Reviewerly/exHarmony huggingface dataset:
GAME-BASED APPLICATIONS TO ENHANCE STUDENTS’ ENGAGEMENT AND PERFORMANCE

The study aimed to determine the effect of game-based applications on engagement and performance of selected Grade 9 students of Looc Integrated School, Calamba City, School Year 2021-2022.It determined the students' perception on the attributes of game-based applications, level of students' engagement and the significant effect of game-based applications on students' engagement and performance.Experimental design of research was used in this study in gathering the necessary data.The researcher used a self-made pre-test and post-test and a survey questionnaire as the main instrument of the study.The data gathered were treated using appropriate treatments which are Mean, Standard Deviation, Percentage and Paired t-test.Based on the data gathered, the students perceived that the use of game-based applications was very effective, and the attributes are very appropriate.The level of engagement of the students was rated very high.The test of difference between the pre-test and post-test of the respondents resulted to rejecting the null hypothesis which implies that there is a significant difference on the performance of students.Moreover, it showed how the game-based applications significantly affect the students' engagement.The game-based applications significantly affect the engagement of students in terms of their participation and self-regulation but does not significantly affect the students' engagement in terms of their attitude towards games, focus and attention and task orientation.It can also be concluded that game-based applications have significant effect on students' performance.The researcher highly suggests the continuous use of game-based applications in online classes since teachers in the new normal education must be innovative and creative in their classes.The use of game-based applications can motivate students and can be used as an engaging way to start a class.The researcher also recommends the use of game-based applications to other learning areas and lessons.
EFIKASI DIRI DAN MOTIVASI BERPRESTASI DALAM PEMBELAJARAN BERBASIS ONLINE SELAMA MASA PANDEMI COVID-19

Throughout the Covid-19 pandemic, many students skilled a decrease in achievement motivation. where they feel much less confident in the abilities they have. This research pursuits to find out the connection between self efficacy and motivation to excel in online based learning at some point of the pandemic in Binjai state high school students. The observe used quantitative techniques, with a sample quantity of 182 students, using proportionate random sampling strategies. data collection uses the self-efficacy scale and the achievement motivation scale. This research data changed into analyzed using regression analysis and determined a positive relationship among self-efficacy and 3.8 percent fulfillment motivation. This shows that self efficacy has a role in increasing the motivation to excel in Binjai state high school students in online based studying in the course of the covid-19 pandemic.
Characteristics of Eye Movements during Musical Expression in Early Childhood by Tonality: Through Quantitative Analysis by Eye Tracking

Early childhood children frequently use body movements while singing songs accompanied to the music. When trying to express the recognition of musical elements by body movement, the child in early childhood creates his own musical expression by thinking and judging while looking at the surrounding children and the accompaniment teacher. This study aims to quantitatively analyze changes in eye movements during musical expression. 3-year-old, 4-year-old, and 5-year-old children at two nursery schools in 2020 and two kindergartens in 2021 (n=118) participated in eye tracking during singing a song using an eye tracker (Tobii3). Quantitative analysis by three-way ANOVA was mainly conducted on the calculated data. As a result, the increase in data such as number of saccade occurrences and size, and the moving average velocity of saccade, showed that saccades during musical expression in early childhood tended to be larger in major key than in minor key. From the calculated data on saccade, which is the eye movement during musical expression, it was predicted that effective feature quantities of eye movement during musical expression for machine learning could be derived in the same way as feature quantities depended on the results of quantitative analysis of body movement during musical expression.
The Lighter The Better: Rethinking Transformers in Medical Image Segmentation Through Adaptive Pruning

Vision transformers have recently set off a new wave in the field of medical image analysis due to their remarkable performance on various computer vision tasks. However, recent hybrid-/transformer-based approaches mainly focus on the benefits of transformers in capturing long-range dependency while ignoring the issues of their daunting computational complexity, high training costs, and redundant dependency. In this paper, we propose to employ adaptive pruning to transformers for medical image segmentation and propose a lightweight and effective hybrid network APFormer. To our best knowledge, this is the first work on transformer pruning for medical image analysis tasks. The key features of APFormer mainly are self-supervised self-attention (SSA) to improve the convergence of dependency establishment, Gaussian-prior relative position embedding (GRPE) to foster the learning of position information, and adaptive pruning to eliminate redundant computations and perception information. Specifically, SSA and GRPE consider the well-converged dependency distribution and the Gaussian heatmap distribution separately as the prior knowledge of self-attention and position embedding to ease the training of transformers and lay a solid foundation for the following pruning operation. Then, adaptive transformer pruning, both query-wise and dependency-wise, is performed by adjusting the gate control parameters for both complexity reduction and performance improvement. Extensive experiments on two widely-used datasets demonstrate the prominent segmentation performance of APFormer against the state-of-the-art methods with much fewer parameters and lower GFLOPs. More importantly, we prove, through ablation studies, that adaptive pruning can work as a plug-n-play module for performance improvement on other hybrid-/transformer-based methods. Code is available at https://github.com/xianlin7/APFormer.
An efficient dynamic access control and security sharing scheme using blockchain

This study seeks to understand the role of institutions and organizations that have used cloud service providers to store and share data as ensuring third-party access to storage is a major challenge to avoid data theft and unwanted access. Hence, in this paper, Blockchain-Based Data Access and Secure Sharing Method (BDASS) is introduced to enhance security processes related to personal data through data access control and secure sharing method, the proposed method uses blockchain aggregation, file system (IPFS), dynamic access control (DAC), and ciphertext-attribute-based encryption (CP-ABE) to enhance the security of personal data. To keep the owner safe, a blockchain-based DAC is designed. To keep data storage and sharing secure, the blockchain-based CP-ABE is designed. In this proposed methodology, the data owner encrypts the data they have stored in IPFS, thus enhancing data security, which has been improved with the help of CP-ABE regarding detailed access policy and data owner. Policy parameters are managed by the DAC. In the proposed methodology, the data owner uses the blockchain to control security and access to the data. Finally, the paper has come up with a set of findings in order to achieve data security and access control for the data owner through the blockchain-based approach. To evaluate the performance of the proposed method, MATLAB was used. The proposed technology also contrasts with existing technologies, such as the Blockchain-Based Security Sharing Scheme for Personal Data (BSSPD) as well as the Rivest-Shamir-Adleman Algorithm (RSA) and Elliptic Curve Cryptography (ECC).
Professor Plucky

When people play music together, they move their bodies, and that movement plays an important role in the activity of group music making. In contrast, when robots play music with people, the robots are usually stiff and mechanical in their movement. In general, it is not well understood how the movement of such robots affects how people interact with them, or how the robot movement should be designed in order to promote certain features of interaction. As an initial exploration into these questions, we built a prototype guitar plucking robot that plucks the strings with either a) kinetic plucking mechanisms that are designed to have visually appealing movement, or b) control plucking mechanisms that do not visually move. In a pilot study we found that when guitarists play with the robot, they move their hands more and look at the robot more when it uses the kinetic mechanisms as opposed to the control ones. However, they do not report preferring the kinetic mechanisms. These preliminary findings suggest some very clear hypotheses for future followup studies.
LEARNERS STRESSORS AND COPING MECHANISM AMIDST PANDEMIC: A BASIS FOR INTERVENTION PLAN

The emergence of the novel coronavirus (COVID-19) pandemic disrupted all economic and social activities around the world.Undoubtedly, the period has been stressful for everyone including the learners.This study determined the significant relationship between the learner's stressors and coping mechanisms amidst pandemic of the students of Pulong Sta.Cruz National High School, School Year 2021-2022.Based on the finding of the study, The extent of learner's stressors amidst the pandemic resulted in High.However, the level of their preferred coping mechanism was Low during the pandemic.The relationship between the demographic profile and the coping mechanism was significant.Likewise, the relationship between the learner's stressors and coping mechanisms was substantial.This implies a need for an intervention plan to address the issue regarding the learner's stressor amidst the pandemic.Therefore, the null hypothesis "There is no significant relationship between learner's profile and coping mechanisms" and "There is no significant relationship between learner's stressors and coping mechanisms" is rejected.Thus, this calls for the acceptance of the alternative, which incites that there is a significant relationship between the two.Parents, Teachers, and school administrators may collaborate to provide activities for the learners that will reduce their stress.
A Content Analysis of Integrated Learning Skills &amp; Assessment in The Textbook Entitled “Grow with English” For the Sixth Grade of Elementary School

Textbook helps the teachers to prepare the lessons. It is also course book used by teachers and students in order to facilitate the teaching – learning process. In terms of its role in learning, it is crucial in teaching and learning process. Related to textbooks, there should be covered by all learning skills and assessment in order to help the students to improve their ability in learning English. This research is aimed (1) to analyze all four learning skills in the textbook, (2) to find out the way four learning skills are implemented, (3) to investigate whether the textbook provides the assessment for students or not in the textbook Entitled “Grow with English” for The Sixth Grade of Elementary School. This research is included as qualitative research design. The sample of this research is an English textbook entitled “Grow with English”. The researcher uses the checklist as the instrument. In collecting and analyzing the data, the researcher does several steps. After that, the data would be calculated by using a formula. The results show that the textbook provided all learning skills differently. For the assessment, it was found that the textbook provided assessment every three chapters. In conclusion, the authors of English textbooks should implement all learning skills every chapter and the assessment at the end of every chapter in the textbooks
Towards Methods and Tasks of the Digital Indology

The article describes the state of affairs and prospects for research and development in the domain of active use of digitalization and computer programming in the study of the Indian intellectual tradition. The term “Digital Indology” is used this term as an analogy of the expression “Digital Humanities”. Here, it will be understood as the reception and study of philosophical and other classical texts of Ancient and Medieval India with the usage of digital technologies, mathematical statistics, contextual analysis methods alongside with the traditional well-established approaches of philosophy and the humanities. The main trends in the development of digital philosophical Indology are being outlined (viz. the formation of a unified computer database of Indian classical texts, the development of special programs that allow setting and solving new pertaining to the content, as well as historical tasks in the study of various texts of various groups, etc.) The use of mathematical statistics and the methods of contextual analysis are suggested as typical auxiliary methods while analyzing classical texts of India. We do not close our eyes to the possible hidden dangers of a possible fascination with digital methods. Our brief manifesto of Digital Philosophical Indology is to define it exclusively being tool for classical Indological research, which retain its specific philosophical objectives and goals.
On the Robustness of Dialogue History Representation in Conversational Question Answering: A Comprehensive Study and a New Prompt-based Method

Most works on modeling the conversation history in Conversational Question Answering (CQA) report a single main result on a common CQA benchmark. While existing models show impressive results on CQA leaderboards, it remains unclear whether they are robust to shifts in setting (sometimes to more realistic ones), training data size (e.g. from large to small sets) and domain. In this work, we design and conduct the first large-scale robustness study of history modeling approaches for CQA. We find that high benchmark scores do not necessarily translate to strong robustness, and that various methods can perform extremely differently under different settings. Equipped with the insights from our study, we design a novel prompt-based history modeling approach, and demonstrate its strong robustness across various settings. Our approach is inspired by existing methods that highlight historic answers in the passage. However, instead of highlighting by modifying the passage token embeddings, we add textual prompts directly in the passage text. Our approach is simple, easy-to-plug into practically any model, and highly effective, thus we recommend it as a starting point for future model developers. We also hope that our study and insights will raise awareness to the importance of robustness-focused evaluation, in addition to obtaining high leaderboard scores, leading to better CQA systems.
Pelatihan Hypermedia Berbasis Virtual Reality Bagi Guru Guru MAN 2 Kudus

This Community Service Activity (PKM) aims to; (1) provide an introduction to teachers at MAN 2 Kudus regarding Virtual Reality learning media as an alternative IT-based learning media and (2) train MAN 2 Kudus teachers to be able to utilize Virtual Reality-based learning media. The methods applied in this service program are the presentation method, the demonstration method, and the practical method. The presentation method is applied in the introduction of hypermedia software using the millelab application, its benefits, and its application in making virtual reality-based media, demonstration methods regarding program operations and practical methods where teachers practice directly making learning media according to their respective subjects with the use of media-based virtual reality.&#x0D; Keywords: Virtual Reality, Technological Innovation, Covid 19 Pandemic
PENGARUH MODEL COOPERATIVE INTEGRATED READING AND COMPOSITION (CIRC) PADA PEMBELAJARAN DARING TERHADAP KEMAMPUAN KOMUNIKASI MATEMATIS SISWA DITINJAU DARI KEMAMPUAN AWAL MATEMATIKA SISWA

The implementation of this study aims to assure the effect of CIRC learning model on students mathematics communication ability based on prior knowledge. The design of reseach is quasi-experimental design with the population is all students in MTsN District of Cakung Academic Year 2020/2021. The research sample chosen by multisage random sampling is students of class VIII-1 MTsN 20 and VIII-2 MTsN 28 as the experiment class and class VIII-2 MTsN 20 and VIII-1MTsN 28 as the control class. Average value mathematics communication ability of the students in experiment class 14.38 and control class 11.35. Based on data interpretation and analysis t-test with a significant value (α) = 0,05, the value is Sig = 0.049, so that Sig &amp;lt; α. With these results it was concluded that there was an effect of the CIRC learning model on the mathematical communication ability of class VIII MTsN students in Cakung District
The Objective Aspect of Online Scam in the Saudi Regulations in Comparison with Egyptian and Kuwaiti Laws

This study deals with the objective aspect of online scam according to Saudi regulations compared to Egyptian and Kuwaiti laws. The study showed that online scam is among financial crimes committed using information systems. The number of online scams has increased as a result of daily use of websites and the widespread use of credit cards in purchases and money transfers. In the face of the increase in online scams, the Saudi regulator and other Arab legislators realized the seriousness of this offence, and therefore have attached paramount importance to develop appropriate solutions to address this crime through the enactment of laws aimed at combating them. In conducting the study, the researcher adopted the comparative analytical descriptive approach. The study comprised two chapters. In the first chapter, the researcher elaborated on various topics such as the nature of online scam, relevant legal issues, similarities and differences between online scam and traditional fraud, and types of online scam. The second chapter explored the financial and moral elements of online scam and its prescribed penalties. The study yielded numerous findings, the most prominent of which are: online scam is increasing daily due to the diversity of scam methods utilizing current technological development and the difficulty in tracing offenders, in addition to the growing number of websites and misleading advertisements. Lastly, the study recommends concluding joint agreements between Arab legislators to combat online scam and to cooperate in the intensification of efforts to arrest offenders.
Factor Analysis for Increasing Reading Literacy in Indonesia

Low interest in reading is a problem for our nation that must be solved, because Indonesia to occupy second position from bottom in terms of literacy. Most of the provinces in Indonesia are at low literacy activity levels and none of the provinces are included in the high literacy activity level. The lack of interest in reading can be influenced by many factors. Access of supporting resource where people get literacy materials, such as libraries, bookstores, and mass media, how people to get the information technology, and media devices to access literacy materials are the factor that can be affect the interest of reading. Literacy is one of the important cultures for a country. That is because the culture is able to influence the intelligence and well-being of a country's life. So the study aims to see what factors affect to increasing the literacy reading in the provinces in Indonesia. This study uses k-means clustering before applying factor analysis. Based on k-means clustering, two clusters are formed and showed one of the cluster showed that the second cluster is the provinces that have the highest number of library’s facilities. In addition based on the analysis factor in each cluster, two factors were formed, namely the standard factor for reading literacy levels and supporting the facilities for reading literacy. It can be concluded that the way to increase reading literacy in two clusters of the area in Indonesia are by increasing the standard of reading literacy level and supporting the facilities for reading literacy.
An Improved Knowledge Graph Question Answering System for English Teaching

Knowledge graph, as a structured semantic knowledge base, has become an essential foundation for artificial intelligence applications with its flexible composition structure and rich semantic representation capability. This paper combines the knowledge graph embedding scoring algorithm with the link scoring algorithm to effectively solve the problem of missing answers in the current knowledge graph embedding question and answer method. This method constructs a query link while searching for the best answer and gives the answer set through the query, which effectively alleviates the omission of answers in the existing methods. The experimental results show that the F1 score of the English teaching test system on the data set is 86.85%, where the answer selection method weakly relies on a priori information such as predicates in the test data and can be trained on a test pair data set without human intervention, with good generalization performance.
Research on Image Retrieval Optimization Based on Eye Movement Experiment Data

Satisfying a user's actual underlying needs in the image retrieval process is a difficult challenge facing image retrieval technology. The aim of this study is to improve the performance of a retrieval system and provide users with optimized search results using the feedback of eye movement. We analyzed the eye movement signals of the user’s image retrieval process from cognitive and mathematical perspectives. Data collected for 25 designers in eye tracking experiments were used to train and evaluate the model. In statistical analysis, eight eye movement features were statistically significantly different between selected and unselected groups of images (p &lt; 0.05). An optimal selection of input features resulted in overall accuracy of the support vector machine prediction model of 87.16%. Judging the user’s requirements in the image retrieval process through eye movement behaviors was shown to be effective.
Data Mining of The Grouping And Mapping of The Health Centers in Sleman Regency With K-Means Clustering Algorithm

This research which is a grouping and mapping system of Puskesmas (public health center) is one solution to obtain information related to areas that have adequate Puskesmas services. With the help of a geographic information system, it is able to describe the state of the Sleman district based on the availability of health centers per sub-district. In a geographic information system, the information produced is in the form of visual images that make it easier for the public to read the information provided. This study uses data from health workers who work in health centers and were grouped first using the k-means method. The reason for grouping them first was to make it easier to map the existing health centers, while the K-means method was chosen because it has a high accuracy to the size of the object, so this algorithm is relatively more scalable and efficient for processing large numbers of objects. In addition, the K-Means algorithm is not affected by the order of objects.