• KEPCO Journal on Electric Power and Energy
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• v.5 no.3
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• pp.149-156
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• 2019

In the field of maintenance of power transmission lines, drones have been used for their patrol and inspection by KEPCO since 2017. This drone technology was originally developed by KEPCO Research Institute, and now workers from four regional offices of KEPCO have directly applied this technology to the drone patrol and inspection tasks. In the drone inspection system, a drone with an optical zooming camera and a thermal camera can fly automatically along the transmission lines by the ground control system developed by KEPCO Research Institute, but its camera gimbal has been remotely controlled by a field worker. Especially the drone patrol and inspection has been mainly applied for the transmission lines in the inaccessible areas such as regions with river-crossings, sea-crossings and mountains. There are often communication disruptions between the drone and its remote controller in such extreme fields of mountain areas with many barriers. This problem may cause the camera gimbal be out of control, even though the inspection drone flies along the flight path well. In addition, interference with the reception of real-time transmitted videos makes the field worker unable to operate it. To solve these problems, we have developed the auto-tracking camera gimbal system with deep learning method. The camera gimbal can track the transmission line automatically, even when the transmitted video on a remote controller is intermittently unavailable. To show the effectiveness of our camera gimbal system, its field test results will be presented in this paper.

• Therapeutic Science for Rehabilitation
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• v.10 no.1
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• pp.53-61
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• 2021

Introduction : OMFT is a therapeutic technique based on sensorimotor, motor control and motor learning, and its major goal is to improve oral motor function. The oral motor conceptual hierarchical development is divided into 5 steps: 1) sensorimotor, 2) movement integration, 3) structural movement, 4) functional oral motor, and 5) comprehensive oral motor. Discussion : The OMFT consists of 3 techniques, 10 categories, and 50 sub-item. 1) Warming up technique: 2 categories, 12 sub-item, warming up by sensory awareness and adaptation, therapy situation adaptation, neck movement; 2) Key point technique: 7 categories, 30 sub-item, oral motor facilitation and increasing chewing skill by direct stroke of oral structures such as the face, lips, cheeks, gum, jaws, and tongue; 3) Application technique: 1 category, 8 sub-item, facilitate food intake and swallowing. Conclusion : The goal of this article is to introduce 3 techniques, 50 sub-item of OMFT, as a comprehensive oral motor therapy method, for application to clients. This article provides information that will help oral motor specialists in treating clients with oral motor problems more effectively and professionally.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.1-10
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• 2022

Deep neural networks are widely used to solve various problems. In a fully connected neural network, the nonlinear activation function is a function that nonlinearly transforms the input value and outputs it. The nonlinear activation function plays an important role in solving the nonlinear problem, and various nonlinear activation functions have been studied. In this study, we propose a combined parametric activation function that can improve the performance of a fully connected neural network. Combined parametric activation functions can be created by simply adding parametric activation functions. The parametric activation function is a function that can be optimized in the direction of minimizing the loss function by applying a parameter that converts the scale and location of the activation function according to the input data. By combining the parametric activation functions, more diverse nonlinear intervals can be created, and the parameters of the parametric activation functions can be optimized in the direction of minimizing the loss function. The performance of the combined parametric activation function was tested through the MNIST classification problem and the Fashion MNIST classification problem, and as a result, it was confirmed that it has better performance than the existing nonlinear activation function and parametric activation function.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.235-246
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• 2023

In this paper, we propose suggestions for developing a Metaverse platform for educational purpose utilizing a Delphi study method with experts on Metaverse and digital education. 17 experts participated in the 1st study and 16 took part in the 2nd study, and data was collected via emails from January 5th to 10th for the 1st study and from January 12th to 17th for the 2nd study in 2022. Collected data in the 1st study was analyzed by applying content analysis. The results for the 1st study indicated that there were 120 sub-factors were derived from 7 main questions(the necessity of a Metaverse platform for future education, how to use the Metaverse platform for education to improve the capacities needed for future human resources, problems that may arise during education using the Metaverse platform, the functions that the Metaverse platform for education should have, the infrastructure and environment required when using the Metaverse platform for education, how to use the Metaverse effectively as a learning space, subjects and educational contents that will be effective if conducted on the Metaverse platform for education). The results for the 2nd study were presented by being ranked with calculated means of sub-factors for each question. Finally, based on the results, suggestions for building a Metaverse platform for educational purpose are stated and limitations of the study and possible future study are discussed.

• Journal of Korean Home Economics Education Association
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• v.23 no.3
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• pp.161-183
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• 2011

This study aims to design, develop the impact of a high school course in practical problem- focused teaching plan which will enable students to deal with an aging society, and prepare well for the aging by looking at issues the elderly face. This study set a target of analyzing the 2007 revised curriculum manual to develop instructor-led teaching and learning plans for 'Successful aging preparation'. Five common subjects were reframed on a practical problem basis through factor analysis of preliminary research regarding aging education for teenagers and the 2007 revised curriculum and textbooks of Technology Home Economics, and Human Development. The practical problem was 'What do we need to do to Successfully live an independent life in aging?', and the subjects studied to answer this question were the aging society and population changes. the nature of the elderly, aging preparation, care of the elderly, and welfare services for the elderly. These five subjects were grouped under the main categories of The Aging Society. Understanding the Elderly, and aging Preparation. The ultimate objective of the lessons was, through critical reasoning, to inquire into the causes of current problems the elderly face so that teenagers can understand aging societies and the elderly, and prepare for a Successful aging. Another objective was to seek reasonable alternatives for teenagers as they prepare for Successful and independent aging, and increase their problem-solving abilities in choosing the best course of action by considering the ripple effect of consequences of each of those alternatives. The practical problem-teaching lesson plans consisted of five classes on practical reasoning instruction. This study suggests that new high school curricula should include lessons on preparation for aging so that students can deal successfully with our aging society.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.259-278
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• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.

• Journal of the Korean Dietetic Association
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• v.15 no.2
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• pp.97-112
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• 2009

The purpose of this study was to develop a nutrition education curriculum with teacher's guide which includes discretionary activities for obese children. A survey was carried out to investigate the recognition of body image and food behaviors according to the obesity index (mild, moderate, severe) in school children (4~6th grade, 158 boys and 60 girls) who were selected based on a physical examination in May, 2006 in the Gyeongnam province. Next, a nutrition education curriculum with teacher's guide was developed on the basis of the findings from the survey and from preceding researches. The results are summarized as follow. The results of this study showed the existence of some nutritional problems such as overeating, prejudice, skipping meals, snacking patterns, etc, which indicate the need for nutritional management for obese children. Most overweight children (80.3%) showed the most interest in the nutrition education program, particularly with regards to dieting for weight control (64.7%). The developed nutrition education curriculum consisted of 8 main subjects and 13 subtitles. The curriculum was prepared for 13 lessons and included songs and singing, making-up lyrics, games about nutrition, discussions of the experience of eating (satiety, thirst, hunger), debates on dietary habits, writing and others to promote the interest for learning. We aimed to develop this program in an attempt to improve the dietary habits of obese school children. This is very important because once a dietary habit is formed in adults, it is difficult to change and the best adjustable stage is during childhood. Therefore, early nutrition education during elementary school can change and build-up the awareness of health in young elementary school children.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.453-462
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• 2021

A lot of license plate data is required for car number recognition. License plate data needs to be balanced from past license plates to the latest license plates. However, it is difficult to obtain data from the actual past license plate to the latest ones. In order to solve this problem, a license plate recognition study through deep learning is being conducted by creating a synthetic license plates. Since the synthetic data have differences from real data, and various data augmentation techniques are used to solve these problems. Existing data augmentation simply used methods such as brightness, rotation, affine transformation, blur, and noise. In this paper, we apply a style transformation method that transforms synthetic data into real-world data styles with data augmentation methods. In addition, real license plate data are noisy when it is captured from a distance and under the dark environment. If we simply recognize characters with input data, chances of misrecognition are high. To improve character recognition, in this paper, we applied the DeblurGANv2 method as a quality improvement method for character recognition, increasing the accuracy of license plate recognition. The method of deep learning for license plate detection and license plate number recognition used YOLO-V5. To determine the performance of the synthetic license plate data, we construct a test set by collecting our own secured license plates. License plate detection without style conversion recorded 0.614 mAP. As a result of applying the style transformation, we confirm that the license plate detection performance was improved by recording 0.679mAP. In addition, the successul detection rate without image enhancement was 0.872, and the detection rate was 0.915 after image enhancement, confirming that the performance improved.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.657-667
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• 2020

The Android framework allows apps to take full advantage of personal information through granting single permission, and does not determine whether the data being leaked is actual personal information. To solve these problems, we propose a tool with static/dynamic analysis. The tool analyzes the Source and Sink used by the target app, to provide users with information on what personal information it used. To achieve this, we extracted the Source and Sink through Control Flow Graph and make sure that it leaks the user's privacy when there is a Source-to-Sink flow. We also used the sensitive permission information provided by Google to obtain information from the sensitive API corresponding to Source and Sink. Finally, our dynamic analysis tool runs the app and hooks information from each sensitive API. In the hooked data, we got information about whether user's personal information is leaked through this app, and delivered to user. In this process, an automated Source/Sink classification model was applied to collect latest Source/Sink information, and the we categorized latest release version of Android(9.0) with 88.5% accuracy. We evaluated our tool on 2,802 APKs, and found 850 APKs that leak personal information.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.153-177
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• 2001

Nowadays, product recommendation is one of the important issues regarding both CRM and Internet shopping mall. Generally, a recommendation system tracks past actions of a group of users to make a recommendation to individual members of the group. The computer-mediated marketing and commerce have grown rapidly and thereby automatic recommendation methodologies have got great attentions. But the researches and commercial tools for product recommendation so far, still have many aspects that merit further considerations. To supplement those aspects, we devise a recommendation methodology by which we can get further recommendation effectiveness when applied to Internet shopping mall. The suggested methodology is based on web log information, product taxonomy, association rule mining, and decision tree learning. To implement this we also design and intelligent Internet shopping mall support system based on agent technology and develop it as a prototype system. We applied this methodology and the prototype system to a leading Korean Internet shopping mall and provide some experimental results. Through the experiment, we found that the suggested methodology can perform recommendation tasks both effectively and efficiently in real world problems. Its systematic validity issues are also discussed.