• Journal of Platform Technology
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• v.11 no.5
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• pp.59-71
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• 2023

This paper proposes a method of estimating the illumination chromaticity of a scene in which an image is taken. Storring and Bianco proposed a method of estimating illuminant chromaticity using skin color. Storring et al. used skin color distribution characteristics and black body locus, but there is a problem that the link between the locus and CIE-xy data is reduced. Bianco et al. estimated the illuminant chromaticity by comparing the skin color distribution in standard lighting with the skin color distribution in the input image. This method is difficult to measure and secure as much skin color as possible in various illumination. The proposed method can estimate the illuminant chromaticity for any input image by analyzing the relationship between the skin color information and the illuminant chromaticity. The estimation method is divided into an analysis stage and a test stage, and the data set was classified into an analysis group and a test group and used. Skin chromaticity is calculated by obtaining skin color areas from all input images of the analysis group, respectively. A mapping is obtained by analyzing the correlation between the average set of skin chromaticity and the reference illuminant chromaticity set. The calculated mapping is applied to all input images of the analysis group to estimate the illuminant chromaticity, calculate the error with the reference illuminant chromaticity, and repeat the above process until there is no change in the error to obtain a stable mapping. The obtained mapping is applied to the test group images similar to the analysis stage to estimate the illuminant chromaticity. Since there is no independent data set containing skin area and illuminant reference information, the experimental data set was made using some of the images of the Intel TAU data set. Compared to Finlayson, a similar theory-based existing method, it showed performance improvement of more than 40%, Zhang 11%, and Kim 16%.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.405-410
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• 2004

In mid-90's, the Korean government introduced the GIS(Geographic Information System) to digitalize every topography of national land and thereby, index locations and attributes of various urban facilities to construct a system whereby every information could be managed and operated in an integrated way, but the reliability of such geographic information has yet to be tested, much less its modification, complementation and maintenance. Under such circumstances, this study was aimed at constructing a reference point infrastructure for Seoul and Kyonggi area and comparing the data obtained from the GPS operation and various facility location data with the existing GIS data to address the problems of GIS operation and suggest their solutions. As a result of calculating the GPS reference point data and analyzing the deviations of the unknown point data in comparison with the fixed point ones, it was found that the horizontal location values were reliable within +/- 5cm, but that the above-sea level values varied as much as 1.4m depending on the deployment of pre-set fixed points determined by the direct level gauging. In addition, as a result of directly surveying major facilities around the roads based on the coordinates of the urban reference points networked with such a reference point system to check their conformity to existing data, it was confirmed that the difference was as wide as 2m. Such differences may be attributable to the fact that the data with their geographic information not confirmed are used as basic data for GIS. Hence, this study suggests the ways to set the absolute geographic data based on reference points and test the reliability of existing data and thereby, suggests a methods to solve the problems.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.237-242
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• 2005

Predicting the cellular location of an unknown protein gives a valuable information for inferring the possible function of the protein. For more accurate prediction system, we need a good feature extraction method that transforms the raw sequence data into the numerical feature vector, minimizing information loss. In this paper, we propose new methods of extracting underlying features only from the sequence data by computing pairwise sequence alignment scores. In addition, we use composition based features to improve prediction accuracy. To construct an SVM ensemble from separately trained SVM classifiers, we propose specificity based weighted majority voting. The overall prediction accuracy evaluated by the 5-fold cross-validation reached 88.53% for the eukaryotic animal data set. By comparing the prediction accuracy of various feature extraction methods, we could get the biological insight on the location of targeting information. Our numerical experiments confirm that our new feature extraction methods are very useful for predicting subcellular localization of proteins.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.198-203
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• 1998

This study, a sub-one of comprehensive research works titled under “Rural Resources Evaluation System”, tried to verify utility/applicability of the developed model system through the case study works on 3 sample villages, Backya, Uyan and Suyu, representing the lowland, upland and seashore villages respectively. From the various surveying and collecting works including the official/statistical data collection, map analysis, insitu investigation, field survey and written material review, the original data set were obtained and manipulated into final input data for resources grading. After then, by the automatized calculation procedure of “Rural Resources Evaluation System”, score results for resources evaluation were finally produced with the total maximum score being 1,000. Through comparing works among score results of 3 case villages and between score results and areal characteristics of each case village, the applicability of the system developed in this study was well confirmed.

• Journal of Veterinary Clinics
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• v.27 no.1
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• pp.71-78
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• 2010

Analysis of variance (ANOVA) is a method to analyze the data from the experimental designs comparing two or more groups or treatments at the same time, and is the most effective tool of analyzing more complex data sets with different source of variations. This article describes the logic of ANOVA, the application of the method to the analysis of a simple data set, and the methods available for performing planned or post hoc multiple comparisons between the treatments means. In addition, the common misuse of the techniques is also discussed to emphasize that an inappropriate statistical analysis is potentially far more harmful than poorly conducted research. Lastly, an example is given for illustration purposes.

• Journal of Korean Society for Atmospheric Environment
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• v.12 no.1
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• pp.67-77
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• 1996

Total suspended particulate matters (TSP) were collected based on a size segregation method by a cascade impactor for 6 consecutive years (form Dec. 1989 to sep. 1994) in the Kyung Hee University-Suwon Campus, and 6 trace metals (Ca, Si, Fe, Pb, Cu, Zn) were determined by an x-ray fluorescence spectroscopy. Total number of samples collected during the study are 118 sets and each set of sample comsists of 9 filters. The levels of TSP and 6 trace metals were then used to examine seasonal and annual variations with respects to their size distributions. For statistical analyses, raw data were initially transformed by both logarithmic and root transformating to approximately normalize them, and then size distribution functions for each trace element were separately developed season-to-season by a regression analysis in order to obtain maximum amount of physical information, Subsequently, each developed model was verified by comparing with supervised data collected on 1994. The result showed that each prediction model was in good agreement except the fall, partly due to lack of the data collected on fall, 1994.

• Journal of Multimedia Information System
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• v.6 no.1
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• pp.37-42
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• 2019

Skyline queries are used in a variety of fields to make optimal decisions. However, as the volume of data and the dimension of the data increase, the number of skyline points increases with the amount of time it takes to discover them. Mainly, because the number of skylines is essential in many real-life applications, various studies have been proposed. However, previous researches have used the k-parameter methods such as top-k and k-means to discover representative skyline points (RSPs) from entire skyline point set, resulting in high query response time and reduced representativeness due to k dependency. To solve this problem, we propose a new Connected Component Clustering based Representative Skyline Query (3CRS) that can discover RSP quickly even in high-dimensional data through connected component clustering. 3CRS performs fast discovery and clustering of skylines through hash indexes and connected components and selects RSPs from each cluster. This paper proves the superiority of the proposed method by comparing it with representative skyline queries using k-means and DBSCAN with the real-world dataset.

• Journal of Korean Society for Atmospheric Environment
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• v.12 no.3
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• pp.323-332
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• 1996

Precipitation samples were collected by the wet-only sampling method at Seoul from September 1993 to June 1995. Sample were analysed for the anions $(NO_3^-, NO_2^-, SO_4^{2-}, Cl^-, and F^-)$ and cations $(Na^+, K^+, Ca^{2+}, Mg^{2+}, and NH_4^+)$ in addition to pH and electric conductivity. In order to establish the chemical analysis data of high quality, the assurance checks for analytical data of precipitation were performed by considering the ion balance and by comparing the measured conductivity with the calculated conductivity. As we applied the various assurance checking methods by the ion balance used until recently to a data set measured in this study, the f value expressed as $\Sigma C/\Sigma A$ was found to be not appropriate for the data screening. Also, the scattering plot between cations and anions in each sample was found to show the general tendency of ion balance but was proved to not quantitate the standard of data screening at a data set of samples of various concentration levels. The h value defined as (A-C)/C for C $\geq$ A and (A-C)/A for C < A was used to check the ion balance. However, the standard of data screening by h value must very in response to total ion concentration of samples. In this study, the quality assurance of chemical analysis data was checked by considering both the ion balance of evaluating by h value and the conductivity balance. Further the quality control was achieved by these quality assurance methods. As the result, 67 samples among total 77 were obtained as valid. As the central tendency value for a statistical summary in the analytical parametr of samples, the volume-weighted mean value was found to represent more the general chemistry of precipitation rather than the arithmetic mean. The volume-weighted mean pH was 5.0 and 25% of samples was less than this mean. The concentrations of sufate and nitrate in precipitation were 90.4 ueq/L and 32.4 ueq/L which made up 59% and 21% of all anions. The raion of $SO_4^{2-}/(NO_3^- + NO_2^-)$ in precipitation was 2.7, which indicates that the contributions of $H_2SO_4$ and $HNO_3$ to the acidity of precipitation are 70% and 30%, respectively.

• Journal of Korea Multimedia Society
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• v.8 no.12
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• pp.1613-1622
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• 2005

Broadcasting is fundamental and effective data dissemination mechanism for route discovery, address resolution, and many other network services in mobile ad hoc networks. Although many approaches for broadcasting have been proposed to minimize the number of retransmissions, none of them guarantee the best-suited bounds of retransmissions. Appropriate use of probabilistic method can lower the chance of contention and collision among neighboring nodes, so that it reduces the number of rebroadcasts. In this paper, we propose a probabilistic approach that dynamically adjusts the rebroadcasting probability according to the distance between the sender and the receiver. While the rebroadcast probabilities of a mobile node close to sender will be set lower, the rebroadcast probabilities of a mobile node far away from sender wi1l be set to higher, The rebroadcast probability of a node wi1l be set according to the distance from sender. We evaluate the performance of proposed approach by comparing it with flooding as well as a fixed probabilistic broadcast approach. Simulation results showed that the performance of proposed scheme outperforms by about $70\%$ than flooding scheme and outperforms by about $20\%$ than fixed probabilistic scheme.

• Journal of Biomedical Engineering Research
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• v.28 no.5
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• pp.665-675
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• 2007

The morphological change of ECG is the important diagnostic parameter to finding the malfunction of a heart. Generally ST segment deviation is concerned with myocardial abnormality. The aim of this study is to detect the change of ST in shape using a polynomial approximation method and the reference ST type. The developed algorithm consists of feature point detection, ST level detection and ST shape classification. The detection of QRS complex is accomplished using it's the morphological characteristics such as the steep slope and high amplitude. The developed algorithm detects the ST level change, and then classifies the ST shape type using the polynomial approximation. The algorithm finds the least squares curve for the data between S wave and T wave in ECG. This curve is used for the classification of the ST shapes. ST type is classified by comparing the slopes of the specified points between the reference ST set and the least square curve. Through the result from the developed algorithm, we can know when the ST level change occurs and what the ST shape type is.