• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.236-238
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• 2022

According to the current Road Traffic Act, the 2020 amendment bill is currently in effect as a system that designates vehicle types for each lane for the purpose of securing road use efficiency and traffic safety. When comparing the number of traffic accident fatalities per 10,000 vehicles in Germany and Korea, the number of traffic accident deaths in Germany is significantly lower than in Korea. The representative case of the German autobahn, which did not impose a speed limit, suggests that Korea's speeding laws are not the only answer to reducing the accident rate. The designated lane system, which is observed in accordance with the keep right principle of the Autobahn Expressway, plays a major role in reducing traffic accidents. Based on this fact, we propose a traffic enforcement system to crack down on vehicles violating the designated lane system and improve the compliance rate. We develop a designated lane enforcement system that recognizes vehicle types using Yolo5, a deep learning object recognition model, recognizes license plates and lanes using OpenCV, and stores the extracted data in the server to determine whether or not laws are violated.Accordingly, it is expected that there will be an effect of reducing the traffic accident rate through the improvement of driver's awareness and compliance rate.

• Korean Journal of Community Nutrition
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• v.6 no.4
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• pp.617-627
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• 2001

This study examined health foods intakes and related variables among the middle aged(150 men and 159 women) in the Jeonbuk region. Health foods were classified into 4 groups including Chinese medicine(CM), toner foods(TF), vitamin or mineral supplements(VMS), and other manufactured health food supplements(MHFS). The number of people taking health foods were higher for those in their 50's than in their 40's. The consumption rate of TF in men was the highest among health foods, this result had significance. The reasons for taking health foods were recovery from fatigue, supplement of nutrients and making smooth body activity in general, but TF was used to increase of vigor. The consumption rate of health foods was a little different according to social-economic factors, namely, the consumption rate of CM was higher in people in rural than urban areas, those who graduated from middle school than university, blue color & self-employed as opposed to housewives and service workers, low level income than high level income, and Buddhism and no religion than Christian. The consumption rate had a correlation with the habits of smoking, alcohol drinking and exercise ; namely, the consumption rate of CM was higher than VMS and MHFS on smokers and alcohol drinkers. The more the frequency of exercise, the higher the consumption rate of TF, but the duration of the exercise was not correlated. This study suggests that middle aged people need nutritional education for the right recognition and selection of health foods and to consider the nature of each type of health foods.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.132-142
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• 2021

The purpose of this study is to present an effective methodology that can measure heart rate, heart rate variability, oxygen saturation, respiration rate, mental stress level, and blood pressure using mobile front camera that can be accessed most in real life. Face recognition was performed in real-time using Blaze Face to acquire facial image data, and the forehead was designated as ROI (Region Of Interest) using feature points of the eyes, nose, and mouth, and ears. Representative values for each channel of the ROI were generated and aligned on the time axis to measure vital signs. The vital signs measurement method was based on Fourier transform, and noise was removed and filtered according to the desired vital signs to increase the accuracy of the measurement. To verify the results, vital signs measured using facial image data were compared with pulse oximeter contact sensor, and TI non-contact sensor. As a result of this work, the possibility of extracting a total of six vital signs (heart rate, heart rate variability, oxygen saturation, respiratory rate, stress, and blood pressure) was confirmed through facial images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.801-814
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• 2004

In this paper, we propose a block adaptive binarization (BAB) using a modified quadratic filter (MQF) to binarize business card images acquired by personal digital assistant (PDA) cameras effectively. In the proposed method, a business card image is first partitioned into blocks of 8${\times}$8 and the blocks are then classified into character Hocks (CBs) and background blocks (BBs). Each classified CB is windowed with a 24${\times}$24 rectangular window centering around the CB and the windowed blocks are improved by the pre-processing filter MQF, in which the scheme of threshold selection in QF is modified. The 8${\times}$8 center block of the improved block is barbarized with the threshold selected in the MQF. A binary image is obtained tiling each binarized block in its original position. Experimental results show that the MQF and the BAB have much better effects on the performance of binarization compared to the QF and the global binarization (GB), respectively, for the test business card images acquired in a PDA. Also the proposed BAB using MQF gives binary images of much better quality, in which the characters appear much better clearly, over the conventional GB using QF. In addition, the binary images by the proposed BAB using MQF yields about 87.7% of character recognition rate so that about 32.0% performance improvement over those by the GB using QF yielding about 55.7% of character recognition rate using a commercial character recognition software.

• Journal of Distribution Science
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• v.17 no.2
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• pp.53-69
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• 2019

Purpose - National scientific technology R&D investment is exceeding 60 trillion won per year, and the results of patent applications and technology transfers are visually improving. However, despite the improving research results of national R&D, the practical results of technology startups are mediocre. It is now time to expand the construction of the technology commercialization ecosystem, where the expansion of national R&D leads to the results of technology startups. Therefore, this study discussed the measures to increase the competitiveness of technology startups through the factual survey of the companies that benefitted from R&D support programs. Research design, data, and methodology - This study targeted 996 companies that benefitted from the R&D projects of the Technology Transfer Center for National R&D Programs, and deducted itemized issues through the survey replies. Survey questions were prepared to estimate the national R&D results, and the technology recognition path, the purpose of detailed introduction of the technology, investment of the commercialization fund, economic results, and the factors of success and failure were analyzed. Results - As for the recognition rate of technology during the process of corporate technology commercialization through the technology transfer, recognition through project participation showed a high response rate, and diverse implications of technology commercialization were deducted through the analysis of economic results. As for the resolution alternatives, the proliferation of technology commercialization platform that can create excellent technology for the companies in early stages and the measure of expanding the distribution of technology infrastructure were suggested. In this study, public technology commercialization strategy is established, and the innovative marketing strategy is presented. Conclusions - This study reveal that the result of creating scientific technology jobs should be deducted, in order to produce the revolutionary results of job creation by suggesting the success models of technology commercialization based on domestic scientific technology. In particular, even though the support systems for public research results are being diversely suggested, accurate studies on their actual conditions are currently lacking. Therefore, this study suggest realistic political alternatives to assure results in the process of public technology commercialization, by examining the current state of public research results of R&D support institutions and diagnosing the issues.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.10
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• pp.139-147
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• 2015

Steady state visual evoked potential (SSVEP) has been actively studied because of its short training time, relatively higher signal-to-noise ratio, and higher information transfer rate. There are two popular analysis methods for SSVEP signals: power spectral density analysis (PSDA) and canonical correlation analysis (CCA). However, the PSDA is known to be vulnerable to noise due to the use of a single channel. Although conventional CCA is more accurate than PSDA, it may not be appropriate for the real-time SSVEP-based BCI system when it has short time window length because it uses sinusoidal signals as references. Therefore, the two methods are not efficient for the real-time BCI system that requires a short TW and a high recognition accuracy. To overcome this limitation of the conventional methods, this paper proposes a frequency recognition method with a combination of CCA and PSDA using the difference between powers of canonical variables obtained from the results of CCA. Experimental results show that the performance of the combination of CCA and PSDA is better than that of CCA for the case of a short TW.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.368-376
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• 2011

This study has undertaken for the analysis of the level of recognition on the Transfer Income Tax. The statistical analysis through the questionnaire is made to find out the issues on the equitableness of Transfer Income Tax first with the level of equitableness of the Transfer Income Tax structure and appropriateness of the degree of different tax rate applied under the Transfer Income Tax, level of equitableness of the Transfer Income Tax structure and intent for avoidance of payment under the present tax policies, level of recognition for administrative disposition on those avoiding diligent payment of taxes, and it analyzed the relationship between the levels of understanding of the structure of the Transfer Income Tax and the level of complexity of the structure of the Transfer Income Tax in order to analyze if it has negative impact on the level of understanding for the structure of the Transfer Income Tax. On the basis of the above analysis result, as the improvement plan on the Transfer Income Tax system, following has been presented; enhancement of equitableness of tax rate structure under the Transfer Income Tax for improving the equitableness of tax burden, establishment of regulations to strengthen the appropriate tax investigation for prevention of diligent tax payment avoidance, relaxation of complication of the structure under the Transfer Income Tax.

• Fire Science and Engineering
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• v.24 no.2
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• pp.145-153
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• 2010

Korea was experienced more forest fire occurrence compared to an area. As a forest fire occurrence from man caused burning for a farming increased and was one of the main reasons of forest fire occurrence in Korea, agriculturist-was a main reason of forest fire occurrence-opinion analysis was needed for forest fire prevention from this reason. Therefore, we asked agriculturist who live in province frequently experienced a forest fire from the burning for farming to answer questions. In result, a half of the respondents have a burning experience for farming and the main reason of the burning was the clearance around farmlands. In result of survey about recognition rate of forest fire prevention policy (forest fire season, incineration inhibition within 100 m from forest, license system for burning, joint burning system by a rural community, imposing a fine for burning) was almost high except license system for the burning, In the result about analysis according to ages and provinces, the recognition rate was high in province experienced severe forest fire damage and low in below 40 years group. So, the direction of forest fire prevention policy would need to be mediated in the view of agriculturist who need to use a fire because of farming labor shortage and higher age. And a consolidated education of forest fire prevention would be needed to agriculturist who live in province experienced rarely forest fire and in below 40 years group.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.90-95
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• 2014

The researchs using brain-computer interface, the new interface system which connect human to macine, have been maded to implement the user-assistance devices for control of wheelchairs or input the characters. In recent researches, there are several trials to implement the speech recognitions system based on the brain wave and attempt to silent communication. In this paper, we studied how to extract features of vowel based on international phonetic alphabet (IPA), as a foundation step for implementing of speech recognition system based on electroencephalogram (EEG). We conducted the 2 step experiments with three healthy male subjects, and first step was speaking imagery with single vowel and second step was imagery with successive two vowels. We selected 32 channels, which include frontal lobe related to thinking and temporal lobe related to speech function, among acquired 64 channels. Eigen value of the signal was used for feature vector and support vector machine (SVM) was used for classification. As a result of first step, we should use over than 10th order of feature vector to analyze the EEG signal of speech and if we used 11th order feature vector, the highest average classification rate was 95.63 % in classification between /a/ and /o/, the lowest average classification rate was 86.85 % with /a/ and /u/. In the second step of the experiments, we studied the difference of speech imaginary signals between single and successive two vowels.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.1-6
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• 2021

In the field of speech recognition, as the DNN is applied, the use of speech recognition is increasing, but the amount of calculation for parallel training needs to be larger than that of the conventional GMM, and if the amount of data is small, overfitting occurs. To solve this problem, we propose an efficient method for robust voice feature extraction and voice signal noise removal even when the amount of data is small. Speech feature extraction efficiently extracts speech energy by applying the difference in frame energy for speech and the zero-crossing ratio and level-crossing ratio that are affected by the speech signal. In addition, in order to remove noise, the noise of the speech signal is removed by removing the noise of the speech signal with an average predictive improved LMS filter with little loss of speech information while maintaining the intrinsic characteristics of speech in detection of the speech signal. The improved LMS filter uses a method of processing noise on the input speech signal by adjusting the active parameter threshold for the input signal. As a result of comparing the method proposed in this paper with the conventional frame energy method, it was confirmed that the error rate at the start point of speech is 7% and the error rate at the end point is improved by 11%.