• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.105-113
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• 2018

In this paper, we proposed a method for effective classification of eye, nose, and mouth of human face. Most recent image classification uses Convolutional Neural Network(CNN). However, the features extracted by CNN are not sufficient and the classification effect is not too high. We proposed a new algorithm to improve the classification effect. The proposed method can be roughly divided into three parts. First, the Haar feature extraction algorithm is used to construct the eye, nose, and mouth dataset of face. The second, the model extracts CNN features of image using AlexNet. Finally, Haar-CNN features are extracted by performing convolution after Haar feature extraction. After that, CNN features and Haar-CNN features are fused and classify images using softmax. Recognition rate using mixed features could be increased about 4% than CNN feature. Experiments have demonstrated the performance of the proposed algorithm.

• The Journal of Korean Medicine
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• v.40 no.2
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• pp.1-16
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• 2019

Objectives: The purpose of this study was to increase the utilization of Korean Medicine Clinical Practice Guidelines(KMCGP) for ankle sprain by investigating the recognition of guideline developed in 2015 and evaluating the current status of treatment. Methods: An e - mail questionnaire survey was conducted for Korean medicine doctor(K.M.D) registered in Korean Medicine Association. Survey data were analyzed through Excel. Results: The most common Korean medicine treatments used in clinic were acupuncture(adjacent points)(28.5%), cupping therapy(19.7%) and pharmacopuncture(9.8%). The treatments with high patient satisfaction were acupuncture (adjacent points)(27.9%), moxibustion(22.4%) and herbal medicine(10.4%). Herbal medicine(17.9%), tuina(10.7%) and embedding therapy(9.2%) were difficult to perform during treatment because of cost. In the case of a later revision, respondents most thought it is necessary to update evidence and adjust recommendation ratings. A majority of all respondents said they would like to know about the revised guideline through the Internet. In the expected revision effect, the first order was 'presentation of standardized treatment method', the second was 'establishing the basis of Korean medicine treatment', and the third was 'strengthening the status of Korean medicine as therapeutic medicine'. Many respondents wished to add exercise therapy. In order to increase the utilization rate of the guideline, many respondents thought it should be included in textbooks and 90.6% of respondents answered that they would use more than 50% of the revised guideline. Conclusion: It is necessary to update evidence and adjust recommendation ratings and to promote KMCGP. At the same time treatment methods should be taught to K.M.D

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.619-630
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• 2019

Dyslipidemia is a representative chronic disease affecting Koreans that requires continuous management. It is also a known risk factor for cardiovascular disease such as hypertension and diabetes. However, it is difficult to diagnose vascular disease without a medical examination. This study identifies risk factors for the recognition and prevention of dyslipidemia. By integrating them, we construct a statistical instrumental nomogram that can predict the incidence rate while visualizing. Data were from the Korean National Health and Nutrition Examination Survey (KNHANES) for 2013-2016. First, a chi-squared test identified twelve risk factors of dyslipidemia. We used a naïve Bayesian classifier model to construct a nomogram for the dyslipidemia. The constructed nomogram was verified using a receiver operating characteristics curve and calibration plot. Finally, we compared the logistic nomogram previously presented with the Bayesian nomogram proposed in this study.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1088-1095
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• 2019

The information and communication technology that is being developed recently has been greatly influencing the automobile market. In recent years, devices equipped with IT technology have been installed for the safety and convenience of the driver. However, it has the advantage of increased convenience as well as the disadvantage of increasing traffic accidents due to driver's distraction. In order to prevent such accidents, it is necessary to develop safety systems of various types and ways. In this paper implements a platform that can recognize LDWS and FCWS and PDWS by using a single camera without using radar sensor and camera fusion and stereo camera method using two or more sensors, and proposes to study multi-function driving safety platform using a single camera by analyzing recognition rate evaluation and validity on a vehicle.

• Journal of the Korean Society of Food Culture
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• v.34 no.1
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• pp.34-43
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• 2019

The aim of this study was to develop and evaluate a nutrition education program that was designed to increase the knowledge, attitudes, and skills of Korean adults regarding nutrition labeling. The education program was 45 minutes of short-term training, which was conducted in the form of lectures and exercises. The contents of the program were as follows: in the introduction stage, talking about status and reasons for checking nutrition labels; in the development stage, explanation of nutrition labeling and their content, reading, and identifying sample nutrition labels, as well as comparing nutrition labels and selecting better foods; in the closing stage, summary of nutrition labeling and a pledge to check nutrition labels when purchasing processed food. A total of 53 adults (88.5% female) aged 30 years and over participated in this study. The nutrition labeling awareness of the subjects was increased significantly from 55.8 to 96.2% after the education. After the education, the correct recognition rate of a nutrition label was increased significantly from 26.9 to 78.8% for the amount of food, from 25.0 to 73.1% for the calorie content, from 36.5 to 69.2% for the nutrient contents, and from 30.8 to 82.7% for the percent daily value. The self-efficacy of checking nutrition labels was also increased significantly compared to that before the education. The overall satisfaction score of the nutrition education program was 4.2 out of 5. The outcome showed that the nutrition education program of nutrition labeling improved the participants' awareness and self-efficacy towards checking nutrition labels.

• Journal of Trauma and Injury
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• v.32 no.2
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• pp.93-100
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• 2019

Purpose: Penetrating vascular trauma though less common poses a challenge to all Surgeons. This study was designed to analyse the profile, management modalities of vascular trauma and the outcomes thereof at a Trauma Care Centre in a Tertiary care setting in hostile environment in India. Methods: A prospective review of all patients with arterial and venous injuries being transferred to the Trauma Center at out Tertiary Care Center between June 2015 and May 2018 was done. Demographics, admission data, treatment, and complications were reviewed. Results: There were a total of 46 patients with 65 vascular injuries, 39 arterial injuries and 26 venous injuries. The age range was 21 to 47 years. Nineteen patients had both arterial and venous injuries. A total of 42 cases presented within 12 hours of injury and complete arterial transections were found in 33 cases (80.49%). There were three mortalities (6.52%) and three amputations (8.33%). The overall limb salvage rate was 91.67% with popliteal artery being the commonest injured artery. Poor prognosticators for limb salvage were increasing time to present to the trauma centre, hypovolemic shock, multi-organ trauma and associated venous injuries. Conclusions: Penetrating missile trauma leading to vascular injuries has not been widely reported. Attempting limb salvage even in cases with delayed presentation should be weighed with the threat to life before revascularisation and should preferably be done at a centre with vascular expertise. A team approach with vascular, orthopaedic, general surgeons, and critical care anaesthesiologists all aboard improve the outcomes manifold. Use of tourniquets and early fasciotomies have been emphasized as is the use of native veins as the bypass conduit. This is probably the largest study on penetrating Vascular trauma in anti-terrorism ops from the Indian subcontinent. It highlights the significance of prompt recognition and availability of vascular expertise in optimally managing cases of vascular trauma.

• The Journal of the Acoustical Society of Korea
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• v.38 no.3
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• pp.308-313
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• 2019

Parkinson's disease, one of the three major diseases in old age, has more than 70 % of patients with speech disorders, and recently, diagnostic methods of Parkinson's disease through speech signals have been devised. In this paper, we propose a method of diagnosis of Parkinson's disease based on deep residual gated recurrent neural network using speech features. In the proposed method, the speech features for diagnosing Parkinson's disease are selected and applied to the deep residual gated recurrent neural network to classify Parkinson's disease patients. The proposed deep residual gated recurrent neural network, an algorithm combining residual learning with deep gated recurrent neural network, has a higher recognition rate than the traditional method in Parkinson's disease diagnosis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1427-1434
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• 2021

In this paper, we propose a psychological state estimation process that computes children's attention and tension in response to training stimuli. Joint attention was adopted as the training stimulus required for behavioral intervention, and the Discrete trial training (DTT) technique was applied as the training protocol. Three types of training stimulation contents are composed to check the user's attention and tension level and provided mounted on a character-shaped tabletop robot. Then, the gaze response to the user's training stimulus is estimated with the vision-based head pose recognition and geometrical calculation model, and the nervous system response is analyzed using the PPG and GSR bio-signals using heart rate variability(HRV) and histogram techniques. Through experiments using robots, it was confirmed that the psychological response of users to training contents on joint attention could be quantified.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.635-644
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• 2020

Object recognition, detection and instance segmentation based on DL (Deep Learning) have being used in various practices, and mainly optical images are used as training data for DL models. The major objective of this paper is object segmentation and building detection by utilizing multimodal datasets as well as optical images for training Detectron2 model that is one of the improved R-CNN (Region-based Convolutional Neural Network). For the implementation, infrared aerial images, LiDAR data, and edges from the images, and Haralick features, that are representing statistical texture information, from LiDAR (Light Detection And Ranging) data were generated. The performance of the DL models depends on not only on the amount and characteristics of the training data, but also on the fusion method especially for the multimodal data. The results of segmenting objects and detecting buildings by applying hybrid fusion - which is a mixed method of early fusion and late fusion - results in a 32.65% improvement in building detection rate compared to training by optical image only. The experiments demonstrated complementary effect of the training multimodal data having unique characteristics and fusion strategy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2086-2097
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• 2021

The current cultural assets are being restored depending on the opinions of experts (craftsmen). We intend to introduce digitalized artificial intelligence techniques, excluding the personal opinions of experts on reconstruction of such cultural properties. The first step toward restoring digitized cultural properties is separation. The restoration of cultural properties should be reorganized based on recorded documents, period historical backgrounds and regional characteristics. The cultural properties in the form of photographs or images should be collected by separating the background. In addition, when restoring cultural properties most of them depend a lot on the tendency of the restoring person workers. As a result, it often occurs when there is a problem in the accuracy and reliability of restoration of cultural properties. In this study, we propose a search method for learning stored digital cultural assets using AI technology. Pagoda was selected for restoration of Cultural Properties. Pagoda data collection was collected through the Internet and various historical records. The pagoda data was classified by period and region, and grouped into similar buildings. The collected data was learned by applying the well-known CNN algorithm for artificial intelligence learning. The pagoda search used Yolo Marker to mark the tower shape. The tower was used a total of about 100-10,000 pagoda data. In conclusion, it was confirmed that the probability of searching for a tower differs according to the number of pagoda pictures and the number of learning iterations. Finally, it was confirmed that the number of 500 towers and the epochs in training of 8000 times were good. If the test result exceeds 8,000 times, it becomes overfitting. All so, I found a phenomenon that the recognition rate drops when the enemy repeatedly learns more than 8,000 times. As a result of this study, it is believed that it will be helpful in data gathering to increase the accuracy of tower restoration.