• International Journal of Computer Science & Network Security
• /
• v.22 no.12
• /
• pp.197-204
• /
• 2022

Sorting is an important data structure in many applications in the real world. Several sorting algorithms are currently in use for searching and other operations. Sorting algorithms rearrange the elements of an array or list based on the elements' comparison operators. The comparison operator is used in the accurate data structure to establish the new order of elements. This report analyzes and compares the time complexity and running time theoretically and experimentally of insertion, merge, and heap sort algorithms. Java language is used by the NetBeans tool to implement the code of the algorithms. The results show that when dealing with sorted elements, insertion sort has a faster running time than merge and heap algorithms. When it comes to dealing with a large number of elements, it is better to use the merge sort. For the number of comparisons for each algorithm, the insertion sort has the highest number of comparisons.

• International Journal of Computer Science & Network Security
• /
• v.23 no.9
• /
• pp.192-198
• /
• 2023

Cyberbullying is a growing problem among adolescents and can have serious psychological and emotional consequences for the victims. In recent years, machine learning techniques have emerged as promising approach for detecting instances of cyberbullying in online communication. This research paper focuses on developing a machine learning models that are able to detect cyberbullying including support vector machines, naïve bayes, and random forests. The study uses a dataset of real-world examples of cyberbullying collected from Twitter and extracts features that represents the ideational metafunction, then evaluates the performance of each algorithm before and after considering the theory of systemic functional linguistics in terms of precision, recall, and F1-score. The result indicates that all three algorithms are effective at detecting cyberbullying with 92% for naïve bayes and an accuracy of 93% for both SVM and random forests. However, the study also highlights the challenges of accurately detecting cyberbullying, particularly given the nuanced and context-dependent nature of online communication. This paper concludes by discussing the implications of these findings for future research and the development of practical tool for cyberbullying prevention and intervention.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.162-169
• /
• 2022

In an attempt to disseminate modernized Korean traditional housing (Hanok), a ten-year research project was initiated in 2010 by the Korean Government to reduce the construction cost, improve the facility performance, and automate the Hanok construction industry. To meet these objectives, various research areas, including public policies, planning methods, design standards, new building materials, construction standards, maintenance procedures, advanced project management tools, and integrated IT applications have been developed. In addition, comprehensive technologies developed were applied to the ten pilot Hanok buildings to validate the real-world performance as part of the research project. To further facilitate the digital transformation of the Hanok industry by using the research results, it is required to disseminate the developed technologies in an automated and standardized manner. In particular, it is crucial to systematize and manage the interoperability of various technical data and accumulated historical data for different business functions, especially within the highly fragmented industry. In this context, this paper proposes an ontology-based Hanok information dissemination platform to enable industry-wide automated knowledge and information sharing. The system architecture, standardized historical database, and advanced analytics based on ontology web language (OWL) for the Hanok industrialization platform are introduced.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.3
• /
• pp.215-221
• /
• 2023

If the C++ programming class, an object-oriented language capable of modeling similar to the real world, is developed as a curriculum that introduces the flipped learning model, students' active problem-solving skills can be cultivated. In this subject development case, it is significant that the flipped learning technique was applied to the programming class and was effective in improving students' active problem-solving skills. First, the lectures in the 4th session were divided into Pre-Class, In-Class, and Post-Class, and the class was conducted in a way that suggested class goals suitable for the subject and formed a team to discuss. At the end of the lecture, a follow-up survey was conducted to check whether the learners learned effectively.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2020.05a
• /
• pp.519-522
• /
• 2020

1989년에 WWW(World Wide Web)이 도입 되면서 세계적으로 인터넷의 보급이 시작되었다. 정보화 시대라고 알려진 3차 산업혁명 이후로 대량의 정보들이 소셜 미디어를 통하여 생산되었다. 소셜미디어는 2007년에 인터넷 사용자들 중 56%의 이용률을 보였지만 2008년 2분기에는 75%의 이용률로 증가함에 따라 대부분의 사용자들이 많이 사용하며 의존하게 되었다. 또한 소셜 미디어를 통해 발생 되는 데이터들을 이용하여 기업들은 이윤 창출을 할 수 있다. 하지만 이러한 소셜 미디어는 악의적인 목적을 통해 주가 조작, 정치적 선동 등을 할 수 있는 가짜 뉴스와 허위 정보들을 생성할 수 있으며 이에 따라 대책이 시급하다. 또한 가짜 뉴스는 사람이 글을 작성할 수도 있지만 최근 인공지능 기술의 발달에 따라 프로그램을 통해 자동적으로 생성 될 수도 있다. 본 논문에서는 이와 같은 실제 뉴스와 인공지능을 기반으로 한 뉴스를 분석한다. Kaggle에서 실제 뉴스 데이터를 수집하여 헤드라인을 OpenAI의 GPT-2 언어 모델을 통해 뉴럴 가짜 뉴스를 생성 하였다. 파이썬의 NLTK 모듈을 이용하여 전처리를 진행하였고 t-검정과 박스 플롯을 활용하여 분석을 진행하였다. 분석된 주요 속성들을 의사결정트리를 통해 모델 검증을 하였고 k-fold 교차검증을 통해 분류 모델을 평가하였다. 결과로 전체 분류 정확도 평균 89%의 성능을 보여주었다.

• Asia pacific journal of information systems
• /
• v.33 no.4
• /
• pp.1016-1035
• /
• 2023

Corporate tax avoidance has been the subject of international debate since the Enron scandal and has raised awareness of the need for greater transparency in financial markets. Efforts have been made to strengthen financial reporting requirements and meet the needs of investors and other stakeholders, including digitalization of financial reporting through Extensible Business Reporting Language (XBRL). This study examines the impact of the mandatory adoption of XBRL on corporate tax avoidance. We tested our predictions using a panel dataset of Indonesian firms listed on the IDX stock exchange. Based on available information in the DATASTREAM database covering the 2013-2017 period, we used two proxies for tax avoidance i.e., GAAP effective tax rate and current effective tax rate. We estimated multiple regression model including industry and year fixed effects. The results show that XBRL implementation has reduced corporate tax avoidance. These findings suggest that improving corporate transparency through XBRL could play a deterrent tool to corporate tax avoidance. The results of this study should be useful to tax authorities and accounting standard setters supporting the benefits of digitalizing financial reporting and continuing to complete XBRL taxonomies around the world.

• Acta Via Serica
• /
• v.8 no.2
• /
• pp.1-24
• /
• 2023

The art of carpet weaving is the most habitual form of traditional art in Azerbaijan, it reflects a rich inner world and occupies a special place in the history of a national culture's development. The Azerbaijani carpet has always stood out for its plots, ornaments, compositions, and high quality and the Azerbaijani people, faithful to their spiritual values, have protected and developed it throughout the centuries. In this article, several Ganja-Gazakh-type carpets from the Azerbaijan National Carpet Museum collection and their artistic and technical characteristics are discussed. Specimens of material, sacred language, and ornamentation are considered. The deepest meaning is embodied in tamga in particular. Tamga is a unique phenomenon serving as an amulet, lineage sign, and self-identification of Turkic peoples. The Gazakh carpets of the Ganja-Gazakh type cover the Gazakh region of Azerbaijan, the Borchali region of Georgia, and the Goycha Lake region of Armenia. Karapapakh Azerbaijani Turks have inhabited these areas since ancient times. Tarakama (nomads) are often equated with the name Karapapakh (black hat). One of the densely populated regions of Tarakama is Gazakh. Gazakh, Garagoyunlu, Salahli, Shikhli, Kamarli, Damirchilar, Gaymagli, Goycali, Daghkasaman, Oysuzlu, Gachagan, and pile carpets with different compositions are woven in the Gazakh carpet weaving center. Large, simple in form, step-shaped or hook-like medallions, horn-shaped patterns, animal images, and stamps with symbols of ancient Turkic tribes characterize the Gazakh carpet weaving group.

• Journal of Information Technology Applications and Management
• /
• v.31 no.3
• /
• pp.149-163
• /
• 2024

As conversational AI systems such as ChatGPT have become more advanced, researchers are exploring ways to use them in education. However, we need effective ways to evaluate these systems before allowing them to help teach students. This study proposes a detailed framework for testing conversational AI across three important criteria as follow. First, specialized benchmarks that measure skills include giving clear explanations, adapting to context during long dialogues, and maintaining a consistent teaching personality. Second, adaptive standards check whether the systems meet the ethical requirements of privacy, fairness, and transparency. These standards are regularly updated to match societal expectations. Lastly, evaluations were conducted from three perspectives: technical accuracy on test datasets, performance during simulations with groups of virtual students, and feedback from real students and teachers using the system. This framework provides a robust methodology for identifying strengths and weaknesses of conversational AI before its deployment in schools. It emphasizes assessments tailored to the critical qualities of dialogic intelligence, user-centric metrics capturing real-world impact, and ethical alignment through participatory design. Responsible innovation by AI assistants requires evidence that they can enhance accessible, engaging, and personalized education without disrupting teaching effectiveness or student agency.

• International Journal of Computer Science & Network Security
• /
• v.24 no.7
• /
• pp.195-201
• /
• 2024

With the Covid-19(Corona Virus) spread all around the world, people are using this propaganda and the desperate need of the citizens to know the news about this mysterious virus by spreading fake news. Some Countries arrested people who spread fake news about this, and others made them pay a fine. And since Social Media has become a significant source of news, .there is a profound need to detect these fake news. The main aim of this research is to develop a web-based model using a combination of machine learning algorithms to detect fake news. The proposed model includes an advanced framework to identify tweets with fake news using Context Analysis; We assumed that Natural Language Processing(NLP) wouldn't be enough alone to make context analysis as Tweets are usually short and do not follow even the most straightforward syntactic rules, so we used Tweets Features as several retweets, several likes and tweet-length we also added statistical credibility analysis for Twitter users. The proposed algorithms are tested on four different benchmark datasets. And Finally, to get the best accuracy, we combined two of the best algorithms used SVM ( which is widely accepted as baseline classifier, especially with binary classification problems ) and Naive Base.

• Cartoon and Animation Studies
• /
• s.42
• /
• pp.151-175
• /
• 2016

The game industry has evolved from mobile games to PC online games after the smart-phone industry was opened up. In this environment, the game industry has rather been negatively developing its commercials means than the sufficient fundamental entertainment to the users. Especially, many games were released with better graphic qualities yet poor originality, continuing to be popular without enhancing the market itself. Moreover, the user's recognition level has improved. The users share their online gaming experience easily with the development of network environment. They receive the feedbacks on the quality of the game through the online channels and media by sharing them together. The high margin of the game industry will lead to the negative feedbacks of the users, effecting them to critique the content although the market looks good for now. The game industry's evolution has to be reviewed in the perspective of users, to look back at the successful cases of the past before the mobile era by analyzing and indicating the quality of the games and content's direction. This research is focused on the success factors of from the user's point of view, which has been widely claimed as a popular game franchise publicly before the mobile games had risen. WOW has been the most successful MMORPG game with its user record of 1.2 million till now. For these reasons, this study analyzes 's success factors from the user's point of view by configuring five expert groups, sequentially applying expert group survey, interview, Jobs-to-be-done and Fishbein Model as UX methodologies based on the business model to see through its long term rein in the industry. Consequently, The success factors from the user side of MMORPG provides an opportunity for the users to interact deeply with the game by (1) using well designed 'world view' over 10 years, (2) providing 'national policy' that is based on the locations of the users' culture and language, (3) providing 'expansions' with changes in time to give the digging elements to the users.