Reviewerly/exHarmony huggingface dataset:
Efektivitas Model Reading Questioning and Answering (RQA) dalam Pembelajaran Online terhadap Kemampuan Kognitif Siswa pada Mata Pelajaran IPA Terpadu

This study aims to determine the effectiveness of the Reading Questioning and Answering (RQA) learning model in online learning on student learning outcomes. The method used is a quantitative quasi-experimental design with a non-equivalent control-group pre-test/post-test design. The research sample was taken by purposive sampling of the eighth grade students of SMPIT An-Nida' Lubuklinggau. The online learning media used is WhatsApp with data collection instruments in the form of cognitive learning outcomes tests with 20 multiple choice questions. The results showed that there was a significant effect of the RQA learning model in online learning on improving student learning outcomes in Integrated Science subjects at SMPIT An-Nida' Lubuklinggau. In conclusion, the RQA learning model is effective in improving student learning outcomes online in Integrated Science subjects at SMPIT An-Nida' Lubuklinggau.&#x0D; Keywords: Cognitive Learning Outcomes, Online Learning, RQA, WhatsApp
An Efficient Approach For Sustainable Agricultural Trading Using Blockchain Technology

The introduction of Blockchain Technology in the human world has brought different disruptions to the traditional systems in an aspect to increase efficiency, traceability, transparency, reliability, and so on. Agriculture is one of the main areas where Blockchain has rooted its nerves and giving profound results. Integration of Information and Communication Technology (ICT) in the agriculture sector has converted traditional agriculture into E-agriculture helping farmers in managing agriculture-related activities for maximizing gain out of daily agriculture labor. However, current centralized systems have their problems causing farmers to lose their efforts along with the security challenges. Besides, these systems do not show fair trading practices to the consumers because of the middle entities. Hence, this study proposes a new methodology using blockchain as its backbone to fix most of the problems occurring in the current centralized systems. The proposed model has given the focus on farmer’s and consumer’s benefits by eliminating middle entities with their charges. It aims to increase the transparency, security, trust, in agriculture activities, reliability among agriculture stakeholders, and farmer’s income through fair trading of produced agricultural products and promoting their efforts.
An insight into crypto world, regulation &amp; framework in India

In general, cryptocurrency can be considered a medium of exchange in digital format only.It is pertinent to note here that Cryptocurrency uses encryption techniques to control and create monetary units and verify money exchange.As a result of the fast improvement of data and correspondence advancements, numerous exercises in our routine have been combined on the web and become more adaptable and robust.An immense development in several online users has enacted virtual word ideas and made another business peculiarity: a cryptocurrency to work with monetary exercises like purchasing, selling, and exchanging.The usage of virtual money has become all over in different structures.Virtual cash isn't controlled and coordinated; along these lines, most countries have not yielded this money in their financial activities.This paper plans to dissect the explanations for the fame of cryptographic funds all over the planet with specific accentuation on India; the paper harps on the legitimateness of digital money in India while contrasting the situation in far off nations; in the last option part, the paper manages moves approaching for the public authority to direct this virtual cash.
Teknik Elisitasi Kebutuhan Perangkat Lunak: Literatur Review

The selection of software requirements elicitation techniques is very important for organizations as the first step in the software development process. This study is motivated by the existence of problems, where the organization does not understand the type of software being developed, so it is difficult to determine the right need elicitation technique. In this study, a literature review was used by collecting existing studies. Used 17 studies related to the discussion of elicitation techniques used. This study aims to review previous studies so as to produce recommendations for software requirements elicitation techniques. Based on the study, it can be concluded that interview, prototyping and JAD are most often used in software projects. In addition, for the small-medium scale software projects, more use of interviews, JAD, and ERD-based specifications. Meanwhile, the large-scale software projects involve more stakeholders with elicitation techniques such as group discussions, interviews, and parallel discussions to find joint solutions.
Learning Boost by Exploiting the Auxiliary Task in Multi-task Domain

Learning two tasks in a single shared function has some benefits. Firstly by acquiring information from the second task, the shared function leverages useful information that could have been neglected or underestimated in the first task. Secondly, it helps to generalize the function that can be learned using generally applicable information for both tasks. To fully enjoy these benefits, Multi-task Learning (MTL) has long been researched in various domains such as computer vision, language understanding, and speech synthesis. While MTL benefits from the positive transfer of information from multiple tasks, in a real environment, tasks inevitably have a conflict between them during the learning phase, called negative transfer. The negative transfer hampers function from achieving the optimality and degrades the performance. To solve the problem of the task conflict, previous works only suggested partial solutions that are not fundamental, but ad-hoc. A common approach is using a weighted sum of losses. The weights are adjusted to induce positive transfer. Paradoxically, this kind of solution acknowledges the problem of negative transfer and cannot remove it unless the weight of the task is set to zero. Therefore, these previous methods had limited success. In this paper, we introduce a novel approach that can drive positive transfer and suppress negative transfer by leveraging class-wise weights in the learning process. The weights act as an arbitrator of the fundamental unit of information to determine its positive or negative status to the main task.
Machine learning approaches for biological function and dynamics

Without any doubt, revolutionary progress has been made with Alphafold2 and RoseTTAfold in predicting static structures.However, biological function involves structural changes, as they occur for example in molecular machines and in the presence of ligands.Data-analytic algorithms based on Geometric Machine Learning made it possible to retrieve continuous conformations and free-energy landscapes from experimental cryoEM single-particle snapshots in thermal equilibrium.However, to understand biological function and dynamics, we need to include the underlying energetics of pathways away from thermal equilibrium.For such non-equilibrium processes, the functional pathways are timedependent and regulated by the environmental protocol.Recent advances with Physics-Informed Neural Networks (PINN) allow to incorporate fundamental laws of Physics and Chemistry and consequently require much less data for Machine Learning.Based on these promises, we propose a conceptional data-algorithmic framework, capable of extracting the dynamics from sparse non-equilibrium timeresolved measurements and to retrieve functional pathways for any choice of environmental protocol.
Blender, a free tool to import data from all fields of crystallography and export to the virtual and physical space

Blender is a free, open-source software that provides one of the most powerful and accessible means for 3D model manipulation.Blender itself is capable of importing over 12 different 3D file formats, including both .xyz's(a common chemistry file type) and .pdb's(protein data bank files).Many crystallographic software packages, including Vesta, Crystal Maker, Olex, ShelXle, Mercury, and Diamond, natively export blender compatible files.Blender can then be used to make any final visual corrections before exportation.The exported files can be imported and visualized directly with PowerPoint365, uploaded to online distribution platforms like Sketchfab to offer inbrowser viewing, built into augmented reality applications for smart phones, or used as instruction files for 3D printing.By making use of Blender's free features, a crystallographer can take almost any set of data and turn it into an aesthetically pleasing form that can be shared with almost anyone.
Mobile Game-Based Learning Application about Semai People

The current platform for cultural education that teaches about indigenous people lacks a sufficient element of gamification and cultural preservation.The main objective of this research project is to develop a mobile game-based learning application of Kenali Semai through the digital platform by applying gamification elements.This mobile game-based learning application would be aimed at the public to pique their interest in learning about Semai's cultural element while playing games and the application uses the Malay language for the content.The methodology adopted is the Digital Educational Game Life Cycle (DEG) which consists of four processes; (i) game design, (ii) software design, (iii) implementation and publishing, and (iv) game-based learning and feedback.A few gamification elements were embedded, and the mobile game-based learning application was developed using Construct 2 and Android Studio and deployed using Google Play Store.As for future works, it is suggested to enhance to iOS platform so that can increase the number of users and improve the feature of the Kenali Semai mobile game-based learning application.
Analyzing Methods for Generating Feedback Comments for Language Learners

Feedback comment generation is the task of generating explanatory notes for language learners. Although various generation techniques are available, little is known about which methods are appropriate for this task. Nagata (2019) demonstrates the effectiveness of neural-retrieval-based methods in generating feedback comments for preposition use. Retrieval-based methods have limitations in that they can only output feedback comments existing in the given training data. Besides, feedback comments can be made on other grammatical and writing items other than preposition use, which has not yet been addressed. To shed light on these points, we investigate a wider range of methods for generating various types of feedback comments in this study. Our close analysis of the features of the task leads us to investigate three different architectures for comment generation: (i) a neural-retrieval-based method as a baseline, (ii) a pointer-generator-based generation method as a neural seq2seq method, (iii) a retrieve-and-edit method, a hybrid of (i) and (ii). Intuitively, the pointer-generator should outperform neural-retrieval, and retrieve-and-edit should perform the best. However, in our experiments, this expectation is completely overturned. We closely analyze the results to reveal the major causes of these counter-intuitive results and report on our findings from the experiments, which will lead to further developments of feedback comment generation.
New Results on the Reconstruction of Permutations Distorted By Single Kendall <i>τ</i>-Errors

The reconstruction problem for permutations on <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> elements from their erroneous patterns which are distorted by single Kendall τ-errors was presented by Konstantinova et al. in 2007. To date, some authors solved some cases where the transmitted permutation can be arbitrary and the erroneous patterns are distorted by at most two or three Kendall τ-errors. In this paper, we study the setup where the transmitted permutation on <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> elements can be arbitrary and the erroneous patterns are distorted by at most four Kendall τ-errors. In this scenario, it is shown that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> - <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> -3/3 erroneous patterns are needed to reconstruct an unknown permutation from an arbitrary unknown permutation for any <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> ≥ 9.
Progress in quantum networks

Once a distant dream, quantum networks are very much a present reality, with an exciting future.
Design and Practice of Linux Curriculum Reform Based on PBL And Its Ideological and Political Teaching

In order to solve the problems of the low teaching quality of Linux operating system courses, the disconnection between the teaching content and the needs of enterprises, and the difficulty in effectively integrating the ideological and political content, this paper takes the course "Linux Principles and Applications" as the research object, reflects on the current teaching status and refers to the teaching objectives, and proposes Taking the PBL teaching method as the core, highlighting the project orientation, moisturizing things silently into the ideological and political education, and a student-oriented teaching model. Divide project tasks according to course knowledge points, run them through the entire learning process, build a teaching system that integrates course projects with ideology and politics, and effectively cultivate students' practical ability, innovation ability, professional quality and positive and optimistic psychological quality. Selecting the 15 experimental class and 16 control class of software engineering major in a private application-oriented university to form a comparison, and using SPSS 22 software to analyze the pre- and post-test scores of the experimental class and the control class, the results show that the curriculum based on the PBL teaching method is adopted. The learning effect of students in the ideological and political teaching mode has been significantly improved.
Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. 1. Type of peer review: Single anonymous 2. Conference submission management system: Morressier 3. Number of submissions received: 192 4. Number of submissions sent for review: 158 5. Number of submissions accepted: 63 6. Acceptance Rate (Submissions Accepted / Submissions Received × 100): 39.9 % 7. Average number of reviews per paper: 2.02 8. Total number of reviewers involved: 109 9. Contact person for queries: Name: Dr. Damodar Panigrahy Affiliation: Assistant Professor, Department of ECE, SRMIST, Kattaknulathur Email: damodarn@srmist.edu.in
Flexible Multi-task Networks by Learning Parameter Allocation

This paper proposes a novel learning method for multi-task applications. Multi-task neural networks can learn to transfer knowledge across different tasks by using parameter sharing. However, sharing parameters between unrelated tasks can hurt performance. To address this issue, we propose a framework to learn fine-grained patterns of parameter sharing. Assuming that the network is composed of several components across layers, our framework uses learned binary variables to allocate components to tasks in order to encourage more parameter sharing between related tasks, and discourage parameter sharing otherwise. The binary allocation variables are learned jointly with the model parameters by standard back-propagation thanks to the Gumbel-Softmax reparametrization method. When applied to the Omniglot benchmark, the proposed method achieves a 17% relative reduction of the error rate compared to state-of-the-art.
Population Density Cluster Analysis in DKI Jakarta Province Using K-Means Algorithm

This study aims to analyze clusters based on the area and population density of the area and population density of the area in DKI Jakarta Province in 2015 using the data mining method by clustering as the first step in planning for population equality. The subject of analysis in this study is a village located in the province of DKI Jakarta which is recorded based on the area and population density in each sub-district until 2015 with several stages, namely data understanding, data processing or cleansing, cluster tendency assessment, clustering, cluster review. From this study, the results were obtained that the data tended to be clustered because the statistical value of Hopkins was close to the value of 0 and in VAT there was a vague picture of clusters that might be formed. Based on this, cluster creation is carried out using the K-Means Algorithm. Based on the results, there are 3 clusters formed, namely cluster 0 (not densely populated), cluster 1 (medium population density), and cluster 2 (densely populated). These results can be used as a basis for policy making in population management.
ORGANIZATIONAL CONTEXT AND PERFORMANCE EVALUATION PROCESS REACTION: A STUDY OF TELECOM SECTOR EMPLOYEES OF ISLAMABAD

The present study scrutinizes the relationship among organizational context (job resource adequacy, co-worker relationship and organizational communication) and performance evaluation process reaction through moderation of procedural justice in the telecom sector of Islamabad, Pakistan. The cross-sectional survey is conducted through adaptation of structured questionnaire as a primary source of data collection. A structured questionnaire was floated among 192 employees working in telecom sector. The study expands on applicable research in this region and stretches out the research in the Pakistani context. To test the hypotheses, multivariate analysis, descriptive statistics, correlation, factor analysis and linear regression is used to analyze the impact, Structured Equation Modeling (SEM) is used to identify multiple relationship effects. The structural model was assessed by using Smart PLS 2.0. The study reveals that reactions to performance evaluation process are positively and significant associated with the independent variables, job resource adequacy, organizational communication and co-worker relationship.
Grafologi Mahasiswa pada Praktikum Zoologi Vertebrata

This study aims to determine the relationship between graphology learning outcomes and practical learning outcomes for the Department of Biology Education students. The method used is a complete report of the Vertebrate Zoology practicum as a sample of student handwriting and then analyzed using a graphological assessment instrument. The results showed that the value of the correlation coefficient or rxy obtained was 0.769. This value means that the higher the analysis of graphology results, the higher the learning outcomes of the Vertebrate Zoology practicum for Biology Education Department students. In conclusion, there is a solid relationship between the analysis of graphology results and the Vertebrate Zoology practicum learning outcomes in the Department of Biology Education, Maros Muslim University.&#x0D; Keywords: Graphology, Learning Outcomes, Practicum
Trash-Talking Pemain Mobile Legends: Bang Bang Mahasiswa FKIP UNS

In this digital era, the development of online games in the world is increasing. The most popular online game in Indonesia is Mobile Legends: Bang Bang. One of the things that stands out in the game Mobile Legends: Bang Bang is the occurrence of trash-talking behavior. The purpose of this study is to find out the meaning of trash-talking players in Mobile Legends: Bang Bang. The method used is descriptive qualitative research method. The research data were collected using the participant observation method. The data sources in this study were 5 participants, determined using a purposive sampling technique with the criteria that FKIP UNS students were actively playing the online game Mobile Legends: Bang Bang. The data analysis technique in this study used the equivalent method. The results showed that the type of trash-talking was divided into four categories, namely the category of intelligence/intelligence including: pekok, tolol, noob, goblok, beleguk, kehed and pe’ak. Sexuality categories include: lee, sangean, ngentot and pepek. The category of disgusting animals is in the form of animal names such as: babi, asu and anjing. The general categories are cuk, lol, fuck, dancok, najis, bangsat, modar, bajingan and bacot. The meaning of trash-talking seen from the situation that occurs is divided into two, namely positive and negative meanings. Positive meaning occurs when trash-talking presents a pleasant situation such as breaking the atmosphere, as a symbol of intimacy, giving a humorous effect and motivating players. The negative meanings occur when trash-talking presents toxic behavior such as annoyance, anxiety, expressions of anger, humiliation and disappointment of the players. Trash-talking in the online game Mobile Legends: Bang Bang is a form of cultural expression as part of local wisdom that characterizes the players' regions of origin.
Motivational strategies in the teaching process

It could be said that metacognition is a topic that has much to contribute in the learning processes at different ages of students, there are motivational strategies that affect the development of learning in children and adolescents , is an investigation that can be developed and contribute different elements depending on the conditions in which the entities studied are shown, the objective of the work is to be able to analyze metacognition and motivational strategies that allow personal development in children, adolescents and different levels of teaching, the bibliographic search was used to know how metacognition behaves at different ages and behavior of students, in addition to the inductive-deductive and historical method where it is valued how it has evolved as new tools and strategies are found in its evolutionary process. It was obtained as a result that metacognition and motivational strategies can be used in teaching-learning processes at different levels and in many cases even in companies that use it to meet their plans and objectives.
Mathematics teacher's ability in inclusion school made learning media with Canva application

Covid 19 has had a massive impact on education, especially in the teaching and learning process. Teachers must rack their brains in delivering teaching materials to students. Therefore, teachers need to learn about applications that are easy and can be accessed quickly by students. Applications that are trained on teachers to create learning media are the Canva application. This research aimed to describe the mathematics teacher's ability to make a learning media using Canva Application. This research method is qualitative research. The research subjects consisted of seven mathematics teachers who teach in inclusive schools at the junior high school level in Surabaya. The research instruments were observation sheets and questionnaire sheets. The results obtained are as follows: able to master mathematics well; able to master the standard of competence and basic competence of mathematics subjects well; able to develop mathematical material creatively; active in school-level professional activities; able to utilize information and communication technology to communicate and establish themselves.