• Title/Summary/Keyword: computer based estimation

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Automatic Segmentation of Renal Parenchyma using Graph-cuts with Shape Constraint based on Multi-probabilistic Atlas in Abdominal CT Images (복부 컴퓨터 단층촬영영상에서 다중 확률 아틀라스 기반 형상제한 그래프-컷을 사용한 신실질 자동 분할)

  • Lee, Jaeseon;Hong, Helen;Rha, Koon Ho
    • Journal of the Korea Computer Graphics Society
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    • v.22 no.4
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    • pp.11-19
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    • 2016
  • In this paper, we propose an automatic segmentation method of renal parenchyma on abdominal CT image using graph-cuts with shape constraint based on multi-probabilistic atlas. The proposed method consists of following three steps. First, to use the various shape information of renal parenchyma, multi-probabilistic atlas is generated by cortex-based similarity registration. Second, initial seeds for graph-cuts are extracted by maximum a posteriori (MAP) estimation and renal parenchyma is segmented by graph-cuts with shape constraint. Third, to reduce alignment error of probabilistic atlas and increase segmentation accuracy, registration and segmentation are iteratively performed. To evaluate the performance of proposed method, qualitative and quantitative evaluation are performed. Experimental results show that the proposed method avoids a leakage into neighbor regions with similar intensity of renal parenchyma and shows improved segmentation accuracy.

Neuro-Fuzzy Modeling based on Self-Organizing Clustering (자기구성 클러스터링 기반 뉴로-퍼지 모델링)

  • Kim Sung-Suk;Ryu Jeong-Woong;Kim Yong-Tae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.6
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    • pp.688-694
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    • 2005
  • In this Paper, we Propose a new neuro-fuzzy modeling using clustering-based learning method. In the proposed clustering method, number of clusters is automatically inferred and its parameters are optimized simultaneously, Also, a neuro-fuzzy model is learned based on clustering information at same time. In the previous modelling method, clustering and model learning are performed independently and have no exchange of its informations. However, in the proposed method, overall neuro-fuzzy model is generated by using both clustering and model learning, and the information of modelling output is used to clustering of input. The proposed method improve the computational load of modeling using Subtractive clustering method. Simulation results show that the proposed method has an effectiveness compared with the previous methods.

Motion vector-tracing algorithms of video sequence (비디오 시퀀스의 움직임 추적 알고리즘)

  • 이재현
    • Journal of the Korea Computer Industry Society
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    • v.3 no.7
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    • pp.927-936
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    • 2002
  • This paper presents the extraction of a feature by motion vector for efficient content-based retrieval for digital video. in this paper, divided by general size block for the current frame by video, using BMA(block matching algorithm) for an estimate by block move based on a time frame. but in case BMA appeared on a different pattern fact of motion in the vector obtain for the BMA. solve in this a problem to application for full search method this method is detected by of on many calculations. I propose an alternative plan in this paper Limit the search region to $\pm$15 and search is a limit integer pixel. a result, in this paper is make an estimate motion vector in more accurately using motion vector in adjoin in blocks. however, refer to the block vector because occurrence synchronism. Such addition information is get hold burden receive to transmit therefore, forecasted that motion feature each block and consider for problems for establish search region. in this paper Algorithm based to an examination Motion Estimation method by for motion Compensation is proposed.

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A Probabilistic Model of Damage Propagation based on the Markov Process (마코프 프로세스에 기반한 확률적 피해 파급 모델)

  • Kim Young-Gab;Baek Young-Kyo;In Hoh-Peter;Baik Doo-Kwon
    • Journal of KIISE:Computer Systems and Theory
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    • v.33 no.8
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    • pp.524-535
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    • 2006
  • With rapid development of Internet technology, business management in an organization or an enterprise depends on Internet-based technology for the most part. Furthermore, as dependency and cohesiveness of network in the communication facilities are increasing, cyber attacks have been increased against vulnerable resource in the information system. Hence, to protect private information and computer resource, research for damage propagation is required in this situation. However the proposed traditional models present just mechanism for risk management, or are able to be applied to the specified threats such as virus or worm. Therefore, we propose the probabilistic model of damage propagation based on the Markov process, which can be applied to diverse threats in the information systems. Using the proposed model in this paper, we can predict the occurrence probability and occurrence frequency for each threats in the entire system.

Parallel Rendering of High Quality Animation based on a Dynamic Workload Allocation Scheme (작업영역의 동적 할당을 통한 고화질 애니메이션의 병렬 렌더링)

  • Rhee, Yun-Seok
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.1
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    • pp.109-116
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    • 2008
  • Even though many studies on parallel rendering based on PC clusters have been done. most of those did not cope with non-uniform scenes, where locations of 3D models are biased. In this work. we have built a PC cluster system with POV-Ray, a free rendering software on the public domain, and developed an adaptive load balancing scheme to optimize the parallel efficiency Especially, we noticed that a frame of 3D animation are closely coherent with adjacent frames. and thus we could estimate distribution of computation amount, based on the computation time of previous frame. The experimental results with 2 real animation data show that the proposed scheme reduces by 40% of execution time compared to the simple static partitioning scheme.

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An Adaptive Peer-to-Peer Search Algorithm for Reformed Node Distribution Rate (개선된 노드 분산율을 위한 적응적 P2P 검색 알고리즘)

  • Kim, Boon-Hee;Lee, Jun-Yeon
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.4 s.36
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    • pp.93-102
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    • 2005
  • Excessive traffic of P2P applications in the limited communication environment is considered as a network bandwidth problem. Moreover, Though P2P systems search a resource in the phase of search using weakly connected systems(peers' connection to P2P overlay network is very weakly connected), it is not guaranteed to download the very peer's resource in the phase of download. In previous P2P search algorithm (1), we had adopted the heuristic peer selection method based on Random Walks to resolve this problems. In this paper, we suggested an adaptive P2P search algorithm based on the previous algorithm(1) to reform the node distribution rate which is affected in unit peer ability. Also, we have adapted the discriminative replication method based on a query ratio to reduce traffic amount additionally. In the performance estimation result of this suggested system, our system works on a appropriate point of compromise in due consideration of the direction of searching and distribution of traffic occurrence.

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Unified DC Offset Cancellation and I/Q Regeneration with Carrier Phase Recovery in Five-Port Junction based Direct Receivers (Five-port 접합을 이용한 RF 수신기를 위한 동시 DC 오프셋 제거와 I/Q 신호 재생 알고리즘)

  • Park, Hyung-Chul;Lim, Hyung-Sun;Yu, Jong-Won
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.44 no.6 s.360
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    • pp.64-70
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    • 2007
  • This paper presents a novel unified DC offset cancellation and I/Q regeneration for five-port junction based direct receivers. It utilizes the symmetry characteristics of the single-frequency continuous-wave (CW) signal, making it possible that the proposed method can be used regardless of carrier phase offset. The proposed method eliminates the additional DC offset cancellation and reduces the I/Q regeneration parameter estimation time. Since the proposed method employs a single-frequency CW signal independent of the modulation scheme, five-port junction based direct receivers can be used for the demodulation of orthogonal frequency-division multiplexing and continuous phase modulation as well as phase shift-keying.

Implementation of Personalized Rehabilitation Exercise Mobile App based on Edge Computing

  • Park, Myeong-Chul;Hur, Hwa-La
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.12
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    • pp.93-100
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    • 2022
  • In this paper, we propose a mobile app for personalized rehabilitation exercise coaching and management service using an edge computing-based personalized exercise information collection system. The existing management method that relies on user input information has difficulty in examining the actual possibility of rehabilitation. In this paper, we implement an application that collects movement information along with body joint information through image information analysis based on edge computing at a remote location, measures the time and accuracy of the movement, and provides rehabilitation progress through correct posture information. In addition, in connection with the measurement equipment of the rehabilitation center, the health status can be managed, and the accuracy of exercise information and trend analysis information is provided. The results of this study will enable management and coaching according to self-rehabilitation exercises in a contactless environment.

Iterative Bispectrum Estimation and Signal Recovery Based On Weighted Regularization (가중 정규화에 기반한 반복적 바이스펙트럼 추정과 신호복원)

  • Lim, Won-Bae;Hur, Bong-Soo;Lee, Hak-Moo;Kang, Moon-Gi
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.37 no.3
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    • pp.98-109
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    • 2000
  • While the bispectrum has desirable properties in itself and therefore has a lot of potential to be applied to signal and Image restoration. few real-world application results have appeared in literature The major problem with this IS the difficulty In realizing the expectation operator of the true bispectrum, due to the lack of realizations. In this paper, the true bispectrum is defined as the expectation of the sample bispectrum, which IS the Fourier representation of the triple correlation given one realization The characteristics of the sample bispectrum are analyzed and a way to obtain an estimate of the true bispectrum without stochastic expectation, using the generalized theory of weighted regularization is shown. The bispectrum estimated by the proposed algorithm is experimentally demonstrated to be useful for signal recovery under blurred noisy condition.

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An Estimation Model for Defence Ability Using Big Data Analysis in Korea Baseball

  • Ju-Han Heo;Yong-Tae Woo
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.8
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    • pp.119-126
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    • 2023
  • In this paper, a new model was presented to objectively evaluate the defense ability of defenders in Korean professional baseball. In the proposed model, using Korean professional baseball game data from 2016 to 2019, a representative defender was selected for each team and defensive position to evaluate defensive ability. In order to evaluate the defense ability, a method of calculating the defense range for each position and dividing the calculated defense area was proposed. The defensive range for each position was calculated using the Convex Hull algorithm based on the point at which the defenders in the same position threw out the ball. The out conversion score and victory contribution score for both infielders and outfielders were calculated as basic scores using the defensive range for each position. In addition, double kill points for infielders and extra base points for outfielders were calculated separately and added together.