• Journal of the military operations research society of Korea
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• v.24 no.1
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• pp.146-156
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• 1998

Cholesky factorization is known to be inefficient to problems with dense column and network problems in interior point methods. We use the conjugate gradient method and preconditioners to improve the convergence rate of the conjugate gradient method. Several preconditioners were applied to LPABO 5.1 and the results were compared with those of CPLEX 3.0. The conjugate gradient method shows to be more efficient than Cholesky factorization to problems with dense columns and network problems. The incomplete Cholesky factorization preconditioner shows to be the most efficient among the preconditioners.

• Proceedings of the Membrane Society of Korea Conference
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• 1993.04a
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• pp.36-37
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• 1993

상전이 공정에 의해 제조된 기체분리용 중공사막은 1차적으로 방사원액의 조성과 내.외부응고제의 조성, 중공사 방사조건 그리고 후처리 과정에 의해서 전체적인 구조가 결정되어진다. 특히 기체 분리에 이용되는 Nonprous Membrane의 경우 Dense Skin의 Thickness와 Pinhole의 유무에 따라 투과성과 선택성에 커다란 영향을 미친다. 따라서 최근에는 Dense Skin의 초박막화와 Pinhole이 없는 비대칭막 제조등 폭넓은 연구가 이루어지고 있다. 본 연구에서는 CO$_2$ Gas 분리용 Polyetherimide 중공사막을 제조하여, 중공사막 제조조건과 후처리 조건에 따른 $CO_2/N_2$ Gas의 분리계수를 측정하였다.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2002.11a
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• pp.393-394
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• 2002

현대 산업 사회의 급속한 발전으로 인해 대기 중에는 다양한 오염원을 통해서 많은 오염물질이 배출됨에 따라 이를 평가하고 방지할 대책이 필요하게 되었다. 이러한 대책 중의 하나로 배출원에서 배출되는 오염물질의 경로 및 발생량을 예측하는 방법이 있는데, 대기 상에 배출되는 오염물질의 농도를 예측할 경우 보통 대기 확산 모델링을 통하여 배출원 주변의 오염물질 확산 및 농도값을 산정한다. 현재 국내에서는 주로 가우시안 확산 모델인 ISC, CALPUFF 모델 등을 사용하여 모델링을 계산하게 된다. (중략)

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.485-486
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• 2018

In this paper, we consider a binary recovery framework of the Compressed Sensing (CS) problem. We derive an upper bound for $L_0$ recovery performance of a binary sparse signal in terms of the dimension N and sparsity K of signals, the number of measurements M. We show that the upper bound obtained from this work goes to the limit bound when the sensing matrix sufficiently become dense. In addition, for perfect recovery performance, if the signals are very sparse, the sensing matrices required for $L_0$ recovery are little more dense.

• Communications of the Korean Mathematical Society
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• v.34 no.3
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• pp.981-989
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• 2019

In this paper we deal with some shadowing properties of discrete dynamical systems on a compact metric space via the density of subdynamical systems. Let $f:X{\rightarrow}X$ be a continuous map of a compact metric space X and A be an f-invariant dense subspace of X. We show that if $f{\mid}_A:A{\rightarrow}A$ has the periodic shadowing property, then f has the periodic shadowing property. Also, we show that f has the finite average shadowing property if and only if $f{\mid}_A$ has the finite average shadowing property.

• Nonlinear Functional Analysis and Applications
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• v.27 no.1
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• pp.111-119
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• 2022

In this article, we prove that diskcyclic C₀-semigroups exist on any infinite-dimensional Banach space. We show that a C₀-semigroup (T_t)_t≥0 satisfies the diskcyclicity criterion if and only if any of T_t's satisfies the diskcyclicity criterion for operators. Moreover, we show that there are diskcyclic C₀-semigroups that do not satisfy the diskcyclicity criterion. Also, we state various criteria for diskcyclicity of C₀-semigroups based on dense sets and d-dense orbits.

• Journal of the Chungcheong Mathematical Society
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• v.35 no.2
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• pp.103-113
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• 2022

The notions of soft rough pre open set, soft rough pre closed set, soft rough dense set, soft rough sub maximal, soft rough pre interior and soft rough pre closure are introduced and studied. We also investigate some related properties of these concepts.

• Kyungpook Mathematical Journal
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• v.18 no.1
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• pp.61-69
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• 1978

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.98-110
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• 2018

In this paper, we propose both Dense grid model and Anchor model to improve the recognition rate of dynamic objects. Two experiments are conducted to study the performance of two proposed CNNs models (Dense grid model and Anchor model), which are to detect dynamic objects. In the first experiment, YOLO-v2 network is adjusted, and then fine-tuned on KITTI datasets. The Dense grid model and Anchor model are then compared with YOLO-v2. Regarding to the evaluation, the two models outperform YOLO-v2 from 6.26% to 10.99% on car detection at different difficulty levels. In the second experiment, this paper conducted further training of the models on a new dataset. The two models outperform YOLO-v2 up to 22.40% on car detection at different difficulty levels.

• Journal of Acupuncture Research
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• v.20 no.6
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• pp.168-181
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• 2003

Objective: The neuroanatomical studies on the acupoints(Waiguan(SJ5), Neiguan(Pe6), Sanyinjiao(SP6) and Xuanzhong(GB39)) projecting to the brain area related to dimentia using the pseudorabies virus (PRV-Ba strain) in the mouse was described. Methods: The common locations of the brain projecting to the Waiguan, Neiguan, Sanyinjiao and Xuanzhong following injection of PRV-Ba were histochemically observed. The results were as follows Results : 1. PRV-Ba labeled areas in medulla oblongata, pons and midbrain were similar to 4 acupoints, theses areas were related to autonomic center. 2. PRV-Ba labeled areas in diencephalon and cebrebrum were differently labeled according to the acupoints. 3. CNS labeled areas in Waiguan were dense labeled in CA1-3 area of hippocampus, amygdaloid nucleus, insular cortex, parietal cortex, entorhinal cortex, perirhinal cortex, dorsal endopiriform cortex, piriform cortex, amygdalopiriform transition and bed n. of stria terminalis. 4. CNS labeled areas in Neiguan were dense labeled in insular cortex, amygdaloid nucleus, parietal cortex, entorhinal cortex, perirhinal cortex, dorsal endopiriform cortex, piriform cortex, amygdalopiriform transition and bed n. of stria terminalis. 5. CNS labeled areas in Sanyinjiao were dense labeled in CA1-3 of hippocampus, suprachiasmatic n., dorsal endopiriform cortex, piriform cortex and bed n. of stria terminalis. 6. CNS labeled areas in Xuanzhong were dense labeled in suprachiasmatic n., dorsal endopiriform cortex and piriform cortex. Conclusions : Following these results, labeled acupoints in brain areas related to dimentia are Waiguan and Neiguan. Common labeled areas are amygdaloid n., entorhinal cortex, amygdaopiriform transition, bed n. stria terminalis and perirhinal cortex.