• Journal of the Korean Data and Information Science Society
• /
• v.15 no.1
• /
• pp.83-94
• /
• 2004

In this study we analyze categorical data by means of spatial statistics and echelon analysis. To do this, we first determine the hierarchical structure of a given contingency table by using echelon dendrogram then, we detect candidates of hotspots given as the top echelon in the dendrogram. Next, we evaluate spatial scan statistics for the zones of significantly high or low rates based on the likelihood ratio. Finally, we detect hotspots of any size and shape based on spatial scan statistics.

• Journal of the Korean Data and Information Science Society
• /
• v.17 no.1
• /
• pp.131-139
• /
• 2006

Statistical analyses for spatial data are important features for various types of fields. Spatial data are taken at specific locations or within specific regions and their relative positions are recorded. Lattice data are synoptic observation covering an entire spatial region, like cancer rates corresponding to each county in a state. The main purpose of this paper is to detect hotspots for the region with significantly high or low rates. Kulldorff(1997) detected hotspots based on circular spatial scan statistics. We propose a new method to find any shapes of hotspots by use of echelon analysis with spatial scan statistics.

• 한국데이터정보과학회:학술대회논문집
• /
• 2004.04a
• /
• pp.183-194
• /
• 2004

본 연구에서는 공간 검색 통계량(spatial scan statistics)과 에셜론 해석법을 이용한 범주형 자료분석을 다룬다. 이를 위해 우선, 에셜론 덴드로그램을 이용하여 주어진 분활표의 계층적 구조(hierarchical structure)를 결정하고서 이로부터 핫스팟(hotspot)의 후보를 검출한다. 다음으로 우도비(likelihood ratio)를 기초로 유의하게 높거나 낮게 나타나는 지역에 대한 공간 검색 통계량을 산출한다. 마지막으로, 이 통계량을 바탕으로 핫스팟을 검출한다.

• Communications for Statistical Applications and Methods
• /
• v.25 no.4
• /
• pp.373-383
• /
• 2018

The spatial scan statistic is a widely used method to detect spatial clusters. The method imposes a large number of scanning windows with pre-defined shapes and varying sizes on the entire study region. The likelihood ratio test statistic comparing inside versus outside each window is then calculated and the window with the maximum value of test statistic becomes the most likely cluster. The results of cluster detection respond sensitively to the shape and the maximum size of scanning windows. The shape of scanning window has been extensively studied; however, there has been relatively little attention on the maximum scanning window size (MSWS) or maximum reported cluster size (MRCS). The Gini coefficient has recently been proposed by Han et al. (International Journal of Health Geographics, 15, 27, 2016) as a powerful tool to determine the optimal value of MRCS for the Poisson-based spatial scan statistic. In this paper, we apply the Gini coefficient to normal-based spatial scan statistics. Through a simulation study, we evaluate the performance of the proposed method. We illustrate the method using a real data example of female colorectal cancer incidence rates in South Korea for the year 2009.

• Journal of Digital Convergence
• /
• v.20 no.3
• /
• pp.75-83
• /
• 2022

Korea, which has the highest pedestrian fatality rate among OECD countries, is making efforts to improve the safe walking environment by enacting laws focusing on pedestrian. Spatial clustering was conducted with scan statistics after examining the social network data related to traffic accidents for children and seniors. The word cloud was used to examine people's recognition Campaigns for children and literature survey for seniors were in main concern. Naedang and Yongsan are the regions with the highest relative risk of weak pedestrian for children and seniors. On the contrary, Bongmu and Beomeo are the lowest relative risk region. Naedang-dong and Yongsan-dong of Daegu Metropolitan City were identified as vulnerable areas for pedestrian safety due to the high risk of pedestrian accidents for children and the elderly. This means that the scan statistics are effective in searching for traffic accident risk areas.

• The KIPS Transactions:PartC
• /
• v.8C no.5
• /
• pp.543-550
• /
• 2001

In this paper, an improved detection system for the network vulnerability scan attacks is proposed. The proposed system improves the methodology for detecting the network vulnerability scan attacks and provides a global detection and response capability that can counter attacks occurring across an entire network enterprize. Through the simulation, we show that the proposed system can detect vulnerable port attacks, coordinated attacks, slow scans and slow coordinated attacks. We also show our system can achieve more global and hierarchical response to attacks through the correlation between server and agents than a stand-alone system can make.

• Journal of the Korean Geographical Society
• /
• v.49 no.2
• /
• pp.275-298
• /
• 2014

This paper aims to delineate Central Business District(CBD) and subcentres of Seoul and compare the functional differences of them by spatial scan statistics. Most existing studies to delimit Seoul CBD have two limits in the methods to make boundaries. First, most Seoul CBD-defining studies presuppose some central area contains CBD and look into just that area in a concentrating manner because it is too difficult to collect the data in a whole city boundary. Therefore the CBD areas have been localized in that study areas. But I analysed the data of the whole area of Seoul and was able to define the CBD and subcentres of Seoul. Second, I analysed the data by a spatial scan statistics technique and was able to minimize the number of subjective items in constructing some conditions for CBD. The CBD area in this study is enlarged eastward over East Gate, a national treasure in Seoul, than the areas in existing studies. In the contrary, westwardly, our CBD is set back a little. The two competing central places in Seoul, CBD and Gangnam have some different specialized subareas. CBD has more governing authorities and wholesale stores and Gangnam has many conglomerates HQs, Offices and cosmetic clinics.

• Journal of Biomedical Engineering Research
• /
• v.39 no.3
• /
• pp.116-123
• /
• 2018

This study is a model experimental study using a phantom to propose an optimized brain CT scan protocol that can reduce the radiation dose of a patient and remain quality of image. We investigate the CT scan parameters of brain CT in clinical medical institutions and to measure the important parameters that determine the quality of CT images. We used 52 multislice spiral CT (SOMATOM Definition AS+, Siemens Healthcare, Germany). The scan parameters were tube voltage (kVp), tube current (mAs), scan time, slice thickness, pitch, and scan field of view (SFOV) directly related to the patient's exposure dose. The CT dose indicators were CTDIvol and DLP. The CT images were obtained while increasing the imaging conditions constantly from the phantom limit value (Q1) to the maximum value (Q4) for AAPM CT performance evaluation. And statistics analyzed with Pearson's correlation coefficients. The result of tube voltage that the increase in tube voltage proportionally increases the variation range of the CT number. And similar results were obtained in the qualitative evaluation of the CT image compared to the tube voltage of 120 kVp, which was applied clinically at 100 kVp. Also, the scan conditions were appropriate in the tube current range of 250 mAs to 350 mAs when the tube voltage was 100 kVp. Therefore, by applying the proposed brain CT scanning parameters can be reduced the radiation dose of the patient while maintaining quality of image.

• The Korean Journal of Applied Statistics
• /
• v.6 no.1
• /
• pp.125-143
• /
• 1993

The primary objective of the paper is to review the development of approximations of the null distribution of a scan statistic and to show how these approximations were improved. Let $X_1, \cdots, X_N$ be a sequence of independent uniform random variables on an interval (0, t]. A can statistic is defined to be the maximum number of observations in a subinterval of length t $\leq$ T, when we continuously (or discretely) move the subinterval from 0 to T. A scan statistic is used to test whether certain events occur in a cluster aganist a null hypothesis of the uniformity. It is difficult to calculate the exact null distribution of a scan statistic. Several authors have suggested approximations of the null distribution of a scan statistic since Naus(1966). We conceive that a scan statistic can be used for detecting a "hot region" is defined to be a region at which the frequencies of mutations are relatively high. A "hot region" may be regarded as a generalized version of a hot spot. We leave it for a further study the concrete formulation of deteciton a "hot region" in a mutational spectrum.uot; in a mutational spectrum.

• Genomics & Informatics
• /
• v.17 no.1
• /
• pp.10.1-10.3
• /
• 2019

To identify miRNA-mRNA interaction pairs associated with binary phenotypes, we propose a hierarchical structural component model for miRNA-mRNA integration (HisCoM-mimi). Information on known mRNA targets provided by TargetScan is used to perform HisCoM-mimi. However, multiple databases can be used to find miRNA-mRNA signatures with known biological information through different algorithms. To take these additional databases into account, we present our advanced application software for HisCoM-mimi for binary phenotypes. The proposed HisCoM-mimi supports both TargetScan and miRTarBase, which provides manually-verified information initially gathered by text-mining the literature. By integrating information from miRTarBase into HisCoM-mimi, a broad range of target information derived from the research literature can be analyzed. Another improvement of the new HisCoM-mimi approach is the inclusion of updated algorithms to provide the lasso and elastic-net penalties for users who want to fit a model with a smaller number of selected miRNAs and mRNAs. We expect that our HisCoM-mimi software will make advanced methods accessible to researchers who want to identify miRNA-mRNA interaction pairs related with binary phenotypes.