• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.1
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• pp.6-17
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• 2013

Recently, the color of vehicle license plate has been changed from green to white. Thus the vehicle plate recognition system used for parking management systems, speed and signal violation detection systems should be robust to the both colors. This paper presents a vehicle license plate recognition system, which works on both of green and white plate at the same time. In the proposed system, the image of license plate is taken from a captured vehicle image by using morphological information. In the next, each character region in the license plate image is extracted based on the vertical and horizontal projection of plate image and the relative position of individual characters. Finally, for the recognition process of extracted characters, PCA(Principal Component Analysis) and LDA(Linear Discriminant Analysis) are sequentially utilized. In the experiment, vehicle license plates of both green background and white background captured under irregular illumination conditions have been tested, and the relatively high extraction and recognition rates are observed.

• The Transactions of the Korea Information Processing Society
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• v.4 no.2
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• pp.465-482
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• 1997

In this paper, we have studied on cinstructing code-recognition shstem by neural network according to a image process taking the DOT classification code stamped on tire surface.It happened to a few problems that characters distorted in edge by diffused reflection and two adjacent characters take the same label,even very sen- sitive to illumination ofr recognition the stamped them on tire.Thus,this paper would propose the algorithm for tire code under being cinscious of these properties and prove the algorithm drrciency with a simulation.Also,we have suggerted the MCBP network composing of multi-linked recognizers of dffcient identify the DOT code being tire classification code.The MCBP network extracts the projection balue for classifying each character's rdgion after taking out the prjection of each chracter's region on X,Y axis,processes each chracters by taking 7$\times$8 normalization.We have improved error rate 3% through the MCBP network and post-process comparing the DOT code Database. This approach has a accomplished that learming time get's improvenent at 60% and recognition rate has become to 95% from 90% than BckPropagation with including post- processing it has attained greate rates of entire of tire recoggnition at 98%.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.11-18
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• 2016

Magnetic resonance image (MRI) is widely used in brain research field and medical image. Especially, non-invasive brain activation acquired image technique, which is functional magnetic resonance image (fMRI) is used in brain study. In this study, we investigate brain activation occurred by LED light stimulation. For investigate of brain activation in experimental small animal, we used high magnetic field 9.4T MRI. Experimental small animal is Balb/c mouse, method of fMRI is using echo planar image (EPI). EPI method spend more less time than any other MRI method. For this reason, however, EPI data has low contrast. Due to the low contrast, image pre-processing is very hard and inaccuracy. In this study, we planned the study protocol, which is called block design in fMRI research field. The block designed has 8 LED light stimulation session and 8 rest session. All block is consist of 6 EPI images and acquired 1 slice of EPI image is 16 second. During the light session, we occurred LED light stimulation for 1 minutes 36 seconds. During the rest session, we do not occurred light stimulation and remain the light off state for 1 minutes 36 seconds. This session repeat the all over the EPI scan time, so the total spend time of EPI scan has almost 26 minutes. After acquired EPI data, we performed the analysis of this image data. In this study, we analysis of EPI data using statistical parametric map (SPM) software and performed image pre-processing such as realignment, co-registration, normalization, smoothing of EPI data. The pre-processing of fMRI data have to segmented using this software. However this method has 3 different method which is Gaussian nonparametric, warped modulate, and tissue probability map. In this study we performed the this 3 different method and compared how they can change the result of fMRI analysis results. The result of this study show that LED light stimulation was activate superior colliculus region in mouse brain. And the most higher activated value of segmentation method was using tissue probability map. this study may help to improve brain activation study using EPI and SPM analysis.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.323-330
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• 2020

This paper proposes the road roughness based Braking Pressure Calculation System(BPCS) for an Autonomous Vehicle Stability. The system consists of an image normalization module that processes the front image of a vehicle to fit the input of the random forest, a Random Forest based Road Roughness Classification Module that distinguish the roughness of the road on which the vehicle is travelling by using the weather information and the front image of a vehicle as an input, and a brake pressure control module that modifies a friction coefficient applied to the vehicle according to the road roughness and determines the braking strength to maintain optimal driving according to a vehicle ahead. To verify the efficiency of the BPCS experiment was conducted with a random forest model. The result of the experiment shows that the accuracy of the random forest model was about 2% higher than that of the SVM, and that 7 features should be bagged to make an accurate random forest model. Therefore, the BPCS satisfies both real-time and accuracy in situations where the vehicle needs to brake.

• Journal of Wetlands Research
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• v.15 no.3
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• pp.367-380
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• 2013

In this study, sub-indicators, and thematic mid-indexes to evaluate the water use characteristics were selected through historical data analysis and factor analysis, and consisted of the subject approach framework. And the integrated index was developed to evaluate water use characteristics of the watershed. Using developed index, the water use characteristics were assessed for 812 standard basins with the exception for North Korea using data of 1990 to 2007 from the relevant agencies. A sensitivity analysis is conducted for this study to determine the proper way through various normalization and weighting methods. To increase the objectivity of developed index, the history of the damage indicators are excluded in the analysis. In addition, in order to ensure its reliability, results from index with and without consideration of the damage history were compared. Also, the index is also applied to real data for 2008 Gangwon region to verify its field applicability. Through the validation process this index confirmed the adequacy for the indicators selection and calculation method. The results of this study were analyzed based on the spatial and time vulnerability of the basin's water use, which can be applied to various parts such as priority decision-making for water business or policy, mitigations for the vulnerable components of the basin, and supporting measures to establishment by providing relevant information about it.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.1
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• pp.35-44
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• 2016

Seed viability is one of the most important parameters that is directly related with seed germination performance and seedling emergence. In this study, a hyperspectral imaging (HSI) system having a range of 1000-2500 nm was used to classify viable watermelon seeds from nonviable seeds. In order to obtain nonviable watermelon seeds, a total of 96 seeds were artificially aged by immersing the seeds in hot water ($25^{\circ}C$) for 15 days. Further, hyperspectral images for 192 seeds (96 normal and 96 aged) were acquired using the developed HSI system. A germination test was performed for all the 192 seeds in order to confirm their viability. Spectral data from the hyperspectral images of the seeds were extracted by selecting pixels from the region of interest. Each seed spectrum was averaged and preprocessed to develop a classification model of partial least square discriminant analysis (PLS-DA). The developed PLS-DA model showed a classification accuracy of 94.7% for the calibration set, and 84.2% for the validation set. The results demonstrate that the proposed technique can classify viable and nonviable watermelon seeds with a reasonable accuracy, and can be further converted into an online sorting system for rapid and nondestructive classification of watermelon seeds with regard to viability.

• Maritime Security
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• v.1 no.1
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• pp.1-30
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• 2020

The study started with the question, "Is Japan's normalization of nationalization a return to militarism?" Therefore, in order to analyze this, the characteristics of the international system after the inauguration of the Japanese Empire during World War I and World War II and the Abe's 2nd Cabinet in contemporary Japan were compared. Through this, there were some differences in the characteristics of the international system of the two periods, and as a result, it was intended to derive the differences between the two examples. During the prewar period of World War I, the militaristic Japanese Empire suffered great damage from the national pride of being the only power in Asia through the Paris Enhancement Conference, the Washington Navy Treaty, and the London Navy Treaty. However, the Western powers with colonies in Asia still existed in the region, so it was not possible to turn them into immediate power expansion. Meanwhile, World War II broke out in Europe. As a result, the Western powers had to focus on the whole of Europe, and the militaristic Japanese empire became a regional hegemony without missing the international system characteristic of "the hegemony." Unlike in the past militarism, Japan's case of pursuing common nationalization since 2012 has been carried out in the order of Northeast Asia in the composition of the "cold war" new cold war. In particular, Japan is attempting to transform itself into a normal state to strengthen the US-Japan alliance on a self-reliant level due to the lack of quantitative military power compared to the neighboring countries.

• Smart Media Journal
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• v.12 no.11
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• pp.185-197
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• 2023

This study was conducted using text mining and network theory to extract useful information for application for occupancy and performance of permit tasks contained in the permit contents from the permit register, which is used only for the simple purpose of recording occupancy permit information. Based on text mining, we analyzed and compared the frequency of vocabulary occurrence and topic modeling in five regions, including Seoul, Gyeonggi, Gyeongsang, Jeolla, Chungcheong, and Gangwon, as well as normalization processes such as stopword removal and morpheme analysis. By applying four types of centrality algorithms, including stage, proximity, mediation, and eigenvector, which are widely used in network theory, we looked at keywords that are in a central position or act as an intermediary in the network. Through a comprehensive analysis of vocabulary appearance frequency, topic modeling, and network centrality, it was found that the 'installation' keyword was the most influential in all regions. This is believed to be the result of the Ministry of Environment's permit management office issuing many permits for constructing facilities or installing structures. In addition, it was found that keywords related to road facilities, flood control facilities, underground facilities, power/communication facilities, sports/park facilities, etc. were at a central position or played a role as an intermediary in topic modeling and networks. Most of the keywords appeared to have a Zipf's law statistical distribution with low frequency of occurrence and low distribution ratio.

• The Journal of Internal Korean Medicine
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• v.45 no.4
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• pp.663-680
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• 2024

Objectives: The purpose of this study was to analyze the research trends of electroacupuncture (EA) at CV23. Methods: Studies published until July 2024 were searched on PubMed and domestic databases (OASIS, ScienceON, RISS, KISS, KCI, KMbase, and DBpia) using the keywords "CV23", "lianquan", "electroacupuncture", "염천", "전침", and "전기자극". Results: A total of 16 studies were selected. There were 6 randomized controlled trials, 1 case report, and 9 experimental studies. Of the 16 papers selected, 15 examined the effect of EA at CV23 on improving swallowing function. Clinical studies found that EA at CV23 was effective in improving dysphagia, aphasia, and drooling symptoms through mechanisms such as increased hyolaryngeal movement, normalization of pathologically elevated NO, ET, and improvement of excitement of the swallowing motor cortex. According to experimental studies, EA at CV23 activates the brain region associated with swallowing function, promotes the swallowing reflex by increasing neurotransmitters, improves electromyography of the swallowing muscles, and improves blood flow around CV23. Conclusion: Electroacupuncture at CV23 may be an effective and safe method for post-stroke dysphagia, post-stroke aphasia, and post-stroke drooling. In the future, research should be conducted in different diseases and high-quality studies should be conducted.

• Journal of Environmental Impact Assessment
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• v.33 no.5
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• pp.187-203
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• 2024

PM_2.5, a type of fine particulate matter, poses serious health risks. Existing pollution management policies and research have generally focused on high-concentration areas. However, this approach has limitations as it does not adequately account for regional characteristics and varying levels of vulnerability, leading to an incomplete reflection of actual risks in specific areas. This study analyzed 229 administrative districts to develop a vulnerability index by comprehensively evaluating PM_2.5 exposure, sensitivity, and adaptive capacity. Using data from 2019, the index was calculated through normalization and entropy weighting methods, and spatial patterns of PM_2.5 vulnerability were examined through LISA and K-means clustering analysis. The findings reveal that the distribution of PM_2.5-vulnerable areas shows distinct patterns within urban settings, which were classified into four distinct types, each characterized by different urban features. This suggests a need for region-specific dust reduction policies. This study contributes to a better understanding of the spatial patterns of PM_2.5 vulnerability and aims to support the development of more effective policy approaches.