• Korean Chemical Engineering Research
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• v.55 no.5
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• pp.646-651
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• 2017

Size and shape of carbon nanotube (CNT) agglomerates in the dilute phase of a bubbling fluidized bed ($0.15m\;i.d{\times}2.6m\;high$) have been determined by the laser sheet technique. Axial solid holdup distribution of the CNT particles showed S curve with dense phase and dilute phase in bubbling fluidization regime. Heywood diameter and Feret diameter of the CNT agglomerates in the dilute phase of bubbling fluidized bed increased with increasing gas velocity. The CNT particle number in the agglomerates increased with increasing of gas velocity. Aspect ratio increased and circularity, roundness and solidity decreased with increasing of gas velocity. A possible mechanism of agglomerates formation was proposed based on the obtained information.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.6
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• pp.486-491
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• 2013

This paper proposes a fast and efficient Haar-like feature selection algorithm for training classifier used in object detection. Many features selected by Haar-like feature selection algorithm and existing AdaBoost algorithm are either similar in shape or overlapping due to considering only feature's error rate. The proposed algorithm calculates similarity of features by their shape and distance between features. Fast and efficient feature selection is made possible by removing selected features and features with high similarity from feature set. FERET face database is used to compare performance of classifiers trained by previous algorithm and proposed algorithm. Experimental results show improved performance comparing classifier trained by proposed method to classifier trained by previous method. When classifier is trained to show same performance, proposed method shows 20% reduction of features used in classification.

• The Journal of the Korea Contents Association
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• v.11 no.2
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• pp.31-39
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• 2011

The facial recognition algorithms using Gabor wavelet based face graph produce very good performance while they have some weakness such as a large amount of computation and an irregular result depend on initial location. We proposed a fully automatic facial recognition algorithm using a Gabor feature based geometric deformable face graph matching. The initial location and size of a face graph can be selected using Adaboost detection results for speed-up. To find the best face graph with the face model graph by updating the size and location of the graph, the geometric transformable parameters are defined. The best parameters for an optimal face graph are derived using an optimization technique. The simulation results show that the proposed algorithm can produce very good performance with recognition rate 96.7% and recognition speed 0.26 sec for FERET database.

• Water for future
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• v.27 no.3
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• pp.115-121
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• 1994

Cohesie sediment movement in estuarine systems is strongly affected by the phenomena of aggregation and flocculation. Aggregation is the process where primary particles are clustered together in tightly-packed formations; flocculation is the process where aggregates and single particles are bonded together to form large particle groups of very low specific density. The size, shape and strength of the flocculants control the rate of deposition and the processes of pollutant exchange between suspended sediments and ambient water. In estuarine waters, suspended sediments above the lutocline form the mobile suspension zone while below the lutocline they form the stationary suspension zone. Suspended particles in the mobile zone are generally in a dispersed state and the controlling forces are the Brownian motion and the turbulent flow fluctuations. In the stationary suspension zone, the driving force is the gravity. This paper discusses the settling and particle flocculation characteristics under quiescient flow conditions. Particles are entering the study domain randomly. Particles in the mobile suspension zone are simulated by using the Smoluchowski's model. Flocs created in the mobil suspension zone are moving into the stationary suspension zone where viscosity and drag effects are important. Utilizing the concepts of the maximum Feret's diameter and the Minkowski's sausage logic, the fractal dimension of the flocs within the stationary suspension is estimated and then compared with results obtained by other studies.

• Korean Chemical Engineering Research
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• v.57 no.1
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• pp.105-110
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• 2019

Effect of height on the size and shape of carbon nanotube (CNT) aggregates in the freeboard region of a bubbling fluidized bed ($0.15m\;i.d.{\times}2.6m\;high$) has been determined. Feret diameter and Heywood diameter of the CNT aggregates in the freeboard region of fluidized bed increased with increasing gas velocity. The average aggregate diameters and CNT particle number in the aggregates decreased with increasing of height in the freeboard. Aspect ratio increased as the location was closer to the surface of the dense phase, but decreased at the highest location. Solidity did not show any significant changes with height. The results showed the aggregates formation process is affected by the height in the freeboard. A correlation was proposed to predict the Heywood diameter of the CNT aggregates.

• The korean journal of orthodontics
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• v.40 no.2
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• pp.106-114
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• 2010

Objective: The aim of this experimental study was to evaluate the effects of direct electrical current stimulation (DECS) on bone regeneration in response to an expansion of the inter-premaxillary suture in the rat. Methods: Sixteen 50 - 60 days old Wistar male rats were separated into two equal groups (control and experimental). Both groups were subjected to expansion, and 30-gram of force was applied to the maxillary incisors with helical-spring. In the experimental group, two metallic-screws were placed at lateral parts of the maxillary segments. Electrodes were connected to the screws. The device was activated with current adjustment to measure $10{\mu}A$ continuously and the current was monitored daily during the expansion and early-retention phase. Bone regeneration in the sutural area was histomorphometrically evaluated including new-bone area (${\mu}m^2$), bone perimeter (${\mu}m$), feret's diameter (${\mu}m$) and newly formed bone (%) parameters. Kruskal-Wallis rank and Mann-Whitney U tests were used for statistical evaluation at p < 0.05 level. Results: Statistical analysis showed significant differences between groups for all investigated histomorphometric parameters. New bone area (p = 0.002), bone perimeter (p = 0.004), feret's diameter (p = 0.002) and newly formed bone percentage (p = 0.002) measurements were significantly higher in the experimental group than the control group. Bone histomorphometric measurements revealed that bone architecture in the DECS group was improved. Conclusions: The application of DECS to an orthopedically expanded inter-premaxillary suture area during the early retention phase stimulated the formation of new bone.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.828-835
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• 2008

We present a novel method for eye location by means of a two-level classifier scheme. Locating the eye by machine-inspection of an image or video is an important problem for Computer Vision and is of particular value to applications in biomedical imaging. Our method aims to overcome the significant challenge of an eye-location that is able to maintain high accuracy by disregarding highly variable changes in the environment. A first level of computational analysis processes this image context. This is followed by object detection by means of a two-class discrimination classifier(second algorithmic level).We have tested our eye location system using FERET and BioID database. We compare the performance of two-level classifier with that of non-level classifier, and found it's better performance.

• Journal of Korea Multimedia Society
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• v.18 no.9
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• pp.1039-1046
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• 2015

We propose a feature generation method for low-resolution face recognition. For this, we first generate new features from the input features (pixels) of a low-resolution face image by adding the higher-order terms. Then, we evaluate the separability of both of the original input features and new features by computing the discriminant distance of each feature. Finally, new data sample used for recognition consists of the features with high separability. The experimental results for the FERET, CMU-PIE and Yale B databases show that the proposed method gives good recognition performance for low-resolution face images compared with other method.

• Journal of Korea Multimedia Society
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• v.18 no.7
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• pp.834-842
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• 2015

We propose a method to construct composite feature vector based on discriminant analysis for face recognition. For this, we first extract the holistic- and local-features from whole face images and local images, which consist of the discriminant pixels, by using a discriminant feature extraction method. In order to utilize both advantages of holistic- and local-features, we evaluate the amount of the discriminative information in each feature and then construct a composite feature vector with only the features that contain a large amount of discriminative information. The experimental results for the FERET, CMU-PIE and Yale B databases show that the proposed composite feature vector has improvement of face recognition performance.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.427-430
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• 2005

본 연구는 기존 단일 생체인식의 단점을 보완하기 위해 다중생체인식(Multi-Modal Biometrics Recognition)기법을 연구한 것으로, 홍채영상을 이용한 홍채인식과 얼굴영상을 이용한 얼굴인식을 융합하기 위해 다양한 방법을 시도해 보았다. 이에, CBNU 홍채 영상데이터를 사용한 홍채인식은 Gabor Wavelet과 FLDA(Fuzzy Linear Discriminant Analysis)를 이용하였으며, FERET 얼굴영상데이터를 사용한 얼굴인식도 FLDA를 이용하여 패턴의 특징을 추출하고 matching에 따른 score를 각각 획득한다. 얻어진 두 score 값에 대하여 다양한 균등화과정을 사용해 보았으며, 다중생체인식 융합방법중 하나인 Weight sum rule을 적용하여 인식률을 얻었다. 또한, 단일 생체인식의 경우보다 좋은 성능을 나타냄을 확인하기 위해 FRR과 FAR등의 인식률 평가방법을 사용하였으며, 기존 단일생체인식 방법보다 좋은 성능을 보이고 있음을 확인할 수 있었다.