• Journal of KIISE
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• v.43 no.2
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• pp.186-195
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• 2016

This paper proposes a vehicle license plate detection method in real road environments using 8 bit-MCT features and a landmark-based Adaboost method. The proposed method allows identification of the potential license plate region, and generates a saliency map that presents the license plate's location probability based on the Adaboost classification score. The candidate regions whose scores are higher than the given threshold are chosen from the saliency map. Each candidate region is adjusted by the local image variance and verified by the SVM and the histograms of the 8bit-MCT features. The proposed method achieves a detection accuracy of 85% from various road images in Korea and Europe.

• Journal of the Korea Society for Simulation
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• v.26 no.1
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• pp.39-46
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• 2017

An arrangement of passive sonars is considered to be a fixed underwater surveillance system for detecting an anti-submarine consistently. An effectiveness score for optimizing the arrangement of passive sonars is defined in a function of the probability of detection and localization. These two features contain various probabilistic variations including seasons, sea states, depths of water, etc. Due to this reason, the effectiveness scores show probabilistic characteristics from the input of the arrangement of passive sonars. This paper defines the optimization problem having the results of probabilistic characteristics from various parameters of input conditions. Also, we suggest a simulation-based process of deciding the optimized arrangement of passive sonars using DPSO(Discrete binary version of PSO) method.

• Korean Journal of Health Education and Promotion
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• v.32 no.5
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• pp.73-81
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• 2015

Objectives: We tried to confirm physical activity of 1,000 Kcal per week was a meaningful point in controlling coronary artery disease risks in female older adults. Methods: Participants were 66 female older adults recruited from senior welfare center. Participants were provided with accelerometer (e-step, Kenz, Japan) for measuring daily energy expenditure. Graded exercise test was done for measuring aerobic fitness. Blood glucose and lipid were analyzed. Framingham risk score was calculated based on blood glucose, blood lipid, and smoking. These variables were compared between the group expended more than 1,000 Kcal/week and the group with energy expenditure below 1,000 Kcal/week. Results: The group expended over 1,000kcal/week showed to be superior to the counterpart group in following variables; AC(Abdominal Circumference), %BF, $HR_{rest}$(resting heart rate), $VO_{2peak}$, FBG, LDL-C, TG, BDI-II, QOL, AR(Absolute Risk), RR(Relative Risk). Conclusions: The group expended over 1,000 Kcal/week was likely to have less probability in CAD than group expended less than 1,000 Kcal/week. The result of this study suggests the important role of active daily life that can be replaced with that of regular exercise especially for those who are not available to do structured exercise.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.113-118
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• 2011

Sequence homology analysis in the substances in the phenomenon of life is to create database by sorting and indexing and to demonstrate the usefulness of informatics. In this paper, Markov models are used in GenScan program to convert the pattern of complex eukaryotic protein sequences. It becomes impossible to navigate the minimum distance, complexity increases exponentially as the exact calculation. It is used scorecard in amino acid substitutions between similar amino acid substitutions to have a differential effect score, and is applied the Markov models sophisticated concealment of the transition probability model. As providing superior method to translate sequences homologous sequences in analysis using blast p, Markov models. is secreted protein structure of sequence translations.

• Korean Journal of Clinical Pharmacy
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• v.23 no.1
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• pp.77-80
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• 2013

메치실린 저항성 황색 포도상구균(MRSA)에 감염된 환자에게 단기간 연속적으로 반코마이신을 투여했을 때 비정상적으로 호중구의 수치가 감소한 약인성 부작용 사례를 보고하고자 한다. 해당 여성 환자는 61세로서 MRSA 감염증을 판정받고 반코마이신 투여와 더불어 점차 백혈구(WBC)와 절대호중구수치(ANC)가 감소하였고, 제10일째에 이르러 호중구 감소증이 발생하여 ANC가 최저 430 $cells/mm^3$까지 낮아졌으나, 반코마이신의 투여를 중단하자 곧 정상수준으로 회복되었다. 본 사례는 Naranjo Probability Scale과 Korean Algorithm Score(Ver. 2.0)로 각각 평가하였을 때 반코마이신의 투여와 호중구감소증의 발현 사이에 모두 '가능한(probable)' 정도의 인과관계를 가진 것으로 평가되었다. 이는 통상적으로 20일 이상 연속투여를 할 때 임상적으로 관측되던 반코마이신-유래 호중구감소증이 단지 10일 정도의 단기간 투여만으로도 발생할 수 있다는 임상적 약물부작용의 사례로서, 향후 MRSA환자에게 반코마이신을 선택할 때에는 이와 같은 부작용을 고려하여 환자의 WBC와 ANC를 면밀히 관찰하면서 투여할 필요성이 있음을 시사한다.

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.77-87
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• 2017

This study analyzed the data from Korea National Health and Nutrition Examination Survey to examine factors associated with help-seeking among Korean adults with suicidal ideation. The results from binary logistic regression analysis showed that being currently married, low family income, and absence of diagnosed clinical depression were negatively associated with seeking help. Gender, age, education, the PHQ total score, and health insurance did not significantly change the probability of seeking help. The future suicide help-seeking intervention should focus on those who are less likely to seek help.

• Korean Journal of Childcare and Education
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• v.15 no.3
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• pp.115-133
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• 2019

Objective: The purpose of the study was to develop a mathematics education program utilizing food to improve the mathematical abilities of 4-year-olds and to analyze the effects of this program on 4-years-olds' mathematical concepts (number and operation, algebra, geometry, measurement, data analysis, and probability). Methods: The study selected 30 4-year-olds from two daycare centers located in K city. The experimental group (N=15) participated in the mathematics education program utilizing food, 10 times for five weeks, while the comparative group (N=15) participated in the seasonal mathematics education program based on the Nuri Curriculum. The activities of this intervention program were designed to cover all domains of Mathematical Exploratory areas in the Nuri Curriculum. For data processing and analysis, pre-test and post-test score differences between the two groups were analyzed through MANCOVA. Results: The experimental group had significantly higher scores on five mathematical concepts compared with the control group. A mathematics education program utilizing food had the positive effect of improving 4-year-olds' mathematical ability. Conclusion/Implications: Mathematic education programs utilizing food are recommended as necessary pedagogical data to develop the mathematical abilities of children in education centers, families, or relating to parenting education.

• STI Policy Review
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• v.9 no.1
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• pp.55-76
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• 2018

This study analyzed the effect of the government R&D subsidy program on long-term firm survival. In order to estimate the average treatment effect for the treated group, we used the survival analysis and matching method by constituting a comprehensive dataset of more than 90,000 observations. The analysis results show that the government R&D subsidy has a negative impact on long-term firm survival. In particular, not only the subsidy does not have a statistically significant effect on firm survival in the relatively short-term, the survival probability of the subsidized firms is statistically significantly lower than the non-subsidized firms after six years. These results can be seen as weakening the justification of government R&D support. There may be problems in the subsidy policy itself and the process of selection of subsidy awardees; however, the more fundamental problem is that the subsidy policy is concluded as the one-time event. Admittedly, it would be difficult for the government to precisely manage the subsidized projects over a long term period. However, in the case of a project in which short-term performance is detected, it would be necessary to provide a step-by-step support to strengthen the firm's competitiveness through further support and continuous development of performance. Of course, mid- and long-term evaluations of subsidy support policy should be performed in parallel with such phased support.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.12
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• pp.1-7
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• 2021

The deep learning image processing technique was used to prevent accidents in lathe work caused by worker negligence. During lathe operation, when the chuck is rotated, it is very dangerous if the operator's hand is near the chuck. However, if the chuck is stopped during operation, it is not dangerous for the operator's hand to be in close proximity to the chuck for workpiece measurement, chip removal or tool change. We used YOLO (You Only Look Once), a deep learning image processing program for object detection and classification. Lathe work images such as hand, chuck rotation and chuck stop are used for learning, object detection and classification. As a result of the experiment, object detection and class classification were performed with a success probability of over 80% at a confidence score 0.5. Thus, we conclude that the artificial intelligence deep learning image processing technique can be effective in preventing incidents resulting from worker negligence in future manufacturing systems.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.688-701
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• 2023

The conventional methods of network intrusion detection system (NIDS) cannot measure the trend of intrusiondetection targets effectively, which lead to low detection accuracy. In this study, a NIDS method which based on a deep neural network in a big-data environment is proposed. Firstly, the entire framework of the NIDS model is constructed in two stages. Feature reduction and anomaly probability output are used at the core of the two stages. Subsequently, a convolutional neural network, which encompasses a down sampling layer and a characteristic extractor consist of a convolution layer, the correlation of inputs is realized by introducing bidirectional long short-term memory. Finally, after the convolution layer, a pooling layer is added to sample the required features according to different sampling rules, which promotes the overall performance of the NIDS model. The proposed NIDS method and three other methods are compared, and it is broken down under the conditions of the two databases through simulation experiments. The results demonstrate that the proposed model is superior to the other three methods of NIDS in two databases, in terms of precision, accuracy, F1- score, and recall, which are 91.64%, 93.35%, 92.25%, and 91.87%, respectively. The proposed algorithm is significant for improving the accuracy of NIDS.