Reviewerly/exHarmony huggingface dataset:
Development of Basic Finger Shapes Indonesian Traditional Dance Application Using Color-Based Hand Gesture Recognition

UNESCO stated that Indonesian traditional dance is a world cultural heritage that must be preserved and maintained. Efforts made by the government to preserve traditional dance are still not successful. Research shows that students have difficulty in learning traditional Indonesian dance exercises. Therefore, this study develops a solution that focuses on the difficulty of learning the basic finger postures in traditional Indonesian dances. This is important because fingers are instruments in dancing that have meaningful forms, such as Closed Urang Chopsticks, Nyempurit, Ngruji, Open Urang Chopsticks, Ke-pelan, Baya Mangap, and Ngithing. Learning the practice of basic finger postures aims to provide an independent learning experience through repetitive movements to strengthen or strengthen. This research has succeeded in making a real-time Color-Based Hand Gesture Recognition application for reliable Android devices. This is evidenced by applications that can function well in test scenarios with varying lighting and background conditions. Finally, students can learn the hand gestures of traditional Indonesian dances independently with ease. In addition, the application of the results of this research also contributes to becoming a learning medium in the current era of Blended Learning. Suggestions for future research are to increase the accuracy of Nyempurit and Ngithing attitudes.
Mathematical modelling and analysis of Kidnapping dynamics

The problem of kidnapping as a social menace to a society is increasing in some African countries such as Nigeria. We therefore proposed a new deterministic mathematical model for the dynamics of Kidnapping in a community. This menace is considered like a two strains communicable disease with kidnapping propagation mission by kidnappers as one strain and adoption mission for kidnapped victims as the other strain to assess the impact of super-infection. The model exhibits four equilibrium points each of which is unique and asymptotically stable both locally and globally under certain conditions. We obtain the kidnapping propagation number where is the propagation number associated with strain . Another important threshold parameters associated with respective strains 1 and 2 are and . Indeed, we show that at most one strain invades the population if one of these parameters is less than unity. while the two strains coexist at endemic state when both and are greater than unity. The global stability results of the model equilibria are established by numerical simulations. This simulations results indicate that the super-infection destabilizes the coexistence equilibrium.
Sosialisasi Pembuatan Media Pembelajaran Problem Based Learning (PBL) untuk Meningkatkan Kualitas Pembelajaran Guru SD Negeri 057761 Kwala Gebang

Preparing a golden generation for the future that can compete in the progress of the times can be done through good education. So that education is a forum for students to be able to develop all the skills they have. As time progresses, technological progress also develops. The rapid development of technology also has an impact on the world of education. Learning activities cannot be separated from methods, models, teaching aids and also media. Teachers can use learning media as a means of conveying knowledge to their students.
Using Digital Literacy Components to Develop ESL Learners’ Digital Mastery

The capacity to locate, assess, and communicate information via keyboards or digital media platforms is known as digital literacy. Utilizing information and communication technology to produce, assess, and distribute information requires a combination of technical and cognitive skills. Some ESL learners are still struggling when they are using the media online to search for articles and journals. In addition, there are still a lot of students that are unsure about how to use digital technology for their education. ESL learners must be proactive and digitally knowledgeable in this age of technology to successfully choose and organize their search results. Without these digital abilities, ESL Malaysian students would not be able to utilize a variety of ICT platforms for information access and processing for academic needs, as well as subsequently for career needs, specifically to fulfil the demands of the Industrial Revolution 4.0 (IR 4.0). This study explores the development of digital mastery using the digital literacy components. The study employed a survey research design. An online questionnaire was distributed to ESL learners in a selected university. A cluster sampling was used in selecting the samples. A sample of 186 university students were involved in this study. Descriptive and inferential statistics were used to analyze the quantitative data collected. Data was analyzed using SPSS version 27 for the questionnaire. In brief, the study contributes to a new model related to digital mastery for ESL students in higher education.
Microfacies analysis and depositional environment of Shiranish Formation in Selected Sections, Kurdistan Region, NE Iraq

Shiranish Formation in both Smaquli and Rawanduz sections is composed of an alternation of marly limestones, limestone and marl beds with fissile shale beds. Depend on color, lithology and other sedimentological criteria during field observations of the studied sections, the Shiranish Formation is divided lithologically into lower, middle and upper units. Planktonic Foraminiferal Lime Mudstone Microfacies (Shf1), Lime Wackestone (Shf2) and Planktonic Foraminiferal Lime Packstone Microfacies (Shf3) have been defined as three distinct microfacies with four submicrofacies ((Keeled Planktonic Foraminiferal Lime Wackestone submicrofacies (Shf2b), Globular Chamber Planktonic Foraminiferal Lime Wackestone submicrofacies (Shf2a), Bioclastic Lime Wackestone submicrofacies (Shf2c), Planktonic Foraminiferal Lime Wackestone submicrofacies (Shf2d)). The major microfacies in both sections was lime wackestone which is dominated in middle and upper units in both sections. Sedimentological and paleontological evidences suggest that the Formation was deposited in the outer shelf setting and progressed to the upper bathyal setting, in addition to that the microfacies changed from packstone to mudstone meaning deeping upward sequence.
A CRITICAL ANALYSIS AND REVIEW OF THE CONTROLLER PLACEMENT PROBLEM IN 5G SDN SECURED NETWORKS. OPEN ISSUES AND POSSIBLE SOLUTIONS

This paper attempts a critical analysis of the Controller Placement Problem (CPP) in Software-Defined Networking (SDN) environments, identifies open issues and exploring potential solutions. The strategies to solve the CPP are examined aiming to enhance network performance, scalability, and resilience. SDN is a powerful technology used more and more in different networks. In particular the SDN control is a strong candidate proposed in 5G architectures. This study considers various aspects of CPP, including latency, reliability, and effective load distribution, which are also important in the context of 5G networks. The analysis reviews existing literature, revealing gaps in current strategies, particularly in addressing the dynamic nature of 5G architectures. Special attention is given to the multi-Controller contexts encountered in large networks, where Multi-controller Placement Problem (MCPP) emerges. This overview not only underscores the criticality of CPP in 5G SDN but also outlines some future research directions by our original proposal for a generic architecture for dynamic optimization in CPP.
Effects of Laughter Yoga on Premenstrual Symptoms.

Premenstrual syndrome (PMS) is associated with a group of emotional, behavioral, and somatic symptoms that occur during the menstrual cycle. Laughter yoga involves a combination of laughter exercises and breathing techniques derived from more traditional yoga practice. No previous studies have examined the effects of laughter yoga on the symptoms of PMS.The study intended to assess the effectiveness of laughter yoga in coping with the premenstrual symptoms of women.The research team performed a pretest and posttest, quasi-experimental study.The study took place in the nursing and midwifery departments at Marmara University, a state university located in Istanbul, Turkey.Participants were 80 female students in those departments at the university between February 2019 and May 2020 who had PMS.The research team divided participants into two groups based on their departments: (1) an intervention group, the laughter yoga group, with 32 participants who took part in a twice-weekly laughter yoga program that included a weekly 30-min group session consisting of laughter and deep breathing, and (2) a control group with 48 participants.The research team collected the data using the Demographic and Descriptive Information Form (DDIF), Premenstrual Syndrome Symptom Scale (PMSS), and Visual Analogue Scale (VAS).Between baseline and postintervention, the laughter yoga group's mean scores for the PMSS subdimensions depressive affection (P = .00), anxiety (P = .04), fatigue (P = .00), irritability (P = .01), depressive thoughts (P = .03), pain (P = .002), changes in sleep (P = .004), and bloating (P = .001) significantly decreased. The laughter yoga group's scores for fatigue (P = .03) and pain (P = .001) were significantly lower than those of the control group postintervention.Laughter yoga is a noninvasive complementary therapy that clinicians can use to reduce the PMS symptoms.
Foreword

Governments, businesses, and individuals worldwide continue to face significant threats from cyber security breaches. The demand for cyber security professionals has grown substantially in recent years, and this trend is expected to continue, resulting in labour shortages in several countries. The first step in addressing the scarcity of skilled workers in the cyber security sector is to understand the supply and demand dynamics of cyber security skills. Governments and organisations can utilise this information to pinpoint vulnerabilities and determine areas requiring additional resources. From the demand side, analysing job postings can help identify trends in demand for cyber security professionals and the skills needed to strengthen organisations' cyber security. Simultaneously, studying cyber security education and training programs offers insights into the evolving development of the cyber security workforce, shedding light on potential mismatches between supply and demand.
Regional Clustering Based on Types of Non-Communicable Diseases Using k-Means Algorithm

Noncommunicable diseases (NCDs) have become a global threat to public health, necessitating a comprehensive understanding of their geographic and epidemiological distribution in order to devise appropriate interventions. The objective of this study is to clustering areas of Banten Province based on NCDS profiles using the unsupervised learning technique. The method used in this study is the k-means algorithm for grouping types of non-communicable diseases based on region. The processing and normalisation of NCDS prevalence data from various health sources preceded cluster analysis using the k-means clustering algorithm. This research is categorised into two scenarios: the first involves the clustering of data obtained from outlier analysis, while the second scenario excludes any outliers. The objective is to observe disparities in regional clustering outcomes by categorising non-communicable diseases according to these two scenarios. The silhouette index is used to determine the validity of cluster results. These findings are analysed in depth to determine the geographic and socioeconomic patterns associated with each cluster's NCDS profile. Based on the mean silhouette index value of 0.812, the results indicate that the sum of k = 2 in the k-means algorithm is the optimal cluster result in this case. Five non-communicable diseases, namely diabetes, hypertension, obesity, stroke, and cataracts, necessitate significant focus in the first cluster (C1), where 202 regions were grouped. Six regions belong to the second cluster (C2), which includes areas that are not only susceptible to the five non-communicable diseases in cluster C1 but also to breast cancer, cervical cancer, heart disease, chronic obstructive pulmonary disease (COPD), and congenital deafness.
Urban Heat Island Literacy Among Geography Education Students of Universitas Muhammadiyah Surakarta

Geography Education students are expected to have literacy about the phenomena around them, one of which is Urban Heat Island (UHI) literacy. It is appropriate by the mission of Geography Education at the Muhammadiyah University of Surakarta (UMS) is to produce geography educators with a view on disaster mitigation. This study aims to determine the UHI literacy of students in 7th semester, Deparment Geography Education, Faculty of Teacher Training and Education, Universitas Muhammadiyah Surakarta. This research is a quantitative descriptive study with survey methods. The study using purposive random sampling of 80 respondents and as many as 54 collage students were selected as samples. The UHI literacy research instrument was developed based on the OECD's International Program for Student Assessment (PISA) in 1999. Based on the indicators in scientific literacy which are divided into three categories, the results are obtained: 1) Indicators of UHI's concepts show that high categories are middle class 20.4 % and the majority of students at a high level with 79.6%; 2) Indicators of UHI's processes obtained results with 1.8 % of students at a low level, 20.4 % of students at a medium level, and 78.8 % at a high level; 3) UHI's situation indicators showed that the high category was 93% and moderate was 7%. The conclusion shows that the UHI literacy of students is relatively high, indicating that curriculum based on disaster insight has been doing well, but further research is needed on other disaster insights and analysis of factors which affect the results above.Keywords: Urban Heat Island, Urban Heat Island Literacy, Curriculum
Expert System for Diagnosing Corn Plant Diseases Using the Web-Based Certainty Factor Method

In the process of corn plant growth, it often faces the threat of various diseases that can hinder optimal growth. Dealing with this issue often requires the presence of a plant expert, such as a field agricultural extension officer. However, limitations in the human resources of agricultural extension officers, time constraints, and geographical distances often make it difficult for farmers to get direct assistance from experts. To overcome these constraints, a system capable of addressing issues related to corn plant diseases, similar to the role of an expert, is needed. In this study, the Certainty Factor method is employed, suitable for an expert system that measures the level of uncertainty, and through testing with 28 sample data cases, the accuracy level of this system reaches 90%.
Perbandingan Algoritma Winnowing dan Algoritma Rabin-Karp pada Aplikasi Pendeteksi Kesamaan Dokumen Skripsi

Plagiarism is often found in the academic world and is considered a serious violation because it involves the appropriation of ideas, opinions, or writings of others. A thesis is the final work of a student that must meet scientific standards and be tailored to the field of study. It is important to check the similarity of the thesis using a web-based sistem to prevent plagiarism and ensure academic integrity. This sistem will be developed as a web-based platform with the aim of comparing the Winnowing algorithm and the Rabin-Karp algorithm in checking the similarity of thesis/final project texts with existing thesis data. In principle, both methods involve searching for strings using hashing functions to compare the sought string (m) with the compared string (n) by comparing the results of the hashing function used. However, the Winnowing algorithm differs in that it does not use all hash values from each formed set of grams. The hash values formed in the previous stage will be divided into a window of size (w). In this research, the sistem testing uses data from Computer Engineering students at Halu Oleo University to facilitate checking the plagiarism level of theses using the Rabin-Karp and Winnowing algorithms. In this study, the Rabin-Karp and Winnowing algorithms have been implemented successfully in the plagiarism checking sistem for students' theses. The test results for the comparison of the Winnowing and Rabin-Karp algorithms in terms of processing time show that the Rabin-Karp algorithm takes 1.509 seconds, while the Winnowing algorithm takes 1.508 seconds. Subsequent testing using Normalized Mean Absolute Error (NMAE) reveals that the Rabin-Karp algorithm has an absolute error value of 0.1829, while the Winnowing algorithm has a value of 0.0194. Therefore, based on the NMAE test, the Winnowing algorithm performs better than the Rabin-Karp algorithm.
Application of scientific and technical means in criminal proceedings in the Republic of Kazakhstan

Relevance. The relevance of the study stems from the fact that the rapid development of new technologies and their introduction into all spheres of social life opens up great prospects for the use of scientific and technological progress in criminal proceedings to ensure full and transparent investigation of various types of crime. Purpose. The purpose of the study is to provide a comprehensive and in-depth examination of the various scientific and technical tools in criminal proceedings, to analyze the effectiveness and expediency of the use of certain technical tools, to study the experience of other countries and to carry out a comparative analysis. Methodology. The formal-legal method led the way, as it enabled a consistent study of the various new technologies used in criminal proceedings and the study of the legal provisions governing the use of such tools. Results. The outcome of the research is a comprehensive study of the most popular scientific and technological means used at all stages of criminal proceedings and by all law enforcement agencies; negative and positive aspects of the use of certain types of scientific and technological means in investigation and prosecution were examined, the experience of using the latest technologies in other countries was examined and a comparative legal analysis was carried out. In addition, the legal framework, which sets out the basic provisions for the use of technical means in the investigation of crimes in different countries, was examined. Conclusions. The practical significance of the research lies in the fact that understanding the specifics of the application of scientific and technical means will help to use them more effectively and reasonably in the process of criminal investigation and court proceedings.
Heat Transfer-Inspired Network for Image Super-Resolution Reconstruction

Image super-resolution (SR) is a critical image preprocessing task for many applications. How to recover features as accurately as possible is the focus of SR algorithms. Most existing SR methods tend to guide the image reconstruction process with gradient maps, frequency perception modules, etc. and improve the quality of recovered images from the perspective of enhancing edges, but rarely optimize the neural network structure from the system level. In this article, we conduct an in- depth exploration for the inner nature of the SR network structure. In light of the consistency between thermal particles in the thermal field and pixels in the image domain, we propose a novel heat-transfer-inspired network (HTI-Net) for image SR reconstruction based on the theoretical basis of heat transfer. With the finite difference theory, we use a second-order mixed-difference equation to redesign the residual network (ResNet), which can fully integrate multiple information to achieve better feature reuse. In addition, according to the thermal conduction differential equation (TCDE) in the thermal field, the pixel value flow equation (PVFE) in the image domain is derived to mine deep potential feature information. The experimental results on multiple standard databases demonstrate that the proposed HTI-Net has superior edge detail reconstruction effect and parameter performance compared with the existing SR methods. The experimental results on the microscope chip image (MCI) database consisting of realistic low-resolution (LR) and high-resolution (HR) images show that the proposed HTI-Net for image SR reconstruction can improve the effectiveness of the hardware Trojan detection system.
Prompting Is All You Need: Automated Android Bug Replay with Large Language Models

Bug reports are vital for software maintenance that allow users to inform developers of the problems encountered while using the software. As such, researchers have committed considerable resources toward automating bug replay to expedite the process of software maintenance. Nonetheless, the success of current automated approaches is largely dictated by the characteristics and quality of bug reports, as they are constrained by the limitations of manually-crafted patterns and pre-defined vocabulary lists. Inspired by the success of Large Language Models (LLMs) in natural language understanding, we propose AdbGPT, a new lightweight approach to automatically reproduce the bugs from bug reports through prompt engineering, without any training and hard-coding effort. AdbGPT leverages few-shot learning and chain-of-thought reasoning to elicit human knowledge and logical reasoning from LLMs to accomplish the bug replay in a manner similar to a developer. Our evaluations demonstrate the effectiveness and efficiency of our AdbGPT to reproduce 81.3% of bug reports in 253.6 seconds, outperforming the state-of-the-art baselines and ablation studies. We also conduct a small-scale user study to confirm the usefulness of AdbGPT in enhancing developers' bug replay capabilities.
Markov Subsampling Based on Huber Criterion

Subsampling is an important technique to tackle the computational challenges brought by big data. Many subsampling procedures fall within the framework of importance sampling, which assigns high sampling probabilities to the samples appearing to have big impacts. When the noise level is high, those sampling procedures tend to pick many outliers and thus often do not perform satisfactorily in practice. To tackle this issue, we design a new Markov subsampling strategy based on Huber criterion (HMS) to construct an informative subset from the noisy full data; the constructed subset then serves as refined working data for efficient processing. HMS is built upon a Metropolis-Hasting procedure, where the inclusion probability of each sampling unit is determined using the Huber criterion to prevent over scoring the outliers. Under mild conditions, we show that the estimator based on the subsamples selected by HMS is statistically consistent with a sub-Gaussian deviation bound. The promising performance of HMS is demonstrated by extensive studies on large-scale simulations and real data examples.