• 한국산업융합학회 논문집
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• 제8권3호
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• pp.143-148
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• 2005

This paper presents a hybrid method for recognizing the faces by using principal component analysis(PCA) and fixed-point independent component analysis(FP-ICA). PCA is used to whiten the data, which reduces the effects of second-order statistics to the nonlinearities. FP-ICA is applied to extract the statistically independent features of face image. The proposed method has been applied to the problems for recognizing the 20 face images(10 persons * 2 scenes) of 324*243 pixels from Yale face database. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed method has a superior recognition performances(speed, rate). The negative angle has been relatively achieved more an accurate similarity than city-block or Euclidean.

• 한국물환경학회지
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• 제24권4호
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• pp.430-435
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• 2008

In order to design Non-point source management, the aspect of statistical features of the entire precipitation data should be focused since non-point source discharge is driven by continuous rainfall runoffs. 3-parameter mixed exponential probability density function is used to establish urban stormwater capture curve instead of previous single-parameter exponential PDF. Then, recent 10-year data in Busan are applied to establish the curve. The result shows that 3-parameter mixed PDF gives better resolution.

• 제어로봇시스템학회논문지
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• 제22권11호
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• pp.883-887
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• 2016

Navigating an unknown environment is a challenging task for a robot, especially when a large number of obstacles exist and the odometry lacks reliability. Pose tracking allows the robot to determine its location relative to its previous location. The ICP (iterative closest point) has been a powerful method for matching two point clouds and determining the transformation matrix between the maps. However, in a situation where odometry is not available and the robot moves far from its original location, the ICP fails to calculate the exact displacement. In this paper, we suggest a method that is able to match two different point clouds taken a long distance apart. Without using any odometry information, it only exploits the features of corner points containing information on the surroundings. The algorithm is fast enough to run in real time.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.153-155
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• 2003

Laser scanning has become a viable technique for the collection of a large amount of accurate 3D point data densely distributed on the scanned object surface. The inherent 3D nature of the sub-randomly distributed point cloud provides abundant spatial information. To explore valuable spatial information from laser scanned data becomes an active research topic, for instance extracting digital elevation model, building models, and vegetation volumes. The sub-randomly distributed point cloud should be segmented and classified before the extraction of spatial information. This paper investigates some exist segmentation methods, and then proposes an octree-based split-and-merge segmentation method to divide lidar data into clusters belonging to 3D planes. Therefore, the classification of lidar data can be performed based on the derived attributes of extracted 3D planes. The test results of both ground and airborne lidar data show the potential of applying this method to extract spatial features from lidar data.

• Journal of Power Electronics
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• 제19권4호
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• pp.944-955
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• 2019

In this paper, the three-level T-type neutral-point-clamped indirect matrix converter topology and the relative space vector modulation methods are introduced to improve the voltage transfer ratio and output voltage performance. The presented converter topology is based on combinations of cascaded-rectifier and three-level T-type neutral-point-clamp inverter. It can overcome the limitation of voltage transfer ratio of the conventional matrix converter and the high voltage rating of power switches of conventional matrix converter. Two SVPWM strategies for proposed converter are described in this paper to achieve the advantages features such as: sinusoidal input/output currents and three-level output voltage waveforms. Results from Psim 9.0 software simulation are provided to confirm the theoretical analysis. Hence, a laboratory prototype was implemented, and the experimental results are shown to validate the simulation results and to verify the effectiveness of the proposed topology and modulation strategies.

• 천문학회보
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• 제44권1호
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• pp.67.4-67.4
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• 2019

We present preliminary results of our long-term (2009-2017) observing campaign using the NASA IRTF at Mauna Kea, to obtain $2-5{\mu}m$ spectroscopy of ~200 red point sources in the line of sight to the Galactic center. Point sources in our sample were selected from the mid-infrared images of the Spitzer Space telescope, and include candidate massive young stellar objects, which have previously been identified from our Spitzer/IRS spectroscopy. We show high foreground extinction of these sources from deep $3.1{\mu}m$ H2O ice and aliphatic hydrocarbon absorption features, suggesting that they are likely located in the central 300 pc region of the Galactic center. While many sources reveal photospheric $2.3{\mu}m$ gas CO absorption, few of them clearly indicate $3.54{\mu}m$ CH3OH ice absorption, possibly indicating a large dust column density intrinsic to a massive young stellar object.

• 로봇학회논문지
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• 제16권2호
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• pp.130-136
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• 2021

In recent years, much study has been conducted in robotic grasping. The grasping algorithms based on deep learning have shown better grasping performance than the traditional ones. However, deep learning-based algorithms require a lot of data and time for training. In this study, a grasping algorithm using an artificial neural network-based graspability estimator is proposed. This graspability estimator can be trained with a small number of data by using a neural network based on the residual blocks and point clouds containing the shapes of objects, not RGB images containing various features. The trained graspability estimator can measures graspability of objects and choose the best one to grasp. It was experimentally shown that the proposed algorithm has a success rate of 90% and a cycle time of 12 sec for one grasp, which indicates that it is an efficient grasping algorithm.

• 제어로봇시스템학회논문지
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• 제20권9호
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• pp.957-963
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• 2014

This paper proposes a predictive control for an efficient human following robot using Kinect sensor. Especially, this research is focused on detecting of foot-end-point and foot-vector instead of human body which can be occluded easily by the obstacles. Recognition of the foot-end-point by the Kinect sensor is reliable since the two feet images can be utilized, which increases the detection possibility of the human motion. Depth image features and a decision tree have been utilized to estimate the foot end-point precisely. A tracking point average algorithm is also adopted in this research to estimate the location of foot accurately. Using the continuous locations of foot, the human motion trajectory is estimated to guide the mobile robot along a smooth path to the human. It is verified through the experiments that detecting foot-end-point is more reliable and efficient than detecting the human body. Finally, the tracking performance of the mobile robot is demonstrated with a human motion along an 'L' shape course.

• 제어로봇시스템학회논문지
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• 제21권10호
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• pp.958-964
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• 2015

In this paper, an object recognition method based on the depth information from the RGB-D camera, Xtion, is proposed for an indoor mobile robot. First, the RANdom SAmple Consensus (RANSAC) algorithm is applied to the point cloud obtained from the RGB-D camera to detect and remove the floor points. Next, the removed point cloud is classified by the k-means clustering method as each object's point cloud, and the normal vector of each point is obtained by using the k-d tree search. The obtained normal vectors are classified by the trained multi-layer perceptron as 18 classes and used as features for object recognition. To distinguish an object from another object, the similarity between them is measured by using Levenshtein distance. To verify the effectiveness and feasibility of the proposed object recognition method, the experiments are carried out with several similar boxes.

• International Journal of Aeronautical and Space Sciences
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• 제18권3호
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• pp.403-413
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• 2017

Dual-point aerodynamic design optimization is conducted for DLR-F6 wing-body-nacelle-pylon configuration adopting an efficient surface mesh movement method for complex junction geometries. A three-dimensional unstructured Euler solver and its discrete adjoint code are utilized for flow and sensitivity analysis, respectively. Considered design conditions are a low-lift condition and a cruise condition in a transonic regime. Design objective is to minimize drag and reduce shock strength at both flow conditions. Shape deformation is made by variation of the section shapes of inboard wing and pylon, nacelle vertical location and nacelle pitch angle. Hicks-Henne shape functions are employed for deformation of the section shapes of wing and pylon. By the design optimization, drag coefficients were remarkably reduced at both design conditions retaining specified lift coefficient and satisfying other constraints. Two-point design results show mixed features of the one-point design results at low-lift condition and cruise conditions.