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A Security Nonce Generation Algorithm Scheme Research for Improving Data Reliability and Anomaly Pattern Detection of Smart City Platform Data Management (스마트시티 플랫폼 데이터 운영의 이상패턴 탐지 및 데이터 신뢰성 향상을 위한 보안 난수 생성 알고리즘 방안 연구)

  • Lee, Jaekwan;Shin, Jinho;Joo, Yongjae;Noh, Jaekoo;Kim, Jae Do;Kim, Yongjoon;Jung, Namjoon
    • KEPCO Journal on Electric Power and Energy
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    • v.4 no.2
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    • pp.75-80
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    • 2018
  • The smart city is developing an energy system efficiently through a common management of the city resource for the growth and a low carbon social. However, the smart city doesn't counter a verification effectively about a anomaly pattern detection when existing security technology (authentication, integrity, confidentiality) is used by fixed security key and key deodorization according to generated big data. This paper is proposed the "security nonce generation based on security nonce generation" for anomaly pattern detection of the adversary and a safety of the key is high through the key generation of the KDC (Key Distribution Center; KDC) for improvement. The proposed scheme distributes the generated security nonce and authentication keys to each facilities system by the KDC. This proposed scheme can be enhanced to the security by doing the external pattern detection and changed new security key through distributed security nonce with keys. Therefore, this paper can do improving the security and a responsibility of the smart city platform management data through the anomaly pattern detection and the safety of the keys.

Designing a Platform Model for Building MyData Ecosystem (마이데이터 생태계 구축을 위한 플랫폼 모델 설계)

  • Kang, Nam-Gyu;Choi, Hee-Seok;Lee, Hye-Jin;Han, Sang-Jun;Lee, Seok-Hyoung
    • Journal of Internet Computing and Services
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    • v.22 no.2
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    • pp.123-131
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    • 2021
  • The Fourth Industrial Revolution was triggered by data-driven digital technologies such as AI and big data. There is a rapid movement to expand the scope of data utilization to the privacy area, which was considered only a protected area. Through the revision of the Data 3 Act, laws and systems were established that allow personal information to be freely transferred and utilized under their consent. But, it will be necessary to support the platform that encompasses the entire process from collecting personal information to managing and utilizing it. In this paper, we propose a platform model that can be applied to building mydata ecosystem using personal information. It describes the six essential functional requirements for building MyData platforms and the procedures and methods for implementing them. The six proposed essential features describe consent, sharing/downloading/ receipt of data, data collection and utilization, user authentication, API gateway, and platform services. We also illustrate the case of applying the MyData platform model to real-world, underprivileged mobility support services.

A Study on Model for Drivable Area Segmentation based on Deep Learning (딥러닝 기반의 주행가능 영역 추출 모델에 관한 연구)

  • Jeon, Hyo-jin;Cho, Soo-sun
    • Journal of Internet Computing and Services
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    • v.20 no.5
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    • pp.105-111
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    • 2019
  • Core technologies that lead the Fourth Industrial Revolution era, such as artificial intelligence, big data, and autonomous driving, are implemented and serviced through the rapid development of computing power and hyper-connected networks based on the Internet of Things. In this paper, we implement two different models for drivable area segmentation in various environment, and propose a better model by comparing the results. The models for drivable area segmentation are using DeepLab V3+ and Mask R-CNN, which have great performances in the field of image segmentation and are used in many studies in autonomous driving technology. For driving information in various environment, we use BDD dataset which provides driving videos and images in various weather conditions and day&night time. The result of two different models shows that Mask R-CNN has higher performance with 68.33% IoU than DeepLab V3+ with 48.97% IoU. In addition, the result of visual inspection of drivable area segmentation on driving image, the accuracy of Mask R-CNN is 83% and DeepLab V3+ is 69%. It indicates Mask R-CNN is more efficient than DeepLab V3+ in drivable area segmentation.

Different Heterogeneous IoT Data Management Techniques for IoT Cloud Environments (IoT 클라우드 환경을 위한 서로 다른 이기종의 IoT 데이터 관리 기법)

  • Cho, Sung-Nam;Jeong, Yoon-Su
    • Journal of Convergence for Information Technology
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    • v.10 no.12
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    • pp.15-21
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    • 2020
  • Although IoT systems are used in a variety of heterogeneous environments as cloud environments develop, all IoT devices are not provided with reliable protocols and services. This paper proposes an IoT data management technique that can extend the IoT cloud environment to an n-layer multi-level structure so that information collected from different heterogeneous IoT devices can be efficiently sorted and processed. The proposed technique aims to classify and process IoT information by transmitting routing information and weight information through wireless data link data collected from heterogeneous IoT devices. The proposed technique not only delivers information classified from IoT devices to the corresponding routing path but also improves the efficiency of IoT data processing by assigning priority according to weight information. The IoT devices used in the proposed technique use each other's reliable protocols, and queries for other IoT devices locally through a local cloud composed of hierarchical structures have features that ensure scalability because they maintain a certain cost.y channels of IoT information in order to make the most of the multiple antenna technology.

Analysis of Minimum Logistics Cost in SMEs using Korean-type CIPs Payment System (한국형 CIPs 결제 시스템을 이용한 중소기업의 최소 물류비용 분석)

  • Kim, Ilgoun;Jeong, Jongpil
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.1
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    • pp.7-18
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    • 2021
  • Recently, various connected industrial parks (CIPs) architectures using new technologies such as cloud computing, CPS, big data, fifth-generation mobile communication 5G, IIoT, VR-AR, and ventilation transportation AI algorithms have been proposed in Korea. Korea's small and medium-sized enterprises do not have the upper hand in technological competitiveness than overseas advanced countries such as the United States, Europe and Japan. For this reason, Korea's small and medium-sized enterprises have to invest a lot of money in technology research and development. As a latecomer, Korean SMEs need to improve their profitability in order to find sustainable growth potential. Financially, it is most efficient for small and medium-sized Korean companies to cut costs to increase their profitability. This paper made profitability improvement by reducing costs for small and medium-sized enterprises located in CIPs in Korea a major task. VJP (Vehicle Action Program) was noted as a way to reduce costs for small and medium-sized enterprises located in CIPs in Korea. The method of achieving minimum logistics costs for small businesses through the Korean CIPs payment system was analyzed. The details of the new Korean CIPs payment system were largely divided into four types: "Business", "Data", "Technique", and "Finance". Cost Benefit Analysis (CBA) was used as a performance analysis method for CIPs payment systems.

Multi-blockchain model ensures scalability and reliability based on intelligent Internet of Things (지능형 사물인터넷 기반의 확장성과 신뢰성을 보장하는 다중 블록체인 모델)

  • Jeong, Yoon-Su;Kim, Yong-Tae
    • Journal of Convergence for Information Technology
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    • v.11 no.3
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    • pp.140-146
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    • 2021
  • As the environment using intelligent IoT devices increases, various studies are underway to ensure the integrity of information sent and received from intelligent IoT devices. However, all IoT information generated in heterogeneous environments is not fully provided with reliable protocols and services. In this paper, we propose an intelligent-based multi-blockchain model that can extract only critical information among various information processed by intelligent IoT devices. In the proposed model, blockchain is used to ensure the integrity of IoT information sent and received from IoT devices. The proposed model uses the correlation index of the collected information to trust a large number of IoT information to extract only the information with a high correlation index and bind it with blockchain. This is because the collected information can be extended to the n-tier structure as well as guaranteed reliability. Furthermore, since the proposed model can give weight information to the collection information based on blockchain, similar information can be selected (or bound) according to priority. The proposed model is able to extend the collection information to the n-layer structure while maintaining the data processing cost processed in real time regardless of the number of IoT devices.

Modeling for Nuclear Energy for IoT Systems as Green Fuels in Mitigating COVID-19 (COVID-19 완화를 위한 녹색 연료로서 IoT 시스템용 원자력 에너지 모델링)

  • Jang, Kyung Bae;Baek, Chang Hyun;Woo, Tae Ho
    • Journal of Internet of Things and Convergence
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    • v.7 no.2
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    • pp.13-19
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    • 2021
  • It is analyzed that the energy pattern is affected by the social matters of the disease trend where the energy consumption has been reduced following the depression of the national economy. The campaign of social distance for the people has been done by voluntary or legally due to the epidemic of the Coronavirus Disease 2019 (COVID-19). Some economic stimulus policies have been done in some countries including the United States, South Korea, and some others. It is shown the susceptible, infectious, and recovered (SIR) modeling applied by system dynamics (SD) where the logical modeling is constructed with S, I, and R. Especially, the I is connected with Society including Population, Race, and Maturity. In addition, Economy and Politics are connected to Income, GDP, Resources, President, Popularity, Ruling Government, and Leadership. The graph shows the big jump on 2020 April when is the starting month of the S value multiplication. This shows the effect of the COVID-19 and its related post-pandemic trend. The trends of OECD and non-OECD are very similar and the effect of the virus hazards causes significantly to the economic depressions.

Social TV User's Object Relations Theory Factors Effects of Interaction and Viewing Satisfaction on Psychological Well-being (소셜TV 이용자의 대상관계요인이 상호작용성과 시청만족을 통해 심리적안녕감에 미치는 영향)

  • Kim, Min-Gyu;Byeon, Benjamin;Kwon, Do-Soon
    • Journal of Convergence for Information Technology
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    • v.11 no.6
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    • pp.243-261
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    • 2021
  • Social TV users and content are increasing day by day. The main purpose was to study the motivation for social television users, but I felt the need to analyze the potential psychological impact of users in various content. This study analyzed the impact on psychological well-being due to the interaction and viewing satisfaction by the object relations theory factors of social TV user in Korea. A survey was conducted on students of N university, ordinary university, and ordinary people who have experience using social TV to prove the observations or experiments of empirical facts in this study. Research result, First, Nonalienation have been have a positive effect on interaction and viewing satisfaction. Second, stable attachment have been have a positive effect on interaction. Third, social competence have been have a positive effect on interaction. Fourth, interaction have been have a positive effect on viewing satisfaction and psychological well-being. Fifth viewing satisfaction have been have a positive effect on Psychological well-being. Through this, This will contribute to the development of subdivided content and user-customized services for social television, and it is necessary to reconfigure and study various events that may occur between users in the future.

Perception and Attitude on Augmented Reality Smart Glass for Healthcare Convergence Simulation (증강현실(AR) 스마트글라스 보건의료 융합 시뮬레이션에 대한 인식 및 태도)

  • Lee, Youngho;Choi, Jongmyung;Yoon, Hyoseok;Kim, Sun Kyung
    • Journal of the Korea Convergence Society
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    • v.12 no.1
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    • pp.369-377
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    • 2021
  • Augmented reality smart-glass enables healthcare providers to use patient and their care related information without interference of workflow. In addition, augmented reality smart-glass simulation had advantages in improving competency via remote collaboration and real-time information sharing. This study investigated perception and attitude regarding augmented reality smart glass based healthcare simulation on three different groups of healthcare major students, computer major students, developers and faculties. Using convenience sampling method, data were obtained from 95 participants and statistical analysis were performed using SPSS 25.0. Developer and faculty group showed the highest scores, followed by healthcare major students. There was the high expectation on augmented reality smart-glass for skill acquisition and the high performance and big screen were essential features of device. The findings of this study revealed that differences between healthcare and computer major students exist and strategies to reduce those gaps are required to adopt augmented reality smart glass in healthcare settings.

Extended Adaptation Database Construction for Oriental Medicine Prescriptions Based on Academic Information (학술 정보 기반 한의학 처방을 위한 확장 적응증 데이터베이스 구축)

  • Lee, So-Min;Baek, Yeon-Hee;Song, Sang-Ho;CHRISTOPHER, RETITI DIOP EMANE;Han, Xuan-Zhong;Hong, Seong-Yeon;Kim, Ik-Su;Lim, Jong-Tea;Bok, Kyoung-Soo;TRAN, MINH NHAT;NGUYEN, QUYNH HOANG NGAN;Kim, So-Young;Kim, An-Na;Lee, Sang-Hun;Yoo, Jae-Soo
    • The Journal of the Korea Contents Association
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    • v.21 no.8
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    • pp.367-375
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    • 2021
  • The quality of medical care can be defined as four types such as effectiveness, efficiency, adequacy, and scientific-technical quality. For the management of scientific-technical aspects, medical institutions annually disseminate the latest knowledge in the form of conservative education. However, there is an obvious limit to the fact that the latest knowledge is distributed quickly enough to the clinical site with only one-time conservative education. If intelligent information processing technologies such as big data and artificial intelligence are applied to the medical field, they can overcome the limitations of having to conduct research with only a small amount of information. In this paper, we construct databases on which the existing medicine prescription adaptations can be extended. To do this, we collect, store, manage, and analyze information related to oriental medicine at domestic and abroad Journals. We design a processing and analysis technique for oriental medicine evidence research data for the construction of a database of oriental medicine prescription extended adaption. Results can be used as a basic content of evidence-based medicine prescription information in the oriental medicine-related decision support services.