• Science of Emotion and Sensibility
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• v.24 no.4
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• pp.129-138
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• 2021

This study aimed to determine the effects of the shape and attachment position of stretchable textile sensors coated with carbon nanotube on their performance when used to measure children's joint movements. Moreover, the child-safe requirements for fabric motion sensors are established. The child participants were advised to wear integrated clothing equipped with the sensors of various shapes (rectangular and boat-shaped) and attachment positions (at the knee and elbow joints or 4 cm below the joints). The voltage change induced by the elongation and contraction of the fabric sensors was determined for arm and leg flexion-extension motions at 60 deg/s (three measurements of 10 repeats each for 60°and 90°angles, for a total of 60 repetitions). Their dependability was determined by comparing the fabric motion sensors to the associated acceleration sensors. The experimental results indicate that the rectangular-shaped sensor affixed 4 cm below the joint is the most effective fabric motion sensor for measuring children's arm and leg motions. In this study, we designed a textile sensor capable of tracking children's joint motion and analyzed the sensor shape and attachment position on motion sensing clothing. We demonstrated that flexible fabric sensors integrated into garments may be used to detect the joint motions of the human body.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.37-46
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• 2022

Recently, our society and environment has changed rapidly due to the pandemic caused by the COVID-19 virus. In this rapidly changing environment, companies fulfill their social responsibilities and require non-financial elements of transparent management activities. ESG has become one of the non-financial factors, and interest of ESG management is increasing worldwide. In this paper, we examine the importance of ESG concept and ESG management performance and the correlation with companies, and examine the necessity of ESG management for companies in the future. The literature reviews are conducted on CU which is currently best practicing ESG management through various secondary data. Also, we used interview articles so that reflect the rich voice of the distribution industry. In addition, after examining ESG characteristics through examples of global companies, we looked at BGF Retail's CU convenience store ESG activities, which is a leader in ESG management, in distribution industry. CU was divided into all sectors of E, S, and G, and all sectors were actively engaged in activities and flexibly coping with changing environments and social needs. In particular, it was confirmed that CU's environmental management, which focuses the most, achieved successful results due to the increase in actual consumption of customers. ESG management activities at CU convenience stores are currently ongoing and future tasks. As a leading company in ESG management in the current industry, it is meaningful to understand the process of growing into a company that shares concerns, efforts, and practical activities and fulfills social responsibility. Through this study, the changes and growth of CU and domestic companies to ESG and sustainable management are expected in the futures.

• Korean Journal of Food Science and Technology
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• v.54 no.3
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• pp.351-361
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• 2022

This study aimed to investigate the differences in the isomaltooligosaccharides present during Makgeolli production according to the type of Nuruk used, fermentation period, and presence of microorganisms. Makgeolli was fermented for 15 days using three kinds of Nuruk (Soyul, Sansung, and Jinju) with and without microbial growth inhibitors. Isomaltooligosaccharide contents were analyzed using high performance anion exchange chromatography. The most abundant isomaltooligosaccharide was panose, which was highest in Makgeolli produced using Soyul Nuruk (SH) on day 6 (24.7 mM), followed by Makgeolli prepared using Sansung Nuruk (SS) on day 2 (18.2 mM) and Makgeolli prepared using Jinju Nuruk (JJ) on day 3 (10.8 mM). Isomaltotriose and isomaltotetraose, which were generated in the control, were not detected when microbial growth was suppressed. Based on these results, isomaltooligosaccharide production is affected more by the enzymes produced by microorganisms during Makgeolli fermentation than by Nuruk itself.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.2
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• pp.89-101
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• 2022

The study was conducted in Erhe Park, a neighborhood park in Dali City, China, to derive the influence of environmental factors in the park on the elderly's satisfaction and to analyze the satisfaction in order to provide improvement recommendations. First, the evaluation indicators were selected, by referencing previous research into the elderly's evaluation of external spatial environments and the influence of various factors was determined from the questionnaire and factor analysis. Second, a fuzzy comprehensive evaluation was conducted to understand the satisfaction of the elderly, and then an Importance-Performance Analysis(IPA) analysis was conducted to develop improvement recommendations. Results of the factor analysis showed that park's environmental factors were grouped into four categories: facility suitability and comfort, safety and convenience of use, natural environment comfort, and parkway convenience. Based on this, the overall satisfaction rating for the environmental factors in Erhe Park was between satisfactory and average. The natural environment comfort was rated satisfactory, the facility suitability and comfort, and convenience and safety were rated average, and parkway convenience was rated near to satisfaction. The IPA analysis revealed that the suitability of rest facilities, suitability of convenience facilities, facility management status, safety of entrances and exits, and nighttime lighting facilities were items of high importance but low satisfaction that needed to be improved. The results of this study can be utilized as a guide for future building or readjustment of senior-friendly parks, and they are critical for increasing senior-friendly park satisfaction.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.897-903
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• 2021

Purpose: Recently, ransomware damage that encrypts victim's data through hacking and demands money in exchange for releasing it is increasing domestically and internationally. Accordingly, research and development on various response technologies and solutions are in progress. Method: A secure storage area and a general storage area were created in the same virtual environment, and the sample data was saved by registering the access process. In order to check whether the stored sample data is infringed, the ransomware sample was executed and the hash function of the sample data was checked to see if it was infringed. The access control performance checked whether the sample data was accessed through the same name and storage location as the registered access process. Result: As a result of the experiment, the sample data in the secure storage area maintained data integrity from ransomware and unauthorized processes. Conclusion: Through this study, the creation of a secure storage area and the whitelist-based access control method are evaluated as suitable as a method to protect important data, and it is possible to provide a more secure computing environment through future technology scalability and convergence with existing solutions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.541-548
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• 2021

Recently, multispectral cameras are being actively utilized in various application fields such as agriculture, forest management, coastal environment monitoring, and so on, particularly onboard UAV's. Resultant multispectral images are typically georeferenced primarily based on the onboard GPS (Global Positioning System) and IMU (Inertial Measurement Unit)or accurate positional information of the pixels, or could be integrated with ground control points that are directly measured on the ground. However, due to the high cost of establishing GCP's prior to the georeferencing or for inaccessible areas, it is often required to derive the positions without such reference information. This study aims to provide a means to improve the georeferencing performance of a multispectral camera images without involving such ground reference points, but instead with the simultaneously onboard high resolution RGB camera. The exterior orientation parameters of the drone camera are first estimated through the bundle adjustment, and compared with the reference values derived with the GCP's. The results showed that the incorporation of the images from a high resolution RGB camera greatly improved both the exterior orientation estimation and the georeferencing of the multispectral camera. Additionally, an evaluation performed on the direction estimation from a ground point to the sensor showed that inclusion of RGB images can reduce the angle errors more by one order.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.185-192
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• 2021

Various methods have been proposed to determine the defect detection of welding bead, and recently sensor data and image data inspection have been steadily announced. There are advantages that sensor data inspection is highly accurate, and two-dimensional-based image data inspection is able to determine the position of the welding bead. However, when analyzing only with sensor data, it is difficult to determine whether the welding has been performed at the correct position. On the other hand, the image data inspection does not have high accuracy due to noise and measurement errors. In this paper, we propose a method that can complement the shortcomings of each inspection method and increase its advantages to improve accuracy and speed up inspection by fusing sensor data inspection which are average current, average volt, and mixed gas data, and image data inspection methods and is implemented as software. In addition, it is intended to allow users to conveniently and intuitively analyze and grasp the results by performing analysis using a graphical user interface(GUI) and checking the data and inspection results used for the inspection. Sensor inspection is performed using the characteristics of each sensor data, and image data is inspected by applying a morphology geodesic active contour algorithm. The experimental results showed 98% accuracy, and when performing the inspection on the four image data, and sensor data the inspection time was about 1.9 seconds, indicating the performance of software that can be used as a real-time inspector in the welding process.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.149-155
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• 2021

In this study, we intend to develop a defective road surface object recognition model that automatically detects road surface defects that restrict the movement of the transportation handicapped using electric mobile devices with deep learning. For this purpose, road surface information was collected from the pedestrian and running routes where the electric mobility aid device is expected to move in five areas within the city of Busan. For data, images were collected by dividing the road surface and surroundings into objects constituting the surroundings. A series of recognition items such as the detection of breakage levels of sidewalk blocks were defined by classifying according to the degree of impeding the movement of the transportation handicapped in traffic from the collected data. A road surface object recognition deep learning model was implemented. In the final stage of the study, the performance verification process of a deep learning model that automatically detects defective road surface objects through model learning and validation after processing, refining, and annotation of image data separated and collected in units of objects through actual driving. proceeded.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.313-322
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• 2022

The number of architects who adopt BIM(Building Information Modeling) as the design method are gradually increasing because of its productivity and efficiency. Climate Change and Global Warming lead to legislation of new energy regulations and strengthen existing ones. The current architectural design methods (2D CAD) take a lot of time and effort to verify energy codes and are hard to adjust according to the design changes. The purpose of this study is to show the effectiveness of the BIM in building envelop energy modeling of the housing project. In the process of design method change, We could contribute to increasing productivity and efficiency in building energy verification through BIM because the updated value could be calculated simultaneously without information omission or recalculation process. The procedure for the study is as follows. Using BIM of the Goldin at Essex Crosing Housing Project by Revit 2011 as a case model, this study analyze the criteria for energy plan to conform to the energy code in NYC. The result value from the setting of the Revit model is compared with the reference value required by the NYC Energy Code. Finally, the data from BIM are entered into COMckeck, the energy verification program provided by U.S. Department of Energy, to check whether the building envelope energy performance conforms to NYC Energy Code.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.263-278
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• 2022

With the recent advent of IoT technology, automatic pet feeders are being distributed so that owners can feed their companion animals while they are out. However, due to behaviors of pets, the method of measuring weight, which is important in automatic feeding, can be easily damaged and broken when using the scale. The 3D camera method has disadvantages due to its cost, and the 2D camera method has relatively poor accuracy when compared to 3D camera method. Hence, the purpose of this study is to propose a deep learning approach that can accurately estimate weight while simply using a 2D camera. For this, various convolutional neural networks were used, and among them, the ResNet101-based model showed the best performance: an average absolute error of 3.06 grams and an average absolute ratio error of 3.40%, which could be used commercially in terms of technical and financial viability. The result of this study can be useful for the practitioners to predict the weight of a standardized object such as feed only through an easy 2D image.