Reviewerly/exHarmony huggingface dataset:
Pemanfaatan Penggunaan Chat GPT Dalam Meningkatkan Kemampuan Pengajaran Bahasa Inggris

ChatGPT is an AI tool that has sparked debates about its potential implications for education. We used the SWOT analysis framework to outline ChatGPT’s strengths and weaknesses and to discuss its opportunities for and threats to education. ChatGPT can increase access to information, facilitate Personalised and complex learning, and decrease teaching workload, thereby making key processes and tasks more efficient. The weaknesses are a lack of deep understanding, difficulty in evaluating the quality of responses, a risk of bias and discrimination, and a lack of higher-order thinking skills. The aim of this community service is to inform about the benefits of using ChatGPT in teaching English for teachers at Mts Muhammadiyah 15 Medan and to conduct a SWOT analysis of ChatGPT.
Sonic Alchemist: AI’s Role in Amplifying Creativity in Film Sound

Defying mainstream views of AI as tools that mimic or replace human input, this paper presents Sonic Alchemist: an avant-garde AI software taking a fresh approach to sound design. Built on the Beginner’s Mind principles, it empowers users to defy familiar paths and habits, fostering collaboration between human and machine. Unique features like automatic sound effects matching and a weight-based sound selection system further enhance this partnership. User feedback and case studies highlight Sonic Alchemist’s capacity to evoke new insights and unexpected solutions, reinforcing its role as a creative ally. Analysis of industry reception and user responses during testing underscores its potential to transform sound design in visual media. This study underlines the enduring significance of human originality, even in the AI era, portraying Sonic Alchemist as an inspiration tool and a champion of human creativity. It asserts that the willingness to unlearn and rediscover is key in creative innovation, even when assisted by advanced AI tools.
Physics Playground Design and Outline

For our third example project, we’ll be tackling some new topics pertaining to the physics of the Unity engine. We’ll implement a mouse-aimed camera with 3D movement for our player, including jumping, gravity, and wall jumping. We’ll play with some objects using proper Rigidbody-controlled physics, giving our player a means of pushing and pulling them from a distance. We’ll also tinker with joints to attach Rigidbodies to each other and “force fields” to play with adding forces to Rigidbodies and/or our player on the fly.
The Influence of Critical Reasoning, Independece, and Resilience to Adversity on The Numeracy Competence of 5th Grade Students in Cluster IV Kerambitan

This study aims to determine the effect of critical reasoning, independence, and resilience to adversity on the numeracy competence of fifth-grade elementary school students in cluster IV Kerambitan. This research is ex-post-facto research. The population used as the sample in this study was 82 students. The independent variables in this study are critical thinking, independence, and resilience to adversity, while the dependent variable is the students' numeracy competence. Data collection methods used in this study were questionnaires and tests. Data on independence and resilience to adversity were collected using the questionnaire method, while data on students' critical thinking and numeracy competencies were collected using the test method. Data analysis used in this study is multiple regression and partial correlation. Based on the research that has been done, it is concluded that: 1) there is a significant influence of critical reasoning on the numeracy competence of fifth-grade elementary school students in cluster IV Kerambitan, with an effect of 40.8% and an effective contribution of 20.26%, 2) there is a significant effect of independence in the numeracy competence of fifth-grade elementary school students in cluster IV Kerambitan, with an effect of 48.9% and an effective contribution of 17.98%, 3) there is a significant effect of resilience to adversity on the numeracy competence of fifth-grade elementary school students in cluster IV Kerambitan, with an effect of 42% and an effective contribution of 28.41%, 4) taken together, there is a significant influence of critical reasoning, independence, and resilience to adversity on the numeracy competence of fifth-grade elementary school students in cluster IV Kerambitan, with an effect of 66.70%.
A Sampling-Based Sentiment Analysis of Imbalanced Streamed Movie Reviews

Sentiment analysis has gained significant importance in analyzing individuals' attitudes and perceptions toward various products, services, and entertainment mediums, including movies. Evaluating the sentiment expressed in movie reviews can provide valuable insights into how users interpret and react to specific films. However, Movie review datasets often suffer from an imbalance in the distribution of positive and negative sentiment labels, which presents challenges for accurate sentiment classification. We propose a framework that harnesses streaming data for enhancing sentiment analysis algorithms. First, we create an initial model using an IMDB movie review dataset to categorize real-time review streams. To address the issue of imbalanced streamed data in movie reviews, we apply diverse sampling techniques, mitigating bias toward the dominant sentiment. This method bolsters the sentiment classifier's effectiveness. Additionally, we iteratively improve the initial model using recorded classification outcomes. We conducted comprehensive experiments on varied movie review datasets to assess our approach's effectiveness. Evaluation metrics were used for comparison, including accuracy, precision, recall, and F1-score. The results encompassed contrasting our sampling-driven method with baseline approaches. The SVC outperformed other algorithms in a native classification environment, whereas the extra tree excelled in a streamed classification environment. These outcomes underscored our framework's efficacy in enhancing sentiment analysis algorithm performance.
Performance Comparison Between Bit Weight Intervention and CCDM Based Probabilistic Shaping

In this paper, we verify the shortcomings of constant component distribution matching (CCDM) over well weight intervention (BWI), the advantages of BWI in other aspects, and some engineering scenarios.
Pengaruh Penggunaan Media Gambar Seri terhadap Kemampuan Menulis Dongeng Fabel Siswa Sekolah Dasar Sekota Bengkulu

This research aims to determine the effect of the use of drawing media series on the ability to write fable fairytales students class IV elementary school Sekota Bengkulu. This type of research is a quantitative research. Reasearch Method used Quasy Experimental research with the design resarch The Matching Only Posttset Control Group Design. This research conucted after giving treatment to the sample class. The population in this research are all elementary school and students who are accredited A and used the curriculum KTSP Sekota Bengkulu. The sampling technique used the cluster random sampling.The sample in this research is students of class IVB SDN 60 as the experimental class and the students of class IVB SDN 82 as the control class. This research instrument used a description test (essay). Data analysis used is descriptive analysis, prerequisite test and inferential analysis that is t-test. T-test of both sample classes with significance level of 5%, obtained tcount = 1,74 while ttable =1,68 tcount &gt; ttable so that H0 rejected and Ha accepted. It means that there the influence of the use of drawing media series to the ability to write fable fairytales class students IV elementary school sekota Bengkulu.
A Revocation Key-based Approach Towards Efficient Federated Unlearning

Federated learning is an approach that ensures privacy in machine learning, but it has its limitations when it comes to preserving the right to be forgotten. To address this challenge, we propose a new method called Unlearning Key Revocation List (UKRL) for implementing federated unlearning. Our approach does not require clients’ data or models to be unlearned; instead, we use revocation keys to remove clients from the model. We pre-trained the model to recognize these keys, so the model will forget the revoked clients when their revocation keys are applied. We conducted four experiments using MNIST datasets to verify the effectiveness of our approach, and the results showed that our work is not only effective but also time-saving since the unlearning time is 0. In conclusion, we provide a new perspective on achieving federated unlearning.
Peran Pustakawan Dalam Manajemen Konflik Informasi di Perpustakaan

Conflict is not a new phenomenon in the library environment, but librarians must be able to deal with it. Emotional intelligence is needed to create existing conflict management. Emotional intelligence is a skill related to emotions such as the ability to control individual and other people's anger so that managing anger is to examine thoughts and actions. Emotional management skills can help individuals understand and manage emotions and use information to influence thinking and behavior when interacting with others in certain organizations. Librarians must be able to deal with moods, emotions and feelings so that librarians don't get emotional easily and don't even affect their performance. It also helps build empathy because when a librarian understands her mood and other people's feelings. Thus introducing a person to work better with others and preventing conflicts.
Comparative Analysis Of Digital Or Print Book Reading References Among Journalism Students

This research is related to the preference for reading printed books with digital books by UIN Jakarta Journalism Study Program students. The purpose of this research is to find out the reading preferences of UIN Jakarta students and find out the advantages and disadvantages of reading printed or physical books. The method used in this research is a quantitative approach method with a descriptive research type, this method uses frequency and percentage variables. This study concludes that UIN Jakarta Journalism Study Program students prefer to read physical books with various advantages of the physical book itself compared to reading digital books which still have shortcomings in quality and convenience for readers
Kemampuan Literasi Informasi Mahasiswa Prodi Perpustakaan dan Ilmu Informasi Angkatan 2021 UIN Malang dalam Menyelesaikan Tugas Perkuliahan dengan Model Literasi Big Six

Students as academics in higher education need information to carry out assignments given by lecturers. Student interaction with information is certainly different from one another. This study was written to describe the information literacy abilities of students majoring in Library and Information Sciences at UIN Malang. The information literacy model used in this research framework is the big six literacy model. The method used is a qualitative approach and data collection techniques using interviews. The results of the study show that each student has different information literacy skills in completing their coursework. Several stages of information literacy that students have mastered are task definition, use of information, and synthesis. However, there are still stages that need to be improved, such as information search strategy, location and access to information, and evaluation
Pemanfaatan Edoo Sebagai Bentuk Inovasi Layanan Di Perpustakaan Sman 15 Bandung

The purpose of this study is to utilize the Edoo digital library application at SMAN 15 Bandung as a form of service innovation in the library. Data collection techniques were carried out by observation with observations and interviews accompanied by literature study. Results from this study shows that the Edoo digital library application useful in assisting learning activities, the advantages and disadvantages of the Edoo digital library application are a challenge for the SMAN 15 Bandung library
Hardware Development of Sphere Intersection in Ray-casting Using High-Level-Synthesis

Game applications that require high graphics performance have a large processing load, which greatly affects the running time of battery-driven mobile terminals. Mobile terminals that support dynamic partial reconfiguration of hardware can perform high-performance and low-power graphics processing through power-efficient hardware execution, rather than software. This paper develops hardware for the intersection determination process in ray-casting, which is utilized in the creation of high-graphic game applications. In the development, the HLS, which is an automated software-to-hardware conversion tool is used. We developed the software of intersection determination process so that the HLS can generate small-resource-usage, high-performance, and power-efficient hardware. Intersection determination of ray-casting is carried out by vector and square root calculation. Usually, these calculations are executed in floating-point operation. However, this operation method tends to increase the size of the circuit because it requires a great deal of resources when implemented hardware. It is not desirable due to a huge circuit size means high power consumption. Therefore, this paper shows an optimal method in vector and square root calculations using fixed point, while considering its accuracy. Also, through demonstrations on actual machines, we evaluate its usefulness in terms of performance, circuit size and power efficiency.
Pelatihan Pengolahan dan Visualisasi Data Penduduk menggunakan Python

Imitations of officers in analyzing and visualizing data in Tabing Banda Gadang Village Head. Most of these problems are caused by the lack of knowledge and expertise of the apparatus as well as the limited number of computers. The data at the Tabing Banda Gadang Village Head are not stored properly, the data is stored in Excel and there is no technology-assisted data management and data presentation. Implementation method by providing training and mentoring. The training provided is in the form of basic skills in using Python in data visualization. Its activities include training and mentoring Data Visualization and data processing using the Python program at Tabing Banda Gadang Urban Village. The implementation of community service conducted interviews and administered questionnaires to find out the extent to which the trainees understood the use of Python software. The service team explains data visualization accurately and concisely. District employees are assisted in understanding and processing data using this Anaconda Jupyter Python Notebook. District officers find it helpful in their work with the applications taught.
THE INFLUENCE OF FAMILY ENVIRONMENT, PEER ENVIRONMENT, AND LEARNING INTEREST ON STUDENTS' LEARNING OUTCOMES IN CLASS X OF BASIC ACCOUNTING AT SMK NEGERI JAKARTA TIMUR

Research was conducted with the aim to find out the influence of the family environment on student learning outcomes, the influence of the peer environment on student learning outcomes, and the effect of interest in learning on student learning outcomes. Research is intended for class X students of basic accounting subjects in the accounting and financial skills program at East Jakarta State Vocational School. The reachable the affordable population for this research is 178 students consisting of class X students at 46 State Vocational Schools Jakarta, 40 State Vocational Schools Jakarta, 50 State Vocational Schools Jakarta. The sample of this research is 122 students. total over sample was chosen according to the Isaac and Michael formula, with an error rate of 5%. This study uses a sampling technique a proportional random sampling technique. The data obtained via method uses the questionnaire method for the independent variable, while the dependent variable uses secondary data in the form of an Odd Semester End Assessment. Data processing is done by performing data analysis techniques including multiple regression equation, analysis data requirements test, classical assumption test, model feasibility test, and hypothesis test. The decision on the results of processing the research data is there is a positive and significant influence between the family environment on learning outcomes, there is a positive and significant influence between the peer environment on learning outcomes, and there is a positive and significant influence between learning interest on learning outcomes. The coefficient of determination in this study is 23.8%.
Spoof Speech Detection Based on Extended Constant-Q Symmetric Subband Cepstrum Coefficients and Fused Features

With the improvement of voiceprint synthesis and recording technologies, the malicious use of spoof speech will pose a significant threat to the automatic speaker authentication system. Therefore, it is essential to study speech feature extraction and spoof detection (SD). In this paper, some feature extraction methods for spoof speech are proposed. In the fore-end feature extraction, constant Q symmetric-subband cepstrum coefficients (CQSCC) and extended constant Q symmetric subband cepstrum coefficients (eCQSCC) based on phase symbol magnitude phase spectrum (PMPS) are proposed. In the back-end detection system, the features proposed in this paper are modelled through the Gaussian mixture model (GMM) and evaluated with EER and t-DCF. Under the physical access (PA) and logical access (LA) scenarios, the eCQSCC is optimized by 35.1% and 34.6%, respectively, compared with baseline feature CQCC. Further, the eCQSCC proposed above and prosodic features in other domains are fused at a scoring level and better anti-deception performance than features in a single domain is obtained.
Toward Applying an Improved Path Planning on Autonomous Car Parking

In this paper, we clarify important sub-issues, which are overstaying of vehicles in parking lots, integration of 3iDAR sensors and simulating in cold weather environments, avoiding the penalty imposed by notification regarding overstay and improving the approach of imposing penalty, and the interactions to decide where to park the car. In the last issue considering the driver’s opinion to park the car is an option in order to decide where to park the car.
Toward an Ontology-based Explainable Strategy Analysis on Multiplayer Multiteam Games

In general, Esports players make high level strategies for winning a match in each game in Esports. On the other hand, the strategy of Esports is always increasing its difficulty and complexity. In this paper, we focus on the way to remove such a hurdle to enjoy playing Esports as competitive for beginners. If we see a long-standing game such as “Shougi”, we already have the ways to support the beginners understand the strategy more easily some existing techniques for making explanations for the strategy automatically. However, we do not expect to have such supporting mechanisms for newly developed games in Esports. In this paper, we propose a preliminary prototype implementation of an ontology-based explanation support system for the strategy analysis on multiplayer multiteam games.
The Impact of Language Properties in Multilingual Datasets on Sarcasm Detection

Currently, people spend a lot of time on social media sites to express their opinions and emotions, making it one of the most important data sources for sentiment analysis tasks executed by machine learning. However, sarcasm can be an obstacle to tasks that seek to determine people’s true intentions such as sentiment analysis. As a result, research on automatic sarcasm detection has garnered attention. In addition, with the globalization of social media, it has become crucial to have sarcasm detection models that can handle multiple languages. Although research on multilingual sarcasm detection models has become popular in recent years, there has been little examination of how the types of languages included in the training dataset affect model performance. Sarcasm is highly dependent on culture, and language represents the culture, so the differences in languages may affect the differences in sarcastic expressions. This study focused on the morphological typological differences between Arabic and Chinese, and trained the model using two datasets. One is an English-Arabic dataset, in which the languages belong to the same category. The other one is an English-Chinese dataset, in which the languages belong to different categories. Then the results were compared using two English test datasets. The experiment showed that the training results of English and Arabic were better than those of English and Chinese, indicating that the morphological typological classification of languages in the dataset affects multilingual sarcasm detection. In other words, to increase the detection effectiveness of languages belonging to a certain category, it is better to use training data of the same type. Additionally, a Multilingual BERT-LSTM model was constructed and compared to the BERT-only experiment. As a result, the LSTM structure was generally found to be effective for multilingual sarcasm detection.
The Trust Mechanism Reconstruction of Energy Management Contracting Leased Assets Securitization Based on BlockChain

Energy management contracting (EMC) is an emerging market-oriented energy saving mechanism, but the development of EMC has been severely restricted in China because of financing obstacle. Theoretically, EMC company packs equipment assets for financial lease further securitized them by financial lease company, which is considered to be a suitable financing way for EMC to obtain long-term sustainable funds and play a key role in promoting its development. However, such securities remain a thin liquidity in market. To answer the question why did it happen and how could it be improved. First, we emphasize that the linear information transfer mechanism is the main reason for the above phenomenon. Second, based on blockchain technology, we reconstructed the linear information transfer mechanism into the network dynamic information transfer mechanism, in which market participants could directly receive the real-time operation information of the underlying assets. Meanwhile, the interaction between investors and underlying assets reconstructs the trust mechanism, which shows the role of blockchain technology in EMC leased assets securitization.
A Mobile Learning App Using Past Exam Questions

This paper presents the development of a mobile learning app designed to enhance the preparation process for the registered dietitian national examination. The authors, affiliated with a registered dietitian training institution, identified the limitations of existing online learning platforms and daily learning methods. To address these shortcomings, they developed a prototype app that offers comprehensive learning content and overcomes the challenges faced by students. The app was subsequently tested by students, and a survey was conducted to gather feedback. This paper provides an overview of the developed system and presents the survey results.
Person 3D Tracking and Action Recognition through Stereo Camera

The use of depth information to estimate the precise position of an object in the world coordinate system has attracted the attention of researchers in 3D multiple object tracking. Recent studies have obtained depth information from expensive LiDAR systems to achieve accurate results in vehicle tracking tasks. Some studies have used pixel information from a single image obtained from a monocular camera to predict depth, which is cheap but has significant limitations in accuracy. To accurately track small objects like the person and analyze their behaviors with a lower cost, in this paper we use stereo camera and propose a combination of 2D detection and 3D tracking method to implement a 3D tracking analysis system. Our approach is less costly and the system can be used conveniently. Our code is publicly available at https://gitlab.com/syo093c/fuminsyoStereo.