Reviewerly/exHarmony huggingface dataset:
A Study on Art Learning Analysis for Personalized Learning in Digital Transformation

2022 국가 수준 교육과정 개정과 함께 교육 혁신과 디지털 전환이 활발하게 논의되고 있다. 본 연구는 이러한 새로운 학교 교육 체제에 대한 사회적 요구에 미술 교과는 어떻게 대응하고 그 변화에 참여할 것인가의 질문에서 시작되었다. 이에 본연구에서는 다음의 연구 문제를 가지고 선행 연구 분석을 실시하였다. 2022 개정 교육과정에서 교육 혁신을 다시 강조하게 되는 시대 의식은 무엇인가? 맞춤형 교육은 미술교과의 맥락에서 어떤 의미를 가지며, 이를 위한 방법론으로서 미술 학습분 석은 어떻게 개념화될 수 있는가? 마지막으로, 미술 학습분석 체제는 어떤 방향에서 구축되어야 할 것인가? 연구 결과로 미술과 안에서 학습자 특성을 규정하는 발달론적, 인지적, 사회문화적 관점을 논의하고 이에 기초하여 ‘조형’, ‘탐구’, ‘독창성’, ‘태도’로 미술 학습분석의 핵심 영역을 제안하였다. 미술 학습분석의 영역은 미술활동에 대한 교수자의 피드백을 토픽 모델링을 활용하여 분석하고 각 주제 안에서 의미구조를 해석하는 방식으로 도출하였다. 본 연구는 거시적인 관점에서 최근 교육의 흐름을 조망하고 시대적 요구에 대응하는 미술교육의 방안을 미술 학습분석이라는 개념을 통해 새롭게 모색하였다는 점에 의의가 있다.Along with 2022 National Curriculum Revision, educational innovation and digital transformation are extensively discussed. This study started with the question of how art subjects would respond to the social demands for an alternative school system and participate in this change. In this study, the literature analysis was conducted with the following research questions. Where does the re-emphasis on educational innovation, on which the 2022 Revised Curriculum is anchored, derive from? What meaning does personalized education have in the context of art subjects, and how can art learning analysis be conceptualized? Finally, what is the direction of constructing an art learning analysis system? As a result, the developmental, cognitive, and sociocultural perspectives that define the characteristics of learners within the art department were discussed. In addition, the core areas of art learning analysis are proposed as ‘aesthetics’, ‘inquiry’, ‘originality’, ‘aptitude’. These core areas of art learning analysis was derived by analyzing the instructor's feedback on art activities using topic modeling technique and interpreting the semantic structure within each topic. The significance of this study can be found in that it shed light on the educational trend from a a macroscopic point of view, and explored new ways of art education through the concept of art learning analysis.
A Multi-label Approach for Diagnosis Problems in Energy Systems using LAMDA algorithm

In this paper, we propose a supervised multilabel algorithm called Learning Algorithm for Multivariate Data Analysis for Multilabel Classification (LAMDA-ML). This algorithm is based on the algorithms of the LAMDA family, in particular, on the LAMDA-HAD (Higher Adequacy Grade) algorithm. Unlike previous algorithms in a multi-label context, LAMDA-ML is based on the Global Adequacy Degree (GAD) of an individual in multiple classes. In our proposal, we define a membership threshold (Gt), such that for all GAD values above this threshold, it implies that an individual will be assigned to the respective classes. For the evaluation of the performance of this proposal, a solar power generation dataset is used, with very encouraging results according to several metrics in the context of multiple labels.
Foreign Geographical Names in Modern Textbooks: Focusing on World Geography and World History Textbooks

This study analyzed types and notations of foreign geographical names in 18 types of world geography textbooks of modern times. It aims to examine various topics as cognition of the world, movement of knowledge, and toponymic contestations during the period from 1895 to 1910. There were toponymic contestations of transliteration between Chinese and Japanese pronunciation, and transitions from Chinese transliteration to Korean translation similar to original pronunciation. Meanwhile, a variety of notations of foreign geographical names coexisted such as Chinese transliteration, Korean translation, their combinations, and a whole new Korean notation in world geography and world history textbooks. Although there are limitations of this research, it is hoped that the data of this study will be usefully used in future researches.
Exploring ways to organize the content system of the 2022 curriculum based on the 2015 curriculum content system analysis

Objectives The purposes of this study were to analyze several critical discussions on the composition of the content system of the 2015 curriculum, and based on this, explore the appropriate content system composition in the 2022 curriculum revision.&#x0D; Methods I analyzed several domestic literatures that developed critical discussions on the composition of the content system of the curriculum in 2015, and reviewed major domestic literature that presented various views on the method of content system composition in the 2022 revision of the curriculum.&#x0D; Results It was confirmed that the newly introduced terms such as core concepts, generalized knowledge, and functions were not implemented as intended. The core concepts did not act as criteria for carefully selecting subject contents, did not fit the role of establishing linkage and integration between subjects, and did not link with generalized knowledge. It was found that clarification, hierarchy, and systematization of function were necessary because the meaning of function was unclear, it was not well connected with the achievement standards, and it did not show the way of thinking or inquiry peculiar to the subject.&#x0D; Conclusions As a way to improve the content system of the curriculum in 2022, deduction of guidelines for curriculum development through joint research between general research and each research team, integration of core concepts and generalized knowledge or consideration of deletion or replacement of generalized knowledge, interpretation of the meaning of functions. It was suggested as a way to improve the composition of the content system, such as giving flexibility and greatly supplementing the content system, moving function from the content system to the items of teaching and learning methods, and setting the direction for broadening or detailing achievement standards.
New Chaotic Attractor Captured with Fractal-Fractional Differential and Integral Operators

Differential operators based on convolution have been recognized as powerful mathematical operators able to depict and capture chaotic behaviors, especially those that are not able to be depicted using classical differential and integral operators. While these differential operators have being applied with great success in many fields of science, especially in the case of dynamical systems, we have to confess that they were not able depict some chaotic behaviors, especially those with additionally similar patterns. To solve this issue, a new class of differential and integral operators were proposed and applied in a few problems. In this paper, we aim to depict chaotic behavior using the newly defined differential and integral operators with fractional order and fractal dimension. Additionally, we introduce a new chaotic operators with strange attractors.
Mathematical Modeling and Diagnostics Using Neural Networks and a Genetic Algorithm for Epilepsy Patients

Medical and biological electroencephalogram (EEG) signals are widely used for diagnosis, further medical support and treatment of such disease as epilepsy. A method for detecting of epileptiform activity presence in patients has been developed based on analysis of EEG signals taken during the 1st, 2nd and 3rd sleep phases. To implement this task, an approach was designed with use of genetic algorithm and artificial neural network (ANN), which can be classified according to the following criteria: the network is analog; self-organizing; a direct distribution network, static. The input neurons count in the neural network is equal to the channels count in the EEG recording, and in this study it is equal to 21, 15 neurons in the hidden layer, 1 output neuron. The input layer accepts data in the form of numbers representing the calculated characteristics for each channel: the largest Lyapunov exponent calculated by the Rosenstein, Wolf, Sano-Sawada methods, for men and women with epilepsy and from the control group. Test sample: 33 patients, of which 6 were healthy and 27 patients with epilepsy with different diagnoses. Some of the combinations made it possible to obtain 100% accuracy in determining the presence or absence of disease in patients.
Listening to the flute

Flute clocks in the Nydahl Collection (Soundspheres rhlb11, issued 2014) showcases the mechanized flute clock, exemplifying interest in experimental and automated music-making in the late 18th and early 19th centuries, and drawing on the Nydahl Collection, which can still be seen today in a permanent exhibition in Stockholm. Rudolf Nydahl (1882–1973) studied music at the Paris Conservatory and later took over his family’s wine shop in Stockholm, the proceeds of which allowed him to found his collection in 1920. The album comprises 17 short tracks, each one conveying the charm (and machine noise) of a mechanical instrument (the flute clocks in question). The programming draws on music contemporary with the flute clocks themselves, featuring pieces by composers such as Graun, Haydn and Gluck, which have been arranged to fit the limited compass of the instruments. The excellent liner notes include colour photographs of the flute clocks and details of their makers and contexts, and explain that on this recording, two different instruments from the Nydahl Collection are used. Tracks 1–4 are heard on an instrument made by an unknown builder, although the case is known to have been built by Lars Jensen Winberg in Copenhagen, probably between 1764 and 1780. Meanwhile tracks 5–17 are played on a clock by Pehr Strand (1756–1826), most likely in 1795. For extended listening, the mechanized sound-world of the album may wear a little thin—I occasionally found myself wanting more human musical contact: the breath of a flautist, the connection of ensemble playing, the sensitivity of an articulation choice. Despite that, the various tracks demonstrate the timbres and sound-worlds of the two instruments effectively, and offer an appealing new way to listen to this music through such arrangements. I would therefore unhesitatingly recommend the album to anyone with a historical or scientific interest in flute clocks.
Blockchain-Empowered Identity Management with a Dual Identity Model for UAVs in 5G Networks

In this work, we study secure and trusted authentication of unmanned aerial vehicles (UAVs) in 5G networks. Existing centralized UAV identity authentication mechanisms may only be able to verify the identity of the UAV itself or manage pilots, which are far from complete protection of legal access. Some recent works on UAV identity management are based on blockchain technology, in which UAV identities are generated through the blockchain software wallets, so they may be vulnerable to UAV identity forgery. To tackle the challenges described above, we propose an authentication mechanism based on a dual-identity (dual-ID) model for UAVs in 5G networks via a cross-layer design of SIM cards, blockchain, and smart contracts. The proposed self-sovereign UAV identity management procedure will then jointly process the authentications of both the UAV device and its pilot through the blockchain hardware wallets embedded in 5G SIM cards. In this way, a global registry of a unique identifier of each UAV device and each pilot can be ensured, and the identity forgery problem can also be avoided. Due to the limited power and processing capacity of UAV devices and the need of quick response for authentication, we employ 5G and multi-access edge computing (MEC) servers for communication and processing. To validate the proposed solution, a developed proof-of-concept system is tested through the 5G MEC testbed at National Taiwan University to demonstrate the flexibility and usability of UAV authentication.
TCT-223 Short- and Long-Term Vascular Responses of Stent With Biodegradable Graft for Artery Dissection in Rabbit Iliac Model

Student exchanges have been demonstrated to increase students' Cultural Intelligence (CQ). However, global problems in recent years, such as the Coronavirus pandemic, have highlighted the need for digital alternatives to traditional in-person visits. One such alternative could be intercultural seminars using telepresence robots, which allow students to experience particularly realistic intercultural interactions in their real environments. In this research, we evaluated the effects of two semi-virtual intercultural seminars on diversity and intercultural competence that integrated telepresence robots to enable interactions between students located in Germany and Kenya. We conducted quantitative and qualitative analyses using data from N ​= ​135 college students. One half of these students actively participated in one of the seminars. The other half did not participate in the seminars or participated only passively (without using the robots), and formed the control group. In line with our expectations, active participants in the seminars showed significant increases in metacognitive CQ, cognitive CQ, and behavioral CQ, likely due to the particular combination of seminar contents and methods. In contrast, no changes in CQ were found in the control group. Our evaluation of the telepresence robots reveals a mixed picture: Although the students showed high acceptance of using telepresence robots in intercultural seminars, this acceptance did not change during the seminars. Moreover, several technical problems hindered the smooth operation of the robots. Nevertheless, the concept of the seminars under examination proved to be promising for enhancing students’ CQ in an efficient manner.
An Analysis of Differences and Influencing Factors in Consumer Product Risk Information Search and Utilization, Risk Information Policy Satisfaction, Risk Information Difference

Background/Objectives: The purpose of the study was investigated whether the four characteristics of consumers differ according to the various demographic characteristics of consumers. In addition, the variables that affect the four characteristics of consumer product risk information were investigated.&#x0D; Methods: In this study, T-test and One-way Analysis of Variance were performed to investigate whether the four product risk information characteristics used in this study differ according to the demographic characteristics of consumers. In addition, Regression Analysis was performed to investigate the independent variables affecting the four product risk information characteristics.&#x0D; Results: The main results of this study are summarized as follows. as a result of the regression analysis, it was found that the level of product risk information search and utilization of consumers was found to be active in women, non-metropolitan residents, consumers who are aware of the KC mark, and consumers with a high level of subjective knowledge about risk information. In addition, it was found that the higher the level of subjective knowledge about risk information, the higher the customer satisfaction with the product risk information policy. On the other hand, the subjective knowledge level of product risk information was found to be higher among males, consumers residing in the Seoul metropolitan area, and consumers with a high level of risk information search and use. Finally, the level of objective knowledge related to product risk information was found to be high in the case of college graduate consumers, non-professional consumers, consumers who know the KC certification mark, and consumers with an older age.&#x0D; Conclusion/Implications: It is necessary to strengthen product safety information policies such as consumer education and public relations strategies so that consumers can find and utilize product risk information more.
Well-Being for Infants and Toddlers in Korea: Focusing on the Infant and Toddler Index

Background/Objectives: The purpose of study is to develop well-being index for infants and toddlers, and analyze the main indicators to find their implications and suggest to develop future development plan .&#x0D; Methods: The methods of this study include literature review, secondary data analysis and indicator reporting, 2-time Delfi-survey and running indicator review committee, and holding seminars and a policy forum.&#x0D; Results: The main areas of infants and toddlers index are nutrition and health, development and learning, safety and protection, material situation and housing environment, play, relationships and care, and finally subjective well-being. In this study, as the main indicators according to the social framework of infants and toddlers: the energy intake rate, the low birth weight rate, overall cognition, the level of language development, the death toll in child safety accidents, the number of cases by type of child abuse, and household material deficit, number of rooms used, number of games with friends, TV watching by smartphone, primary caregiver status, and time spent with parents were analyzed.&#x0D; Conclusion/Implications: Increasing the validity and practicality of existing indicators, we continuously produce additional indices related to infants and toddlers, and focus on data production that infants and toddlers can respond to rather than related questions such as institutions or teachers. To this end, it is necessary to develop measurement methods or technical methods for infants and toddlers.
Preface to the International Conference on Electronics, Engineering Physics and Earth Science (EEPES’2022)

The International Conference on Electronics, Engineering Physics and Earth Science (EEPES’2022) was held in hybrid mode in Sts. Constantine and Helena Resort, Varna, Bulgaria from 22 to 24 June, 2022. The EEPES’2022 was organized by the Association on Communication, Information, Electronic and Energy System. Academic partners of the conference are renowned scientists from the International Hellenic University (Department of Physics) and University of Ruse (Department of Telecommunications and Department of Electrical Power Engineering), backed by a strong international scientific committee and a specialized pool of reviewers. The goal of the EEPES’2022 conference is to provide an international forum for researchers, academics, people in industry, and students to address recent research results and to present and discuss their ideas, theories, technologies, systems, tools, applications, work in progress and experiences on all theoretical and practical issues arising in all areas of physics and allied technology, such as Engineering Physics, Computer Science, Electronics, Earth Science, Mathematics and Green Technologies, etc. The technical program of the conference consists of one plenary session, one special session, and six tracks for research papers. The authors of the accepted papers, who are unable to attend the conference in person, were given an option to present their papers online and attend an interactive virtual conference. Online presentations were held in a virtual room environment via Zoom Meeting platform for the opening ceremony, all conference sessions, and meetings. All online authors prepared a video presentation of up to 12 minutes that was played on stream with authors participating in a live discussion during the session. Presentations were made in real-time video conferencing. A separate virtual room was defined for each session. List of General Conference Chairs, Technical Programmme Chair, Steering Committee Chair, Review Committee Chair, Guest Editor, Steering Committee, Organizing Committee, International Scientific Committee, Reviewers are availabe in this pdf.
NukeLM: Pre-Trained and Fine-Tuned Language Models for the Nuclear and Energy Domains

Natural language processing (NLP) tasks (text classification, named entity recognition, etc.) have seen revolutionary improvements over the last few years. This is due to language models such as BERT that achieve deep knowledge transfer by using a large pre-trained model, then fine-tuning the model on specific tasks. The BERT architecture has shown even better performance on domain-specific tasks when the model is pre-trained using domain-relevant texts. Inspired by these recent advancements, we have developed NukeLM, a nuclear-domain language model pre-trained on 1.5 million abstracts from the U.S. Department of Energy Office of Scientific and Technical Information (OSTI) database. This NukeLM model is then fine-tuned for the classification of research articles into either binary classes (related to the nuclear fuel cycle [NFC] or not) or multiple categories related to the subject of the article. We show that continued pre-training of a BERT-style architecture prior to fine-tuning yields greater performance on both article classification tasks. This information is critical for properly triaging manuscripts, a necessary task for better understanding citation networks that publish in the nuclear space, and for uncovering new areas of research in the nuclear (or nuclear-relevant) domains.
Seeing red: Distraction influences visual attention for anger but not for other negative emotions.

Emotion regulation is a vital skill that improves psychological well-being and overall functioning. Distraction (the purposeful internal disengagement from an emotional stimulus) and cognitive reappraisal (the process of changing one's thoughts about an emotional event/stimulus) are two well-established regulation strategies that can effectively decrease negative affect. Less understood, however, are the attention allocation strategies that occur when engaging in these emotion regulation strategies-specifically, do people visually scan emotional information differently when distracting vs. reappraising? In the current study, community participants were randomly assigned to either distract, reappraise, or view naturally while watching four emotional film clips that each elicited a different negative emotional state: anger, fear, sadness, and disgust. Eye tracking was used to record total time spent gazing ("dwell time") at faces within the emotion-eliciting film clips. An effect of condition was found for anger-eliciting material only: participants in the distraction condition exhibited shorter dwell times compared with reappraisal and natural viewing. Importantly, this effect was moderated by state anxiety, such that it was found at low but not high levels of state anxiety. These results show that emotion regulation strategies differentially affect attention to emotion-eliciting stimuli and points to the role of current affective states in impacting how distraction is used. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
The First French COVID19 Lockdown Twitter Dataset

In this paper, we present a mainly French coronavirus Twitter dataset that we have been continuously collecting since lockdown restrictions have been enacted in France (in March 17, 2020). We offer our datasets and sentiment analysis annotations to the research community at https://github.com/calciu/COVID19-LockdownFr. They have been obtained using high performance computing (HPC) capabilities of our university's datacenter. We think that our contribution can facilitate analysis of online conversation dynamics reflecting people sentiments when facing severe home confinement restrictions determined by the outbreak of this world wide epidemic. We hope that our contribution will help decode shared experience and mood but also test the sensitivity of sentiment measurement instruments and incite the development of new instruments, methods and approaches.