• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권8호
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• pp.1890-1910
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• 2013

Routing overlay offers an ideal methodology to improve the end-to-end communication performance by deriving a backup path for any node pair. This paper focuses on a challenging issue of selecting a proper backup path to bypass the failures on the default path with high probability for any node pair. For existing backup path selection approaches, our trace-driven evaluation results demonstrate that the backup and default paths for any node pair overlap with high probability and hence usually fail simultaneously. Consequently, such approaches fail to derive a robust backup path that can take over in the presence of failure on the default path. In this paper, we propose a three-phase RBPS approach to identify a proper and robust backup path. It utilizes the traceroute probing approach to obtain the fine-grained topology information, and systematically employs the grid quorum system and the Bloom filter to reduce the resulting communication overhead. Two criteria, delay and fault-tolerant ability on average, of the backup path are proposed to evaluate the performance of our RBPS approach. Extensive trace-driven evaluations show that the fault-tolerant ability of the backup path can be improved by about 60%, while the delay gain ratio concentrated at 14% after replacing existing approaches with ours. Consequently, our approach can derive a more robust and available backup path for any node pair than existing approaches. This is more important than finding a backup path with the lowest delay compared to the default path for any node pair.

• 시스템엔지니어링학술지
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• 제11권1호
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• pp.81-93
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• 2015

Steam Reforming H2 Generation (SRH2G) System is a chemical process to produce hydrogen through steam reforming of hydrocarbon. Largely speaking, there are two types of materials for the SRH2G: 1) Oil and coal, and 2)Natural Gas such as shale gas. From the perspective of cost, quality (purity), and environmental burden (pollution), the latter is much more desirable than the former. For this reason, research on SRH2G using natural gas is actively carried out, and implemented and operated in the various industry. In this paper, we develop a natural gas based SRH2G system via systems engineering approach. Specifically, we first derived stakeholder requirements, followed by systems requirements and finally system architecture via a tailored SE process for plant (called Plant Systems Engineering (PSE) process) based on ISO/IEC 15288. The developed method was applied to iron and steel plant as a case study. Through the case study, by the SE approach, we were convinced that a successful system satisfying stakeholders' requirements within the given constraints can be developed, verified and validated.

• 한국농공학회논문집
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• 제64권1호
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• pp.15-26
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• 2022

3D open-field farm model developed from UAV (Unmanned Aerial Vehicle) data could make crop monitoring easier, also could be an important dataset for various fields like remote sensing or precision agriculture. It is essential to separate crops from the non-crop area because labeling in a manual way is extremely laborious and not appropriate for continuous monitoring. We, therefore, made a 3D open-field farm model based on UAV images and developed a crop segmentation model using a supervised machine learning algorithm. We compared performances from various models using different data features like color or geographic coordinates, and two supervised learning algorithms which are SVM (Support Vector Machine) and KNN (K-Nearest Neighbors). The best approach was trained with 2-dimensional data, ExGR (Excess of Green minus Excess of Red) and z coordinate value, using KNN algorithm, whose accuracy, precision, recall, F1 score was 97.85, 96.51, 88.54, 92.35% respectively. Also, we compared our model performance with similar previous work. Our approach showed slightly better accuracy, and it detected the actual crop better than the previous approach, while it also classified actual non-crop points (e.g. weeds) as crops.

• 전기학회논문지
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• 제67권11호
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• pp.1549-1554
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• 2018

Recently the design of railway systems have been performed, based on the analysis of operational conditions and service targets, it is to optimize the effectiveness and efficiency of system operation. Many RAMS requirements have been developed to transform operation conditions into system design characteristics. However, our railway industry has not actived the application of RAMS into system design performance. According to short of RAMS application, many technologies that have been developed are not only applied the existing systems that is operating, but also have not succeed to apply for new systems. In order to design the effective and efficient railway systems that are optimized to operation conditions and service targets, a systems approach and RAMS management are necessary in railway development, operation and maintenance. Therefore, in this study, the RAMS performance requirement design methods are discussed. the allocation methods from system level to each devices of subsystems.

• 시스템엔지니어링학술지
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• 제11권1호
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• pp.55-65
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• 2015

In steel making plant, sampling system for raw material such as iron ore, limestone is necessary for quality control purpose. For the sake of efficiency and productivity, automation of the sampling system is highly desirable. From technical standpoint, the development of the automated system requires multi-disciplinary domain knowledge such as mechanical engineering, industrial engineering, information technology and computer engineering. Up to present time, the development has been mainly carried out by a single domain expert with project manager. The automated system developed in this way caused problems in the final system. This paper suggests a systems engineering approach to the development of automation for raw material sampling plant via a tailored process called Plant Systems Engineering (PSE) Process based on ISO/IEC 15288. Through the PSE process, we could derive right requirements and architecture of the Systems Of Interest (SOI), and we were convinced that the PSE Process can be applied to many other Plant Systems.

• 한국산업정보학회논문지
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• 제22권6호
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• pp.61-69
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• 2017

기업들은 ERP 시스템 도입 후에도 기존 시스템을 결합하여 운용하거나 새로운 시스템을 도입하기도 하며 각 기업의 ERP 시스템들이 연결, 통합되기도 한다. 이와 같은 이유로 ERP 출현과 함께 보다 강력하고 편리한 데이터 입력 기술에 대한 필요성이 점차 증가해왔다. 본 연구에서는 SAP R/3 시스템에서 제공하고 있는 인터페이스 기술과 함께 새로이 VBA기술을 사용하여 SAP R/3 시스템의 새로운 데이터 입력 인터페이스를 설계 및 구현하는 방안을 제시하였다. 이 방안의 장점은 사용자 관점에서 시스템 사용에 대한 거부감을 줄일 수 있으며 보다 편리한 데이터 입력과 출력으로 업무 효율성을 높일 수 있는 것으로 나타났다.

• 대한안전경영과학회지
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• 제16권4호
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• pp.11-19
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• 2014

Modern systems development becomes more and more complicated due to the need on the ever-increasing capability of the systems. In addition to the complexity issue, safety concern is also increasing since the malfunctions of the systems under development may result in the accidents in both the test and evaluation phase and the operation phase. Those accidents can cause disastrous damages if explosiveness gets involved therein such as in weapon systems development. The subject of this paper is on how to incorporate safety requirements in the design of safety-critical systems. As an approach, a useful system structure using the method of design structure matrix (DSM) is studied while reflecting the need on systems safety. Specifically, the effects of system components failure are analyzed and numerically modeled first. Also, the system components are identified and their interfaces are represented using a component DSM. Combining the results of the failure analysis and the component DSM leads to a modified DSM. By rearranging the resultant DSM, a modular structure is derived with safety requirements incorporated. As a case study, application of the approach is also discussed in the development of a military UAV plane.

• International Journal of Control, Automation, and Systems
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• 제3권4호
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• pp.509-523
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• 2005

We are developing a novel framework, PRIDE (PRediction In Dynamic Environments), to perform moving object prediction (MOP) for autonomous ground vehicles. The underlying concept is based upon a multi-resolutional, hierarchical approach which incorporates multiple prediction algorithms into a single, unifying framework. The lower levels of the framework utilize estimation-theoretic short-term predictions while the upper levels utilize a probabilistic prediction approach based on situation recognition with an underlying cost model. The estimation-theoretic short-term prediction is via an extended Kalman filter-based algorithm using sensor data to predict the future location of moving objects with an associated confidence measure. The proposed estimation-theoretic approach does not incorporate a priori knowledge such as road networks and traffic signage and assumes uninfluenced constant trajectory and is thus suited for short-term prediction in both on-road and off-road driving. In this article, we analyze the complementary role played by vehicle kinematic models in such short-term prediction of moving objects. In particular, the importance of vehicle process models and their effect on predicting the positions and orientations of moving objects for autonomous ground vehicle navigation are examined. We present results using field data obtained from different autonomous ground vehicles operating in outdoor environments.

• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.928-938
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• 2008

This study presents an approach for approximation an unknown function from a numerical data set based on the synthesis of a neuro-fuzzy model. An adaptive input data space parting method, which is used for building hyperbox-shaped clusters in the input data space, is proposed. Each data cluster is implemented here as a fuzzy set using a membership function MF with a hyperbox core that is constructed from a min vertex and a max vertex. The focus of interest in proposed approach is to increase degree of fit between characteristics of the given numerical data set and the established fuzzy sets used to approximate it. A new cutting procedure, named NCP, is proposed. The NCP is an adaptive cutting procedure using a pure function $\Psi$ and a penalty function $\tau$ for direction the input data space parting process. New algorithms named CSHL, HLM1 and HLM2 are presented. The first new algorithm, CSHL, built based on the cutting procedure NCP, is used to create hyperbox-shaped data clusters. The second and the third algorithm are used to establish adaptive neuro- fuzzy inference systems. A series of numerical experiments are performed to assess the efficiency of the proposed approach.

• International Journal of CAD/CAM
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• 제5권1호
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• pp.1-10
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• 2005

A new approach based on vector field clustering for tool path optimization of 5-axis CNC machining is presented in this paper. The strategy of the approach is to produce an efficient tool path with respect to the optimal cutting direction vector field. The optimal cutting direction maximizes the machining strip width. We use the normalized cut clustering technique to partition the vector field into clusters. The spiral and the zigzag patterns are then applied to generate tool path on the clusters. The iso-scallop method is used for calculating the tool path. Finally, our numerical examples and real cutting experiment show that the tool path generated by the proposed method is more efficient than the tool path generated by the traditional iso-parametric method.