Reviewerly/exHarmony huggingface dataset:
Disruption of Balaghah learning media during the Covid-19 pandemic in IAIN Tulungagung

Purpose of the study: The premise of this paper is to describe the disruption of the Balaghah learning media during the covid-19 pandemic in IAIN Tulungagung Methodology: It is a descriptive study with a qualitative approach. It represents two main descriptions such as the problems of online-based Balaghah learning for IAIN Tulungagung students and Balaghah learning media disturbances during the covid-19 pandemic in IAIN Tulungagung. Main Findings: The results showed that at the beginning of its implementation, many students well responded to this online class, however, after several times of the courses, many students experienced difficulties in learning. This situation reduces the quality of the teaching and learning process. Most students choose the learning process in the offline class because the students faced some problems while having an online class. The freedom provided, on the other hand, even distracts the students’ focus. The disruption of Balaghah learning media during the Covid-19 pandemic in IAIN Tulungagung is the shift from conventional to online-based media such as Zoom Meeting, Google Meet, Google Classroom, and WhatsApp Group. Novelty/Originality of this study: This research addressed the online learning problems of Balaghah for IAIN students, Tulungagung are the difficulty of receiving Balaghah learning materials related to words and sentences pronunciation, much subject matter that is too hard to understand, lack of student interest and motivation to learn, little time available, network quality in certain areas, as well as an environment that is less supportive of Balaghah learning. The disruption of the Balaghah learning media during the Covid-19 pandemic at IAIN Tulungagung is the use of various online media such as (1) Media with video conference features, Zoom Meeting and Google Meet, (2) Media with low capacity video conferencing features, WhatsApp Group, and (3) Alternative media, Google Classroom.
Recursion and Sequentiality in Categories of Sheaves.

We present a fully abstract model of a call-by-value language with higher-order functions, recursion and natural numbers, as an exponential ideal in a topos. Our model is inspired by the fully abstract models of O'Hearn, Riecke and Sandholm, and Marz and Streicher. In contrast with semantics based on cpo’s, we treat recursion as just one feature in a model built by combining a choice of modular components.
Data Collection Through Translation Network Based on End-to-End Deep Learning for Autonomous Driving

To avoid manual collections of a huge amount of labeled image data needed for training autonomous driving models, this paperproposes a novel automatic method for collecting image data with annotation for autonomous driving through a translation network that can transform the simulation CG images to real-world images. The translation network is designed in an end-to-end structure that contains two encoder-decoder networks. The forepart of the translation network is designed to represent the structure of the original simulation CG image with a semantic segmentation. Then the rear part of the network translates the segmentation to a realworld image by applying cGAN. After the training, the translation network can learn a mapping from simulation CG pixels to the realworld image pixels. To confirm the validity of the proposed system, we conducted three experiments under different learning policies by evaluating the MSE of the steering angle and vehicle speed. The first experiment demonstrates that the L1+cGAN performs best above all loss functions in the translation network. As a result of the second experiment conducted under different learning policies, it turns out that the ResNet architecture works best. The third experiment demonstrates that the model trained with the real-world images generated by the translation network can still work great in the real world. All the experimental results demonstrate the validity of our proposed method.
SISTEM INFORMASI PENGOLAHAN DATA NILAI SISWA: (Studi Kasus: SMK Taruna Bangsa Ciamis)

SMK Taruna Bangsa is a private school that has several departments, namely: NetworkCommunication Engineering, Light Vehicle Engineering, Motorcycle Engineering, Nursing,Pharmacy, and Office Automation and Governance. Web-based Student Value DataProcessing Information System is a system that provides information on student activenessreports online in the form of report values and information related to the student based on theweb, thus helping speed and quality in delivering information.The problem of this study is that there is often a delay in informing students of grades, thedelay in knowing the increase in students in each year, and the difficulty of printing examcards quickly. Therefore, in order to be able to answer the objectives of the study, it isnecessary to apply the PIECES analysis method. And the purpose of this study is toaccelerate in informing about academic differences between students, teachers, and parentsof students.Information system processing student value data, is an academic service intended forstudents, teachers and parents of students at Taruna Bangsa Vocational School in accessinginformation relating to academic records during the learning process. Teacher and studentinformation delivered includes student data information, teacher data information, valuedata, attendance, and exam card printing. even.Keywords: information systems, value processing, web
Medical Quora Tagging using MATAR and LDA Algorithm

Abstract The success of clustering or classification methods the detection of relevant textual formats is incredibly meaningful. The high dimensionality and irrelevance of textual materials was subjected to text records. Existing methods lack integration and are particularly vulnerable to original value. Metaheuristic algorithms are also applied to solve the challenges of standard classification algorithms. In this paper, an enhanced Latent Dirichlet Assignment clustering method &amp; Inter Modeling for Tag Suggestion rating system is documented to boost correlation - based &amp; identification efficiency to suggest labels with material modern web labels that promotes the exchange of medical information using unmonitored data through question-answering. For accurate tagging, Methods like POS marking, Hopping, Whistles&amp; Stopping words are being used for speech recognition. The efficiency of the evolved architectures is compared to the standard methods, by using specificity of the recommendation, defining features, sensitivity, plain word and speed. The findings reveal that the classification and grouping scheme of the proposed structure succeeds traditional textual record approaches.
SIGN LANGUAGE TO SPEECH CONVERSION

Humans communicate with one another in order to share their ideas, thoughts, and experiences with others around them. For deaf-mute individuals, however, this is not the case. Deaf-mute individuals can communicate thanks to sign language. A deaf-mute individual may communicate without the use of acoustic noises by using sign language. The goal of this project is to create a system for detecting sign language that allows individuals with speech impairments and normal people to communicate, thereby closing the communication gap. Hand gestures are essential because they convey the user's ideas in less time than other motions (arm, face, head, and body). A flex sensor-based gesture recognition module is being created in this project to identify a few phrases and broadcast them via a speaker.Dumb and deaf individuals make up a large portion of India's population. As a result, the system is developing a glove-based device for converting sign language (ASL) to voice. The fundamental system consists of two parts: recognition of sign language and conversion to text, followed by voice. The sign language glove is made up of basic hand gloves with flex sensors that track the amount of bend in the fingers. The sensors that vary the resistance based on the degree of bend on the sensor are known as flex sensors. The data from the sensors is sent to the CC3200 control unit. The analogue signals from the sensors are digitally translated and compared to the recorded value for sign recognition, after which the text is shown on the android smartphone. In addition, the text output is wirelessly sent to a cellular phone or a PC running test-to-speech software. We are currently working on a simple prototype that will translate basic Alphabets and numbers, which will be expanded for word recognition in the future.The primary goal is to convert sign language into text or voice. The framework enables speech-impaired people to communicate with the rest of the world via sign language. As a result, the intermediate person, who usually serves as a translator, is no longer required. By offering speech/text output for a sign gesture input, this would provide a user-friendly environment for the user.
PENGARUH FRAUD PENTAGON TERHADAP PERILAKU KECURANGAN AKADEMIK

The purpose of this study was to determine the effect of the fraud pentagon on academic fraud behavior. Collecting data in this study was carried out with a quantitative type of research by distributing questionnaires to 100 (one hundred) students. The data analysis method used is using multiple linear regression analysis. The results showed that the fraud pentagon had a positive and significant effect on academic fraud behavior. Partially there is a positive and significant effect of pressure on academic cheating behavior, there is an insignificant effect of opportunity on academic cheating behavior, there is an insignificant effect of rationalization on academic cheating behavior, there is a positive and significant effect on the ability of academic cheating behavior and there is positive and significant influence of ethics on academic deficiency behavior.
Σύγκριση της υλοποίησης εφαρμογών βάσεων δεδομένων με χρήση σχεσιακών (MySQL) και μη σχεσιακών συστημάτων διαχείρισης Βάσης Δεδομένων (MongoDB) και του Λογισμικού Διαχείρισης Περιεχομένου Wordpress

Databases are an integral part of modern programming. They are necessary for the creation of variousapplications that are used mainly in the professional field that require the storage and use of largeamounts of data. In this dissertation, an attempt was made to create three accommodation rentalapplications using the MySQL and MongoDB databases in order to assess which of these databases isconsidered the most suitable for use in such an application. It is aimed mainly at computer sciencestudents who can understand the implementation process in depth. The implementation of theapplications was done using the languages PHP plus HTML, JavaScript and Node.js plus HTML, whilethe Wordpress content management system was also used, which creates its own database.
Media Literacy in the Context of Foreign Language Education

Media literacy has become a significant aspect of modern educational process. However there are lots of contradictions in the field regarding its definition, methods and scale of its implementation. Most broadly media literacy is understood as an ability to search, analyze and create media content. As modern generation is considered to be digital natives the skill of searching the information are innate to them and should not be taught, so the concept of media literacy is mostly aimed at teaching the students to analyze information they obtain from mass media sources as well as creating their own content. Nowadays it is widely accepted that media literacy should be integrated into the educational system as cross-curriculum subject. This concept is reflected in numerous international and local documents. The most potent sphere that can be used as an example of successful media literacy implementation (though teachers not always have enough training and qualification in the sphere) is classes of English as foreign language as here usage of mass media materials has long been proved to be successful in teaching. The purpose of the paper is to examine the potential of media literacy project in Russian universities by exploring the opinion of EFL teachers on media literacy education and the way they implement it in the classroom. The study was conducted through a qualitative method by interviews with high school EFL teachers. The results of the research showed that the majority of EFL teachers limit media literacy to media critics which they understand as ability to withstand influential and manipulative forces of mass media as well as to identify fake information. Among the media literacy activities that were named are translation of printed articles and discussion of news broadcasts. It was underlined by the respondents that such activities enable to go beyond traditional forms of working with such materials (e. g. translation, summing up) and to engage students into discussion of tools the author uses to make the text more influential as well as the possible reasons for that. The findings emphasized the need for clear road map of media literacy project realization as well as lack of vocational courses and trainings for teachers in the sphere. At the same time the conducted research proved teachers’ positive attitude and awareness of the media literacy importance that suggests that media literacy in Russia has significant growth and development potential.
PENGARUH METODE PEMBELAJARAN CURAH GAGASAN (BRAIN STORMING) TERHADAP HASIL BELAJAR EKONOMI PESERTA DIDIK KELAS X IPS

The problems in the study are 1) the low student learning outcomes, 2) the learning process in the class is still passive 3) the use of less varied learning methods and 4) the brain storming learning method the teacher has not used at Tegineneng 2 Public High School when delivering lessons. The purpose of this study was to determine the effect of brainstorming methods on the economic learning outcomes of class X students. IPS the even semester of SMA Negeri 2 Tegineneng academic year The method used in this study is an experimental method because in this study the author teaches directly to the object under study using brain storming learning methods. The population in this study were all students of class X. ILPS Tegineneng 2 SMA 2 totaled 61 students, the sample consisted of two classes namely class X. IPS 1 and X. IPS 2, where class X. IPS 1 as an experimental class amounting to 30 students and class X. IPS 2 as a control class with 31 students. The sampling technique uses cluster random sampling technique. The instrument in this study used multiple choice tests and hypothesis testing in this study using the formula t test. Testing the hypothesis using the statistical formula t-test obtained t hit = 5.99 and the distribution table t at a significant level of 5% is known tdaf is t (1-1 / 2 α) = 2.00 so that it is proven t hit> t daf. Thus it can be concluded that there is the influence of brainstorming methods on the economic learning outcomes of class X students. IPS the even semester of SMA Negeri 2 Tegineneng in the academic year 2018/2019.
Communicating Science: Reform Model of the Gates Open Research Platform

The EU’s scientific potential is increasingly flowing into the world of new scientific knowledge. The object of this paper is the communication interpretation of the Open Science policy, covering not only access and storage of scientific information and preservation of scientific information, but communication aspects also. Purpose of the study: Establish modern trends in the scientific ecosystem oriented towards facilitating the publication and communication of scientific results. Tasks of the study: Compare new solutions in science communication models in the most popular platforms, and explore what is the alternative to traditional scientific journals. Methodology/approach: The qualitative systematic review (qualitative evidence synthesis),scientific criticism of sociological surveys, methods of analytic and synthetic processing of primary and secondary resources, secondary data analysis and overview of scientific publications available in the libraries worldwide, have been used to obtain data about the impact of new EU solutions: the European Road Map for development of the European Research Area (ERA),the European Strategy Forum for Research Infrastructures (ESFRI), the Organization for Economic Cooperation and Development, etc. A comparative analysis of innovation in publishing platforms was conducted with special attention to the Bill and Melinda Gates Foundation’s Gates Open Research platform. Results: The creators of the Gates Open Research platform defend the view of the rapid and socially beneficial effect of new and publicly-accepted scientific knowledge.The cutting-edge solutions are: transfer power from the hands of editors to the hands of the authors; minimize barriers or gatekeepers on the path of the new scientific outcome for society; assessment of the research not in view of the venue of publication but on the basis of the intrinsic value of the completed study; minimize the funds invested in publishing and dissemination. Implications: The conclusions can be important in identifying technological and ideological regularities for optimizing the model of scientific publications and increasing the speed and visibility of any scientific news.
Fast or efficient? Strategy selection in the game Entropy Mastermind

Author(s): Bertram, Lara; Elsaser, Florian; Feduzi, Albero; Gyarmathy, Zsofia; Kowalik, Weronika; Onojaife, Aaliyah; Elkaref, Mohab; Bentivegna, Eloisa; Nelson, Jonathan D. | Abstract: How do people acquire information and make decisions in an inherently complex world? We use the game Entropy Mastermind to investigate the cognitive strategies people adopt under various task conditions in situations characterized by high combinatorial complexity. N = 42 participants completed a total of 271 games, varying in incentive structure: In the speed condition, participants were incentivised for solving games quickly; in the efficiency condition, incentives were given for solutions requiring few problem solving steps; in the mixed condition, both speed and efficiency were incentivised. We found that participants adapted their problem solving strategies to the imposed constraints: In the speed condition simpler strategies were used, making feedback easy to interpret. Our results support the hypothesis that in complex environments people flexibly adjust their cognitive strategies to optimize the fit between situational requirements and their cognitive resources.
Probabilistic Message-Passing Control

There is insufficient current understanding of how to apply fully decentralized control to networks of sparsely coupled nonlinear dynamical subsystems subject to noise to track a desired state. As exemplars, this class of problem is motivated by practical requirements of creating decentralized power grids robust to cascade failures, the digital transformation of Industry 4.0 managing IoT connectivity reliably, and controlling transport flow in smart cities by computing at the edge. We demonstrate that an approach utilizing probability theory to characterize and exploit the uncertainty in locally received information, and locally optimized messages passed between neighboring subsystems is sufficient to implicitly infer global knowledge. Thus, control of a global state could be realized through decentralized control signals applied only to local subsystems using only local information without any reference to a global current state. Given a global system that can be decomposed into a set of locally coupled subsystems, we develop a theoretical method of probabilistic message passing and probabilistic control signals all interacting only at the subsystem level, but which promotes a system-wide convergence to a desired state. Our theoretical results are corroborated using computational experiments on a network of a 10-node partially coupled system decomposed into four separated subsystems with control inputs applied and determined at the subsystem level. Comparing the results with a centralized control method utilizing information from all the nodes to achieve global state convergence validates our hypothesis that local decentralized probabilistic control can be affected by the mechanism of local probabilistic message passing without needing access to global centralized information. We also provide a set of numerical experiments increasing the network size showing that the decentralized algorithm is independent of the global system size.
IMPLEMENTASI K-NEAREST NEIGHBOR UNTUK MENENTUKAN PREDIKSI PENJUALAN: (STUDI KASUS : PT MAKSIPLUS UTAMA INDONESIA)

Maksiplus Utama Indonesia is an MLM based company that produces and sells fertilizers. Maksiplus has many products spread in Indonesia. From some of these products sometimes there are some whose sales results are not as expected, and cause a lack of company profits. Management sometimes feels difficulty in determining whether product sales will rise or not. To help predict sales, a method that is able to provide alternative solutions is needed. The method used in this sales prediction is K-Nearest Neighbor. The system output is presented in the form of the calculation results from the K-Nearest Neighbor method. The results to be achieved in this study are companies can be helped in making decisions. From the output of the system in the form of numbers, it is expected to be easily understood and used as material for consideration by management in determining whether a product's sales will rise or not.   Keywords: sales predictions, K-Nearest Neighbor, Maksiplus.
ParsFEVER: a Dataset for Farsi Fact Extraction and Verification

Training and evaluation of automatic fact extraction and verification techniques require large amounts of annotated data which might not be available for low-resource languages.This paper presents ParsFEVER: the first publicly available Farsi dataset for fact extraction and verification.We adopt the construction procedure of the standard English dataset for the task, i.e., FEVER, and improve it for the case of low-resource languages.Specifically, claims are extracted from sentences that are carefully selected to be more informative.The dataset comprises nearly 23K manually-annotated claims.Over 65% of the claims in ParsFEVER are many-hop (require evidence from multiple sources), making the dataset a challenging benchmark (only 13% of the claims in FEVER are many-hop).Also, despite having a smaller training set (around one-ninth of that in Fever), a model trained on ParsFEVER attains similar downstream performance, indicating the quality of the dataset.We release the dataset and the annotation guidelines at https://github.com/Zarharan/ParsFEVER.