• Journal of KIISE:Software and Applications
• /
• v.34 no.6
• /
• pp.539-548
• /
• 2007

Mobile content adaptation is a technology of effectively representing the contents originally built for the desktop PC on wireless mobile devices. Previous approaches for Web content adaptation are mostly device-dependent. Also, the content transformation to suit to a smaller device is done manually. Furthermore, the same contents are provided to different users regardless of their individual preferences. As a result, the user has difficulty in selecting relevant information from a heavy volume of contents since the context information related to the content is not provided. To resolve these problems, this paper proposes an enhanced method of Web content adaptation for mobile devices. In our system, the process of Web content adaptation consists of 4 stages including block filtering, block title extraction, block content summarization, and personalization through learning. Learning is initiated when the user selects the full content menu from the content summary page. As a result of learning, personalization is realized by showing the information for the relevant block at the top of the content list. A series of experiments are performed to evaluate the content adaptation for a number of Web sites including online newspapers. The results of evaluation are satisfactory, both in block filtering accuracy and in user satisfaction by personalization.

• Journal of Korean Society for Geospatial Information Science
• /
• v.18 no.2
• /
• pp.29-33
• /
• 2010

The purpose of LiDAR ground classification is to archive both goals which are acquiring confident ground points with high precision and describing ground shape in detail. In spite of many studies about developing optimized algorithms to kick out this, it is very difficult to classify ground points and describing ground shape by airborne LiDAR data. Especially it is more difficult in a dense forested area like Korea. Principle misclassification was mainly caused by complex forest canopy hierarchy in Korea and relatively coarse LiDAR points density for ground classification. Unfortunately, a lot of LiDAR surveying performed in summer in South Korea. And by that reason, schematic LiDAR points distribution is very different from those of Europe. So, this study propose enhanced ground classification method considering Korean land cover characteristics. Firstly, this study designate highly confident candidated LiDAR points as a first ground points which is acquired by using big roller classification algorithm. Secondly, this study applied weighted gradient kernel(WGK) algorithm to find and include highly expected ground points from the remained candidate points. This study methods is very useful for reconstruct deformed terrain due to misclassification results by detecting and include important terrain model key points for describing ground shape at site. Especially in the case of deformed bank side of river area, this study showed highly enhanced classification and reconstruction results by using WGK algorithm.

• Journal of the Korea Society of Computer and Information
• /
• v.10 no.1 s.33
• /
• pp.93-100
• /
• 2005

This study is to desist and implement an efficient microbial medical image retrieval system based on knowledge and content of them which can make use of more accurate decision on colony as doll as efficient education for new techicians. For this. re first address overall inference to set up flexible search path using rule-base in order U redure time required original microbial identification by searching the fastest path of microbial identification phase based on heuristics knowledge. Next, we propose a color ffature gfraction mtU, which is able to extract color feature vectors of visual contents from a inn microbial image based on especially bacteria image using HSV color model. In addition, for better retrieval performance based on large microbial databases, we present an integrated indexing technique that combines with B+-tree for indexing simple attributes, inverted file structure for text medical keywords list, and scan-based filtering method for high dimensional color feature vectors. Finally. the implemented system shows the possibility to manage and retrieve the complex microbial images using knowledge and visual contents itself effectively. We expect to decrease rapidly Loaming time for elementary technicians by tell organizing knowledge of clinical fields through proposed system.

• The Journal of Society for e-Business Studies
• /
• v.8 no.4
• /
• pp.69-88
• /
• 2003

In high dimensional data, most of clustering algorithms tend to degrade the performance rapidly because of nature of sparsity and amount of noise. Recently, partial dimensional clustering algorithms have been studied, which have good performance in clustering. These algorithms select the dimensional data closely related to clustering but discard the dimensional data which are not directly related to clustering in entire dimensional data. However, the traditional algorithms have some problems. At first, the algorithms employ grid based techniques but the large amount of grids make worse the performance of algorithm in terms of computational time and memory space. Secondly, the algorithms explore dimensions related to clustering using k-medoid but it is very difficult to determine the best quality of k-medoids in large amount of high dimensional data. In this paper, we propose an efficient partial dimensional clustering algorithm which is called CLIP. CLIP explores dense regions for cluster on a certain dimension. Then, the algorithm probes dense regions on a next dimension. dependent on the dense regions of the explored dimension using incremental projection. CLIP repeats these probing work in all dimensions. Clustering by Incremental projection can prune the search space largely and reduce the computational time considerably. We evaluate the performance(efficiency, effectiveness and accuracy, etc.) of the proposed algorithm compared with other algorithms using common synthetic data.

• Korean Journal of Optics and Photonics
• /
• v.28 no.4
• /
• pp.158-165
• /
• 2017

The physical shape of an ultrasound transducer has not been considered in previous studies of the photoacoustic saturation effect, where a photoacoustic signal's magnitude linearly increases as an absorption coefficient increases and it is finally saturated. In this paper, the effect of a spherically focused ultrasound transducer on photoacoustic nonlinearity is investigated. The focused ultrasound transducer's spatial filtering effect on photoacoustic signals is analytically derived considering the combined concept of a virtual point detector and Green function approach. The ultrasound transducer's temporal response (i.e., transfer function) effect on photoacoustic signals is considered by integrating photoacoustic signal values within the absorption area covered by a spatial resolution of the ultrasound transducer. Results from the analytically derived expression show that the magnitude of photoacoustic signals measured by a spherical focused ultrasound transducer shows a maximum at a specific absorption coefficient, and decreases after that maximum point as an absorption coefficient is increased. The origin of this photoacoustic nonlinearity is physically understood by comparing the ultrasound transducer's transfer functions and photoacoustic resonance spectra. In addition, this physical interpretation implies that the photoacoustic nonlinearity is strongly dependent on the irradiance distribution inside an absorption medium.

• Journal of Biomedical Engineering Research
• /
• v.32 no.3
• /
• pp.245-250
• /
• 2011

Parallel imaging technique can provide several advantages for a multitude of MRI applications. Especially, in SENSE technique, sensitivity maps were always required in order to determine the reconstruction matrix, therefore, a number of difference approaches using sensitivity information from coils have been demonstrated to improve of image quality. Moreover, many filtering methods were proposed such as adaptive matched filter and nonlinear diffusion technique to optimize the suppression of background noise and to improve of image quality. In this study, we performed SENSE reconstruction using computer simulations to confirm the most suitable method for the feasibility of filtering effect and according to changing order of polynomial fit that were applied on variation of spatial resolution of sensitivity map. The image was obtained at 0.32T(Magfinder II, Genpia, Korea) MRI system using spin-echo pulse sequence(TR/TE = 500/20 ms, FOV = 300 mm, matrix = $128{\times}128$, thickness = 8 mm). For the simulation, obtained image was multiplied with four linear-array coil sensitivities which were formed of 2D-gaussian distribution and the image was complex white gaussian noise was added. Image processing was separated to apply two methods which were polynomial fitting and filtering according to spatial resolution of sensitivity map and each coil image was subsampled corresponding to reduction factor(r-factor) of 2 and 4. The results were compared to mean value of geomety factor(g-factor) and artifact power(AP) according to r-factor 2 and 4. Our results were represented while changing of spatial resolution of sensitivity map and r-factor, polynomial fit methods were represented the better results compared with general filtering methods. Although our result had limitation of computer simulation study instead of applying to experiment and coil geometric array such as linear, our method may be useful for determination of optimal sensitivity map in a linear coil array.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.5
• /
• pp.444-450
• /
• 2015

The accuracy of small and low cost CCD camera is insufficient to provide data for precisely tracking unmanned aerial vehicles(UAVs). This study shows how UAV can hover on a human targeted tracking object by using CCD camera rather than imprecise GPS data. To realize this, UAVs need to recognize their attitude and position in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for an UAV to estimate of his attitude by environment recognition for UAV hovering, as one of the best important problems. In this paper, we describe a method for the attitude of an UAV using image information of a maker on the floor. This method combines the observed position from GPS sensors and the estimated attitude from the images captured by a fixed camera to estimate an UAV. Using the a priori known path of an UAV in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a marker on the floor and the estimated UAV's attitude. Since the equations are based on the estimated position, the measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the UAV. The Kalman filter scheme is applied for this method. its performance is verified by the image processing results and the experiment.

• Geophysics and Geophysical Exploration
• /
• v.2 no.4
• /
• pp.184-190
• /
• 1999

A study of gas hydrate is a worldwide popular interesting subject as a potential energy source. A seismic survey for gas hydrate have performed over the East sea by the KIGAM since 1997. General indicators of natural submarine gas hydrates in seismic data is commonly inferred from the BSR (Bottom Simulating Reflection) that occurred parallel to the see floor, amplitude decrease at the top of the BSR, amplitude Blanking at the bottom of the BSR, decrease of the interval velocity, and the reflection phase reversal at the BSR. So the seismic data processing for detecting gas hydrates indicators is required the true amplitude recovery processing, a accurate velocity analysis and the AVO (Amplitude Variation with Offset) analysis. In this paper, we had processed the field data to detect the gas hydrate indicators, which had been acquired over the East sea in 1998. Applied processing modules are spherical divergence, band pass filtering, CDP sorting and accurate velocity analysis. The AVO analysis was excluded, since this field data had too short offset to apply the AVO analysis. The accurate velocity analysis was performed by XVA (X-window based Velocity Analysis). This is the method which calculate the velocity spectrum by iterative and interactive. With XVA, we could determine accurate stacking velocity. Geobit 2.9.5 developed by the KIGAM was used for processing data. Processing results say that the BSR occurred parallel to the sea floor were shown at $367\~477m$ depths (two way travel time about 1800 ms) from the sea floor through shot point 1650-1900, the interval velocity decrease around BSR and the reflection phase reversal corresponding to the reflection at the sea floor.

• Spatial Information Research
• /
• v.20 no.3
• /
• pp.27-38
• /
• 2012

As the necessity of forest conservation and management has been increased, various forest studies using LIDAR data have been actively performed. These studies often utilize the tree height as an important parameter to measure the forest quantitatively. This study thus attempt to apply two representative methods to estimate tree height from airborne LIDAR data and compare the results. The first method based on the detection of the individual trees using a local maximum filter estimates the number of trees, the position and heights of the individual trees, and the mean tree height. The other method estimates the maximum and mean tree height, and the crown mean height for each grid cell or the entire area from the canopy height model (CHM) and height histogram. In comparison with the field measurements, 76.6% of the individual trees are detected correctly; and the estimated heights of all trees and only conifer trees show the RMSE of 1.91m and 0.75m, respectively. The tree mean heights estimated from CHM retain about 1~2m RMSE, and the histogram method underestimates the tree mean height with about 0.6m. For more accurate derivation of diverse forest information, we should select and integrate the complimentary methods appropriate to the tree types and estimation parameters.

• Journal of the Microelectronics and Packaging Society
• /
• v.12 no.2 s.35
• /
• pp.105-109
• /
• 2005

A compact antenna switch module for GSM/DCS dual band applications based on multilayer low temperature co-fired ceramic (LTCC) substrate is presented. Its size is $4.5{\times}3.2{\times}0.8 mm^3$ and insertion loss is lower than 1.0 dB at Rx mode and 1.2 dB at Tx mode. To verify the stability of the developed module to the process window, each block that is diplexer, LPF's and bias circuit is measured by probing method in the variation with the thickness of ceramic layer and the correlation between each block is quantified by calculating the VSWR In the mean while, two types of bias circuits -lumped and distributed - are compared. The measurement of each block and the calculation of VSWR give good information on the behavior of full module. The reaction of diplexer to the thickness is similar to those of LPF's and bias circuit, which means good relative matching and low value of VSWR, so total insertion loss is maintained in quite wide range of the thickness of ceramic layer at both band. And lumped type bias circuit has smaller insertion itself and better correspondence with other circuit than distributed stripline structure. Evaluated ceramic module adopting lumped type bias circuit has low insertion loss and wider stability region of thickness over than 6um and this can be suitable for the mass production. Stability characterization by probing method can be applied widely to the development of ceramic modules with embedded passives in them.