Reviewerly/exHarmony huggingface dataset:
초등학생을 위한 종교 교육 프로그램이 다문화수용성에 미치는 영향 연구

The purpose of this study was to analyze the effect of religious education program on the multiculture acceptance of elementary students. To accomplish this, an religious education program was developed from references to domestic and foreign books, studies, and programs. This study was designed by 3 religious education programs for Creative experience activities, Korean, Social studies. The subjects of the study were 20 elementary students in one 3rd grade class of G elementary school located in Busan City. Pre- and post-questionnaire surveys were conducted with these students.The main contents of this religious education programs are so far beyond religious education centered on religious life, religious conflict, history, content, culture and religious prejudice of various religions.The effects of the program on the multicultural acceptance of these students were analyzed. Analysis results, Significant changes were observed in all terms of multicultural acceptance: diversity, relationships, universality. In particular, it has had a great effect on reducing stereotypes and discrimination in diversity areas.Religious education in public education has been taboo so far that it has not known much about other religions, and such ignorance has led to prejudice, rejection and fear. Until now, religious education has been dismissed as an individual''s religious life, but religious education in a multicultural society is a necessary education to understand others. Through this religious education, we can foster religious tolerance and achieve multicultural coexistence.Expecting more religious education programs to be developed, I would like to suggest the following for future research on multicultural acceptance and the development and effectiveness of religious education programs based on the basis of the results of this study.First, religious education should be conducted more systematically and continuously as a topic of multicultural education.Second, it is necessary to develop various programs linked to more diverse subjects in follow-up studies. (Busan Bo-su Elementary School)
Switching Transferable Gradient Directions for Query-Efficient Black-Box Adversarial Attacks

We propose a simple and highly query-efficient black-box adversarial attack named SWITCH, which has a state-of-the-art performance in the score-based setting. SWITCH features a highly efficient and effective utilization of the gradient of a surrogate model $\hat{\mathbf{g}}$ w.r.t. the input image, i.e., the transferable gradient. In each iteration, SWITCH first tries to update the current sample along the direction of $\hat{\mathbf{g}}$, but considers switching to its opposite direction $-\hat{\mathbf{g}}$ if our algorithm detects that it does not increase the value of the attack objective function. We justify the choice of switching to the opposite direction by a local approximate linearity assumption. In SWITCH, only one or two queries are needed per iteration, but it is still effective due to the rich information provided by the transferable gradient, thereby resulting in unprecedented query efficiency. To improve the robustness of SWITCH, we further propose SWITCH$_\text{RGF}$ in which the update follows the direction of a random gradient-free (RGF) estimate when neither $\hat{\mathbf{g}}$ nor its opposite direction can increase the objective, while maintaining the advantage of SWITCH in terms of query efficiency. Experimental results conducted on CIFAR-10, CIFAR-100 and TinyImageNet show that compared with other methods, SWITCH achieves a satisfactory attack success rate using much fewer queries, and SWITCH$_\text{RGF}$ achieves the state-of-the-art attack success rate with fewer queries overall. Our approach can serve as a strong baseline for future black-box attacks because of its simplicity. The PyTorch source code is released on https://github.com/machanic/SWITCH.
Action Space Shaping in Deep Reinforcement Learning

Reinforcement learning (RL) has been successful in training agents in various learning environments, including video-games. However, such work modifies and shrinks the action space from the game's original. This is to avoid trying "pointless" actions and to ease the implementation. Currently, this is mostly done based on intuition, with little systematic research supporting the design decisions. In this work, we aim to gain insight on these action space modifications by conducting extensive experiments in video-game environments. Our results show how domain-specific removal of actions and discretization of continuous actions can be crucial for successful learning. With these insights, we hope to ease the use of RL in new environments, by clarifying what action-spaces are easy to learn.
Blended Learning: Post Pandemic Solutions

&lt;p&gt;Pandemi telah mengubah pembelajaran tatap muka menjadi Pembelajaran Jarak Jauh (PJJ) yang menimbulkan kendala seperti ketidaksiapan menggunakan aplikasi pembelajaran online, belum tersedianya materi untuk diunggah, jaringan internet yang tidak stabil, biaya kuota internet, dan kejenuhan siswa. Penelitian ini bertujuan untuk memberikan gambaran pelaksanaan PJJ dan upaya implementasi blended learning sebagai solusi proses pembelajaran di sekolah dasar dan sekolah menengah pertama. Metode penelitian yang digunakan adalah kuantitatif dan kualitatif, melalui observasi, wawancara, kuesioner dan dokumentasi. Hasil penelitian menunjukkan kombinasi dari pembelajaran online, offline dan tatap muka mampu menciptakan suasana yang lebih menyenangkan bagi siswa, guru dan orang tua.&lt;/p&gt;&lt;p&gt;&lt;em&gt;The pandemic has transformed face-to-face learning into distance learning which has caused obstacles such as unpreparedness to use online learning applications, unavailability of material to upload, unstable internet networks, internet quota fees, and student saturation. This study aims to provide an overview of the implementation of &lt;/em&gt;&lt;em&gt;distance learning&lt;/em&gt;&lt;em&gt; and efforts to implement blended learning as a solution for the learning process in elementary and junior high schools. The research method&lt;/em&gt;&lt;em&gt;s&lt;/em&gt;&lt;em&gt; used &lt;/em&gt;&lt;em&gt;are&lt;/em&gt;&lt;em&gt; &lt;/em&gt;&lt;em&gt;quantitative and &lt;/em&gt;&lt;em&gt;qualitative &lt;/em&gt;&lt;em&gt;through observation,&lt;/em&gt;&lt;em&gt; interview, questionnaire&lt;/em&gt;&lt;em&gt;,&lt;/em&gt;&lt;em&gt; and documentation. The results showed that the combination of online, offline&lt;/em&gt;&lt;em&gt;,&lt;/em&gt;&lt;em&gt; and face-to-face learning &lt;/em&gt;&lt;em&gt;could&lt;/em&gt;&lt;em&gt; create a more pleasant atmosphere for students, teachers&lt;/em&gt;&lt;em&gt;,&lt;/em&gt;&lt;em&gt; and parents.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt; &lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;.&lt;/em&gt;&lt;/p&gt;&lt;p&gt; &lt;/p&gt;
Promoting gallery walk to foster students writing skill

This research highlighted the application of gallery walk to enhance students’ achievement in writing a recount text. The goal of this research are to assess whether or not the use of gallery walk could foster the students’ writing score and to find the significant difference in students’ recount text writing achievement between those who were taught by using gallery walk and that of those who were not. This research used a quasi-experimental research design with no random sampling. The samples were taken by using purposive sampling, consisting of 37 students for the experimental and control groups. The data were collected by using a written test and administered before and after the treatment. To verify the hypotheses, the data were analyzed using paired sample t-test and independent sample-test and the calculation was done using SPSS program. The result showed that the promotion of gallery walk could foster students’ achievement in writing a recount text and there was a significant difference between posttest results of both groups.
Study on Influencing Factors of Subjective Well-being of Workers in Manufacturing Industry

Strengthening the research on the influencing factors of subjective well-being of workers in manufacturing industry is helpful to adopt comprehensive measures to improve the well-being of industrial workers, enhance the competitiveness of enterprises and promote their better development. This paper attempts to analyze the factors that affect workers’ subjective well-being from the aspects of employees themselves, economic income, and enterprise organization.
Geomojis &amp;#8211; a Global Symbology for Communicating Geosciences

&amp;lt;p&amp;gt;Communicating geosciences across linguistic and cultural borders is becoming increasingly important in our globalised world, and it is as important to have a globally coherent communication as it is to have global research infrastructure. In the context of geological hazards and the geological environment, we need a clear system that enables specialists and others to communicate effectively with each other. By using symbols and pictograms to represent geohazards, we can communicate these hazards clearly and efficiently. Certain hazard symbols are already in use across the globe, such as those for chemical or environmental hazards. In this project, we focus on the geological environment and geohazards, and much of the work is done within a UNESCO Geoscience Programme project 'Geoheritage for Resilience', using geoheritage sites as sites for communication and testing. The geological pictograms, or &amp;amp;#8216;geomojis&amp;amp;#8217;, bridge the gap between simple symbols and words, crossing language borders by representing concepts that we have identified as particularly important for understanding geohazards and risk. Our geomojis are based on the Global Framework for Geology (see Global and Planetary Change, 2018 - https://digitalcommons.mtu.edu/michigantech-p/427), also introduced during the IUGG centenary at UNESCO. This shows the context where they fit in the Earth system. We invite feedback on the geomojis that we have created, to consolidate geoscience knowledge and create a basic standardised set of symbols for all geological hazards. This standardisation of geohazard symbols could improve communication not only between specialists and non-specialists, but between geologists themselves. The global framework and geomojis will help us to think outside the box of our specialist environment. The geohazard pictograms can be used for geoscience communication in all forms, from hazard and risk publications to signage at geological sites. They can be adapted and modified for the local context and needs, while providing a central, and global, base for comparison. We plan to use the geomojis to accompany a multilingual glossary on geological hazard and risk terminology, a project that we hope will help international geoscience communication.&amp;lt;/p&amp;gt;
Implementation of Preference Selection Index Method in Decision Support System for Selecting School Inventory Users

This study aims to solve the problem of using a limited inventory of supporting media for learning at SD 096782 Tumorang Huta Dua Tumorang school, Gunung Maligas District, Simalungun Regency. The limitations of school inventories in the use of instructional media must be distributed to teachers so that they can be used in teaching. Therefore, the difficulty of distributing school inventory was overcome by implementing a decision support system using the Preference Selection Index (PSI) method. This method uses 6 criteria consisting of: years of service, behavior, performance, attendance, responsibility, and last education. The results of the application of the DSS with the PSI method obtained alternatives that are priority recommendations for school inventory users. The recommendation results obtained from the application of the DSS with the PSI method are Teacher_3 alternative with a final value of 0.8506. The second alternative is Teacher_01 with a final score of 0.8190 and the third alternative is Teacher_07 with a final score of 0.7846.
Revisiting Cloud Security Threats: Elevation of Privilege

Research study depicts that security needs to be recognized and threat vector in Cloud Computing needs to be focused on. There are numerous threats to cloud security and accordingly, individual threat study must be revised regularly to meet the changing requirements of a highly volatile security environment. These malicious attackers are considerable risk for today’s Cloud Computing. Even a single malicious Cloud user or administrator can eavesdrop or harm business, stored data or Personally Identifiable Information (PII) and computations. Cloud Computing processes mostly need higher privilege accesses in order to operate information systems and to provide services these get affected by threats due to destabilized privilege management. This paper presents a broad indication of a destabilized privilege management factor or threat known as ‘Elevation of Privilege’. A comprehensive survey on the same has been presented. The paper also focuses on various directions for future research in the area of Elevation of Privilege Threat based on the prior published works and industry/organization reports.
Ghost Signals: Verifying Termination of Busy-Waiting (Extended Version)

Programs for multiprocessor machines commonly perform busy waiting for synchronization. We propose the first separation logic for modularly verifying termination of such programs under fair scheduling. Our logic requires the proof author to associate a ghost signal with each busy-waiting loop and allows such loops to iterate while their corresponding signal $s$ is not set. The proof author further has to define a well-founded order on signals and to prove that if the looping thread holds an obligation to set a signal $s^\prime$, then $s^\prime$ is ordered above $s$. By using conventional shared state invariants to associate the state of ghost signals with the state of data structures, programs busy-waiting for arbitrary conditions over arbitrary data structures can be verified.
코로나바이러스감염증-19 상황에서 대학생의 감염불안, 충동성, 의사결정유형이 인터넷에서의 건강정보추구행위에 미치는 영향

Purpose: This study investigated the influencing factors of COVID-19 infection anxiety, impulsivity, and decisionmaking type on health information-seeking behavior on the internet. Methods: This study was conducted by 178 college students of 5 cities in Korea using a self-reporting survey with structured questionnaires of COVID-19 anxiety, impulsiveness, decision-making style, and health information-seeking behavior on the internet. SPSS 25 was used for the statistical analysis. Results: The results showed that non-planning impulsivity(s=-.25, p<.001), dependent decision-making types(s=.23, p<.001), and COVID-19 infection anxiety(s=.22, p=.001) had statistically significant effects on health information-seeking behavior on the internet with 33.6% overall explanatory power. Conclusion: Findings of this study indicate that college students’ dependent decision-making types, COVID-19 infection anxiety had a positive effect, and non-planning impulsivity had a negative effect on health information-seeking behavior on the internet. Based on the results of this study, it is necessary to identify and compare health information-seeking behavior on the internet based on infection and self-quarantine experiences.
Overview on Biometric Based Delicate Computing Methods for Client Verification

Nowadays security of data and passwords is a major challenge for the mankind. Therefore, the need to solve this issue is growing rapidly and we are always in the need to come up with some better security techniques. Till date the security of passwords using biometric is considered the best option. This paper revolves around a survey of different keystroke biometric techniques for password authentication. In this paper a detailed study of various artificial intelligence techniques is done that includes the domain of neural networks, genetic algorithms, fuzzy rulebased systems, statistical analysis, support vector machine and hybrid systems. The researches in each domain are discussed in detail. From the results it can be concluded that techniques involving neural networks and genetic algorithm give low error rate and higher accuracy, though, fuzzy rule-based systems and support vector machine have lesser complexity factors. However, this result is not absolute.
Privacy-Preserving Constrained Domain Generalization via Gradient Alignment

Deep neural networks (DNN) have demonstrated unprecedented success for medical imaging applications. However, due to the issue of limited dataset availability and the strict legal and ethical requirements for patient privacy protection, the broad applications of medical imaging classification driven by DNN with large-scale training data have been largely hindered. For example, when training the DNN from one domain (e.g., with data only from one hospital), the generalization capability to another domain (e.g., data from another hospital) could be largely lacking. In this paper, we aim to tackle this problem by developing the privacy-preserving constrained domain generalization method, aiming to improve the generalization capability under the privacy-preserving condition. In particular, We propose to improve the information aggregation process on the centralized server-side with a novel gradient alignment loss, expecting that the trained model can be better generalized to the "unseen" but related medical images. The rationale and effectiveness of our proposed method can be explained by connecting our proposed method with the Maximum Mean Discrepancy (MMD) which has been widely adopted as the distribution distance measurement. Experimental results on two challenging medical imaging classification tasks indicate that our method can achieve better cross-domain generalization capability compared to the state-of-the-art federated learning methods.
Designing for AI

In chapter 4, I posed the question why the type of artificial intelligence methods we have seen so many examples of in this book are not used more in games. I outlined a couple of potential reasons for this. One of the reasons I mentioned is that game development is a surprisingly risk-averse industry because of the hit-driven nature of the business and that the technology may not be mature enough yet. Now, after spending the past few chapters on AI methods for playing games, modeling players, and generating content, we'll revisit the question. This time we focus on the role of game design in enabling AI and, conversely, AI in enabling game design.
PREDICTING THE ACQUISITION OF RESISTANT PATHOGENS IN ICUS USING MACHINE LEARNING TECHNIQUES

To develop models to predict CR-GNB acquisition in ICUs using machine-learning techniques.To find the probability of each patient to acquire the bacteria Sampling method Different Balancing Strategies Matched Case-control Study Hyperparameter Tuning Metric AUC Brier score Evaluation Metric MCC and NPV Brier score Interpretation Error analysis (confusion matrix) Calibration Belt Comparison of the techniques' performances Yes No Computational Time Analysis Yes No Analysis of the difference between hospitals No Yes
FUNCTIONAL ROLE OF IMAGINATION IN THE PROCESSES OF CONSCIOUS SELF-REGULATION: THEORETICAL ANALYSIS

The article is devoted to the problem of the functional role of imagination in the processes of conscious self-regulation of personality as a complex integrative phenomenon. The need to consider conscious self-regulation in the context of the resource approach is determined.&#x0D; Conscious self-regulation, manifesting itself in the initiative-creative mode, in the ease and success of mastering new types of purposeful activity, in the ability to solve non-standard tasks, in changing conditions that require changes, etc., associated with the generalized ability to set goals, to model significant external and internal conditions, to program actions, to control and evaluate current and final results, and to adjust the regulatory system.&#x0D; The adequacy of these skills to the requirements of the activity, their flexibility and reliability is largely determined by the functional involvement of the imagination in self-regulatory processes, where it 1) provides goal setting (goal-setting function) and expanding activity’s meaning basis (meaning-making function); 2) participates in modeling and subsequent productive transformation of the figurative content of the problem situation (modeling function); 3) enables reflexive regulation (control, evaluation, correction) by a person of his/her own actions and deeds, which determines the constructive direction of activity (reflexive-regulatory function).
Local structure alignment guided domain adaptation with few source samples.

Domain adaptation has received lots of attention for its high efficiency in dealing with cross-domain learning tasks. Most existing domain adaptation methods adopt the strategies relying on large amounts of source label information, which limits their applications in the real world where only a few label samples are available. We exploit the local geometric connections to tackle this problem and propose a Local Structure Alignment (LSA) guided domain adaptation method in this paper. LSA leverages the Nystrom method to describe the distribution difference from the geometric perspective and then perform the distribution alignment between domains. Specifically, LSA constructs a domain-invariant Hessian matrix to locally connect the data of the two domains through minimizing the Nystrom approximation error. And then it integrates the domain-invariant Hessian matrix with the semi-supervised learning and finally builds an adaptive semi-supervised model. Extensive experimental results validate that the proposed LSA outperforms the traditional domain adaptation methods especially when only sparse source label information is available.
온라인 교육서비스 품질이 교육서비스 가치와 전공만족에 미치는 영향: 항공서비스학과 학생들을 대상으로

This paper will examine the service quality of online education as a substitute for face-to-face classes, rather than an auxiliary role in classroom settings after COVID-19. For this purpose, the research subjects were selected as students attending airline service departments. Research on whether online education has the service quality that can replace traditional face-to-face lectures could lead to a variety of implications, both theoretically and practically.The data collection for research was conducted through an online survey, then the analysis found that materiality, reliability, responsiveness, assurance, empathy of the quality of online education services all have a positive impact on the value of education services. Also, the value of education service has a positive effect on satisfaction of major.Based on these results, the fact that the performance of the system for online education, communication with students, and prompt response to student inquiries should all be recognized as important. In addition, reliability should be the most important quality of online education services. Finally, in order to enhance students'' satisfaction with their majors, they should increase the value of the educational services they feel.
Reconstructing Small 3D Objects in front of a Textured Background.

We present a technique for a complete 3D reconstruction of small objects moving in front of a textured background. It is a particular variation of multibody structure from motion, which specializes to two objects only. The scene is captured in several static configurations between which the relative pose of the two objects may change. We reconstruct every static configuration individually and segment the points locally by finding multiple poses of cameras that capture the scene's other configurations. Then, the local segmentation results are combined, and the reconstructions are merged into the resulting model of the scene. In experiments with real artifacts, we show that our approach has practical advantages when reconstructing 3D objects from all sides. In this setting, our method outperforms the state-of-the-art. We integrate our method into the state of the art 3D reconstruction pipeline COLMAP.