• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2001년도 추계학술발표논문집 (하)
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• pp.1355-1358
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• 2001

IP Multicast can efficiently provide enormous bandwidth savings by enabling sources to send a single copy of a message to multiple recipients who explicitly want to receive the information. But due to the complexity of IP multicast and its fundamental differences from unicast, there are not very many tools available fer monitoring and debugging multicast networks, and only a few experts understand the tools that do exist. This thesis proposes a Multicast Routing Debugger (MRD) system that monitor the status of a multicast network. This system is aimed to multicast-related faults detection. In thesis, first, we define the set of information that should be monitored. Second, the method is developed to take out such information from multicast routers. Third, MRD system is prototyped to collect, process information from heterogeneous routers on a multicast network and to display the various status of the network comprehensively. The prototype of MRD system is implemented and deployed. We perform experiments with several scenarios. Experimental results show we can detect various problems as information that we define is monitored. The MRD system is simple to use, web-based and intuitive tool that can monitor the status of a specific multicast network.

• 대한의용생체공학회:의공학회지
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• 제38권2호
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• pp.82-88
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• 2017

Enlargement of the lateral ventricles have been identified as a surrogate marker of neurological disorders. Quantitative measure of the lateral ventricle from MRI would enable earlier and more accurate clinical diagnosis in monitoring disease progression. Even though it requires an automated or semi-automated segmentation method for objective quantification, it is difficult to define lateral ventricles due to insufficient contrast and brightness of structural imaging. In this study, we proposed a fully automated lateral ventricle segmentation method based on a graph cuts algorithm combined with atlas-based segmentation and connected component labeling. Initially, initial seeds for graph cuts were defined by atlas-based segmentation (ATS). They were adjusted by partial volume images in order to provide accurate a priori information on graph cuts. A graph cuts algorithm is to finds a global minimum of energy with minimum cut/maximum flow algorithm function on graph. In addition, connected component labeling used to remove false ventricle regions. The proposed method was validated with the well-known tools using the dice similarity index, recall and precision values. The proposed method was significantly higher dice similarity index ($0.860{\pm}0.036$, p < 0.001) and recall ($0.833{\pm}0.037$, p < 0.001) compared with other tools. Therefore, the proposed method yielded a robust and reliable segmentation result.

• Earthquakes and Structures
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• 제7권4호
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• pp.449-462
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• 2014

Seismically induced structural damage, as well as any damage caused by a natural catastrophic event, covers a wide area. This suggests to supervise the event consequences by vision tools. This paper reports the evolution from the results obtained by the project RADATT (RApid Damage Assessment Telematics Tool) funded by the European Commission within FP4. The aim was to supply a rapid and reliable damage detector/estimator for an area where a catastrophic event had occurred. Here, a general open-source methodology for the detection and the estimation of the damage caused by natural catastrophes is developed. The suitable available hazard and vulnerability data and satellite pictures covering the area of interest represent the required bits of information for updated telematics tools able to manage it. As a result the global damage is detected by the simple use of open source software. A case-study to a highly dense agglomerate of buildings is discussed in order to provide the main details of the proposed methodology.

• 대한인간공학회지
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• 제31권6호
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• pp.793-800
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• 2012

Objective: This study investigated the problems that could be faced with when engineers try to improve the affective quality using the DMAIC model. Background: Affective quality is considered one of the most influential factors for the competitive power of consumer products and many engineers make effort to improve the affective quality. Since the Six Sigma process is effective and wide-used method for quality improvement, it can also be used to improve the affective quality. However six sigma tools cannot be directly used for affective quality because of the subjective and qualitative characteristics of the human affection. Method: Investigate the goals, processes and key factors of DMAIC model and find the difficulties to use six sigma tools for the affective quality. Results: Most of the problems arise from measuring and quantifying the human affective response level and understanding the relationship between the human affective factors. Conclusion: Both the protocol for measuring human affection and the monitoring system to find the affective response change for the product or service are required. Application: The results of this study could be helpful for the engineers not specialized in ergonomics to improve the affective quality in systematic approach.

• 한국컴퓨터정보학회논문지
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• 제21권8호
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• pp.95-103
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• 2016

Food habit forming the basis for a lifetime of food and nutrient intake is established in early childhood and has an effect to the child's growth, sociality, and obesity. A variety of nutrition screening tools exists for assessing the health and nutrition status of children such as the Growth Curve, for determining if growth is appropriate. Body mass index(BMI) as a more reliable index of overweight to prevent childhood obesity, and Nutrition Quotient(NQ) and eating behaviors questionnaire for young children and parents to estimate their nutrient intake adequate or not. Such tools are mainly used by health practitioners, such as doctor and dietitian to provide nutrition intervention services to children at risk, especially and are not easy to use for general parents, who need assessment at any time and at any place. We propose Growth Assistance System for infants and children, which is possible to assess their physical condition, nutritional status, and eating behavior integrated. To be convenient and portable, it is implemented over the smartphone as an application. The system offers the growth charts, the BMI curves, NQ and eating behavior questionnaire to take a monitoring and the functionalities operate well. We hereby expect this system support the normal growth and development of infants and young children. And also support for the health practitioner (dietitians and nutritionists) to take a role in providing nutrition counseling and education to children needing nutrition services.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 추계학술발표대회
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• pp.39-42
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• 2018

Log analysis and monitoring have a significant importance in most of the systems. Log management has core importance in applications like distributed applications, cloud based applications, and applications designed for big data. These applications produce a large number of log files which contain essential information. This information can be used for log analytics to understand the relevant patterns from varying log data. However, they need some tools for the purpose of parsing, storing, and visualizing log informations. "Elasticsearch, Logstash, and Kibana"(ELK Stack) is one of the most popular analyzing tools for log management. For the ingestion of log files configuration files have a key importance, as they cover all the services needed to input, process, and output the log files. However, creating configuration files is sometimes very complicated and time consuming in many applications as it requires domain expertise and manual creation. In this paper, an auto configuration module for Logstash is proposed which aims to auto generate the configuration files for Logstash. The primary purpose of this paper is to provide a mechanism, which can be used to auto generate the configuration files for corresponding log files in less time. The proposed module aims to provide an overall efficiency in the log management system.

• Nuclear Engineering and Technology
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• 제52권12호
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• pp.2687-2698
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• 2020

Most of the machine learning-based intrusion detection tools developed for Industrial Control Systems (ICS) are trained on network packet captures, and they rely on monitoring network layer traffic alone for intrusion detection. This approach produces weak intrusion detection systems, as ICS cyber-attacks have a real and significant impact on the process variables. A limited number of researchers consider integrating process measurements. However, in complex systems, process variable changes could result from different combinations of abnormal occurrences. This paper examines recent advances in intrusion detection algorithms, their limitations, challenges and the status of their application in critical infrastructures. We also introduce the discussion on the similarities and conflicts observed in the development of machine learning tools and techniques for fault diagnosis and cybersecurity in the protection of complex systems and the need to establish a clear difference between them. As a case study, we discuss special characteristics in nuclear power control systems and the factors that constraint the direct integration of security algorithms. Moreover, we discuss data reliability issues and present references and direct URL to recent open-source data repositories to aid researchers in developing data-driven ICS intrusion detection systems.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 추계학술대회
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• pp.264-266
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• 2014

현재 시스템 구조는 기존 단순 구조에서 복잡하고 다양한 구조로 빠르게 변화되고 있으며, 특히 새로운 사이버 위협 등으로 시스템 리스크는 점점 증대되고 있다. 이러한 시스템 리스크를 최소화하기 위하여 각종 시스템 모니터링 및 분석 툴들이 많이 출시되고 있지만 자동화 툴에 의존하기에는 한계가 있다. 따라서 본 연구에서는 시스템 리스크를 최소화 하기 위해 기존 시스템 관리방식의 틀에서 벗어나 변화하는 새로운 환경에 맞는 효율적 시스템 관리를 위한 시스템 관리자의 역할에 대해 제시하고자 한다.

• International Journal of Contents
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• 제11권2호
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• pp.37-49
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• 2015

Sensors, equipment, ICT facilities and their corresponding software have a relatively short lifetime relative to that of constructional structure, so these devices have to be continuously fixed or exchanged during maintenance and management. Furthermore, software or analysis tools should be periodically upgraded according to advances in ICT and analysis technology. Conventional monitoring systems have serious problems in that it is difficult for site engineers to modify or upgrade hardware and analysis algorithms. Moreover, we depend on the original system developer when we want to modify or upgrade inner program structures. In this paper, we propose a novel design for integrated maintenance and management of a monitoring system by applying the mobile cloud concept. The system is intended for use in disaster prevention of constructional structures, including bridges, tunnels, and in traditional buildings in a local heritage village, we analyze the status of these structures over a long term or a short-term period as well as in disaster situations. Data are collected over a mobile cloud and future expectations are analyzed according to probabilistic and statistical techniques. We implement our integrated monitoring system to solve the existing problems mentioned above. The final goal of this study is to design and implement a monitoring system for more than 10,000 structures spread within Korea. Furthermore, we can specifically apply the monitoring system presented here to a bridge made from timber in Asan Oeam Village and a traditional house in Andong Hahoe Village to monitor for possible disasters. The entire system design and implementation can be developed on the LinkSaaS platform and the monitoring services can also be implemented on the platform. We prove that the proposed system has good performance by performing a TTA authentication test, web accommodation test, and operation test using emulated data.

• 한국가스학회지
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• 제2권3호
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• pp.54-59
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• 1998

가스 산업계에서 분산 제어 시스템 (DCS)이나 공정 정보 시스템 (PIS)이 널리 도입됨에 따라 데이터를 기반으로 하는 공정 이상 감시 기술이 많은 관심을 끌고 있다. 하지만 회분식 공정의 경우는 공정의 강한 비선형성으로 인해 이러한 기술들이 효과적으로 이용되지 못했다. Multiway principal component analysis (MPCA)가 개발됨에 따라 이러한 문제점을 해결하면서 산업계에 널리 이용되고 있는데 이 또한 다양한 정보를 해석하기 위해서는 상당한 통계적 지식이 요구되고 이 결과 운전원들이 이용하기가 어렵다는 단점이 있다. 이를 해결하기 위해서 본 논문에서는 운전원들이 쉽게 이해하고 활용할 수 있는 도구들을 제-공하는 회분식 가스 제조공정용 실시간 감시 시스템을 소개한다. 본 시스템은 데이터의 수집부터 이상의 원인을 파악하는 진단에 이르기까지 감시와 진단에 필요한 기능들을 모두 제공하는 총괄적인 시스템으로 개발된 시스템은 회분식 가스제조, 정밀화학제품, 의약품 등의 회분식 고부가가치 제품생산에 널리 이용될 것으로 보인다. 개발된 시스템은 산업체의 전형적인 회분식 반응기 감시를 위한 감시 시스템을 구축하여 봄으로써 검증하였으며 검증 결과 감시와 진단에 매우 효과적이라는 것을 알 수 있었다.