Reviewerly/exHarmony huggingface dataset:
The Implementation of Reading Aloud Strategy to Develop Student Skill Responding to Expression of Giving Good and Bad News

Speaking skills are a very important aspect of learning English to establish good communication. However, many students still need help expressing what they want to convey, be it ideas, ideas in a reading, or opinions when communicating, because of a lack of confidence from students. Thus, this study aims to improve students' speaking skills and to find out the factors and causes of students' difficulties in understanding reading by applying the learning method of reading aloud in learning text reports. This research was conducted at SMKN 1 SOREANG class X-TKJ (Network Computer Engineering) 1 with 36 participants. This research uses qualitative methods with a Classroom Action research approach. Data collection techniques in this study used three techniques, namely, Instruments: observations, field notes, and interviews. Based on the results of the study, the researcher can conclude that the application of the aloud reading learning method carried out by the teacher can run smoothly because, by the procedure, application of reading aloud, students can follow the teacher's direction well. In this learning process, students are very enthusiastic, and this encourages student learning motivation, especially in reading English texts; besides that, students can improve significantly in student speaking skills In several aspects it has so that students can be responsive when answering questions related to the reading that the teacher gives quickly. Therefore, based on the results of the research, some of the consequences of students' difficulties in speaking skills can be overcome by applying the method of learning to read aloud by increasing aspects of speaking skills in students, namely: 1) Fluency, 2) Pronunciation; 3) Intonation; 4) Accuracy.
Mapping Hoaxes, Disinformation, and Hate Speeches in Indonesia

Hoaxes and disinformation remain significant challenges for Indonesians in this era of information proliferation. A staggering number of approximately 2,093 hoaxes circulate within the society each year, averaging around 175 hoaxes per month.&#x0D; Recognizing the urgency, the government has taken a proactive stance in the battle against disinformation, hoaxes, and hate speeches within society. Operating under the East Java Department of Communication and Information, they have established an information verification platform accessible at https://klinikhoaks.jatimprov.go.id/. This platform empowers individuals to actively ask for verification of the information they encounter through social media or other online sources.&#x0D; On a monthly basis, the team engages in the verification of a minimum of fifty pieces of information. These items originate from public requests and the team's independent searches across various publicly accessible information channels. The information being examined covers a wide range of aspects, including the specific problem at hand, information based on region, the categorical classification of the data, and the sources of dissemination media.&#x0D; Due to its inherent diversity, this study aims to comprehensively represent the verified information submissions on the website https://klinikhoaks.jatimprov.go.id/. It employs Krippendorff's content analysis framework; the research endeavours to cartographically delineate information categories, issue typologies, and media origins.&#x0D; The research population comprises a total of 331 information, simultaneously serving as the research sample. These data points encapsulate the entire information meticulously authenticated by East Java Department of Communication and Information, spanning the temporal interval from February to August 2023.&#x0D; Derived from the findings of this study, it becomes evident that the prevailing information disseminated within the society pertains predominantly to public figures, political matters, government affairs, and fraudulent activities. Concurrently, regarding information dissemination media, TikTok has emerged as a nascent source. However, platforms such as YouTube, WhatsApp, and Facebook are conduits for the most contentious information dissemination.
Elastic Network Regression Based on Sobol Sequence Initialized Lightning Attachment Procedure Optimization

Linear regression is an important machine learning (ML) based regression method in the fields of engineering and finance. In linear regression algorithm system, there are usually two methods to improve the matrix irreversibility problem in the process of solving parameters caused by the collinearity phenomenon: one is ridge regression using L2 regularization method; the other is lasso regression using L1 regularization method. However, the errors of L2 regularization method are easily to be amplified and reduced, while L1 regularization method has non differentiable points. In order to solve such problems, L1 regularization and L2 regularization are generally combined in a typical linear regression method called elastic network, and subgradient descent (SubGD) and coordinate gradient descent (CD) are generally used. Nevertheless, SubGD and CD fall into the local minimum trap easily. To overcome this shortcoming, in this paper, a Sobol sequence initialized lightning attachment procedure optimization (SSLAPO) algorithm has been proposed and has been combined with elastic network regression, and via numerical experiment, its effectiveness has been verified.
Optimal Transport-Embedded Neural Network for Fairness Transfer Problem

Research on neuromorphic computing has gained popularity in recent years. In particular, regularized embedded neural systems have been applied in several significant real-world situations, such as recommendation systems and transfer learning. This paper deals with the fairness transfer learning problem, which has been insufficiently explored. In fairness transfer settings, the source domain has limit-tagged training samples, which may lead to performance degradation in the target domain. To solve such problems, a linear data-augmentation-based optimal transport-embedded neural network is proposed in this paper. It can augment the source samples to make the distribution of the source domain balanced and can align the source and target distributions simultaneously. Moreover, the distribution of the augmented data by mixup is limited to a certain bound that can avoid the abnormal samples generated. The effectiveness of the proposed method has been demonstrated in several transfer learning tests, including regression and classification. In 1-shot and 3-shot classification tasks on the Office dataset, our method’s accuracy is 4.8 and 3.9% better, respectively, than the second-best model. Additionally, our model’s performance is about 2–3 percentage points superior to the second-best model in the OfficeHome dataset. It is simple yet effective, making it perfect for low-power edge AI applications.
THE IMPORTANCE OF USE OF THE REGIONAL LANGUAGE MALAY DELI IN FORMAL EDUCATION IN MEDAN CITY

The aim is to hone regional language skills and develop students' personalities. It is our obligation as Indonesian citizens (WNI) to master and apply Indonesian in our daily lives properly and correctly, so that our regional languages maintain their authenticity. The aim of this research is to find out; 1) Understanding the language, 2) Indonesian language courses for students, 3) The importance of regional languages in formal education, 4) Aims and benefits of Indonesian language courses. So Indonesian is important to study in higher education, because Indonesian is a unifying language, a guide to the preparation and use of good and correct language in scientific communication, as well as to deepen the language in communication and to be preserved by native speakers.
Blockchain-based Clinical Trials: A Meta-Model Framework for Enhancing Security and Transparency with a Novel Algorithm

Clinical trials are crucial to medication research, but data security, transparency, and integrity issues often arise. Blockchain technology offers a decentralized, tamper-proof framework for clinical trial data management, promising to overcome these issues. Current blockchain-based clinical trial platforms lack scalability, interoperability, and integrity. A meta-model paradigm for blockchain-based clinical trial security and transparency addresses these constraints. The system employs a unique algorithm with smart contracts and consensus procedures to protect data privacy, reduce redundancy, and promote platform compatibility. The algorithm aims to maximize resource consumption and reduce computational overhead while ensuring security and trust. To improve security and transparency, we analyze the proposed meta-model framework utilizing performance, scalability, and security metrics and benchmarks. We observed that the meta-model framework and algorithm are efficient, scalable, and safe, laying the groundwork for future research. In particular, the framework can minimize clinical trial costs and time while improving data quality, traceability, and accountability. The suggested meta-model framework and algorithm can improve blockchain-based clinical trial security and transparency, making data management more trustworthy and efficient.
Scientific and Methodological Support of Professional Self-Determination of Schoolchildren In the Process of Teaching Geography: a Model and Tools

The main goal of this study is to study the problems of modern geographical education through the prism of professional self-determination of students. The content of geographical education is considered as a key component of professional self-determination. The use of geography teachers as methodological tools for project activities, educational excursions, professional tests, etc. is justified. The article focuses on the need to provide scientific and methodological support to geography teachers and improve their professional competence in the conditions of a continuous system of professional self-determination of young people. The authors present a model of scientific and methodological support for the professional self-determination of schoolchildren in the process of teaching geography, a model for organizing project activities of a career guidance nature in geographical education in the conditions of interaction between a pedagogical university, a school and a professional community, and consider a variant of thematic planning of a geography course with career guidance content.
Incremental Learning of Goal-Directed Actions in a Dynamic Environment by a Robot Using Active Inference

This study investigated how a physical robot can adapt goal-directed actions in dynamically changing environments, in real-time, using an active inference-based approach with incremental learning from human tutoring examples. Using our active inference-based model, while good generalization can be achieved with appropriate parameters, when faced with sudden, large changes in the environment, a human may have to intervene to correct actions of the robot in order to reach the goal, as a caregiver might guide the hands of a child performing an unfamiliar task. In order for the robot to learn from the human tutor, we propose a new scheme to accomplish incremental learning from these proprioceptive–exteroceptive experiences combined with mental rehearsal of past experiences. Our experimental results demonstrate that using only a few tutoring examples, the robot using our model was able to significantly improve its performance on new tasks without catastrophic forgetting of previously learned tasks.
A Comparative Study of Students’ Listening Skills Using Media; Song and Podcast

&lt;p align="center"&gt;&lt;strong&gt;Abstract&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;Listening skill is commonly used in daily activities. Nevertheless, there are a lot of students who still got difficulties when it comes to listening activity. One of the solution to solve listening problem is to use the existance of media, namely song and podcast to help students improving their listening comprehension. In this paper, researcher employed quantitative method with quasi-experimental design using two-group pretest-posttest. The aim of this research were: (1) to find out whether there was a significant difference in achievement of students’ listening skills after being taught by using song and those who were taught by using podcast, and (2) to find out which media that gave more significant effect in students’ listening skills. The data was analyzed by using Independent Sample t-test in SPSS 20. This paper showed that there was significant difference in achievement of students’ listening skills between the students who were taught by using song and those who were taught by using podcast. From the results of the data, teaching listening through podcast gave more significant effect to increase students’ listening skills.&lt;/p&gt;&lt;p class="abstrak" align="left"&gt;&lt;strong&gt;Keywords:&lt;/strong&gt; song, podcast, listening skills&lt;/p&gt;&lt;p class="abstrak" align="center"&gt;&lt;strong&gt;Abstrak &lt;/strong&gt;&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;em&gt;Keterampilan mendengarkan selalu digunakan dalam kegiatan sehari-hari. Meskipun demikian, masih banyak siswa yang mengalami kesulitan dalam kegiatan mendengarkan. Salah satu solusi untuk memecahkan masalah mendengarkan adalah dengan menggunakan media, yaitu lagu dan podcast untuk membantu siswa meningkatkan pemahaman mendengarkan mereka. Dalam penelitian ini peneliti menggunakan metode kuantitatif dengan desain eksperimen semu dengan membandingkan menggunakan two-group pretest-posttest. Tujuan dari penelitian ini adalah: (1) untuk mengetahui apakah ada perbedaan yang signifikan dalam pencapaian keterampilan mendengarkan siswa setelah diajar dengan menggunakan lagu dan mereka yang diajar dengan menggunakan podcast, dan (2) untuk mengetahui media apa yang memberikan pengaruh yang lebih signifikan dalam keterampilan mendengarkan siswa. Data dianalisis dengan menggunakan Independent Sample t-test di SPSS 20. Penelitian ini menunjukkan bahwa ada perbedaan yang signifikan dalam pencapaian keterampilan mendengarkan siswa antara siswa yang diajar dengan menggunakan lagu dan mereka yang diajar dengan menggunakan podcast. Dari hasil data tersebut, kegiatan mendengarkan melalui podcast memberikan pengaruh yang lebih signifikan terhadap peningkatan keterampilan mendengarkan siswa.&lt;/em&gt;&lt;/p&gt;&lt;p class="abstrak"&gt;&lt;strong&gt;&lt;em&gt;Kata Kunci: &lt;/em&gt;&lt;/strong&gt;&lt;em&gt;lagu&lt;/em&gt;&lt;em&gt;, &lt;/em&gt;&lt;em&gt;podcast&lt;/em&gt;&lt;em&gt;, &lt;/em&gt;&lt;em&gt;kemampuan mendengar&lt;/em&gt;&lt;em&gt;&lt;/em&gt;&lt;/p&gt;
Penerapan Media Gambar dalam Meningkatkan Kemampuan Membaca Siswa Sekolah Dasar

In carrying out the learning process in grade 1 elementary school, of course, there are problems, especially in reading skills, but these problems can be solved by means of a teacher's creativity. The purpose of this study was to find out the increase in students' reading skills after applying media images for grade 1 students of elementary school 007 Kotabaru Reteh, Keritang District. The method used by researchers is a qualitative and quantitative method with the type of classroom action research carried out in 3 cycles. The results obtained were that students' reading skills increased after applying learning media with pre-cycle values of 50.5%, cycle 1 57.9%, cycle 2 75.5% and cycle 3 88.9% so it can be concluded that reading ability can increased after applying media images to grade 1 elementary school students.
Analisis Implementasi Pembelajaran Tematik Berorientasi Multiple Intelegences di Kelas Rendah SD/MI

This research is motivated by the lack of understanding of educators on the intelligence of students. Referring to these problems, thematic learning based on multiple intelligences can develop various intelligences of students in learning. The role of educators is needed in implementing multiple intelligences-based thematic learning for elementary school students. Educators must realize the importance of learning by not only emphasizing one intelligence but also exploring the intelligences possessed by students. The purpose of the study was to analyze the extent to which elementary/MI low grade educators were able to apply thematic learning oriented to multiple intelligences. This research is library research, that is, using library resources to obtain research data on Research and development (R&D) development. The data sources used in this research are books, journals and internet sites related to the chosen topic. Data collection techniques in this study are descriptive and analysis. The data analysis technique in this literature research is analysis at the time of data collection, this is intended to better capture the essence or core of the focus of the research to be carried out through the sources collected and contained in the verbal linguistic formulation, this process is carried out aspect by aspect, in accordance with research map. The results of this study indicate that the application of thematic learning in elementary/MI low grades strongly supports the development of multiple intelligences (multiple intelligences) of students. This is corroborated by the data that the 9 intelligences possessed by students are applied to the theme books for grade 2 SD/MI Theme 1 “live in harmony” Subtheme 1 “live in harmony at home”.
Perancangan Iklan Layanan Masyarakat Untuk Mengurangi Kecanduan Game Pada Pelajar SMP

Abstract The influence of the game is so great for Junior High School students, in which games can create addiction for them. As a result, they cannot manage their time well, skip their classes, and oftenly disturbed while studying because they constantly think about games on and on. The main cause is likely because of the psychology of junior high school students that still cannot control what they want wisely. As a result, their performance in studying will certainly decrease, which is resulted in their failure in academics. If this phenomena continues, it will surely impact their future in negative way. Therefore, it is necessary for the media to help junior high school students to be aware about the importance of managing their time, as well as giving the understanding that play games is not bad but they should know the boundary. Keywords: Public Service Ads, Games, Junior High School Students.
Korean-Chinese Machine Translation Method Based on Independent Language Features

Currently, the mainstream approach for Korean-Chinese machine translation is to improve the performance of translation models by building upon existing deep learning models. However, there has been insufficient focus on leveraging the linguistic relationship between Korean and Chinese to enhance translation quality. This paper proposes an improvement method that uses the natural connection between the two languages-the Sino-Korean words. Firstly, we shorten the word vector distance of the Sino-Korean words in the semantic space to extract the independent language features of the Sino-Korean words. Secondly, we propose a fine-tuning model to solve mistranslation and translation ambiguity issues caused by 1:N Sino-Korean word pairs. Lastly, we add the coverage loss function to the machine translation model to reduce duplication of translation. This paper conducted experiments on the datasets SWRC and East Asia Daily. Compared with the baseline model, the score of Chinese-to-Korean translation on the SWRC and the East Asia Daily increased by 6.41 BLEU points and 4.09 BLEU points respectively; and the score of Korean-to-Chinese translation increased by 8.43 BLEU points and 4.13 BLEU points respectively.
Object-Oriented Techniques

For the last 30 years, object-oriented techniques have become the standard for software design and development. Since C++ fully supports OO programming, it is essential that you have a good understanding of OO techniques in order to solve many of the challenges presented by options and derivatives programming.
An Implementation of Man-in-the-Browser Attack and Defense Method in the Google Chrome Browser

The web browsers (e.g., Google Chrome, Internet Explorer and Firefox) are application softwares for accessing the world wide web. In recent years, extensions which are software programs built on web technologies such as HTML, CSS, and JavaScript are applied in order to enable users to customize the browsing experience and improve the functionality of browsers. Because browser extensions can access sensitive data, such as user credentials, there have been instances of malware (malicious browser extensions). In this paper, a malicious browser extension to Chrome web browser is implemented which can obtain the user input and send them to the remote malicious database. A defense method for this attack based on monitoring HTTP POST method in the Google Chrome browser environment is implemented.
Facies Model Generation with Deep Variational Autoencoders

Summary The ability to generate geologically plausible subsurface models is critical for many applications related to energy resources such as hydrocarbon and geothermal reservoirs and to geo-storage of carbon dioxide and hydrogen. Geostatistical methods have been the preferable tools to create numerical representations of the subsurface due to their ability to integrate data with different spatial resolutions while accounting for uncertainties. However, these methods might be computationally expensive and might have limitations to account for scenarios not sampled by the existing data. The recent advances in deep learning open new ways to overcome some of these limitations. We show herein, the applicability of a Variational Autoencoder (VAE) for the reconstruction of subsurface models in the presence and absence of direct observations. The VAE learn the spatial structure of the available data and allow generating multiple subsurface models. The application examples show the ability of VAE to predict the spatial distribution of electrical resistivity for the conditioning and unconditional cases with similar performance of geostatistical modelling tools.
Effective Facemask Detection Using a Few Learning-Based Recognition Methods

Global healthcare systems are effectively dealing with the pandemic arising out of COVID-19 virus yet there are requirements to formulate appropriate risk minimization methods. In the absence of effective medical resources, certain alternatives are recommended to stem the infection. Mask wearing is regarded to be a non-pharmaceutical intervention measure to prevent rapid spread of the virus from an infected individual. As part of measures to ensure wearing of marks in public places, certain methods of monitoring are being developed. Majority of these are based on learning-aided pattern recognition methods. This paper discusses the design of a few learning-based methods like Artificial Neural Network (ANN), Convolutional Neural Network (CNN) and Support Vector Machine (SVM) and also includes discussion on the performance of these methods which are configured and trained to find the best suitable approach for checking mask wearing in a real-time situation. It is observed that the proposed technique based on VGG-16 CNN achieves high accuracy (99.0%) during the testing phase but when implemented with SVM during training, similar results are obtained.