Reviewerly/exHarmony huggingface dataset:
Ballet Form Training Based on MediaPipe Body Posture Monitoring

Abstract People are increasingly turning to the cloud in the context of “healthy China” to engage in online exercise. The use of artificial intelligence technology to address broad population health-related challenges has become increasingly important as information technology has matured. The MediaPipe artificial intelligence framework, which Google recently released, is used in this article to optimize video feedback and support the “cloud movement” of widespread home ballet instruction in order to examine the effects of digital technology-enabled ballet training on the general improvement of physical health. Based on the experiment’s findings, trainers can use MediaPipe video feedback as an additional method of “cloud movement” training in public homes. This allows trainers to visually reflect on any issues that arise during the exercise process and to promptly modify training according to motion monitoring in order to reduce the risk of physical injury brought on by improper motion training. It is possible to envision a day in the future when video feedback built on the MediaPipe architecture would combine artificial intelligence with exercise training to achieve training objectives that enhance the accuracy of trainers’ motions and enhance physical balance.
THE STUDY OF STUDENT PARAGRAPH DEVELOPMENT AT SHIPBUILDING INSTITUTE OF POLYTECHNIC SURABAYA BY ENGAGING CONTROLLING IDEA IN WRITING PROCESS

Building a single paragraph needs techniques and strategies in order to arrange the ideas in a clear and logical order. This research aimed to gain the ideas development created by polytechnic students in building the paragraph for their writing process. This study was descriptive qualitative supported by the quantitative data to find out the ways how the students developed the ideas and arranged them in a good single paragraph. There were 24 students who were taken as the objects of research. The data were collected by purposive random sampling to get the qualitative data and the textual analysis was used to get the deeper interpretation of the data. The result showed that the students developed the single paragraph by stating the topic sentence in the beginning of their writing completed by the part of speech with adjective(70,8%) to control the ideas. It could be concluded that engaging the controlling idea in a topic sentence could make the students develop the ideas easily. Hopefully, this research could portrait the phenomenon which was useful for the lecturer to choose the effective strategies based on the students need in the skill of writing.
CamDiff: Camouflage Image Augmentation via Diffusion

The burgeoning field of Camouflaged Object Detection (COD) seeks to identify objects that blend into their surroundings. Despite the impressive performance of recent learning-based models, their robustness is limited, as existing methods may misclassify salient objects as camouflaged ones, despite these contradictory characteristics. This limitation may stem from the lack of multi-pattern training images, leading to reduced robustness against salient objects. To overcome the scarcity of multi-pattern training images, we introduce CamDiff, a novel approach inspired by AI-Generated Content (AIGC). Specifically, we leverage a latent diffusion model to synthesize salient objects in camouflaged scenes, while using the zero-shot image classification ability of the Contrastive Language-Image Pre-training (CLIP) model to prevent synthesis failures and ensure that the synthesized objects align with the input prompt. Consequently, the synthesized image retains its original camouflage label while incorporating salient objects, yielding camouflaged scenes with richer characteristics. The results of user studies show that the salient objects in our synthesized scenes attract the user’s attention more; thus, such samples pose a greater challenge to the existing COD models. Our CamDiff enables flexible editing and effcient large-scale dataset generation at a low cost. It significantly enhances the training and testing phases of COD baselines, granting them robustness across diverse domains. Our newly generated datasets and source code are available at https://github.com/drlxj/CamDiff.
Developing English Learning Materials for Accounting Students: Language Challenges and Accounting Education

This study explores the relationship between language challenges and accounting education in the S1 AccountingProgram at Universitas Muhammadiyah Metro. Using a meticulous mixed-methods approach involving language assessments, surveys, and focus group discussions, the research examines students' perceptions of language barriers. The findings emphasize the role of tailored English learning materials in addressing these challenges, enhancing language proficiency, and boosting students' confidence in comprehending complex accounting content.Collaboration between language instructors and accounting experts is highlighted as a key factor in achieving effective integration. The study also underscores the broader relevance of this approach, aligning with the evolving demands of the global business landscape and improving students' employability. The study offers practical recommendations for institutions, students, educators, and researchers to address language challenges holistically and foster specialized discipline proficiency. By implementing these suggestions, stakeholders can bridge the language-discipline gap and cultivate graduates skilled not only in their chosen field but also in effective cross-disciplinary communication. Ultimately, this research contributes to the discourse on integrating language and specialized education, presenting practical avenues for implementation.
Incentive structures and their impact on the economic viability of academic and research institutions: a case-based methodological investigation

In the rapidly globalizing world characterized by increasing competitiveness in the academic and research sectors, the influence of incentive structures on the economic viability of institutions has gained prominence. This article proposes a comprehensive case-based methodological investigation to examine how various incentive mechanisms affect the economic standing of academic and research institutions in Kazakhstan. Drawing from the interdisciplinary fields of economics, management science, and sociology, we aim to delineate the causal linkages between incentive structures and institutional economics. The economic viability of academic and research institutions is increasingly subjected to scrutiny in contemporary discussions surrounding higher education and research funding paradigms. In a symbiotic relationship, incentive structures act as critical levers that can either augment or constrain the economic viability of these institutions. This interdisciplinary research article embarks on an empirical journey to explore the interconnections between incentive structures and economic outcomes within the academic and research institutions in Kazakhstan. The study employs a case-based methodological framework, focusing on both quantitative and qualitative data gathered from a representative sampling of institutions. Grounded in Institutional Economics, Transaction Cost Economics, and Social Capital Theory, the investigation seeks to dissect the underlying mechanisms that condition the efficacy of various types of incentives - monetary, social, and reputational - on the financial stability, operational efficiency, and overall economic performance of these institutions. The article aims to contribute to the extant literature by filling the current empirical void and providing actionable insights for policymakers, institutional administrators, and the academic community at large. The findings have far-reaching implications not only for Kazakhstan but also for similar emerging economies grappling with the challenges of fostering economically viable and globally competitive academic and research institutions.
ANALYSIS OF THE NEEDS FOR ENGLISH MATHEMATICS SUBJECTS USES ANDROID-BASED LEARNING MEDIA

The purpose of this research is to determine students' needs in learning media based on Android in Mathematics English lectures. The research method is quantitative with second-semester student research subjects. The instrument used in this study was a questionnaire or questionnaire, involving two indicators. The indicators for the need for facilities and learning style tendencies show that 100% of students have Android-based smartphones, and student interaction with smartphones leads to a presentation of 94.1%. It indicates that smartphone facilities are very much needed, mainly since only 29.4% of students use Android-based learning media. The questionnaire results from indicators of the tendency for student learning styles to prefer, with a percentage of 41.2% using words such as feel, touch, and hold, and 47.1% of students more easily remember things seen or read. What is done, 58% of students prefer to read than read, then 52.5% of students strongly agree, and 47.1% agree if Android-based learning media is developed. Based on the results of this study, it is necessary to establish Android-based learning media in the learning process. Results of Indicators of Facilities Needs for Android-Based Learning Media
Eksposur materi autentik di kelas Bahasa Inggris sebagai Bahasa Asing

Grammar rule-based learning is frequently emphasized in traditional English classes in Indonesian primary, middle, and high schools. The test-based education system creates classes that produce a type of English that does not appear to be spoken outside of the classroom. As a result, the students struggle to adjust to English by native speakers in the real world. Those who connect with native speakers must constantly alter their linguistic behavior in areas of language where suitable instruction was not provided. To address this phenomenon, it is important to build a self-created "English Environment" by exposing students to authentic material that is set at their natural level and interest, which will raise their sensitivity and proficiency in the target language. Authentic materials such as writing, essays, short stories, and song lyrics in realistic language can be used in class and English teachers should ideally use a variety of authentic materials in addition to English textbooks to stimulate the natural language learning process, allowing for effective English as a foreign language class. Thus, the article discusses how teachers can use authentic materials effectively in English as a foreign language classes and how authentic materials can help students learn the real context of English.
APPLYING WHATSAPP GROUP TO DEVELOP STUDENTS’ WRITING SKILL FOR JUNIOR HIGH SCHOOL STUDENTS

This reseach is aimed to improve Students Writing Ability through a Whatsapp Group and know how the classroom situation when the students practice their writing ability through the Whatsapp Group. It is a classroom action research undertaken at SMPN 8 Metro in 2020/2021 academic year. The subject of the study was 22 students of the eighth grade. It was completed in two cycles. The criteria of success put in this study, if the students have big interests and high motivation in writing practices through WhatsApp group and get a minimum standard of 60.4 score. The data yielded by conducting classical teaching activity, doing interviews, observations, and tests. The data were analyzed descriptively and simple statistically. The pre-test result showed that the average score gained by the students in the pre-cyclewas less than 60.4(78.12%).Only 5 students (21.88%) got 75 scores, otherwise 17 students (63.64%) were under the passing grade. Then, the students who got score ≥ 75 in post test of cycle 1 were 63.64% or 14 students while 36.36% or 8 students got score &lt; 75. Furthermore, in post test of cycle 2 showed that 85 % of the students got ≥ 75 scores. Furthermore, the classroom situation before the treatment was classified into low category with the mean score of 56.00 or . Then, the students’ activity after the treatment in cycle I increase significantly with the mean score 64. There were 16 active students (72.72%). The average of score yielded in cycle 2 was classified into high category with the mean score of 80 and the number of active students became 19 students (86.36%). Thus, it can be concluded that WhatsApp group is able to improve students’ writing ability. Therefore, it is recommended implemented by teachers in practicing English writing.
PROSPERITY AS REFLECTED IN FITZGERALD’S THE GREAT GATSBY

This study aims to shed light on the prosperous era that occurred in America during the 1920s, as depicted in F. Scott Fitzgerald's The Great Gatsby. In conducting this research, the writer uses a qualitative method in which the data are in the form of words and the writer is the key instrument. The sources are taken from the work itself and other relevant books supporting the analysis. The writer employs a mimetic approach to data analysis, which holds that literary work is a reflection and imitation of aspects of the universe. As a result of remaining neutral during World War I and the occurrence of migration, America can now concentrate on economic mobilization. Prosperity is marked by the rise of consumerism, business fortune, and residence, but it also has a negative impact on the American people in terms of the rise of a new way of life and the decline of morality, such as a proclivity for free life, alcoholism, and free sex.&#x0D; &#x0D;
AN ANALYSIS OF STUDENTS' SPEAKING ANXIETY IN AN EFL CLASS AT MUHAMMADIYAH UNIVERSITY OF METRO

This study aims to identify the fundamental causes of anxiety and create treatments to reduce it. This survey was done since a lot of pupils don't know what worries are or how to handle them. Using a qualitative technique, the researcher looked at and discussed the data on student anxiety. This study included 26 students from the sixth semester of the English Education Department at Muhammadiyah University of Metro. The researcher employed an interview, an FLCAS questionnaire created by Horwitz in 1986 that had been modified to fit the research focus, and an observation to gather data. According to the survey results, there are five levels of anxiety among students, ranging from low to high. The next step was to choose 10 students from the low anxiety and high anxiety groups for interviews to determine the reasons and treatments for anxiety. According to the study's findings, 15.3% of students had low anxiety, 3.84% of students had very low anxiety, 30.7% of students had moderate anxiety, 34.6% of students had very high anxiety, and 15.3% of students had severe anxiety. After analysing the data of the interviews, the study identified six traits that contributed to students' worry: poor English proficiency, misinterpretation anxiety, low self-esteem, evaluation anxiety, lack of preparation, and excessive test anxiety. Researcher also came up with a number of strategies that may be utilized to help students feel less anxious, including changing one's perspective, being well-prepared, practicing to boost one's confidence and English proficiency, and finally, being brave. Additionally, the researcher detailed the recommendations that other researches could have used. The next researchers should determine from various angles of the speaking anxiety, including the learning setting, the history of the students, and instructor insight.
The Impact Of English Language On The Existence Of Indonesian Language In The Age Of Globalization

Globalization is not only disseminating information and technology to develop the human life, but it also brings cultures with new languages which are then absorbed and utilized by people. Likewise, English has turned into an international language which is able to be mastered by various Indonesian people. However, the use of English in Indonesia is increasingly symptomatic and fades the Indonesian language. The phenomenon is unallowed since its dominance can damage the development of Indonesian language which makes its construction necessary. Thus, this research is expected to raise public awareness to uphold the Indonesian language amidst globalization.
The probability analysis of using programmable controllers in water distribution management in the Don Main Canal

Purpose: to analyze the possibilities of using programmable logic controllers (PLC) in water distribution management in the Don Main Canal. The work is an analytical study based on the principles of automation and optimization of water resources control. Discussion. The architecture of the control system, including programmable logic controllers, network modules and water level sensors in the main canal is discussed. The main attention is paid to justifying the use of PLC in the design and development of a water distribution control system, which allows control and regulate the water level in the channel using the upstream control scheme. The software offers possibility for monitoring water parameters, calculating optimal values and automatic adjustment of control signals. The advantages of using PLC in water distribution control system, including high flexibility, reliability and the possibility of easy integration with other systems are also analyzed. The methods of PLC setting, regulator optimization and energy management to achieve efficient and economical water resources management are described. The research confirms the effectiveness and applicability of using the programmable controllers in water distribution management system in the Don Main Canal. Conclusions: the results obtained make it possible to increase the efficiency of water resources use, reduce energy consumption and ensure stable control of water level in the irrigation canal.
3D Feature-Based Sampled-Data Visual Tracking*

3D feature-based Visual Servoing (VS) on the one hand shows attractive peculiarities, on the other hand it suffers from drawbacks related to the existence of local minima, which may affect the convergence character of the VS control loop. Furthermore, the performance of the visual tracking module may constitute a bottleneck enforcing severe constraints on the workspace and visual task execution speed. In this paper we introduce a novel sampled-data model of the 3D feature-based VS, and, in order to avoid drawbacks due to local minima, we plan the target reference trajectory in the feature space with the aim to constraint the feature error dynamics to remain close to the desired equilibrium point. Then, we propose a novel feature generation based on the homography provided by a template matching algorithm based on the Zero mean Normalized Cross Correlation (ZNCC) and the design of a visual tracking scheme by resorting to the Extended Kalman Filter (EKF) and Lyapunov direct method, which explicitly takes into account the camera velocity limits, while ensuring stability.
Common Encryption Key Generation and Secure Communication Using PDE Chaotic Synchronization

This paper deals with the topic related the application of observer for a 2 × 2 hyperbolic system to secure communication. The hyperbolic system has a form in which a nonlocal integral term is included in the boundary condition that causes chaotic phenomena. A weight function included in the nonlocal integral term serves as a common encryption key. In the system of this paper, it is easy to redesign the observer when changing the common encryption key. Taking advantage of this feature, the common encryption key is generated using another chaos synchronization. With such a system configuration, it is possible to make the previous secure communication system (Sano and Wakaiki, 2022) more secure. Finally, an application example to image encryption/decryption is shown, and the numerical simulation result is given.
Clustering of Linear Time-Invariant Systems: A Bayesian Nonparametric Method

In this paper, we consider the clustering of linear time-invariant (LTI) systems according to the similarity of dynamics. There are two main difficulties for clustering of LTI systems: one is to determine the labels of LTI systems and the number of clusters, and another one is to build models of LTI systems. To address these two difficulties simultaneously, a Bayesian nonparametric method based on Dirichlet process mixture models (DPMM) and kernel-based regularization method is proposed. To be specific, the Dirichlet process mixtures of Bayesian linear regression models (DPM-BLRM) is proposed to determine the label of each LTI system according to the probability that the system belongs to each cluster, and adapt the number of clusters to the complexity of data. In addition, DPM-BLRM incorporates the prior knowledge of LTI systems to deal with the possible large variance of model parameters estimation when the collected data is short or has low signal-to-noise ratio, where the carrier of prior knowledge is kernel matrix. Then Markov chain Monte Carlo (MCMC) method is used for Bayesian inference for the DPM-BLRM. The simulation results illustrate the efficiency of the proposed method.
The Effect of Strategic Planning on the Success of e-learning: Al-Nisour University College as a Case Study

This research aims at identifying the effect of strategic planning with the dimensions (strategic orientation, strategic analysis, and strategic choice) within e-learning and the dimensions (personal dimensions, environmental dimensions, and system dimensions) at Al-Nisour University College. The importance of study stemmed from the instrumental role of strategic planning before the transition from traditional education to e-learning. The study used the descriptive analytical curriculum. In order to collect the required data, the form of questionnaire was adopted and applied to a sample of (60) teaching staff at the university, in addition to adopting the method of interviews. The study used a set of statistical methods, the most important ones are (arithmetic mean, standard deviation, coefficient of variation, Pearson correlation coefficient, and multiple linear regression coefficients). This study came up with a set of conclusions, including a correlation and effect between strategic planning variables and e-learning variables.
Copy-Move Forgery Detection in Medical Images Using Handcrafted Features

Abstract: In the realm of medical imaging, the authenticity and integrity of images are paramount for accurate diagnosis and treatment planning. Copy-move forgery, a prevalent form of image tampering, poses a significant threat to the reliability of medical images. This research project focuses on the development and implementation of a robust copy-move forgery detection system tailored specifically for medical images. The proposed methodology leverages handcrafted features, extracting distinctive characteristics from the images to detect instances of forgery. Through a meticulous process of feature engineering and selection, the algorithm aims to enhance sensitivity and specificity in identifying manipulated regions within medical images. The study explores the application of advanced image processing techniques and pattern recognition algorithms to achieve a high level of accuracy in forgery detection.
Securing Unrecorded Physical Transactions

Abstract: Every day, we perform many transactions, some of which are recorded and some of which are not. Recorded transactions are those that have a physical record maintained, such as online transactions or bank loans. Unrecorded transactions are those that do not have a record maintained, such as most physical transactions. Unrecorded transactions are difficult to verify, which makes them susceptible to fraud. This paper proposes a solution for preventing fraud in physical unrecorded transactions by digitalizing their record using blockchain and developing a model of transaction which will secure the record of transaction and ensure that money is actually being transferred. This solution has a number of potential benefits, including reducing the number of victims of fraud, saving businesses money, and improving public trust in the financial system.