• Title/Summary/Keyword: Information Infrastructure

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A Video Encryption Based Approach for Privacy Protection of Video Surveillance Service (개인정보보호를 위한 영상 암호화 아키텍처 연구)

  • Kim, Jeongseok;Lee, Jaeho
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.12
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    • pp.307-314
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    • 2020
  • The video surveillance service is being widely deployed around our lives and the service stores sensitive data such as video streams in the cloud over the Internet or the centralized data store in an on-premise environment. The main concerning of these services is that the user should trust the service provider how secure the video or data is stored and handled without any concrete evidence. In this paper, we proposed the approach to protecting video by PKI (public key infrastructure) with a blockchain network. The video is encrypted by a symmetric key, then the key is shared through a blockchain network with taking advantage of the PKI mechanism. Therefore, the user can ensure the sensitive data is always kept secure and traceable in its lifecycle.

The Analysis and Classification of Urban Types for Potential Damage from Hazardous Chemical Accidents Using Factor and Cluster Analysis (요인 및 군집분석을 이용한 유해화학물질 사고 잠재적 피해에 대한 도시 유형 분류 및 특성 분석)

  • Lee, Seung Hoon;Ryu, Young Eun;Kim, Kyu Ri;Back, Jong In;Kim, Ho-Hyun;Ban, Yong Un
    • Journal of Environmental Health Sciences
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    • v.46 no.6
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    • pp.726-734
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    • 2020
  • Objectives: The aim of this study was to analyze and classify the characteristics of potential damage from hazardous chemical accidents in 229 administrative units in South Korea by reflecting the social and environmental characteristics of areas where chemical accidents can occur. Methods: A number of indicators were selected through preceding studies. Factor analysis was performed on selected indicators to derive factors, and cluster analysis was performed based on the factor scores. Results: As a result of the cluster analysis, 229 administrative units were divided into three clusters, and it was confirmed that each cluster had its own characteristics. Conclusions: The first cluster, "areas at risk of accident occurrence and spread of damage" was a type with a high potential for accident damage and a high density of hazardous facilities. The second cluster, "Urban infrastructure damage hazard areas" appeared to be a cluster with high urban development characteristics. Finally, the third cluster 'Urban and environmental damage hazard areas' appeared to be a cluster with an excellent natural environment. This study went further from the qualitative discussion related to existing chemical accidents to identify and respond to accident damage by reflecting the social and environmental characteristics of the region. Distinct from the previous studies related to the causes of accidents and the response system, it is meaningful to conduct empirical research focusing on the affected areas by analyzing the possibility of accident damage in reflection of the social and environmental characteristics of the community.

A Research on V2I-based Accident Prevention System for the Prevention of Unexpected Accident of Autonomous Vehicle (자율주행 차량의 돌발사고 방지를 위한 V2I 기반의 사고 방지체계 연구)

  • Han, SangYong;Kim, Myeong-jun;Kang, Dongwan;Baek, Sunwoo;Shin, Hee-seok;Kim, Jungha
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.3
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    • pp.86-99
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    • 2021
  • This research proposes the Accident Prevention System to prevent collision accident that can occur due to blind spots such as crossway or school zone using V2I communication. Vision sensor and LiDAR sensor located in the infrastructure of crossway somewhere like that recognize objects and warn vehicles at risk of accidents to prevent accidents in advance. Using deep learning-based YOLOv4 to recognize the object entering the intersection and using the Manhattan Distance value with LiDAR sensors to calculate the expected collision time and the weight of braking distance and secure safe distance. V2I communication used ROS (Robot Operating System) communication to prevent accidents in advance by conveying various information to the vehicle, including class, distance, and speed of entry objects, in addition to collision warning.

A Study on the Intention to use the Artificial Intelligence-based Drug Discovery and Development System using TOE Framework and Value-based Adoption Model (TOE 프레임워크와 가치기반수용모형 기반의 인공지능 신약개발 시스템 활용의도에 관한 실증 연구)

  • Kim, Yeongdae;Lee, Won Suk;Jang, Sang-hyun;Shin, Yongtae
    • Journal of Information Technology Services
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    • v.20 no.3
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    • pp.41-56
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    • 2021
  • New drug discovery and development research enable clinical treatment that saves human life and improves the quality of life, but the possibility of success with new drugs is significantly low despite a long time of 14 to 16 years and a large investment of 2 to 3 trillion won in traditional methods. As artificial intelligence is expected to radically change the new drug development paradigm, artificial intelligence new drug discovery and development projects are underway in various forms of collaboration, such as joint research between global pharmaceutical companies and IT companies, and government-private consortiums. This study uses the TOE framework and the Value-based Adoption Model, and the technical, organizational, and environmental factors that should be considered for the acceptance of AI technology at the level of the new drug research organization are the value of artificial intelligence technology. By analyzing the explanatory power of the relationship between perception and intention to use, it is intended to derive practical implications. Therefore, in this work, we present a research model in which technical, organizational, and environmental factors affecting the introduction of artificial intelligence technologies are mediated by strategic value recognition that takes into account all factors of benefit and sacrifice. Empirical analysis shows that usefulness, technicality, and innovativeness have significantly affected the perceived value of AI drug development systems, and that social influence and technology support infrastructure have significant impact on AI Drug Discovery and Development systems.

A Decentralized Face Mask Distribution System Based on the Decentralized Identity Management (블록체인 분산신원증명에 기반한 탈중앙화된 마스크 중복구매 확인 시스템)

  • Noh, Siwan;Jang, Seolah;Rhee, Kyung-Hyune
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.12
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    • pp.315-320
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    • 2020
  • Identity authentication is an important technology that has long been used in society to identify individuals and provide appropriate services. With the development of the Internet infrastructure, many areas have expanded into online areas, and identity authentication technologies have also expanded online. However, there is still a limit to identity authentication technology that relies entirely on trusted third parties like the government. A centralized identity management system makes the identification process between agencies with different identity management systems very complex, resulting in a waste of money and time for users. In particular, the limits of the centralized identity management system were clearly revealed in the face mask shortage in the 2020 COVID-19 crisis. A Decentralized Identity (DID) is a way for users to manage their identity on their own, and recently, a number of DID platform based on blockchain technology have been proposed. In this paper, we analyze the limitations of the existing centralized identity management system and propose a DID system that can be utilized in future national emergency situations such as COVID-19.

Comparison of Research Characteristics in Western, Chinese Traditional Medicine and Korean Medicine on Psoriasis (건선의 동서의학적 연구 특징의 비교)

  • Lee, Sundong;Jung, Seyoung;Lee, Seung eun
    • The Journal of Korean Medicine
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    • v.42 no.2
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    • pp.72-81
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    • 2021
  • Objectives: We compared research characteristics of western medicine, Chinese medicine and Korean medicine on causes, mechanisms, types, treatments and prevention of psoriasis. Methods: For western medicine, "Psoriasis" was used as keyword on Pubmed, for Chinese medicine, "銀屑病" and "中医" on CNKI (China National Knowledge Infrastructure" and for Korean medicine, "건선" on OASIS. Keyword searches were done for papers and books published after 2010. For Chinese medicine, there were more in-depth searches done for "從血論 (血熱, 血瘀, 血燥)" and "陽虛症". Results: Western medicine puts an emphasis on the foci, and approaches it from molecular and genetic levels based on molecular biology; while it views psoriasis as a disease with multiple possible causes, it ultimately sees it as an inflammation that is immunity-mediated. Western medicine seeks to suppress cytokine in order to prevent and eliminate inflammation at each stage of treatment While they are effective short-term, psoriasis recurs shortly after. Chinese and Korean medicines categorize psoriasis as an internal comprehensive systemic diseases that encompasses the patient's physical and mental characteristics, and defines it as a disease that has many causes and mechanisms such as "血熱, 血瘀, 血燥" and "陽虛". They use herbal medicine, acupuncture, and lifestyle interventions to improve the overall health of the patient in addition to treating psoriasis. Treatments are effective, but it takes relatively longer to see results, and can recur. Conclusion: In order for more progress to happen on psoriasis treatment, each branch of medicine must exchange knowledge and information more frequently.

A Study on the Strategy of the Use of Big Data for Cost Estimating in Construction Management Firms based on the SWOT Analysis (SWOT분석을 통한 CM사 견적업무 빅데이터 활용전략에 관한 연구)

  • Kim, Hyeon Jin;Kim, Han Soo
    • Korean Journal of Construction Engineering and Management
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    • v.23 no.2
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    • pp.54-64
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    • 2022
  • Since the interest in big data is growing exponentially, various types of research and development in the field of big data have been conducted in the construction industry. Among various application areas, cost estimating can be a topic where the use of big data provides positive benefits. In order for firms to make efficient use of big data for estimating tasks, they need to establish a strategy based on the multifaceted analysis of internal and external environments. The objective of the study is to develop and propose a strategy of the use of big data for construction management(CM) firms' cost estimating tasks based on the SWOT analysis. Through the combined efforts of literature review, questionnaire survey, interviews and the SWOT analysis, the study suggests that CM firms need to maintain the current level of the receptive culture for the use of big data and expand incrementally information resources. It also proposes that they need to reinforce the weak areas including big data experts and practice infrastructure for improving the big data-based cost estimating.

Design and Development of Cognitive Judgment Platform using Augmented Reality (증강현실을 이용한 인지 판단 플랫폼 설계 및 개발)

  • Lee, Cheol-Seung;Kim, Kuk-Se
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.6
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    • pp.1249-1254
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    • 2021
  • Computing technology and networking technology in the era of the 4th industrial revolution are rapidly evolving into an intelligent information society. AR, VR, and MR technologies, which are dual immersive media fields, are being applied in many convergence technologies, especially! The development of the health and healthcare field is actively progressing. In the field of health and healthcare, there are many problems due to aging of the population, increase in chronic progress, lack of infrastructure, and lack of professional manpower. services in the field are adopted. Therefore, this study applies cognitive evaluation through a computing system to the mild cognitive impairment, designs and develops a cognitive judgment platform using augmented reality based on the cognitive judgment technology system design, and integrates AI and BigData-based intelligent cognitive rehabilitation in the future. It is used as basic data for service platform development.

A Study on The Effect of Perceived Value and Innovation Resistance Factors on Adoption Intention of Artificial Intelligence Platform: Focused on Drug Discovery Fields (인공지능(AI) 플랫폼의 지각된 가치 및 혁신저항 요인이 수용의도에 미치는 영향: 신약 연구 분야를 중심으로)

  • Kim, Yeongdae;Kim, Ji-Young;Jeong, Wonkyung;Shin, Yongtae
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.12
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    • pp.329-342
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    • 2021
  • The pharmaceutical industry is experiencing a productivity crisis with a low probability of success despite a long period of time and enormous cost. As a strategy to solve the productivity crisis, the use cases of Artificial Intelligence(AI) and Bigdata are increasing worldwide and tangible results are coming out. However, domestic pharmaceutical companies are taking a wait-and-see attitude to adopt AI platform for drug research. This study proposed a research model that combines the Value-based Adoption Model and the Innovation Resistance Model to empirically study the effect of value perception and resistance factors on adopting AI Platform. As a result of empirical verification, usefulness, knowledge richness, complexity, and algorithmic opacity were found to have a significant effect on perceived values. And, usefulness, knowledge richness, algorithmic opacity, trialability, technology support infrastructure were found to have a significant effect on the innovation resistance.

A Study on Vehicle License Plate Recognition System through Fake License Plate Generator in YOLOv5 (YOLOv5에서 가상 번호판 생성을 통한 차량 번호판 인식 시스템에 관한 연구)

  • Ha, Sang-Hyun;Jeong, Seok Chan;Jeon, Young-Joon;Jang, Mun-Seok
    • Journal of the Korean Society of Industry Convergence
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    • v.24 no.6_2
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    • pp.699-706
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    • 2021
  • Existing license plate recognition system is used as an optical character recognition method, but a method of using deep learning has been proposed in recent studies because it has problems with image quality and Korean misrecognition. This requires a lot of data collection, but the collection of license plates is not easy to collect due to the problem of the Personal Information Protection Act, and labeling work to designate the location of individual license plates is required, but it also requires a lot of time. Therefore, in this paper, to solve this problem, five types of license plates were created using a virtual Korean license plate generation program according to the notice of the Ministry of Land, Infrastructure and Transport. And the generated license plate is synthesized in the license plate part of collectable vehicle images to construct 10,147 learning data to be used in deep learning. The learning data classifies license plates, Korean, and numbers into individual classes and learn using YOLOv5. Since the proposed method recognizes letters and numbers individually, if the font does not change, it can be recognized even if the license plate standard changes or the number of characters increases. As a result of the experiment, an accuracy of 96.82% was obtained, and it can be applied not only to the learned license plate but also to new types of license plates such as new license plates and eco-friendly license plates.