• Title/Summary/Keyword: 통합적 환경관리 지침

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Directions for Legislative Improvement for the Creation and Operation of Ecological Parks (생태공원의 조성과 운영 내실화를 위한 법제적 개선 방향)

  • Kim, Ah-Yeon
    • Journal of the Korean Institute of Landscape Architecture
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    • v.52 no.1
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    • pp.71-86
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    • 2024
  • Despite the increasing importance of urban parks' ecological functions in dealing with the climate crisis, ecological parks are not clearly defined in Korea's legal system. Numerous ecological parks created nationwide cannot be systematically designated and managed due to various legal bases and varying management authorities. It is important to clarify the legal status of ecological parks in order to lead the ecological paradigm shift of urban parks and to improve the natural park system for a comprehensive and integrated approach to protect the national ecosystem. To this end, related laws were analyzed to identify problems and to draw directions for legislative improvement. Through the literature review of relevant laws, acts, and ordinances, six major directions for improvement were suggested based on the analysis of problems. First, the legal status of ecological parks in the administrative dichotomy of the current park system is ambiguous, and ecological parks should be clarified through the revision of park-related laws. Second, an ecological park can be defined as a sustainable park created and managed in an ecological manner, promoting the protection and restoration of the ecosystem, conservation, and promotion of biodiversity, and balancing nature observation, ecological learning, and leisure activities. Third, the role of the state and local governments should be systematically revised to lead to a new park planning and management model through new governance. Fourth, since the characteristics of ecological parks are affected by individual laws, the possibility of overlapping ecological parks for other uses should be allowed. Fifth, detailed guidelines and standard ordinances need to be enacted to meet the goals, principles, and facilities of ecological parks. Lastly, along with the revision of the laws, ordinances by local governments also need to be more concrete. This study, which tracks various legal realities related to ecological parks, can contribute to policymaking that can systematize the foundation for the creation of ecological parks to preserve nationwide ecosystems and provide citizens with opportunities to experience and learn about nature.

Implementation and Design of the Framework for Consolidated Transportation Model (공동 수배송 모델을 위한 프레임워크 설계 및 구축)

  • Lee, Myeong-Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.9 no.4
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    • pp.980-985
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    • 2008
  • The environment of IT is, currently, on its developing process to the period of web 2.0 and mashup which not only enable computer and internet to be utilized like the water or the air, but also be a new motivating force for its advance. One of the biggest changes of the industry that lies ahead is consolidated transportation. However, no party outstands as the leading party for nationwide improvement of logistics, nor does the right analysis and design for it. Therefore, successful nationwide logistics model is yet to exist. This study provides individual parties, which consider consolidated transportation model as their implementation and design of the framework, with instructions for logistics information system so that they could be competitive in the market. It also helps companies collect user requirements for logistics information system consolidated transportation, and utilize it for its development. Finally, the study provides a implementation and design of pilot system for consolidated transportation model.

A Study on Continuous Monitoring Reinforcement for Sales Audit Using Process Mining Under Big Data Environment (빅데이터 환경에서 프로세스 마이닝을 이용한 영업감사 상시 모니터링 강화에 대한 연구)

  • Yoo, Young-Seok;Park, Han-Gyu;Back, Seung-Hoon;Hong, Sung-Chan
    • Journal of Internet Computing and Services
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    • v.17 no.6
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    • pp.123-131
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    • 2016
  • Process mining in big data environment utilize a number of data were generated from the business process. It generates lots of knowledge and insights regarding implementation and improvement of the process through the event log of the company's enterprise resource planning (ERP) system. In recent years, various research activities engaged with the audit work of company organizations are trying actively by using the maximum strength of the mining process. However, domestic studies on applicable sales auditing system for the process mining are insufficient under big data environment. Therefore, we propose process-mining methods that can be optimally applied to online and traditional auditing system. In advance, we propose continuous monitoring information system that can early detect and prevent the risk under the big data environment by monitoring risk factors in the organizations of enterprise. The scope of the research of this paper is to design a pre-verification system for risk factor via practical examples in sales auditing. Furthermore, realizations of preventive audit, continuous monitoring for high risk, reduction of fraud, and timely action for violation of rules are enhanced by proposed sales auditing system. According to the simulation results, avoidance of financial risks, reduction of audit period, and improvement of audit quality are represented.

A Study on the Relationship between Enterprise RFID Capability and Strategic Supply Chain Capability and Firm Performance: Focusing on Logistics, Distribution and Supply Chain Enterprises in China (기업의 RFID 역량과 전략적 공급사슬역량 및 기업성과 간 관계에 관한 연구: 중국 내 물류, 유통, 공급망 기업을 중심으로)

  • Shang Meng;Yong Ho Shin;Chul Woo Lee
    • Information Systems Review
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    • v.20 no.2
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    • pp.87-110
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    • 2018
  • This study reviews previous studies about the effects of RFID capabilities on strategic supply chain competence and business performance in the Chinese context. This study introduces a new perspective that measures the degree to which RFID capability levels contribute to business performance. Such an assumption is based on the fact that companies build their own capabilities through RFID capabilities and that these capabilities provide a competitive advantage for enterprises. Data on all sorts of logistics, distribution, and manufacturing companies that introduced RFID system in China were collected for data analysis. This study analyzes the structural equation modeling using Smart-PLS 2.0 program. This study confirms that internal reliability, convergent validity, and discriminant validity are satisfied. The hypothesis test result on the relationship between RFID capacity and strategic supply chain competence and strategic supply chain competence and company results is partially adopted. This study aids in establishing a RFID system construction strategy to enhance supply chain competence by suggesting guidelines for the successful introduction of RFID system through identifying the causal relationship between RFID capacity and strategic supply chain competence. This study also suggests the influence of RFID competency on visibility, agility, flexibility, and collaborations.

A Research in Applying Big Data and Artificial Intelligence on Defense Metadata using Multi Repository Meta-Data Management (MRMM) (국방 빅데이터/인공지능 활성화를 위한 다중메타데이터 저장소 관리시스템(MRMM) 기술 연구)

  • Shin, Philip Wootaek;Lee, Jinhee;Kim, Jeongwoo;Shin, Dongsun;Lee, Youngsang;Hwang, Seung Ho
    • Journal of Internet Computing and Services
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    • v.21 no.1
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    • pp.169-178
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    • 2020
  • The reductions of troops/human resources, and improvement in combat power have made Korean Department of Defense actively adapt 4th Industrial Revolution technology (Artificial Intelligence, Big Data). The defense information system has been developed in various ways according to the task and the uniqueness of each military. In order to take full advantage of the 4th Industrial Revolution technology, it is necessary to improve the closed defense datamanagement system.However, the establishment and usage of data standards in all information systems for the utilization of defense big data and artificial intelligence has limitations due to security issues, business characteristics of each military, anddifficulty in standardizing large-scale systems. Based on the interworking requirements of each system, data sharing is limited through direct linkage through interoperability agreement between systems. In order to implement smart defense using the 4th Industrial Revolution technology, it is urgent to prepare a system that can share defense data and make good use of it. To technically support the defense, it is critical to develop Multi Repository Meta-Data Management (MRMM) that supports systematic standard management of defense data that manages enterprise standard and standard mapping for each system and promotes data interoperability through linkage between standards which obeys the Defense Interoperability Management Development Guidelines. We introduced MRMM, and implemented by using vocabulary similarity using machine learning and statistical approach. Based on MRMM, We expect to simplify the standardization integration of all military databases using artificial intelligence and bigdata. This will lead to huge reduction of defense budget while increasing combat power for implementing smart defense.

Development of a deep-learning based tunnel incident detection system on CCTVs (딥러닝 기반 터널 영상유고감지 시스템 개발 연구)

  • Shin, Hyu-Soung;Lee, Kyu-Beom;Yim, Min-Jin;Kim, Dong-Gyou
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.19 no.6
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    • pp.915-936
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    • 2017
  • In this study, current status of Korean hazard mitigation guideline for tunnel operation is summarized. It shows that requirement for CCTV installation has been gradually stricted and needs for tunnel incident detection system in conjunction with the CCTV in tunnels have been highly increased. Despite of this, it is noticed that mathematical algorithm based incident detection system, which are commonly applied in current tunnel operation, show very low detectable rates by less than 50%. The putative major reasons seem to be (1) very weak intensity of illumination (2) dust in tunnel (3) low installation height of CCTV to about 3.5 m, etc. Therefore, an attempt in this study is made to develop an deep-learning based tunnel incident detection system, which is relatively insensitive to very poor visibility conditions. Its theoretical background is given and validating investigation are undertaken focused on the moving vehicles and person out of vehicle in tunnel, which are the official major objects to be detected. Two scenarios are set up: (1) training and prediction in the same tunnel (2) training in a tunnel and prediction in the other tunnel. From the both cases, targeted object detection in prediction mode are achieved to detectable rate to higher than 80% in case of similar time period between training and prediction but it shows a bit low detectable rate to 40% when the prediction times are far from the training time without further training taking place. However, it is believed that the AI based system would be enhanced in its predictability automatically as further training are followed with accumulated CCTV BigData without any revision or calibration of the incident detection system.