Reviewerly/exHarmony huggingface dataset:
FORMATION OF SPEECH SKILLS IN ONLINE TEACHING RUSSIAN AS A FOREIGN LANGUAGE

From the point of view of the current state of the methodology of teaching a foreign language, mastering a foreign language occurs if the foreign speaker has developed communicative competence, the ability to solve communicative problems by speech means is formed.Even though the presence of linguistic and speech competence is considered as an intermediate link, the success of communication largely depends on the degree of formation of speech skills, their automation, which is developed by playing many situations using the appropriate speech models (Passov, 2010).During a pandemic, sometimes the only possible form of distance learning and the absence of a language environment become conditions that are fundamentally different from the conditions of communication, which further complicates the teacher's task to form the student's speech skills capable of transferring to the situation of real communication.In addition, the factors of repeatability of speech samples, the regularity of their presentation, so necessary for the automation of speech skills, can cause boredom in the student and even the desire to stop learning a new language for him.Thus, in our opinion, in a distant format, it becomes especially important for a teacher to make the process of teaching speech models at the initial stage of language learning as interesting, variable, and effective for memorization as possible.The aim of the study is to describe the most effective approaches to the formation of speech skills among foreign students, considering the disadvantages of online teaching of Russian as a foreign language.
RAPID APPLICATION DEVELOPMENT DALAM RANCANGAN SISTEM INFORMASI PEMINJAMAN DAN PENGEMBALIAN BUKU

Ananda School, which is located in Bogor City, is a school that is very active in the habit of reading its students. This school has a fairly complete library with quality books, but unfortunately, the system of borrowing and returning books is still conventional by recording transactions on many books. This causes problems in the process of searching for books and transactions that have occurred so that they are less effective and efficient in daily activities. The design of the Book Borrowing and Returning Information System is a solution to overcome the problems that occur by using the Rapid Application Development model in the software development method. The data collection process uses the interview method, observations by paying attention to the system that is currently running, and several examples of sites related to information systems for borrowing and returning books, and literacy are also used as reference materials. The Information System for Borrowing and Returning Books at this school has also made it much better with the various kinds of databases used and the reports that are the output of this information system.
Three Approaches to Criticisms and Support in Evaluation of Arguments

Introduction. In the article we defend a claim that criticisms and counterarguments play a more important role in modeling and evaluating arguments than defending and supporting the thesis. The novelty of this idea lies in that it shifts the main focus of the study of argumentation from the support and proof, with which it is traditionally associated, to criticism and refutation. Compared to the support and proof, criticism and refutation play more important role in the context of soft skills and communication in the practical activities, including obtaining and verifying information. The relevance of our study is dictated by the fact that argumentation is essential in both of the areas of activities, the importance of which is increasing at the present stage. Methodology and sources. We identify three ways to understanding criticism with respect to three approaches to understanding of arguments, – inferential, dialogical and abstract. The inferential view relies on verification and aims to justify a conclusion by deriving it from premises. The dialogical view sees in it the grounds offered by its author to its addressee. The author aims at achieving the latter's consent to its conclusion, and the acceptability of the arguments is verified by both justifying their conclusions and rejecting objections to them. The dialogical view relies on the principles of verification and falsification. The abstract view abstracts from the internal structure of arguments and evaluates their acceptability through the falsification, conveying the rejection of arguments in defense of the opposite conclusion. Results and discussion. The inferential view presupposes one-step criticism based on its analysis and final assessment, the dialogical one presupposes a multi-step revision of the assessment, and the abstract view implies arguments’ ability to reject counterarguments and demonstrates its role in defending the set of arguments to which it belongs protecting many arguments from criticism to which it belongs. Conclusion. In the dialogical and abstract approaches, objections and criticisms of arguments play a more important role in justifying and defending arguments than the defense and support defined by them, which play a leading role in the inferential approach to arguments.
Learning to Rank with BERT for Argument Quality Evaluation

The task of argument quality ranking, which identifies the quality of free text arguments, remains, to this day, a challenge. While most state-of-the-art initiatives use point-wise ranking methods and predict an absolute quality score for each argument, we instead focus on learning how to order them by their relative convincingness, experimenting with several learning-to-rank methods for argument quality. We leverage BERT's powerful ability in building a representation of an argument, paired with learning-to-rank approaches (point-wise, pairwise, list-wise) to rank arguments according to their measure of convincingness. We also demonstrate how an ensemble of models trained with different ranking losses often improves the performance at identifying the most convincing arguments of a list. Finally, we compare BERT coupled with learning-to-rank methods to state-of-the-art approaches on all major argument quality datasets available for the ranking task, demonstrating how a learning-to-rank approach generally performs better at outlining the topmost convincing arguments.
SISTEM INFORMASI PENGGAJIAN PADA BMT BINA UMAT MANDIRI

This study aims to determine and evaluate the payroll information system at Baitul Maal Wa Tamwil Bina Usaha Mandiri (BMT BUM) which includes functions, procedures, documents and internal controls. This study uses a qualitative approach. Data collection was obtained from observation, interviews and literature study. In general, the payroll information system at Baitul Maal Wa Tamwil Bina Usaha Mandiri (BMT BUM) has been implemented properly and in accordance with the related theory. Although there are some differences, it is not a problem, because the differences are due to the characteristics of the organization, the use of information technology systems and are still under internal control system.
Les termes complexes de type locution dans l’enseignement du français L2 en langue de spécialité : le cas du domaine du commerce international

The Case of International Trade
PENERAPAN KONSEP FINITE STATE AUTOMATA UNTUK PENJURUSAN IPA ATAU IPS

Majoring high school students (SMA) in the grouping of majors in science or social studies is currently still very difficult to do. So that there are still many students entering majors that are not their abilities and choices, and this can lead to a decrease in students' ability to learn at school. Based on this background, this research is designed to be able to assist students in determining majors at school. In this study, the specialization carried out was explored based on the interests and talents of students which were explored briefly with a quiz system, not based on grades at school with the FSA concept approach. The majors application is designed very simply using the google form application.
IEEE Transactions on Evolutionary Computation Information for Authors

The IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (TEVC), published six times a year, publishes archival quality original papers in evolutionary computation and related areas including nature-inspired algorithms, population-based methods, and optimization where selection and variation are integral, and hybrid systems where these paradigms are combined.Purely theoretical papers are considered as are application papers that provide general insights into these areas of computation.
Perancangan Prototype Sistem Informasi Repository Skripsi Berbasis Web Di UNA’IM Yapis Wamena Papua

In Indonesia, there are many institutions that use information systems in the field of education, one of which is the Repository information system. Repository is a digital-based library term where this information system can be used to access student thesis, both the academic community and academics outside the campus as reference material for writing scientific papers. Even so, not all colleges use it. One of them is Amal Ilmiah Yapis Wamena University. As a university located in conflict and mountainous areas, data loss often occurs. Likewise with the use of information systems that have not been maximized. This study aims to design a prototype of a web-based thesis repository information system at the Amal Ilmiah Yapis Wamena University. The method used is simulated prototyping. The results of this study show the prototype/prototype design in the form of a web-based thesis repository information system mockup as many as 7 (seven) mockup pages, including the login page, lecturer list, Lecturer data entry form, student list, student data entry form, repository list, and form. repository data entry.
SISTEM INFORMASI GEOGRAFIS UNTUK PEMETAAN PARIWISATA KABUPATEN KARANGANYAR BERBASIS WEB

Karanganyar is an area that has diverse tourism potential. In the delivery of tourist information for now is still in the form of books, posters, pamphlets, and brochures. Currently the number of tourist visits has decreased due to less effective promotions. The purpose of utilizing the web-based Geographic Information System (SIG) so that prospective tourists can find the location of tourist attractions interactively, the hope is to be used as information on Karanganyar regency attractions to all communities in various parts of the world quickly, accurately and thoroughly. This SIG can also provide information about the activities that take place (events) in the tourist attraction and mileage so that it is expected to influence prospective tourists to visit. System Development methods and their analysis use linear sequential methods (Waterfall) and structured modeling. Through this research, the results are a SIG application for Mapping Tourism of Web-Based Karanganyar Regency that is able to provide information to prospective tourists about the location of tourist attractions, infrastructure facilities and distance information.
Pemanfaatan Algoritma K-Means untuk Pengelompokkan Pasien Penyakit Infeksi Saluran Pernafasan Akut (ISPA)

This study discusses Acute Respiratory Infections (ARI) at the Bah Biak Health Center. Bah Biak Health Center is one of the health centers in Marihat in Pematangsiantar city. Every day the number of patients who come and perform medical treatment at this health center is quite a lot. The high number of patient visits at this puskesmas causes the amount of medical record data to be very large as well. So far, data containing information about patients at the puskesmas has not been used properly. This information can actually be used as knowledge for puskesmas, especially for patients who have a history of ARI disease. Therefore, the purpose of this study was to classify patients with ARI at the Puskesmas. The method used is K-Means clustering. The results of this study were able to classify ARI patients into 2 clusters, cluster 1 gave a high recommendation of 72 patients, and cluster 2 gave a low recommendation of 70 patients. The cluster process stops at the 5th iteration of data. Based on the manual calculation process using Ms. Excel and testing using Rapidminer 5.3, yielded the same value. It can be concluded that in this case, the K-Means algorithm can classify ARI patients at the Bah Biak health center well.
Adversarial Learning to Reason in an Arbitrary Logic

Existing approaches to learning to prove theorems focus on particular logics and datasets. In this work, we propose Monte-Carlo simulations guided by reinforcement learning that can work in an arbitrarily specified logic, without any human knowledge or set of problems. Since the algorithm does not need any training dataset, it is able to learn to work with any logical foundation, even when there is no body of proofs or even conjectures available. We practically demonstrate the feasibility of the approach in multiple logical systems. The approach is stronger than training on randomly generated data but weaker than the approaches trained on tailored axiom and conjecture sets. It however allows us to apply machine learning to automated theorem proving for many logics, where no such attempts have been tried to date, such as intuitionistic logic or linear logic.
Komparasi Kinerja Integrated Development Environment (IDE) Dalam Mengeksekusi Perintah Python

An IDE is basically a software package consisting of tools used to develop and test software. IDEs help automate developer tasks by reducing manual effort and combining all tools in a common framework. If the IDE does not exist, then the developer will have to do the selection, integration, and deployment process manually. This study tries to compare the performance of ideas in recognizing writing errors or the simplest syntax in the python language, namely indentation. The test results of the 6 IDEs used found 1 IDE that managed to detect syntax writing errors, namely w3schools. The choice lies with the developer. Generally, the idea is used for programs such as compiled languages such as C, C++, Java, .NET. While the code editor is used for scripts and interpreted, such as PHP, JavaScript, Python, Ruby. In terms of features, of course, using an IDE is more complete than a text editor. If the developer uses VS code, the environment can be adjusted like a code editor but still carries the reliability of an IDE.
Virtual Assistant to follow Internet and PC commands

A virtual assistant, is an application program that understands natural language voice and completes tasks for the user. The purpose of this assistant is to perform internet and desktop command for user. Not everyone is a technical person; they don’t know what is CMD and how to give command. This assistant will perform command simply through voice and person will not have to type everything manually. In our project we will only focus on system that works on and for PC only. This assistant is in software format which user will able to download and install in his/her PC. Key Words: AI, python, Assistant, Speech Recognition
Intelligent Tutoring Systems by Bayesian Nets with Noisy Gates

Directed graphical models such as Bayesian nets are often used to implement intelligent tutoring systems able to interact in real-time with learners in a purely automatic way. When coping with such models, keeping a bound on the number of parameters might be important for multiple reasons. First, as these models are typically based on expert knowledge, a huge number of parameters to elicit might discourage practitioners from adopting them. Moreover, the number of model parameters affects the complexity of the inferences, while a fast computation of the queries is needed for real-time feedback. We advocate logical gates with uncertainty for a compact parametrization of the conditional probability tables in the underlying Bayesian net used by tutoring systems. We discuss the semantics of the model parameters to elicit and the assumptions required to apply such approach in this domain. We also derive a dedicated inference scheme to speed up computations.
MINING FIRE HOTSPOTS OVER NUSA TENGGARA AND BALI ISLANDS

Forest fires are still one of the most common problems in Indonesia. In fact, many of these forest fires origin from human activities, namely fires that are intentionally raised for a purpose such as widening the land to prepare for the planting season in the Nusa Tenggara Island. Forest fire events can be identified by observing hotspot data which are monitored through remote sensing satellites. Hotspot is an area that has a relatively higher surface temperature than the surrounding area based on certain temperature thresholds monitored by remote sensing satellites. The area is represented as a point that has certain coordinates. The actual fires can be monitored by observing the hotspot attribute, namely Confidence, Brightness Temperature and FRP (Fire Radiate Power). To find the similarities of the three mentioned attributes, the clustering process is carried out to make monitoring easier. The objective of this research is to cluster hotspots in the Nusa Tenggara and Bali Islands from year 2013 to 2018 using the K-Means Clustering Method with 28,519 hot spot data. This could be a benefit for the Ministry of Environment and Forestry in Indonesia to identify the priority level of the area to be monitored. By knowing this result, the ministry can use this data for patrol priority management. This research successfully clustered three types of hotspot classes based on the risk of fire with details as follow; High Risk Class contains 12,212 data with ranges of mean values of confidence in the range of 49.3–100%, brightness in the range of 305.1–421.3o K and FRP in the range of 2.5–714.3; Medium Risk contains 12,250 data mean values of confidence with a range of 20.3–74.3%, brightness in the range of 301.06–341.86o K and FRP in the range of 3.6–141.4; and Low Risk contains 4,057 data with a range of mean values of confidence in the range of 0–39.8%, brightness in the range of 300–365.86oK and FRP in the range of 3.5–275.6. All of the clusters were obtained by the implementation of K-Means clustering over the hotspot data and its parameter as mentioned, respectively. The cluster performance showed the confidential value of 88.45% accuracy using 100 hotspot data from 2019
RANCANG BANGUN SISTEM INFORMASI PENGOLAHAN DOKUMEN KREDIT PEMILIKAN RUMAH (KPR) BERBASIS DEKSTOP DENGAN MENGGUNAKAN METODE PROTOTYPE

Institutions engaged in services, namely banking. One of the credit facilities provided by the bank is a home ownership loan (KPR). This research is descriptive qualitative. The existence of documents in a company is very important, because it functions as a means of interpersonal communication and as a formal form of accountable activity. Obstacles in managing documents in an agency include the use of applications that are still manual, making it difficult for agencies to manage documents. The method of data collection in the preparation of this research is the method of observation and literature review with the analytical method in the form of qualitative analysis, namely the method of analyzing data without using statistical analysis. The research method used is the prototype method. This study aims to produce an information system design for Home Ownership Credit (KPR) document management that can provide information on the completeness of Home Ownership Credit (KPR) documents to facilitate finance services in managing mortgage documents.
Scanning the Issue

How to Build a Graph-Based Deep Learning Architecture in Traffic Domain: A Survey
Towards Increasing the Coverage of Interactive Recommendations

An interactive recommender system pursues two somewhat contradictory goals. On one hand, the system should provide highly relevant recommendations with the best match to the overall user needs. On the other hand, the recommendations should be sufficiently diverse to cover a range of users' possible interests. Such recommendations increase chances that the user finds items that match their context while also informing the system which items are currently most important. In this paper, we present a ranking approach that balances the demands of relevance and coverage. We evaluate the approach on two problems, of advisor and movie recommendations, where the immediate needs of the user are likely to be diverse. Our approach considerably increases chances that the user finds relevant items in the first few steps of the recommendation dialog.
ETMS@IITKGP at SemEval-2022 Task 10: Structured Sentiment Analysis Using A Generative Approach

Structured Sentiment Analysis (SSA) deals with extracting opinion tuples in a text, where each tuple (h, e, t, p) consists of h, the holder, who expresses a sentiment polarity p towards a target t through a sentiment expression e.While prior works explore graph-based or sequence labeling-based approaches for the task, we in this paper present a novel unified generative method to solve SSA, a SemEval-2022 shared task.We leverage a BART-based encoderdecoder architecture and suitably modify it to generate, given a sentence, a sequence of opinion tuples.Each generated tuple consists of seven integers respectively representing the indices corresponding to the start and end positions of the holder, target, and expression spans, followed by the sentiment polarity class associated between the target and the sentiment expression.We perform rigorous experiments for both Monolingual and Cross-lingual subtasks, and achieve competitive Sentiment F1 scores on the leaderboard in both settings.
The Role of Higher Education for the Ethical AI Society

AI is creating numerous ethical issues. In the upcoming AI society, we will have to deal with the Influence of AI correctly. To this end, ethical education is needed for experts who learn and develop AI technology. Above all, this is because their ethical capabilities lead to ethical AI technologies and services. Therefore, this study sought the role and direction of AI ethics education in the field of higher education that educates AI experts.
Interpretable Model for Collaborative Filtering Using an Extended Latent Dirichlet Allocation Approach

With the increasing use of AI and ML-based systems, interpretability is becoming an increasingly important issue to ensure user trust and safety. This also applies to the area of recommender systems, where methods based on matrix factorization (MF) are among the most popular methods for collaborative filtering tasks with implicit feedback. Despite their simplicity, the latent factors of users and items lack interpretability in the case of the effective, unconstrained MF-based methods. In this work, we propose an extended latent Dirichlet Allocation model (LDAext) that has interpretable parameters such as user cohorts of item preferences and the affiliation of a user with different cohorts. We prove a theorem on how to transform the factors of an unconstrained MF model into the parameters of LDAext. Using this theoretical connection, we train an MF model on different real-world data sets, transform the latent factors into the parameters of LDAext and test their interpretation in several experiments for plausibility. Our experiments confirm the interpretability of the transformed parameters and thus demonstrate the usefulness of our proposed approach.
Cybersecurity risk management in the industry 4.0

A referential and abstract model will be presented to be applied in risk management on cloud computing and industry ICS platforms in general. we are looking at the types of assessments that are out there, we explore the different approaches and techniques behind information technology systems risk assessments and complexity of conducting industrial control system safely at-risk control level.