Reviewerly/exHarmony huggingface dataset:
ENHANCING SPEAKING SKILL THROUGH AI-POWERED TECHNOLOGY

. Artificial Intelligent (AI) is a field of computer science devoted to solve cognitive problems, commonly associated with human intelligence, such as learning, problem solving and pattern recognition. From education point of views, it helps teachers to facilitate learning process especially for speaking skill. The research method runs with mixed method (qualitative. And quantitative) The aim of this research is investigating the students’ speaking performance with artificial intelligence. The data collection is taken from interviews, photo, and literature studies. The result of this study is the increasing student’s speaking performance with AI.
The Market for Foreign Bases

Power projection is a central means by which states exert influence. Conventional wisdom holds that states pay more for foreign bases in the presence of third-party competitors, yet the mechanisms by which competition shapes the costs of bases are both theoretically underspecified and empirically understudied. This article tests three mechanisms by which competition can shape the price of access: denial, crowding out, and information. We study the behavior of the United States in Africa, using new data on US compensation and bases and qualitative evidence from the US presence in Djibouti. Our findings suggest that China’s economic incentives have crowded out the effectiveness of US economic incentives in securing access. We further show that Djiboutian leaders escalated their demands for US compensation as other base-seekers entered the market due to a combination of US efforts to limit its rivals’ access and Djibouti’s learning about the value of its real estate.
Influence of Using CANVA Media on Learning Outcomes of ClassVII Students at MTSN 2 Sidenreng Rappang

The lack of excitement for training students' speaking abilities is at the root of the problem in this study. Researchers are curious about: 1) This English Tutor exercise provides an incentive for students to practice speaking English. 2) Students' conduct or effort in practicing speaking English through English Tutor activities, attitudes, interests, values, or desires The design of this study is descriptive-quantitative. Creswell (2012: 13) describes quantitative research as defining a research challenge based on trends in the field or the need to explain why something occurs. According to the study's findings, 1) the learner's effort in practicing speaking English among ILP students is 63% or higher, and 2) the students'' interest in practicing speaking English is 37%. 3) 47% of learners have a positive attitude regarding English-speaking practice. 4) The student has a 50% motivation to practice speaking English. The following are the findings: 1) Having a variety of learning activities and subjects available is beneficial for increasing motivation and offering opportunity for concept exploration. 2) To avoid monotony, vary the tactics employed in the learning process. 3) Rewarding and encouraging students who can successfully express themselves in English. 4) Making the classroom an inviting atmosphere.
GCLR: A self-supervised representation learning pretext task for glomerular filtration barrier segmentation in TEM images

Automatic segmentation of the three substructures of glomerular filtration barrier (GFB) in transmission electron microscopy (TEM) images holds immense potential for aiding pathologists in renal disease diagnosis. However, the labor-intensive nature of manual annotations limits the training data for a fully-supervised deep learning model. Addressing this, our study harnesses self-supervised representation learning (SSRL) to utilize vast unlabeled data and mitigate annotation scarcity. Our innovation, GCLR, is a hybrid pixel-level pretext task tailored for GFB segmentation, integrating two subtasks: global clustering (GC) and local restoration (LR). GC captures the overall GFB by learning global context representations, while LR refines three substructures by learning local detail representations. Experiments on 18,928 unlabeled glomerular TEM images for self-supervised pre-training and 311 labeled ones for fine-tuning demonstrate that our proposed GCLR obtains the state-of-the-art segmentation results for all three substructures of GFB with the Dice similarity coefficient of 86.56 ± 0.16%, 75.56 ± 0.36%, and 79.41 ± 0.16%, respectively, compared with other representative self-supervised pretext tasks. Our proposed GCLR also outperforms the fully-supervised pre-training methods based on the three large-scale public datasets – MitoEM, COCO, and ImageNet – with less training data and time.
AI-Generated Text Detection: Challenges and Future Directions

With the rapid development of large language models (LLMs), the quality of AI-generated context (AIGC) is rapidly improving, and the correctness and detection of generated content have become a global challenge. In this paper, we review the current methods of AIGC detector and introduce the definition, dataset and methods of AIGC detection, including the manual-based methods, rule-based methods, statistical learning-based methods, deep learning-based methods, knowledge enhancement-based methods and watermarking-based methods. However, these methods have very low recognition accuracy when facing the latest LLMs, such as ChatGPT and GPT-4. This paper also suggests that more work should be put into identifying AIGC quality in the future, such as whether there are logical errors, knowledge errors or data falsification, which may have more severe consequences and be more likely to be detected.
GiusBERTo: Italy’s AI-Based Judicial Transformation: A Teaching Case

In an age when open access to law enforcement files and judicial documents can erode individual privacy and confidentiality, miscreants can abuse this open access to personal information for blackmail, misinformation, and even social engineering. Yet, limiting access to law enforcement and court cases is a freedom-of-information violation. To address this tension, this collaborative action-research-based teaching case exemplifies how Italy’s Corte dei Conti (Court of Auditors) used artificial intelligence in the automated deidentification and anonymization of court documents in Italy’s public sector. This teaching case is aimed at undergraduate and graduate students learning about Artificial Intelligence (AI), Large Language Model (LLM) (e.g., ChatGPT) evolution, development, and operations. The case will help students learn the origin and evolution of AI transformer models and architectures, and discusses the GiusBERTo operation and process, highlighting opportunities and challenges. GiusBERTo, Italy’s custom-AI model, offers an innovative approach that walks a tightrope between anonymizing Italy’s judicial court documents without sacrificing context or information loss. The case ends with a series of questions, challenges, and potential for LLMs in data anonymization.
Using Data Interviews to Map Research Data Services (RDS) Needs at a Health Science Institution

Objective: On January 21, 2023 the National Institutes of Health Data Management and Sharing Policy (NIH DMSP 2023) went into effect. Ahead of these expanded data sharing requirements, the Health Sciences Library at the University of Tennessee Health Science Center (UTHSC) set out to better understand health science research data service (RDS) needs and how the Library could develop new services in alignment with existing institutional support.Methods: Building upon a set of data interview questions created by Read et al. (2015), the author conducted a series of semi-structured interviews with 10 researchers in the fall of 2022. The interview transcripts were inductively coded and analyzed for themes relevant to RDS needs.Results: Analysis of the interviews identified several opportunities for the Library to take ownership of RDS activities in the areas of support services, training and instruction, and tools and technology. Additionally, these interviews helped to characterize existing institutional support and to develop an informal community of practice at the University of Tennessee Health Science Center (UTHSC). These RDS topics were mapped onto Harvard’s Biomedical Data Lifecyle to further clarify areas of need and opportunities for growth for the Library and institutional RDS partners.&amp;nbsp;Conclusions: The study identified critical RDS needs among UTHSC researchers and highlighted the potential role of the Library as a valuable partner in addressing these needs and fostering collaboration among campus stakeholders. Conversations informed by these findings continue with stakeholders about the best way to meet the needs of researchers on campus as well as centralize and coordinate existing endeavors.
Machine Learning Models: A Study of English Essay Text Content Feature Extraction and Automatic Scoring

Accurate automatic scoring of English essay is beneficial for both teachers and students in English teaching. This paper briefly introduced an XGBoost-based automated scoring algorithm for English essay. To improve the accuracy of the algorithm, a long short-term memory (LSTM) semantic model was introduced to extract semantic scoring features from essays. Finally, the improved XGBoost algorithm was compared with the traditional XGBoost and LSTM algorithms in a simulation experiment using five types of essay prompts. The results indicate that the improved XGBoost algorithm has the best performance for automatic scoring of English essay and also requires the shortest scoring time.
Uso de los FAB LAB en el desarrollo de capacidades de innovación en los docentes de Educación para el Trabajo

ABSTRACT This opinion article entitled: Use of FAB LAB in the development of innovation skills in teachers of Education for Work, aims to make known the importance of the use of FAB LAB in the development of innovation skills in teachers of Education for Work. To this end, a review of the emergence of FAB LAB and some examples of how they operate are presented. If such technologies are used by citizens, they would have the capacity to co-design their material culture, Malinowski (2021). It is concluded that it is necessary to boost innovation through technology.
Educational possibilities of gaming technologies in the process of teaching school students in the class and under the conditions of blended learning

The article reveals the methodological and didactic possibilities of using gaming technologies in the classroom and in online learning. The productivity of this technology in solving educational problems is substantiated. Specific practical tools are considered that allow the teacher to achieve the planned result. Directions for improving the methodological support of the lesson in the organization of work in the format of blended learning are proposed.
Hybrid application development with Delphi &amp; Javascript

The paper contains brief insights into the history of the development of Delphi and JavaScript programming languages and some ways to create hybrid source code applications. The application design is created in Delphi and the JavaScript code is implemented through the TWebBrowser component. This combines the Delphi concept of fast application creation with the multitude of open-source JavaScript libraries.
Face Authentication using MTCNN and FaceNet

Abstract: Advancements in facial recognition are on the rise after the recent breakthroughs in deep learning technologies and the extensive training datasets. But still, the practical application of facial recognition for authentication purposes faces some difficulties and problems when dealing with variations that are observed in real-world scenarios, including variations in facial poses, varying angles, lightning conditions and potential obstructions. In order to resolve these challenges, this paper presents an innovative deep learning API, which combines the capabilities of MTCNN and FaceNet, to overcome these limitations. Building upon the foundations of MTCNN and FaceNet, we have developed an API capable of verifying the identity of users through a two-step verification process. The system utilizes MTCNN for precise face detection and FaceNet for facial feature extraction that has the ability to directly map facial images into a compact Euclidean space in which spatial distances directly reflect facial similarity, and then storing this data securely within a MongoDB database. We have used the cutting-edge Deep Face model, developed by Facebook’s AI research team. Its reliable deep learning capabilities have helped us in achieving exceptional accuracy in the user’s verification process. This system serves to provides a superior level of user authentication, effectively reducing the risk of an unauthorized access while optimizing the user experience. Even though there is still some room for improvement within our experiment, we are committed to providing a comprehensive summary of our findings and an exploration of the challenges on the horizon.
Educational policies specific to ICT programs in primary education

This article presents the theoretical aspects of educational policies specific ICT programs in primary education, conceptual determinations on educational policies, the development of educational politicies, as well as studies on the use of ICT in primary education.
Analysis of Students’ Ability to Rearrange Jumbled Sentences into an Effective Procedure Text

An explanation of how something is accomplished through a series of steps or actions is given in a procedure text. It has features of language, general structure, and text arrangement. The goal of this study was to find out whether or not students could successfully rearrange a collection of sentences into a process text. Descriptive research methodology was used. Students of vocational high school Kartika 1-2 Padang's second year made up the study's population. Forty students made up the samples. Utilizing proportional stratified random sampling, the sample was taken. The researcher used a writing test instrument called a scrambled sentence test to get the data for this study. According to the results, it can be said that the second-year students at vocational high school Kartika 1-2 Padang had a fair amount of aptitude for organizing sentences into an effective procedural text. Therefore, the teacher should go over the process text materials and encourage the pupils to learn more about procedure text.
Perception of Students about the Effectiveness of the Flipped Classroom and Technological Tools in the Learning of Mathematics

This quantitative research analyses the perception of students about the use of flipped classroom and technological tools in the functions unit considering the machine learning algorithms on linear regression, a decision tree and neural networks. This research proposes consulting YouTube videos about functions and use of the Desmos application in the teaching-learning process. The results of the linear regression indicate that the consultation with YouTube videos before the class and use of the Desmos application collaboratively during the class, and individually after the class, positively influence the teaching-learning process on the functions. Likewise, the decision tree identifies three predictive models. The neural network establishes how the activities of this pedagogical model influence the teaching-learning process. The implications of this research suggest that universities update their courses and carry out creative school activities outside and inside the classroom through flipped classroom. Finally, the flipped classroom facilitates the active role of the students during the learning process, promotes the construction of new educational virtual spaces and allows for improving the educational process through the incorporation of technological tools before, after and during face-to-face sessions.
Music as a tool of intercultural education for future teachers

The article deals with the problems of intercultural education of future teachers in the higher education system of Moldova through musical art. The author made a brief analysis of the state of intercultural education in the republic. Some methodological directions of the formation of intercultural competencies of students in the study of the discipline "Methods of musical education at school" are outlined. The key educational technologies, forms and methods of classroom and independent activities of students are identified, and criteria for evaluating/self-evaluating the results of individual works in the course of preparing a teacher for intercultural activities in a modern school are developed.
Methodological aspects of developing calligraphic writing of numbers in first grade students

The formation of the concept of number is based on: knowledge and use in writing of specific graphic symbols used to write numbers. Number writing is a higher stage in the abstraction process. Writing numbers often requires psychological difficulties for the child, some even more difficult than writing the first signs of the alphabet. The number represents the sign the graphic sign of the number when writing which is necessary the close connection between: the numerical concept, the verbal expression and the graphic sign.
Aspects for training the skills of primary school students to identify possibilities of overcoming mistakes by appealing trusters

This article clarifies some scientific, normative and methodological aspects of training students' abilities to identify opportunities to overcome mistakes, by appealing to trusted people (discipline "Personal Development", class III).
The importance of the games in the pupil’s education in Primary School

One of the many current issues of primary education consists in finding some optimal methods of active thinking development. The didactic games provide a favorable framework for consolidating the skills of intellectual work and for active learning, the participation at them stimulating both the learning and creativity of pupils. An increasing number of psychologists and teachers assert that any person has creative potential. The game can be used in forming all creative factors at all educational objectives. With the aid of the game it would be discovered the field in which the child has the most prominent skills, which would be encouraged and fostered. The game provides means with which the teacher can help the small pupils to learn profound knowledge in easier and more pleasant ways. When skillfully handled, the games bring an important contribution in preparing the pupils for life.
Descriptive feedback in the context of developing selfassessment capacity in primary school students

In this article, some main ideas are reviewed with reference to use descriptive feedback in the process of forming the self-assessment skills of primary school students. It presents the ways to achieve descriptive feedback (oral and written), the criteria of a valid feedback and self-assessment, the principles of a successful feedback.
Designing an Adaptive Instructional System for Financial Literacy Training

Adaptive instructional systems (AIS) provide instruction tailored to an individual’s abilities and/or needs to meet their educational goal. AISs have been shown to improve learning and performance outcomes and reduce time in training relative to traditional approaches. Typical AISs that are documented in training and education research involve use cases in which the educational objective is to maximize a learner’s understanding of a topic or performance on a task and employ different instructional techniques based on the learner’s performance during training. This paper aims to explore another method of adaptation to promote adult learning or workplace training where it may be more relevant to focus interventions that personalize content for learners. Personalization can help learners find information they need quickly and is theorized to increase motivation to learn by having content more directly related to a learner’s personal experience. Using financial literacy as a use case, we discuss how we used this personalization approach to design a mobile-based AIS to train U.S. service members about personal finance topics.
Visual literacy within art education in primary school

Nowadays the visual literacy became an important indicator for many areas of social activity. It enlarges traditional semnification of literacy and is recognized as necessary for surveillance and communication in modern era. The discipline of plastic education from primary school suggests checking of visual education for confirming the visual literacy. The ability of understating, exploring, interpretating and aesthetical summarizing of the visual images in this area can be obtained by activities of interaction with the medium natural, medium vital and that of art.
Efficiency of teachers in the institutions of early education

The article addresses the issue of teacher efficiency in general but also the effectiveness of teachers in early education, its key elements, the role of personal qualities, but also professional skills to increase the efficiency of teachers. Some key elements of teacher efficiency are proposed, by arguing the relationship: personal efficiency-professional efficiency.
The issue of capitalizing of didactic technologies in the formation of text elaboration competence at primary school students

In this article we addressed the issue of capitalizing of didactic technologies in the formation of text elaboration competence at primary school students. The results of the investigation confirm that all teachers use information technologies (digital writing tools, e-mail, to share ideas and request suggestions from students, and digital assessment technologies) to form text-writing skills. Most teachers argue that the exercise method is one of the most effective methods to train students in primary school writing skills. In conclusion, we mention that the implementation of didactic technologies contributes to the efficiency of the formation of the competence of the text elaboration at the students of the primary level of education.
Enabling Sustainable Development Through Artificial Intelligence-Based Surveillance System on Cloud Platform

AI-based surveillance can assist in better managing staggered and irregular work schedules by seamlessly identifying which employees are supposed to be in particular areas at certain times. This is important given that 98% of IT leaders are concerned about security challenges related to a hybrid workforce. Nowadays with the help of artificial intelligence; a video management system (VMS) can be trained to recognize VIPs, authorized personnel, and visitors. This may ease up the entering process for these individuals. But these systems have heavy equipment, let alone the requirement of a separate server room for storage. Therefore, this research paper highlights the need to build a compact, modular and robust security surveillance system based on Artificial Intelligence and Cloud Infrastructure. The proposed system is equipped with Artificial Intelligence and is going to detect both the intruder as well as the vulnerable zones within the facility. The entire system runs on a cloud platform with all the IOT devices working in-sync.
Rough Set Method for Determining Customer Satisfaction at Pdam Tirtanadi Medan City

It is very important to evaluate customer satisfaction as an effort to see the level of performance of PDAM Tirtanadi, Medan City. With this research was carried out to determine the level of customer satisfaction at PDAM Tirtanadi, Medan City using data mining. The research method used is an analytical method with a structured approach which is complete with the tools and techniques needed in the system so that the analysis results of the system being developed produce a system whose structure can be defined well and clearly. The main goal of rough set analysis is to synthesize conceptual approaches from the data obtained. This research aims to determine the level of customer satisfaction of PDAM Tirtanadi Medan City so that it can help PDAM to better understand the complaints of people who use PDAM Tirtanadi Medan City services.