Reviewerly/exHarmony huggingface dataset:
Matching Embeddings for Domain Adaptation

In this work we address the problem of transferring knowledge obtained from a vast annotated source domain to a low labeled target domain. We propose Adversarial Variational Domain Adaptation (AVDA), a semi-supervised domain adaptation method based on deep variational embedded representations. We use approximate inference and domain adversarial methods to map samples from source and target domains into an aligned class-dependent embedding defined as a Gaussian Mixture Model. AVDA works as a classifier and considers a generative model that helps this classification. We used digits dataset for experimentation. Our results show that on a semi-supervised few-shot scenario our model outperforms previous methods in most of the adaptation tasks, even using a fewer number of labeled samples per class on target domain.
Rx, Ry and Rz Rotation Operators of Spin 4 Systems in Quantum Information Theory

Quantum computing requires use of various physical techniques together with quantum theory. One of the promising systems is spin systems as applied and seen in pulsed nuclear magnetic resonance (NMR) and pulsed electron paramagnetic resonance (EPR) spectroscopies and hence spin-based quantum information technology. Construction of higher spin systems and related rotation operators is important for the theoretical infrastructure that can be used in quantum information theory. It is expected that as the value of spin increases, it will give way to longer time in the computation with bigger data. Spin operators up to spin-4 have been published in previous studies. In this work, explicit symbolic expressions of x, y and z components of rotation operators for spin-4 were worked out via exponential operator for each element of related spin operator matrices and simple linear curve fitting process. The procedures gave out exact expressions of each element of the rotation operators. It can be predicted that quantum rotation operators for higher spins, like spin-4, will theoretically and practically contribute to spin-based quantum information technology.
High Recall Data-to-text Generation with Progressive Edit

Data-to-text (D2T) generation is the task of generating texts from structured inputs. We observed that when the same target sentence was repeated twice, Transformer (T5) based model generates an output made up of asymmetric sentences from structured inputs. In other words, these sentences were different in length and quality. We call this phenomenon "Asymmetric Generation" and we exploit this in D2T generation. Once asymmetric sentences are generated, we add the first part of the output with a no-repeated-target. As this goes through progressive edit (ProEdit), the recall increases. Hence, this method better covers structured inputs than before editing. ProEdit is a simple but effective way to improve performance in D2T generation and it achieves the new stateof-the-art result on the ToTTo dataset
Basic English conversation training for tourism actors on Untung Jawa Island

During the Covid-19 pandemic, tourism activities almost stopped. Tourism actors on the Untung Jawa island attempt to improve tourism facilities and infrastructure and increase the capacity of their human resources. The purpose of this activity is to improve communication skills in English. The results of the pre-training questionnaire show that the required English is conversational English at the basic level. The method of community service activities is online basic level conversational English training using drill techniques. The materials are arranged according to language functions and the participants are divided into small groups of four to six people. The results of the activity showed that the participants were able to initiate and engage in short conversations using phrases and making short narratives.
Improvement of design anti-pattern detection with spatio-temporal rules in the software development process

In [1] we presented a framework for mining spatiotemporal rules in the software development process.The rules are based on specific relations between structures of the source code which relate both to spatial (e.g. a direct call between methods of two classes) and temporal dependencies (e.g. one class introduced into the source code before the other) observed in the process.To some extent, spatio-temporal rules allow us to predict where and when certain design anti-patterns will appear in the source code of a software system.This paper presents how, with slight modifications, such framework can be used to improve the quality of detecting a few popular design anti-patterns, such as Blob, Swiss Army Knife, YoYo or Brain Class.In the proposed method, we not only check the structure of a piece of the source code, but we also analyse its spatio-temporal relations.Only on the basis of the two analyses can we decide if the given piece of code is an anti-pattern.Experimental validation shows that the addition of spatio-temporal perspective improves detection of anti-patterns by 4% in terms of F-measure.
Two new operations over extended index matrices and their applications in Big Data

The Index Matrices (IMs) are extensions of the matrices of algebra.Over the IMs different operations, relations and operators are defined.In the present paper, two new operations over IMs are defined and some of their properties are studied.An application of these operations for describing of Big Data procedure is discussed.Hortonworks Data Platform (HDP) is used to provide capabilities for data warehouse processing in the Big Data environment.Apache Hive is selected for data warehouse construction and querying.Firstly, data warehouse for product sells is implemented.The tables for employees, customers, products and product sells are created.Thereafter the new index matrix operations for difference between two IMs are executed for the first time in the Big Data environment .SQL queries are written to demonstrate the operations.The new index matrix operations are executed using SQL JOIN notation and logical operator NOT EXISTS.
Three-way Learnability: A Learning Theoretic Perspective on Three-way Decision

In this article we study the theoretical properties of Three-way Decision (TWD) based Machine Learning, from the perspective of Computational Learning Theory, as a first attempt to bridge the gap between Machine Learning theory and Uncertainty Representation theory.Drawing on the mathematical theory of orthopairs, we provide a generalization of the PAC learning framework to the TWD setting, and we use this framework to prove a generalization of the Fundamental Theorem of Statistical Learning.We then show, by means of our main result, a connection between TWD and selective prediction.
Pelatihan Dan Pengembangan Media Pembelajaran Dori (Ludo Surili) Berbasis Ekoliterasi Dengan Memanfaatkan Limbah Industri Rumah Tangga Kain Perca di Desa Langonsari Kabupaten Bandung

There are potentials and problems that occur in Langonsari Village, namely patchwork waste originating from the UMKM industry and waste can be used as potential, one of which is as a learning media material. With the problem of waste, elementary school students must be able to recognize and have a caring attitude towards the environment which is often called ecoliteracy and the development and training of learning media must continue to be carried out both for teachers and the community. One example of learning media is DORI (Ludo Surili) which is adapted from Ludo but has a different size. The research subjects consisted of training for partners and development for 16 elementary school students who were divided into 4 groups. Data collection techniques are observation, questionnaire, pre-test and post-test. The learning media development techniques consist of: (1) the planning phase, (2) the preparation phase, (3) the implementation phase and (4) the evaluation phase. The results of the study on the effectiveness of learning media showed that with a percentage of 97.463 in the very good category, while the results of the pre-test and post-test showed that the average value had increased, both individually or as a whole, the increase showed that the pre-test was at number 42, 7 and on the post-test at 68.2 so that students are able to understand the material given with DORI learning media.&#x0D;
RANCANG BANGUN SISTEM NOMER ANTRIAN BERBASIS INTERNET OF THINGS (IOT)

Queuing is a phenomenon that we can encounter anywhere and anytime, such as queuing to get food orders, ticketing services, and so on. However, unfortunately not everyone likes to queue, especially queuing for public agency services. This is because of various kinds, such as irregular queues, the number of people queuing so that it makes people lazy to queue, or even because there is a sudden need so they cannot queue for long. Especially during the Covid-19 pandemic, people avoid physical contact between each other, so to overcome this, an organized queue number system is needed and can be ordered online through an application on a smartphone. Customers can order a queue number and monitor the queue number being served through an application on a smartphone, there is also a call to each queue number to be served. This research also applies the internet of things (IoT) system which is used to display the queue number served on a P10 LED Display.
Distance technologies in the organization of asynchronous education of students: challenges, problems, solutions

Abstract. New computer technologies, which became the cause of the information revolution in education in the second half of the 20th century, gave impetus to the rapid development of distance learning methods and the formation of the concept of open education. Distance learning at the turn of the second and third millennia became a global phenomenon and significantly changed the structure of education systems in many countries of the world. In the conditions of the information society, during the avalanche-like growth of the amount of knowledge accumulated by mankind, the intensity of updating theoretical provisions, practical information, and experimental results, necessary for use in various spheres of human activity, increases. The objective necessity of development and improvement of knowledge transmission mechanisms, which provide the possibility of continuous training of a large number of people throughout their lives in accordance with the needs of the individual and society, is becoming urgent. The problem of the introduction of remote technologies into the educational process became particularly widespread during the coronavirus pandemic. However, asynchronous distance learning itself became especially relevant with the beginning of hostilities on the territory of Ukraine, which led to the restriction of education seekers in access to the Internet, damage to telecommunication networks, lack of electricity supply, mass migration of refugees, the destruction of educational institutions, the involvement of education seekers in the ranks of the territorial defense etc. There was a need to organize the educational process and present educational materials, conduct control measures considering all the circumstances of today. Thus, Sumy State University, with the support of the distance learning MIX platform, organized distance learning for students of physical and technical specialties in synchronous and asynchronous distance format. The work highlights the peculiarities of providing educational services to students with limited access to educational materials (work in an asynchronous format). The article focuses on the issues of training organization, which consider the student's work in an asynchronous format. Explanations are provided for some special aspects of the organization of such training. An analysis of the advantages and disadvantages of the chosen form of work was made. The article highlights further directions of work on improvement and optimization of relevant educational materials and forms of their presentation to extend learning in today's difficult conditions. Key words: distance learning, synchronous and asynchronous learning format, MIX distance learning platform, and remote access, mathematical and physical disciplines.
A CONCEPTUAL CLASSIFICATION MODEL OF KNOWLEDGE AS A WAY TO IMPROVE UNIVERSAL DECIMAL CLASSIFICATION

The article deals with the urgent task of improving the universal decimal classification (UDC) in connection with its numerous shortcomings. The examples given in the article show that the well-known rules for constructing classifications are violated in the UDC and the system principles for constructing classification models are not applied. These circumstances turn UDC indexing into a complex and extremely time-consuming creative, heuristic process, the result of which in many cases, in principle, cannot be correct. To solve the problem, a systematic approach to the construction of conceptual classification models (CCM) was applied, which allows representing a conceptual (conceptual) model of the form and content of knowledge, which will ensure the ease of its perception, memorization and use, as well as the uniqueness of solving the problem of choosing a document index on the content and form of information. The basic classification of knowledge and the classification of knowledge by content and form are presented, on the basis of which classifiers of specific subject areas can be developed.
Secondary Students' Perceptions on Learning Management System in the Midst of Covid-19 Pandemic

The breakthrough of using Learning Management System (LMS) is urgently required nowadays midst pandemic era to boost the outcome of teaching learning. Such facts proved that the provided LMS are felt to be difficult and complicated that students are discouraged to operate them. Therefore, this paper aimed at exploring students’ perceptions about the implementation of LMS used. It was sequential explanatory mixed-method research design involved 48 students from various secondary schools in Semarang as the samples. The questionnaire distributed using Google Form was then analyzed to identify their perceptions about LMS quantitatively and qualitatively. The result shows that the highest need was about the need of platform which covers a synchronous learning process (63%) and interaction between students and students, both in small groups and large groups (60%), also platform that has been equipped with facilities/menus that accommodate students in order to improve their critical thinking habits (54%). As solution, they need platform which has more interesting menu options so as to make students not to be bored in the learning process (54%), they also need simple platforms covering synchronous and asynchronous activities (54%). They even need platform which has menus where teachers can give feedback or correction on students’ work independently both in small and large groups. Therefore, the findings of this study incite the researchers to design a Hybrid Smart Learning System in order to fulfil the students’ need and build students’ metacognition.&#x0D; Keywords: Students’ perceptions, LMS, secondary schools, covid-19 pandemic
Performance comparison between selected chess engines

Selected chess engines were compared to each other in terms of performance, using Lucas Chess. The list of engines was cut into three categories, depending on strength in ELO points. The point of this study is to find the strongest and the lightest engines in each category. Then, each category was tested using three different starting positions. White, black and overall wins were highlighted. At the same time, data of CPU and RAM usage of each engine was collected. A script was developed to print CPU and RAM usage of a specific process. Maximum and average percent of used CPU thread and RAM were highlighted. Chess engines with most amount of wins were, from weakest to strongest: Bikjump, Rybka and Stockfish. Least amount of system resources was consumed by: Cinnamon, Demolito and Critter.
Pembatasan Akses Menggunakan MAC Address dengan Metode Access Control List

The Cangehgar Cyber Command Center of the 14th Arhanud/ PWY Battalion from Cirebon City is one of the offices with IT equipment to assist the job. The servers, like the office PCs, are connected via the local network. Due to the risk of leaking secret data from within, network security concerns must be handled so that unauthorized users cannot mistakenly access the server. It seeks to limit access when there are administrative customers and employees in each room by utilizing the access control list approach using a MAC address. Access to the server is restricted to the administrator's computer, while access to the employee's PC is disallowed. Then the questionnaire was distributed to find out the respondent's assessment of the access control list. According to the results of the study on security indicators, access control lists containing MAC addresses are useful in limiting access to server computers.
DISTANCE LEARNING IN SERBIA – THE EXPERIENCE IN PRIMARY EDUCATION DURING THE COVID-19 CRISIS

In this paper, we consider the response of the education system of the Republic of Serbia to the COVID-19 epidemiological crisis in relation to the teaching process and distance learning activities in primary schools in Serbia. We examine learning through the televised programs of Serbia’s public broadcaster and other related internet services. The aim of this research is to estimate the quality of the teaching process and distance learning in primary schools. In accordance with the purpose of the research, a questionnaire about the educational experience and practices in primary schools during the spring and autumn of 2020 was created. The questionnaire is designed for school principals, teachers, students and parents/legal guardians of students. In total, 28186 people participated in this study conducted in March and April 2021. The results show that most schools used online resources efficiently despite the initially low digital competencies of teachers and students. Limited access to the internet and digital resources, as well as difficulties in engaging students, were gradually overcome during the fall of 2020. Based on the results of this research, we formulated the most important recommendations for the organization of distance learning and its future integration in the hybrid model of teaching and learning in school practice.
Academic Satisfaction of Pedagogy Students Regarding Learning in Virtual Mode

The Covid-19 pandemic in Chile was declared as such in March 2020. As a result, the Ministry of Education compiled guidelines to provide continuity to the formative processes, through which the concept of remote learning emerged. This research paper aims at identifying academic satisfaction of pedagogy students in a higher education institution (HEI) regarding learning in the virtual mode in the pandemic context. A quantitative, non experimental, cross-sectional methodology was used. The sample consisted of 337 students in 6 pedagogical courses at an HEI in the Araucanía region to whom a questionnaire on satisfaction with virtual teaching was administered. Results indicated that student satisfaction was low regarding the way content was handled and evaluation mechanisms used in the virtual mode. However, high satisfaction was shown in the items corresponding to teacher-student interaction. In addition, we found no statistically significant differences in the items related to the fulfillment of expectations and learning achieved in the virtual mode, either by gender, level of study, program, or academic performance. Finally, there was high dissatisfaction with virtual teaching during the present academic cycle. We recommend the systematic evaluation of the indicators of educational quality, mainly linked to the treatment of the content, the evaluation mechanisms used, and the teacher-student interaction channels, since they improve the academic performance of HEIs.
Optimizing the role of the Cahaya Ilmu library in Selomirah Village, Ngablak, Magelang Regency

Social inclusion library is a National Library program that aims to improve the quality of human resources through literacy. This community service program aims to create a social inclusion library. The method used in this community service program goes through four stages, namely: observation, socialization, training, and mentoring. This community service activity received a positive response and was able to improve the knowledge and skills of librarians in realizing social inclusion-based libraries through various literacy improvement programs for the community.
Online English Learning in the Middle of Covid-19 Pandemic in English Education

Language is a tool that humans use to communicate with each other. As a communicative social tool, we need to differentiate the use of language based on the purpose of communication. This study uses a qualitative approach with ethnographic methods. Data was collected through observation, interviews, and documentation review. Data analysis was carried out based on the analysis model using domain, taxonomy, componential, and cultural theme analysis. The results of the research on the process of learning English at STKIP PGRI Trenggalek showed that it was very good and effective in increasing competence in mastering English because all the learning processes carried out were made based on careful planning. In addition, a good learning process is also supported by students who are motivated to learn and teaching lecturers who are always eager to continue to innovate themselves and have adequate learning facilities.
Multi-Stage Contour Primitive of Interest Extraction Network with Dense Direction Classification

For intelligent vision measurement, the geometric image feature extraction is an essential issue. Contour primitive of interest (CPI) means a regular-shaped contour feature lying on a target object, which is widely used for geometric calculation in vision measurement and servoing. To realize that the CPI extraction model can be flexibly applied to different novel objects, the one-shot learning based CPI extraction can be implemented with deep convolutional neural network, by using only one annotated support image to guide the CPI extraction process. In this paper, we propose a multi-stage contour primitives of interest extraction network (MS-CPieNet), which uses the multi-stage strategy to improve the discrimination ability of CPI and complex background. Second, the spatial non-local attention module is utilized to enhance the deep features, by globally fusing the image features with both short and long ranges. Moreover, the dense 4-direction classification is designed to obtain the normal direction of the contour, and the directions can be further used for the contour thinning post-process. The effectiveness of the proposed methods is validated by the experiments with the OCP and ROCM datasets. A 2-D measurement experiments are conducted to demonstrate the convenient application of the proposed MS-CPieNet.