• Journal of Mechanical Science and Technology
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• v.19 no.2
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• pp.716-727
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• 2005

Comprehensive measurements for velocity and temperature fields have been conducted. A Micro PIV 2-color LIF system have been setup to measure the buoyancy driven fields in a 1-mm heated channel with low Grashof-Prandtl numbers [$86]. Fluorescence microscopy is combined with an MPIV system to obtain enough intensity images and clear pictures from nano-scale fluorescence particles. The spatial resolution of the Micro PIV system is $75{\mu}m\;by\;67{\mu}m$ and error due to Brownian motion is estimated $1.05\%$. Temperature measurements have achieved the $4.7\;{\mu}m$ spatial resolution with relatively large data uncertainties the present experiment. The measurement uncertainties have been decreased down to less than ${\pm}1.0^{\circ}C$ when measurement resolution is equivalent to $76\;{\mu}m$. Measured velocity and temperature fields will be compared with numerical results to examine the feasibility of development as a diagnostic technique.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.7
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• pp.189-195
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• 2000

For free motions, vibration suppression of flexible manipulators has been one of the hottest research topics. However, for constrained motions, a little effort has been devoted for vibration suppression control. Using the dependency of elastic deflections of links on contact force under static conditions, vibrations for constrained planar two-link flexible manipulators have been suppressed successfully by controlling the contact force. However, for constrained spatial multi-link flexible manipulators, the vibrations cannot be suppressed by only controlling the contact force. So, the aim of this paper is to clarify the vibration mechanism of a constrained, multi-DOF, flexible manipulator and to devise the suppression method. We apply a concise hybrid position/force control scheme to control a flexible manipulator modeled by lumped-parameter modeling method. Finally, a comparison between simulation and experimental results is presented to show the performance of our method.

• The Journal of Information Technology
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• v.5 no.2
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• pp.69-80
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• 2002

Conventionally, we have used an acoustic microscope at single operating frequency. The resolution and quality of the measured images are determined by transducer of the microscope. In this paper, we have studied Vertical Resolution Enhancement with Acoustic Reflection Microscope using combining bases of support for SFR(Spatial Frequency Response). Increased Vertical resolution can be obtained by taking three-dimensional images at more that one frequency and numerically combining the results. As results of the experiment, we could get enhanced images with the rate of contrast in proportion to the changing rate of depth.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.525-527
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• 2003

Recently, the spatial resolution of earth observation satellites is significantly increased to a few meters. Such high spatial resolution images definitely will provide lots of information for detail-thirsty remote sensing users. However, it is more difficult to develop automated image algorithms for automated image feature extraction and pattern recognition. In this study, we propose a two-stage procedure to extract road information from high resolution satellite images. At first stage, a watershed segmentation technique is developed to classify the image into various regions. Then, a knowledge is built for road and used to extract the road regions. In this study, we use panchromatic and multi-spectral images of the IKONOS satellite as test dataset. The experiment result shows that the proposed technique can generate suitable and meaningful road objects from high spatial resolution satellite images. Apparently, misclassified regions such as parking lots are recognized as road needed further refinement in future research.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.455-457
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• 2019

In this paper we study the effect of decomposed spatiotemporal convolutions for action recognition in videos. Our motivation emerges from the empirical observation that spatial convolution applied on solo frames of the video provide good performance in action recognition. In this research we empirically show the accuracy of factorized convolution on individual frames of video for action classification. We take 3D ResNet-18 as base line model for our experiment, factorize its 3D convolution to 2D (Spatial) and 1D (Temporal) convolution. We train the model from scratch using Kinetics video dataset. We then fine-tune the model on UCF-101 dataset and evaluate the performance. Our results show good accuracy similar to that of the state of the art algorithms on Kinetics and UCF-101 datasets.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.235-244
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• 2022

Many new techniques have been adopted in HEVC (High efficiency video coding) standard, such as quadtree-structured coding unit (CU), prediction unit (PU) partition, 35 intra-mode, and so on. To reduce computational complexity, the paper proposes two optimization algorithms which include fast CU depth range decision and fast PU partition mode decision. Firstly, depth range of CU is predicted according to spatial-temporal correlation. Secondly, we utilize the depth difference between the current CU and CU corresponding to the same position of adjacent frame for PU mode range selection. The number of traversal candidate modes is reduced. The experiment result shows the proposed algorithm obtains a lot of time reducing, and the loss of coding efficiency is inappreciable.

• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.643-652
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• 2006

Decision trees are mainly used for the classification and prediction in data mining. The distribution of spatial data and relationships with their neighborhoods are very important when conducting classification for spatial data mining in the real world. Spatial decision trees in previous works have been designed for reflecting spatial data characteristic by rating Euclidean distance. But it only explains the distance of objects in spatial dimension so that it is hard to represent the distribution of spatial data and their relationships. This paper proposes a decision tree based on spatial entropy that represents the distribution of spatial data with the dispersion and dissimilarity. The dispersion presents the distribution of spatial objects within the belonged class. And dissimilarity indicates the distribution and its relationship with other classes. The rate of dispersion by dissimilarity presents that how related spatial distribution and classified data with non-spatial attributes we. Our experiment evaluates accuracy and building time of a decision tree as compared to previous methods. We achieve an improvement in performance by about 18%, 11%, respectively.

• Korean Institute of Interior Design Journal
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• v.26 no.5
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• pp.83-92
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• 2017

This research is about the characteristics of the saccades that occurring in the process of observing the spatial. The size of the saccades is the visual activity for acquiring the information, and the search trace that left by the spatial visitor. Reviewed over the saccade through the analysis of observation process that appeared in the eye-tracking experiment of sports store from the department store, the saccade is defined as the sight movement in the process of finding a component to view in the spatial. If some spatial component induces saccade, and able to know which specific component acquired through the saccade, then the designer will have a clue which able to provide the spatial desired by the consumer. The results of analyzing the process in the deriving the spatial component and saccade characteristic from industrial space, can be summarised as follows. The first, the average fixed number of [IN].[OUT] zone appeared similarly, and it leads to knowing that the time used for attention with one frequency is about 0.3 seconds. Second, there were more saccades toward [$IN{\rightarrow}OUT$] (13 persons, 76.5%) than [$OUT{\rightarrow}IN$] (4 persons, 23.5%). The Los Angeles area has lots of interesting things to watch, so it able to thinks to begins with small saccade and then occur to bigger saccade activity to find new interests shortly after [OUT] saccade. Third, according to time range changes, keep eyes on the characteristics of saccade, [IN].[OUT] frequency has slightly decreased the changes of viewing time, but there was no significant change in an average number of observations. This means that the frequency and the number of observations are decreased together. Therefore, it can be seen that the amount of information to be acquired (frequency) is decreased (count) as the observation time elapses.

• Spatial Information Research
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• v.14 no.1 s.36
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• pp.85-94
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• 2006

Image fusion techniques are widely used to integrate a lower spatial resolution multispectral image with a higher spatial resolution panchromatic image. However, the existing techniques either cannot avoid distorting the image spectral properties or involve complicated and time-consuming decomposition and reconstruction processing in the case of wavelet transform-based fusion. In this study a simple spectral preserve fusion technique: the Smoothing Filter-based Replacement(SFR) is proposed based on a simplified solar radiation and land surface reflection model. By using a ratio between a higher resolution image and its low pass filtered (with a smoothing filter) image, spatial details can be injected to a co-registered lower resolution multispectral image minimizing its spectral properties and contrast. The technique can be applied to improve spatial resolution for either colour composites or individual bands. The fidelity to spectral property and the spatial quality of SFM are convincingly demonstrated by an image fusion experiment using IKONOS panchromatic and multispectral images. The visual evaluation and statistical analysis compared with other image fusion techniques confirmed that SFR is a better fusion technique for preserving spectral information.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.385-392
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• 2011

Recently, the concern of IT-in-Agriculture convergence technology that combines information technology and agriculture is increasing rapidly. Especially, the crop cultivation related prediction services by spatial data mining (SDM) can play an important role in reducing the damage of natural disaster and enhancing crop productivity. However, the data conversion and integration procedure to acquire the learning dataset of SDM for the prediction service need a lot of effort and time, because of their heterogeneity between distributed data. In addition, calculating spatial neighborhood relationships between spatial and non-spatial data necessitates requires the complicated calculation procedure for large dataset. In this paper, we suggest a SOA-based data integration framework that can effectively integrate distributed heterogeneous data by treating each data source as a service unit and support to find the optimal prediction service by improving productivity of learning dataset for SDM. In our experiment, we confirmed that our framework can be effectively applied to find the optimal prediction service for the frost damage area, by considering the case of peach crop cultivation in Icheon in Korea.