• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 제14회 신호처리 합동 학술대회 논문집
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• pp.283-286
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• 2001

In this paper, we present a robust region segmentation method based on the watershed transformation of a pseudo-distance map (PDM). A usual approach for the segmentation of a gray-scale image with the watershed algorithm is to apply it to a gradient magnitude image or the Euclidean distance map (EDM) of an edge image. However, it is well known that this approach suffers from the oversegmentation of the given image due to noisy gradients or spurious edges caused by a thresholding operation. In this paper we show thor applying the watershed algorithm to the EDM, which is a regularized version of the EDM and is directly computed form the edgestrength function (ESF) of the input image, significantly reduces the oversegmentation, and the final segmentation results obtained by a simple region-merging process are more reliable and less noisy than those of the gradient-or EDM-based methods. We also propose a simple and efficient region-merging criterion considering both boundary strengths and inner intensities of regions to be merged. The robustness of our method is proven by testing it with a variety of synthetic and real images.

• 한국공간정보시스템학회 논문지
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• 제11권2호
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• pp.45-53
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• 2009

The fast progress on multimedia data acquisition technologies has enabled collecting vast amount of videos in real time. Although the amount of information gathered from these videos could be high in terms of quantity and quality, the use of the collected data is very limited typically by human-centric monitoring systems. In this paper, we propose a framework for analyzing long traffic video using series of content-based analyses tools. Our framework suggests a method to integrate theses analyses tools to extract highly informative features specific to a traffic video analysis. Our analytical framework provides (1) re-sampling tools for efficient and precise analysis, (2) foreground extraction methods for unbiased traffic flow analysis, (3) frame property analyses tools using variety of frame characteristics including brightness, entropy, Harris corners, and variance of traffic flow, and (4) a visualization tool that summarizes the entire video sequence and automatically highlight a collection of frames based on some metrics defined by semi-automated or fully automated techniques. Based on the proposed framework, we developed an automated traffic flow analysis system, and in our experiments, we show results from two example traffic videos taken from different monitoring angles.

• Journal of Computing Science and Engineering
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• 제9권3호
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• pp.155-162
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• 2015

The last decade has seen a rapid growth in the use of mobile devices all over the world. With an increasing use of mobile devices, mobile applications are becoming more diverse and complex, demanding more computational resources. However, mobile devices are typically resource-limited (i.e., a slower-speed CPU, a smaller memory) due to a variety of reasons. Mobile users will be capable of running applications with heavy computation if they can offload some of their computations to other places, such as a desktop or server machines. However, mobile users are typically subject to dynamically changing network environments, particularly, due to user mobility. This makes it hard to choose good offloading decisions in mobile environments. In general, users' mobility can provide some hints for upcoming changes to network environments. Motivated by this, we propose a mobility model of each individual user taking advantage of the regularity of his/her mobility pattern, and develop an offloading decision-making technique based on the mobility model. We evaluate our technique through trace-based simulation with real log data traces from 14 Android users. Our evaluation results show that the proposed technique can help boost the performance of mobile devices in terms of response time and energy consumption, when users are highly mobile.

• 대한임베디드공학회논문지
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• 제10권1호
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• pp.13-23
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• 2015

Recently, a few image-processing based mobile urine testers have actively been studied since the urine-analysis result can be available to the user in real time immediately after the test is done. However, the accuracy of test result can be severely degraded due to variable illumination environments and a variety of manners to capture the image with a camera embedded in the smartphone according to different users. This paper proposes the Check4Urine system, a novel smartphone-based portable urine-analysis tester and provides three techniques to improve such a performance degradation problem robust to various test environments and disturbances, which are the compensation algorithm to correct the varying illumination effect, an urine strip detection algorithm robust to edge loss of the object image, and the color decision algorithm based on the pre-processed reference table. Experimental results show that the proposed Check4Urine system increases the accuracy of urine-analysis by 20-50% at various test conditions, compared with the existing image-processing based mobile urine tester.

• 항공우주시스템공학회지
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• 제7권1호
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• pp.19-25
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• 2013

Smoothed Particle Hydrodynamics(SPH) method uses a grid of historical analysis and is not Lagrangian particles using the grid method. The Navier-Stokes equations were used to solve the viscous flow of the non-compressed. In this study, the numerical analysis of the three-dimensional Coin Drop Simulation using SPH method was performed, and the analysis results are compared with experimental results, and a similar behavior can be seen. The commercial program used was Abaqus/Explicit. SPH method to reduce the error by comparing the existing flow analysis or interpretation of the continuing research is needed in the future. That will enable real-time analysis of material obtained as a result of these numerical simulations similar to the actual flow phenomena, depending on the development of computer graphics technology to show visually. As a result, this method can be applied to the analysis fluid - structure interaction problems in a variety of fields.

• 대한기계학회논문집A
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• 제25권5호
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• pp.850-856
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• 2001

Even though the hydraulic servo system has been widely used in industrial and military equipments since it has a lot of advantages, it is not easy to design controller due to the high nonlinearities and the parametric uncertainties. The dynamic behavior of the real process in the hydraulic servo system differs from that described by its model because the model is linearized. Another reason of the difference is caused by the variety of parameters, since the system parameters of the dynamic equation are affected by the operating conditions such as temperature and pressure. In this study, the designing process of the MRNC with a PID compensator is introduced and applied to the load sensing hydraulic servo system. The results show that the designed controller guarantees the robust control performance despite of both the nonlinearities and the parametric uncertainties.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권11호
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• pp.5556-5573
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• 2017

As a main component of Internet of Things (IoTs), the wireless sensor networks (WSNs) have been widely applied to various areas, including environment monitoring, health monitoring of human body, farming, commercial manufacture, reconnaissance mission in military, and calamity alert etc. Meanwhile, the privacy concerns also arise when the users are required to get the real-time data from the sensor nodes directly. To solve this problem, several user authentication and key agreement schemes with a smart card and a password have been proposed in the past years. However, these schemes are vulnerable to some attacks such as offline password guessing attack, user impersonation attack by using attacker's own smart card, sensor node impersonation attack and gateway node bypassing attack. In this paper, we propose an improved scheme which can resist a wide variety of attacks in WSNs. Cryptanalysis and performance analysis show that our scheme can solve the weaknesses of previously proposed schemes and enhance security requirements while maintaining low computational cost.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권8호
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• pp.3606-3629
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• 2018

The discovered high potential utility itemsets (HPUIs) have significant influence on a variety of areas, such as retail marketing, web click analysis, and biological gene analysis. Thus, in this paper, we propose an algorithm called HPUIM-QGA (Mining high potential utility itemsets based on a quantum genetic algorithm) to mine HPUIs over uncertain datasets based on a quantum genetic algorithm (QGA). The proposed algorithm not only can handle the problem of the non-downward closure property by developing an upper bound of the potential utility (UBPU) (which prunes the unpromising itemsets in the early stage) but can also handle the problem of combinatorial explosion by introducing a QGA, which finds optimal solutions quickly and needs to set only very few parameters. Furthermore, a pruning strategy has been designed to avoid the meaningless and redundant itemsets that are generated in the evolution process of the QGA. As proof of the HPUIM-QGA, a substantial number of experiments are performed on the runtime, memory usage, analysis of the discovered itemsets and the convergence on real-life and synthetic datasets. The results show that our proposed algorithm is reasonable and acceptable for mining meaningful HPUIs from uncertain datasets.

• 산업경영시스템학회지
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• 제32권2호
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• pp.132-139
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• 2009

Yield is a very important measure that can expresses simply for productivity and performance of company. So, yield is used widely in many industries nowadays. With the development of the information technology and online based real-time process monitoring technology, many industries operate the production lines that are developed into automation system. In these production lines, the product structures are very complexity and variety. So, there are many multi-variate processes that need to be monitored with many quality characteristics and associated process variables at the same time. These situations have made it possible to obtain super-large manufacturing process data sets. However, there are many difficulties with finding the cause of process variation or useful information in the high capacity database. In order to solve this problem, neural networks technique is a favorite technique that predicts the yield of process for process control. This paper uses a neural networks technique for improvement and maintenance of yield in manufacturing process. The purpose of this paper is to model the prediction of a sub process that has much effect to improve yields in total manufacturing process and the prediction of adjustment values of this sub process. These informations feedback into the process and the process is adjusted. Also, we show that the proposed model is useful to the manufacturing process through the case study.

• 한국지능시스템학회논문지
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• 제21권1호
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• pp.106-111
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• 2011

영상 기반의 움직이는 객체의 검출 및 추적은 실시간 감시 시스템이나 영상회의 시스템 등에서 널리 사용되어지고 있다. 또한 인간-컴퓨터 상호 작용(Human-Computer Interface)이나 인간-로봇 상호 작용(Human-Robot Interface)으로 확장되어 사용할 수 있기 때문에 움직이는 객체의 추적 기술은 중요한 핵심 기술 중에 하나이다. 특히 다중 객체의 움직임 환경에서 특정 객체의 움직임만을 추적할 수 있다면 다양한 응용이 가능할 것이다. 본 논문에서는 파티클 필터를 이용한 특정 객체의 움직임 추적에 관하여 연구 하였다. 실험 결과들로부터 파티클 필터를 이용한 단일 객체의 움직임 추적과 다중 객체의 움직임 환경에서 특정 객체의 움직임 추적에서 좋은 결과를 얻을 수 있었다.