Reviewerly/exHarmony huggingface dataset:
Path Planning via Swarm Intelligence Algorithms in Unmanned Aerial Vehicle Population

Unmanned Aerial Vehicle (UAV) is an autonomous aerial vehicle capable of operating autonomously or in swarm cooperation, performing various tasks in civilian and military domains that exceed human capabilities. These vehicles, which can be produced in different models with varying hardware and software features, include flight control systems, route tracking systems, sensors, and numerous additional components. UAVs have the ability to process data from themselves, the control center, and the external environment. Data processing enables functions such as flight management, swarm optimization, and target and route analysis. In this analysis process, optimization algorithms and especially swarm intelligence algorithms inspired by creatures that move in flocks in nature are used. In this study, the aim was to determine the optimal route and distance from 10 different coordinate points for collective task optimization within a UAV swarm. Artificial Bee Colony (ABC) Optimization and Particle Swarm Optimization (PSO) were used during the task optimization process. The application was coded in Python. As a result of the application, the optimal distance was calculated as 0.123 km for the ABC algorithm and 0.167 km for the PSO algorithm. In addition, both algorithms determined the best routes according to different start and end points in route planning task optimisation.
Inception Model for Automatic Arabic Speech Recognition

Reproducing basic human abilities has always been the main purpose for Artificial Intelligence (AI) systems. Since speech is essential to people’s communication, AI was applied to this major field to achieve Automatic Speech Recognition (ASR). In this paper, we focus on the inception model as a solution for Arabic speech recognition, due to its remarkable results on image classification tasks. We adapted this model for ASR problems and tried it on a dataset of spoken Arabic digits collected from social media apps and published corpora which resulted in more than 54000 utterances. A comparison between the proposed model and a traditional Convolutional Neural Network (CNN) shows the superiority of the inception model in ASR tasks. The inception model achieved 99.70% accuracy on the training dataset which is far better than the traditional CNN that achieved 87.46% on the same set, it did also great performance on the test subset with 88.96% accuracy compared to the traditional model with 84.78% recognition rate.
Using RDF Models to Create Knowledge Bases in the Kazakh Language: Comparison with Other Methods

Currently, there is a rapid development of information technologies, the amount of information on the Internet is growing very fast and it is becoming increasingly difficult to find the necessary information. A search using keywords does not give results adequate to the meaning of the information sought. Therefore, the creation of a technology for designing intelligent question answering systems in the Kazakh language based on the presentation, processing and extraction of knowledge is a very actual problem, since it is in such a system that the linguistic and semantic relationships between the texts of the request and the answer can be taken into account. This research paper focuses on the integration of the Resource Description Framework (RDF) model, a semantic web technology, and provides a detailed evaluation of data mining techniques in Kazakh. The paper examines many Kazakh language data collection methods such as online scraping, community collaboration and translation. It also explores the function of RDF models in organizing knowledge, connecting data points and adding semantic richness to datasets. The paper discusses linguistic features and challenges unique to the Kazakh language and emphasizes the need to address these challenges with domain-specific data. The need for thorough cleaning, annotation and data quality assurance is emphasized to guarantee the reliability and use of the collected datasets. Within global communications and technology, the study emphasizes the importance of languages other than English and examines how semantic web technologies can improve data representation and knowledge retrieval. The study lays the groundwork for future initiatives to address the shortage of datasets in languages with fewer resources and to create semantic web technologies for language diversity.
Zullen en willen

This paper offers a corpus-based investigation of the diachronic evolution of the Dutch modal verbs zullen ‘shall/will’ and willen ‘want’. Although they show considerable differences in their developments, neither of these verbs participates in the marked tendency to regain grammatical autonomy characterizing the ‘central’ modals kunnen ‘can’, mogen ‘may’, moeten ‘must’ and hoeven ‘need’. While the latter verbs from New Dutch onwards occur increasingly often without an additional main verb in the clause, this evolution is largely absent in zullen and willen. The paper attempts to offer an explanation on the basis of the developments in the semantic profile of the modal verbs.
The Analysis of Curriculum Approaches in Foreign Language in Indonesia

Foreign language education in Indonesia is evolving with the progress of globalization and increasing exchanges between countries. One of the key aspects of foreign language teaching is the curriculum approach used in the learning process. The purpose of this article is to analyze the curriculum approach used in foreign language teaching in Indonesia. This approach encompasses a variety of curriculum design methods and strategies and focuses on key aspects of foreign language learning. The purpose of this article is to examine curricular approaches to foreign language teaching in Indonesia. This type of research is qualitative research (qualitative research). Qualitative research seeks to understand and interpret the meaning of events in specific situations from the researcher's unique perspective. Qualitative research is a research-based process for understanding the problems of understanding and interpreting texts and creating big pictures from words in a scientific setting. The data collection method used in this study is a data collection method using the library search method. The results of this study demonstrate that this approach has been used as a perspective for curriculum development. Each institution takes a different approach depending on the educational goals they are trying to achieve.
AI Chatbot Innovation – Leading toward Consumer Satisfaction, Electronic Word of Mouth and Continuous Intention in Online Shopping

AI-powered chatbots have emerged as influential tools in the realm of online shopping, effectively driving digital users toward heightened satisfaction, sustained usage intention and positive electronic word of mouth (e-WOM). This research delves deep into the intricate behavioural dynamics that consumers exhibit in their interactions with AI chatbots. A comprehensive online survey, encompassing 554 respondents who willingly engaged with AI chatbots, was conducted, with a focus on established frameworks like the information systems success (ISS) model, the technology acceptance model (TAM), engagement, and the elicitation of pleasurable feelings. The study’s findings underscore the pivotal role AI chatbots play in elevating user satisfaction and, in turn, predicting positive outcomes. These insights hold immense value for brand managers, offering a nuanced understanding of Indian online shoppers’ behaviour. Furthermore, the study highlights the significant impact of e-WOM generated by AI chatbots within the online shopping domain, further solidifying their role as essential components of digital services in the contemporary landscape. As digital services continue to shape and define modern business operations, AI chatbots have emerged as critical facilitators in enhancing the satisfaction of digital users, making them indispensable for businesses seeking to thrive in the digital realm.
The Influence of Learning Environment in the Mastering of 3rs in Public Primary Schools in Nyang’hwale District – Tanzania

This study investigated the influence of the learning environment in the mastering 3Rs in public primary schools in Nyang’hwale District, Tanzania. The study was guided by three objectives namely: factors that lead to pupils’ failure to master 3Rs from standard one up to standard three in public primary schools in Nyang’hwale District, Tanzania, how school environment supports pupils to master 3Rs in public primary schools in Nyang’hwale District. The other objective was to find out the solutions on how we can improve the mastering of the 3Rs to secondary school pupils in Nyang’hwale District. The study used a mixed research approach where both qualitative and quantitative approaches approach were applied. The sample size of the study was 106 respondents, who were obtained through percentages. The participants were selected using simple random sampling stratified sampling and purposive sampling while data of the study were collected through questionnaires and interview guides. Quantitative data were coded through Statistical Package for Social Sciences (SPSS) 20 edition and were analysed by thematic analysis technique. On their part, qualitative data were analysed through content after being grouped. The analysed data were presented in charts, graphs, Tables and explanations. The findings of the study show that there was poor mastery of the 3Rs among primary school pupils in Nyang’hwale District. Most of the primary school pupils in Nyang’hwale District were found to have the problem of poor mastering of the 3Rs. In addition, the findings indicate that the teaching and learning environment had a great influence on the mastering of the 3Rs to primary school pupils in Nyang’hwale District. The study recommends that Teachers should implement strategic teaching methodologies and apply current teaching and learning materials.
Enhancing Verification &amp; Authenticity through Digital Certificate Generation with Facial Recognition for Educational Institutions: A Case Study of IndoAI app

Abstract: In today's dynamic academic environment, millions of students seek various certificates while studying in academic institutions amplifying challenges for educators and administrators in manually handling academic records and certificates, particularly during employment processes and record maintenance. The persistent threat of counterfeiting adds to these challenges. This Case study of IndoAI ‘s Certification addresses the need for a robust authentication mechanism for academic certificates, proposing the utilization of digital certificate systems alongside cutting-edge facial recognition technology. This integration streamlines verification processes, reduces administrative burdens, ensures confidentiality, and enhances overall security. The integration of digital certificates and facial recognition emerges as a comprehensive solution, mitigating the risks associated with identity fraud and impersonation in academic settings and can be answer to blockchain technology in terms of scalability, ease of use and implementation. This system can very well be adopted by Organization’s HR department for internal certifications with Dutypar App’s robust feedback system.
Empowering Introvert Students: How Artificial Intelligence Applications Enhance Speaking Ability

The rapid development of technology has increased the use of Artificial Intelligence (hereafter, AI) applications to improve students’ English skills, especially in speaking skill. This study aimed to investigate the effectiveness of AI applications to improve the introvert students’ speaking ability. Pre-experimental one group pre-test and post-test design was utilized in this study. This study conducted with 85 introvert students from two universities in Riau, Indonesia chosen by using MBTI test and purposive sampling technique. The data were collected through the questionnaire and speaking test. The data were analyzed by using SPSS 25th version to find out the descriptive statistic, normality test, and paired sample t-test. This finding shed light AI applications were effective in improving the introvert students’ speaking ability. It was proved that the t-test was higher than the t-table value (12.8231.663) with the level of significance p0.05. In short, there was significant difference on the students’ speaking ability before and after using AI applications for English speaking practiced. In conclusion, AI applications can be implemented to improve university students’ speaking ability.
Gamification on Netboard: The Students’ Perceptions of its Practice in ESP Classroom

Gamification is a learning approach that uses element from games to motivate students in the learning process and enhance feelings of enjoyment and engagement with the learning process This research aimed to investigate the students’ perception toward gamification as applied in English Language Education. This research was conducted at a private university in Riau, and the sample was 47 students of the sixth semester. This research used descriptive-quantitative approach, and the instrument is questionnaire. The questionnaire consists of 35 questions, divided into 7 indicators. The results of this study were processed quantitatively using the Likert scale formula. The result of this research indicates that students were dominant agreed with the 35 statements of 7 indicators about gamification. The research found that the 1st indicator agreed with index 68.65%, the 2nd indicator agreed with index 71.47%, the 3rd indicator agreed with index 68.65%, the 4th indicator agreed with index 67.16%, the 5th indicator agreed with index 71.1%, the 6th indicator agreed with index 71.7%, and 7th indicator agreed with index 70.8%. Therefore, gamification is a platform that suitable for teachers and students in the learning process, especially in learning English for specific purposes.
Analysis of Research Trends in Elementary Practical Arts Education

This study identifies trends in practical education research and outlines directions for research development by analyzing papers published in academic journals affiliated with academic societies related to practical education. The study analyzed 1,349 papers, comprising 674 papers from the Journal of Korean Practical Arts Education and 675 papers from the Journal of Korean Practical Arts Education Research, published between 2007 and 2022. Papers were analyzed based on frequency and percentage, using a framework that considered publication year, research field, research area, research method, main statistical method, comparison across variables according to research field, research subject, researchers, and language.&#x0D; The study found that the number of research papers published in the academic journals “The Korean Association of Practical Arts Education” and “The Society of Korean Practical Arts Education Research” from 2006 to 2022 exhibited almost identical trends. Regarding the year, publications peaked in 2008 and then exhibited a downward trend from 2011 onward. In the field of practical education research, home science emerged as the largest area of focus, while textbooks and educational materials were most popular across most research fields. In terms of the research method, most papers employed survey research, primarily utilizing the questionnaire method. Quantitative studies primarily employed the t-test. Concerning the variables related to the research field, when compared to research areas, the field of textbooks and educational materials had the highest number of papers across almost all fields. Similarly, when comparing research methods, the majority of papers used research methods involving literature research and questionnaires. Regarding major statistical methods, the t-test was the most frequently used statistical method in all research fields. In addition, the majority of papers related to practical education were aimed at elementary school students, and nearly half of the studies were conducted as independent research by the research team. The predominant language used in most papers was Korean.&#x0D; Therefore, the development of domestic practical education research requires a discernible need for heightened interest and academic engagement, efforts on academic aspects of practical education, promotion of research on educational facilities and philosophical and ideological aspects, utilization of diverse research methods and analysis techniques, and collaborative research undertakings in producing papers and writing in foreign languages.
Findings

The findings obtained by analyzing data from the initial and final questionnaires, as well as the conversation historyConversationHistory of participants, intend to answer the main research questions of this project.
Will the U.S. Court Judge TDM for Artificial Intelligence Machine Learning as Fair Use?

A representative debate is whether TDM (Text and Data Mining) in the machine learning process, which occurs when AI uses other people’s copyrighted works by unauthorized means such as copying, is in accordance with the fair use principle or not. The issue is whether one can be exempted from copyright infringement.&#x0D; In this regard, Korean scholar’s attitude starts from the optimistic perspective that U.S. courts will view AI TDM or AI machine learning as fair use based on the fair use principle.&#x0D; Nevertheless, there is no direct basis for the claim that US courts will exempt AI TDM or AI machine learning from fair use. This is because there has been no case in the United States where a court has recognized fair use by clearly targeting AI TDM or AI machine learning. Meanwhile, The Internet Archive case and the Andy Warhol case are hesitant to expand the fair use principle and are giving rise to pessimistic views on whether the use of other people’s copyrighted works in the AI TDM or AI machine learning process will be considered fair use.&#x0D; Taking that into consideration, American scholars are also developing the argument that the use of copyrighted works for AI machine learning or AI TDM should be considered fair use.&#x0D; Therefore, the positive stance on the possibility of TDM exemption under Article 35-5 of the Korean Copyright Act needs to be carefully reexamined.
Copyright Law Issues Regarding AI-based Literature Translation: Déjà-vu of the Tower of Babel?

Translation is a form of creativity, and AI creativity is making remarkable strides in many fields, including music, art, and literature, but especially in literature translation, where AI-based machine translation is becoming a reality. The recent happening about the winner of the Newcomer Award Competition of Literature Translation Institute of Korea, who was found to have utilized machine translation, has drawn attention to the question of how to set the boundaries between machine and human translation. I argue that AI-generated translation (AIGT), which is a purely AI translation without human assistance, is only reproduction under copyright law, while AI-assisted translation (AIAT), which is a human translation with the help of AI, can be a derivative work under copyright law as a translation. The distinguishing factor between the two is the control and subjectivity of human users of machine translation in the post-editing process, and the context surrounding the translation. This paper points out that excessive pre-editing by human users to facilitate machine translation may undermine the diversity of the original text. Once the legal status of machine translation output has been determined, I discuss the legal responsibility of human users to exercise due care at the stage of publication. The legal liability of failing to disclose that a work is the result of machine translation is also discussed, as well as plagiarism liability, which is not a legal liability.
IMPLEMENTATION OF THE K-MEDOIDS METHOD IN CLUSTERING HUMAN DEVELOPMENT INDEXES IN INDONESIA

The Human Development Index (HDI), which takes into account three fundamental aspects of human existence, a long and healthy life, knowledge, and a reasonable level of living, is one tool used to assess the effectiveness of human progress. Clustering provinces based on the human development index is important so that development disparities can be identified and help identify provinces with high, medium or low levels of development. The purpose of this study was to use the k-medoids approach to perform a cluster analysis of HDI in Indonesia based on life expectancy, average years of schooling, expected years of schooling, and expenditure per capita adjusted for 2022. The analysis indicate that two clusters were created: cluster 1 had a high human development index, while cluster 2 had a low human development index. More provinces belonged to cluster 1 than cluster 2 suggesting that human development index in Indonesia in 2022 was largely in the high category
Understanding Basic Literacy and Information Literacy for Primary Students

This research describes basic literacy and information literacy for elementary (primary) students. This research is library research. The analysis shows that primary students should understand six basic literacies, including 1). Literacy Read and Write (ability to understand the contents of written texts both explicit and implicit). 2). Numerical Literacy (ability to use basic mathematical symbols and numbers to solve practical problems and analyze mathematical information). 3). Scientific Literacy (ability to understand natural phenomena both scientific literacy and social phenomena). 4). Financial Literacy (ability to understand finance, concepts, management, risks, and skills in the financial sector. 5). Digital Literacy (ability to use digital media, create communication content, and filter information). 6). Cultural Literacy and Civic (ability to understand values, rights, and obligations as Indonesian citizens). Besides, understanding information literacy is also important for students. Several benefits of literacy are 1) training basic skills to read, write and count, 2) developing to think critically and logically when entering society and facing any situation. 3) having good literacy development correlates with better learning and communication skills, solving logical problems even academic achievement.
The Techniques Used in Mitosis Detection in Breast Cancer Histopathology Images: A Survey

Breast cancer consider as the second cause of death around the world after heart disease, and it is the primary cause of death for women. Timely detection of breast cancer plays a crucial role in lowering mortality rates, as it enhances the patient's prospects of survival through prompt diagnosis and appropriate treatment. The discovery of the mitotic number is one of the necessary procedures that must be performed for a person suffering from breast cancer because it is an important marker for determining the aggressiveness of the tumor. According to the Nottingham scale, it gives 3 degrees to determine the degree of the tumor, whether it is of the first degree, the second degree, or the third degree of seriousness. Deep learning algorithms have many contributions in the medical fields, including in the field of mitotic number discovery, as the mitotic number process is a difficult and tiring task that requires time and effort from pathologists (diagnostic doctors), because the work environment is under microscopes with high magnification degrees, for this reason deep learning techniques were used to reduce the burden on diagnostic doctors and save time for the patient to know the result of his examination, as the biopsy results in developed countries take from 10 days to two weeks for the results to appear. In this survey, we will evaluate the deep learning techniqus employed for mitotic number detection.