• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.1
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• pp.1-8
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• 2011

An analytical study on the flow resistance of tree-shaped channel-flow architectures was carried out based on the principle of the constructal law; the evolutionary increase in the access to currents that flow through the channels with improvements in the flow configurations were studied in a square domain using two diameters. Two types of tree-shaped configurations were optimized. The minimized global flow resistance decreased steadily as the system size $N^2$ increased. From the two channel configurations, the one that resulted in better pressure drop was selected. Further, it was shown that the system performance can be enhanced by adopting the second tree-shaped configurations when the system size is greater than $18^2$.

• Journal of Sensor Science and Technology
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• v.12 no.6
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• pp.249-257
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• 2003

The bio-telemetry technologies, that use the wireless miniaturized telemetry module implanted in the human body and transmits several biomedical signal from inside to outside of the body, have been expected to solve the problem such as the patient's inconvenience and the limit for diagnosis. In the case of transceiver system using the wireless RF transmission method, the method of three-dimensional localization for implantable miniaturized telemetry module is necessary to detect the exact position of disease. A new method for three-dimensional localization using small loop antenna in the implantable miniaturized telemetry module was proposed in this paper. We proposed a method that can accurately determine the position of telemetry module by analyzing the differences in the strength of signal, which is received at each of the small size RF receiver array installed on the body surface.

• Journal of the Korea Computer Graphics Society
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• v.17 no.3
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• pp.9-19
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• 2011

Computing triangle-triangle intersections has been a fundamental task required for many 3D geometric problems. We propose a novel robust GPU algorithm to efficiently compute intersections in a large triangle set. The algorithm has three stages:k-d tree construction, triangle pair generation, and exact intersection computation. All three stages are executed on GPU except, for unsafe triangle pairs. Unsafe triangle pairs are robustly handled by CLP(controlled linear perturbation) on a CPU thread. They are identified by floating-point filtering while exact intersection is computed on GPU. Many triangles crossing a split plane are duplicated in k-d tree construction, which form a lot of redundant triangle pairs later. To eliminate them efficiently, we use a split index which can determine redundancy of a pair by a simple bitwise operation. We applied the proposed algorithm to computing 3D Minkowski sum boundaries to verify its efficiency and robustness.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1176-1182
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• 2021

Recently, with the development of artificial intelligence and IoT technology, automation, and unmanned work are progressing in various fields, and the importance of image processing, which is the basis of AI object recognition, is increasing. In particular, in systems that require detailed data processing, noise removal is used as a preprocessing step, but the existing algorithm does not consider the noise level of the image, so it has the disadvantage of blurring in the filtering process. Therefore, in this paper, we propose a modified Gaussian filter that determines the weight by determining the noise level of the image. The proposed algorithm obtains the noise estimate for the AWGN of the image using quadtree segmentation, determines the Gaussian weight and the pixel weight, and obtains the final output by convolution with the local mask. To evaluate the proposed algorithm, it was simulated compared to the existing method, and superior performance was confirmed compared to the existing method.

• Clean Technology
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• v.19 no.2
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• pp.105-112
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• 2013

In this study, polyaniline (PANI)-based $TiO_2$ (PANI-$TiO_2$) composites calcined at different temperatures were prepared and their applications for control of trichloroethylene (TCE) and tetrachloroethylene (TTCE) at indoor air levels were investigated. For these target compounds, the photocatalytic control efficiencies of PANI-$TiO_2$ composites did not exhibit any trend with varying calcination temperatures (CTs). Rather, the average control efficiencies of PANI-$TiO_2$ composites over 3-h photocatalytic process increased from 61 to 72% and from 21 to 39% for TCE and TTCE, respectively, as the CT increased from 350 to $450^{\circ}C$. However, for both the target compounds, the average control efficiencies of PANI-$TiO_2$ composites decreased gradually as the CT increased further to 550 and $650^{\circ}C$. These results were ascribed to contents of anatase crystal phase and specific surface area of different particle sizes in the PANI-$TiO_2$ composites, which were demonstrated by the X-ray diffraction and scanning electron microscopy images, respectively. At the lowest input concentration (IC, 0.1 ppm), average control efficiencies of TCE and TTCE were 72 and 39%, respectively, whereas at the highest IC (1.0 ppm) they were 52 and 18%, respectively. As stream flow rate increased from 0.1 to 1.0 L $min^{-1}$, the average control efficiencies of TCE and TTCE decreased from ca. 100 to 47% and ca. 100 to 18%, respectively. In addition, the average control efficiencies of TCE and TTCE decreased from ca. 100 to 23% and ca. 100 to 8%, respectively as the relative humidity increased from 20 to 95%. Overall, these findings indicated that as-prepared PANI-$TiO_2$ composites could be used efficiently for control of chlorinated compounds at indoor air levels;if operational conditions were optimized.

• Journal of The Korean Society of Grassland and Forage Science
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• v.40 no.1
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• pp.57-65
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• 2020

This study was conducted to investigate the effect of sowing and harvesting dates on agronomic characteristics and feed values of rye and triticale at Sanchoeng, South Korea. The experimental design consisted of the different sowing and harvesting dates as follows; rye (Secale cereale L., cv. Gogu) of sowing (October 15, 25, and November 5) in 2015 and harvesting (April 20, May 1 and May 11) in 2016, and triticale (X Triticosecale, cv. Joseong) of sowing (October 15, 25, and November 5) in 2015 and harvesting (May 18, 28, and June 7) in 2016. In rye, fresh and dry matter (DM) yields increased (p<0.05) with the delayed-harvesting date. Crude protein (CP) content and relative feed value (RFV) decreased (p<0.05) with the delayed-harvesting date, but neutral detergent fiber (NDF) content increased (p<0.05). In triticale, fresh and dry matter (DM) yields increased (p<0.05) with the delayed-harvesting date. The CP content decreased (p<0.05) with the delayed-harvesting date, but NDF content and RFV increased (p<0.05). This study concluded that rye sown in the middle of October then harvested in early May, and the triticale sown at the end of October then harvested at the end May are recommended to increase dry matter yield and feed value.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.11
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• pp.1025-1032
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• 2009

This study investigated a possibility to develop an adsorption process for volatile organic compounds (VOCs) of the solvent emitted during dry cleaning. Pitch activated carbon fiber (ACF) was chosen as an adsorbent of VOCs, and an electric swing adsorption process was utilized for the reproduction of the adsorbent after the completion of VOCs adsorption. Effects of ACF types and several solvents such as trichloroethylene (TCE) and toluene were examined on breakthrough curves and amounts of adsorbed VOCs. ACF was pretreated under various conditions in order to enhance the amounts of the adsorbed VOCs. Temperatures and voltages were measured for the reproduction of the ACF after full adsorption. ACF having micropores exhibited high adsorption of TCE, and high surface area of ACF could increase the adsorption property of toluene. In general, ACF could adsorb 41~54% TCE of the adsorbent weight. The increase of inlet VOCs concentration significantly decreased the breakthrough time and slightly lowered the amounts of adsorbed VOCs. Thus, ACF could effectively adsorb VOCs in low concentration in the feed stream. ACF pretreated by heat under vacuum showed excellent toluene adsorption with controlling oxygen functional groups on the ACF surface, which revealed that vacant carbon site could be the adsorption point of toluene. Most adsorbed toluene was desorbed at $150^{\circ}C$.

• Journal of Korea Water Resources Association
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• v.46 no.6
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• pp.655-666
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• 2013

Lately, intensity and frequency of natural disasters such as flood are increasing because of abnormal climate. Casualties and property damages due to large-scale floods such as Typhoon Rusa in 2002 and Typhoon Maemi in 2003 rapidly increased, and these show the limits of the existing disaster prevention measures and flood forecasting systems regarding irregular climate changes. In order to efficiently respond to extraordinary flood, it is important to provide effective countermeasures through an inundation model that can accurately simulate flood inundation patterns. However, the existing flood inundation analysis model has problems such as excessive take of analysis time and accuracy of the analyzed results. Therefore, this study conducted a flood inundation analysis by using the Gerris flow solver that uses quadtree grid, targeting the Baeksan Levee in the Nakdong River Basin that collapsed because of a concentrated torrential rainfall in August, 2002. Through comparisons with the FLUMEN model that uses unstructured grid among the existing flood inundation models and the actual flooded areas, it determined the applicability and efficiency of the quadtree grid-based flood inundation model of the Gerris flow solver.

• Journal of KIISE:Databases
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• v.29 no.5
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• pp.367-380
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• 2002

Due to recent increase in applications requiring huge amount of data such as spatial data analysis and image analysis, clustering on large databases has been actively studied. In a hierarchical clustering method, a tree representing hierarchical decomposition of the database is first created, and then, used for efficient clustering. Existing hierarchical clustering methods mainly adopted the bottom-up approach, which creates a tree from the bottom to the topmost level of the hierarchy. These bottom-up methods require at least one scan over the entire database in order to build the tree and need to search most nodes of the tree since the clustering algorithm starts from the leaf level. In this paper, we propose a novel top-down hierarchical clustering method that uses multidimensional indexes that are already maintained in most database applications. Generally, multidimensional indexes have the clustering property storing similar objects in the same (or adjacent) data pares. Using this property we can find adjacent objects without calculating distances among them. We first formally define the cluster based on the density of objects. For the definition, we propose the concept of the region contrast partition based on the density of the region. To speed up the clustering algorithm, we use the branch-and-bound algorithm. We propose the bounds and formally prove their correctness. Experimental results show that the proposed method is at least as effective in quality of clustering as BIRCH, a bottom-up hierarchical clustering method, while reducing the number of page accesses by up to 26～187 times depending on the size of the database. As a result, we believe that the proposed method significantly improves the clustering performance in large databases and is practically usable in various database applications.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1314-1323
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• 1999

컴퓨터의 사용이 일반화됨에 따라 데이타를 생성하고 수집하는 것이 용이해졌다. 이에 따라 데이타로부터 자동적으로 유용한 지식을 얻는 기술이 필요하게 되었다. 데이타 마이닝에서 얻어진 지식은 정확성과 이해성을 충족해야 한다. 본 논문에서는 데이타 마이닝을 위하여 퍼지 결정트리에 기반한 효율적인 퍼지 규칙을 생성하는 알고리즘을 제안한다. 퍼지 결정트리는 ID3와 C4.5의 이해성과 퍼지이론의 추론과 표현력을 결합한 방법이다. 특히, 퍼지 규칙은 속성 축에 평행하게 판단 경계선을 결정하는 방법으로는 어려운 속성 축에 평행하지 않는 경계선을 갖는 패턴을 효율적으로 분류한다. 제안된 알고리즘은 첫째, 각 속성 데이타의 히스토그램 분석을 통해 적절한 소속함수를 생성한다. 둘째, 주어진 소속함수를 바탕으로 ID3와 C4.5와 유사한 방법으로 퍼지 결정트리를 생성한다. 또한, 유전자 알고리즘을 이용하여 소속함수를 조율한다. IRIS 데이타, Wisconsin breast cancer 데이타, credit screening 데이타 등 벤치마크 데이타들에 대한 실험 결과 제안된 방법이 C4.5 방법을 포함한 다른 방법보다 성능과 규칙의 이해성에서 보다 효율적임을 보인다.Abstract With an extended use of computers, we can easily generate and collect data. There is a need to acquire useful knowledge from data automatically. In data mining the acquired knowledge needs to be both accurate and comprehensible. In this paper, we propose an efficient fuzzy rule generation algorithm based on fuzzy decision tree for data mining. We combine the comprehensibility of rules generated based on decision tree such as ID3 and C4.5 and the expressive power of fuzzy sets. Particularly, fuzzy rules allow us to effectively classify patterns of non-axis-parallel decision boundaries, which are difficult to do using attribute-based classification methods.In our algorithm we first determine an appropriate set of membership functions for each attribute of data using histogram analysis. Given a set of membership functions then we construct a fuzzy decision tree in a similar way to that of ID3 and C4.5. We also apply genetic algorithm to tune the initial set of membership functions. We have experimented our algorithm with several benchmark data sets including the IRIS data, the Wisconsin breast cancer data, and the credit screening data. The experiment results show that our method is more efficient in performance and comprehensibility of rules compared with other methods including C4.5.