Reviewerly/exHarmony huggingface dataset:
Using the ideal point method to search the best authentication method in corporate information systems

Nowadays, various information systems, including enterprise ones, are becoming increasingly popular. Many of these systems store sensitive data of their users. Basically, this data is protected only by a login and a password, which today can no longer provide a high level of security and guarantee the safety of the data. Along with the development of information systems, methods and tools that attackers can use to get hold of confidential information are also evolving. It is not uncommon to hear news that some of the large companies have leaked its users' personal data. So, in order to minimize the risk of compromising user data, it is worth taking a more careful approach to selecting a method of authenticating users in the system. Aim. To determine the most appropriate method of authentication in enterprise information systems with the help of a mathematical approach and taking into account certain criteria. Materials and methods. The following types of authentication were considered: reusable password authentication, TOTP (Time-based one-time password authentication), SMS-based authentication, biometric authentication, OpenID, SAML (Security Assertion Markup Language). The Pareto set method and the ideal point method were used to determine the most preferable authentication method to implement. Results. In the article, the authors describe the authentication methods considered, the algorithm of their work, and diagrams of their interaction. Using the ideal point method, SAML was determined to be the most appropriate authentication method.
The Use of Macromedia Flash Application in Improving the Mathematical Understanding of Elementary School Students

Mathematics learning will run optimally if it is supported by the use of learning media in accordance with learning objectives and student needs. One of them is the application of learning media through Macromedia Flash to improve students' mathematical understanding. This type of research is classroom action research (Classroom Action Research). This research was conducted in class V of MI Al Washliyah Jangungan in the even semester of the 2020/2021 school year. The subjects of this study were students of class V with a total of 16 children. The object of this research is the learning process by applying learning media based on Macromedia Flash. The results of this study indicate that the application of learning media based on Macromedia Flash 8 in building materials is able to improve students' mathematical understanding with a percentage of 94% of 16 students, which can be categorized in the "Very Strong" category. His learning outcomes also increased from the average value of 80.4 in cycle 1 to 87,625 in cycle 2 and was declared "Completed".
Energy-Efficient Dataflow Scheduling of CNN Applications for Vector-SIMD DSP

Dataflow-scheduling techniques for convolutional neural networks (CNNs) are extensively studied to minimize the off-chip memory access. However, the efficiencies of the previously proposed techniques are limited because their optimizations only consider the general hardware such as FPGA and GPU. To overcome this limitation, this paper proposes dataflow scheduling for vector-SIMD DSP to minimize the energy consumption for the off-chip memory access. First, the proposed technique attempts to group as many given layers as possible. For grouping the layers, the tiles in different layers are executed in sequence without the off-chip memory access except the first and the last layers in the group. The length of the grouped layers is determined with regard to the minimization of the energy consumption of off-chip memory by estimating the proposed energy model of the off-chip memory. However, grouping the layers results in the additional computation. To minimize this overhead, this paper solves the optimization problem for in the grouped layers. Second, for layers that cannot be grouped, the tiling along the W-axis is not considered, to maximize the size of the overlapped data in consecutive tiles. Consequently, the reuse of the overlapped data in the on-chip buffer is maximized, thereby reducing the energy consumption by the off-chip memory. For evaluation, a cycle-accurate simulation environment is established to measure the energy consumption of the off-chip memory by tracing the data between a vector-SIMD DSP and an off-chip memory. The experimental results show that compared with the baseline tiling and scheduling techniques, the proposed technique reduces the energy consumption by an average of 51% for CNN applications such as Tiny YOLOv2, MobileNetv1, VDSR.
Generating Modified-Half-Normal Random Variates by a Relaxed Transformed Density Rejection Method

Abstract The modified-half-normal distribution often occurs as one of the posterior conditionals in many Bayesian statistical models. In order to developa uniformly efficient random variate generator for the entire parameter range of such distribution, we propose a relaxed transformed density rejection method such that it is available in case the optimal contact points in the original transformed density rejection method have no closed-form. Simulation results verify that the resultant generator is fast and robust for various distribution parameters. The proposed generator is particularly suitable for the varying parameter case such as in Gibbs sampler.
RFID Implemented Library System

Libraries are important aspects of our life. These are important in providing or acquiring essential knowledge about anything around us. Earlier Library system faced a lot of problems related to the user accessing it using conventional methods. The RFID implementation on Library Management system faced a lot of problems. The RFID implementations on library management helps to reduce and sort out such issues that faced by conventional Library system. Using RFID implementation, the database shows the availability of the book in the library so that the student can search in the database and if available, they can collect book from the library. It helps to handle the issue, renewal and return process for books using RFID tags implemented on it. Students will also get notified about their status of due of books also.
Comparison of transformer architecture neural network models based on evaluating the vector representation compactness of semantically similar texts in the European classification skills ESCO

In the process of analyzing short texts of the requirements of the Russian labor market, it was revealed that the same skills may have different formulations in natural language. In this regard, the search for a neural network model capable of effectively identifying semantically similar groups of texts of requirements for further formation of profiles of the skills and professions of the Russian labor market becomes an urgent task. The purpose of the study is to develop a method for evaluating neural network models built on the architecture of transformers by comparing the compactness of vector representations of semantically close short texts of skills of professions from the European classification (European Skills, Competencies, and Occupations). Materials and methods. The article provides an analysis for the original model of the European taxonomy of ESCO skills in English, and the texts of skills translated into Russian by the Yandex Translator and Google Translate automatic translation services. The article also provides a comparison of various methods for obtaining sentence attachments (cls, mean, pooling, Sentence Transformers) for various neural network models built on the transformer architecture. The results of the study show that with the help of the proposed method, it is possible to effectively implement the choice of neural network models for the task of searching for groups of semantically similar texts of requirements from online job texts. Conclusion. The proposed method made it possible to effectively select neural network models for the task of identifying compact groups of semantically similar texts of professional skills, which in turn will make it possible to identify groups of skills when forming profiles of professional skills, inclu¬ding semantically similar formulations, and profiles of entire professions. Such tools will allow you to quickly identify: key changes in the needs of the labor market at the level of individual competencies, will allow you to form an idea of the dynamics and sets of relevant competencies, will increase the effectiveness of management decisions to create digital literacy programs, retraining and advanced training, will allow you to assess competencies, will help all participants in the labor market to more accurately assess the existing trends, supply and demand in the labor market.
THE USE OF INFORMATION AND COMPUTER TECHNOLOGIES IN THE DEVELOPMENT OF «DIGITAL SAVVY» OF THE TEACHER

The article describes the need to develop the digital savvy of teachers in connection with the transition to online learning. The possibilities of using information technologies in online learning are illustrated, which contribute to the development of interest in learning and the formation of imaginative thinking.
CC Thinker: Mobile-based Assessment to Train Creative and Critical Thinking in Students

This research aims to combine assessment of creative and critical thinking in a mobile device context, to see its effect on the creative and critical thinking of students. Design-based research as the method was used to develop the assessment as learning. It is begun with the assessment model and android application development, also experiments in the end. Three assessment sessions are participated by 46 students. The analysis using Kruskal Wallis gains the result that there are significant differences in the creative thinking (Chi-square 18.245, Asymp. Sig 0.000) and the critical thinking (Chi-square 7.620. Asymp. Sig 0.022). A significant difference in creative thinking is seen since the second session, while the difference in critical thinking needs the time up to the third session.
LIMITATIONS OF THE DIGITAL LEARNING TOOLS OF THE 21ST CENTURY

This paper takes a step forward and investigates into the higher education industry of Latvia and seeks to understand the labyrinth of the teachers &amp; students with the use of digital learning platforms such as «Learning Management Software», (LMS) and for this particular article the LMS platform investigated is (Moodle), in one particular higher education institution (HEI) of Latvia, International College of Cosmetology (ICC). The research tries to analyze the limitations students’ &amp; teachers’ face during the exercise of such digital tools in their daily routine and what do they demand or seek more from such LMS platforms. Based upon the analysis of the results, a potential new LMS modification is suggested that will help to suffice the current Latvian HEIs’ need and demands with the changing educational trends and help the academics, stakeholders attached to the educational sector incorporate an LMS platform that is based and formulated on the study of the local market &amp; people.
Rethinking Negative Sampling for Handling Missing Entity Annotations

Negative sampling is highly effective in handling missing annotations for named entity recognition (NER). One of our contributions is an analysis on how it makes sense through introducing two insightful concepts: missampling and uncertainty. Empirical studies show low missampling rate and high uncertainty are both essential for achieving promising performances with negative sampling. Based on the sparsity of named entities, we also theoretically derive a lower bound for the probability of zero missampling rate, which is only relevant to sentence length. The other contribution is an adaptive and weighted sampling distribution that further improves negative sampling via our former analysis. Experiments on synthetic datasets and well-annotated datasets (e.g., CoNLL-2003) show that our proposed approach benefits negative sampling in terms of F1 score and loss convergence. Besides, models with improved negative sampling have achieved new state-of-the-art results on real-world datasets (e.g., EC).
Degree of Practicing Administrative Creativity by Education District Managers as Perceived by Department Heads and Administrators in the Districts of Mafraq Governorate

The study aimed to assess the perceptions of department heads and administrators regarding the degree to which Educational District Managers practice administrative creativity in the districts of Mafraq governorate. To achieve this objective, the study followed the descriptive survey method, and used a questionnaire to collect data from the study sample which was selected from a population of 240 male and female employees (40 heads and 200 employees in education districts of Mafraq governorate). The sample consisted of (150) participants (25 department heads and 125 male and female employees). The data was analyzed by the use of statistical methods, such as means, standard deviations, the analysis of multiple variance and the method of Scheffe. The study findings revealed that the participants' degree of perception was moderate, and that there were differences in their perceptions according to their different demographic variables. The study recommended preparing and designing training programs to develop the performance of educational leaders in education districts to implement the requirements of administrative innovation and creativity.
Pembuatan Animasi 3D Pengolahan Kelapa Sawit menjadi Minyak Mentah Kelapa Sawit menggunakan Metode MDLC

Current technological developments make it easier for people to find information using communication tools such as smartphone, computers, and televisions,but many people don’t understand how the process of processing palm oil into crude palm oil. In making animation processing palm oil into crude palm oil, the information is still in the form of text, and still little information in form video. The method used in this research is Multimedia Development Life Cycle (MDLC) which consist of concept, design, material collecting, assembly, testing, distribution is made using Blender software versi 2.9, dan Adobe Premiere Pro cc2017. This 3D animation will be used for the banefit of community in understanding the process of processing palm oil into crude palm oil. The result of this study are 3D animated videos in format MP4.
Twin prime difference set and its application on a coded mask

Difference sets have wide applications in constructing sequences and codes in engineering and cryptography, and in imaging with coded masks in astronomical events and in medical events. In this paper, the relation between difference sets and binary sequences is presented and a coded mask as an application of difference sets is given. First of all, an algorithm for an appropriate difference set is written in C++ by using twin primes and then a coded mask for imaging astronomical events is designed with the aid of this algorithm.
Methodological framework for the axiological paradigm in the learning environment

Modern conditions of education require the development of new methodological approaches for the implementation of the educational process. The purpose of study is to analyze the axiological paradigm in the Kazakhstan’s system of teacher training and determines experimentally the phases of its development in Kazakhstan in early 21st century. A total of 284 students participated in the experiment. The findings suggest that students in the control group repeated what was said during the lecture. Generally, they did not go beyond repetitions. Out of 142 students who were involved in the first phase of the experimental group, 80 students responded at the heuristic level, 12 students responded at the innovative level, and 8 students responded at the creative level. Students in the experimental group were capable of independent thinking beyond lectures. 8 students proved to be 40% capable of drawing conclusion to an unusual, phenomenally high degree. Practical implications and further research might focus on the special aspects of developing the axiological paradigm not only for students in Kazakhstan, but also in other countries in a comparative aspect. New research can also rely on the experiment’s methodological framework.
Credit Card Fraud Detection using Logistic Regression Compared with t-SNE to Improve Accuracy

Aim: The principle objective of this article is to improve the accuracy of Credit card fraud detection using Novel logistic regression compared with the t-SNE. Materials and Methods: The categorizing is performed by adopting a sample size of n = 10 in novel logistic regression and sample size n = 10 in t-SNE with a sample size = 10, obtained using the G-power value 80%. Results: The analysis of the results shows that the Novel logistic regression has a high accuracy of (99.89) in comparison with the t-SNE(60.99). There is a statistically significant difference between the study groups with (p&lt; 0.05). Conclusion: For Credit card fraud detection it shows that the Logistic Regression appears to generate more accuracy than the t-SNE
RelOntoUML: Relációs modellen, ontológián és UML-en alapuló modell

This paper presents a model that combines ontology, UML modeling, and a relational model.The ontology model (and the Ontology Web Language -OWL), UML, and relational model are first introduced in the article.After a review of the literature, the comparison and conversion of the systems are presented.The created model is then presented and a real ontology is modeled using the presented model.
Linguistics of sports media discourse: metaphors that produce sense of belonging

The article is devoted to the study of conceptual metaphor SPORT is UNITY OF PEOPLE that contributes to creating the sense of belonging among target audience of sports analytical articles.As far as author's position is likely to be emotional, the text of sports articles tends to be very metaphorical, containing reference to UNITY concept that in its turn evokes feeling of belonging.The latter one has been analysed as a triad of interconnected components: companionship, affiliation, and connectedness, that generate attachment on interpersonal, community and social levels accordingly.
THE EFFECTIVENESS OF USING MYENGLISHSTEP AND SUMBER.BELAJAR.KEMDIKBUD.GO.ID IN COMPOSING DESCRIPTIVE

This study investigates how effective using myenglishstep and sumber.belajar.kemdikbud.go.id 7th grade students in composing descriptive text at SMP Negeri 42 Semarang. The writer used a quantitative method. There 2 as experimental classes which is using myenglishstep and sumber.belajar.kemdikbud.go.id. The result of the study is that there is correlation between myenglishstep and sumber.belajar.kemdikbud.go.id in composing descriptive text for 7th grade students.The objective is to discover which show is more viable than the two models when connected in learning to compose descriptive writings in course 7 junior high school. Based on the calculation of the normal increment, the student's last test normal score in the test course 1 of 87.230, where's the normal esteem of the student's last test in the test course 2 of 80.50. There's a distinction in esteem of 6.73 between experimental lesson 1 and exploratory lesson 2. So, it can be concluded that class Experiment 1 is more successful than test course 2.On the other hand, It can be seen that the normal beginning test score was 79,961 and the normal last test score was 87,230. This appears that the utilize of myenglishstep demonstrate is viable when connected to learning compose an informative content since the comes about appear an increment between some time recently and after the exploratory lesson 1 was given a treatment of 7.269.
Detection of suspicious activity using mobile sensor data and Modified Sub-space K-NN for criminal investigations

With the bulk availability of mobile sensors, the data collected from them mustn’t be wasted. Nowadays the creation of black-box software that collects this data is not a very difficult task. It is possible to detect suspicious unlawful events using this black-box data. In this paper, we present a novel way of doing forensic investigation using a modified sub-space K-NN (MSK) algorithm. The MSK algorithm is capable of detecting suspicious activities from mobile sensor data. Using this technique, we could detect any normal activity versus suspicious activity with 99.7 % accuracy. We expect the future researcher to develop on this idea and build a solid digital forensic system capable of doing bias-free decisions. Keywords: Forensic, Mobile sensor data, Black box, mobile data collection
AN ANALYSIS OF ABSTRACT USING MOVE MODEL ON HYLAND’S THEORY IN PROJECT JOURNAL ARTICLE

An abstract is one of the important parts in a research paper. It must give detail information to the readers. This research aimed to analyze abstracts’ content by using Move model proposed by Hyland (2003). It consists of introduction, purpose, method, result or product, and conclusion. This research used a qualitative method which specifically used content analysis design. Content analysis design was used because the researcher analyzed the content of abstracts taken from PROJECT Journal article which meant whether the writers presented the detail information as Move model or not. Evidently, from 15 articles analyzed, it was only one person who displayed detail information which was appropriate with Move model and the others were still not what the researcher expected except in informing the methods used. From the result of analysis, the understanding of writers about giving detail information in an abstract still lacks. It proves that the data finding presented in the result showed the weakness of abstracts which were not suitable yet with Move model.
SURFACE STRATEGY TAXONOMY: ERROR ANALYSIS IN ACADEMIC WRITING

This research aimed at describing the types of errors and their sources produced by 25 students of the Academic Writing Class of the Talent Scouting Program at IAIN Salatiga. This research used a qualitative method using students' writing assignments as the data source. The Theory of Surface Strategy Taxonomy was used in the data analysis. In finding the source of error, the researcher used comparative analysis. This study found four types of errors, with a total of 29 errors, including the omission 17 times, misinformation 5 times, addition 5 times, and misordering 2 times. Meanwhile, four error types were found for the source of errors: developmental or intralingual errors 14 times, unique errors 6 times, interlingual errors 2 times, and ambiguous errors 7 times.
THE STUDENTS’ NEWS WRITING DIFFICULTIES BASED ON COGNITIVE PROCESS

What are the students' news writing challenges in the fourth semester of Grade E, according to this study's major issue? And what are the cognitive process-based characteristics that affect the students' difficulty with news writing in the fourth semester of grade E? The goal was to determine the students' news writing challenges in the fourth semester of Grade E and the factors affecting those challenges based on the students' cognitive processes at that time. The focus of the study was the fourth semester's twenty-two student population. The Qualitative Research Method was employed in this study. The information was acquired through observation, document (news articles written by students), and interview. The results demonstrated that there are two categories of students who have trouble pre-writing and pre-drafting a news article. The outcome showed there are nine students.