• Title/Summary/Keyword: Network Convergence

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Social Capital and Cross-Cultural Effect of Korean Wave (Hallyu): Genre-specific Hallyu, Social Trust, and Network Heterogeneity in Europe (한류의 사회자본 효과와 문화간 커뮤니케이션 영향: 유럽 사회 한류 문화소비와 사회 연계망의 관계를 중심으로)

  • Na, Eunkyung
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.3
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    • pp.367-375
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    • 2022
  • Given the growing changes in media environment and cultural consumption, globally popular contents of Korean Wave(Hallyu) has also been transformed in its forms and genres. Moreover, extant research on Hallyu has focused on any single respective genre, mostly on East-Asian countries, or studied from Korea-centered perspective. This study examined the social capital effect of Korean Wave in users' own counties, especially in non-English European societies. Survey analysis results reveal that both narrative and non-narrative contents in Hallyu had negative impact on social trust and trust toward people of their own country, whereas positive effect on trust toward Koreans. In contrast, K-pop Hallyu showed positive effect on all types of social trust toward their own country and Koreans, as well as on social participation and bridging/bonding social networks.

Current State of Animation Industry and Technology Trends - Focusing on Artificial Intelligence and Real-Time Rendering (애니메이션 산업 현황과 기술 동향 - 인공지능과 실시간 렌더링 중심으로)

  • Jibong Jeon
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.821-830
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    • 2023
  • The advancement of Internet network technology has triggered the emergence of new OTT video content platforms, increasing demand for content and altering consumption patterns. This trend is bringing positive changes to the South Korean animation industry, where diverse and high-quality animation content is becoming increasingly important. As investment in technology grows, video production technology continues to advance. Specifically, 3D animation and VFX production technologies are enabling effects that were previously unthinkable, offering detailed and realistic graphics. The Fourth Industrial Revolution is providing new opportunities for this technological growth. The rise of Artificial Intelligence (AI) is automating repetitive tasks, thereby enhancing production efficiency and enabling innovations that go beyond traditional production methods. Cutting-edge technologies like 3D animation and VFX are being continually researched and are expected to be more actively integrated into the production process. Digital technology is also expanding the creative horizons for artists. The future of AI and advanced technologies holds boundless potential, and there is growing anticipation for how these will elevate the video content industry to new heights.

Efforts against Cybersecurity Attack of Space Systems

  • Jin-Keun Hong
    • Journal of Positioning, Navigation, and Timing
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    • v.12 no.4
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    • pp.437-445
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    • 2023
  • A space system refers to a network of sensors, ground systems, and space-craft operating in space. The security of space systems relies on information systems and networks that support the design, launch, and operation of space missions. Characteristics of space operations, including command and control (C2) between space-craft (including satellites) and ground communication, also depend on wireless frequency and communication channels. Attackers can potentially engage in malicious activities such as destruction, disruption, and degradation of systems, networks, communication channels, and space operations. These malicious cyber activities include sensor spoofing, system damage, denial of service attacks, jamming of unauthorized commands, and injection of malicious code. Such activities ultimately lead to a decrease in the lifespan and functionality of space systems, and may result in damage to space-craft and, lead to loss of control. The Cybersecurity Adversarial Tactics, Techniques, and Common Knowledge (ATT&CK) matrix, proposed by Massachusetts Institute of Technology Research and Engineering (MITRE), consists of the following stages: Reconnaissance, Resource Development, Initial Access, Execution, Persistence, Privilege Escalation, Defense Evasion, Credential Access, Discovery, Lateral Movement, Collection, Command & Control, Exfiltration, and Impact. This paper identifies cybersecurity activities in space systems and satellite navigation systems through the National Institute of Standards and Technology (NIST)'s standard documents, former U.S. President Trump's executive orders, and presents risk management activities. This paper also explores cybersecurity's tactics attack techniques within the context of space systems (space-craft) by referencing the Sparta ATT&CK Matrix. In this paper, security threats in space systems analyzed, focusing on the cybersecurity attack tactics, techniques, and countermeasures of space-craft presented by Space Attack Research and Tactic Analysis (SPARTA). Through this study, cybersecurity attack tactics, techniques, and countermeasures existing in space-craft are identified, and an understanding of the direction of application in the design and implementation of safe small satellites is provided.

Dual-mode diagnosis system for water quality and corrosion in pipe using convolutional neural networks (CNN) and ultrasound (합성곱 신경망과 초음파 기반 상수도관 수질 및 부식 분석용 이중모드 진단 시스템)

  • So Yeon Moon;Hyeon-Ju Jeon;Yeongho Sung;Min-Seo Kim;Daehun Kim;Jaeyeop Choi;Junghwan Oh;O-Joun Lee;Hae Gyun Lim
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.685-686
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    • 2023
  • 상수도관의 수질 및 부식도 검사에는 파이프에 손상을 입히지 않고 지속적인 방법이 필요하다. 초음파는 이를 만족하면서 상태를 확인할 수 있고 주파수가 높을수록 해상도가 좋아져 정밀한 측정이 가능하다는 장점이 있다. 이러한 특성을 이용해 상수도관 모니터링 시스템으로 초음파 기반의 Scanning Acoustic Microscopy(SAM)과 Convolutional Neural Network(CNN)을 사용하는 새로운 방법을 제안한다. 기존의 Non-Destructive Testing(NDT)방식의 단점을 보완하면서 더 높은 해상도로 상수도관을 점검하는 방식으로, SAM 을 이용하여 부식으로 인한 파이프 두께 변화와 부유물의 여부 및 수질을 동시에 감지하고 얻은 데이터를 CNN 으로 분석했다. CNN 의 높은 정확도 결과로 이 시스템의 파이프 부식도 및 수질 모니터링에 대한 적합성을 보여주었다.

AI Crime Prediction Modeling Based on Judgment and the 8 Principles (판결문과 8하원칙에 기반한 인공지능 범죄 예측 모델링)

  • Hye-sung Jung;Eun-bi Cho;Jeong-hyeon Chang
    • Journal of Internet Computing and Services
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    • v.24 no.6
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    • pp.99-105
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    • 2023
  • In the 4th industrial revolution, the field of criminal justice is paying attention to Legaltech using artificial intelligence to provide efficient legal services. This paper attempted to create a crime prediction model that can apply Recurrent Neural Network(RNN) to increase the potential for using legal technology in the domestic criminal justice field. To this end, the crime process was divided into pre, during, and post stages based on the criminal facts described in the judgment, utilizing crime script analysis techniques. In addition, at each time point, the method and evidence of crime were classified into objects, actions, and environments based on the sentence composition elements and the 8 principles of investigation. The case summary analysis framework derived from this study can contribute to establishing situational crime prevention strategies because it is easy to identify typical patterns of specific crime methods. Furthermore, the results of this study can be used as a useful reference for research on generating crime situation prediction data based on RNN models in future follow-up studies.

Artificial Neural Network-based Thermal Environment Prediction Model for Energy Saving of Data Center Cooling Systems (데이터센터 냉각 시스템의 에너지 절약을 위한 인공신경망 기반 열환경 예측 모델)

  • Chae-Young Lim;Chae-Eun Yeo;Seong-Yool Ahn;Sang-Hyun Lee
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.6
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    • pp.883-888
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    • 2023
  • Since data centers are places that provide IT services 24 hours a day, 365 days a year, data center power consumption is expected to increase to approximately 10% by 2030, and the introduction of high-density IT equipment will gradually increase. In order to ensure the stable operation of IT equipment, various types of research are required to conserve energy in cooling and improve energy management. This study proposes the following process for energy saving in data centers. We conducted CFD modeling of the data center, proposed an artificial intelligence-based thermal environment prediction model, compared actual measured data, the predicted model, and the CFD results, and finally evaluated the data center's thermal management performance. It can be seen that the predicted values of RCI, RTI, and PUE are also similar according to the normalization used in the normalization method. Therefore, it is judged that the algorithm proposed in this study can be applied and provided as a thermal environment prediction model applied to data centers.

Accident Detection System for Construction Sites Using Multiple Cameras and Object Detection (다중 카메라와 객체 탐지를 활용한 건설 현장 사고 감지 시스템)

  • Min hyung Kim;Min sung Kam;Ho sung Ryu;Jun hyeok Park;Min soo Jeon;Hyeong woo Choi;Jun-Ki Min
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.605-611
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    • 2023
  • Accidents at construction sites have a very high rate of fatalities due to the nature of being prone to severe injury patients. In order to reduce the mortality rate of severely injury patients, quick response is required, and some systems that detect accidents using AI technology and cameras have been devised to respond quickly to accidents. However, since existing accident detection systems use only a single camera, there are blind spots, Thus, they cannot detect all accidents at a construction site. Therefore, in this paper, we present the system that minimizes the detection blind spot by using multiple cameras. Our implemented system extracts feature points from the images of multiple cameras with the YOLO-pose library, and inputs the extracted feature points to a Long Short Term Memory-based recurrent neural network in order to detect accidents. In our experimental result, we confirme that the proposed system shows high accuracy while minimizing detection blind spots by using multiple cameras.

Study of Policy on Seowon's Preservation·Support : Focusing on Big Data Analysis on Laws (한국 서원의 보존·지원 정책에 관한 연구 : 법률에 대한 빅데이터 분석을 중심으로)

  • Bang, Mee Young
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.875-883
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    • 2023
  • In Korea, the number of preservation and management entities to connect the traditional cultural heritage to next generations is rapidly decreasing. Building an infrastructure to pass on traditional cultural heritage to the next generation and to pay attention to the preservation and management of the next generation is important including the 'Seowon', a World Cultural Heritage listed by UNESCO. This study is based on the laws that regulates the preservation and support of traditional cultural assets and 'Seowon, through Big Data analysis techniques. The main keywords in each law were extracted, schematized, and a mutual Word Network was constructed and policy advice was derived. As policy advice, it is necessary to establish and implement policies to nurture and support businesses specialized in the region for the preservation·utilization, preservation·management and preservation·support of Seowons.

A Case Study on the Disaster Management of the Private Sector in Japan (일본의 민간협력형 도서관재난관리 사례연구)

  • Youn You-Ra;Lee Eun-Ju
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.951-956
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    • 2023
  • In the current situation where systematic and active disaster management is becoming more important, domestic libraries do not have their own disaster management plans or support systems. In order to improve these problems, this study looked at overseas cases. Among them, we looked at Japan, where related cases and research are actively underway due to its exposure to various geopolitical disasters. In particular, we focused on cases of public-private cooperation established after the Great East Japan Earthquake. Association's Library Disaster Response Committee and saveMALK, a voluntary network of experts. The Library Disaster Response Committee played a central role in organizing donations and volunteer activities, and saveMALK played a role in collecting and sharing information by forming a collective intelligence among relevant experts. This analysis of the Japanese case has positive implications for building collaborative disaster management system.

Combined Treatment With TGF-β1, Retinoic Acid, and Lactoferrin Robustly Generate Inducible Tregs (iTregs) Against High Affinity Ligand

  • Young-Saeng Jang;Sun-Hee Park;Seung-Goo Kang;Jung-Shin Lee;Hyun-Jeong Ko;Pyeung-Hyeun Kim
    • IMMUNE NETWORK
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    • v.23 no.5
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    • pp.37.1-37.11
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    • 2023
  • Forkhead box P3-positive (Foxp3+)-inducible Tregs (iTregs) are readily generated by TGF-β1 at low TCR signaling intensity. TGF-β1-mediated Foxp3 expression is further enhanced by retinoic acid (RA) and lactoferrin (LF). However, the intensity of TCR signaling required for induction of Foxp3 expression by TGF-β1 in combination with RA and LF is unknown. Here, we found that either RA or LF alone decreased TGF-β1-mediated Foxp3 expression at low TCR signaling intensity. In contrast, at high TCR signaling intensity, the addition of either RA or LF strongly increased TGF-β1-mediated Foxp3 expression. Moreover, decreased CD28 stimulation was more favorable for TGF-β1/LF-mediated Foxp3 expression. Lastly, we found that at high signaling intensities of both TCR and CD28, combined treatment with TGF-β1, RA, and LF induced robust expression of Foxp3, in parallel with powerful suppressive activity against responder T cell proliferation. Our findings that TGFβ/RA/LF strongly generate high affinity Ag-specific iTreg population would be useful for the control of unwanted hypersensitive immune reactions such as various autoimmune diseases.