Reviewerly/exHarmony huggingface dataset:
Effective Cyberbullying Detection with SparkNLP

Abstract: People of all ages are affected by cyberbullying, which has become a serious problem that can have negative effects like depression and even suicide. As a result, social media content regulation is becoming more and more necessary. Our research project uses SparkNLP, a potent and scalable natural language processing library, to address the problem of cyberbullying. A model for detecting cyberbullying was developed by us using a dataset of 48,000 tweets from Kaggle for training. We used the Universal Sentence Encoder (USE) to extract text data, and ClassifierDL, which employs deep neural networks and uses USE as an input for text classification, was used to build the classification model. Class imbalance is a problem, so we used text augmentation to address it. Age, ethnicity, gender, religion, other cyberbullying, and not cyberbullying are six categories into which our methodology accurately detects and categorizes cyberbullying. We evaluated the model on a held-out set of data to assess its accuracy and resilience, and it produced remarkable results of 93.34% on training data and 89% on test data. The goal of our project is to support and reinforce the ongoing initiatives that are working to stop cyberbullying and to advance a secure and positive online environment for everyone.
The Effect of Word Square Model on Students Vocabulary at Grade X of SMK Tamansiswa Sukadamai in Academic Year 2019/2020

The title of this study is the effect of word square model on students’ vocabulary at grade X of SMK Tamansiswa Sukadamai in Academic Year 2019/2020. The objectives of the study is to describe how the implementation of teaching english vocabulary by using word square at SMA.N.1. Buntu Pane. The population of this research was taken from the grade X students at SMK Tamansiswa Sukadamai, which have 102 students. The data were collected by using 10 essay question. Several steps of work have been done preliminary. The further steps is to follow the active concerning with the data. Starting from library check, confirming the location, asking permission from the pre-test and post-test value that worked by students in experiment class and control class are very significant. The data were analyzed by t-test. The result of students’ vocabulary. It was suggested that using media in teaching can made the students feel enjoy when they study about vocabulary and according to this skripsi the teacher can increase their teaching skill.&#x0D; Keywords: Word square model; students’ vocabulary; media in teaching
Analysis of Language Acquisition in Early Children's Language Development and Teaching

The research objective was to identify and describe the results of the analysis of language acquisition in the development and preparation of early childhood language in Paringgonan village as phonology teaching materials. The method used is descriptive method. Collecting data using observation, taking notes in the form of records, important notes from interviews. Data analysis techniques used are reduction, presentation, and retrieval of research results. Based on the research results, it is known that the language stimuli received by children are regular. Children understand understand linguistic systems of first language before turning 5 years of age. However, after coaching and building good and correct language for children. It is known that 78% of children’s language acquisition is better in pronouncing vowels, consonants, every word &amp; sentence (in the field of phonology) using Indonesian. Furthermore, based on the results of interviews with the child’s parents, it is known that 80% of the educational background &amp; application of the parents greatly affects the child’s language in good and correct language.&#x0D; Keywords: Language acquisition; development; early children’s; teaching
Comparison of Machine Learning Algorithms for Human Activity Recognition

Human activity recognition (HAR) is utilized to automatically identify the daily-life activities of people for the effective management of age-related health conditions.Classical machine learning (ML) algorithms are used to design HAR systems, in a subject-specific or population-based configuration depending on the application.In this study, the performance of 8 classical and ensemble-learning-based ML classifiers has been studied for both HAR configurations.Inertial measurement unit (IMU) signals from 10 healthy participants, corresponding to various static, dynamic, and transitional daily-life activities, were acquired.Random forest (RF), ensemble adaptive boosting (EAB), ensemble subspace (ES), decision tree (DT), k-nearest neighbors (KNN), linear discriminant analysis (LDA), support vector machine (SVM), and artificial neural network (ANN) were used to classify these activities.The performance of the classifiers was measured in terms of mean classification accuracy (MCA).The results showed that, for a subject-specific HAR system, ES (97.78%) has achieved the highest MCA followed by RF (96.61%) and SVM (96.11%) while outperforming the DT, KNN, and LDA (P-value < 0.05).For a population-based HAR system, SVM (95.18%) achieved the highest MCA, however, no significant difference has been observed among the MCA of all the investigated classifiers (P-value > 0.05).Also, the class-wise comparison reveals that SVM outperformed the other investigated classifiers in terms of MCAs for each of the distinct activities.Based on the HAR configuration incorporating diverse static, dynamic, and transitional daily-life activities, the findings may be used to develop a customized HAR system for the effective management of movement disorders. INTRODUCTIONAccording to the International Diabetes Foundation (IDF), the global diabetes prevalence in adults aged 20 to 79 years old is expected to be 536.6 million in 2021, rising to 783.2 million in 2045 (Atlas, 2015).Similarly, more than 10 million people worldwide are living with Parkinson's disease (PD) and the incidence of PD increases with age (Tysnes & Storstein, 2017).Such an aging population needs care.Smart healthcare systems seem to be a possible answer to the rising aging population dilemma.They can provide smart health services to meet the needs of this rising population by monitoring and analysing any critical health state of the elderly in their daily a
Integration as a Basis for Holistic Training of Students-Journalists (on the example of the experience of the department of journalism of NSPU)

Existing approaches to teaching at a university involve the widespread use of innovative technologies, which, however, are not completely capable of overcoming the subject disunity of the modern education system. This problem is relevant in the training of personnel for the media. The authors of the article see its overcoming in the integrated training of student journalists, which involves the formation of both professional and personal competencies. The purpose of the article is to identify the specifics of teaching journalism students, which is carried out within the framework of an integrated approach, which helps to ensure integrity in the training of future workers in the field of mass media. Methodology and research methods. The work is based on the study of general approaches to the organization of integrated learning. The main methods are theoretical, including analysis of the literature on the research problem, synthesis, generalization and interpretation of data, and empirical, represented by a participant observation. Research results. The authors propose their own definition of integrated learning, the study describes the system for training student journalists at NSPU, which allows achieving the integrity of learning through integration. Conclusion. Integration in the training of students-journalists is understood as an educational process implemented in educational and extracurricular activities, which are determined by the qualitative transformations that occur during the multidirectional training of students.
System of searching for vague duplicates in electronic texts

International scientific conference «Information technologies and management in higher education and sciences» : conference proceedings (November 28, 2022. Fergana, the Republic of Uzbekistan). Riga, Latvia : “Baltija Publishing”, 2022. Part 3. 432 pages.
Detection of uses of disposed resources in C\# source code using static analysis

The paper is devoted to the scalable approach for the detection of uses of disposed resources in C# source code, that is based on static symbolic execution. The resulting detector is implemented as a part of an industrial SharpChecker, that performs a scalable inter-procedural path-, and context-sensitive analysis. The evaluation of the developed detector shows 70% true positive ratio allowing it to include to the standard set of detectors and provide functionality to users. The paper describes a detection algorithm that takes into account the limitations imposed by the existing infrastructure of SharpChecker, its evaluation on the set of open-source programs containing 6 mln LOC and some examples of found errors in real projects.
On the possibilities of using artificial intelligence in higher education

International scientific conference «Information technologies and management in higher education and sciences» : conference proceedings (November 28, 2022. Fergana, the Republic of Uzbekistan). Riga, Latvia : “Baltija Publishing”, 2022. Part 3. 432 pages.
The role of information and digital competence of a modern teacher in the conditions of transformations of the educational process

International scientific conference «Information technologies and management in higher education and sciences» : conference proceedings (November 28, 2022. Fergana, the Republic of Uzbekistan). Riga, Latvia : “Baltija Publishing”, 2022. Part 3. 432 pages.
Sоciаl cоmpetence аs а pаrt оf the prоfessiоnаl cоmpetence оf the future sоciоlоgist

International scientific conference «Information technologies and management in higher education and sciences» : conference proceedings (November 28, 2022. Fergana, the Republic of Uzbekistan). Riga, Latvia : “Baltija Publishing”, 2022. Part 3. 432 pages.
System for Automatic Grouping of Metadata of Three-Dimensional Models

The purpose of this work is to develop the structure of the algorithm for automatic grouping (clustering) of 3D model metadata which may include model name, dimensions, file size, file format, keywords etc.. The relevance of this work is determined by the need for companies to process complexly structured data, in particular 3D models, and detect groups of similar 3D models for forming their catalogues and other purposes. "similarity", we mean the proximity of objects in a multidimensional space of features, and the problem is reduced to partitioning this space into subspaces of objects so that the objects located in the subspaces form homogeneous groups. We propose an algorithm for automatic grouping of the 3D models based on their metadata, which enables us to group objects according to their numeric and categorical characteristics. The experiments were carried out with the involvement of experts, their evaluation showed the high efficiency of the developed method.
Classification Algorithm With Lexicase Selection

The hybrid fuzzy genetic based algorithm was implemented. The genetic fuzzy systems are applied for classifier learning, and although they allow creating interpretable rule bases, the process of designing a rule base can be improved with specific genetic operators, such as lexicase selection. The influence of lexicase selection on the efficiency of its work for data classification is examined in this article. “Ring”, “Phoneme” and “Satimage” datasets were used for verification. The results were analyzed by verification using Mann-Whitney U test. According to the results of basic hybrid fuzzy genetic based algorithm with lexicase selection of several runs, where in each the duration of the search for the best rule base was limited to five hundred generations, efficiency was only on number of rules, but paired with the previously developed initialization modification, the accuracy and F-score were improved on “Satimage” dataset and the number of rules decreased on all of the datasets.
Identification of Differential Equations Systems With Various Input Effects

Nowadays, differential equations and their systems are one of the most preferred ways to represent models of dynamic objects. Objects from different areas are dynamic. Therefore, a great number of methods for dynamical systems identification have been developed. However, as processes become more complex, there exist a need to develop new tools. A change in the input action according to a predetermined law could be one of features for dynamic processes. The paper studies the efficiency of the method based on evolutionary algorithms to identify objects in the form of systems of differential equations with various input effects. Genetic programming and differential evolution are the algorithmic basis of the method. The method performs self-configuring of parameters for evolutionary algorithms. The presented paper studies efficiency of the proposed method on five problems where the initial objects are represented by systems of differential equations of various orders. The conducted study takes into account the presence of noise in the initial samples. It demonstrates graphical interpretation of the obtained results. The obtained results prove efficiency of the developed method under various input influences.
Crime Scene in Cybercrime Criminal Offenses: Evidence Management and Processing

Since the 1990s, when the first computers were introduced as workplace tools and the technological expansion began, computers, information technologies, and the internet have become an indispensable part of our daily lives. Computers are now an essential tool in all aspects of life, including business, telecommunications, and personal use. Given the increased use of information technologies in our businesses and daily lives, it is not surprising that computer-related crimes are on the rise. The widespread use of computers in our society has resulted in a rapid rise in issues and problems associated with crime, particularly cybercrime. As cybercrime committed via the internet and computer networks becomes more prevalent, courts require technical personnel who are experts in this field. The proper legal framework and division of investigative responsibility are not always clear. Law enforcement faces new challenges as it works to improve its capacity to investigate and prosecute cybercrime. This paper discusses crime scene management for cybercrime criminal offenses. So, we aim to research and present in the most meaningful way what the crime scene is, how site inspection is carried out, how the crime scene is preserved and secured, and what the crime scene documentation is, knowing that traces and material evidence in cybercrime cases occupy a special place in the investigative process.&#x0D; &#x0D; Received: 17 November 2022 / Accepted: 12 February 2023 / Published: 5 March 2023
THE SIXTH AND SEVENTH LARGEST NUMBER OF SUBUNIVERSES OF FINITE LATTICES

Abstract. By a subuniverse, we mean a sublattice or the emptyset. We prove that the sixth largest number of subuniverses of ann-element lattice is 21.125·2n-5 and the seventh largest number is20.75 · 2n-5. Also, we describe the n-element lattices with exactly21.125 · 2n-5 and 20.75 · 2n-5 subuniverses
Bullying and School Coexistence in the Return to Class of Primary School Students after the COVID-19 Pandemic: Evidence Collected in Peru

Bullying is a public health problem widely discussed by both academics and education professionals. It is a permanent behaviour of violence that could be physical, verbal, psychological and even sexual, which discredits the victim and places him/her in a situation of fragility in his/her environment. The objectives of this research were to determine the levels of bulling (and its dimensions); to determine the levels of school coexistence (and its dimensions); and finally to analyse the relationship between bullying and school coexistence (and its dimensions) in an educational institution located in Cajamarca, Peru in the first year back to school after the pandemic caused by COVID-19. The study presented a quantitative approach, with a descriptive and correlational level, and a non-experimental design. According to the literature explored, bullying has 4 dimensions (physical bullying, verbal bullying, sexual bullying and psychological bullying), while school coexistence has 3 dimensions (inclusive coexistence, democratic coexistence and peaceful coexistence). The population consisted of 120 students in the sixth grade of primary education, of both sexes, from a school located in Cajamarca, in northern Peru. Two instruments were used: the school bullying questionnaire (with 56 items) and the school coexistence questionnaire (with 37 items). Both instruments showed validity and reliability after being tested. Among the results, it was observed that most of the schoolchildren presented bullying at low level (57.5%), followed by medium level (22.5%) and high level (20.0%); on the other hand, regarding the school coexistence variable, the low level was 36.0%, the medium level 53.0% and the high level 11.0%. Finally, it was determined that bullying is significantly related to school coexistence (p. &lt; 0.001); as for the intensity of the correlation, it is negative and moderate (r = -0.551), the greater the bullying in school contexts, the lower the school coexistence in this space.&#x0D; &#x0D; Received: 11 November 2022 / Accepted: 12 February 2023 / Published: 5 March 2023
Vocabulary introduction about word classes for Al-Islah Islamic Kindergarten teachers, Sukoharjo

The community service program was carried out with encouragement to improve the ability and understanding of word classes in English for kindergarten teachers, especially TKIT Al-Islah, Jombor Village, Mojolaban District, Sukoharjo. The material presented consists of pronoun, verb, adjective, noun, and adverb. Service activities in the form of this training begin with pretest questions and end with post tests. The evaluation showed an increase in word classes knowledge in English where the pretest results were 72 to 90 during the posttest. Thus, it is expected that teachers can develop English learning materials by utilizing their word classes knowledge.
DEVELOPMENT OF TEACHING MATERIALS TO IMPROVE READING COMPREHENSION SKILLS FOR 5TH GRADE STUDENTS: CANVA APP SUPPORTED

The purpose of this study was to examine the effect of teaching materials based on the Canva application developed on improving the reading comprehension skills of grade 5 students. The approach used in this study was Design and Development (Ellis &amp; Levy, 2010) with six steps, namely Identify the Problem, Describe the Objectives, Design &amp; Develop the Artifact, Test the Artifact and Evaluate the Testing Result, Communicating the Testing Result and Dissemination. Data were collected through teacher interviews, questionnaires, pre-test and post-test. This study used a sample of 171 5th grade students in 3 elementary schools. The results of this study indicate that the use of teaching materials based on the Canva application has a significant effect on increasing the ability to read comprehension of information texts for grade 5 students. This is evidenced by the differences in students' reading comprehension abilities of information texts before and after learning by using application-based teaching materials. canva. This research has implications for the ease of teachers in achieving learning objectives with the support of teaching materials, media, worksheets and interesting and practical activities that are able to stimulate students in improving their reading comprehension skills, especially informational texts.
A DEPTH INSPECTION ON INFORMAL SCHOOL STUDENTS’ DILEMMA IN TRANSLATING ENGLISH ARGUMENTATIVE TEXT TO INDONESIA

The aim of this research is to analyse students' difficulties in translating argumentative text. It was conducted at FLC Course. The participant of this research consisted 15 students. The method of this research was descriptive qualitative. The instruments of this research were translation text and questionnaire sheet. The result of this study from translation text, students made mistake which were the ambiguity, sentence pattern, missing words, and non-linguistics factor. In questionnaire sheet, the highest score of students' difficulties was in linguistics factor which was about 55 score. It was difficulty in translating words which had double meaning. In non-linguistics factor, the highest score was 52 score. It was difficulty in translating words that related with ideology value. Besides, there are internal and external factors from within students that affect their difficulties where the internal factor is the students' motivation and interested in learning is lacking. While external factors are a lack of attention from the teacher and parent, inexact of methodologies in leaning and the lack of student facilities in learning. Based on the result above, it can be concluded that students' difficulties in translating argumentative text more dominant come from linguistics factor than non-linguistics factor.
TEACHER PERCEPTIONS ON THE USE OF QUIPPER SCHOOL APPLICATION IN TEACHING READING

This study was focus on the teacher perceptions on the use of quipper school in teaching English reading. The study was conducted at SMA N 1 Kayu Agung. There were two English teachers who became the sample for this study. The aim of this study was to answer this following question; How were the teachers perceptions using quipper school application in teaching reading at SMA N 1 Kayuagung? A qualitative study was used for this study. Based on the result of this study, the English teacher assumed that Quipper School application is very helpful for teaching English reading. However, the researcher hope that the next study can conduct a deepen study on the students’ perception in leaning English reading using Quipper school.
The Effort Of Theacer To Help Children With Special Needs Who Have Learning Difficulties At SDI Bung

There is a special issue faced at SDI Bung, namely there are students who have reading difficulty, writing difficulty, and calculating difficulty even though they are already in the high grade (grades 4, 5 and 6). They are grouped in children with special needs. They could not distinguish letters and interpret them, copy handwriting and put it in sentences, distinguish signs, symbols or numbers. The research aims are to find out the types of learning difficulties of children with special needs at SDI Bung and the efforts of teachers to overcome it. The method used in this research is descriptive qualitative with interview technique. The results showed that there were three types of learning difficulties for children with special needs at SDI Bung, namely reading difficulties (dyslexia), writing difficulties (dysgraphia), and calculating difficulties (dyscalculia). Toward these three difficulties, the teacher tries to help them by providing instructions according to the level of error such as entering the alphabet, practicing combining letters into words (dyslexia); training students to trace letter shapes and practice copying text (dysgraphia); and make basic practical exercises using visual aids, intensive guidance and provide teaching according to the level of complexity (dyscalculia). Seeing the three types of learning difficulties for children with special needs above, the researchers suggest that teachers at SDI Bung must train students in the three basic skills, namely reading, writing and counting in lower grades until they master them.