• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.323-328
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• 2004

The development of group-specific tissue probability maps (TPM) provides a priori knowledge for better result of cerebral tissue classification with regard to the inter-ethnic differences of inter-subject variability. We present sequential procedures of group-specific TPM and evaluate the age effects in the structural differences of TPM. We investigated 100 healthy volunteers with high resolution MRI scalming. The subjects were classified into young (60, 25.92+4.58) and old groups (40, 58.83${\pm}$8.10) according to the age. To avoid any bias from random selected single subject and improve registration robustness, average atlas as target for TPM was constructed from skull-stripped whole data using linear and nonlinear registration of AIR. Each subject was segmented into binary images of gray matter, white matter, and cerebrospinal fluid using fuzzy clustering and normalized into the space of average atlas. The probability images were the means of these binary images, and contained values in the range of zero to one. A TPM of a given tissue is a spatial probability distribution representing a certain subject population. In the spatial distribution of tissue probability according to the threshold of probability, the old group exhibited enlarged ventricles and overall GM atrophy as age-specific changes, compared to the young group. Our results are generally consistent with the few published studies on age differences in the brain morphology. The more similar the morphology of the subject is to the average of the population represented by the TPM, the better the entire classification procedure should work. Therefore, we suggest that group-specific TPM should be used as a priori information for the cerebral tissue classification.

• The Journal of Advanced Prosthodontics
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• v.9 no.5
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• pp.321-327
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• 2017

PURPOSE. The aim of this study was to investigate dental arch dimensions and to classify arch shape in Korean young adults. MATERIALS AND METHODS. The sample included 50 Koreans with age ranging from 24 to 32 years. Maxillary and mandibular casts were fabricated using irreversible hydrocolloid and type III dental stones. Incisor-canine distance, $incisor-1^{st}$ molar distance, $incisor-2^{nd}$ molar distance, intercanine distance, $inter-1^{st}$ molar distance, and $inter-2^{nd}$ molar distance in both the maxillary and mandibular arch were measured using a three-dimensional measuring device. The dental arch was classified into three groups using five ratios from the measured values by the K-means clustering method. The data were analyzed with one-way analysis of variance. RESULTS. Arch lengths (IM2D, $incisal-2^{nd}$ molar distance) were 44.13 mm in the maxilla and 40.40 mm in the mandible. Arch widths (M2W, inter $2^{nd}$ molar width) were 64.12 mm in the maxilla and 56.37 mm in the mandible. Distribution of the dental arch form was mostly ovoid shape (maxilla 52% and mandible 56%), followed by the V-shape and the U-shape. The arch width for the U-shape was broader than for the other forms. CONCLUSION. This study establishes new reference data for dental arch dimensions for young Korean adults. The most common arch form is the ovoid type in the maxilla and mandible of Koreans. Clinicians should be aware of these references and classify arch type before and during their dental treatment for effective and harmonized results in Koreans.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.3
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• pp.14-28
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• 2010

The aim of this study is to investigate crime hotspot areas using the spatio-temporal cluster analysis which is possible to search simultaneously time range as well as space range as an alternative method of existing hotspot analysis only identifying crime occurrence distribution patterns in urban area. As for research method, first, crime data were collected from criminal registers provided by official police authority in M city, Gyeongnam and crime occurrence patterns were drafted on a map by using Geographic Information Systems(GIS). Second, by utilizing Ripley K-function and Space-Time Scan Statistics analysis, the spatio-temporal distribution of crime was examined. The results showed that the risk of crime was significantly clustered at relatively few places and the spatio-temporal clustered areas of crime were different from those predicted by existing spatial hotspot analysis such as kernel density analysis and k-means clustering analysis. Finally, it is expected that the results of this study can be not only utilized as a valuable reference data for establishing urban planning and crime prevention through environmental design(CPTED), but also made available for the allocation of police resources and the improvement of public security services.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.77-96
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• 2011

An exhibition is defined as market events for specific duration to present exhibitors' main products to business or private visitors, and it plays a key role as effective marketing channels. As the importance of exhibition is getting more and more, domestic exhibition industry has achieved such a great quantitative growth. But, In contrast to the quantitative growth of domestic exhibition industry, the qualitative growth of Exhibition has not achieved competent growth. In order to improve the quality of exhibition, we need to understand the preference or behavior characteristics of visitors and to increase the level of visitors' attention and satisfaction through the understanding of visitors. So, in this paper, we used the observation survey method which is a kind of field research to understand visitors and collect the real data for the analysis of behavior pattern. And this research proposed the following methodology framework consisting of three steps. First step is to select a suitable exhibition to apply for our method. Second step is to implement the observation survey method. And we collect the real data for further analysis. In this paper, we conducted the observation survey method to obtain the real data of the KIDS & EDU EXPO for Children in SETEC. Our methodology was conducted on 160 visitors and 78 booths from November 4th to 6th in 2010. And, the last step is to analyze the record data through observation. In this step, we analyze the feature of exhibition using Demographic Characteristics collected by observation survey method at first. And then we analyze the individual booth features by the records of visited booth. Through the analysis of individual booth features, we can figure out what kind of events attract the attention of visitors and what kind of marketing activities affect the behavior pattern of visitors. But, since previous research considered only individual features influenced by exhibition, the research about the correlation among features is not performed much. So, in this research, additional analysis is carried out to supplement the existing research with data mining techniques. And we analyze the relation among booths using data mining techniques to know behavior patterns of visitors. Among data mining techniques, we make use of two data mining techniques, such as clustering analysis and ARM(Association Rule Mining) analysis. In clustering analysis, we use K-means algorithm to figure out the correlation among booths. Through data mining techniques, we figure out that there are two important features to affect visitors' behavior patterns in exhibition. One is the geographical features of booths. The other is the exhibit contents of booths. Those features are considered when the organizer of exhibition plans next exhibition. Therefore, the results of our analysis are expected to provide guideline to understanding visitors and some valuable insights for the exhibition from the earlier phases of exhibition planning. Also, this research would be a good way to increase the quality of visitor satisfaction. Visitors' movement paths, booth location, and distances between each booth are considered to plan next exhibition in advance. This research was conducted at the KIDS & EDU EXPO for Children in SETEC(Seoul Trade Exhibition & Convention), but it has some constraints to be applied directly to other exhibitions. Also, the results were derived from a limited number of data samples. In order to obtain more accurate and reliable results, it is necessary to conduct more experiments based on larger data samples and exhibitions on a variety of genres.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.1-14
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• 2017

In Korea, the soil series derived from sedimentary rocks are classified into seven soil series of coarse loamy soil such as Dain, Danbug, Dongam, Imdong, Jeomgog, Maryeong, and Yonggog; seventeen soil series of fine loamy soil such as Angye, Anmi, Banho, Bigog, Deoggog, Dogye, Dojeon, Gamgog, Gugog, Jincheon, Maji, Mungyeong, Oggye, Samam, Yanggog, Yeongwol, and Yulgog; six soil series of fine silty soil such as Goryeong, Bonggog, Juggog, Gyeongsan, Yuga, and Yugog; and four soil series of clayey soil such as Mitan, Pyeongan, Pyeongjeon, and Uji. All thirty-four soil series have different drainage rates and topography. However, the soil texture depends on the parent rock. The buffer functions in GIS (Geographic Information System) techniques were used to calculate adjacent soil series from a soil series. The length of the adjacent soil series was adjusted because a side of the buffer area was one meter long. The cluster analysis was conducted using the CCC (Cubic Clustering Criterion) method, in which the number of clusters is calculated based on the individual soil series ratio. Soil survey has been carried out since 1964 as "The reconnaissance soil survey", and 1:5,000 detailed soil survey was completed in 1999 with a five-years plan in Korea. Today, all the soil survey information has been computerized. GIS techniques were used to establish a digital soil map; however, there have not been any studies to interpret pedogenesis using the GIS technique. In this study, the area of the adjacent soil series were obtained using the GIS technique. The area of the adjacent soil series can be calculated based on the information area. The similarities of soil originated from sedimentary rocks were estimated using the length. As a result, the distribution of grain size was different based on the types of sedimentary rocks and the location. The clusters were distinguished into limestone, sandstone, and shale. In addition, the soil derived from shale was divided into red shale and gray shale. This means that quantitative interpretation of the catena and this established method can be used to interpret the relationship between soil series.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.377-393
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• 2016

Vehicle emissions have been known as a critical factor to give a negative impact on the public health. In particular, particulate matters(PM) and NOx are highly related with respiratory diseases such as asthma. This study aimed at analyzing spatio-temporal patterns of PM and NOx generated from urban freeway traffic. MOVES, which is a well-known emission analysis tool presented by US Environmental Protection Agency(EPA), was applied to estimate PM and NOx based on traffic volume and speed data obtained from Seoul Outer Ring Expressway during January~June, 2012. K-means clustering analysis was used for categorizing the Level of Vehicle Emissions(LOVE) to support more systematical identification of the significance of emissions. Then, spatio-temporal analyses of estimated emissions were conducted by LOVE. Finally, this study proposed a set of strategies to reduce both PM and NOx to enhance public health based on analysis results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.740-748
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• 2016

IT and communication technologies has contributed significantly to the convenience of passengers and the financial management of stations in accordance with the task automation in the field of the urban railway system. The foundation of the above development is based on the large amounts of data from various sensors installed in railways, trains, and stations. In particular, the sensor network that is installed in the station and train has played an important role in the railway information system. The performance of AP is affected by the number of APs and their locations installed in the station. In the installation of APs in stations, the intensity of the radio wave of the AP on its underlying position is considered to determine the number and position of APs. This paper proposes a method to estimate the number of APs and their position based on the structure of the underlying station and implemented a simulator to simulate the performance of the proposed method. The implemented simulator was applied to the decision of AP installation at Busan Seomyeon station to evaluate its performance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.1
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• pp.25-33
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• 2020

A drought event is characterized by duration, severity and affected area. In general, after calculating a drought index using hydro-meteorological time series at a station, a drought event is defined based on the run theory to identify the beginning and end time. However, this one-dimensional analysis has limitations for analyzing the spatio-temporal occurrence characteristics and movement paths of drought. Therefore, this study is to define a three-dimensional drought event using a simple clustering algorithm and to develop a drought map that can be used to understand the drought severity according to the spatio-temporal expansion of drought. As a result, compared with the two-dimensional monitoring information to show spatial distribution of drought index, a proposed drought map is able to show three-dimensional drought characteristics inclusing drought duration, spatial cumulative severity, and centroid of drought. The analysis of drought map indicated that there was a drought event which had the affected area less than 10 % while on occations while there were 11 drought events (44 %) which had the affected area more a than 90 % of the total area. This means that it is important to understand the relationship between spatial variation of drought affected area and severity corresponding to various drought durations. The development of drought map based on three-dimensional drought analysis is useful to analyze the spatio-temporal occurrence characteristics and propagation patterns of regional drought which can be utilized in developing mitigation measures for future extreme droughts.

• Journal of Gifted/Talented Education
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• v.21 no.3
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• pp.773-796
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• 2011

This study examined the thinking styles of scientifically gifted students on the basis of Sternberg's theory of mental self-government, and the relationship between thinking styles and self-regulated learning ability of the students and their scientific inquiry ability by the different types of thinking styles. 110 middle school students who belonging to the university science-gifted education center participated in this study. 13 thinking styles were postulated that fall along 5 dimensions which are functions, forms, levels, scopes and leanings of the mental self-government. Scientifically gifted students responded to the Thinking Style Inventory (TSI) that standardized Korean version, Self-regulated Ability Inventory and Test of Science Inquiry Skills Inventory (TSIS). The results indicated that scientifically gifted students prefer legislative, liberal, external, hierarchical and judical thinking styles, rather than conservative style. This result also showed that subscales of thinking styles were significantly correlated with self-regulated learning ability and scientific inquiry ability. The legislative style, hierarchical style, local style and liberal style were significant predictors of self-regulation learning ability. The legislative style was significant predictor, whereas oligarchic style was negative predictor of scientific inquiry ability. The results of k-means clustering analysis and MANOVA showed that the self-regulated learning ability and scientific inquiry ability were significantly correlated with the pattern and level of thinking style.

• Journal of the Korea Society of Computer and Information
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• v.18 no.6
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• pp.21-28
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• 2013

This paper proposes an effective fire detection approach that includes the following multiple heterogeneous algorithms: moving region detection using grey level histograms, color segmentation using fuzzy c-means clustering (FCM), feature extraction using a grey level co-occurrence matrix (GLCM), and fire classification using support vector machine (SVM). The proposed approach determines the optimal threshold values based on grey level histograms in order to detect moving regions, and then performs color segmentation in the CIE LAB color space by applying the FCM. These steps help to specify candidate regions of fire. We then extract features of fire using the GLCM and these features are used as inputs of SVM to classify fire or non-fire. We evaluate the proposed approach by comparing it with two state-of-the-art fire detection algorithms in terms of the fire detection rate (or percentages of true positive, PTP) and the false fire detection rate (or percentages of true negative, PTN). Experimental results indicated that the proposed approach outperformed conventional fire detection algorithms by yielding 97.94% for PTP and 4.63% for PTN, respectively.