Reviewerly/exHarmony huggingface dataset:
Peranan Sistem Informasi Manajemen Dalam Meningkatkan Kinerja Karyawan Pada Tirta Bina Labuhanbatu

Management Information System (MIS) is a system that processes and organizes useful data and information to support the implementation of tasks in an organization/company. A company will use information systems to improve / assist employees to support their performance. SIM is very important for the company because its role is very vital or very impactful for the company itself. With the use of SIM companies can have advantages in business processes within the company. Processes in a business that previously did not use a SIM will take a long time. Using SIM will have advantages for the company because business processes can be shortened or simplified. In its use, SIM has a system that can help the performance of employees in the company. So the company does not need to take a long time in some of its business processes
PARENTS’ ROLE IN MOTIVATING THEIR CHILDREN TO STUDY ENGLISH DURING THE COVID PANDEMIC 19

This research discusses about parents role to motivate their children to stud English during Corona Virus pandemic. This study is case study in MTs arrohman and MTs al Urwatul Wutsqo Jombang. Using qualitative descriptive, interview and observation as instrument. The data collected by Miles &amp; Huberman model. This study resulted that parents’ role in motivating their children to learn English during pandemic are as educator, motivator, facilitator, and being good models for their children. To do that, they faced some problem, and overcome them by advising patiently, working cooperatively with other parents to prohibit their children from playing while studying, and devide time well. The children motivation to study English depended on the way their parents motivated.
Product Review Based on Machine Learning Algorithms

The purchase of products or administrations through an electronic trade called web based shopping over internet using a web browser. Online Product surveys are significant for up and coming purchasers in helping them decide. To this end, distinctive sentiment mining systems have been proposed, where making a decision about a survey sentence’s direction (e.g., positive or negative) is one of their key difficulties. As of late, Machine learning has risen as powerful methods for taking care of assumption order issues. An AI model inherently learns a helpful portrayal consequently without human endeavors. In any case, we propose a regulated AI structure for item audit conclusion arrangement which utilizes pervasively accessible evaluations as powerless supervision signals. To assess the proposed system, we build a dataset containing 2, 00,000 pitifully named survey sentences and 15000 marked audit sentences from Amazon. Trial results show the more exactness contrasted with past one.
Methods for online search of databases with scientific articles

The selection and use of bibliographic sources in doctoral research is a very important process that takes place until the thesis is finished. How researchers carry out those activities can have a major impact on the quality of the doctoral thesis and scientific publications. This article tries to answer the following questions: "how do researchers choose a database of scientific articles to document the current status in the field the study ?" and "how do researchers look for information relevant to the topic of doctoral research ?".
Learning with semi-definite programming: statistical bounds based on fixed point analysis and excess risk curvature

Many statistical learning problems have recently been shown to be amenable to Semi-Definite Programming (SDP), with community detection and clustering in Gaussian mixture models as the most striking instances Javanmard et al. (2016). Given the growing range of applications of SDP-based techniques to machine learning problems, and the rapid progress in the design of efficient algorithms for solving SDPs, an intriguing question is to understand how the recent advances from empirical process theory and Statistical Learning Theory can be leveraged for providing a precise statistical analysis of SDP estimators. In the present paper, we borrow cutting edge techniques and concepts from the Learning Theory literature, such as fixed point equations and excess risk curvature arguments, which yield general estimation and prediction results for a wide class of SDP estimators. From this perspective, we revisit some classical results in community detection from Guedon and Vershynin (2016) and Fei and Chen (2019), and we obtain statistical guarantees for SDP estimators used in signed clustering, angular group synchronization (for both multiplicative and additive models) and MAX-CUT. Our theoretical findings are complemented by numerical experiments for each of the three problems considered, showcasing the competitiveness of the SDP estimators.
Penerapan Metode Demster Shafer Pada Sistem Pakar Terhadap Penyakit Rabies Hewan

Dogs (Canis Lupus Familiaris) are one of the pets that are liked by humans because they are easy to adjust and can make friends. Zoonoses are infectious diseases from animals to humans but from about 200 types of zoonoses or parasites that are transmitted by animals. Rabies disease, Campylobacteriosis, skin disease, Toxocariasis, are some of the diseases that can be transmitted by dogs. Dog owners sometimes do not understand when disease strikes their dog. Dog owners usually treat them in their own way without paying attention to their health and not being balanced with knowledge about handling dog diseases. Prevention of disease transmission must be balanced with knowledge of dog owners about the types of dog diseases and knowledge of the symptoms that appear in dogs to determine whether the dog is positive for the disease or not. In today's world of health, there is an information system where the system has the ability to solve problems like experts. The information system is called the Expert System.
Pelayanan Referensi Era Milenial di Perpustakaan Perguruan Tinggi: Perspektif Perubahan Sosial Pengguna Perpustakaan

This study describes contemporary reference services in college libraries with a written perspective on social changes that exist in millennial users or users today. This study also explains the current innovation of reference services in the sample library samples discussed. Examples of library reference services discussed are retrieving information on library pages at IPB, UPI and UNAIR libraries. The research method used is a qualitative research method with a descriptive approach by online observation by taking information on the library website page. The analysis was carried out using online observation on the library website which focuses on observation in the context of reference services. Furthermore, a comparison with social theory is carried out on three types of radical social change in the literature on young users of the digital era. The results in this paper are that these three types of changes can be used as a contextual analysis of the scope of young users or millennial users in determining policies on innovation implemented in library reference services. Information technology innovation by making reference service applications that run on desktop and mobile is one of the current innovations that are right on target and in accordance with current library users. This is evidenced by the increasing number of library service applications so that libraries can innovate in collaboration with mobile or desktop reference services.
Assessment literacy as a component of the professional competence of a teacher in the conditions of reforming the evaluation system in Kazakhstani schools

The realities of modern world have led to reform of educational systems in different countries. Assessment is recognized as main component in determining effectiveness of training. In context of a shift in emphasis from «assessment of learning» to «assessment for learning», problem of developing assessment literacy of practicing teachers and students - future teachers becomes urgent Directions of research: based on analysis of literature on educational assessment, identify approaches to determining teacher’s assessment literacy; to highlight requirements for assessment activity of a teacher and, based on theoretical premises, organize and conduct an empirical study in order to identify significance of this problem in Kazakhstan education and possible ways to solve it. The theoretical research was carried out using a comparative analysis of scientific sources and regulatory documents on problem of educational assessment and a survey of practicing teachers, which formed basis of empirical research. Analysis and systematization of survey results showed that advanced training courses for teachers and courses on criteria-based assessment for university students provide a knowledge component of teacher’s assessment literacy, but problem of improving practical component remains. The solution to this problem is possible through various practices of professional development of teachers, involving theoretical training and independent design of their own assessment activities, taking into account the subject specifics of discipline. Of particular importance in formation of teacher’s assessment literacy is training of future teachers during their studies at university, which should be implemented through formation of deep knowledge in chosen subject area, participation in assessment practices within framework of methodological disciplines and pedagogical practices, interaction with practicing teachers. The scientific and pedagogical significance of study lies in obtaining author’s definition of teacher’s assessment literacy, as well as establishing main directions of its formation and development. Key words: educational assessment, assessment literacy of teachers, formative assessment, summative assessment.
DYNAMICS OF THE EDUCATIONAL PROCESS IN RUSSIAN UNIVERSITIES

It is known that fundamental higher education is one of the foundations of successful socio-economic and socio-political development of modern states.An important component of the process of integration of the Russian Federation into the world community, which has been taking place in recent years, is the construction of effective interaction between the domestic and European educational systems, which causes legitimate interest among researchers and requires a deep and comprehensive study of a whole range of problems.Both the problem and its actual side, despite the existing work, are far from being exhausted.
Video-Based Ice Breaker Game In The Department of Arabic Language Education

Online and distance learning leads to reduced student motivation, boredom, and reduced levels of understanding. The solution to solve this problem is ice breaker-based video. In Arabic learning, ice breaker video content is not found much because ice breakers are usually practiced for offline learning. Therefore, ice breakers are required in videos for online learning by producing them in large quantities. This study aims to describe the results of a review of ice breaker-based videos that have been successfully designed by students in the Department of Arabic Language Education. It is a mixture of quantitative and qualitative approaches. With qualitative content analysis, it is known that students successfully produce Arabic-language ice breaker-based videos that are of good quality from the aspect of content, themes, and teaching materials for all levels of education, from children to adults. This video can be applied independently or under the guidance of a classroom teacher. The success of students in producing ice breaker-based videos is because the Arabic education curriculum has accommodated elective courses called Games, Songs, and Stories so that students are equipped with teaching skills and the ability to become content creators.
TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads

TensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing resources and monitors their utilization. Reservations granted on the basis of flexible access control settings are protected by pluggable violation hooks. The job execution module includes auto-configuration templates for distributed neural network training jobs in frameworks such as TensorFlow and PyTorch. Documentation, source code, usage examples and issue tracking are available at the project page: https://github.com/roscisz/TensorHive/
Mask-Net: Learning Context Aware Invariant Features Using Adversarial Forgetting (Student Abstract)

Training a robust system, e.g., Speech to Text (STT), requires large datasets. Variability present in the dataset, such as unwanted nuances and biases, is the reason for the need for large datasets to learn general representations. In this work, we propose a novel approach to induce invariance using adversarial forgetting (AF). Our initial experiments on learning invariant features such as accent on the STT task achieve better generalizations in terms of word error rate (WER) compared to traditional models. We observe an absolute improvement of 2.2% and 1.3% on out-of-distribution and in-distribution test sets, respectively.
Distinguishability in Abstract Argumentation

In abstract argumentation, the admissible semantics can be said to distinguish the preferred semantics in the sense that argumentation frameworks with the same admissible extensions also have the same preferred extensions. In this paper we present an exhaustive study of such distinguishability relationships, including those between sets of semantics. We further examine restricted classes of argumentation frameworks, such as self-attack-free and acyclic frameworks. We discuss the relevance of our results in the context of the argumentation framework elicitation problem.
Access to Government Information and Corruption: An Empirical Investigation

&#x0D; This study taps into a newly constructed index of actual access to government information with a view to finding out whether such access reduces corruption. It draws on a few cases at the micro level and on cross-country data at the macro level to investigate this research question. The study is designed to detect for methodological problems commonly encountered in regression models used to empirically investigate the causes of corruption.&#x0D; The principal finding of the study is that access to government information reduces corruption at both the micro and macro levels. Another key finding is that a supporting institutional and political environment is necessary for the effectiveness of access to government information as an anti-corruption policy tool. A third finding is that access to government information through the traditional is an effective policy tool for curbing corruption, particularly in contexts characterized by limited computer and Internet penetration in society. This study underscores the importance of using traditional media as civic engagement tools in anti-corruption policy initiatives. The policy implication here is that access to government information through the traditional media may have to be an important component of anti-corruption policy initiatives.
Training neural networks for solving 1-D optimal piecewise linear approximation

Recently, the interpretability of deep learning has attracted a lot of attention. A plethora of methods have attempted to explain neural networks by feature visualization, saliency maps, model distillation, and so on. However, it is hard for these methods to reveal the intrinsic properties of neural networks. In this work, we studied the 1-D optimal piecewise linear approximation (PWLA) problem and associated it with a designed neural network, named lattice neural network (LNN). We asked four essential questions as following: (1) What are the characters of the optimal solution of the PWLA problem? (2) Can an LNN converge to the global optimum? (3) Can an LNN converge to the local optimum? (4) Can an LNN solve the PWLA problem? Our main contributions are that we propose the theorems to characterize the optimal solution of the PWLA problem and present the LNN method for solving it. We evaluated the proposed LNNs on approximation tasks, forged an empirical method to improve the performance of LNNs. The experiments verified that our LNN method is competitive with the start-of-the-art method.
INNOVATION PROCESSES IN THE VOCATIONAL EDUCATION SYSTEM CONSULTING DEVELOPMENT

The tendencies of innovative processes of post-industrial development of higher education are revealed and analyzed, the peculiarities of its functioning in the era of the economy based on knowledge are characterized.The social order of public organizations, employers initiated a new impetus for the emergence of needs in the provision of consulting assistance, pedagogical support of the educational process in the system of higher and secondary vocational education using innovative technologies.The essence of innovative pedagogical consulting lies in the provision of the necessary assistance by a competent specialist in identifying contradictions arising in the educational process and in a qualified solution of problems by an educational organization using modern technologies.The penetration of innovative technologies into all spheres of a person's life determines the level of requirements for a university graduate to master STEAM skills, self-realization in his chosen profession, as well as adaptation of technical projects to the changing socio-economic environment.
Levels of connectivity in the new school normality: the case of the Autonomous University of Tamaulipas

The impact of the SARS-CoV-2 virus in the educational sector generates the challenge of making visible the problems that the school community presents when moving the face-to- face school classes to the virtual modality. The objective of this work is to evaluate the characteristics of the digital divide among the students of the Autonomous University of Tamaulipas (UAT). The methodology is quantitative and descriptive, using a virtual survey where 1 192 students from the Faculty of Law and Social Sciences of the UAT participated. The results identified that despite having sufficient digital access and connectivity, digital skills continue to be an obstacle and the gender gap is significant, as women have the least opportunities to appropriate ICTs.
Augmented Reality (AR) - based Human Digestive System Mobile Learning Platform

Overtime, the inadequacy and abstraction of conventional teaching materials had been a bane of bringing the interest of students to learning.Likewise, teaching method driven by abstraction may often not seem appealing to the targeted audience.Thus computer-aided teaching such as the use of augmented reality serves as an alternative to effective and efficient teaching.This research presents a 3D anatomical representation of the human digestive system using Augmented Reality (AR) thus creating a paradigm for students to have a better picture and understanding of the human anatomy and how human body parts are connected.Drawbacks such as inaccessibility to cadaver due to ethics/regulations and anxiety/nausea when participating in such sessions can be reduced or controlled using AR through computer-aided graphics to add an additional layer of information for better interaction and understanding.The system also presents a real-time direct or indirect view of a real world environment that has been augmented.Students also get the chance to play quiz game to examine their knowledge on digestive system.
Cooperative Infrastructure Platform for Delivering Mission-critical Services

To solve various social problems, we are researching the integration of network and computing technologies as social infrastructure.The Cooperative Infrastructure Platform being researched and developed at NTT Network Service Systems Laboratories is introduced in this article.To meet service requirements in an end-to-end manner and provide mission-critical services, this platform uses coordinated control among three domains-information processing, network, and device-in fields such as remote monitoring and control of autonomous agricultural machinery, advanced autonomous vehicles, and smart cities.
Implementation Data Mining of Employement Contract Exten-sion at Indosat Using Naïve Bayes

Contract employees are company resources in carrying out oprasional activities for a certain time based on an agreement or contract. Every company that uses a work contrak system every year, there must be employees who are extended and not renewed. Employees will get additional contracts if they have good performance. In this case to determine whether an employee is extended or not extended his work contract, there is difficulty in determining it and requires a long time and process. Therefore, this research was conducted to help guarantee the extension of the employee’s work contract by classifier it into the labes “Eligble” and “Not Feasible” which has 4 variables for the process of employees who will be extended or not. The four variables are age, years of service, aspects of delay, achievement. In this study, the alternatives used as samples were employees at PT. Indosat Ooredoo. The number of data tested is 5 employees with two classes. From the results of the calculation of the Naïve Bayes Algorithm, it is obtained classification with 3 employees eligible class and 2 employees not eligible class. The results of this study found that the level of accuracy of 100.00%.
Case Study of The Utilization Zoom Cloud Meeting for Natural Science Learning PGSD STKIP Muhammdiyah Muara Bungo Students

The study aims to increase the use of online learning applications, one of which is using Zoom Cloud Meetings.The zoom cloud meetings application certainly has advantages and disadvantages that users must face.Next, what about the process and online learning products using zoom cloud meetings.This research is qualitative research with a descriptive approach.The subjects in this case study were PGSD level V students and lecturers who taught science learning subjects.The research data were collected through questionnaires, document studies, and interviews.The results showed that online learning made students less competent, the atmosphere of lecture competition was less, the opportunity to ask questions was not used during the lecture process, online lectures technically made it difficult for students to complete college assignments.However, online learning has provided good learning knowledge.Furthermore, for natural science online learning products in the form of a learning implementation plan, several components need to be evaluated to be improved, namely the main material components, learning media, learning steps, and assessment of learning outcomes.
Attaining Cloud Security Solution Over Machine Learning Techniques

Cloud computing provides physical and logical computation resource on demand for the set of service. Cloud environment reduce the infrastructure cost and easy to use without any extra burden. Cloud storage an access raised the several security issues like data privacy, access control, authentication, virtual machine security, web security etc., In one side hackers, breaches, cloud security issues and threats get expanded. But in another side many technologies are keep increased to secure cloud data. Technology may be cryptographic technique, anonymization technique, machine learning technique etc., In this paper we analyse cloud computing basics, models, machine learning technique and some security solution through machine learning technique such as support vector machine (SVM), K-Nearest Neighbour (KNN), Decision tree and Naïve Bayes classifier technique.