• The Journal of Korean Academy of Sensory Integration
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• v.19 no.1
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• pp.69-82
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• 2021

Objective : This recent work intended to provide basic information for researchers and practitioners related to occupational therapy about Developmental Coordination Disorder (DCD) in South Korea. The previous research of screening DCD and the effects of intervention programs were reviewed. Methods : Peer-reviewed papers relating to DCD and published in Korea from January 1990 to December 2020 were systematically reviewed. The search terms "developmental coordination disorder," "development coordination," and "developmental coordination" were used to identify previous Korean research in this area from three representation database, the Research Information Sharing Service, Korean Studies Information Service System, and Google Scholar. We found a total of 4,878 articles identified through the three search engines and selected seventeen articles for analysis after removing those that corresponded to the overlapping or exclusion criteria. We adopted "the conceptual model" to analyze the selected articles about DCD assessment and intervention. Results : We found that twelve of the 17 studies showed the qualitative level of Level 2 using non-randomized approach between the two groups. The Movement Assessment Battery for Children and its second edition were the most frequently used tools in assessing children for DCD. Among the intervention studies, the eight articles (47%) were adopted a dynamic systems approach; a normative functional skill framework and cognitive neuroscience were each used in 18% of the pieces; and 11% of the articles were applied neurodevelopmental theory. Only one article was used a combination approach of normative functional skill and general abilities. These papers were mainly focused on the movement characteristics of children with DCD and the intervention effect of exercise or sports programs. Conclusion : Most of the reviewed studies investigated the movement characteristics of DCD or explore the effectiveness of particular intervention programs. In the future, it would be useful to investigate the feasibility of different assessment tools and to establish the effectiveness of various interventions used in rehabilitation for better motor performance in children with DCD.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.384-392
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• 2022

The objective of this study was to estimated nitrogen content and chlorophyll using RGB, Hyperspectral sensors to diagnose of nitrogen nutrition in apple tree leaves. Spectral data were acquired through image processing after shooting with high resolution RGB and hyperspectral sensor for two-year-old 'Hongro/M.9' apple. Growth data measured chlorophyll and leaf nitrogen content (LNC) immediately after shooting. The growth model was developed by using regression analysis (simple, multi, partial least squared) with growth data (chlorophyll, LNC) and spectral data (SPAD meter, color vegetation index, wavelength). As a result, chlorophyll and LNC showed a statistically significant difference according to nitrogen fertilizer level regardless of date. Leaf color became pale as the nutrients in the leaf were transferred to the fruit as over time. RGB sensor showed a statistically significant difference at the red wavelength regardless of the date. Also hyperspectral sensor showed a spectral difference depend on nitrogen fertilizer level for non-visible wavelength than visible wavelength at June 10th and July 14th. The estimation model performance of chlorophyll, LNC showed Partial least squared regression using hyperspectral data better than Simple and multiple linear regression using RGB data (Chlorophyll R²: 81%, LNC: 81%). The reason is that hyperspectral sensor has a narrow Full Half at Width Maximum (FWHM) and broad wavelength range (400-1,000 nm), so it is thought that the spectral analysis of crop was possible due to stress cause by nitrogen deficiency. In future study, it is thought that it will contribute to development of high quality and stable fruit production technology by diagnosis model of physiology and pest for all growth stage of tree using hyperspectral imagery.

• 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.

• Journal of Life Science
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• v.32 no.4
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• pp.325-330
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• 2022

While swimming is a very popular competitive sports activity, swimming injuries are unique due to the repetitive nature of the swimming stroke and demanding training programs that can result in upper limb overuse. Therefore, the primary objective of this review was to analyze swimmers' injury areas, injury types by stroke type, and swimming rehabilitation, as well as to discuss safety management for improving swimming performance. In this study, the injuries incurred in swimming events were discussed in the order of upper limb injuries (neck, shoulder, arm, and wrist), lower limb injuries (knee and ankle), and waist injuries. An analysis by stroke type found that shoulder injuries occurred most often with freestyle, backstroke, and butterfly strokes, followed by rotator cuff injury, impingement syndrome, and SLAP (superior labral tear from anterior to posterior) lesions. Knee injuries were associated with the breaststroke, whereas spinal cord injuries occurred with the breaststroke and butterfly stroke. Finally, back injuries were associated with the butterfly stroke. During the freestyle stroke, the shoulder undergoes repetitive overhead movement; hence, shoulder and musculoskeletal pain are the most common and well-documented complaints of swimmers. For safety management, coaches and instructors must ensure that athletes do sufficient warm-up and cool-down exercises to avoid injuries. In case of an injury, they should be familiar with first aid measures so that secondary damage can be prevented with its quick application. In addition, coaches and instructors need to be trained in injury prevention and treatment so that they can provide appropriate rehabilitation treatment for athletes. Although swimming-related injuries cannot be completely eliminated, to reduce them to a minimum, leaders need the knowledge to apply scientific and systematic training principles and methods individualized for each athlete.

• Journal of agricultural medicine and community health
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• v.47 no.3
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• pp.166-180
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• 2022

Objective: This study evaluated the effects of a non-face-to-face obesity management program, implemented during the pandemic. Methods: The non-face-to-face obesity management program used the Intervention mapping protocol (IMP). The program was put into effect over the course of eight weeks, from September 14 to November 13, 2020 in 48 overweight and obese adults, who applied to participate through the Daegu Citizen Health Support Center. Results: IMP was first a needs assessment was conducted; second, goal setting for behavior change was established; third, evidence-based selection of arbitration method and performance strategy was performed; fourth, program design and validation; fifth, the program was run; and sixth, the results were evaluated. The average weight after participation in the program was reduced by 1.2kg, average WC decreased by 3cm, and average BMI decreased by 0.8kg/m² (p<0.05). The results of the health behavior survey showed a positive improvement in lifestyle factors, including average daily intake calories, fruit intake, and time spent in walking exercise before and after participation in the program. A statistically significant difference was seen (p<0.05). The satisfaction level for program process evaluation was high, at 4.57±0.63 point. Conclusion: The non-face-to-face obesity management program was useful for obesity management for adults in communities, as it enables individual counseling by experts and active participation through self-body measurement and recording without restriction by time and place. However, the program had some restrictions on participation that may relate to the age of the subject, such as skill and comfort in using a mobile app.

• Journal of agricultural medicine and community health
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• v.47 no.2
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• pp.90-98
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• 2022

Objective: This study aimed to provide basic data for preventing and managing sarcopenia by identifying the relationship between sarcopenia, malnutrition, and psychosocial factors among the elderly in the community. Methods: The study included 1,019 subjects aged 60 and over. "Possible sarcopenia" was defined by low handgrip strength with or without reduced physical performance. Nutrition was evaluated according to the mini nutrition assessment (MNA), and the psychosocial factors examined were self-efficacy, social isolation, fear of falling, and social capital (trust and participation). A logistic regression analysis was also performed on the relationship between risk of malnutrition, psychosocial factors, and sarcopenia. Results: MNA was significantly associated with social participation (OR = 1.747, p <0.001), fear of falling (OR = 2.905, p <0.001), and self-efficacy (high/low, OR = 0.654, p = 0.011). In model 3, which included both MNA and psychosocial factors, sarcopenia was significantly associated with MNA (OR = 2.529, p <0.001) and fear of falling (OR = 1.544, p = 0.045). Compared with the low self-efficacy group, the high group (OR = 0.589, p = 0.009) was significant. The factors related to possible sarcopenia include risk of malnutrition, fear of falls, and low self-efficacy. Conclusion: It will be necessary to improve self-efficacy so that individuals feel they can do activities of daily living themselves and to reduce their fear of falling through muscle strength and balance exercises. Finally, it is also necessary to increase regular participation in community social activities.

• Journal of Bio-Environment Control
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• v.32 no.1
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• pp.48-56
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• 2023

High-pressure sodium (HPS) lamps have been widely used as a useful supplemental light source to emit sufficient photosynthetically active radiation and provide a radiant heat, which contribute the heat requirement in greenhouses. The objective of this study to analyze the thermal characteristics of HPS lamp and thermal behavior in supplemented greenhouse, and evaluate the performance of a horizontal leaf temperature of sweet pepper plants using computational fluid dynamics (CFD) simulation. We simulated horizontal leaf temperature on upper canopy according to three growth stage scenarios, which represented 1.0, 1.6, and 2.2 plant height, respectively. We also measured vertical leaf and air temperature accompanied by heat generation of HPS lamps. There was large leaf to air temperature differential due to non-uniformity in temperature. In our numerical calculation, thermal energy of HPS lamps contributed of 50.1% the total heat requirement on Dec. 2022. The CFD model was validated by comparing measured and simulated data at the same operating condition. Mean absolute error and root mean square error were below 0.5, which means the CFD simulation values were highly accurate. Our result about vertical leaf and air temperature can be used in decision making for efficient thermal energy management and crop growth.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.57-78
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• 2023

COVID-19, which started in Wuhan, China in November 2019, spread beyond China in 2020 and spread worldwide in March 2020. It is important to prevent a highly contagious virus like COVID-19 in advance and to actively treat it when confirmed, but it is more important to identify the confirmed fact quickly and prevent its spread since it is a virus that spreads quickly. However, PCR test to check for infection is costly and time consuming, and self-kit test is also easy to access, but the cost of the kit is not easy to receive every time. Therefore, if it is possible to determine whether or not a person is positive for COVID-19 based on the sound of a cough so that anyone can use it easily, anyone can easily check whether or not they are confirmed at anytime, anywhere, and it can have great economic advantages. In this study, an experiment was conducted on a method to identify whether or not COVID-19 was confirmed based on a cough sound. Cough sound features were extracted through MFCC, Mel-Spectrogram, and spectral contrast. For the quality of cough sound, noisy data was deleted through SNR, and only the cough sound was extracted from the voice file through chunk. Since the objective is COVID-19 positive and negative classification, learning was performed through XGBoost, LightGBM, and FCNN algorithms, which are often used for classification, and the results were compared. Additionally, we conducted a comparative experiment on the performance of the model using multidimensional vectors obtained by converting cough sounds into both images and vectors. The experimental results showed that the LightGBM model utilizing features obtained by converting basic information about health status and cough sounds into multidimensional vectors through MFCC, Mel-Spectogram, Spectral contrast, and Spectrogram achieved the highest accuracy of 0.74.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.419-429
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• 2023

The objective of this study was to determine the management water level of an estuary reservoir considering three aspects: the water use, flood control and water quality, and to use a robust decision-making to consider uncertainty due to climate change. The watershed-reservoir linkage model was used to simulate changes in inflow due to climate change, and changes in reservoir water level and water quality. Five management level alternatives ranging from -1.7 El.m to 0.2 El.m were evaluated under the SSP1, 2, 3, and 5 scenariosof the ACCESS-CM2 Global Climate Model. Performance indicators based on period-reliability were calculated for robust decision-making considering the three aspects, and regret was used as a decision indicator to identify the alternatives with the minimum maximum regret. Flood control failure increased as the management level increased, while the probability of water use failure increased as the management level decreased. The highest number of failures occurred under the SSP5 scenario. In the water quality sector, the change in water quality was relatively small with an increase in the management level due to the increase in reservoir volume. Conversely, a decrease in the management level resulted in a more significant change in water quality. In the study area, the estuary reservoir was found to be problematic when the change in water quality was small, resulting in more failures.

• The Journal of KAIRB
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• v.2 no.2
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• pp.37-48
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• 2020

Purpose: The purpose of this study is to assess the operational status and level of understanding among IRB and HRPP staffs at a hospital or a research institute to the HRPP guideline set by the Ministry of Food and Drug Safety (MFDS) and to provide recommendations. Methods: Online survey was distributed among members of Korean Association of IRB (KAIRB) through each IRB office. The result was separated according to topic and descriptive statistics was used for analysis. Result: Survey notification was sent out to 176 institutions and 65 (37.1%) institutions answered the survey by online. Of 65 institutions that answered the survey; 83.1% was hospital, 12.3% was university, 3.1% was medical college, 1.5% was research institution. 23 institutions (25.4%) established independent HRPP offices and 39 institutions (60.0%) did not. 12 institutions (18.5%) had separate IRB and HRPP heads, 21 (32.3%) institutions separated business reporting procedure and person in charge, 12 institutions separated the responsibility of IRB and HRPP among staff, and 45 institutions (69.2%) had audit & non-compliance managers. When asked about the most important basic task for HRPP, 23% answered self-audit. And according to 43.52%, self-audit was also the most by both institutions that operated HRPP and institutions that did not. When basic task performance status was analyzed, on average, the institutions that operated HRPP was 14% higher than institutions that only operated IRB. 9 (13.8%) institutions were evaluated and obtained HRPP accreditation from MFDS and the most common reason for obtaining the accreditation was to be selected as Institution for the education of persons conducting clinical trial (6 institutions). The most common reason for not obtaining HRPP accreditation was because of insufficient staff and limited capacity of the institution (28%). Institutions with and without a plan to be HRPP accredited by MFDS were 20 (37.7%) each. 34 institutions (52.3%) answered HRPP evaluation method and accreditation by MFDS was appropriate while 31 institutions (47.7%) answered otherwise. 36 institutions answered that HRPP evaluation and accreditation by MFDS was credible while 29 institutions (44.5%) answered that HRPP evaluation method and accreditation by MFDS was not credible. Conclusion: 1. MFDS's HRPP accreditation program can facilitate the main objective of HRPP and MFDS's HRPP accreditation program should be encouraged to non-tertiary hospitals by taking small staff size into consideration and issuing accreditation by segregating accreditation. 2. While issuing Institution for the education of persons conducting clinical trial status as a benefit of MFDS's HRPP accreditation program, it can also hinder access to MFDS's HRPP accreditation program. It should also be considered that the non-contact culture during COVID-19 pandemic eliminated time and space limitation for education. 3. For clinical research conducted internally by an institution, internal audit is the most effective and sole method of protecting safety and right of the test subjects and integrity for research in Korea. For this reason, regardless of the size of the institution, an internal audit should be enforced. 4. It is necessary for KAIRB and MFDSto improve HRPP awareness by advocating and educating the concept and necessity of HRPP in clinical research. 5. A new HRPP accreditation system should be setup for all clinical research with human subjects, including Investigational New Drug (IND) application in near future.