• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.117-124
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• 2021

This study is a study to recognize hand movements using a neural network for wrist rehabilitation. The rehabilitation of the hand aims to restore the function of the injured hand to the maximum and enable daily life, occupation, and hobby. It is common for a physical therapist, an occupational therapist, and a security tool maker to form a team and approach a doctor for a hand rehabilitation. However, it is very inefficient economically and temporally to find a place for treatment. In order to solve this problem, in this study, patients directly use smart devices to perform rehabilitation treatment. Using this will be very helpful in terms of cost and time. In this study, a wrist rehabilitation dataset was created by collecting data on 4 types of rehabilitation exercises from 10 persons. Hand gesture recognition was constructed using a neural network. As a result, the accuracy of 93% was obtained, and the usefulness of this system was verified.

• Journal of the Korean earth science society
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• v.42 no.5
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• pp.571-587
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• 2021

This study aims to investigate the problem recognition and clue capture processes of the observation stage in a geological field trip using abductive inquiry. To this end, eight outdoor geological programs were developed in the order of diagnostic evaluation, outdoor geological fieldwork, and review. Six middle-school students participated in these programs The geological field trip was conducted twice, followed by data provision, observation, rule generation, hypothesis generation, and final hypothesis presentation. Outdoor geological fieldwork recordings and student activity sheets were collected and analyzed qualitatively. From these data, three aspects of student observations emerged during the geological fieldwork: The characteristics of each pattern were subdivided into the geological importance of the clues, attention, type of clues, observation characteristics (attention factor), clue utilization, and clue deletion. Here, by combining these results, we propose educational applications that correspond to each aspect.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.7
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• pp.3-12
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• 2018

The present remodeling makes almost no difference from rebuilding as all the building materials are removed remaining frame structure only. And, in case of vertical extension of building, higher construction cost and safety problem occur. The Ministry of Land, Transport and Maritime Affairs, therefore, recommends customized remodeling that can be made in light of the resident' needs such as parking lot, elevator, bathroom, and room for the alternative of remodeling of vertical extension of building. The purpose of this study is to present real data that can be referred to the constructor's decision making before starting the remodeling, by investigating and analyzing the weight and importance between evaluation factors for customized remodeling at the completed time of remodeling. Accordingly, the factors were divided into environmental factor, social factor, and economical factor, and the survey was performed for the residents living in remodeling houses. In addition, for the professionals, AHP (Analytic Hierarchy Process) has been carried out for the priority in the customized remodeling. For environmental factor, the level of importance made difference from that before remodeling, except parking level. For social factor, every item, including psychological satisfaction and community satisfaction, made difference. For economical factor, the recognition level of importance in rent made difference, except sale price of the factor for price satisfaction. In case of the factor for cost satisfaction, it was checked that construction cost and administration cost both could be considered important. As a result of AHP, the most importantly emphasized item was construction cost, and sale price, administration cost, residence structure, and parking lot were followed by priority in order. This study could contribute to reliably settle down customized remodeling by giving reasonable and substantial help from the analysis of the differences in the customized remodeling items before/after the remodeling.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.183-193
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• 2021

The purpose of this study was to verify how organizational fairness affects organizational commitment to social welfare officials, and to examine the mediating effect of organizational support. Social welfare officials have tried to find out what factors can be more adapted to the organization and immersed in the organizational aspect, as overwork and poor working conditions are becoming a problem. As the subject and method of the study, a questionnaire survey was conducted on 172 social welfare officials in P and U cities in northern Gyeonggi Province, and analyzed using multiple regression analysis. As a result of the study, organizational fairness of social welfare officials had a positive effect on organizational commitment, and organizational support had a partial mediating effect. Based on the results of this study, administrative and policy implications for the organizational adaptation and commitment of public officials in charge of social welfare were presented.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.175-182
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• 2021

The purpose of this paper is to develop a machine learning-based marine drone to prevent the farming from harmful birds such as ducks. Existing drones have been developed as marine drones to solve the problem of being lost if they collide with birds in the air or are in the sea. We designed a CNN-based learning algorithm to judge harmful birds that appear on the sea by maritime drones operating by autonomous driving. It is designed to transmit video to the control PC by connecting the Raspberry Pi to the camera for location recognition and tracking of harmful birds. After creating a map linked with the location GPS coordinates in advance at the mobile-based control center, the GPS location value for the location of the harmful bird is received and provided, so that a marine drone is dispatched to combat the harmful bird. A bird fighting drone system was designed and implemented.

• Journal of The Korean Society of Clinical Toxicology
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• v.18 no.2
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• pp.51-56
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• 2020

Purpose: Acute nicotine poisoning by liquid nicotine in electronic cigarettes is becoming an increasing problem worldwide. The current systematic review aimed to determine the harm of acute nicotine poisoning by reviewing published case reports. Methods: An online literature search with PubMed, Embase, Cochrane Library, and KoreaMed database was performed to identify relevant studies addressing acute nicotine poisoning with electronic cigarettes. Two investigators searched the case reports written in English or Korean. Results: Twenty-six cases were included in this study. The routes of intoxication included ingestion in 18 cases, intravenous injection in three cases, subcutaneous injection in two cases, and ocular exposure in two cases. Ten cases had a cardiac arrest, and seven of them died. Seven out of 12 cases with intentional poisoning had a cardiac arrest. Nine children under 18 years were reported, and three of them had a cardiac arrest. Sixteen cases without a cardiac arrest recovered well, except for one case with sudden sensorineural hearing loss. Conclusion: The authors reviewed the risks of electronic cigarette liquid in terms of acute poisoning through a systematic review. The nicotine solution of an e-cigarette can be life-threatening in cases of acute poisoning. Therefore, active emergency treatment with early recognition is necessary. In addition, various management methods and regulations for preventing acute nicotine poisoning, such as restriction of distribution and nicotine concentration, should be considered.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1437-1444
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• 2020

With the development of computer vision systems, many advances have been made in the fields of surveillance, biometrics, medical imaging, and autonomous driving. In the field of autonomous driving, in particular, the object detection technique using deep learning are widely used, and the paved road detection is a particularly crucial problem. Unlike the ROI detection algorithm used in general object detection, the structure of paved road in the image is heterogeneous, so the ROI-based object recognition architecture is not available. In this paper, we propose a deep neural network architecture for atypical paved road detection using Semantic segmentation network. In addition, we introduce the multi-scale semantic segmentation network, which is a network architecture specialized to the paved road detection. We demonstrate that the performance is significantly improved by the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.146-151
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• 2021

Currently, the demand for vehicles from one family is increasing in many countries at home and abroad, reducing the number of people on the vehicle and increasing the number of vehicles on the road. The multi-passenger lane system, which is available to solve the problem of traffic congestion, is being implemented. The system allows police to monitor fast-moving vehicles with their own eyes to crack down on illegal vehicles, which is less accurate and accompanied by the risk of accidents. To address these problems, applying deep learning object recognition techniques using images from road sites will solve the aforementioned problems. Therefore, in this paper, we compare and analyze the performance of existing deep learning models, select a deep learning model that can identify real-time vehicle occupants through video, and propose a vehicle occupancy detection algorithm that complements the object-ident model's problems.

• Journal of IKEEE
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• v.24 no.4
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• pp.1050-1057
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• 2020

Immersive 360-degree media has a problem of slowing down the video recognition speed when the video is processed by the conventional method using a variety of rendering methods, and the video size becomes larger with higher quality and extra-large volume than the existing video. In addition, in most cases, only one scene is captured by fixing the camera in a specific place due to the characteristics of the immersive 360-degree media, it is not necessary to extract feature information from all scenes. In this paper, we propose a reference frame selection method for immersive 360-degree media and describe its application process to copyright protection technology. In the proposed method, three pre-processing processes such as frame extraction of immersive 360 media, frame downsizing, and spherical form rendering are performed. In the rendering process, the video is divided into 16 frames and captured. In the central part where there is much object information, an object is extracted using an RGB vector per pixel and deep learning, and a reference frame is selected using object feature information.