Reviewerly/exHarmony huggingface dataset:
Face Recognition-Based Attendance System Using Haar Cascade: A Case Study Between Siblings

Traditional attendance systems have long been recognised as inefficient and outdated. For the past years, a lot of research and implementation have been using technological attendance such as web attendance, QR code attendance and mobile attendance. However, due to technological limitations, complexity, inflated costs, power consumption, and limited data transfer capabilities, face recognition systems were not viable options. Today, with significant advancements in technology, computers have become more efficient and powerful, marking a notable departure from the limitations of the past. In UiTM, currently, the implemented system is either web attendance or the traditional attendance system. Many students have pointed out the issue with the web system as students with bad internet reception or issues with their mobile devices will have an issue recording their attendance. On the other hand, traditional systems have imposture issues, by having other people sign the attendance. In this paper, face recognition technology in attendance systems is explored with the benefits it offers, such as improved efficiency and accuracy. The method of the study is by using Python programming language in PyCharm with the implementation of Haar Cascade Adaboost Frontal Face Detector,-Based on the test results, the accuracy for individual testing is calculated at 59.72% with 26 total true positives and 17 true negatives, while the precision, positive rate and F1-score were 57.77 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup> , 0.7222 and 0.6419 respectively. In the group testing, the subjects between three siblings, on the other hand, accuracy, and precision both went down to only a mere 50%.
Modeling Coastal Area Change Analysis of Coastal Urban Areas at Semarang City, Indonesia

A coastal area is defined as the boundary between land and sea. Coastal urban areas are susceptible to various hazards that are becoming more severe, such as flooding, erosion, and subsidence due to a mix of man-made and natural factors, including urbanization and climate change. Regardless of the high importance of coastal area monitoring, conducting field surveys is expensive, time-consuming, and geographically limited to non-remote regions. Semarang City is one of the cities in Indonesia that is at risk of changes in its coastline and causes various natural problems. This research aims to estimate changes in the coastal land area in Semarang City. In observing the phenomenon of changes in area in coastal areas in Semarang City, remote sensing technology with Sentinel-2 satellite imagery was used. This research implements and compares the Random Forest (RF) and Support Vector Machine (SVM) machine learning methods in building classification models. From the results of land area in 2019, 2021, and 2023 with the best classification model, namely SVM, information was obtained on an increase in coastal area of 387.94 ha in 2021, then a change in area decrease of 417.32 ha in 2023.
Hate Speech Recognition: The Role of Empathy and Awareness of Social Media Influence

RICONOSCIMENTO DELL’HATE SPEECH: IL RUOLO DELL’EMPATIA E DELLA CONSAPEVOLEZZA DELL’INFLUENZA DEI SOCIAL MEDIA Abstract Hate speech occurs within democratic societies that embrace freedom of expression and is made tangible in the social network context. It is characterized by a specific form of discrimination based on the use of verbal expressions or other media content and, usually, directed at minority groups. Although there is a lack of consensus about a unique and shared definition of hate speech, its social and personal consequences are particularly relevant for the whole society. For these reasons, it seems of crucial importance to identify hate speech recognition antecedents. The present study aimed at analyzing the relationship between hate speech recognition and specific psychological constructs, namely, empathy and awareness of social media influence. More in details, we hypothesized the association between empathy and hate speech recognition was mediated by awareness of social media influence. Data obtained from 146 participants revealed that empathy positively predicted hate speech recognition, and such relationship was mediated by awareness. Implication of such findings are discussed.
Automated Indonesian Text Augmentation with Web-Based Application Using Flask Framework

Text classification is one of the fundamental tasks in natural language processing (NLP). In the real world, data and resources available for text classification are limited. One of the issues with labeled data is imbalanced data. The problem of imbalanced data affects the performance and accuracy of the model because the model only focuses on data with majority labels. This impacts the model performance, which tends to classify correctly for the majority label only. Meanwhile, in some cases, it is more important for the minority label to be predicted correctly. Therefore, the measure of model accuracy cannot describe the true performance of the model. To overcome this, an oversampling approach is carried out. Text-based oversampling is known as text augmentation. However, NLP resources for the Indonesian language are still limited, especially in performing text augmentation. Therefore, this research conducts the development of a web application to augment Indonesian text automatically. The application was built using the prototype method. Users can perform augmentation automatically for the entire text in the dataset. Users can select preferred augmentation techniques and are required to upload datasets as input. The output of the application is the same dataset file as the input, with an additional column containing synthetic text augmented by the application.
Recognizing fake news based on natural language processing using the BM25 algorithm with fine-tuned parameters

The object of the research is the method of natural language processing (NLP) with balanced parameters of the BestMatch25 (ВМ25) algorithm to recognize and classify fake news based on natural language processing (NLP). The unsatisfactory accuracy and speed of existing methods for detecting fake news in unstructured input data demanded the development of a new approach for their effective detection. The study investigated the BM25 algorithm, methods for selecting parameters k1 and b, and their impact on the algorithm's effectiveness in detecting fake news. It was established that precise and detailed adjustment of these parameters is crucial in achieving optimal accuracy and data processing speed. The results showed that the successful selection of BM25 parameters improves the model's accuracy by up to 14 % compared to standard term frequency – inverse document frequency (TF-IDF) calculations. These results were made possible by experimentally tuning different combinations of k1 and b parameters, in which the algorithm shows the best speed indicator or the most accurate estimate of the importance of a term in a document. Balanced values of k1 and b parameters were identified, leading to the algorithm's optimal speed and accuracy in assessing word importance considering the input data's peculiarities. The balanced setting of the BM25 algorithm parameters explains the obtained results. They can be used for automated recognition and analysis of news and information on social media based on natural language processing. However, in practice, the effectiveness of the set of parameters depends on linguistic variations, content, and the theme within new input data sets
Penerapan Model Pembelajaran TGT Untuk Meningkatkan Prestasi Belajar dan Perilaku Toleransi Siswa Kelas IV SD

This study aims to improve student achievement and tolerance behavior in Thematic learning class IV SDN 17 Bengkulu City by applying the Cooperative learning model type Teams Games Tournament (TGT). The observation data analysis technique uses the formula of the average score, the highest score, the lowest score, the difference in score and the range of values ​​for each criterion. Test data were analyzed using the formula of the average grade and the percentage of classical learning. The average results of the application of the type 1 cooperative learning model Teams Games Tournament obtained 2.44 and cycle II increased 3.68. The average results of the tolerance behavior of students in the first cycle were 7.92 with sufficient categories and the second cycle obtained 13.58 with very good categories. Learning achievements of the first cycle in social studies subjects average grade of 62.4, in the second cycle the average value of the class was 82. Indonesian subjects in the first cycle average grade of 67.2, in the second cycle the average value average class of 80.4. PPKn subjects in the first cycle the average value of the class is 69.2, in the second cycle the average value of the class is 78.88. Thus the application of cooperative learning model type Teams Games Tournament (TGT) can improve student achievement and tolerance behavior in Thematic learning in class IV SDN 17 Bengkulu City.
Analysis of ChatGPT's capabilities for solving problems of reverse-engineering of software

The article presents the results of the analysis and evaluation of the capabilities of the open version of the chatbot with artificial intelligence ChatGPT 3.5 for solving typical problems of software reverse engineering. Three classes of reverse engineering tasks were selected for analysis: source code analysis, binary code analysis, and data models analysis. In each class of tasks, the most typical tasks were selected taking into account the limitations of ChatGPT regarding the processing of graphical models and the amount of input and output data, and sets of test tasks were developed for each task. As an approach to assessment, an approach similar to the assessment of competencies of higher education applicants after studying the relevant discipline was chosen. The following were considered as criteria for evaluating answers to test tasks: correctness (rightness, coincidence with expectations); completeness (obtaining the final result); accuracy (solving the task without additional questions); reasonableness (availability of explanations and answers to questions). The following scale was used and described for evaluations: excellent, very good, good, satisfactory, sufficient, unsatisfactory. During the testing for each test task, tasks statement and all necessary data were entered through the ChatGPT interface. As a result of the analysis, it was determined that ChatGPT better solves the problems of source code analysis (excellent and very good grades were obtained for semantic and structural analysis, restoration of mathematical support, quality assessment, security audit and refactoring, as well as for conversion to another programming language), tasks of decompilation of IDA pseudocode into complete C source code, tasks of reverse engineering of relational databases, and tasks of generating YARA rules for recognizing file formats. Unsatisfactory grades were obtained for dynamic analysis of assembly code and determination of binary file structures of non-standard formats. ChatGPT solves the rest of the problems well and satisfactorily, but requires checking the results, clarifying queries and prompts, as well as manual error correction in some cases. ChatGPT errors were observed when analyzing binary data represented by hexadecimal symbols, as well as errors in generated scripts for programming in IDA. On the basis of the set grades, conclusions were made regarding the expediency, possibility, or impracticality of using ChatGPT to solve each type of software reverse engineering problems, and appropriate recommendations were also provided. Prospects for further research include testing new versions of ChatGPT and other similar artificial intelligence systems regarding the capabilities of analyzing and synthesizing graphical models of software.
Application and Constraint of Illegal Evidence Exclusion in AI Service

With the progress of scientific and technological means, emerging technologies such as AI algorithm and big data mining technology continue to provide strong support for the development of procuratorial work. In the field of illegal evidence exclusion, in addition to seeing the enabling prospect provided by AI, it is also necessary to fully realize a series of technical constraint principles that AI enables the exclusion of illegal evidence. At the same time, a series of prerequisite problems existing in basic theory also need to be fully sorted out and studied before the application and promotion of the exclusion of illegal evidence enabled by AI. Finally, it is necessary to form a refined working mechanism for the exclusion of illegal evidence, including the hierarchical mechanism of normal exclusion and abnormal exclusion, the specific work flow of "machine preliminary screening, business qualitative, case management analysis, and notification of the prosecution Commission" and the hierarchical management mechanism.
STYLISTIC PECULIARITIES AND NON-STORY ELEMENTS CONCEPTS OF NOVEL “GUEST” BY GURAM GEGESHIDZE

The novel “Guest” is important because of the signs of magical realism, as the boundary between real and fictitious, existing and nonexisting world does not exist. The flow of the protagonist’s thoughts is like the characters of Marquez travels in the labyrinth from one decade to another, the thoughts in his consciousness come as a flow, and the histories are replaced by one another, which are ignored by the reader. A strange feeling fell into him, as if, Tarkhuji is an unbalanced individual in time and space. In the paragraph findings of Martin Dujardin and William James are used as a theoretical base to analyse the originality of the “flow of consciousness”. In the paper two kinds of associative natures of consciousness flow are separated: Random and fictional analysis dependant. An internal form of monologue existing in the story is assigned to the last one, which created the works. In the mentioned novel in order to analyze the function of dreams the works of psychologist Sigmund Freud and fundamentalists of psychology Carl Gustav Jung are used in the paper. Also, the dissertation of specialist of Literature Ana Dolidze Psychosemiotic of Dream in Georgian fiction discourse. Herewith, the textbook of Nana Gafrindashvili and Mariam Miresashvili is used as a theoretical base: “Fundamentals of Literature”. Considering the above-mentioned textbook dream is illustrated as a nonthematic element in the paper that is used as an ideological content of the work and psychological description of a character. Based on the dissertation of Ana Dolidze in which a prophetic dream is illustrated as a characteristic of a modernistic story, the article’s function of dream is discussed as another proof confirming that the modernistic ecbasis and tendencies of novel “Guest” is striking. In the paper prophetic dream is discussed based on the example of Tarkhuji’s dream being on the verge of committing suicide.
The Role of Technology in Modern Science Education

The evolution of technology usage in science education, moving from simple tools to advanced applications, forms the focus of this study. An analysis of the positive impacts and challenges faced with current technology in science teaching is conducted. Innovations like virtual learning environments, robotic tools, 3D printing, and AI provide a rich array of options to enhance instruction. Despite the numerous benefits, significant obstacles persist, including the rapid pace of tech advances, unequal access, potential over-reliance on these tools, and privacy and security concerns. The effective use of these technologies necessitates considerable financial and infrastructural support, along with comprehensive teacher training. The research concludes by emphasizing a balanced and critical approach to technology integration, where traditional teaching isn't overshadowed. Future research must focus on equitable tech accessibility, data protection, and adaptability to continuous technological progression for a comprehensive, high-efficiency learning experience.
Navigating Legal Boundaries: Academic Freedom and Content Restrictions in Turkish Publication

In a MetroPOLL survey conducted in July 2020, 62 percent of Turkish respondents asserted that the media in Turkey lacks freedom, while 50 percent felt inhibited in freely expressing their thoughts on social media due to perceived monitoring and the potential ramifications of their actions. In response to criticism, the government often resorts to accusing critics of terrorist affiliations, posing a threat to the state, or engaging in activities jeopardizing national security. Publicly criticizing the state or government in Turkey carries inherent risks, including facing civil lawsuits, criminal charges, or investigations. Individuals who opt to publish or speak on sensitive subjects or criticize the government may undergo scrutiny, punishment, and legal prosecution, with potential consequences such as job loss and imprisonment. Legal proceedings against those expressing critical opinions have multifaceted negative implications for society, influencing perceptions of freedom of expression and serving as a means to intimidate civil society and stifle dissent. This study focuses on elucidating the primary reasons behind these restrictions and examining prevalent instances of legal action. Moreover, precision in language, avoidance of redundancy, cohesive transitions, quantifying information with specific examples, and the use of neutral language have been employed to enhance the academic tone and clarity of the paragraph.
THE EFFECT OF COMPETITIVE ADVANTAGE ON THE RELATIONSHIP BETWEEN ENVIRONMENTAL UNCERTAINTY AND HOTEL PERFORMANCE IN SAUDI ARABIA

The study explores the relationship between environmental uncertainty, competitive advantage, and hotel performance in the context of 1, 2, and 3-star hotels in Saudi Arabia. Quantitative methodology was chosen as the primary research approach. This approach systematically collects numerical data and statistical analysis to derive meaningful insights. The research collected comprehensive data from a specific target group, namely the 1, 2, and 3-star hotels in Saudi Arabia. The findings reveal a significant mediation effect of competitive advantage on the relationship between environmental uncertainty and hotel performance. This underscores the importance of developing and maintaining a competitive advantage to thrive in an uncertain environment by anticipating and adapting to market changes. This study emphasises the vital role of competitive advantage in bolstering hotel performance amidst environmental uncertainty. Future research should seek broader industry representation. Overall, it enhances our understanding of Saudi Arabia's hospitality sector, offering practical guidance for hotel owners and managers in navigating uncertainties.
Social Media’s Influence on Students’ College Selection Processes

Colleges have a keen interest in learning how students choose a college. In the present age of science and technology, young students are extremely influenced by social media. This influences how students make decisions while selecting colleges for their higher education. The main objective of this study was to explore the influence of social media on the college choice process of students in higher education. This study deployed a descriptive survey method under a quantitative research design. The sample was selected by stratified random sampling method. Education, Management, and Humanities faculties were considered as strata for this sampling purpose, within the strata, 270 students have been selected containing 90 students from each stratum using the simple random sampling method. The instrument used to collect the primary data for this study was a self-structured questionnaire. The questionnaire consisted of various structured items, including several four/five-point Liker t- scales, ranking scales, and multiple-choice questions. Descriptive analyses, t-test, and analyses of variance (ANOVAs) at 95% level of significance were used to identify the purpose of using ICT and effect of social media in college choice process of +2 students for their further study. The finding of this study shows that every faculty, gender, and ethnicity group students equally influenced by social media in their college choice process.
PERCEIVED ORGANISATIONAL SUPPORT AND ORGANISATIONAL TRUST LINK TO INNOVATIVE WORK BEHAVIOUR BY THE MEDIATION OF TACIT KNOWLEDGE SHARING

The aim of this study is to determine how perceived organisational support and organisational trust affect innovative work behaviour through the mediation mechanism of tacit knowledge sharing in a public organisation context in Nigeria. Using the cross-sectional research design, data were randomly collected from 258 employees from the Delta State Ministry of Health, which was subjected to the partial least square (PLS) analytical procedure for hypothesis testing. The PLS analysis results suggested that while tacit knowledge sharing mediates perceived organisational support and organisational trust link to innovative work behaviour, it also mediates perceived organisational support link to innovative work behaviour sequentially with organisational trust as an antecedent. The study concluded that perceived organisational support and organisational trust prediction of innovative work behaviour can be explained by tacit knowledge sharing. The study puts forward important practical implications for organisations/management to follow in effectuating the linkages among the constructs in a meaningful and coherent manner.
A Study of Prosodic Entrainment and Social Factors in Mandarin Conversations

In conversations, interlocutors usually adopt prosody to that of their partner, and they become similar in prosodic production for successful communication. This phenomenon of prosodic entrainment is related to complex factors. This study aims to explore the relationship between prosodic entrainment and social factors. Two analyses are accomplished: the analysis of prosodic entrainment and gender, and the analysis of prosodic entrainment and role. In terms of prosodic entrainment and gender, it is found that the most prosodic features are entrained in female-male conversations, and the least in male-male conversations. In terms of prosodic entrainment and roles, it is found that different roles have influence on the entrainment degree, and information givers entrain more to followers in conversation.
Code Blocks and Methods

We’re about to go over some universal rules of code syntax to learn the structure of code files and to understand some fundamental terms and concepts.