• Molecules and Cells
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• v.43 no.3
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• pp.286-297
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• 2020

Mammalian patatin-like phospholipase domain containing proteins (PNPLAs) play critical roles in triglyceride hydrolysis, phospholipids metabolism, and lipid droplet (LD) homeostasis. PNPLA7 is a lysophosphatidylcholine hydrolase anchored on the endoplasmic reticulum which associates with LDs through its catalytic region (PNPLA7-C) in response to increased cyclic nucleotide levels. However, the interaction of PNPLA7 with LDs through its catalytic region is unknown. Herein, we demonstrate that PNPLA7-C localizes to the mature LDs ex vivo and also colocalizes with pre-existing LDs. Localization of PNPLA7-C with LDs induces LDs clustering via non-enzymatic intermolecular associations, while PNPLA7 alone does not induce LD clustering. Residues 742-1016 contains four putative transmembrane domains which act as a LD targeting motif and are required for the localization of PNPLA7-C to LDs. Furthermore, the N-terminal flanking region of the LD targeting motif, residues 681-741, contributes to the LD targeting, whereas the C-terminal flanking region (1169-1326) has an anti-LD targeting effect. Interestingly, the LD targeting motif does not exhibit lysophosphatidylcholine hydrolase activity even though it associates with LDs phospholipid membranes. These findings characterize the specific functional domains of PNPLA7 mediating subcellular positioning and interactions with LDs, as wells as providing critical insights into the structure of this evolutionarily conserved phospholipid-metabolizing enzyme family.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.2-5
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• 2022

With the advent of deep learning and the rapid development of ICT (Information and Communication Technology), research using artificial intelligence is being actively conducted in various fields of society such as politics, economy, and culture and so on. Deep learning-based artificial intelligence technology is subdivided into various domains such as natural language processing, image processing, speech processing, and recommendation system. In particular, as the industry is advanced, the need for a recommendation system that analyzes market trends and individual characteristics and recommends them to consumers is increasingly required. In line with these technological developments, this paper extracts and classifies attribute information from structured or unstructured text and image big data through deep learning-based technology development of 'language processing intelligence' and 'image processing intelligence', and We propose an artificial intelligence-based 'customized fashion advisor' service integration system that analyzes trends and new materials, discovers 'market-consumer' insights through consumer taste analysis, and can recommend style, virtual fitting, and design support.

• Journal of Intelligence and Information Systems
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• v.10 no.1
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• pp.65-75
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• 2004

It is notorious that PIN(Personal Identification Number) is used widely for user verification and authentication in networked environment. But, when the user Identification and password are exposed by hacking, we can be damaged monetary damage as well as invasion of privacy. In this paper, we adopt face recognition-based authentication which have nothing to worry what the ID and password will be exposed. Also, we suggest the remote authentication and verification system by considering not only 2-Tier system but also 3-Tier system getting be distributed. In this research, we analyze the face feature data using the SVM(Support Vector Machine) and PCA(Principle Component Analysis), and implement artificial intelligence face recognition module in distributed environment which increase the authentication speed and heightens accuracy by utilizing artificial intelligence techniques.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1365-1377
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• 2019

Summarizing the differences in Chinese-Vietnamese bilingual news plays an important supporting role in the comparative analysis of news views between China and Vietnam. Aiming at cross-language problems in the analysis of the differences between Chinese and Vietnamese bilingual news, we propose a new method of summarizing the differences based on an undirected graph model. The method extracts elements to represent the sentences, and builds a bridge between different languages based on Wikipedia's multilingual concept description page. Firstly, we calculate the similarity between Chinese and Vietnamese news sentences, and filter the bilingual sentences accordingly. Then we use the filtered sentences as nodes and the similarity grade as the weight of the edge to construct an undirected graph model. Finally, combining the random walk algorithm, the weight of the node is calculated according to the weight of the edge, and sentences with highest weight can be extracted as the difference summary. The experiment results show that our proposed approach achieved the highest score of 0.1837 on the annotated test set, which outperforms the state-of-the-art summarization models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.5112-5128
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• 2016

Tracking human body is an important problem in computer vision field. Tracking failures caused by occlusion can lead to wrong rectification of the target position. In this paper, a robust human tracking algorithm is proposed to address the problem of occlusion, rotation and improve the tracking accuracy. It is based on Tracking-Learning-Detection framework. The key auxiliary information is used in the framework which motivated by the fact that a tracking target is usually embedded in the context that provides useful information. First, face localization method is utilized to find key face location information. Second, the relative position relationship is established between the auxiliary information and the target location. With the relevant model, the key face information will get the current target position when a target has disappeared. Thus, the target can be stably tracked even when it is partially or fully occluded. Experiments are conducted in various challenging videos. In conjunction with online update, the results demonstrate that the proposed method outperforms the traditional TLD algorithm, and it has a relatively better tracking performance than other state-of-the-art methods.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.1-13
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• 2020

With the advent of an intelligent information society, research toward artificial intelligence education was conducted. In previous studies, the subject of research is biased, and studies that analyze attitudes toward artificial intelligence are insufficient. So, in this study developed a test tool to measure the artificial intelligence of high school students and analyze their attitudes toward artificial intelligence. To develop the test tool, 229 high school students completed a preliminary test, of which the results were analyzed via exploratory factor analysis. To analyze the students' attitudes toward artificial intelligence, the resulting test tool was applied to 481 high school students, and their test results were analyzed according to factors. From the study's results, there was no difference according to gender in the students' attitudes toward artificial intelligence, but there was a significant difference per grade. In addition, there was a significant difference in attitudes according to artificial intelligence-related experiences: the high school students who had direct and indirect experience with artificial intelligence, programming, and more frequently used it had more positive attitudes toward artificial intelligence than students without this experience. However, artificial intelligence education experience negatively influenced the students' attitudes toward artificial intelligence. Overall, the higher their interest in artificial intelligence, the more positive the high school students' attitudes toward artificial intelligence.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.302-309
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• 2023

Artificial intelligence (AI) plays a crucial role in the intelligent development of China's power system. It is also an important part of the digital development of the power grid. The development of AI determines whether the digital transformation of China's power system can be successfully implemented. Therefore, this paper discusses the digital transformation of the power grid based on AI technologies. The author has established a digital evaluation index system to reflect the development of the power grid in one province. Both qualitative and quantitative methods have been adopted in the analysis, which delves into the economic effectiveness, quality, and coordination of power grid development in the province in a comprehensive way. Results show that, to meet the needs of the power grid's digital transformation, the correlation coefficient between the power grid's development and the province's overall coordination has been increasing in recent years.

• Journal of Information Technology Applications and Management
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• v.17 no.1
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• pp.127-139
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• 2010

Customer behavior pattern discovery is the fundament for conducting customer oriented services and the services management. But, the composition, need, interest and experience of customers may be continuously changing, thereof lead to the difficulty in refining a stable description of their consistent behavior pattern. This paper presented a new method for the behavior pattern discovery from a changing collection of customers. It was originally inspired from the swarm intelligence of ant colony. By the adaptive clustering, some typical behavior patterns which reflect the characteristics of related customer clusters can extracted dynamically and adaptively.

• Proceedings of the Korean Society for Information Management Conference
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• 2002.08a
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• pp.69-74
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• 2002

오늘날 인터넷과 정보기술의 발전은 정보입수 채널을 다양화시킴에 따라 과거 대학도서관이 누렸던 대학 내 정보제공자로서의 독점적 위치를 상실하도록 만들었다. 이러한 새로운 환경은 대학도서관의 역할에 있어서 새로운 패러다임을 요구하게 되었다. 따라서 대학도서관은 도서관을 둘러싼 모든 환경의 변화를 감지하고 그에 대처하는 능력을 갖출 필요가 있다. 이에 본 연구에서는 Sense Making, Knowledge Creation, Decision Making, Holistic 등 경쟁정보(Competitive Intelligence) 관점에서의 정보 이용형태에 초점을 맞추어 대학도서관을 분석하고, 그에 따라 새로운 모델을 제시하고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.110-111
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• 2018

모바일 게임 시장의 성장과 함께 보안 위협도 함께 증가하고 있는 것이 현재 상황이다. 게임 앱을 해킹하여 결제를 우회한 뒤 금전적 이익을 가로채거나, 원작 게임의 복제 앱을 만들어 부당이득을 취하는 일이 빈번하게 발생하고 있다. 본 논문에서는 모바일 게임 보안을 위하여 위협 인텔리전스와 같은 기술을 기반으로 모바일 게임에서 악용되고 있는 단순한 공격 유형들을 대상으로 사전에 수집 분석하여 지능형 공격을 차단할 수 있는 방안을 제시한다.