• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.100-118
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• 2015

This study established a land-cover classification method on objects using satellite images, and figured out distributional patterns of land cover according to categories through spatial statistics techniques. Object-based classification generated each land cover classification map by spectral information, texture information, and the combination of the two. Through assessment of accuracy, we selected optimum land cover classification map. Also, to figure out spatial distribution pattern of land cover according to categories, we analyzed hot spots and quantified them. Optimal weight for an object-based classification has been selected as the Scale 52, Shape 0.4, Color 0.6, Compactness 0.5, Smoothness 0.5. In case of using the combination of spectral information and texture information, the land cover classification map showed the best overall classification accuracy. Particularly in case of dry fields, protected cultivation, and bare lands, the accuracy has increased about 12 percent more than when we used only spectral information. Forest, paddy fields, transportation facilities, grasslands, dry fields, bare lands, buildings, water and protected cultivation in order of the higher area ratio of DMZ according to categories. Particularly, dry field sand transportation facilities in Yanggu occurred mainly in north areas of the civilian control line. dry fields in Cheorwon, forest and transportation facilities in Inje fulfilled actively in south areas of the civilian control line. In case of distributional patterns according to categories, hot spot of paddy fields, dry fields and protected cultivation, which is related to agriculture, was distributed intensively in plains of Yanggu and in basin areas of Cheorwon. Hot spot areas of bare lands, waters, buildings and roads have similar distribution patterns with hot spot areas related to agriculture, while hot spot areas of bare lands, water, buildings and roads have different distributional patterns with hot spot areas of forest and grasslands.

• The Journal of Korean Academy of Prosthodontics
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• v.48 no.4
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• pp.287-293
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• 2010

Purpose: This study evaluated the effect of polishing techniques on surface roughness of polymethyl methacrylate (PMMA), as well as the influence of light-cured surface glaze and subsequent brushing on surface roughness. Materials and methods: A total of 60 PMMA specimens ($10{\times}10{\times}5\;mm$) were made and then divided into 6 groups of 10 each according to the polymerization methods (under pressure or atmosphere) and the surface polishing methods (mechanical or chemical polishing) including 2 control groups. The mechanical polishing was performed with the carbide denture bur, rubber points and then pumice and lathe wheel. The chemical polishing was performed by applying a light-cured surface glaze ($Plaquit^{(R)}$; Dreve-Dentamid GmbH). Accura $2000^{(R)}$, a non-contact, non-destructive, optical 3-dimensional surface analysis system, was used to measure the surface roughness (Ra) and 3-dimensional images were acquired. The surface roughness was again measured after ultrasonic tooth brushing in order to evaluate the influence of brushing on the surface roughness. The statistical analysis was performed with Mann-Whitney test and t-test using a 95% level of confidence. Results: The chemically polished group showed a statistically lower mean surface roughness in comparison to the mechanically polished group (P = .0045) and the specimens polymerized under the atmospheric pressure presented a more significant difference (P = .0138). After brushing, all of the groups, except the mechanically polished group, presented rougher surfaces and showed no statistically significant differences between groups. Conclusion: Although the surface roughness increased after brushing, the chemical polishing technique presented an improved surface condition in comparison to the mechanical polishing technique.

• Journal of forensic and investigative science
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• v.1 no.2
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• pp.5-19
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• 2006

Data mining is an information extraction activity to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Law enforcement agencies deal with mass data to investigate the crime and its amount is increasing due to the development of processing the data by using computer. Now new challenge to discover knowledge in that data is confronted to us. It can be applied in criminal investigation to find offenders by analysis of complex and relational data structures and free texts using their criminal records or statement texts. This study was aimed to evaluate possibile application of data mining and its limitation in practical criminal investigation. Clustering of the criminal cases will be possible in habitual crimes such as fraud and burglary when using data mining to identify the crime pattern. Neural network modelling, one of tools in data mining, can be applied to differentiating suspect's photograph or handwriting with that of convict or criminal profiling. A case study of in practical insurance fraud showed that data mining was useful in organized crimes such as gang, terrorism and money laundering. But the products of data mining in criminal investigation should be cautious for evaluating because data mining just offer a clue instead of conclusion. The legal regulation is needed to control the abuse of law enforcement agencies and to protect personal privacy or human rights.

• Korean journal of applied entomology
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• v.57 no.4
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• pp.243-251
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• 2018

Eggs, immature eggs, and pupae of 8 different insects (Halyomopha halys, Riptortus pedestris, Lymantria dispar, Antheraea yamamai, Verlarifictorus spp, Antheraea pernyi, and Musca domestica) including Lycorma delicatura were used to select the alternative host for laboratory mass rearing of A. orientalis. Except L. delicatula's eggs and immature eggs of A. pernyi, other 7 tested insects were not parasitized by A. orientalis. A. pernyi was reared with oak tree leaves and its cocoons were harvested on mid-July and early October. On 4 or 5 days after emergence, only female adults showing swollen abdomen were collected and stored at $1{\sim}5^{\circ}C$. We could get 150~200 eggs per one female by dissecting the female's abdomen. For examining the possibility for laboratory mass rearing of A. orientalis with A. pernyi's immature eggs, developmental periods from egg to pupa between the two different hosts were compared. Developmental periods were 36.1 days on immature eggs of A. pernyi and 36.8 days on an original host's eggs, respectively. The number of parasitized eggs by A. orientalis' female for 24 h was 3.4 on immature eggs of A. pernyi and 4.2 on an original host's eggs, respectively. However, there were no significant statistical differences in developmental period and parasitization between the two hosts. By supplying honeyed water to newly emerged female parasitoids, it was able to maximize their longevities up to 64.3 days after emergence. Therefore, our results support potential for laboratory mass-rearing of A. orientalis using A. pernyi's immature eggs as an alternative host.