interactions.
Integrated photonic reservoir computing with an all-optical readout

Integrated photonic reservoir computing has been demonstrated to be able to tackle different problems because of its neural network nature. A key advantage of photonic reservoir computing over other neuromorphic paradigms is its straightforward readout system, which facilitates both rapid training and robust, fabrication variation-insensitive photonic integrated hardware implementation for real-time processing. We present our recent development of a fully-optical, coherent photonic reservoir chip integrated with an optical readout system, capitalizing on these benefits. Alongside the integrated system, we also demonstrate a weight update strategy that is suitable for the integrated optical readout hardware. Using this online training scheme, we successfully solved 3-bit header recognition and delayed XOR tasks at 20 Gbps in real-time, all within the optical domain without excess delays.
Analisis Sentiment Twitter Berbasis Grid Search Algorithm (GSA) Dengan Metode Support Vector Machine (SVM)

Twitter is a social networking service that has undergone tremendous growth and is gaining worldwide popularity at an accelerated rate. Twitter allows for the expression of unbiased thoughts on a variety of issues and can assist businesses in providing public feedback on well-known brands and items. Twitter is having trouble with good and negative answers. Researchers evaluated English-language tweets to determine the proportion of positive and negative replies to popular companies and items. This study will explore Twitter sentiment analysis utilizing the Grid Search Algorithm (GSA) and the support vector machine (SVM) technique. GSA is utilized by the feature selection model to optimize the classification procedure. In this work, training data and testing data are required to do sentiment analysis. Sanders Twitter 0.2 utilizes a dataset consisting of tweets retrieved from Twitter using the search terms @apple, #google, #microsoft, and #twitter. The collected dataset was manually annotated and included 654 negatives, 570 positives, 2503 neutrals, and 1786 irrelevant entries. Data are loaded, tokenized, weighted, preprocessed, filtered, and classified to conduct a sentiment analysis. The application's sentiment analysis achieved a degree of accuracy of up to 79% based on testing. The ratio of neutral and bad tweets on data sandboxes tends to be greater than the percentage of positive tweets, hence optimization rather than accuracy is obtained.
Implementasi Program Buku Bergilir (BULIR) di Nagari Saok Laweh Kabupaten Solok

This research is motivated by the lack of public interest in reading. This research was conducted using a qualitative approach with a descriptive method. The research location was carried out in Nagari Saok Laweh. In determining informants, researchers use purposive sampling methods and techniques. In this study using data types, namely primary data and secondary data. Data collection techniques are carried out by interviews, observation, and documentation. In testing the validity of the data, researchers used method triangulation techniques. As for data analysis techniques using data reduction, data presentation, and conclusions. The results showed that the implementation of the Rotating Book Program (BULIR) in Nagari Saok laweh in Solok Regency was carried out in detail such as communication, disposition and bureaucratic structure. However, the implementation has not been carried out properly because the number of human resources is still small such as the number of cadres and the limited budget used.
The Role Of The Teacher In Increasing Students' Reading Literacy Motivation In Mts Darun Nahwi Indramayu

The low motivation of students' reading literacy is one of the factors that causes student achievement to decline. This is possible because their curiosity about subjects is still low, external factors (friends, family, and the environment) do not support studying Islamic Cultural History subjects and so on. Meanwhile, learning achievement of Islamic Cultural History is influenced by several factors such as student learning activities, learning models used by teachers in teaching, students' ability to accept the lessons provided by teachers, student learning motivation and so on. The role of the teacher greatly influences the motivation of reading literacy for students in Islamic Culture history lessons. This research use desciptive qualitative approach. The purpose of this study is to find out how the role of the teacher in increasing the reading literacy motivation of students at MTS Darun Nahwi and how the teacher's role is in increasing students' reading literacy motivation in Islamic Cultural History lessons at MTS Darun Nahwi
Stakeholder Participation and Solid Waste Management in Lira City East Division

Purpose: this study examined the contribution of stakeholder participation to SWM in Lira City East division. Specifically, the study determined the effect of stakeholder participation on solid waste reduction, solid waste recycling and on waste reuse.&#x0D; Methodology: The study adopted a cross-sectional study design, which employed a mixed methods approach of both quantitative and qualitative methods. The study population consisted of 195 respondents, which included political leaders and civil servants of Lira City East division and heads of household in Lira City East. Both the Simple random sampling technique and purposive sampling technique were used to select a sample of 132 participants. The researcher adopted Self-Administered Questionnaires to collect quantitative data and an interview guide to collect qualitative data. Both descriptive statistics (mean, and standard deviation), and inferential statistics (correlation and regression) were used to analyse numerical data. Content analysis was used to analyse qualitative data.&#x0D; Findings: The findings revealed a statistically significant positive relationship between stakeholder participation and SWM. Further, it was revealed that stakeholder participation yields a significant effect on waste reduction, waste recycling and waste reuse.&#x0D; Unique contribution to theory, practice and policy: It is concluded that stakeholder participation affects SWM in Lira City East division. This study contributes an original and empirical-evidence of the contribution of stakeholder participation on SWM in Lira City East division. It is recommended that, for better management of solid waste in Lira City division, the authorities of Lira City east division should sensitise the residents on the possible mechanisms of reducing the amount of waste generated at homestead, how the waste generated can be recycled to other useful forms and how the waste generated can be reused. This study contributes to the reawakening of the urban stakeholders in Lira city and Uganda, as a whole, on the magnitude of the solid waste challenge and how this calls for instantons effort to achieve healthy and cleaner cities/urban centers
On Boomerang Attacks on Quadratic Feistel Ciphers

The recent introduction of the Boomerang Connectivity Table (BCT) at Eurocrypt 2018 revived interest in boomerang cryptanalysis and in the need to correctly build boomerang distinguishers. Several important advances have been made on this matter, with in particular the study of the extension of the BCT theory to multiple rounds and to different types of ciphers.In this paper, we pursue these investigations by studying the specific case of quadratic Feistel ciphers, motivated by the need to look at two particularly lightweight ciphers, KATAN and Simon. Our analysis shows that their light round function leads to an extreme case, as a one-round boomerang can only have a probability of 0 or 1. We identify six papers presenting boomerang analyses of KATAN or Simon and all use the naive approach to compute the distinguisher’s probability. We are able to prove that several results are theoretically incorrect and we run experiments to check the probability of the others. Many do not have the claimed probability: it fails distinguishing in some cases, but we also identify instances where the experimental probability turns out to be better than the claimed one.To address this shortfall, we propose an SMT model taking into account the boomerang constraints. We present several experimentally-verified related-key distinguishers obtained with our new technique: on KATAN32 a 151-round boomerang and on Simon-32/64 a 17-round boomerang, a 19-round rotational-xor boomerang and a 15-round rotational-xor-differential boomerang.Furthermore, we extend our 19-round distinguisher into a 25-round rotational-xor rectangle attack on Simon-32/64. To the best of our knowledge this attack reaches one more round than previously published results.
A hybrid deep learning framework for modeling the short term global horizontal irradiance prediction of a solar power plant in India

1. Alghamdi, H.A. 2022. A Time Series Forecasting of Global Horizontal Irradiance on Geographical Data of Najran Saudi Arabia. Energies 15(3), pp. 1–19, DOI: 10.3390/en15030928. CrossRef Google Scholar
Improving Students’ Writing Skill by Applying Fishbone Techniques at the Grade X MAN 2 Padang Lawas

This study aims to determine the improvement achieved by students in the ability to write descriptive text using the fishbone technique. This research was conducted by applying quantitative research method and an experimental research design consisting of pre-test, treatment and post-test to improve students' descriptive writing skills using the fishbone technique in class X MAN 2 Padang Lawas. The instruments used are writing descriptive text materials based on a given topic, written test, fishbone improved by the students and lesson plan (RPP). To assess students' performance in writing descriptive text, several criteria are used. The cumulative score ranges from (0-100). To determine student achievement in writing there are several criteria that are considered to have five scales of assessment components namely content, organization, vocabulary, use of language, and mechanism. After analyzing the data, it is concluded that there is significant effectiveness of using the Fishbone Technique on the student's writing skill. The finding shows that the score of t (effect) is 0.06. Therefore the effect of using the Fishbone Technique has a significant effect on students' achievement in writing skills.
The Role of Private Security Organizations in crime prevention and homeland security management in Ghana

The study was to explore the play by Private Security Organizations in crime prevention and homeland security management in Ghana. The study used a descriptive design of the qualitative of which respondents from the various management of Private Security Organizations in Accra were targeted. Purposive sampling technique was employed to select 7 participants to form part of the study. Interview guide was used at the data collection instrument. Data from interviews were analysed thematically based on the research objectives. The study found that key security services provided by the PSOs included the four functions mandated by the laws of Ghana. Also, their operations basically covers; watching and guarding services, patrolling services, and escort services. PSOs follow some form laid down procedures and principles in recruiting and selecting employees. PSOs have some collaboration with the Ghana Police Service with regards to its mandate enshrined by the constitution of Ghana to prevent crime and protect lives and properties. However, the key challenges of the PSOs are financial constraints, inadequate logistics and resources, high cost of operations, poor perception of the general public on their roles in fighting against crime as well as protecting lives and properties. Therefore, the study recommended that various PSOs should come together to form some associations that can fight for their right and welfare of their members. Also, the government of Ghana through the Ministry of Interior and the Ghana Police Service should sponsor some of their activities such as training and workshops. Moreover, the government can support them in terms of vehicles or patrol cars and fueling allowances
Motivasi Belajar Mahasiswa Pada Pemahaman Membaca Bahasa Inggris

This research was aimed to find out the influence of students’ motivation toward their reading comprehension for the first semester students at 2019/2020 academic year. This research was quantitative approach. The sample of this research was all students of accountancy program who were in the first semester at 2019/2020 academic year. The data were collected by using questionnaire and reading comprehension test. The data were analyzed by using regression technique with SPSS version 16.0 for windows. The research findings show that students’ motivation gave influence toward their reading comprehension.
Analysis of the Influence of the Experience and qualifications of Teachers of the Simulation Center on the Quality of Education of Residents of the 2nd Year of Study Based on an Anonymous Survey

The study presents the results of assessing the activities of teachers of the simulation center by questioning residents of the 2nd year of study who have completed simulation courses. The survey involved 357 residents of the 2nd year of study, who were asked to evaluate the work of the teachers of the simulation center — 12 teachers aged from 26 to 62 years, with less than 5 years of work experience — 7 teachers and more than 5 years — 5. As a result of the analysis of feedback questionnaires for 2023, we can conclude that the vast majority of residents of the 2nd year of study are satisfied with the quality of teaching courses.
Wildfires Classification Using Feature Selection with K-NN, Naïve Bayes, and ID3 Algorithms

Wildfires are a problem with a high intensity of occurrence and recurrence in Indonesia. If this problem is not properly addressed, it will threaten air circulation in the world. The source of fire can be natural or man-made. As a preventive measure for the widespread spread of fire, it is necessary to investigate the type of fire early on so that it can be determined the type of fire with the highest priority to be extinguished immediately. The process of identifying fire types can be done by classification. This research aims to classify the type of fire with three algorithms, namely K-Nearest Neighbour (K-NN), Naïve Bayes and Iterative Dichotomise 3 (ID3). The forest fire dataset was obtained from the Global Forest Watch (GFW) platform. Before entering the classification stage, the dataset went through a feature selection process, where attributes meeting the threshold were selected for the classification process. The performance of ID3 algorithm is superior compared to other algorithms with an accuracy of 65.83, precision 67.4, recall 67.02 and F1 67.21 per cent. Finally, the feature selection process contributes positively to the classification process, increasing the model performance by 2-5 per cent.
Application of Deep Learning using Convolutional Neural Network (CNN) Algorithm for Gesture Recognition

Gesture recognition is a fascinating method of human-computer interaction that goes beyond traditional means such as keyboards, pointers, and joypads. In gesture recognition, Convolutional Neural Network (CNN) algorithms are utilized in Deep Learning to train models using datasets comprising gesture images. The training process involves pattern recognition and identification of crucial features from gesture images, followed by evaluation to measure the model's accuracy. Gesture recognition holds immense potential across various fields, including human-computer interaction, gaming, healthcare, and autonomous vehicles, and continues to be a focus of research and development in the future.