• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3479-3492
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• 2022

Longitudinal quantification of brain changes due to development, aging or disease plays an important role in the filed of personalized-medicine applications. However, due to the temporal variability in shape and different imaging equipment and parameters, estimating anatomical changes in longitudinal studies is significantly challenging. In this paper, a longitudinal Magnetic Resonance(MR) brain image segmentation algorithm proposed by combining intensity information and anisotropic smoothness term which contain a spatial smoothness constraint and longitudinal consistent constraint into a variational framework. The minimization of the proposed energy functional is strictly and effectively derived from a fast optimization algorithm. A large number of experimental results show that the proposed method can guarantee segmentation accuracy and longitudinal consistency in both simulated and real longitudinal MR brain images for analysis of anatomical changes over time.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.709-714
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• 2023

A flexible planning system is an important element for the robot to perform various tasks. In this paper, we introduce an automated planning system architecture that can deal with the changing environment. PDDL is used for symbolic-based task planning, and a graph database is used for real-time environment information updates for automated PDDL generation. The proposed framework was verified through scenario-based experiments.

• Annual Conference of KIPS
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• 2020.05a
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• pp.142-145
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• 2020

캐시 부채널 공격은 캐시 기반의 공격 기법으로 개인정보 유출에 대한 위험성이 큰 보안 취약점이다. 해당 취약점을 막기 위해 실시간 공격 탐지 기법에 관한 연구들이 진행되고 있지만 사용자에게 이벤트값과 탐지 결과를 빠르고 편리하게 보여줄 필요성이 있다. 본 논문은 효율적인 캐시 부채널 공격 탐지를 위해 Intel PCM 과 기존의 탐지프로그램을 개선하여 탐지에 필요한 데이터들을 실시간으로 모니터링 및 경고를 보내주는 프레임워크를 제작했다. 해당 프레임워크는 캐시 부채널 공격을 실시간 탐지 및 관련 데이터들을 대시보드로 보여준다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.361-364
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• 2022

본 논문에서는 스마트 기기를 사용할 시 자세가 거북목 자세인지 아닌지 판별하는 시스템을 제안한다. 거북목 증후군이란 목이 구부정하게 앞으로 나오는 자세를 오래 취해 목이 일자목으로 바뀌고 뒷목, 어깨, 허리 등에 통증이 생기는 증상을 말하며, 수술이나 약물치료보다 평소의 자세 습관을 고치는 방법이 효과적이다. 기존의 연구들은 노트북에 내장되어있는 웹캠을 이용한 CNN기반의 학습모델은 영상의 명도와 학습 데이터 등에 많은 영향을 받고 학습 데이터를 모을 때 초상권 문제로 수집이 어렵다. 본 논문에서는 이러한 문제를 예방하고자 Openpose 오픈 소스를 이용한 뼈대를 기반으로 측면에서의 앉은 자세를 한습 모델로 실시간 검증하여, 거북목 자세인지 아닌지를 효율적이고 정확하게 판별한다.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3515-3524
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• 2023

A reinforcement learning framework is proposed for the control problem of outlet steam pressure of the once-through steam generator(OTSG) in this paper. The double-layer controller using Proximal Policy Optimization(PPO) algorithm is applied in the control structure of the OTSG. The PPO algorithm can train the neural networks continuously according to the process of interaction with the environment and then the trained controller can realize better control for the OTSG. Meanwhile, reinforcement learning has the characteristic of difficult application in real-world objects, this paper proposes an innovative pretraining method to solve this problem. The difficulty in the application of reinforcement learning lies in training. The optimal strategy of each step is summed up through trial and error, and the training cost is very high. In this paper, the LSTM model is adopted as the training environment for pretraining, which saves training time and improves efficiency. The experimental results show that this method can realize the self-adjustment of control parameters under various working conditions, and the control effect has the advantages of small overshoot, fast stabilization speed, and strong adaptive ability.

• Communications for Statistical Applications and Methods
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• v.31 no.5
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• pp.601-612
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• 2024

A functional clustering analysis is a crucial machine learning technique in functional data analysis. Many functional clustering methods have been developed to enhance clustering performance. Moreover, due to the phase variability between functions, elastic functional clustering methods, such as applying the Fisher-Rao metric, which can manage phase variation during clustering, have been developed to improve model performance. However, aligning functions without considering the phase variation can distort functional information because phase variation can be a natural characteristic of functions. Hence, we propose a state-of-the-art functional hierarchical clustering that can manage phase and amplitude variations of functional data. This approach is based on the phase and amplitude separation method using the norm-preserving time warping of functions. Due to its invariance property, this representation provides robust variability for phase and amplitude components of functions and improves clustering performance compared to conventional functional hierarchical clustering models. We demonstrate this framework using simulated and real data.

• Korean Journal of Construction Engineering and Management
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• v.12 no.1
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• pp.141-152
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• 2011

The market volume of urban regeneration projects has steadily increased, thereby mixed-use development also shows significant market growth. However, previous researches on urban regeneration mainly deduced suggestions and plans for institution improvement based on comparison between projects implemented the inside and outside of the country. Whereas, researches on project management closely related to project success were limited, particularly in performance management. Accordingly, this research aims at developing a program performance management framework for public clients so as to succeed mixed-use development projects. Through extensive literature review and expert interview, this research developed performance indices for diverse facilities, risk management framework and integrating method of program performance score. The proposed framework is able to consider total life cycle from basic planning to maintenance phase and to check real-time performance level. Moreover, risk management framework can periodically assess and control the level of inherent risks within performance indices. The results can contribute to improve existing performance management practices and be basis for a web-based system developed in future.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.164-173
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• 2014

In underwater robotics, vision would be a key element for recognition in underwater environments. However, due to turbidity an underwater optical camera is rarely available. An underwater imaging sonar, as an alternative, delivers low quality sonar images which are not stable and accurate enough to find out natural objects by image processing. For this, artificial landmarks based on the characteristics of ultrasonic waves and their recognition method by a shape matrix transformation were proposed and were proven in Part 1. But, this is not working properly in undulating and dynamically noisy sea-bottom. To solve this, we propose a framework providing a selection phase of likelihood candidates, a selection phase for final candidates, recognition phase and tracking phase in sequence images, where a particle filter based selection mechanism to eliminate fake candidates and a mean shift based tracking algorithm are also proposed. All 4 steps are running in parallel and real-time processing. The proposed framework is flexible to add and to modify internal algorithms. A pool test and sea trial are carried out to prove the performance, and detail analysis of experimental results are done. Information is obtained from tracking phase such as relative distance, bearing will be expected to be used for control and navigation of underwater robots.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.545-559
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• 2020

In this paper, we propose a content creation framework that enables users without programming experience to easily create interactive media content that responds to user gestures. In the proposed framework, users define the gestures they use and the media effects that respond to them by numbers, and link them in a text-based configuration file. In the proposed framework, the interactive media content that responds to the user's gesture is linked with the dynamic projection mapping module to track the user's location and project the media effects onto the user. To reduce the processing speed and memory burden of the gesture recognition, the user's movement is expressed as a gray scale motion history image. We designed a convolutional neural network model for gesture recognition using motion history images as input data. The number of network layers and hyperparameters of the convolutional neural network model were determined through experiments that recognize five gestures, and applied to the proposed framework. In the gesture recognition experiment, we obtained a recognition accuracy of 97.96% and a processing speed of 12.04 FPS. In the experiment connected with the three media effects, we confirmed that the intended media effect was appropriately displayed in real-time according to the user's gesture.

• The KIPS Transactions:PartC
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• v.12C no.6 s.102
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• pp.881-890
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• 2005

Over for the past 10 years, the increase in geometric progression for the internet traffic, has allowed the IP protocol framework to be the most important network technology. In addition, the internet service is being developed as a service mode differentiated, aiming to support the new-mode real-time multimedia services such as internet phone, video conference, cyber reality, and internet game, focusing on offering a latest service. These days, aiming to solve the need for broad bandwidth along with guaranteeing QoS, the WDM technology of offering multiple gigabit wavelengths is emerging as the core technology of next-generation optical internet backbone network. In the next-generation optical internet backbone network based on WDM, the QoS framework is one of fore subjects aiming to offer a service of guaranteeing QoS This study analyzes the requirements of performance related to QoS framework in IP Subnet and in WDM optical backbone network, and suggests optical QoS service framework differentiated. in order to guarantee end-to-end QoS through the next-generation optical internet backbone network, using GMPLS control protocol.