• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.529-542
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• 2000

Recent years, the use of multimedia information is rapidly increasing, and the video media is the most rising one than any others, and this field Integrates all the media into a single data stream. Though the availability of digital video is raised largely, it is very difficult for users to make the effective video access, due to its length and unstructured video format. Thus, the minimal interaction of users and the explicit definition of video structure is a key requirement in the lately developing image and video management systems. This paper defines the terms and hierarchical video structure, and presents the system, which construct the clustering-based video hierarchy, which facilitate users by browsing the summary and do a random access to the video content. Instead of using a single feature and domain-specific thresholds, we use multiple features that have complementary relationship for each other and clustering-based methods that use normalization so as to interact with users minimally. The stage of shot boundary detection extracts multiple features, performs the adaptive filtering process for each features to enhance the performance by eliminating the false factors, and does k-means clustering with two classes. The shot list of a result after the proposed procedure is represented as the video hierarchy by the intelligent unsupervised clustering technique. We experimented the static and the dynamic movie videos that represent characteristics of various video types. In the result of shot boundary detection, we had almost more than 95% good performance, and had also rood result in the video hierarchy.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.315-324
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• 2011

In Web environment, a flood of spam causes serious social problems such as personal information leak, monetary loss from fishing and distribution of harmful contents. Moreover, types and techniques of spam distribution which must be controlled are varying as days go by. The learning based spam classification method using Bag-of-Words model is the most widely used method until now. However, this method is vulnerable to anti-spam avoidance techniques, which recent spams commonly have, because it classifies spam documents utilizing only keyword occurrence information from classification model training process. In this paper, we propose a spam document detection method using a characteristic of repeating words occurring in spam documents as a solution of anti-spam avoidance techniques. Recently, most spam documents have a trend of repeating key phrases that are designed to spread, and this trend can be used as a measure in classifying spam documents. In this paper, we define six variables, which represent a characteristic of word repetition, and use those variables as a feature set for constructing a classification model. The effectiveness of proposed method is evaluated by an experiment with blog posts and E-mail data. The result of experiment shows that the proposed method outperforms other approaches.

• Journal of Radiation Protection and Research
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• v.37 no.1
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• pp.10-15
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• 2012

Design and performance test results of a newly developed optically stimulated luminescence (OSL) measurement system are presented in this paper. Generally, different types of optical filters are used in OSL reader system to minimize the interference of the stimulation light in the OSL signal. For optically stimulation of $Al_2O_3:C$, we have arrived at an optimal combination of the filters, i.e., GG420 filter for filtering the stimulating light source, and a combined UG11 and BG39 filter at the detecting window (PMT). By using a high luminance blue LED (Luxeon V), sufficient luminous intensity could be obtained for optically stimulation. By using various control boards, the OSL reader device was successfully interfaced with a personal computer. A software was developed to deliver required commands to operate the OSL reader by using the LabView program (National Instruments, Inc.). In order to evaluate the reliability and the reproducibility of newly designed-OSL reader. Performance testing of the OSL reader was carried out for OSL efficiency, OSL decay curve and signal to noise ratio of the standard $Al_2O_3:C$ OSL material. It was found to be comparable with that of commercial Riso reader system.

• Journal of Korean Society of Forest Science
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• v.101 no.4
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• pp.547-557
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• 2012

This study purposed to estimate the forest biomass using k-Nearest Neighbor (k-NN) algorithm. Multiple data sources were used for the analysis such as forest type map, field survey data and Landsat TM data. The accuracy of forest biomass was evaluated with the forest stratification, horizontal reference area (HRA) and spatial filtering. Forests were divided into 3 types such as conifers, broadleaved, and Korean pine (Pinus koriansis) forests. The applied radii of HRA were 4 km, 5 km and 10 km, respectively. The estimated biomass and mean bias for conifers forest was 222 t/ha and 1.8 t/ha when the value of k=8, the radius of HRA was 4 km, and $5{\times}5$ modal was filtered. The estimated forest biomass of Korean pine was 245 t/ha when the value of k=8, the radius of HRA was 4km. The estimated mean biomass and mean bias for broadleaved forests were 251 t/ha and -1.6 t/ha, respectively, when the value of k=6, the radius of HRA was 10 km. The estimated total forest biomass by k-NN method was 799,000t and 237 t/ha. The estimated mean biomass by ${\kappa}NN$method was about 1t/ha more than that of filed survey data.

• Fashion & Textile Research Journal
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• v.13 no.4
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• pp.600-613
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• 2011

The purpose of this study is to provide Torso pattern for Korean middle-aged women using 3D human body scan data. 155 women in their 40's or 50's were measured by Martin's anthropometry. Merging the data of 914 middle aged women provided by Korean agency for technology and standards, total of 1,069 subjects' data were analyzed. For data analysis, ANOVA, factor analysis and cluster analysis were done using SPSS PC+. And representative subject of each cluster was selected and they participated in 3D scanning and Torso pattern suggested for middle-aged women Torso pattern which investing the amount of ease according to each group for diffuse front interscye 30%, armscye circumference 30%, back interscye 40% using 3D human body scan data. The results of this study are as follows. Firstly, as a result of the factor analysis, the first factor was 'obesity index of body', The second factor was 'verticality size of body', The third factor was 'verticality length of upper bodice', The fourth factor was 'drop value to represent silhouette', and the fifth factor was 'physique of upper bodice'. And, middle-aged women type were classified 3 types according to the cluster analysis. Type 1(Y-type) was the long upper Torso with wide shoulder. Type 2(H-type) was flat-body type with comparatively thin upper bodice and thin lower bodice. And type 3(A-type) was the obese type with comparatively thin upper bodice and fat lower bodice. Secondly, using CAD program, point filtering was performed and approximated surface model was made. It used that generated surface smoothing corrected for abnormally extruded points and scattered points based on the curvature information. And 3D surfaces were flatted onto the plane by the internal tools of CAD program. Difference ratios of outline length and area between 3D curves and 2D plane were 0.42% and 0.54%, respectively. Third, wearing test by the sensory evaluation showed that distinct difference almost every category. The movement functionality test shows that, in all the tests which reveal significant differences, especially, 'comparison pattern A' experienced inconvenience to neck width and neck depth.

• Journal of KIISE:Databases
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• v.41 no.4
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• pp.249-255
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• 2014

Copy number variations(CNVs) are a recently recognized class of human structural variations and are associated with a variety of human diseases, including cancer. To find important cancer genes, researchers identify novel CNVs in patients with a particular cancer and analyze large amounts of genomic and clinical data. We present a tool called CNVDAT which is able to detect CNVs from NGS data and systematically analyze the genomic and clinical data associated with variations. CNVDAT consists of two modules, CNV Detection Engine and Sequence Analyser. CNV Detection Engine extracts CNVs by using the multi-resolution system of scale-space filtering, enabling the detection of the types and the exact locations of CNVs of all sizes even when the coverage level of read data is low. Sequence Analyser is a user-friendly program to view and compare variation regions between tumor and matched normal samples. It also provides a complete analysis function of refGene and OMIM data and makes it possible to discover CNV-gene-phenotype relationships. CNVDAT source code is freely available from http://dblab.hallym.ac.kr/CNVDAT/.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.27 no.4
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• pp.269-282
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• 2017

Objectives: Currently, masks against yellow dust and fine particulates are being certified with no consideration of facial dimensional variations among children and adults. The aims of this study were to develop masks against yellow dust and fine particulates for children in Korea and provide basic data to suggest new test methods for mask certification that consider the breathing capacity of children. Methods: A total of 730 study participants aged from six to 13 years old were recruited in the Seoul, Gyeonggi, and Incheon region. This study used a 3D scanning instrument to obtain 16 facial anthropometric data points. Literature reviews, a comparison of breathing capacity between adults and children, and analysis of children's pulmonary physiological data were conducted in order to suggest new test standards for certifying children's masks against yellow dust and fine particulates. In addition, types of children's masks, choice of wearing a mask or not, and reasons for not wearing masks were surveyed. Results: Based on a clustering analysis of participants' facial dimensions, facial shapes were classified into three groups: small, medium, and large. The sizes of children's masks were subtracted by using 3D sketch techniques(Large: $121.25mm{\times}89.46mm$, Medium: $111.92mm{\times}78.55mm$, Small: $102.13mm{\times}72.87mm$). In certifying children's mask, flow rates of $60{\ell}/m$ for the filtering efficiency test and $20{\ell}/m$ for the breathing resistance test were recommended, since children's pulmonary physiological capacity is about 60-70% of adults' pulmonary capacity. Conclusions: The results of this study suggest that three mask sizes for children would be sufficient and practical for providing protection against yellow dust and fine particulates. Revising current test methods for certifying respiratory protective devices for children is important, since children's pulmonary physiological capacity substantially differs from that of adults. Therefore, it is recommended that new test standards for certifying children's masks be promulgated in the near future.

• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.318-326
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• 2005

This paper presents the image feature extraction method and the image classification technique to select the harmful image flowed from the Internet by grade of image contents such as harmlessness, sex-appealing, harmfulness (nude), serious harmfulness (adult) by the characteristic of the image. In this paper, we suggest skin area detection technique to recognize whether an input image is harmful or not. We also propose the ROI detection algorithm that establishes region of interest to reduce some noise and extracts harmful degree effectively and defines the characteristics in the ROI area inside. And this paper suggests the multiple-SVM training method that creates the image classification model to select as 4 types of class defined above. This paper presents the multiple-SVM classification algorithm that categorizes harmful grade of input data with suggested classification model. We suggest the skin likelihood image made of the shape information of the skin area image and the color information of the skin ratio image specially. And we propose the image feature vector to use in the characteristic category at a course of traininB resizing the skin likelihood image. Finally, this paper presents the performance evaluation of experiment result, and proves the suitability of grading image using image feature classification algorithm.

• KSBB Journal
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• v.22 no.2
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• pp.102-108
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• 2007

A sewage was treated using a vertical flow zeolite-filled reed bed. The sewage from the student dormitory of Changwon National University was fed into the reed bed for 10 minutes every 6 hours at the hydraulic load of $314L/m^3{\cdot}$day. The filtering height of the reed bed was 100 em and the zeolite mixture was filled in the reed bed. The mixture consisted of the same volume of two types of zeolite: 0.5$\sim$1 mm and 1$\sim$3 mm in diameter. Annual average removal efficiency was 88 89.9%, $COD_{Cr}$ 86.1 %, $COD_{Mn}$ 81.2%, T-N 34.0%, $NH_4^+$-N 97.3% and T-P 34.6%. T-N of effluent was mostly $NO_3^-$-N and the concentration of $NO_2^-$-N in effluent was lower than 0.1 mg/L. All removal efficiencies did not show a remarkable seasonal change. The ranking of phosphorous fractions fixed to the zeolite in column test was Ca-P > Fe-P > reductant soluble Fe-P > occluded P > saloid P > AI-P at all depths of the filter. All phosphorous fractions except for AI-P reduced at deeper filter layer, while their content ratios increased at deeper filter layer. Organic matter content was the highest at the highest layer (0$\sim$5 cm from the top of the filter) and only small differences were observed at the deeper filter layer than 5 em from the top. Organic matter content increased at all depths of the filter with the operating time.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.18-25
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• 2014

To increase wireless capacity, the concurrent use of multiple wireless interfaces on different frequency bands, called aggregation, can be considered. In this paper, we focus on aggregation of multiple Wi-Fi interfaces with packet-level traffic spreading between the interfaces. Two aggregation schemes, link bonding and multipath TCP (MPTCP), are tested and compared in a dualband Wi-Fi radio system with their Linux implementation. Various test conditions such as traffic types, network delay, locations, interface failures and configuration parameters are considered. Experimental results show that aggregation increases throughput performance significantly over the use of a single interface. Link bonding achieves lower throughput than MPTCP due to duplicate TCP acknowledgements (ACKs) resulting from packet reordering and filtering such duplicate ACKs out is considered as a possible solution. However, link bonding is fast responsive to links' status changes such as a link failure. It is shown that different combinations of interface weights for packet spread in link bonding result in different throughput performance, envisioning a spatio-temporal adaptation of the weights. We also develop a mathematical model of power consumption and compare the power efficiency of the schemes applying different power consumption profiles.