Reviewerly/exHarmony huggingface dataset:
PENGEMBANGANLKPD MENULIS TEKS CERPEN BERBASIS INKUIRI UNTUK SISWA SMP KELAS IX

The purpose of this study was to produce an Inquiry-based Student Activity Sheet (LKPD) on the subject matter of writing short text and testing its feasibility in learning to write short text on junior high school students. The research method used in this research is research and development (Research and Development). Data collection techniques through interviews and questionnaires in three schools, namely SMPN 1 Bengkunat, SMPN 2 Bengkunat, and SMPN 3 Bengkunat. The results showed that 1) successfully developed teaching materials in the form of LKPD based on inquiry in writing short text, 2) the overall feasibility of LKPD was declared "very good" by material experts, media experts, and practitioners with presentation assessments 83, 88, and 88, 3) LKPD also received a "very decent" assessment from teachers and students in three schools.
Supplementary Figure S1 from Dense and Nondense Mammographic Area and Risk of Breast Cancer by Age and Tumor Characteristics

&lt;p&gt;Distribution of dense area (DA) and non dense area (NDA) phenotypes prior to standardization. The age effect on DA and NDA as well as the differences in the distribution across the studies observed for breast cancer cases.&lt;/p&gt;
Advantages and Challenges of eLearning Before and After the COVID-19 Pandemic: Faculty and Student Perceptions in Saudi Education

Novelty and Topicality: The COVID-19 pandemic significantly affected the education sector, with eLearning transforming the global education system. Research Purpose: This study sheds light on how the English departments of King Khalid University overcame the pandemic’s impact, with respect to the shift to online learning. Motivation for the Study: The findings of the present study are of great importance for transforming the education system, not only in Saudi Arabia but worldwide. The globalization of education will help the universities of the Kingdom of Saudi Arabia make borderless, cost-effective education available to the citizens of the world from the comforts of their homes. Design and Methods: The study seeks to identify the challenges and advantages of eLearning, based on the perceptions of English-as-a-foreign-language (EFL) learners and instructors. The data were collected through Google forms and analysed using various SPSS software tools. Main findings: The findings revealed that the advantages of eLearning outweigh the challenges faced by students. The advantages of teaching English online include flexibility of learning, constant availability of learning materials, time efficiency, and the upgrade of technical skills. The major challenges for students and instructors include a lack of in-person interaction and poor Internet connectivity. Practical Implications: Notably, the study findings can improve the efficacy of eLearning in the education field in general and Saudi English departments in particular. Contribution: The outcomes can help explore future possibilities for reforming the education sector, both within and outside the Kingdom of Saudi Arabia.
Analysis and Design of Student Point Systems to Improve Student Achievement using The Clustering Method

The student points system is an application for recording students' achievement and offense points. The lack of recording and dissemination of information on achievement results makes students less motivated to improve achievement, and the distribution of scholarships for outstanding students is inappropriate. To improve student achievement, an application program is needed that can record and disseminate student achievement data in real-time, accurate, and effective. So, the purpose in this study is to know and analyze the design of the student point system to improve student achievement using the clustering method. Researchers use the Clustering Method in calculating data to determine the accuracy of scholarship distribution for outstanding students. Clustering with the most achievement points is clustering 2 with 25,254 Achievement Points. The total number in the level 2 cluster is 1,797 which indicates the number is close to 2,000 or 2 which is the result of data transformation from the junior high level. The implication of clustering research on student point data is to provide useful information for the Foundation as an institution that houses schools in allocating scholarships for outstanding students. In this case, clustering 2 with the highest number of Achievement Points indicates that there is a group of students with high achievement points. By using the clustering results, the Foundation can allocate scholarships more effectively and efficiently, because it can identify outstanding students from various school levels more easily.
A Novel Method for Prediction of Cryptocurrency Price

Abstract: The safe hash method (SHA) 256 and message digest (MD) 5 are used in peer-to-peer transaction arrangements, also known as sophisticated forms of currency, to safeguard data transfers. Prices for Bitcoin are extremely volatile, act erratically, and have reached eccentricity. They are frequently used for initiative and have mostly replaced traditional trading vehicles like metals, bequests, and the stock market. They must be created due to the significance of reliable deciding models in business. However, it is difficult to predict bitcoin's price because it is based on other digital currencies. Bitcoin prices have been evaluated by a variety of researchers using machine learning (ML) and deep learning models, in addition to other tendency-based market processes. Changing the price of one type of encrypted money may influence other encrypted types of money because all digital currencies are in the same category. The researchers combined sentiments from Twitter and other online amusement sites to enhance the effectiveness of the framework. DL-Gues, a robust and solid structure for forecasting computerized cash costs that considers its reliance on other cryptography-based currencies and market sentiment, is inspired by this work. Twitter as well as cost reports from Run, Litecoin, and Bitcoin were used in our investigation of the Run cost premise. To determine whether DLGather could be applied to more sophisticated monetary standards, we evaluated the ends for the premise for the cost of BitcoinCash using the price data and tweets of Bitcoin, Litecoin, and Bitcoin.
CAMRI Loss: Improving the Recall of a Specific Class without Sacrificing Accuracy

In real world applications of multiclass classification models, misclassification in an important class (e.g., stop sign) can be significantly more harmful than in other classes (e.g., no parking). Thus, it is crucial to improve the recall of an important class while maintaining overall accuracy. For this problem, we found that improving the separation of important classes relative to other classes in the feature space is effective. Existing methods that give a class-sensitive penalty for cross-entropy loss do not improve the separation. Moreover, the methods designed to improve separations between all classes are unsuitable for our purpose because they do not consider the important classes. To achieve the separation, we propose a loss function that explicitly gives loss for the feature space, called class-sensitive additive angular margin (CAMRI) loss. CAMRI loss is expected to reduce the variance of an important class due to the addition of a penalty to the angle between the important class features and the corresponding weight vectors in the feature space. In addition, concentrating the penalty on only the important class hardly sacrifices separating the other classes. Experiments on CIFAR-10, GTSRB, and AwA2 showed that CAMRI loss could improve the recall of a specific class without sacrificing accuracy. In particular, compared with GTSRB's second-worst class recall when trained with cross-entropy loss, CAMRI loss improved recall by 9%.
Visualizing the Implicit Model Selection Tradeoff

The recent rise of machine learning (ML) has been leveraged by practitioners and researchers to provide new solutions to an ever growing number of business problems. As with other ML applications, these solutions rely on model selection, which is typically achieved by evaluating certain metrics on models separately and selecting the model whose evaluations (i.e., accuracy-related loss and/or certain interpretability measures) are optimal. However, empirical evidence suggests that, in practice, multiple models often attain competitive results. Therefore, while models’ overall performance could be similar, they could operate quite differently. This results in an implicit tradeoff in models’ performance throughout the feature space which resolving requires new model selection tools. This paper explores methods for comparing predictive models in an interpretable manner to uncover the tradeoff and help resolve it. To this end, we propose various methods that synthesize ideas from supervised learning, unsupervised learning, dimensionality reduction, and visualization to demonstrate how they can be used to inform model developers about the model selection process. Using various datasets and a simple Python interface, we demonstrate how practitioners and researchers could benefit from applying these approaches to better understand the broader impact of their model selection choices.
The Effect of Youtube Shows on Second Language Acquisition : Case Study on Ghania Al-Adawiya

YouTube is a website channel of various sources that contain video clips around the world. In the site YouTube there are several languages, one of which is Foreign language that can influence and facilitate students in the acquisition of a second language. This study aims to reveal and describe the influence of YouTube on second language acquisition. This study uses analytical data. Qualitative methods are methods that aim to obtain descriptive data. The data in this study is a conversation related to the influence of YouTube on second language acquisition, the data is transcribed into written text. Data were collected using interview, selection, descriptive and verification techniques. Data were analyzed using qualitative descriptive based on Siswantoro’s theory. Conversations or sentences related to influence YouTube's on second language acquisition are analyzed in order to identify the language acquisition process. The results of this study show that; first, video clips, movies, songs and English conversations can enhance and develop the vocabulary of Ghania Al-Adawiyah in acquiring a second language. Second, Ghania Al-Adawiyah in learning a second language through YouTube using the strategies of watching, listening, writing, reading and practicing.
Vocabulary Learning Strategies in Vocational School for English Specific Purposes

There are several difficulties for both teachers and students in EFL classrooms while planning lessons and activities. The way they deal with the challenge, the quality with which they perform the task, and the value they provide to the group are just some of the ways in which this circumstance reveals its solutions. In this research, we questioned SMKN 2 Magelang's business and management students to get insight into the challenges they face while trying to learn English. The researchers in this study used a qualitative approach by recording their observations and conducting in-depth interviews. The results were confirmed once the data was summarized and presented. The results show that ESL students experience a broad variety of challenges while learning English. This happened because of the wide range of pupils' starting points in terms of competency.&#x0D;
The Effect of Flashcard Media On 5th Grade Students Narrative Essay Writing Skill At UPT SDN Unggulan Bontomanai

This research conducted of the problems found in elementary school related to writing skills, there are still some students who have difficulty in writing narrative essays. The purpose of this research is to know the description of flashcard media implementation, to know the description of students narrative essay writing skills, and to determine the effect of using flashcard media on narrative essay writing skills of fifth grade elementary school students of UPT SDN Unggulan Bontomanai. The type of research conducted in this research is quantitative experimental with a pretest-posttest control group design, with pretest, treatment, and posttest stages. . The population and sample in this study were fifth grade students of UPT SDN Unggulan Bontomanai, Bontomarannu District, Gowa Regency with a total of 54 students and determined by simple random sampling technique with a sample of 48 students. The data were using the writing skills test, observation sheets and documentation. Data were analyzed using descriptive and inferential analysis. The results of the descriptive analysis showed that the use ofmedia flashcard at the first meeting was sufficient with a percentage of 64% and at the second meeting it went very well with a percentage of 89%. The improvement of students' narrative writing skills in the experimental group was 42% and the control group was 4%. The results of inferential analysis used independent sample t-test showed a probability value of 0.00 &lt; significance level of 0.05 and T count of 5.675 &gt; Ttable of 2.012. So it can be concluded that there is a effect on the use of flashcard media on the narrative essay writing skills of the fifth grade students of UPT SDN Unggulan Bontomanai, Bontomarannu District, Gowa Regency.
Application Of Process Approach To Improve Students Exposition Writing Skills Class V SDN 2 Tondon, Tondon District Toraja Utara Regency

The problem in this research is the low skill of writing exposition in class V SDN 2 Tondon, Tondon district Toraja Utara regency. The formulation of the problem in this research is how to apply the process approach to improve students exposition writing skills class V SDN 2 Tondon, Tondon district Toraja Utara regency? The purpose of this research is to describe the application of process approach to improve students’ exposition writing skills class V SDN 2 Tondon, Tondon district Toraja Utara regency. The approach used in implementation of this research is a qualitative approach, the type of this research is Classroom Action Research (CAR). The application of the process approach consist of 5 stages, there are pre-writing, drafting, revising, editing, and the last publishing, these stages are carried out in exposition writing. The research subject are teacher and students class V SDN 2 Tondon, Tondon district Toraja Utara regency with there 22 students, consisting of 12 female students and 10 male students. Teacher activity data and students activities were obtained through observation sheets and the result of students exposition writing skills were obtained from the result of students exposition writing. The result of writing exposition in the first cycle of meetings 1 and 2 not completed but in the second cycle meetings 1 and 2 have increased and in categorized completed. In addition, activities of teacher and students in applying the process approach have also increased, in cycle I and cycle II teacher teaching activities are categorized very good. Students learning activities in cycle I of meeting 1 were categorized poor and meeting 2 categorized good and then increased in cycle II which meeting 1 and meeting 2 were categorized very good. Thus it can be concluded that the application of the process approach can improve exposition writing skills students class V SDN 2 Tondon, Tondon district Toraja Utara regency
Preserving Integrity of Evidence with Blockchain Technology in Cloud Forensics for Immigration Management

As the popularity of cloud computing increases, safety concerns are growing as well. Cloud forensics (CF) is a smart adaptation of the digital forensics model that is used for fighting the related offenses. This paper proposes a new forensic method relying on a blockchain network. Here, the log files are accumulated and preserved in the blockchain using different peers. In order to protect the system against illegitimate users, an improved blowfish method is applied. In this particular instance, the system is made up of five distinct components: hypervisor (VMM), IPFS file storage, log ledger, node controller, and smart contract. The suggested approach includes six phases: creation of the log file, key setup and exchange, evidence setup and control, integrity assurance, agreement validation and confidential file release, as well as blockchain-based communication. To ensure efficient exchange of data exchange between the cloud provider and the client, the methodology comprises IPFS. The SSA (FOI-SSA) model, integrated with forensic operations, is used to select the keys in the best possible way. Finally, an analysis is conducted to prove the effectiveness of the proposed FOI-SSA technique.
Preliminary Exploration on the Application of 5G+VR/AR Scenario in Teaching - Taking the Lesson “Crossing the Currency Town” of Financial Literacy Education as an Example

The application of 5G technology in education is a major challenge in creating a new teaching ecosystem. The use of 5G+VR/AR scenarios in teaching is still in the theoretical exploration stage, lacking practical cases for education. This paper discusses the practical thinking of 5G+VR/AR scene intelligent teaching, providing cases of 5G+VR/AR classroom application to promote intelligent teaching in the direction of visualization, intelligence and scenario-based learning. Yizhou Primary School developed a curriculum resource “Crossing the Currency Town” that combines financial literacy teaching with 5G+VR/AR scenarios. The school built a 5G+VR smart cloud classroom based on the 5G network and VR/AR intelligent devices, educational terminals, and network devices to create an immersive and real-time teaching scene.&#x0D; The implementation of intelligent teaching requires the construction of an intelligent environment through the use of intelligent technology to improve the learners’ classroom experience and realize the interaction and cooperation between teachers, students, and machines. Intelligent equipment can also conduct multiple evaluations and monitor students’ learning effects in real-time, generating accurate analysis reports of the learning situation. The data collected can provide resources for personalized recommendation of intelligent teaching and generate intelligent and personalized learning programs.
Design of Smart Door Lock System Using Face Recognition and Mask Detection Based on Viola-Jones Algorithm with Android Integration

Indonesia has been affected by COVID-19 since 2020. In order to stop the virus spreading, the government puts Large Scale Social Restrictions. There is no denying that during this pandemic, criminality is increasing, and this is due to nothing other than the need to survive. The stealing and invading of homes is one of the crimes that have increased. Additionally, the government has strengthened health procedures to require that individuals wear masks while doing activities outside. A system that can identify faces and identify the use of masks was developed in order to solve this issue. Face recognition is used to increase security, and mask detection systems work to enforce the wearing of masks when engaging in outside activities. Both of these technologies can be combined into a single smart door lock system for the home. The system will apply facial recognition identification when someone wants to enter the house and mask detection when they want to do activities outside the house. As a monitoring tool, data will be delivered in the form of an image via the user's Android. This is proven by the accuracy rates of facial identification of 95% and mask detection of 97.5% in this research.
High-Speed Railway Earthquake Early Warning Testing System Based on LabVIEW

This paper mainly introduces a set of high-speed railway earthquake early warning test system based on LabVIEW, which serves for the indoor prototype test of high-speed railway earthquake early-warning system, which is used to simulate wave generation instead of seismic sensors. From the perspective of indoor prototype simulation, a high-speed railway earthquake early warning (EEW) test system based on virtual instrument (VI) technology is developed. Through the test system, seismic wave and non-seismic interference wave are simulated, generated and sent, so as to carry out test technology research on the current high-speed railway EEW system in China. Based on the virtual instrument development platform LabVIEW, the high-speed railway earthquake warning test system is developed. The function of the test system is verified by an example, and the consistency between the original waveform and the acquisition waveform is analyzed. The results show that the amplitude accuracy of the test system is 0.005 ± 0.002 gal and the acceleration peak time is no difference, that is, the high-speed railway EEW test system based on VI technology is accurate and reliable.
Analysis and Suggestions on the Advantages and Disadvantages of Smart Classroom in the Application of Geography Teaching in Senior Middle School

As the information age advances, traditional classroom methods are no longer sufficient for meeting modern educational needs. Smart classroom technology has emerged as a new teaching method, particularly in high school geography, offering various advantages such as displaying content in a comprehensive way and promoting real-time interaction. However, some issues persist in the practical application of this technology. This paper analyzes the benefits and drawbacks of using smart classroom technology in geography teaching, and provides suggestions for improving its effectiveness. Advantages of smart classroom technology in geography teaching include the ability to highlight teaching focuses and overcome difficulties, increase students’ interest in learning, and improve classroom knowledge and teaching efficiency. On the other hand, drawbacks include the lack of expertise among geography teachers in utilizing smart classroom technology, reduced independence of students’ thinking due to the intelligent classroom teaching mode, over-reliance on technology which affects teaching outcomes, and information overload that can hamper students’ acceptance. To address these advantages and disadvantages, this paper offers several recommendations: improving the efficiency of resource collection and production, selecting the appropriate smart classroom mode according to actual teaching needs, striking a balance between intelligent and traditional teaching methods, and providing geography teachers with training to enhance their information technology skills.