Reviewerly/exHarmony huggingface dataset:
대면 서비스직 종사자의 COVID-19 스트레스, 정량뇌파 스트레스 지수와 대처방식의 상관분석

Purpose: This study aimed to measure COVID-19 stress and the quantitative electroencephalography (QEEG) stress quotient and identify the coping styles of face-to-face service industry employees during the COVID-19 pandemic. Methods: This cross-sectional study administered structured questionnaires consisting of sections on general characteristics, COVID-19 stress, and coping style for stress to 21 face-to-face service industry employees between April 1 and April 18, 2021. The physical tension & stress quotient and psychological distraction & stress quotient were measured in the prefrontal lobe with QEEG. Results: Emotional easiness (r=.62, p=.002) and escape-avoidance (r=.55, p=.009) as a passive coping style were associated with COVID-19 stress, and seeking social support as an active coping style was associated with the left physical tension & stress quotient (r=.47, p=.031). Conclusion: These findings provide evidence regarding the objective status of the mental health of face-to-face service industry employees using both a self-reported scale and neuroscientific indicators, including brain quotients.
Short-term solar power forecasting using satellite images

Solar irradiance forecasting will turn into a major challenge in the future integration of solar energy resources into existing structures of energy supply. There are squeezing requirements for app...
Improving the Quality of Training at Universities in Vietnam According to the Requirements of Digital Transformation in Education

Digital transformation in higher education is the comprehensive transformation of all institutions and activities of higher education based on digital technology. However, it is a difficult and complex process and still focuses mainly on the field of teaching and learning with the main manifestations of online education and open education. Due to different challenges and barriers on a global scale, digital transformation in higher education takes place in different ways, at different rates and paces from one region to another, country to country, even school to school in the same country. The objective of the research: to improve university governance capacity, take the digital transformation in higher education in Vietnam into practice, thereby improving the quality of training in universities in Vietnam. Research Methodology: SWOT analysis is used as a strategic technique to identify strengths, weaknesses, opportunities and challenges in university governance in the context of digital transformation. Research results: the research team assumes that at present there are still some limitations and challenges for the digital transformation in education. However, with the solutions being implemented by the government, the Ministry of Education and Training and related organizations the quality of higher education in Vietnam will be improved.
Algebraic Hardness versus Randomness in Low Characteristic.

We show that lower bounds for explicit constant-variate polynomials over fields of characteristic p > 0 are sufficient to derandomize polynomial identity testing over fields of characteristic p. In this setting, existing work on hardness-randomness tradeoffs for polynomial identity testing requires either the characteristic to be sufficiently large or the notion of hardness to be stronger than the standard syntactic notion of hardness used in algebraic complexity. Our results make no restriction on the characteristic of the field and use standard notions of hardness.We do this by combining the Kabanets-Impagliazzo generator with a white-box procedure to take pth roots of circuits computing a pth power over fields of characteristic p. When the number of variables appearing in the circuit is bounded by some constant, this procedure turns out to be efficient, which allows us to bypass difficulties related to factoring circuits in characteristic p.We also combine the Kabanets-Impagliazzo generator with recent bootstrapping results in polynomial identity testing to show that a sufficiently-hard family of explicit constant-variate polynomials yields a near-complete derandomization of polynomial identity testing. This result holds over fields of both zero and positive characteristic and complements a recent work of Guo, Kumar, Saptharishi, and Solomon, who obtained a slightly stronger statement over fields of characteristic zero.
Peningkatan Kapasitas Sumber Daya Manusia PAUD dengan Pelatihan Bahasa Inggris Di Kecamatan Nanggulan Kabupaten Kulon Progo Yogyakarta

Community service activities, specifically the Community Partnership Program (PKM), aims to improve the ability of Early Childhood Education (PAUD) teachers, both in terms of pronunciation and the methods that support it in Nanggulan sub-district, Kulon Progo district. The target audience for this service program are the PAUD teachers in SPS Tunas Harapan, which amount to 4 (four) people. The programs that have been implemented are training 1) How to pronounce English words, and 2) English methods for PAUD level. The overall process of science and technology transfer is carried out with a pattern of education and training that is equipped with socialization to these teachers to improve the ability and skills to use English developed through English language training (pronunciation on pronunciation or pronunciation) and methods and benefits to improve teacher ability and school quality.
Urdu Handwritten Characters Data Visualization and Recognition Using Distributed Stochastic Neighborhood Embedding and Deep Network

In this paper, we make use of the 2-dimensional data obtained through t-Stochastic Neighborhood Embedding (t-SNE) when applied on high-dimensional data of Urdu handwritten characters and numerals. The instances of the dataset used for experimental work are classified in multiple classes depending on the shape similarity. We performed three tasks in a disciplined order; namely, (i) we generated a state-of-the-art dataset of both the Urdu handwritten characters and numerals by inviting a number of native Urdu participants from different social and academic groups, since there is no publicly available dataset of such type till date, then (ii) applied classical approaches of dimensionality reduction and data visualization like Principal Component Analysis (PCA), Autoencoders (AE) in comparison with t-Stochastic Neighborhood Embedding (t-SNE), and (iii) used the reduced dimensions obtained through PCA, AE, and t-SNE for recognition of Urdu handwritten characters and numerals using a deep network like Convolution Neural Network (CNN). The accuracy achieved in recognition of Urdu characters and numerals among the approaches for the same task is found to be much better. The novelty lies in the fact that the resulting reduced dimensions are used for the first time for the recognition of Urdu handwritten text at the character level instead of using the whole multidimensional data. This results in consuming less computation time with the same accuracy when compared with processing time consumed by recognition approaches applied to other datasets for the same task using the whole data.
PENERAPAN MODEL PEMBELAJARAN EXAMPLE NON-EXAMPLE DENGAN MEDIA GAME EDUKASI QUIZIZ DALAM MENINGKATKAN HASIL BELAJAR SISWA

This study aims to determine the increase in student learning outcomes after applying the Non-Example Example learning model with the Quiziz Educational Game media to improve student learning outcomes in the seventh grade Solar System material at Maria Goretti Kabanjahe Private Junior High School. The no-example example learning model with quiziz game media is a learning strategy that uses pictures and videos as a medium to convey subject matter with the help of quiziz educational games as a medium in delivering the test instruments carried out. The subjects of this study amounted to 26 students. This non-example example method uses pretest and posttest actions in cycle I and cycle II, in order to improve student learning outcomes. Gradually in the pre-test, the average learning score was still 46.92 with a mastery percentage of 23.07%, followed by the first cycle, it was found that the student learning average was 48.46 and the percentage of completeness was 38.46%, there was a slight increase from before experiment was carried out. Then it was further improved in the second cycle, the researchers found an average learning score of 70.90 with a completeness percentage of 77.27%, it can be said that the improvement in student learning outcomes is getting better and increasing.
Pengembangan Media Animasi Berbasis Sparkol Videoscribe pada Materi Pembuatan Pola Celana Pria di Smk Negeri 1 Batu

This study aims to develop animation media based on Sparkol Video Scribe on the material making patterns of men's pants at 1 Batu Vocational High School. This is related to the development of technology, so that there is a need for new computer-based media that are more interactive to support the learning process The method used in this research is development research with ADDIE models. Stages of development carried out include: (1) analysis, (2) design, (3) development, (4) implementation, (5) evaluation. The research subjects in this development research were class XII students of the Boutique Clothing Department at 1 Batu Vocational High School totaling 26 students. The developed media contains learning objectives and competencies, the understanding of men's pants and men's pants patterns, sizes, and animated video tutorials for making men's pants patterns. The feasibility of the media that has been made is tested on material experts, media experts and linguists, after being repaired and declared feasible then proceed to the implementation phase of the XII grade students of the Boutique Clothing Department at 1 Batu Vocational High School. The results of expert validation and field trials state that learning media that have been developed are suitable for use with the following results: material expert validation was 92.7 percent, media expert validation was 97.2 percent, language expert validation was 97.5 percent. Data from the field trial results was 92.74 percent. Based on these results it can be concluded that the developed animation media is suitable as a learning media. The media developed are clear, easy to understand and easy to operate, an attractive media display can motivate and attract students to learn because the media can be used as a means of independent learning. Suggestions for further researchers should be the duration in the video tutorial for making men's pants patterns slowed down so that students find it easier to follow the stages of learning.
Deep Learning Model Development to Classify Technology from Social Media

The important characteristic of societal platform is the unremitting cohort of content which leads to root of novel data out of it. Community platforms are active in nature and they can be painstaking as new type of data resources for upcoming trend forecasts with application of data analytics technique. Due to world-wide contribution in open-source technologies, new technologies are released frequently. The innovation and instruments learned by individuals become supplanted in a brief timeframe. As the I.T. industry required regular overhauls in abilities and new advancements are being discharged, it is basic to trail and realize novel upcoming innovation patterns of the field. To accomplish this point, a deep learning model is created to distinguish up and coming innovations from internet-based life strings. This paper presents technology classifier model to categorize unstructured text content in to relevant technologies. To develop technology classifier, classification algorithms SVM - Support Vector Machine, Decision Tree, kNN – k Nearest Neighbor, Artificial Neural Network and Deep Feed-Forward Neural Network are trained and experimented to forecast expertise terms from unstructured content of social posts. The results of experiment show that Feed-Forward deep neural network outperforms other classification models and provide better accuracy and technology term prediction.
DIGITAL DOCUMENTATION’S ONTOLOGY: CONTEMPORARY DIGITAL REPRESENTATIONS AS EXPRESS AND SHARED MODELS OF REGENERATION AND RESILIENCE IN THE PLATFORM BIM/CONTAMINATED HYBRID REPRESENTATION

Abstract. The study illustrates a university research project of “Digital Documentation’s Ontology”, to be activated with other universities, of an Platform (P) – Building Information Modeling (BIM) articulated on a Contaminated Hybrid Representation (diversification of graphic models); the latter, able to foresee categories of Multi-Representations that interact with each other for to favour several representations, adapted to a different information density in the digital multi-scale production, is intended as platform (grid of data and information at different scales, semantic structure from web content, data and information storage database, archive, model and form of knowledge and ontological representation shared) of: inclusive digital ecosystem development; digital regenerative synergies of representation with adaptable and resilient content in hybrid or semi-hybrid Cloud environments; phenomenological reading of the changing complexity of environmental reality; hub solution of knowledge and simulcast description of information of Cultural Heritage (CH); multimedia itineraries to enhance participatory and attractive processes for the community; factor of cohesion and sociality, an engine of local development. The methodology of P-BIM/CHR is articulated on the following ontologies: Interpretative and Codification, Morphology, Lexicon, Syntax, Metamorphosis, Metadata in the participatory system, Regeneration, Interaction and Sharing. From the point of view the results and conclusion the study allowed to highlight: a) Digital Regenerative synergies of representation; b) Smart CH Model for an interconnection of systems and services within a complex set of relationships.
Popular synchronous, asynchronous and hybrid e-learning systems

Online education requires careful thinking about how students and teachers are equipped to change traditional education to the new digital technology requirements. Digital learning management systems, communication tools and e-learning platforms play a crucial role in the new conditions of online learning. Programs and applications can help learning providers manage, plan, deliver, and track learning. Teachers, in addition to specialized skills in the field of teaching subjects, are presented with new skills of knowledge and management of digital tools. Digital competence is one of the eight key competences, materializing in the confident and critical use of the entire range of information and communication technologies for information, communication and problem solving in all areas of life. The use of digital technologies and living speech, represents a whole didactic creation, which individualizes the presented discourse to become an art in shaping the souls of the young generation.
Tracking the Growth of the PID Graph

The connections between scholarly resources generated by persistent identifiers (PIDs) and associated metadata form a graph: the PID Graph [Fenner &amp;amp; Aryani (2019)]. We developed this PID Graph concept in the EC-funded FREYA project, and have identified important use cases and technical requirements. In May, DataCite introduced a GraphQL API to standardize and simplify how users can contribute to and consume the PID Graph [Fenner (2019b)].
Error Correction Based on Transformer LM in Uyghur Speech Recognition

For Uyghur, Kazakh and other minority languages or dialects, it is difficult to collect large-scale labeled corpus. In the case of low resources, reducing the recognition granularity which using phonemes or characters as the recognition unit can get good character recognition rate, but the information between words is not fully utilized intuitively, which can not solve the problem of high word error rate in the practical process. In order to correct the wrong words in the recognition, this paper proposes to use Levenshtein distance and Transformer language model with words as modeling units as the secondary scoring criteria to correct the end-to-end recognition results. In the Uyghur end-to-end recognition deployed with Conformer-CTC acoustic model, the WER decreases by 5.7%, In the end-to-end recognition deployed with BLSTM-CTC as acoustic model, it decreased by 9.1%.
Penerapan metode genius learning strategy sebagai upaya meningkatkan prestasi belajar IPA di sekolah dasar

Penelitian ini merupakan Penelitian Tindakan Kelas dengan tujuan untuk meningkatkan prestasi hasil belajar IPA dengan menggunakan metode Genius Learning Strategy. Subyek penelitiannya adalah siswa kelas V SD Negeri Cibeunying 03 yang berjumlah 17 siswa. Instrumen-instrumen yang digunakan dalam penelitian adalah tes pembelajaran IPA, lembar observasi guru, lembar observasi siswa, lembar catatan lapangan, wawancara dan dokumentasi. Untuk menentukan validitas instrumen digunakan rumus korelasi product moment dan dikonsultasikan dengan ahli. Data dianalisis secara deskriptif kuantitatif dan kualitatif. Adapun indikator keberhasilan penelitian ini ditandai dengan meningkatnya kualitas proses (keaktifan siswa dan suasana kelas menjadi lebih hidup) dan hasil belajar IPA (75% siswa mencapai kriteria ketuntasan minimal/KKM 7,5). Hasil penelitian menunjukkan dengan diterapkannya metode Genius Learning Strategy, kualitas proses pembelajaran menjadi meningkat, terbukti siswa menjadi lebih aktif, komunikatif, dan suasana kelas menjadi lebih menyenangkan. Selain itu, prestasi hasil belajar IPA pada siswa juga meningkat, terbukti dengan nilai rata-rata siswa pratindakan sebesar 6,91 dengan pencapaian KKM 41,12%, pascatindakan siklus I sebesar 8,03 dengan pencapaian KKM 64,70%, dan pascatindakan siklus II sebesar 8,29 dengan pencapaian KKM 82,39%. This research is Class Action Research with the aim to improve the achievement of science learning results by using genius learning strategy method. The subject of his research was grade the fifth grade students of SD Negeri Cibeunying 03 which involve 17 students. The instruments used in the research are science learning tests, teacher observation sheets, student observation sheets, field notes, interviews and documentation. To determine the validity of the instrument used product moment correlation formula and consulted with experts. The data is analyzed descriptively quantitatively and qualitatively. The indicators of success of this study are characterized by increasing quality of process (student activity and classroom atmosphere becoming more lively) and science learning outcomes (75% of students achieved passing grades/KKM 7.5). The results showed that with the implementation of Genius Learning Strategy method, the quality of the learning process became improved, students proved to be more active, communicative, and the classroom atmosphere became more pleasant. In addition, the achievement of science learning outcomes in students also increased, as evidenced by the average score of pre-act students of 6.91 with the achievement of KKM 41.12%, post-act cycles I of 8.03 with the achievement of KKM 64.70%, and post-act cycle II of 8.29 with the achievement of KKM 82.39%.
Use of Application Variations on Online Teaching and Learning during the Covid-19 Pandemic Era

Abstract: The government's use of social distancing has a considerable influence on many institution learning activities. Most instructors use social media apps like WhatsApp to coordinate learning and debate. The most prevalent roadblock encountered during the introduction of online learning is lecturers' and student teacher candidates' inadequate internet connectivity. This study aims to investigate the problems and solutions that teachers face during the Covid-19 pandemic that teachers need to teach and learn online. This survey is a descriptive survey using the online survey method. The data was collected using an online survey from 25 respondents to teacher of St. Thomas School, Thrissur. We found that 100% of St. Thomas School, Thrissur respondents completed online learning during the Covid-19 pandemic. Based on the results, 100% of teachers learn the online model. In addition, in implementing e-learning, teachers use many different applications such as WhatsApp Web, Google Classroom, Zoom Meeting, Webinar and YouTube. WhatsApp is the primary app choice for teachers. It claims that 100% of teachers are first choice.
Resource Allocation Using Particle Swarm Optimization Algorithm in Cloud Computing

Abstract: Cloud computing is now widely used in organisations and bussiness firms because of its on-demand accessibility of framework assets, web innovation, and pay-as-you-go principle. Despite of numerous advantages of cloud computing, such as availability and accessibility, it also has few significant drawbacks. The most fundamental issue is the resource management, where Cloud computing provides IT assets such as memory, network, storage, and so on based on a virtualization concept and a pay-as-you-go model. Much research has gone into the administration of these assets. The suggested framework employs the particle swarm optimization algorithm method for assigning and performing the tasks of an application. The proposed algorithm will likely reduce task completion time, cost by utilizing the maximum resources. The proposed system is evaluated using the cloudsim toolkit. Keywords: Particle swarm optimization algorithm, Resource allocation, Cloud computing.
Multi-Scale Input Strategies for Medulloblastoma Tumor Classification using Deep Transfer Learning

Abstract Medulloblastoma (MB) is a primary central nervous system tumor and the most common malignant brain cancer among children. Neuropathologists perform microscopic inspection of histopathological tissue slides under a microscope to assess the severity of the tumor. This is a timeconsuming task and often infused with observer variability. Recently, pre-trained convolutional neural networks (CNN) have shown promising results for MB subtype classification. Typically, high-resolution images are divided into smaller tiles for classification, while the size of the tiles has not been systematically evaluated. We study the impact of tile size and input strategy and classify the two major histopathological subtypes-Classic and Desmoplastic/Nodular. To this end, we use recently proposed EfficientNets and evaluate tiles with increasing size combined with various downsampling scales. Our results demonstrate using large input tiles pixels followed by intermediate downsampling and patch cropping significantly improves MB classification performance. Our top-performing method achieves the AUC-ROC value of 90.90% compared to 84.53% using the previous approach with smaller input tiles.
PEMANFAATAN MEDIA THINGLINK UNTUK MENGEMBANGKAN LITERASI SAINS SISWA DALAM PEMBELAJARAN IPA SAAT PANDEMI DI MTs N 34

This study aimed to determine the use of thinglink media for the development of scientific literacy in science learning during the pandemic. This type of research is a classroom action research with a qualitative descriptive method. The data obtained show that 29 students of grade 7.3 can understand scientific literacy with moderate and high qualifications of 40%. The understanding of scientific literacy in this qualification is in the aspect of students' abilities in a personal context and scientific attitudes in support of inquiry activities. Meanwhile, students' abilities in evaluating and designing scientific investigations and interpreting scientific evidence and data are still in low qualification (60%). The ratio of values in cycles 1 and 2 is 40%: 51%. The selection of the right measuring instrument to be embedded in the thinglink media dramatically affects the learning process and measures students' understanding of scientific literacy during the pandemic.