• The Journal of the Korea Contents Association
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• v.6 no.6
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• pp.1-8
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• 2006

This paper presents an intelligent pattern matching method that can be used to acquire the reliable calibration data for automatic PCB pattern inspection. The inaccurate calibration data is often acquired by geometric pattern variations and selecting an inappropriate model manual. It makes low the confidence of inspection and also the inspection processing time has been delayed. In this paper, the geometric features of PCB patterns are utilized to calculate the accurate calibration data. An appropriate model is selected automatically based on the geometric features, and then the calibration data to be invariant to the geometric variations(translation, rotation, scaling) is calculated. The method can save the inspection time unnecessary by eliminating the need for manual model selection. As the result, it makes a fast, accurate and reliable inspection of PCB patterns.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.2
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• pp.93-100
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• 2014

3D object recognition using only 2D images is a difficult work because each images are generated different to according to the view direction of cameras. Because SIFT algorithm defines the local features of the projected images, recognition result is particularly limited in case of input images with strong perspective transformation. In this paper, we propose the object recognition method that improves SIFT algorithm by using several sequential images captured from rotating 3D object around a rotation axis. We use the geometric relationship between adjacent images and merge several images into a generated feature space during recognizing object. To clarify effectiveness of the proposed algorithm, we keep constantly the camera position and illumination conditions. This method can recognize the appearance of 3D objects that previous approach can not recognize with usually SIFT algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.271-274
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• 2006

This paper deals with a similarity decision method between the shape of hand-postures and their structures to improve performance of the vision-based hand-posture recognition system. Hand-posture recognition by vision sensors has difficulties since the human hand is an object with high degrees of freedom, and hence grabbed images present complex self-occlusion effects and, even for one hand-posture, various appearances according to viewing directions. Therefore many approaches limit the relative angle between cameras and hands or use multiple cameras. The former approach, however, restricts user's operation area. The latter requires additional considerations on the way of merging the results from each camera image to get the final recognition result. To recognize hand-postures, we use both of appearance and structural features and decide the similarity between the two types of features by learning.

• Advances in aircraft and spacecraft science
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• v.5 no.3
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• pp.363-383
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• 2018

One-dimensional (1D) models of incompressible flows, can be of interest for many applications in which fast resolution times are demanded, such as fluid-structure interaction of flows in compliant pipes and hemodynamics. This work proposes a higher-order 1D theory for the flow-field analysis of incompressible, laminar, and viscous fluids in rigid pipes. This methodology is developed in the domain of the Carrera Unified Formulation (CUF), which was first employed in structural mechanics. In the framework of 1D modelling, CUF allows to express the primary variables (i.e., velocity and pressure fields in the case of incompressible flows) as arbitrary expansions of the generalized unknowns, which are functions of the 1D computational domain coordinate. As a consequence, the governing equations can be expressed in terms of fundamental nuclei, which are invariant of the theory approximation order. Several numerical examples are considered for validating this novel methodology, including simple Poiseuille flows in circular pipes and more complex velocity/pressure profiles of Stokes fluids into non-conventional computational domains. The attention is mainly focused on the use of hierarchical McLaurin polynomials as well as piece-wise nonlocal Lagrange expansions of the generalized unknowns across the pipe section. The preliminary results show the great advantages in terms of computational costs of the proposed method. Furthermore, they provide enough confidence for future extensions to more complex fluid-dynamics problems and fluid-structure interaction analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.620-626
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• 2008

We propose a feature map method to detect a collision for a motion-based game. The feature map can be made an optimally reduced motion data using subtraction image and virtual ball images according to image size and condition. And we calculate the overlapped ratio between moving image data and objects. This ratio is an invariant for detection even though image size is changed. And we compare this ration with collision detection constant, the feature map can detect fast collisions as well as the collided direction. To evaluate the method, we implemented a motion-base game that consists of a web cam, a player, an enemy, and some virtual balls, and we obtained some valid results for our method for the collision detection. The results demonstrated that the proposed approach is robust, and they can be used as a basic collide detection algorithm for a motion-based game where the size and the position of characters are continuously changing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1095-1100
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• 2008

In a process of insect foot recognition, footprint segments as basic areas for recognition need to be extracted from scanned insect footprints and appropriate features should be found from the footprint segments in order to discriminate kinds of insects, because the characteristics of the features are important to classify insects. In this paper, we propose methods for automatic footprint segmentation and feature extraction. We use a Trace transform method in order to find out appropriate features from the extracted segments by the above methods. The Trace transform method builds a new type of data structure from the segmented images by functions using parallel trace lines and the new type of data structure has characteristics invariant to translation, rotation and reflection of images. This data structure is converted to Triple features by Diametric and Circus functions, and the Triple features are used for discriminating patterns of insect footprints. In this paper, we show that the Triple features found by the proposed methods are enough distinguishable and appropriate for classifying kinds of insects.

• Journal of agriculture & life science
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• v.43 no.4
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• pp.9-14
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• 2009

The purpose of this study was to estimate height growth pattern and to derive site index equation for Pinus densiflora grown at Mt. Osu region, Chungnam. A total of 21 repre - sentative trees from the established temporary plots around Boryeng and Cheongyang regions were destructively sampled to measure diameter, height, volume growth per 1-year interval by using of DTRS- 2000 measurement instrument. The Schnute growth function was select ed for height growth prediction using 181 height-age paired observations and derived anamorphic base age invariant site index curves (base index age 30 years). The fitted index and the asymptotic value of Schnute model indicated both 0.96 and 10.8 meter, respectively. The results suggested in this study could be very useful to understand the height growth pattern and productivity of the site quality on Pinus densiflora grown at Mt. Osu region, Chungnam.

• Korean Journal of Remote Sensing
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• v.22 no.1
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• pp.1-10
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• 2006

During the northern burning season, biomass burning is found north of the equator, while satellite estimates from the residual-type method such as the CCD method show higher ozone south of the equator. This discrepancy is called the tropical Atlantic paradox (Thompson et ai., 2000). We use satellite and ground-based measurements to investigate the paradox. When the background tropospheric ozone over the Pacific Ocean from TOMS measurements is subtracted from the latitudinal total ozone distribution (e.g. TOMS-Pacific method), the results show remarkable agreement with the latitudinal stratospheric ozone distribution using the CCD method. The latitudinal tropospheric ozone distribution using the CCD method, with a persistent maximum over the southern tropical Atlantic, is also seen in the latitudinal tropospheric ozone distribution using the TOMS-Pacific method. It suggests that the complicated CCD method can be replaced by the simple TOMS-Pacific method. However, the tropical Atlantic paradox exists in the results of both the CCD and TOMS-Pacific methods during the northern buming season. In order to investigate this paradox, we compare the latitudinal ozone distributions using the CCD and TOMS-Pacific methods by using the SAGE measurements (e.g. TOMS-SAGE method) and the SHADOZ ozonesoundings (e.g. TOMS-Sonde method) assuming zonally invariant stratospheric ozone, which is the same assumption as of the CCD method. During the northern burning season, the latitudinal distributions in the tropospheric ozone derived from the TOMS-SAGE and TOMS-Sonde methods show higher tropospheric ozone over the northern tropical Atlantic than the southern Atlantic due to a stronger gradient in stratospheric ozone relative to that from the CCD and TOMS-Pacific methods. This indicates that the latitudinal tropospheric ozone distribution can be changed depending on the data that is used to determine the latitudinal stratospheric ozone distribution. Therefore, there is a possibility that the north-south gradient in stratospheric ozone over the Atlantic can be a solution of the paradox.

• Smart Structures and Systems
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• v.13 no.2
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• pp.219-233
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• 2014

In a companion paper, Pasala and Nagarajaiah analytically and experimentally validate the Adaptive Length Pendulum Smart Tuned Mass Damper (ALP-STMD) on a primary structure (2 story steel structure) whose frequencies are time invariant (Pasala and Nagarajaiah 2012). In this paper, the ALP-STMD effectiveness on a primary structure whose frequencies are time varying is studied experimentally. This study experimentally validates the ability of an ALP-STMD to adequately control a structural system in the presence of real time changes in primary stiffness that are detected by a real time observer based system identification. The experiments implement the newly developed Adaptive Length Pendulum Smart Tuned Mass Damper (ALP-STMD) which was first introduced and developed by Nagarajaiah (2009), Nagarajaiah and Pasala (2010) and Nagarajaiah et al. (2010). The ALP-STMD employs a mass pendulum of variable length which can be tuned in real time to the parameters of the system using sensor feedback. The tuning action is made possible by applying a current to a shape memory alloy wire changing the effective length that supports the damper mass assembly in real time. Once a stiffness change in the structural system is detected by an open loop observer, the ALP-STMD is re-tuned to the modified system parameters which successfully reduce the response of the primary system. Significant performance improvement is illustrated for the stiffness modified system, which undergoes the re-tuning adaptation, when compared to the stiffness modified system without adaptive re-tuning.

• KSCI Review
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• v.14 no.1
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• pp.265-271
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• 2006

In this paper, we propose a new automatic fingerprint identification system that identifies individuals in large databases. The algorithm consists of three steps: preprocessing, classification, and matching, in the classification, we present a new classification technique based on the statistical approach for directional image distribution. In matching, we also describe improved minutiae candidate pair extraction algorithm that is faster and more accurate than existing algorithm. In matching stage, we extract fingerprint minutiaes from its thinned image for accuracy, and introduce matching process using minutiae linking information. Introduction of linking information into the minutiae matching process is a simple but accurate way, which solves the problem of reference minutiae pair selection in comparison stage of two fingerprints quickly. This algorithm is invariant to translation and rotation of fingerprint. The proposed system was tested on 1000 fingerprint images from the semiconductor chip style scanner. Experimental results reveal false acceptance rate is decreased and genuine acceptance rate is increased than existing method.