Reviewerly/exHarmony huggingface dataset:
Revised Elementary English Curriculum: Major changes and challenges in curriculum implementation.

This study aimed to analyze major changes in the 2022 Revised Elementary English Curriculum, identify the challenges that in-service teachers might encounter in its implementation, and explore ways to address these challenges. To accomplish this, the curriculum document was examined for changes in its overall structure as well as for detailed changes in four major components to identify the main direction of the revision. Subsequently, to identify any implementation challenges, this study conducted a content analysis of opinion documents from in-service teachers collected during the curriculum development process, along with related research reports and journal articles. The major changes in the new curriculum can be broadly summarized as follows: 1) the notion of a competency-based curriculum was fully realized, with subject competencies explicitly presented, and a framework of learning contents and achievement standards aligned with them; 2) in order to strengthen basic literacy education, the achievement standards for grades 3-4 were adjusted upwards, and the continuity between grade groups was enhanced; 3) there was an emphasis on the use of various educational technologies and artificial intelligence in teaching and assessment, as well as individually tailored learning and assessment. In relation to these changes, three implementation issues emerged from the content analysis: difficulties with teaching and assessing competencies, particularly regarding strategies, attitudes, and values; interpreting and applying the revised achievement standards; and dealing with an increased level of written language in grades 3-4 and providing support for struggling learners.
Analisis Pengolahan Bahan Pustaka di Perpustakaan Sekolah UPTD SMP Negeri 1 Kec. Situjuah Limo Nagari

The aim of this research is to examine the process of handling library materials at the State Junior High School 1kec. Situjuah Limo Nagari Library. The objective is to assess how effective and efficient this process is in meeting the standards for proper library management. This research was conducted using a qualitative descriptive approach. Data was collected through documentation, observation, and interviews with library staff. Data collection techniques included observing the processing of library materials, examining relevant documents, and conducting structured interviews with the staff.Subsequently, the collected data was analyzed qualitatively to identify the process of handling library materials, evaluate the efficiency and effectiveness of each stage, and compare it with other methods of processing library materials.The study's findings show that the State Junior High School 1Kec. Situjuah Limo Nagari Library processes books in an efficient and well-organized manner. Standard operating protocols are strictly adhered to in the cataloging, categorization, inventory, and shelving processes.The use of computerized systems in catalog creation also facilitates user access to information. Therefore, the library has achieved a high level of efficiency in handling library materials. This analysis provides a comprehensive overview of the quality of library management at the institution, serving as a basis for improving library services in the future.
Studi Deskripsi Kerjasama Perpustakaan Universitas Kristen Maranatha dengan Forum Perpustakaan Perguruan Tinggi Indonesia (FPPTI) Wilayah Jawa Barat dalam Kegiatan Peningkatan Kualitas Pustakawan

Libraries as non-profit institutions cannot stand alone. There needs to be collaborative activities so that they can have a positive impact on each other through various forms. This research aims to determine the activities as a form of collaboration carried out by the Maranatha Christian University Library with the Indonesian Higher Education Library Forum in the West Java region and its impact on librarians. This research uses a descriptive qualitative approach method by taking primary data sources through interviews and observations, as well as secondary data sources through literature studies. The data analysis used uses data reduction, data presentation, as well as verification and drawing conclusions. The results of the research show that collaboration between university libraries and university library forums can result in 1) collaborative workshop activities to improve the quality of librarians, where in this research the focus is on research data management and visual analysis of institutional repositories 2) the opening of information networks quickly and widely through membership college library forum. The benefits of collaboration have significantly provided positive results for both parties, both the Maranatha Christian University Library and the Indonesian Higher Education Library Forum in the West Java region.&#x0D; Keywords: Library Cooperation; University Libraries; Library Forums
Extraction of factor scores reflecting factor indeterminacy and application to factor score regression model

Factor analysis is a multivariate analysis method widely used to extract latent factors from high dimensional data and interpret multidimensional data through dimension reduction. Additionally, factor scores of individual observations for the extracted factors are calculated and used in a subsequent regression analysis. This factor model has the characteristics of parameter indeterminacy which means parameters such as the factor loading matrix or unique variance are not uniquely determined, and factor indeterminacy which represents that latent factors are not uniquely determined even in situations where the parameters of the factor model are determined. In this paper, we examine the indeterminacy of factor scores and propose a new method of calculating factor scores that maximize the correlation coefficient between a response variable and a factor in a factor score regression model. Simulations and real data analysis were conducted to compare the existing factor scores using the regression method and the proposed factor scores utilizing the indeterminate part of factors in factor score regression setting. As a result of data analysis, it was confirmed that the estimation accuracy of regression model was higher when using the proposed factor scores.
Big Data Analysis Of Banten Community Information Consumption After The Decline of The Covid 19 Case

This research explains the information consumption of Banten people after the decline of the covid 19 case. What information themes are communicated by the community about Banten on social media. This research was conducted with a qualitative approach by discussing the results of data mining searches (data retrieval on social media through applications), while the application used is NodeXL. The following are the results of this study; among the five aspects of information that researchers examined the data (health, education, economy, tourism, and politics), health information was the least communicated (both one-way and two-way) by the community. Meanwhile, politics and tourism are the most communicated aspects of social media. It can be said that the communication behavior of the community about Banten Province on YouTube social media is generally not dominated by two-way or more communication models. Feedback only occurs on certain information themes. The theme of political information and tourism is the most two-way or more. Meanwhile, health information is the least discussed and does not generate much feedback. It can be concluded that health information is no longer a public concern after the decline in covid 19 cases.
A Study on the Utilization Strategies of Subjective Questions in Public Agency Surveys Using Deep Learning Techniques

The objective of this study is to assess the impact of incorporating subjective questions in public agency satisfaction surveys using deep learning techniques. Each year, around 1,000 public agencies carry out satisfaction surveys. Nevertheless, the reliance on standardized surveys for comparability restricts the gathering of nuanced information. In response, subjective questions have been introduced. Yet, the examination of these questions remains fragmented and hasn't been integrated into mainline satisfaction surveys. To address this gap, we evaluated feedback from roughly 1,500 participants associated with K-Public Agency. For handling these subjective questions, we leveraged the RoBERTa algorithm and employed a range of models, such as XGBoost, neural networks, and logistic regression. Preliminary findings underscore the effectiveness of XGBoost when dealing with structured data. Notably, its performance showed variations when considering subjective inputs. A significant finding was that integrating subjective questions enhanced both the accuracy and recall in predicting satisfaction levels. This indicates that deep learning offers a detailed interpretation of subjective inquiries, which elevates the overall quality of public satisfaction surveys.
Implementasi Metode WAN pada Proses Preprocessing Ekstraksi Karakter Citra Digital

Character extraction in digital images is an interesting topic in the field of image processing. One of the steps in this processes is image preprocessing , that is preparing the image before extraction. There are many methods that can be used, one of which is the WAN method. The WAN method is a development of the Sauvola method, a method commonly used to improve the quality of text images. In an journal article, the WAN method provides better results than other methods for improving the quality of text images. In this research, this claim was tested by applying it as a preprocessing process in text character extraction using Optical Character Recognition (OCR) technology. The purpose of this research is to find out how well the WAN method is used compared to other methods. The result is that OCR technology give better result to an original image compare to image with preprocessing process, including using WAN method with a match rate of 52.33%. Meanwhile, if the preprocessing process is carried out first, the WAN method gives better results than the Sauvola method with a match rate of 26.93% for the WAN method and 23.27 for the Sauvola method.
KESIAPAN GURU DALAM MELAKSANAKAN PEMBELAJARAN BERDIFERENSIASI PADA PENINGKATAN KEMAMPUAN NUMERASI SISWA SD/MI DI LOMBOK TENGAH

&lt;p&gt;&lt;em&gt;Observation results show that teachers can carry out initial assessments but have not been able to design learning strategies that suit students' learning needs. Therefore, it is necessary to carry out research regarding teacher readiness in implementing differentiated learning to improve students' numeracy abilities. This research is a quantitative descriptive study that presents conclusions based on statistical presentation. This research was carried out by surveying 16 elementary/MI schools in North Batukliang, Pujut, and Batukliang Districts which are target schools for the SAC (All Smart Children) program from INOVASI. The research subjects were 32 SD/MI teachers consisting of 2 teachers in each educational unit, namely class I and IV teachers who had implemented the principles of an independent curriculum in learning. The results of the research show that elementary/MI teachers in Central Lombok are ready and able to carry out differentiated learning that focuses on improving students' numeracy skills but still requires improvement in several aspects of each achievement indicator that has been determined.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt; &lt;/em&gt;&lt;/p&gt;
Development of a five-tier diagnostic test instrument to identify the level of understanding and misconceptions on the subject of equilibrium of rigid bodies at SMA Negeri 9 Jambi City

This research aims to identify students' misconceptions regarding website-based rigid body equilibrium material at SMA Negeri 9, Jambi City. This research focuses on developing a diagnostic paper-based test (PBT) in the form of a website. This research method is R&amp;D (Research and Development) development with the ADDIE (analysis, design, development, implementation, evaluation) development model. However, this research has only reached the implementation stage. The instruments used in the research were the results of media questionnaires, instrument validation, and student responses. The research results are as follows: First, Dreamweaver, MySQL, and HTML can be used in website development. Second, the results of this product development can be used because they have been validated by media experts, namely Validator One and Validator 2, to determine the feasibility of the product being developed. Thus, a five-tier diagnostic test in the form of a paper-based test has been successfully developed into a website with a suitable category for identifying misconceptions among students regarding the equilibrium of rigid bodies.
Effectiveness of Educational Games in Improving Students' Cognitive and Social Skills

Cognitive ability is an inner skill that uses the brain that is needed to perform tasks or anything that is simple to the most complex tasks. Games in education for students will help them develop the ability of cognitive structures in themselves, with the development of cognitive skills, students will also foster social attitudes in themselves and will help them socialize in society. The purpose of this study is to examine the effectiveness of educational games in improving students' cognitive and social skills. This research was conducted to understand that educational games can improve students' cognitive skills and can also develop students' social attitudes, while this research will also illustrate whether these educational games can be applied to all levels of education in schools. The method used in this study is a quantitative method in which in this case, the data collection used is by means of a questionnaire, with the correlation method to be applied through SPSS statistical software. Respondents involved in this study are students who are currently studying elementary school education and the results of the preparation of students who are used as assessment materials. The results obtained from this study explain that the effectiveness of educational games in improving students' cognitive and social skills has a good impact on students who are taking elementary school education, educators can also find out the effectiveness of educational games in improving students' cognitive and social skills. The conclusion obtained from this research outlines the effectiveness of educational games in improving the cognitive and social skills of students who are still studying in elementary school. With educational games can also find out the cognitive skills possessed by students and can also find out their attitudes in their social environment. Educational games can also develop students' cognitive and social attitudes.
SMARTnatomy CARDIO MOBILE APPLICATION FOR IMPROVEMENT IN EFFECTIVENESS OF ANATOMY LEARNING MEDIA

Background: Anatomy is an important science to know how the body works, the relationship between body structures that change due to disease, as well as the basis for medical students to carry out physical examinations on patients. Currently, students perceive anatomy as a difficult science. Therefore, an anatomy learning method with more effective learning media is needed. The purpose of this study is to determine the difference in the effectiveness of the SMARTnatomy Cardio mobile application with the atlas for medical students.Methods: This research is a quasi-experimental study with equivalent control group design which is conducted at the Faculty of Medicine, Sebelas Maret University, Surakarta. The sample of this study are 66 medical students who were taken by purposive sampling technique. Independent variable is the SMARTnatomy Cardio mobile application and anatomy atlas. The dependent variable is effectiveness of anatomy learning media. The data obtained are pretest, posttest, and grade increases. The data are then calculated using SPSS software and analyzed using the Mann Whitney U-Test and Wilcoxon Test.Results: Test results show anatomy atlas and the SMARTnatomy Cardio mobile application are equally effective as anatomy learning media (p = 0.000). However, there is a significant difference in post test scores (p = 0.035) where anatomy atlas is slightly more effective than SMARTnatomy Cardio mobile application (p = 0.017).Conclusion: There is a difference in the effectiveness of the SMARTnatomy Cardio mobile application with the atlas for medical students.
Digital Twins for Creating Virtual Models of Solar Photovoltaic Plants

Amidst the challenges posed by the high penetration of distributed energy resources (DERs), particularly a number of distributed photovoltaic plants (DPVs), in modern electric power distribution systems (MEPDS), the integration of new technologies and frameworks become crucial for addressing operation, management, and planning challenges. Situational awareness (SA) and situational intelligence (SI) over multi-time scales is essential for enhanced and reliable PV power generation in MEPDS. In this paper, data-driven digital twins (DTs) are developed using AI paradigms to develop actual and/or virtual models of DPV s, These DTs are then applied for estimating and forecasting the power outputs of physical and virtual PV plants. Virtual weather stations are used to estimate solar irradiance and temperature at user-selected locations in a localized region, using inferences from physical weather stations. Three case studies are examined based on data availability: physical PV plant, hybrid PV plants, and virtual PV plants, generating real-time estimations and short-term forecasts of PV power production that can support distribution system studies and decision-making.
Synchronization of External Inertial Sensors and Built-in Camera on Mobile Devices

The fusion of inertial and visual data is an effective approach to human motion analysis, with applications in areas such as sports or rehabilitation exercise monitoring. Employing wireless, low-cost, external inertial sensors and a built-in camera on mobile devices provides a convenient acquisition system, available for wide range of potential users. In order to take advantage of both data modalities, robust time synchronization is required. We consider consumer-grade devices, for which direct access to internal clocks is not available and only high-level API is provided. At the same time, we aim to avoid event-based synchronization that would require additional user actions. We investigate sources of acquisition errors on mobile devices, and then we propose and evaluate a novel synchronization method for inertial and visual data. Experimental results indicate that the proposed method provides robust synchronization.
An Open Dataset of Synthetic Speech

This paper introduces a multilingual, multispeaker dataset composed of synthetic and natural speech, designed to foster research and benchmarking in synthetic speech detection. The dataset encompasses 18,993 audio utterances synthesized from text, alongside with their corresponding natural equiva-lents, representing approximately 17 hours of synthetic audio data. The dataset features synthetic speech generated by 156 voices spanning three languages, namely, English, German, and Spanish, with a balanced gender representation. It targets state-of-the-art synthesis methods, and has been released with a license allowing seamless extension and redistribution by the research community.
JPEG Steganalysis Using Leaked Cover Thumbnails

JPEG steganalysis seeks to detect the presence of hidden messages in JPEG images. In some cases, additional information is available that may aid JPEG steganalysis. One instance is a thumbnail of the cover image, which may be acquired from a seized device or from the image file because the steganography software did not update the metadata. This paper studies how a leaked cover thumbnail can aid JPEG steganalysis. We distinguish two types of thumbnails: pre-compression thumbnails produced from uncompressed pre-covers, and post-compression thumbnails produced from JPEG-compressed covers. The analysis proceeds in three stages. First, we quantify the amount of information left in the cover thumbnail. Second, we demonstrate that post-compression cover thumbnails allow for near-perfect steganalysis by re-creating the thumbnail. Third, we study how an EfficientNet detector can benefit from the additional cover information in pre-compression thumbnails.
A Comprehensive Study of Blasphemy and Freedom OF Speech in the Light of Islamic Jurisprudence and the Pakistani Legal Perspective: A Critical Analysis

The offence of blasphemy is one that elicits strong feelings. Every time it comes up, it kicks off a highly contentious discussion in Pakistan. Every time a new event takes place in Pakistan, the country's blasphemy laws are thrust into the spotlight. After doing an in-depth investigation into the matter, one discovers that it is a very serious crime, and as a result, strong action needs to be taken against the person responsible for it. The blasphemer is subject to the mandatory death sentence under Islamic law. In a similar way, the legislation of Pakistan calls for the imposition of a fine in addition to the death penalty and life imprisonment. This law has received a great deal of criticism, the most common of which is the assertion that it is used to target and persecute members of minority groups as well as adversaries on the basis of personal grudges. The problem can be solved by enhancing the preliminary stages of the experiments.
Do DL models and training environments have an impact on energy consumption?

Current research in the computer vision field mainly focuses on improving Deep Learning (DL) correctness and inference time performance. However, there is still little work on the huge carbon footprint that has training DL models. This study aims to analyze the impact of the model architecture and training environment when training greener computer vision models. We divide this goal into two research questions. First, we analyze the effects of model architecture on achieving greener models while keeping correctness at optimal levels. Second, we study the influence of the training environment on producing greener models. To investigate these relationships, we collect multiple metrics related to energy efficiency and model correctness during the models’ training. Then, we outline the trade-offs between the measured energy efficiency and the models’ correctness regarding model architecture, and their relationship with the training environment. We conduct this research in the context of a computer vision system for image classification. In conclusion, we show that selecting the proper model architecture and training environment can reduce energy consumption dramatically (up to 98.83%) at the cost of negligible decreases in correctness. Also, we find evidence that GPUs should scale with the models’ computational complexity for better energy efficiency.