Reviewerly/exHarmony huggingface dataset:
Perceptions of Chemistry MGMP Teachers of MA West Sumatera on the TrainingActivities for Development of Teaching Material in the Form of E-Modules

Teaching materials are something that cannot be separated from every learning activity,therefore the skills of teachers in developing teaching materials need to be trained, one of which isthrough community service activities. The purpose of this activity is to train the skills of MGMPChemistry MA teachers in West Sumatra in developing teaching materials in the form of e-modules.The training method is carried out online and offline. Participants in the activity totaled 37 state andprivate madrasah chemistry teachers from several districts / cities in West Sumatra. Data collection wascarried out using a questionnaire. The data obtained were analyzed by using the percentage technique.From the results of the questionnaire analysis, the average percentage of participants' assessment of theimplementation of activities was 90% (very good), the delivery of material by the informants was 89%(very good), and the benefits of the activities for participants were 85% (very high). This data showsthat the MA Chemistry MGMP teachers throughout West Sumatra have very good perceptions of theimplementation, presentation of material, and the benefits of community service activities that havebeen carried out to train the skills of teachers to develop teaching materials in the form of e-modules.
Evaluation of Software Fault Proneness with a Support Vector Machine and Biomedical Applications

The high throughput and good quality software are developed if effective defect prone modules can be predicted by testers at early stages. This enables the testers to focus on the activities, allocation of effort, and efficient resource management. Accurate prediction of fault inclined modules in software development manner allows effective detection and identity of defects. The existing researches used support vector machine (SVM) in standalone mode in the sense that no pre-processing is performed before invoking classification; thus degrading the accuracy of prediction. This chapter delivered a singular approach combining SVM and feature choice for software fault proneness prediction (SFPP). Experiments suggest that the accuracy of the proposed method using five object-oriented (OO) metrics, that is, line of code (LOC), program level (L), branch count (BR), and unique operands. Hence, the OO metrics have a large prone in defect prone modules.
3P-624 : Deep learning for an image recognition of plant engineering diagram

A piping and instrumentation diagram (P&ID) is a core drawing in the EPC(Engineering, Procurement, Construction) industry because it contains information about the units and instrumentation of the plant. Until now, simple repetitive tasks, such as listing symbols in P&ID drawings, have been done manually. Currently, a deep learning model based on CNN(Convolutional Neural Network) has been studied for drawing object detection, but the detection time is too long and the accuracy is not satisfactory to be implemented in the practical application. In this study, the detection of symbols in a drawing was performed using the 1-stage object detection algorithm, YOLO(You Only Look Once). Specifically, we built the training data using the image labeling tool, and trained it on the model. Next, the performance of the model was compared with the conventional recognition algorithms.
HUMANITARIAN SELF-DETERMINATION OF A PERSONALITY: REGIONAL AND AXIOLOGICAL ASPECTS

Problem statement of this study links with the relevance of the authors’ longitudinal research in-tended to meet the pedagogues’ interests, possibilities, and their motives for recurrent education based on personalized training strategy and tactics in the frameworks of current university edu-cation and additional professional programmes of the In-Service Institute. The purpose of this paper is to stand back from the surface details of formal and informal education of teachers and to provide some of the prospects on creating axiological priorities of professional education spaces in line with innovative approaches to teaching and learning the ways of interpretation of database on the «difficult» issues of National History and Culture. Methodology and materials of the research reflect on the main concepts of acculturation of the educational environment, harmonious interaction of both educators and learners, historical memo, national and language consciousness which constitute the basis for the comprehensive value dominant model, and are focused on transforming the socio-cultural atmosphere of a particular region and the country where the dominant values of national and cultural identity have sharply worsened during the past twenty years. Results and their discussion based on scientific exposition that concern the axiology of the problem statements distinguished via three main groups of scholarship, method-ology and pedagogy of civil education and national public school education in the frameworks of the problem issues of what to teach (Knowledge Content) and the issue of how to establish for training and learning of students innovation educational practices (Technological Aspects) for efficacy (Personality ConceptSphere of Dominant Values). In conclusion, there come some of the authors’ findings on personalized training and learning that compose the axiological model of «management techniques» on the solution of «difficult» questions of Russian history integrat-ed into the concept sphere of the learner via the Thesaurus and Knowledge Content efficacy of additional professional programmes.
THE USE OF TEXT WALK STRATEGY IN TEACHING READING COMPREHENSION AT THE EIGHTH GRADE STUDENT OF SMP DHARMA YADI MAKASSAR

This research aimed to determine whether or not the use of Text Walk Strategy improves the students reading comprehension. This research used a pre-experimental method. The total of sample was 20 students by using purposive sampling technique by taking class 2B. In collecting data the researcher used reading test which administered in pre-test and post-test. The result of the data showed that the mean score of students in pre-test was 55.25 and the mean score in post-test was 75. It means that the mean score of students post-test was higher than the mean score of students in pre-test. The t-test value was higher than the t-table (13.42>2.093). Based on the result of data analysis, it can be concluded that Text Walk Strategy improves the students’ reading ability at the eighth grade students of SMP Dharma Yadi Makassar
DEVELOPING READING MATERIALS BY USING QUIZIZZ FOR 10TH GRADE STUDENTS OF COMPUTER AND NETWORK ENGINEERING MAJOR AT SMK NEGERI 1 GALANG

This study focuses on how reading text are developed for vocational school. The objective of this study was to develop reading materials by using Quizizz for tenth grade students of computer and network engineering major of SMK Negeri 1 Galang. This study was conducted by using Research and Development (R&D) design. It was started from collecting data, analyzing data, designing new materials, validating to experts, and revising for final product. The subject of this study was grade X students of Computer and Network Engineering major at SMK Negeri 1 Galang consisting 21 students. The instruments of collecting data were documents, questionnaire, and interview. The interview and questionnaire result proved that the students’ need the reading materials which contain terms related to Computer and Network Engineering. The reading materials were focused on descriptive text. The developed reading materials were validated by two experts. The average score from English Lecturer were 3.56 and from English Teacher were 3.66. It shows that the reading materials categorized as relevant for students of Computer and Network Engineering major grade X. The result of product distributed to the students by using Quizizz.
Responses from the centre

The evolution of the response of policy makers to the emergence of cryptoassets is presented as falling into four phases. Emergence: when cryptoassets first appeared on the radar of regulatory agencies. Counteraction: when regulatory agencies first began to impose their authority, typically to restrict practices. Traction: when most regulatory agencies and international bodies recognized that cryptoassets were here to stay in one form or another and began to recognise the desirability of regulating the industry at a more granular level. Point of no return: when regulations began to change, or proposals for change put forward, to accommodate cryptoassets. The fifth phase now getting underway may represent the ossification of a vector of thinking informed more by past experiences than by future possibilities, a topic that is returned to in Part 4.
ASMMC21: The 6th International Workshop on Affective Social Multimedia Computing

Affective social multimedia computing is an emergent research topic for both affective computing and multimedia research communities. Social multimedia is fundamentally changing how we communicate, interact, and collaborate with other people in our daily lives. Comparing with well-organized broadcast news and professionally made videos such as commercials, TV shows, and movies, social multimedia media computing imposes great challenges to research communities. Social multimedia contains much affective information. Effective extraction of affective information from social multimedia can greatly help social multimedia computing (e.g., processing, index, retrieval, and understanding). Although much progress have been made in traditional multimedia research on multimedia content analysis, indexing, and retrieval based on subjective concepts such as emotion, aesthetics, and preference, affective social multimedia computing is a new research area. The affective social multimedia computing aims to proceed affective information from social multi-media. For massive and heterogeneous social media data, the research requires multidisciplinary understanding of content and perceptual cues from social multimedia. This workshop served as a successful step towards this goal and attracted contributions from different research disciplines on the analysis of affective signals in interaction (multimodal analyses enabling artificial agents in Human-Machine Interaction, social Interaction with artificial agents) and social multimedia (e.g., twitter, wechat, weibo, youtube, facebook, etc). This paper provides a summary of the activities of the workshop and the accepted papers and abstracts.
Attribute-Based Encryption Scheme for Secured data Storage in Cloud Computing

This a storage security model in Cloud Computing and making a considerable measure of convincing purposes behind organizations to convey cloud-based storage. For another business, start-up costs are fundamentally decreased in light of the fact that there is no compelling reason to contribute capital in advance for an inner to help the business. By a long shot, the main inquiry customers considering a move to cloud storage ask is regardless of whether their data will be secure. Stored data offsite doesn't change data security necessities; they are the same as those confronting data put away on location. Security ought to be based on business prerequisites for particular applications and data sets, regardless of where the data is stored. We trust that data storage security in Cloud Computing, a zone brimming with challenges and of fundamental significance, is still in its earliest stages now, and numerous examination issues are yet to be distinguished. In this paper, we examined the issue of data security in cloud data storage, to guarantee the rightness of customers' data in cloud data storage. We proposed a Hierarchical Attribute-Based Secure Outsourcing for moldable Access in Cloud computing which likewise guarantees data storage security and survivability accordingly giving put stock in condition to the customers. To battle against unapproved data spillage, delicate data must be encoded before outsourcing in order to give end-to-end data confidentiality affirmation in the cloud and past. It upgrades the security in the proposed model successfully.
Pengaruh Model Problem Based Learning (PBL) terhadap Hasil Belajar Siswa SDI Tangkala 1

One of the efforts made to overcome the low learning outcomes is the selection of the right learning model. The purpose of this study was to determine the application of the Problem Based Learning model and its effect on science learning outcomes for class V SDI Tangkala 1. This research approach was quantitative, the type of experimental research was quasi-experimental design. This research is located at SDI Tangkala 1. The population of class V SDI Tangkala 1 Makassar City is 36 students. The sampling technique used saturated sampling, so the number of samples remained 36 students. Data collection techniques: tests, observations and documentation. Data analysis techniques: Descriptive and inferential statistics. Independent sample T-Test hypothesis test. The results showed that the application of the Problem Based Learning model could be carried out well based on the stages of learning. The results of the study showed that the average value in the experimental group was higher than the control group. There is an effect of the Problem Based Learning model on the science learning outcomes of fifth grade students of SDI Tangkala 1 based on the analysis test stating that the t-count value is greater than the t-table value.
A Comparison of Back propagation and PSO for training RBF Neural Network for Wavelet based Detection and Classification of Power Quality Disturbances

This paper introduces a novel approach to detect and classify power quality disturbances in the power system using Radial Basis Function Neural Networks (RBFNN) trained by Particle Swarm Optimization (PSO).Back Propagation (BP) algorithm is the most commonly used for training, but it suffers from extensive computation and also convergence speed is relatively slow. Feature extracted through the wavelet is used for training. After training, the weight obtained is used to classify the power quality problems. For classification, 8 types of disturbance are taken in to account. The classification performance of RBFNN trained PSO algorithm is compared with BP algorithm. The simulation result using PSO possess significant improvement over BP methods in signal detection and classification
Many are Better Than Few: Financial Isolation and Political Violence in Africa

This paper investigates how misconduct, in the form of state-level human rights violations, is reflexively related to the concentration of external relationships, in the form of global financial ties. The argument is agnostic to which comes first, though the evidence demonstrates different predictive pathways for each. State-caused deaths resulting from political violence, a clear violation of human rights, across Africa from 2003 through 2015 serve as the macro-level form of misconduct. Descriptive and econometric analyses demonstrate that homogeneity of foreign financial ties has a direct predictive effect on state-caused political deaths. Foreign countries, however, vary in their reactions to this misconduct. I find that bilateral relations based in natural resource trade and colonial ties are durable to and even grow following such misconduct events. Identifying types of relationships durable to misconduct demonstrates a mediated pathway through which misconduct may result in the homogeneous relations that support rather than deter misconduct. Adding these country-level results to previous work at individual and group levels suggests a generalizable way of understanding the prevalence of misconduct by demonstrating relational accounts of the causes and consequences of misconduct across levels of analysis.
WHATSAPP: NUEVA VÍA DE EDUCACIÓN A LAS FAMILIAS DE LOS NIÑOS CON TEA EN TIEMPOS DE PANDEMIA

This article communicates the experience of researchers on education and guidance to families with children with autism spectrum disorders in the face of the challenges posed by the Covid-19 epidemic. Today the co-responsibility of families is increasing, together with the teachers of the comprehensive education of children and adolescents; however, we are living a historical stage of transformations; new ideas are imposed in confrontation with traditions of the previous society, which was marked by inequity in social relationships. The advent of the epidemic and its demands for isolation caused changes in social life. In the new context, the relationships between the school and the families were restricted, the educators saw their help and guidance to the parents diminished. In this situation, we proposed to promote alternatives to maintain and develop the spaces for participation and education for families.
Towards Evaluating the Representation Learned by Variational AutoEncoders

At the heart of a deep neural network is representation learning with complex latent variables. This representation learning has been improved by disentangled representations and the idea of regularization terms. However, adversarial samples show that tasks with DNNs can easily fail due to slight perturbations or transformations of the input. Variational AutoEncoder (VAE) learns $P(z\vert x)$ , the distribution of the latent variable $z$ , rather than $P(y\vert x)$ , the distribution of the output $y$ for the input x. Therefore, VAE is considered to be a good model for learning representations from input data. In other words, the mapping of $x$ is not directly to $y$ , but to the latent variable $z$ . In this paper, we propose an evaluation method to characterize the latent variables that VAE learns. Specifically, latent variables extracted from VAEs trained by two well-known data sets are analyzed by the k-nearest neighbor method(kNN). In doing so, we propose an interpretation of what kind of representation the VAE learns, and share clues about the hyperdimensional space to which the latent variables are mapped.
PENGEMBANGAN MULTIMEDIA INTERAKTIF BERBASIS ANDROID UNTUK MENINGKATKAN PRESTASI BELAJAR GEOGRAFI PADA SISWA KELAS X DI SMA NEGERI 1 PAGAR ALAM

This study aims to describe the development of android-based interactive multimedia that was feasible to be developed to improve geography learning achievement and to describe the effectiveness of android-based interactive multimedia that was developed to improve geography learning achievement. This research is included in research and development (Research and Development). The research subjects were students of class in X SMA Negeri 1 Pagar Alam. The data collection technique was done by using assessment sheets and student achievement test. The data analysis used mean and t-test. The conclusion of this research was that android-based interactive multimedia which was developed is feasible to improve geography learning achievement and android-based interactive multimedia which developed was effectively to improve geography learning achievement of tenth grade students at SMA Negeri 1 Pagar Alam
The Impact of Good Ui Design

In this era of rapid Internet development, software development exists in any field. UI design, as a vital link in the software design process, is inseparable in every field. This report conducts in-depth research on what is good UI design based on previous research. And what impact a good UI design can have on the software. Finally, I studied how to maintain a good UI design, and what aspects of the current UI design field need to be improved.
ANALISIS MINAT BELAJAR SISWA MELALUI MEDIA MONOPOLI KERAGAMAN SUKU (MORASU) PADA TEMA 7 SUB TEMA 1 KELAS IVB DI SDN 2 SURODAKAN KABUPATEN TRENGGALEK

Interest in learning for IVB graders at Surodakan Elementary School 2, Trenggalek Regency is less than optimal. This condition is characterized by the presence of students who are less active and busy themselves. So that researchers conduct research to find out how much students interest in following the learning process. To find out the interest in learning students, learning media is used. One of the media used is the media monopoly on ethnic diversity (morasu). The media is adapted to the learning material in class IVB students.This study uses descriptive qualitative methods. All problems and results will be explained in detail according to the conditions in the field. The research subjects were IVB graders, which numbered 34 students. To obtain information, researchers as the main instrument will be assisted with supporting instruments, namely observation instruments, interviews, questionnaires and documentation.Based on the analysis of the data obtained, class IVB students showed greater interest in learning when learning using monopoly media. It can also be a lesson for teachers to be more creative. High interest in learning will give good results for further learning.
DEVELOPING REAL-TIME FACE MASK DETECTION WITH FACIAL TEMPERATURE MEASURE FOR COVID-19 INDOOR MONITORING SYSTEM

The coronavirus (COVID-19) is the latest pandemic that hit human health in 2019. Wear a face mask in public areas to decrease the spread of the coronavirus. This work presents real-time face mask detection with facial temperature measures for the COVID-19 indoor monitoring system. Detecting people using ultrasonic sensors, face mask detection, and facial temperature measure using Grid-Eye Sensor are three modules applied in the proposed system. We also evaluated the proposed monitoring system in the real environment and confirmed the accuracy of 98.8% of mask detection.
Όλα (;) επιτρέπονται: οι πραγματολογικές δεξιότητες στη ΝΕ/Γ2 ενήλικων προσφύγων

The current discussion focuses on teaching the speech act of offer-accept/deny a gift to an adult refugee target group that learns Greek as a second language and investigates the progress of the learners’ pragmatic competence as a result of targeted exposition to the speech act. The steps of the guidance towards the pragmatic norms of L2 are being elaborated and learners’ pragmatic output is being assessed over pragmatic failure. We argue in favor of explicit teaching the pragmatic aspect of L2, which is connected with the basic principles of functional literacy model framing our theoretical approach.
Challenges and Solutions in Inclusive Education: A Case Study With Group Investigation

Inclusive education gains the interest and the attention of all Romanian educational factors. However, the challenge of developing inclusive schools is not only for policy makers but also for teachers, professionals, parents and students alike. This qualitative case study explores through Group Investigation the lived experiences of primary school teachers in attempting to create an inclusive learning environment. The purpose of the study is to help students from Pedagogy, future educators, to become familiar with the inclusive education challenges and best interventions. Data have been collected through interviews, observations, and document analysis. Results showed that teachers face challenges due to their initial professional training not enough adequate to the inclusive education reality, diversity of special needs in classrooms, insufficient support from the families of the students with SENs, and a reduced number of itinerant teachers. The study offers participants’ solutions to cope with the inclusion challenges, showing that inclusive education can become a reality when educational factors work together.