• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.221-232
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• 2021

In recent years, with the existence of huge amounts of data stored in huge databases, the need for developing accurate tools for analyzing data and extracting information and knowledge from the huge and multi-source databases have been increased. Hence, new and modern techniques have emerged that will contribute to the development of all other sciences. Knowledge discovery techniques are among these technologies, one popular technique of knowledge discovery techniques is data mining which aims to knowledge discovery from huge amounts of data. Such modern technologies of knowledge discovery will contribute to the development of all other fields. Data mining is important, interesting technique, and has many different and varied algorithms; Therefore, this paper aims to present overview of data mining, and clarify the most important of those algorithms and their uses.

• Journal of information and communication convergence engineering
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• v.19 no.4
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• pp.257-262
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• 2021

Providing web services to users has become expensive in recent times. For better web services, a web server is provided with high-performance technology. To achieve great web service experiences, tools such as general-purpose graphics processing units (GPGPUs), artificial intelligence, high-performance computing, and three-dimensional simulation are widely used. However, graphics processing units (GPUs) are used in high-speed operations and have limited general applications. In this study, we developed a task queue in a GPU to improve the performance of a web service using a multiprocessor and studied how to receive and process user requests in bulk. We propose the use of a GPGPU-based task queue to process user requests more than GPGPU based a central processing unit thread, and to process more GPU threads on task queue at about 136% to 233%, and proved that the proposed method is effective for web service.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.229-235
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• 2022

This study aims to substantiate an interdisciplinary methodology for automated analysis and qualitative assessment of legislation and court decisions. The development of this kind of methodology will make it possible to fill a number of methodological gaps in various research areas, including law effectiveness assessment and legal monitoring. We have defined a methodology based on the interdisciplinary principles and tools. In general, it should be noted that even at the level of qualitative assessment made with the use of the methodology described above, the accumulation of knowledge about the relationship between legal objectives, indicators and computer methods of their identification can reduce the role of expert knowledge and subjective factor in the process of assessment, planning, forecasting and control over the state of legislation and law enforcement. Automation of intellectual processes becomes inevitable in a digital society, but, releasing experts from routine work, simultaneously reorients it to development of interdisciplinary methods and control over their application.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.366-370
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• 2005

The construction environment is dynamic in nature and is characterized by various degrees of uncertainties. The uncertainties such as lack of coordination, non availability of resources, condition of temporary structures and varying weather conditions have a significant impact on estimating the duration of activities. These are subjective, vague and imprecisely defined and are expressed in subjective measures rather than mathematical terms. Conventionally, various quantitative techniques such as CPM and PERT have emerged in construction industry. These techniques cannot solve the above problems and rely on human experts which may not always be possible. In such situations Artificial Intelligence tools such as fuzzy sets and neural networks handle such variables and provide global strategies. The present paper evaluates the effect of qualitative factors to identify the activity duration using new intelligent approach. The results are compared with conventional methods for effective project management. A case study is considered to demonstrate the applicability of fuzzy logic for project scheduling.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.103-110
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• 2023

Financial inclusion is the safe and timely access of formal financial services to people at affordable costs. Various barriers of legacy financial system hinder the involvement of all segments of populations in the financial sector. The journey from financial exclusion to financial inclusion has to be achieved with the implementation of technological breakthroughs. Covid-19 has also raised the need for technology in all sectors of the economy. This research paper introduces the concept of intelligent financial inclusion which is the provision of financial services to people with the help of intelligent systems. This intelligent system will take the concepts from the human mind, cognitive sciences, and artificial intelligence tools and techniques. For achieving the optimal level of financial inclusion, economies must shift their financial sector from traditional means to intelligent financial systems. In this way, intelligent financial inclusion will achieve the target of involving all people in the financial sector.

• Journal of Korea Artificial Intelligence Association
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• v.1 no.2
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• pp.7-13
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• 2023

In this paper, Depression is a mental disorder characterized by a lack of enthusiasm and feelings of sadness, which significantly impairs daily functioning. In 2018, there was an increase in book sales in the essay genre, particularly the popularity of "healing essays." This trend is seen as challenging the negative image and prejudices associated with depression. In 2021, a significant rise in the proportion of 20-year-old patients with depression is attributed to factors like job-related stress, interpersonal issues, and financial burdens. Additionally, there is a strong correlation between depression and suicidal thoughts, particularly among individuals who have experienced feelings of depression. Despite the increasing prevalence of depression among young adults, research in this area is lacking. To address this gap, statistical tools such as logistic regression and chi-squared tests are employed. The analysis reveals various independent variables associated with feelings of depression, shedding light on the relationships between these factors.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.199-204
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• 2024

This study aims to explore the issue of character consistency in AI-generated artwork. First, the concept of character consistency is explained, including the consistency of appearance, actions, and lighting, and its importance in continuous creation and storytelling is analyzed. Next, the study examines current mainstream AI drawing tools such as MidJourney and Stable Diffusion-based WebUI and ComfyUI, evaluating their strengths and limitations in maintaining character consistency. Finally, methods to improve AI drawing technology were proposed to enhance character consistency, aiming to achieve a higher level of consistency in AI art creation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.701-713
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• 2021

Race Condition is a vulnerability in which two or more processes input or manipulate a common resource at the same time, resulting in unintended results. This vulnerability can lead to problems such as denial of service, elevation of privilege. When a vulnerability occurs in software, the relevant information is documented, but often the cause of the vulnerability or the source code is not disclosed. In this case, analysis at the binary level is necessary to detect the vulnerability. This paper aims to detect the Time-Of-Check Time-Of-Use (TOCTOU) Race Condition vulnerability of UNIX kernel-based File System at the binary level. So far, various detection techniques of static/dynamic analysis techniques have been studied for the vulnerability. Existing vulnerability detection tools using static analysis detect through source code analysis, and there are currently few studies conducted at the binary level. In this paper, we propose a method for detecting TOCTOU Race Condition in File System based on Control Flow Graph and Call Graph through Binary Analysis Platform (BAP), a binary static analysis tool.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.495-509
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• 2020

This study is a theoretical research to explore ways to effectively learn AI in the age of intelligent information driven by artificial intelligence (hereinafter referred to as AI). The emphasis is on presenting a teaching method to make AI education accessible not only to students majoring in mathematics, statistics, or computer science, but also to other majors such as humanities and social sciences and the general public. Given the need for 'Explainable AI(XAI: eXplainable AI)' and 'the importance of storytelling for a sensible and intelligent machine(AI)' by Patrick Winston at the MIT AI Institute [33], we can find the significance of research on AI storytelling learning model. To this end, we discuss the possibility through a pilot study targeting general students of an university in Daegu. First, we introduce the AI storytelling(AI+ST) learning method[30], and review the educational goals, the system of contents, the learning methodology and the use of new AI tools in the method. Then, the results of the learners are compared and analyzed, focusing on research questions: 1) Can the AI+ST learning method complement algorithm-driven or developer-centered learning methods? 2) Whether the AI+ST learning method is effective for students and thus help them to develop their AI comprehension, interest and application skills.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.193-206
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• 2021

Artificial Intelligence (AI) has been inserted into people's lives through Intelligent Virtual Assistants (IVA), like Alexa. Moreover, intelligent systems have expanded to design studios. This research delves into designers' perspectives on developing AI-based practices and examines the challenges of adopting future intelligent design assistants. We surveyed UX/UI professionals in Brazil to understand how they use IVAs and AI design tools. We also explored a scenario featuring the use of Alexa Sensei, a hypothetical voice-controlled AI-based design assistant mixing Alexa and Adobe Sensei characteristics. The findings indicate respondents have had limited opportunities to work with AI, but they expect intelligent systems to improve the efficiency of the design process. Further, majority of the respondents predicted that they would be able to collaborate creatively with AI design systems. Although designers anticipated challenges in natural language interaction, those who already adopted IVAs were less resistant to the idea of working with Alexa Sensei as an AI design assistant.