• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.380-386
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• 2019

Shoulder joint pain is a very common musculoskeletal disorder, in which about 20 percent of adults experience it more than once in their lives. In this study, an objective assessment was made that subacromial space was increased by pectoralis minor stretching exercise, which has a positive effect on impingement syndrome and shoulder pain. Also, This study examined the effects on pectoralis minor length(PML) and acromio-humeral distance(AHD) following pectoralis minor self-stretching exercise in normal adults. In this study, a total of 30 subjects were recruited and randomly divided into a self-stretching exercise group(n=15) and manual stretching exercise group(n=15) to compare the immediate effects of treatment. Studies have shown that both groups have significantly increased both PML and AHD within the group(p<.05). There was no statistically significant difference in the comparison between the groups(p>.05). The results suggest that self-stretching exercise can be recommended as a treatment method for impingement syndrome and prevention of shoulder disease.

• Journal of Environmental Impact Assessment
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• v.30 no.5
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• pp.297-304
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• 2021

The environmental impact assessment(EIA) project in Korea has undergone changes and revisions in various evaluation items for about 30 years after the introduction of the Environmental Conservation Act (1997). However, despite the importance of land use evaluation items under the current EIA Act, there are insufficient studies to consider. Therefore, this study focused on the land-use evaluation items based on the EIA guidelines, reviewed 90 of the evaluation documents and consultation documents, and tried to suggest implications and supplementary points forthe domestic EIA land-use evaluation items. As a result, the paradigm was changing from land efficiency centered on development in the past to land efficiency centered on the natural environment and resource conservation. However, in spite of the manual for fitting the paradigm change, opinions on the conservation of the natural environment are still being drawn in the consultation document, so it needs improvement. Two improvements in the impact assessment process suggested in this study are the establishment of standardized spatial data and a quantitative impact and reduction method evaluation tool based on it. In particular, there is a need for a plan evaluation tool for land use arrangement and distribution that can solve the needs of minimizing damage to the natural environment and securing green space and a green network.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.499-506
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• 2021

Hackers' cyber attack techniques are becoming more sophisticated and diversified, with a form of attack that has never been seen before. In terms of information security vulnerability standard code (CVE), about 90,000 new codes were registered from 2015 to 2020. This indicates that security threats are increasing rapidly. When new security vulnerabilities occur, damage should be minimized by preparing countermeasures for them, but in many cases, companies are insufficient to cover the security management level and response system with a limited security IT budget. The reason is that it takes about a month for analysts to discover vulnerabilities through manual analysis, prepare countermeasures through security equipment, and patch security vulnerabilities. In the case of the public sector, the National Cyber Safety Center distributes and manages security operation policies in a batch. However, it is not easy to accept the security policy according to the characteristics of the manufacturer, and it takes about 3 weeks or more to verify the traffic for each section. In addition, when abnormal traffic inflow occurs, countermeasures such as detection and detection of infringement attacks through vulnerability analysis must be prepared, but there are limitations in response due to the absence of specialized security experts. In this paper, we proposed a method of using the security policy information sharing site "snort.org" to prepare effective countermeasures against new security vulnerability attacks.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.93-106
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• 2021

Many recent studies on deep learning-based road crack detection have shown significantly more improved performances than previous works using algorithm-based conventional approaches. However, many deep learning-based studies are still focused on classifying the types of cracks. The classification of crack types is highly anticipated in that it can improve the crack detection process, which is currently relying on manual intervention. However, it is essential to calculate the severity of the cracks as well as identifying the type of cracks in actual pavement maintenance planning, but studies related to road crack detection have not progressed enough to automated calculation of the severity of cracks. In order to calculate the severity of the crack, the type of crack and the area of the crack in the image must be identified together. This study deals with a method of using Mobilenet-SSD that is deep learning-based object detection techniques to effectively automate the simultaneous detection of crack types and crack areas. To improve the accuracy of object-detection for road cracks, several experiments were conducted to combine the U-Net for automatic segmentation of input image and object-detection model, and the results were summarized. As a result, image masking with U-Net is able to maximize object-detection performance with 0.9315 mAP value. While referring the results of this study, it is expected that the automation of the crack detection functionality on pave management system can be further enhanced.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.174-192
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• 2021

The LIDAR sensor, which provides higher cognitive performance than cameras and radar, is difficult to apply to ADAS or autonomous driving because of its high price. On the other hand, as the price is decreasing rapidly, expectations are rising to improve existing autonomous driving functions by taking advantage of the LIDAR sensor. In level 3 autonomous vehicles, when a dangerous situation in the cognitive module occurs due to a sensor defect or sensor limit, the driver must take control of the vehicle for manual driving. If the driver does not respond to the request, the system must automatically kick in and implement a minimum risk maneuver to maintain the risk within a tolerable level. In this study, based on this background, a LIDAR-based LKS MRM algorithm was developed for the case when the normal operation of LKS was not possible due to troubles in the cognitive system. From point cloud data collected by LIDAR, the algorithm generates the trajectory of the vehicle in front through object clustering and converts it to the target waypoints of its own. Hence, if the camera-based LKS is not operating normally, LIDAR-based path tracking control is performed as MRM. The HAZOP method was used to identify the risk sources in the LKS cognitive systems. B, and based on this, test scenarios were derived and used in the validation process by simulation. The simulation results indicated that the LIDAR-based LKS MRM algorithm of this study prevents lane departure in dangerous situations caused by various problems or difficulties in the LKS cognitive systems and could prevent possible traffic accidents.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.751-760
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• 2021

Most bridges in Korea are over 20 years old, and many problems linked to their deterioration are being reported. The current practice for bridge inspection mainly depends on expert evaluation, which can be subjective. Recent studies have introduced data-driven methods using building information modeling, which can be more efficient and objective, but these methods require manual procedures that consume time and money. To overcome this, this study developed an image-based automaticbridge component classification network to reduce the time and cost required for converting the visual information of bridges to a digital model. The proposed method comprises two convolutional neural networks. The first network estimates the type of the bridge based on the superstructure, and the second network classifies the bridge components. In avalidation test, the proposed system automatically classified the components of 461 bridge images with 96.6 % of accuracy. The proposed approach is expected to contribute toward current bridge maintenance practice.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.3
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• pp.241-264
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• 2022

Bibliographic metadata can help researchers effectively utilize essential publications that they need and grasp academic trends of their own fields. With the manual creation of the metadata costly and time-consuming. it is nontrivial to effectively automatize the metadata construction using rule-based methods due to the immoderate variety of the article forms and styles according to publishers and academic societies. Therefore, this study proposes a two-step extraction process based on rules and deep neural networks for generating bibliographic metadata of scientific articlles to overcome the difficulties above. The extraction target areas in articles were identified by using a deep neural network-based model, and then the details in the areas were analyzed and sub-divided into relevant metadata elements. IThe proposed model also includes a model for generating reference summary information, which is able to separate the end of the text and the starting point of a reference, and to extract individual references by essential rule set, and to identify all the bibliographic items in each reference by a deep neural network. In addition, in order to confirm the possibility of a model that generates the bibliographic information of academic papers without pre- and post-processing, we conducted an in-depth comparative experiment with various settings and configurations. As a result of the experiment, the method proposed in this paper showed higher performance.

• Journal of the Korean Society of Floral Art and Design
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• no.45
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• pp.47-56
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• 2021

It was applied by making the models such as the prior learning (e-learning), modeling by manual, learner's practice, 1:1 teaching coaching, self evaluation, coaching behavior assessment(primary, secondary), and self-directed practice. First, the cognitive practice education through the prior learning is very essential in the practice of floral design. Second, the practice class of floral design is a class where the professor generally set an example first, and the learners followed. Third, this study was to prepare the checklist, reflect it through the self evaluation, and prepare the evaluation form in accordance with the element, principle, and technical parts of floral design about the finished works. Fourth, contrary to the existing class completing within the class hour, the practice class is a process of trying to do self-directed practice, returning to home. Fifth, this study was to evaluate the works the learner made once again through the sketching and photographing by placing the work process of portfolio at the last step. To conclude, this study has found that such series of process through six steps on the practice form by the learner only would be excellent teaching learning model to improving the basic capacity of floral design. Accordingly, the development of teaching materials related to this and adaptation in the field in the future is considered as it will be very helpful to the learners' self-directed learning.

• Journal of the Korean Society of Radiology
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• v.16 no.7
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• pp.985-993
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• 2022

This study was conducted to compare and evaluate the expectations and satisfaction of clinical practice for students who conducted practice at clinical practice institutions of various sizes before and after COVID-19, and to suggest future clinical practice guidance methods and operation directions. There was a significant difference in the evaluation of satisfaction with practice before and after COVID-19, especially after the evaluation of satisfaction with practice guidance, practice environment, and practice time. As a result of analyzing the decisive influencing factors related to practice satisfaction, students who conducted practice at university hospitals highly evaluated the institutional environmental factors, and students who conducted practice at small and medium-sized hospitals showed high satisfaction in participation-oriented practice. Therefore, it is thought that practice that utilizes the strengths and weaknesses of university hospitals and small and medium-sized hospitals will be more effective than clinical practice that relies only on university hospitals. However, in order to diversify the training institution to small and medium-sized hospitals, it is necessary to create a manual on standardized training courses, training methods, and evaluation methods suitable for the training goals and curriculum, and provide them to the institution. In addition, if it is operated through sufficient exchange of opinions and consultation with institutions, schools will be able to obtain opportunities to cultivate practical talents, and small and medium-sized hospitals with difficulties in expanding manpower will be able to secure excellent human resources first.

• Journal of the Korean Society of Food Culture
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• v.37 no.1
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• pp.1-12
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• 2022

This qualitative study analyzed various environmental factors and difficulties faced by school foodservices during the COVID-19 pandemic. Focus group interviews were conducted by enrolling 12 nutrition teachers and nutritionists. Data collected were subsequently analyzed for changes implemented during the pandemic, in hygiene management, diet management, and distribution management of the school meal. The content and method of delivery of information related to diet guidance and school foodservice by related organizations were also examined. Results of the survey show that personal hygiene (such as maintaining student-to-student distance, checking students for a fever, and hand disinfection) was duly applied, installation of table coverings and distancing between school cafeteria seats were conducted, and mandatory mask-wearing to prevent droplet transmission was enforced. Depending on the COVID-19 situation, the number of students having school meals was limited per grade, and time-spaced meals were provided. To prevent infection, menus that required frequent hand contact were excluded from the meal plan. Overall, it was difficult to manage the meal plan due to frequent changes in tasks, such as the number of orders and meal expenses. These changes were communicated by nutrition teachers and nutritionists wherein the numbers of school meals were adjusted, depending on situations arising from each COVID-19 crisis stage. Furthermore, in some schools, either face-to-face nutrition counseling was stopped entirely, or nutrition education was conducted online. Parent participation was disallowed in the monitoring of school meals, and the prohibition on conversations inside the school cafeteria resulted in the absence of communication among students, nutrition teachers, and nutritionists. Additionally, confusion in meal management was caused by frequent changes in the school meal management guidelines provided by the Office of Education and the School Health Promotion Center in response to COVID-19. In anticipation of the emergence of a new virus or infectious diseases caused by mutations in the years to come, it is suggested that a holistic, well-thought-out response manual for safe meal operation needs to be established, in close collaboration with schools and school foodservice-related institutions.