• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.71-73
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• 2017

본 논문에서는 4 방향 윤곽선 추적 기법과 히스토그램 분석 기법을 기반으로 한 개선된 FCM 알고리즘을 적용하여 색조 도플러 초음파 영상에서 상완 동맥의 혈류를 추출하고 분석하는 방법을 제안한다. 제안된 방법에서는 상완 동맥의 혈류를 정확히 추출하기 위해 전처리 과정으로 색조 도플러 초음파 영상 이외의 환자 정보가 있는 영역을 제거한 후, ROI 영역을 추출한다. 추출된 ROI 영역에서 영상의 최대 명암도를 임계치로 설정한 이진화 기법을 적용하여 ROI 영역을 이진화한다. 이진화된 ROI 영역에서 4 방향 윤곽선 추적 기법을 적용하여 상완 동맥이 존재하는 사다리꼴 형태의 영역을 추출한다. 색 정보를 분석한 히스토그램을 이용하여 특징점의 개수를 계산하고 계산된 특징점의 개수를 FCM 알고리즘의 초기 클러스터의 개수로 설정한 후, 추출된 사다리꼴 형태의 영역에 적용하여 양자화 한다. 양자화된 영역 중에서 빨간색으로 분류된 영역을 고혈압 영역으로 추출한다. 제안된 추출 방법을 20개의 색조 도플러 초음파 영상을 대상으로 실험한 결과, 20개의 색조 도플러 초음파 영상에서 18개의 색조 도플러 초음파 영상이 정확히 추출되었다.

• Polymer(Korea)
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• v.25 no.1
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• pp.90-97
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• 2001

Dispersions are prepared from poly(ethylene-co-acrylic acid) (PEAA) ionomer with two different counter-ions, ammonium and sodium. The diffusional characteristic of urea aqueous solution are measured for the films prepared from the above mentioned dispersions. It is attempted to find the relationship between diffusional behavior and various chemical and physical characteristics of films. DSC is employed to characterize glass transition temperature and degree of crystallinity and the structural features of crystal phase and ionic clusters are examined by WAXD and FTIR. The diffusional characteristics of ionomer is found to be dependent on various parameters such as the size of initial dispersion as well as the kind of counter ion and the degree of neutralization.

• The Journal of the Acoustical Society of Korea
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• v.31 no.8
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• pp.542-550
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• 2012

In this paper, an adaptive scheme for network topology configuration is proposed to save the overall energy consumption in underwater acoustic sensor network. The proposed scheme employs a self-organized networking methodology where network topology is locally optimized by exchanging the energy-related information between neighboring nodes such as the remaining energy of each node, in a way that the network life time can be augmented without any centralized control function. Computer simulation is used to evaluate the proposed scheme comparing with LEACH in terms of the number of alive nodes after a given time, the deviation of individual nodes' residual energy and the energy consumption at the initialization and coordination stages.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.6
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• pp.493-497
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• 2016

Infrared (IR) imaging is capable of detecting targets that are not visible at night, thus it has been widely used for the security and defense system. However, the quality of the IR image is often degraded by low resolution and noise corruption. This paper addresses target segmentation with the IR image. Multiple regions of interest (ROI) are extracted by the multi-level segmentation and targets are segmented from the individual ROI. Each level of the multi-level segmentation is composed of a k-means clustering algorithm an expectation-maximization (EM) algorithm, and a decision process. The k-means clustering algorithm initializes the parameters of the Gaussian mixture model (GMM) and the EM algorithm iteratively estimates those parameters. Each pixel is assigned to one of clusters during the decision. This paper proposes the selection and the merging of the extracted ROIs. ROI regions are selectively merged in order to include the overlapped ROI windows. In the experiments, the proposed method is tested on an IR image capturing two pedestrians at night. The performance is compared with conventional methods showing that the proposed method outperforms others.

• Investigative Magnetic Resonance Imaging
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• v.6 no.2
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• pp.137-146
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• 2002

Purpose : This paper introduces an improved classification approach which adopts a deterministic relaxation method and an agglomerative clustering technique for the classification of MRI using neural network. The proposed approach can solve the problems of convergency to local optima and computational burden caused by a large number of input patterns when a neural network is used for image classification. Materials and methods : Application of Hopfield neural network has been solving various optimization problems. However, major problem of mapping an image classification problem into a neural network is that network is opt to converge to local optima and its convergency toward the global solution with a standard stochastic relaxation spends much time. Therefore, to avoid local solutions and to achieve fast convergency toward a global optimization, we adopt MFA to a Hopfield network during the classification. MFA replaces the stochastic nature of simulated annealing method with a set of deterministic update rules that act on the average value of the variable. By minimizing averages, it is possible to converge to an equilibrium state considerably faster than standard simulated annealing method. Moreover, the proposed agglomerative clustering algorithm which determines the underlying clusters of the image provides initial input values of Hopfield neural network. Results : The proposed approach which uses agglomerative clustering and deterministic relaxation approach resolves the problem of local optimization and achieves fast convergency toward a global optimization when a neural network is used for MRI classification. Conclusion : In this paper, we introduce a new paradigm to classify MRI using clustering analysis and deterministic relaxation for neural network to improve the classification results.

• Resources Recycling
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• v.21 no.5
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• pp.79-87
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• 2012

With the increasing size and universalization of lithium-ion batteries, the development of cathode materials has emerged as a critical issue. The energy density of 18650 cylindrical batteries had more than doubled from 230 Wh/l in 1991 to 500 Wh/l in 2005. The energy capacity of most products ranges from 450 to 500Wh/l or from 150 to 190 Wh/kg. Product developments are focusing on high capacity, safety, saved production cost, and long life. As Co is expensive among the cathode active materials $LiCoO_2$, to increase energy capacity while decreasing the use of Co, composites such as $LiMn_2O_4$, $LiCo_{1/3}N_{i1/3}Mn_{1/3}O_2$, $LiNi_{0.8}Co_{0.15}Al_{0.05}O_2$, and $LiFePO_4$-C (167 mA/g) are being developed. Furthermore, many studies are being conducted to improve the performance of battery materials to meet the requirement of large capacity output density such as 500Wh/kg for electric bicycles, 1,500Wh/kg for electric tools, and 4,000~5,000Wh/kg for EV and PHEV. As new cathodes active materials with high energy capacity such as graphene-sulfur composite cathode materials with 600 Ah/kg and the molecular cluster for secondary battery with 320 Ah/kg are being developed these days, their commercializations are highly anticipated.

• Journal of radiological science and technology
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• v.32 no.1
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• pp.45-52
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• 2009

Digital Mammography is an efficient imaging technique for the detection and diagnosis of breast pathological disorders. Six mammographic criteria such as number of cluster, number, size, extent and morphologic shape of microcalcification, and presence of mass, were reviewed and correlation with pathologic diagnosis were evaluated. It is very important to find breast cancer early when treatment can reduce deaths from breast cancer and breast incision. In screening breast cancer, mammography is typically used to view the internal organization. Clusterig microcalcifications on mammography represent an important feature of breast mass, especially that of intraductal carcinoma. Because microcalcification has high correlation with breast cancer, a cluster of a microcalcification can be very helpful for the clinical doctor to predict breast cancer. For this study, three steps of quantitative evaluation are proposed : DoG filter, adaptive thresholding, Expectation maximization. Through the proposed algorithm, each cluster in the distribution of microcalcification was able to measure the number calcification and length of cluster also can be used to automatically diagnose breast cancer as indicators of the primary diagnosis.

• The Journal of the Acoustical Society of Korea
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• v.39 no.2
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• pp.120-130
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• 2020

This paper solves the problem in underdetermined convolutive mixture by improving the disadvantages of the multichannel nonnegative matrix factorization technique widely used in blind source separation. In conventional researches based on Spatial Covariance Matrix (SCM), each element composed of values such as power gain of single channel and correlation tends to degrade the quality of the separated sources due to high variance. In this paper, level and frequency normalization is performed to effectively cluster the estimated sources. Therefore, we propose a novel SCM and an effective distance function for cluster pairs. In this paper, the proposed SCM is used for the initialization of the spatial model and used for hierarchical agglomerative clustering in the bottom-up approach. The proposed algorithm was experimented using the 'Signal Separation Evaluation Campaign 2008 development dataset'. As a result, the improvement in most of the performance indicators was confirmed by utilizing the 'Blind Source Separation Eval toolbox', an objective source separation quality verification tool, and especially the performance superiority of the typical SDR of 1 dB to 3.5 dB was verified.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.712-712
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• 2012

하 폐수 처리방류수를 물리적, 화학적 그리고 생물학적 기술을 이용하여 처리한 후 재활용수로 이용하고자 하는 새로운 노력들이 진행되고 있지만 국내의 경우 방류수 재활용 기술과 처리수의 재이용에 대한 평가기술이 선진국에 비해 초기 단계에 있어 이 분야에 대한 적극적인 기술개발이 요구된다. 막 분리 기술을 이용한 처리 수는 소독 등의 추가적인 처리 없이 살수용수나 수경용수로 이용이 가능하며, 잔류염소를 유지시킬 경우 화장실 세정용수로의 이용도 가능하며, 또한 후처리 기술을 조합하면 고급 공업용수 등으로 사용가능하므로 선진기술로서 수요조건에 맞게 전 후 처리를 조합한 수요자 맞춤형 재이용수 공정기술을 개발할 필요가 있다. 이에 효율적인 하 폐수 재이용을 이용하여 농업용수(축산 음용수, 첨단 수출원예용수, 첨단 농업용수, 농산업 클러스터 복합 곡물 용수), 원예용수(원예단지), 공업용수 등의 다양한 용도에 활용 가능한 수요자 맞춤형 모듈 및 공정 개발을 수행하였다. 개발된 공정은 AOP 및 막 세정 시스템을 이용한 새로운 공정으로, AOP 시스템은 전기 이온 모듈을 통해 OH 라디칼을 생성 및 염분 제거 효율을 극대화 하여 오염 물질을 산화시키는 공정이며, FDA 시스템은 탁도가 높은 원수가 과다 유입 될 경우 후단 여과 막의 부하를 줄이는 역할을 하며, 부유 물질을 여과 시킨다. 막 세정 시스템은 미세 입자를 구성된 기포를 이용하여 눈에 보이지 않는 곳 까지 세척하며, 살균 작용을 하며, 분리 막의 성능을 증대 시킨다. 이어 UF 분리 막 시스템은 원수의 미세불순물, 박테리아, 스케일 물질 등을 제거하며, NF 시스템을 통하여 미립자, 박테리아 유기 화합물 및 2가 염 제거를 하여 재이용수를 생산하는 공정을 개발하였다. 개발된 수요자 맞춤형 공정은 하수 재이용 기술의 이용 목적 및 수요자별로 맞춤형으로 운영이 가능하며, 개발된 세척 기술은 분리 막 세정 유지관리비 및 에너지를 저감 할 수 있으며, 현장 적용의 실증화 과정을 거쳐 공정 기술을 신뢰도를 향상하고, 보유 기술을 수요자 맞춤형으로 업그레이드함으로써 기술의 경쟁력 및 고품질의 하수 재이용 기술의 새로운 방향을 제시 할 수 있을 것으로 판단된다.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.3
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• pp.105-112
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• 2017

PCI Express is a bus technology that connects the processor and the peripheral I/O devices that widely used as an industry standard because it has the characteristics of high-speed, low power. In addition, PCI Express is system interconnect technology such as Ethernet and Infiniband used in high-performance computing and computer cluster. PGAS(partitioned global address space) programming model is often used to implement the one-sided RDMA(remote direct memory access) from multi-host systems, such as computer clusters. In this paper, we design and implement a OpenSHMEM API based on PCI Express maintaining the existing features of OpenSHMEM to implement RDMA based on PCI Express. We perform experiment with implemented OpenSHMEM API through a matrix multiplication example from system which PCs connected with NTB(non-transparent bridge) technology of PCI Express. The PCI Express interconnection network is currently very expensive and is not yet widely available to the general public. Nevertheless, we actually implemented and evaluated a PCI Express based interconnection network on the RDK evaluation board. In addition, we have implemented the OpenSHMEM software stack, which is of great interest recently.