Reviewerly/exHarmony huggingface dataset:
Practical Application of Mixed Teaching Mode in the Course of Graphic and Image Processing

"Graphics and Image Processing" is a very practical course. Teachers need to break the traditional teaching mode, use modern teaching means and methods, combine teaching content with practical projects, and improve students' interest and enthusiasm in learning. This paper discusses the mixed teaching and the course of "Graphic and Image Processing", describes the teaching design of "Graphic and Image Processing" in detail, and deeply analyzes the practical application of mixed teaching mode in the course of "Graphic and Image Processing", aiming at providing a new perspective and thinking mode for educators and promoting the teaching reform and innovation of "Graphic and Image Processing".
Guidelines for Diagnosing and Refining Activities in Korean Language Textbooks: Focusing on Implementing Learner-Participatory Instruction

The aim of this paper is to propose measures to refine activities in Korean language textbook learning, making them suitable for learner-participatory instruction. Firstly, the foundations and orientations of learner-participatory method were examined, through which the problem awareness present in major learner-participatory learning models was identified. Based on this, the essential core principles of learning innovation proposed by these major learnerparticipatory learning models in response to their respective problem awareness were extracted. Lastly, by incorporating these identified problem awareness and innovative ideas through the approach of 'drawing upon,' guidelines were formulated to refine textbook activities from the perspective of implementing learner-participatory instruction. The practical implementation of refining activities in Korean language textbooks using these guidelines is illustrated.
Citizens' Awareness of Multiculturalism and Educational Policy Direction

The purpose of this paper is to understand through the important intersection of citizen awareness and education policy in the context of multiculturalism, this study examines how multiculturalism in modern society causes citizens to recognize cultural diversity and the role of education policy in forming this awareness. Based on various theoretical frameworks, empirical data, and case studies on education policy, we focused on uncovering the complex dynamics surrounding the relationship between citizen perceptions and education policy. To this end, we investigated the beliefs and perceptions of prospective teachers and analyzed their impact on multicultural awareness, explored the historical development of multiculturalism and its impact on modern education policy, and focused on cultivating awareness of cultural heritage through education. It sought to highlight the complex relationship between civic awareness and education policy in multicultural societies and provide insight into effective strategies to promote a more culturally aware society. I hope that more active research related to diverse educational policies and multiculturalism will be conducted in the future.
Development of Liberal Arts Course for Adaptation to College and Career Development of Freshmen in College of Culture and Arts

The purpose of this study is to develop a liberal arts course for freshmen in College of Culture and Arts which facilitates their adaptation to college and promotes career awareness. The study was based on literature reviews and analysis of the existing career course for freshmen at other universities in Korea. In addition, learning objects was determined by subject analysis of current career-related programs and IPA Matrix analysis of survey response data from the first-year students. After we developed a 15-week lesson plan through the process of specification of performance goals, content structure, and evaluation tool design, we implemented it for new students in the spring semester of 2023. The result shows the effectiveness of the career course for freshmen evidenced by students’ positive adaptation to college, major satisfaction, self leadership, learning outcomes. Hence, we discussed the implications of improvement strategies for the new student career course from the teaching and learning perspective.
The Effect of Academic Stress on Self-efficacy, Dropout Intention of College Students Majoring in Airline Services in the Post Corona Era

In this study, we attempted to conduct an empirical study on the effect of academic stress and self-efficacy on the dropout intention of college students majoring in airline services. The survey was conducted through a total of 200 questionnaires from Aug 28th to Sep 11th in 2023. Data from an survey of 188 valid samples were collected with SPSS 18.0. program and AMOS 18.0 program presented the evidence for a reasonable level of validity and reliability of this model. The results are as follows. First, among academic stress, emotional exhaustion and cynicism did not have a negative effect on self-efficacy. On the other hand, decreased efficacy was found to have a negative effect on self-efficacy. Second, self-efficacy was found to have a negative effect on school intention, student intention, and parent intention on dropout intention. Third, self-efficacy was found to have a mediating effect between decreased efficacy and dropout intention. The significance of this study is to find ways to maintain college life by increasing self- efficacy in order to prevent college students majoring in airline services in the post-corona era from having the intention of dropping out while experiencing academic stress. Through this, we are seeking ways to reduce the intention to drop out by increasing the self-efficacy of college students at local universities that are facing a crisis due to a decrease in the school-age population.
A Study on the Design of Metadata for the Archives of Local Culture and Arts Resources

The purpose of this paper is to develop metadata area elements for the archive of local culture and arts resources. To this end, first, it was decided to divide the construction area of local culture and arts resources into management and unmanagement areas and to build a DB focusing on new data with high preservation value. Second, 400 villages with a high risk of extinction were selected by selecting population-reduced areas at the city, county, and district level nationwide, and the DB construction team entered data directly or established a participatory DB in connection with local cultural centers. Third, for this purpose, the technical elements were divided into basic, content, management, and additional areas to enter actual data and present the required and optional fields separately. Fourth, after establishing the system necessary for conducting actual online services, it was largely divided into basic areas, content areas, and functional areas, detailed areas were designated again, and a new metafield of local culture and arts resources was designed. It is hoped that the design types and methods for building new metadata presented in this study will contribute to the implementation of an integrated archive system of local culture and arts resources.
Rancang Bangun Aplikasi Pembelajaran Ilmu Tajwid Berbasis Android

Abstrak Ilmu taljwid merupalkaln dalsalr untuk membalcal All-Qur’aln yalng balik daln benalr, sertal ilmu taljwid aldallalh ilmu yalng mempelaljalri calral pengucalpaln huruf-huruf yalng terdalpalt dallalm All-Qur’aln. Seiring perkembalngaln teknologi, digunalkalnlalh sualtu alplikalsi sebalgali medial pembelaljalraln ilmu taljwid berbalsis alndroid yalng di halralpkaln malmpu memberikaln pembelaljalraln dimalnal saljal daln kalpaln saljal kepaldal umalt muslim yalng tidalk sempalt mendalpaltkaln pelaljalraln ilmu taljwid. Metode Peralncalngaln yalng digunalkaln aldallalh metode walterfalll. Metode ini sudalh digunalkaln secalral luals untuk pengembalngaln alplikalsi. Metode ini salngalt terstruktur daln bersifalt linier. Penelitialn ini bertujualn untuk menghalsilkaln alplikalsi ilmu taljwid berbalsis alndroid sebalgali medial pembelaljalraln yalng mudalh untuk digunalkaln. Malteri yalng ditalmpilkaln dalpalt membalntu penggunal dallalm mengenall ilmu taljwid daln malteri malkhralj sebalgali contoh pengucalpaln setialp huruf. Berdalsalrkaln halsil pengujialn terhaldalp penggunal paldal alplikalsi secalral keseluruhaln sudalh mendalpaltkaln respon yalng balik dengaln persentalsi mencalpali 88%. Sehingal disimpulkaln alplikalsi ini bisal digunalkaln sebalgali medial pembelaljalraln dallalm malteri ilmu taljwid. Abstract The science of recitaltion is the balsis for realding the Qur'aln properly alnd correctly, alnd the science of taljwid is the study of how to pronounce the letters contalined in the Qur'aln. Allong with the development of technology, aln alpplicaltion is used als aln Alndroid-balsed lealrning medial for recitaltion which is expected to be alble to provide lealrning alnywhere alnd alnytime to Muslims who do not halve time to get recitaltion lessons. The design method used is the walterfalll method. This method hals been widely used for alpplicaltion development. This method is highly structured alnd linealr. This study alims to produce alpplicaltions of Alndroid-balsed recitaltion als al lealrning medium thalt is ealsy to use. The malteriall displalyed caln help users get to know the science of recitaltion alnd malkhralj malteriall als aln exalmple of the pronuncialtion of ealch letter. Balsed on the results of user testing, the alpplicaltion als al whole hals received al good response with al percentalge realching 88%. So thalt it caln be concluded thalt this alpplicaltion caln be used als al lealrning medium in the subject of recitaltion.
Robust Credit Card Fraud Detection: A Model Comparison Study

In this credit card fraud prediction project, we aimed to develop models capable of accurately identifying potentially fraudulent transactions. The dataset encompassed various attributes including transaction amount, gender, city population, age, transaction month and year, as well as geographical coordinates, which were used to train and evaluate the models. Two distinct machine learning algorithms, namely Logistic Regression and Decision Tree, were employed for this task. The models were fine-tuned using techniques such as feature selection and hyperparameter tuning to enhance their predictive accuracy. The Logistic Regression model demonstrated an accuracy of X% on the test set, showcasing its proficiency in distinguishing between fraudulent and nonfraudulent transactions. Additionally, the Decision Tree model exhibited a similar accuracy of Y%. Through an in-depth analysis of feature importance, it was revealed that attributes such as transaction amount, age, and latitudinal distance played pivotal roles in making accurate predictions. Furthermore, the project emphasizes the significance of employing soft computing techniques, which involve computational methods designed to emulate human cognitive processes, for credit card fraud detection. By leveraging machine learning algorithms and feature engineering, we were able to construct robust models capable of safeguarding financial transactions from potentially fraudulent activities. This project highlights the efficacy of modern data-driven approaches in enhancing security measures within the financial industry. Keywords— Intrusion detection, Machine learning, Optimization algorithms.
ONLINE VOTING SYSTEM

The project is mainly aimed at providing a secured and user friendly Online Voting System. The problem of voting is still critical in terms of safety and security. This system deals with the design and development of a web based voting system using fingerprint and adhar card in order to provide a high performance with high security to the voting system. The proposed Online Voting System allows the voters to scan their fingerprint, which is then matched with an already saved image within a database that is retrieved from adhar card database of the government. The voting system is managed in a simpler way as all the users must login by adhar card number and click on his/her favorable candidates to cast the vote By using biometric fingerprint it provides enough security which reduces the dummy votes.
Detailed Review about Street Fighter Game using Python

This paper examines the varied cultural meanings of computer game play in competitive and professional computer gaming and live-streaming. A fighting game is a genre of video game that involves combat between two or more characters. Fighting game combat often features mechanics such as blocking, grappling, counter- attacking, and chaining attacks together into "combos". Characters generally engage in battle using hand-to-hand combat—often some form of martial arts. The fighting game genre is related to, but distinct from, the beat 'em up genre, which pits large numbers of computer-controlled enemies against one or more player characters. The controls for Final Fight consist of an eight-way joystick and two buttons for attacking and jumping respectively. Pressing the attack button repeatedly when attacking an enemy Pressing the attack and jump buttons simultaneously allows the player to perform a special attack that strikes all surrounding enemies, but will drain a small portion of the player's health. Enemies can be grabbed simply by walking into one of them. When an enemy is grabbed, the player can perform a grab attack by pressing the attack button or perform a throw by tilting the joystick left or right. A thrown enemy can be tossed at another for additional damage. Items such as weapons, health recovery items, and items awarding extra points can be picked up by standing over one and pressing the attack button. Weapons have limited uses and will disappear if the player is disarmed by an enemy too much or when the player moves to a new area.
Detecting Phishing Website using Machine Learning

Phishing attack is a simplest way to obtain sensitive information from innocent users. Aim of the phishers is to acquire critical information like username, password and bank account details. Cyber security persons are now looking for trustworthy and steady detection techniques for phishing websites detection. This paper deals with machine learning technology for detection of phishing URLs by extracting and analyzing various features of legitimate and phishing URLs. Decision Tree, random forest and Support vector machine algorithms are used to detect phishing websites. Aim of the paper is to detect phishing URLs as well as narrow down to best machine learning algorithm by comparing accuracy rate, false positive and false negative rate of each algorithm. Keywords Phishing attack, Machine learning
Legislative Evaluation of the Cultural Diversity Act: Realization of the Constitutional Principle of Cultural Nation and Protection of Cultural Diversity

How does cultural diversity contribute to our lives? What is the difference between a society where cultural diversity is protected and promoted and a society that is not? The subject of this paper is how the Act on the Protection and Promotion of Cultural Diversity plays a role in the protection and promotion of cultural diversity after legislation and how it can be evaluated.&#x0D; The enactment and enforcement of the Cultural Diversity Protection Act should be an important basis for practical cultural diversity protection and promotion in Korea. The Cultural Diversity Act is evaluated as an important law that can operate as a stabilizer in our society. The Cultural Diversity Act should be a legal and institutional device that can reduce cultural conflicts between members of society and groups, coordinate cultural values, and contribute to creative cultural development based on individual creativity and autonomy. Various national policies that can be implemented under the Cultural Diversity Act should help protect and promote practical aspects of cultural diversity.&#x0D; The direction of the cultural diversity project is also important. Both bottom-up and top-down approaches are valuable and need an appropriate balance. Various attempts should be made to spread cultural diversity from below, such as a model to spread cultural diversity by establishing and revitalizing cultural and artistic networks among migrant groups, local governments, grassroots organizations, and culture and arts organizations.
A Study of Junior High School Students' Motivations and Learning Effects of English Tutoring in Zhaoqing Zhixing Tutorial School

Nowadays, English has become a universal language and an efficient tool for international communication. In China, English is one of the three most important subjects of the nine-year compulsory education; also, it occupies a significant position in extra-tutoring of tutorial schools. In the meanwhile, parents and students pay more and more attention to English instruction after class. This article tries to explore English tutoring in Zhaoqing Zhixing Tutorial School in terms of junior high school students’ motivations, the most effective ways and learning effects by the means of questionnaire survey and interview. According to the research result, most of students go to English tutorial school for improving their academic grade, and the majority of students regard synchronous tutorship and learning methods’ analysis as the most effective ways. In addition to this, more than 90% of the students thought attending English tutorial school is to some extent helpful.
Research on the Strategies of Stimulating Students' Motivation in Higher Vocational English Teaching

English, as a compulsory basic course for vocational college students, has also received increasing attention. In English teaching practice, it has been found that learning motivation is the internal driving force that directly drives English learning and plays a crucial role in the effectiveness of English learning. Therefore, educators find it crucial to cultivate, stimulate, and maintain the English learning motivation of vocational college students, and help them transition from "I want to learn" to "I want to learn." Learning motivation can not only guide students in their direction but also promote their hard work in learning. It is an essential driving force. The lack of motivation for vocational college students to learn English is a very important fundamental reason, and it is quite difficult to improve the level of learning motivation for this group. This is because overall, vocational college students have a low starting point, lack hard work, good learning habits, and a certain degree of self-learning ability. They also lack confidence in learning English well. To address these challenges, educators need to continuously improve the difficulty of the goal, stimulate students' exploration interest and learning motivation. In addition, after students achieve a goal, teachers should give timely praise, encouragement, and guidance for unfinished goals to enhance students' confidence.
International Comparative Study of Digital Textbook Application Policies

To determine the right direction for the future application of digital textbooks, it is essential to gain insights by analyzing the actual situations in countries that have already implemented digital textbooks. Therefore, this paper, building upon a review of the development of digital textbook policies in China, compares the application policies of digital textbooks in the United States, South Korea and Taiwan. The impact of digital textbook policies in these countries is analyzed from three aspects: the promoting body and strategy, the scope of application, the distribution system, and the methods of application. Based on these influences, a proposal for improving China's digital textbook policy is put forward. The improvement plan for digital textbooks presented in this paper is intended to serve as foundational material for shaping future policies and strategies for the development of digital textbooks.
The Impact of Artificial Intelligence on the News Industry and Strategies for Addressing IT

The application of artificial intelligence technology to news production is a crucial direction for the high-quality development of the news industry. AI technology has the potential to effectively empower the news industry in various aspects, including setting news topics, producing news content, and shaping news dissemination. However, there are currently some potential risks associated with AI's empowerment of the news industry, such as undermining the cognitive abilities of news audiences, damaging the credibility of the news industry, and inducing social and cultural biases. Therefore, news professionals and relevant regulatory authorities should adopt the following strategies:Firstly, establish a value optimization mechanism to promote the integration of technological ethics into the news industry;Secondly, construct a content-oriented mechanism to enrich the effective supply of news discourse content;Lastly, build a content supervision mechanism to promote the ethical development of artificial intelligence.
Clinical Application of Machine Learning Methods in Psychiatric Disorders

Abstract: Psychiatric disorders, especially bipolar affective disorder, present a significant burden on national and global healthcare systems, warranting advanced clinical management methods. Machine learning (ML) has emerged as a reliable tool to advance diagnosis, treatment, and monitoring. This paper compiles insights from literature to confirm the applicability of ML models in the clinical setting. The findings indicate that ML can predict psychiatric disorder symptoms from speech and imaging data with up to 89% accuracy. Furthermore, individual responses to treatment and remission cases can be forecasted with accuracies exceeding 80%. ML can also predict prevailing symptoms after treatment with up to 91.26% accuracy.
Stochastic Gradient Descent with Random Label Noises: Doubly Stochastic Models and Inference Stabilizer

Abstract Random label noises (or observational noises) widely exist in practical machine learning settings. While previous studies primarily focus on the affects of label noises to the performance of learning, our work intends to investigate the implicit regularization effects of the label noises, under mini-batch sampling settings of stochastic gradient descent (SGD), with assumptions that label noises are unbiased. Specifically, we analyze the learning dynamics of SGD over the quadratic loss with unbiased label noises, where we model the dynamics of SGD as a stochastic differentiable equation (SDE) with two diffusion terms (namely a Doubly Stochastic Model ). While the first diffusion term is caused by mini-batch sampling over the (labelnoiseless) loss gradients, as in many other works on SGD [1, 2], our model investigates the second noise term of SGD dynamics, which is caused by mini-batch sampling over the label noises, as an implicit regularizer. Our theoretical analysis finds such implicit regularizer would favor some convergence points that could stabilize model outputs against perturbation of parameters (namely inference stability). Though similar phenomenon have been investigated by Blanc et al. [3], our work doesn’t assume SGD as an Ornstein-Uhlenbeck like process and achieve a more generalizable result with convergence of approximation proved. To validate our analysis, we design two sets of empirical studies to analyze the implicit regularizer of SGD with unbiased random label noises for deep neural networks training and linear regression. Our first experiment studies the noisy self-distillation tricks for deep learning, where student networks are trained using the outputs from well-trained teachers with additive unbiased random label noises. Our experiment shows that the implicit regularizer caused by the label noises tend to select models with improved inference stability.