Reviewerly/exHarmony huggingface dataset:
Factors Associated with Reading Performance in English

Aims: Reading, Writing, and Arithmetic are three essential skills a pupil should learn and acquire. The purpose of this study was to identify factors associated with pupils’ reading; the pupils’ level of reading performance and the significant relationship between the level of reading performance and factors associated with reading performance.&#x0D; Study Design: The study employed Content Analysis with Descriptive Correlation.&#x0D; Place and Duration of Study: The study was conducted in selected schools in the division of El Salvador City during the school year: 2022.&#x0D; Methodology: The respondents were all the One hundred-twenty (120) Grade 3 pupils at the selected schools in El Salvador City. This study used a researcher-modified survey questionnaire that underwent validity and reliability testing.&#x0D; Results: The results showed that pupils’ reading performance was at a Frustration level, while factors associated with reading performance were rated as Unlikely. It was concluded that pupils' reading performance was significantly correlated to reading performance. Thus, it must be given consideration and attention. The researcher recommends that parents, teachers, and stakeholders should unite in providing and supporting reading-related activities and interventions for better performance and outcomes.&#x0D; Conclusions: As was clearly illustrated in data analysis and results, in conclusion: According to the results of the student's reading performance, the majority of the students are still experiencing frustration. This performance is still regarded as being quite poor. While the reading materials are accessible at home, parents have less time to monitor and support their children. As a result of being alone or receiving less support and attention from their family members at home, students may develop negative attitudes toward reading and poor study habits. There was a strong correlation between the student's reading ability and the elements that affect reading ability. As a result, elements related to reading ability are important for how well they read in English. Based on the findings and conclusion of the study, it is recommended that: Due to the students' alarming reading performance, teachers, parents, and stakeholders must collaborate to establish reading programs and activities for the students. The best solution to whatever pupils' problem is a collaboration between teachers and parents. Teachers might think about stressing to parents and other stakeholders how important it is to help, mentor, and give time to their kids so they feel supported in their academics and problems. The students will get inspiration and self-assurance in this way as they understand that their families are behind them. To help instructors deliver reading activities and services and to motivate and engage stakeholders in creating a better teaching and learning environment, administrators may consider workshops and training sessions, particularly on various reading methods and interventions.
IoT-driven Solar Tracking System for Reliable and Efficient Energy Generation

Abstract: The surge in global energy consumption can be attributed to the growing global population and rising living standards. However, since fossil fuel and oil supplies are finite, the need for renewable energy sources has become paramount. In view of the rapid advancements in renewable energy technologies, a solar energy tracking rotatable panel for power generation is being developed as part of this project's objectives. This panel will be engineered to track the sun's position for optimal energy output, thereby serving as a useful tool for power consumption.
E-Ration Distribution System Based on QR-Code

Abstract: Ration cards are essential for many households as they provide access to necessities such as food and fuel. However, the existing ration distribution system has one main drawback: fraudulence, where distributors sell materials to unauthorized customers. In this paper, we propose an E-Ration distribution system based on QR-code to address these issues. The proposed system uses QR-codes on ration cards, which when scanned provide details about the customer and distributor as well as the available ration. To implement the system, we develop an application that tracks the distribution of ration and logs its status. The application also allows for easy monitoring of stock levels and distribution records, which can be accessed by authorized personnel. This minimizes the human intervention as much as possible to make the system efficient and cost-effective.
Racism detection by analyzing differential opinions through sentiment analysis using stacked ensemble GCR-NN

Because of the unquestionable person of the stage on the worldwide field, a few surviving and new types of bias have arisen. Prejudice has surfaced through online entertainment in both concealed and open forms, concealed through the use of images and open through the distribution of discriminatory expressions under fake characters, to generate contempt, viciousness, and cultural flimsiness. Prejudice is currently flourishing on the basis of diversity, origin, language, culture, and, most importantly, religion, despite the fact that it is frequently associated with nationality. It has been deemed a grave threat to global harmony as well as social, political, and social fortitude that web-based entertainment's capacity to incite racial tensions. Therefore, it is necessary to keep an eye on social media, which serves as the primary channel through which racist ideas are disseminated, identify racist expressions, and swiftly criminalize them. By analyzing the sentiment of tweets, this study aims to identify biased tweets. By combining gated recurrent units (GRU), convolutional neural networks (CNN), and recurrent neural networks (RNN), gated convolutional recurrent neural networks (GCR-NN) are formed. This is done to make use of the superior presentation provided by deep learning. GRU is at the top of the GCR-NN model for extracting acceptable and recognizable characteristics from unrefined text, whereas CNN dissects fundamental components for RNN to create precision expectations. The proposed GCR-NN's presentation within the framework of machine learning (ML) and deep learning models is the subject of numerous analyses. The results show that GCR-NN performs better and has a precision of 0.98 that is higher. In 97% of tweets, the proposed GCR-NN model can recognize extremist remarks.
Aspect-Based Sentiment Analysis on Flipkart Data

Abstract: This research In this paper, an Aspect-Based Sentiment Assessment (ABSA) model using the The Long Short-Term Memory (LSTM) network for analyzing info on Flipkart sentiment The suggested model seeks to identify and extract certain elements of a product or service, as well as to characterise their related sentiment polarity as positive, negative, or neutral. On a Flipkart dataset that is open to the public, experiments were run to assess the effectiveness of the suggested model. The LSTMbased ABSA model surpasses other baseline models, according to the results, achieving an accuracy of above 90%. The suggested approach is also capable of locating and extracting the key features of a good or service that influence consumers' opinions. This research provides a valuable contribution to the field of sentiment analysis on Flipkart data, and has significant practical implications for Flipkart companies seeking to improve customer satisfaction and loyalty
Securing Smart Devices on Blockchain

Abstract: A smart device uses information technology to integrate and manage physical, social, and business infrastructures data in order to provide better services to its dwellers while ensuring efficient and optimal utilization of available resources. With the proliferation of technologies such as Internet of Things (IoT), cloud computing, and interconnected networks, for securing smart devices, they can deliver a lot of innovative solutions. Despite a number of potential benefits, digital disruption poses many challenges related to information security and privacy. Here, this project proposes a security framework that integrates the blockchain technology with smart devices to provide security to smart devices.
Automatic Face Recognition and Detection for Criminal Identification Using Machine Learning

Abstract: With the use of machine learning technologies, discovering connections and patterns among various types of data has gotten much easier. Finding out what kind of crime might happen given the location where it has previously occurred is the main goal of this research. We have created a model utilizing the machine learning concept using a training set of data that has been cleaned up and transformed. In contemporary civilization, criminal activity is growing dramatically. Effectively identifying criminals to stop crime is the police's principal challenge, but there aren't enough policemen to go around. There are numerous technical approaches to apprehend criminals, yet many of them are ineffective. In this project, a face detection and recognition system for criminal identification is created using a machine learning algorithm. This system will be able to instantly differentiate the 3D faces of criminals and recognize their faces. This system's one-shot learning method only requires a single image of the criminal to identify him. The objective is to identify the criminal from a distance, extract the criminal's information from the database, and notify the police personnel of the location where the criminal was being observed by a camera.
PENERAPAN METODE FUZZY TIME SERIES-MARKOV CHAIN DALAM PERAMALAN CURAH HUJAN SEBAGAI JADWAL TANAMAN PADI

Rice plants are plants that depend on rainfall because it affects the productivity and quality of rice plants. The purpose of this study is to forecast rainfall in order to determine the right time to plant rice. This study uses the Fuzzy Time Series-Markov Chain method which is a hybrid Fuzzy Time Series method with a markov chain stochastic process. This study uses monthly rainfall data in Kab. Mandailing Christmas from January 2017- December 2022 in mm (millimeter). The data was taken online from the official BPS-North Sumatra website. The results showed that the Fuzzy Time Series-Markov Chain method has a MAPE value of 4.30% which means it has a very good forecasting accuracy value because it is less than 10%. So it can be concluded that forecasting with FTS-MC is a fairly good method in predicting rainfall so that it can forecast for the following month.
PENERAPAN MODEL PEMBELAJARAN CUPS UNTUK MENINGKATKAN KEMAMPUAN PEMAHAMAN KONSEP MATEMATIS DAN MINAT BELAJAR SISWA

The purpose of this study is to improve the ability to understand mathematical concepts and students' interest in learning by applying the CUPs learning model. This research is a classroom action research (PTK) which consists of four stages, namely planning, implementing, observing and reflecting. Data collection techniques carried out in this study used questionnaires, written tests, observations and interviews. Data analysis used is descriptive quantitative and qualitative. This research was conducted in two cycles. The results showed that there was an increase in the percentage of KKM in the ability to understand students' mathematical concepts and the percentage of students' learning interest. In cycle one, the percentage of KKM students' ability to understand mathematical concepts was 52.38% and in cycle two was 85.71%. This was also accompanied by an increase in student learning interest, namely in the first cycle of 71.43% and in the second cycle of student interest in learning, namely 90.48%. Therefore it can be concluded that through the CUPs learning model the ability to understand mathematical concepts and students' learning interest can be improved
A multiple sensitive attributes data publishing method with guaranteed information utility

Abstract Data publishing methods can provide available information for analysis while preserving privacy. The multiple sensitive attributes data publishing, which preserves the relationship between sensitive attributes, may keep many records from being grouped and bring in a high record suppression ratio. Another category of multiple sensitive attributes data publishing, which reduces the possibility of record suppression by breaking the relationship between sensitive attributes, cannot provide the sensitive attributes association for analysis. Hence, the existing multiple sensitive attributes data publishing fails to fully account for the comprehensive information utility. To acquire a guaranteed information utility, this article defines comprehensive information loss that considers both the suppression of records and the relationship between sensitive attributes. A heuristic method is leveraged to discover the optimal anonymity scheme that has the lowest comprehensive information loss. The experimental results verify the practice of the proposed data publishing method with multiple sensitive attributes. The proposed method can guarantee information utility when compared with previous ones.
Usability Analysis of Puskesmas Depok II Management Information System Using Heuristic Evaluation Method

Puskesmas is the frontline institution in health services and counseling. In order to give the services usually Puskesmas has management information system (MIS) to support in data processing. The MIS that is used by them should be in top performance to ease the worker finds and work more effectively and efficiently. In order to ensure the MIS always performes, analysis must be conducted to find problems so improvement can be made. Using heuristic evaluation method, an evaluation is carried out based on 10 indicators by distributing questionnaires to the clinician at Puskesmas. Analysis shows that there are 8 problems from 4 heuristic indicators such as visibility of system status, comparison between the system and real world, flexibility and efficiency of use, help and documentation. The problems that were found are considerably small problems with small priority for improvements. Such problems can be use as references for improvements, enhancements and feature additions to the MIS in Puskesmas Depok II, Sleman District and to ease the user.
When Agility Meets a Project Portfolio: A Study of Success Factors in Large Organisations

The iterative nature of agile methods combined with high levels of team and customer interactions and continuously changing IT and software development project requirements make the management of agile project portfolios very complex. To date, the mechanisms under which project portfolio management adapts to these complexities and achieves portfolio success have not been thoroughly investigated. This study explores the notion of success and its impacting factors in large organisations' portfolios of agile IT and software development projects. Using a multiple case study design, we analysed the agile project portfolios of seven large organisations. We identified four success criteria and 15 success factors and categorised them into a unique agile portfolio success framework. Some of these criteria and factors are unique to agile project portfolios. The framework contributes to agile and project management literature by conceptualising the notion of success in portfolios of agile projects while revealing a set of factors that affect the relationship between an agile portfolio with its subcomponents and the surrounding environment. The framework supports managers and practitioners in large organisations in reflecting on their agility efforts to achieve higher success rates in their agile portfolios.
ANALISIS TINGKAT KERENTANAN BENCANA Studi Kasus: Kawasan Cagar Budaya Candi Muara Jambi

Kawasan Cagar Budaya Candi Muara Jambi is one of the cultural heritage and national heritage in Jambi Province, its location along the Batanghari watershed has a threat to the Batanghari river overflow flood disaster. This study aims to analyze and map the level of disaster vulnerability with the aim of reducing the impact of losses and the impact of the population exposed to disasters. Determination of the level of disaster vulnerability is done with several vulnerability parameters, namely social, economic, physical and environmental vulnerability. In this study, a Geographic Information System (GIS) approach was used to analyze the level of disaster vulnerability using weighting scoring techniques and overlay techniques. This research used secondary data. Based on the results of the study obtained information that the level of vulnerability of flood disasters in the study area is at a moderate level of vulnerability with a high level of vulnerability parameter, namely economic vulnerability with a moderate level of vulnerability parameter, namely social, physical and environmental vulnerability.
Pelatihan Penggunaan Aplikasi Google Form, Puzzlemaker, dan Quizizz sebagai Media Evaluasi Pembelajaran bagi Guru SDI Waemata

One important part of the learning process is evaluation. Implementation of learning evaluation can be done with the help of technology, for example by carrying out computer-based tests. Teachers can also use applications such as Google Forms, Puzzlemaker, and Quizizz as learning evaluation media which are considered more effective and increase student activity. Teachers at Waemata elementary school still use the old way of carrying out learning evaluations by writing test questions on the board for students to complete. Some teachers already know that several applications that can be used to evaluate learning, but they don't know how to use them. Therefore, the solution offered is the implementation of training on using the Google Form, Puzzlemaker, and Quizizz applications which can be used as learning evaluation media. The methods used in this activity are lectures, discussions, and practice using the Google Form, Puzzlemaker, and Quizizz applications as learning evaluation media. As a result, teachers can understand and use these three applications to make a test.
0687 Loneliness, Sleep, and High Risk Alcohol Use in College Students Before and During the COVID-19 Pandemic

Abstract Introduction The aim of this study is to determine what behavioral and psychological factors were predictive of high-risk drinking in students with and without a Substance Use Disorder (SUD) diagnosis. We also compared how these relationships differed between Fall 2019, before the COVID-19 pandemic, and Fall 2020, a period of increased financial stress, distance learning, and social isolation. Methods We used factor analysis to extract a wide range of behavioral and psychological predictor variables from the Fall 2019 and Fall 2020 American College Health Association’s National College Health Assessment III (ACHA-NCHA). Next, we used structural equation modeling to identify significant drivers of high-risk alcohol use (ASSIST alcohol subscale) in students with (n = 577) and without (n = 50,926) SUD diagnosis. Results When compared to 2019, both students with and without SUD diagnosis showed lower levels of high-risk drinking, more difficulties falling asleep, and longer sleep duration. In students without SUD, short sleep duration and loneliness were the primary predictors of past year high risk alcohol use. In students with SUD, long sleep latencies and loneliness (UCLA Loneliness Scale) were the primary predictors, and sleep factors predicted more variance in high-risk alcohol use than in the general college population. Students with SUD diagnosis who also had sleep latencies &amp;gt;30 minutes were significantly more likely to report binge drinking (&amp;gt;5 drinks in one sitting) than those with shorter sleep latencies. Conclusion Sleep factors and loneliness are large predictors of problematic alcohol use in both students with and without diagnoses of Substance Use Disorder. In the first year of the COVID-19 pandemic, students sleep patterns changed with students reporting longer sleep, but also greater symptoms of insomnia. Support (if any)
ANALYSIS OF BITCOIN LEGALIZATION AS AN OFFICIAL TRANSACTION TOOL IN EL SALVADOR

This research begins with the phenomenon of the emergence of Cryptocurrency, one of which is Bitcoin, which is used as currency in El Salvador. In this regard, the research aims to question El Salvador's reasons for legalizing Bitcoin as an official means of transaction. This paper answers questions through qualitative methods using secondary data. The data were then analyzed using a qualitative descriptive analysis. The results of this study indicate that El Salvador's reason for legalizing Bitcoin is to reduce dependence on the United States dollar, attract investors from abroad, and improve the El Salvador economy.
Mediapipe and its suitability for sign language recognition

The paper presents the framework MediaPipe as a tool to extract pose features for the task of word-level isolated sign language recognition.It tests the framework's suitability on the state-of-the-art sign language dataset AUTSL.Extracted sequences of pose features are classified by the Long Short-Term Memory recurrent neural network constructed with the TensorFlow computational library.The paper describes the proposed method flow, preprocessing of the extracted features, and training.Obtained results are then validated on test datasets, and the impact of face landmarks is evaluated.The top-1 accuracy with face landmarks is 49.89 %, while 53.21 % without them.
Artificial Intelligence that Exists in the Human Mind

This article asserts that some general AIs are incomprehensible to humans and that computers are innately incapable of performing certain human cognitive activities, including 1) Misconceptions of Godel's theorem and related statistics and mathematical results are at the root of objections to using AI; 2) Reductionism and objections to monistic reductionism, as well as a minimal appreciation of responses to different levels of discussion; 3) Concerns raised by a thorough understanding of computers or computing Developing a model in which "cognitive" functions can be created independently and referred to as "wetware" is pragmatic, according to a psychologist. The cognitive and essential assumptions for individuals involved in the usefulness of AI are pragmatic. From this point of view, AI is heavily invested in the future of cognitive psychology, if only because of their similar fate.
REINFORCING STUDENTS’ SHORT FUNCTIONAL TEXT WRITING SKILL THROUGH MIND MAPPING TECHNIQUE

This research is generally aimed at problem-solving and improvement attempts for students’ writing skill, especially in short functional text writing. In particular, it is also expected to contribute to the betterment of the teaching and learning processes of the Short Functional Text Writing subject in the Department of English Education (DEE) in the Faculty of Teacher Training and Education of Universitas Muhammadiyah Surakarta and as an alternative technique in teaching the subject for the lecturers. Class Action Research (CAR) is applied to identify whether using mind mapping can help reinforce students’ skill in writing short functional texts. The subject of this research is the first semester students who are being taught Short Functional Text Writing subject. The researchers gathered the data from two cycles in a qualitative manner. The data were obtained from the observation, the results of the tests and the questionnaire. The results of this research are that the students’ motivation increased since they could harness their creativity in making a variety of mind maps from different media and the students’ comprehension about short functional texts improved since mind mapping could help them understand the materials