• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.30 no.3
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• pp.116-120
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• 2019

Objectives: This study was conducted to re-validate the clinical efficacy of the Korean Adult Attention-Deficit/Hyperactivity Disorder (ADHD) Rating Scale (K-AARS), which is a self-report scale for ADHD in adults, and to determine the clinical utility and cut-off scores of K-AARS. Methods: The participants were 135 drug naïve adults with ADHD and 144 healthy controls. To diagnose ADHD based on the diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition, two board-certified pediatric psychiatrists interviewed the participants and completed the Mini International Neuropsychiatric Interview. K-AARS was applied to all participants. K-AARS comprises six clinical subscales, one impairment subscale, and one driving behavior subscale. The receiver operating characteristic analysis was conducted to calculate the cut-off scores of K-AARS. Results: All subscale scores, including six clinical subscale, impairment subscale, and driving behavior subscale scores, were found to be significant in distinguishing adults with ADHD from healthy controls. The sensitivity and specificity of the six clinical subscales were 63.0-77.0% and 66.7-79.9%, respectively. The combined total score of the six clinical subscales, had a sensitivity of 80.0% and specificity of 79.9%. Conclusion: The discriminative power of K-AARS for the diagnosis of ADHD in adults was excellent, and K-AARS and the empirical diagnosis of adults can be useful in diagnosing ADHD in adulthood.

• The Journal of Korean Medicine
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• v.31 no.6
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• pp.58-63
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• 2010

Objective: We present a case of chemotherapy-induced neuropathic pain with the aim of driving further study evaluating the effectiveness of Oriental medical treatment on patients with neuropathic pain. Method: We prescribed Bogijetong-tang (BJT) two times a day and performed acupuncture and moxibustion once a day over one month of hospitalization. Laboratory tests were performed twice a month during this period. To evaluate the therapeutic effect, Total Symptom Score (TSS) or Visual Analog Score (VAS) was examined at intervals of 7 days. Result: Laboratory data showed no abnormal signs compared with those of initial examination. The patient's subjective symptoms were rapidly relieved within one month. Also, the sums of TSS scores (upper limbs/lower limbs) decreased from 13.64/7.32 to 3.32/3.32 points, and VAS scores (upper limbs/lower limbs) improved from 19/10 to 6/8 points. Conclusion: This case presents a possibility that Oriental medical treatment may offer potential benefits (from an approach aimed at relieving of pain) for patients with chemotherapy-induced neuropathic pain.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.31 no.4
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• pp.367-377
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• 2021

Objectives: Taxi drivers are exposed to various hazards, such as long periods of sedentary work and traffic-related air pollutants. However, studies on the health effects among taxi drivers in South Korea are insufficient. Methods: To assess subclinical hematologic change related to cardiovascular disease among male taxi drivers, we analyzed data from the second Korean National Environmental Health Survey. Fifty-nine taxi drivers and 1,912 controls were included in the analysis. Propensity score matching was performed to adjust for age, body mass index, and urinary cotinine. A total of 295 subjects were matched with 59 taxi drivers. Leukocyte count, platelet count, hematocrit, triglyceride, total cholesterol, HDL cholesterol land total IgE of the taxi drivers were compared with the control groups. Results: Taxi drivers showed significantly elevated blood leukocytes and platelets. Serum total IgE was significantly reduced in taxi drivers. However, blood leukocytes, platelets, and serum total IgE were not significantly correlated with work period among taxi drivers. Conclusions: Regarding the change of the blood leukocyte count, platelet count, and serum total IgE, taxi driving has the possibility to be associated with peripheral inflammation, humoral immunity and cardiovascular risk.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.2
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• pp.157-163
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• 2017

The aim of the study is to examine the reliability and validity of UFOV, which is a visual driving evaluation tool that has been proven to be reliable and valid in western countries, for the purpose of adapting the tool in a systematic manner to the South Korean population. Two evaluator assessed 23 healthy and 19 stroke patients with UFOV, Trail Making Test A & B(TMT A & B) and Motor Free Visual Perception Test(MVPT) from 7 October 2014 to 25 November, 2014. The researcher analyzed inter-rater reliability, correlation between raters of UFOV with Intraclass correlation coefficient, test-retest reliablility, UFOV with spearman correlation coefficient, concurrent validity, UFOV, TMT A & B and MVPT with spearman correlation coefficient, and discriminative validity, comparison mean scores of UFOV between groups, healthy and stroke with Mann-Whitney U test. UFOV score of participants with stroke had lower compared to the healthy control group. The inter-rater reliability(p<.001), test-retest reliability(p<.01) and concurrent validity(p<.01) was statistically significant. Also discriminant validity was statistically significant(p<.001). Based on this study, Use of UFOV for drivers at risk is essential to prevent future traffic accidents and support driving rehabilitation.

• Physical Therapy Rehabilitation Science
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• v.11 no.3
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• pp.363-369
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• 2022

Objective: The purpose of this study was to prepare evidence for the prevention and management of nonspecific chronic neck pain (NSCNP) by examining the correlation between activity of daily living and physical activities of office workers with NSCNP. Design: Crossed-sectional study Methods: 89 patients with NSCNP were recruited for this study. But 2 subjects met the exclusion criteria and were dropped out, and 86 subjects finally participated. Numerical pain rating scale (NPRS) and neck disability index (NDI) were used to check the pain intensity and disability of patients with neck pain, respectively. For the activity of daily living, computer use time, sleep time, and driving time were used. To find out the physical activities of the subjects, International Physical Activity Questionnaires (IPAQ-SF) was used. Correlation analysis was performed to find out the correlation of each variable. Results: A clear positive correlation was established between computer use time and pain (p<0.05), and a clear positive correlation was established between computer use time and disability index (p<0.05). The correlation between NPRS and NDI and physical activity total time, high intensity activity score, moderate intensity activity score, and walking score were not statistically significant (p>0.05). Conclusions: In treating patients with NSCNP, it is necessary to reduce the computer usage time as a professional factor or to educate the proper posture. In addition, rather than emphasizing physically comprehensive physical activity, grafting therapeutic exercise directly related to neck pain could have a more positive effect on NSCNP patients.

• International Journal of Automotive Technology
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• v.6 no.4
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• pp.367-374
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• 2005

This paper proposes a sound quality index to evaluate the vehicle interior noise. The index was developed using a correlation analysis of an objective measurement and a subjective evaluation data. First, the objective set of measurements was obtained at two specified driving conditions. One is from a wide-open test condition and the other is from a constant-speed test condition. At the same time, subjective evaluation was carried out using a score of ten scale where 17 test engineers participated in the experiment. The correlation analysis between the psycho-acoustic parameters derived from the objective measurement and the subjective evaluation was performed. The most critical factors at both test conditions were determined, and the corresponding equations for the sound quality were obtained from the multiple factor regression method. Finally, a comparative work between previous index and present index was performed to validate the effectiveness of the proposed index.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.1
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• pp.1-8
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• 2021

Detecting Out-of-Distribution (OOD) data is fundamentally required when Deep Neural Network (DNN) is applied to real-world AI such as autonomous driving. However, modern DNNs are quite vulnerable to the over-confidence problem even if the test data are far away from the trained data distribution. To solve the problem, this paper proposes a novel Adversarial-Mixup training method to let the DNN model be more robust by detecting OOD data effectively. Experimental results show that the proposed Adversarial-Mixup method improves the overall performance of OOD detection by 78% comparing with the State-of-the-Art methods. Furthermore, we show that the proposed method can alleviate the over-confidence problem by reducing the confidence score of OOD data than the previous methods, resulting in more reliable and robust DNNs.

• ETRI Journal
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• v.45 no.5
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• pp.862-873
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• 2023

Determining whether an autonomous self-driving agent is in the middle of an intersection can be extremely difficult when relying on visual input taken from a single camera. In such a problem setting, a wider range of views is essential, which drives us to use three cameras positioned in the front, left, and right of an agent for better intersection recognition. However, collecting adequate training data with three cameras poses several practical difficulties; hence, we propose using data collected from one camera to train a three-camera model, which would enable us to more easily compile a variety of training data to endow our model with improved generalizability. In this work, we provide three separate fusion methods (feature, early, and late) of combining the information from three cameras. Extensive pedestrian-view intersection classification experiments show that our feature fusion model provides an area under the curve and F1-score of 82.00 and 46.48, respectively, which considerably outperforms contemporary three- and one-camera models.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.939-951
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• 2022

The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.

• Physical Therapy Korea
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• v.4 no.2
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• pp.18-35
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• 1997

The purpose of this study were to determine causes of low back pain in bus drivers who usually work in prolonged sitting position and to find the relationship of back pain with general characteristics and work environmental characteristics, stress symptoms, to com맹re lordosis angle of habitual driving posture and resting posture in low back pain group and non-low back pain group, and to use this result as a basis for improvement of work environment and comprehensive rehabilitative management of low back pain. Ninety-eight bus drivers were selected from the membership of an urban transit union in Seoul. These informations were collected from May 1, 1997 to May 25, 1997 by means of structured questionnaires and X-ray findings. These data were analyzed by $x^2$ test, t-test, logistic regression using SAS. The major results were as follows: 1. Of the respondents, 66.3% of bus drivers were found to be experiencing back pain. 2. Of the respondents of low back pain groups, 78.5% reported that major cause of low back pain was due to prolonged sitting. 3. The group with experiences of frequent or continuous vibration had more low back pain (p<0.05). There were no significant differences among other work environmental factors. 4. Average stress score was significantly higher in the group with low back pain than in the group without low back pain (p<0.05). 5. The results of the logistic regression analyses were statistically significant vibration from seat and stress score among the risk factors (p<0.05). 6. Averaged lordosis angle of habitual driving posture was $7.6{\pm}14.9$ degrees in low back pain group, $16.5{\pm}8.7$ degrees in non-low back pain and averaged lordosis angle of resting sitting posture was $10.8{\pm}13.7$ degrees in low back pain, $18.9{\pm}9.6$ degrees in non-low back pain group but the difference in mean lordosis angles of two groups was not statistically significant. The results of this study indicate that professional drivers developed chronicity of low back pain due to unfit seat, poor habitual posture and stress from vibration or other risk factors. Therefore, there is need to improve work environment, i.e. enough resting, to set a seat to support lumbar spine properly and to provide comprehensive rehabilitation program including early diagnosis, proper treatment and education for self help management.