• Journal of forensic and investigative science
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• v.1 no.1
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• pp.72-87
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• 2006

Accidents and terrorist acts that utilize explosives have a great influence on society and thus require a prompt investigation for the arrest of the culprit. However, such investigations are often met with difficulties due to the vastness of the crime scene, restrictions on approaching the scene, fragility of the evidence, complexity of investigation, and the lack of expertise. In spite of such facts, scientific investigation regarding explosives have not been widely studied in Korea. Therefore, the focus of this research primarily concerns the effective scientific investigation methods in cases of accidents that involve chemical explosives. Although the a systematic investigation method is at the heart of scientific investigation in cases of explosive accidents, it is only at its rudimentary stage. Therefore, in this research, a systematic investigation method is put forth for the 'scene investigation, the documentation of the scene, and the collection and processing of evidence. Further, I have set forth a 'scene investigation check list' the ensure a thorough scene investigation and to promote an exhaustive evidence collection that would guarantee the admissibility of such evidence in court. The above efforts were aimed at simplifying the currently complicated investigation system. 1) In the future, a guidebook that can be generally applied to accidents involving explosives in Korea ught to be produced, a continual systematic education and integrated training excises for investigators ought to be established, laws that require additives in explosives ought to be instituted so that the type, components, and source of explosives can be identified, and lastly, a database that contain information on former explosion accidents, trends, and techniques of criminal activities that involve explosion accidents should be compiled.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.279-283
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• 2004

In general, triangular shape filters are used in the filter bank when we extract MFCC feature parameters from the spectrum of the speech signal. A different approach, which uses specific filter shapes in the filter bank that are optimized to the spectrum of training speech data, is proposed by Lee et al. to improve the recognition rate. A principal component analysis method is used to get the optimized filter coefficients. Using a large amount of 4-digit telephone speech database, in this paper, we get the MFCCs based on the PCA-optimized filter bank and compare the recognition performance with conventional MFCCs and direct weighted filter bank based MFCCs. Experimental results have shown that the MFCC based on the PCA-optimized filter bank give slight improvement in recognition rate compared to the conventional MFCCs but fail to achieve better performance than the MFCCs based on the direct weighted filter bank analysis. Experimental results are discussed with our findings.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.6
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• pp.486-491
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• 2013

This paper proposes a fast and efficient Haar-like feature selection algorithm for training classifier used in object detection. Many features selected by Haar-like feature selection algorithm and existing AdaBoost algorithm are either similar in shape or overlapping due to considering only feature's error rate. The proposed algorithm calculates similarity of features by their shape and distance between features. Fast and efficient feature selection is made possible by removing selected features and features with high similarity from feature set. FERET face database is used to compare performance of classifiers trained by previous algorithm and proposed algorithm. Experimental results show improved performance comparing classifier trained by proposed method to classifier trained by previous method. When classifier is trained to show same performance, proposed method shows 20% reduction of features used in classification.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.8
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• pp.758-765
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• 2016

This paper proposes a novel method for the recognition of the inverse synthetic aperture radar(ISAR) image of multiple targets flying in formation. Rather than separating the ISAR image of each target, the proposed method combines an ISAR image obtained by fusing the ISAR images in the training database. Fusion is conducted by optimizing the non-linear problem whose parameters are the aspect angle and the target location. Assuming that the aspect angle is properly estimated, the proposed method estimates the number of the targets and their locations by optimizing the template matching using PSO. In simulations using the F-16 scale model, the efficiency of the proposed method was demonstrated by yielding the ISAR image identical to that of targets in formation.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.73-79
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• 2012

This study attempts to analyze changes in land use patterns in a compound urban and agricultural city Kimje-si, using LANDSAT TM imagery and to forecast future changes accordingly. As a new approach to supervised classification, HSB(Hue, Saturation, Brightness)-transformed images were used to select training zones, and in doing so classification accuracy increased by more than 5 percent. Land use changes were forecasted by using a cellular automaton algorithm developed by applying Markov Chain techniques, and by taking into account classification results and GIS data, such as population of the pertinent region by area, DEMs, road networks, water systems. Upon comparing the results of the forecast of the land use changes, it appears that geographical features had the greatest influence on the changes. Moreover, a forecast of post-2030 land use change patterns demonstrates that 21.67 percent of mountain lands in Kimje-si is likely to be farmland, and 13.11 percent is likely to become city areas. The major changes are likely to occur in small mountain lands located in the heart of the city. Based on the study result, it seems certain that forecasting future land use changes can help plan land use in a compound urban and agricultural city to procure food resources.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.67-73
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• 2010

In this paper, a new face detection method that is more accurate than the conventional methods is proposed. This method utilizes a hybrid of Hausdorff distance based on the geometric similarity between the two sets of points and the LBP distance based on the distribution of local micro texture of an image. The parameters for normalization and the optimal blending factor of the two different metrics were calculated from training sample images. Popularly used face database was used to show that the proposed method is more effective and robust to the variation of the pose, illumination, and back ground than the methods based on the Hausdorff distance or LBP distance. In the particular case, the average error distance between the detected and the true face location was reduced to 47.9% of the result of LBP method, and 22.8% of the result of Hausdorff method.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.21 no.3
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• pp.170-175
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• 2018

Purpose: Lactose intolerance (LI) is perceived to be frequent in Asia and has been reported to have considerable impact on dietary intake, nutritional status and the quality of life. We aimed to gather information from healthcare professionals on the perceived incidence, diagnosis and management of LI in 1 to 5 year old children in Southeast Asia. Methods: An anonymous electronic survey was sent randomly among healthcare professionals registered in the database of the pediatric societies in Thailand, Indonesia, and Singapore between June and October 2016. Results: In total, 259 health care professionals responded of which 45.5% (n=118) were from Thailand, 37.4% (n=97) from Indonesia and 16.9% (n=44) from Singapore. Of the participants who responded (n=248), primary LI prevalence among children 1 to 3 years of age was estimated to be less than 5% by 56.8%. However, about 18.9% (n=47) answered they did not know/unsure. Regarding secondary LI, 61.6% of respondents (n=153) estimated the prevalence to be less than 15%. But again, 10.8% (n=27) answered they did not know or unsure. Rotavirus gastroenteritis was ranked as the top cause for secondary LI. There was considerable heterogeneity in the diagnostic methods used. The majority of respondents (75%) recommended lactose-free milk to manage primary and secondary LI. Conclusion: More education/training of pediatricians on this topic and further epidemiological studies using a more systematic approach are required.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.2
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• pp.765-768
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• 2013

Background and Aims: Prostate cancer is the most commonly diagnosed cancer in males in many populations. Metformin is the most widely used anti-diabetic drug in the world, and there is increasing evidence of a potential efficacy of this agent as an anti-cancer drug. Metformin inhibits the proliferation of a range of cancer cells including prostate, colon, breast, ovarian, and glioma lines. MicroRNAs (miRNAs) are a class of small, non-coding, single-stranded RNAs that downregulate gene expression. We aimed to evaluate the effects of metformin treatment on changes in miRNA expression in PC-3 cells, and possible associations with biological behaviour. Materials and Methods: Average cell viability and cytotoxic effects of metformin were investigated at 24 hour intervals for three days using the xCELLigence system. The $IC_{50}$ dose of metformin in the PC-3 cells was found to be 5 mM. RNA samples were used for analysis using custom multi-species microarrays containing 1209 probes covering 1221 human mature microRNAs present in miRBase 16.0 database. Results: Among the human miRNAs investigated by the arrays, 10 miRNAs were up-regulated and 12 miRNAs were down-regulated in the metformin-treated group as compared to the control group. In conclusion, expression changes in miRNAs of miR-146a, miR-100, miR-425, miR-193a-3p and, miR-106b in metformin-treated cells may be important. This study may emphasize a new role of metformin on the regulation of miRNAs in prostate cancer.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1386-1399
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• 2004

This paper presents correlation-based automatic image captioning. Given a training set of annotated images, we want to discover correlations between visual features and textual features, so that we can automatically generate descriptive textual features for a new unseen image. We develop models with multiple design alternatives such as 1) adaptively clustering visual features, 2) weighting visual features and textual features, and 3) reducing dimensionality for noise sup-Pression. We experiment thoroughly on 10 data sets of various content styles from the Corel image database, about 680MB. The major contributions of this work are: (a) we show that careful weighting visual and textual features, as well as clustering visual features adaptively leads to consistent performance improvements, and (b) our proposed methods achieve a relative improvement of up to 45% on annotation accuracy over the state-of-the-art, EM approach.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.4
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• pp.451-455
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• 2008

In this paper, the k-nearest templates method is proposed to combine multiple classifiers effectively. First, the method decomposes training samples of each class into several subclasses based on the outputs of classifiers to represent a class as multiple models, and estimates a localized template by averaging the outputs for each subclass. The distances between a test sample and templates are then calculated. Lastly, the test sample is assigned to the class that is most frequently represented among the k most similar templates. In this paper, C-means clustering algorithm is used as the decomposition method, and k is automatically chosen according to the intra-class compactness and inter-class separation of a given data set. Since the proposed method uses multiple models per class and refers to k models rather than matches with the most similar one, it could obtain stable and high accuracy. In this paper, experiments on UCI and ELENA database showed that the proposed method performed better than conventional fusion methods.