• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.6
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• pp.498-505
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• 2010

In-Wheel System is a high-efficiency system to supply a new concept of platform which raises the efficiency of motor drive system and applies it to an environment-friendly automobile by installing a highly efficient electric motor directly to wheels and removing factors of power train. The proliferation of these systems is directly related to the safety of our lives, so check the reliability of the part in the development phase and should be certified. Reliability is the ability of a system or component to perform its required functions under stated conditions for a specified period of time. This paper presents to the verification methods for durability, one of reliability assessments of the Motor, the study calculated acceleration and deceleration torque and the effective torque from driving conditions of In-Wheel Motor, and based on this, it reduced the test time and suggested the verification methods of In-Wheel Motor reliability through the accelerated life test.

• The Journal of Korean Academy of Prosthodontics
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• v.58 no.1
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• pp.23-29
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• 2020

Purpose: The purpose of this retrospective study was to evaluate the method using the S-reamer and gel-type graft material by the success rate and survival rate. Materials and methods: Implantation period was from 2008 to 2014, Follow check up year is 2019. There were 59 patients and 117 implants. All implants were placed in the posterior maxilla with the sinus lift. The patients population consisted of 34 men and 25 women, ranging from 19 to 75 years. The residual bone heights were from 1 mm to 6 mm. Sinus was perforated with S-reamer without membrane tearing and gel type bone graft material was used for membrane lifting and filling the space. all implants were placed simultaneously. Panoramic X-ray was taken. After 5 - 6 months healing period, final prostheses were restored. After more 5-years implant surgery, Panoramic X-ray was obtained and X-ray analysis and clinical examination were performed. Success criteria was referred to a Buser's success critera. All implants were classified to success implant, survival implant, failed implant. A success implant was satisfying success criteria, a survival implant was a implant that was acute infection with suppuration and bone loss, a failed implant was a implant that was mobile, removed. Results: Five implants were removed, and 4 implants had infected with bone loss. Survival rate was 95.7% and success rate was 92.3%. Conclusion: This retrospective study presented that this method with S-reamer and gel-type graft material was a successful treatment without membrane tear in the condition of 1-6 mm residual bone height.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.27-35
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• 2023

In this paper, we propose a process of increasing productivity by applying a deep learning-based defect detection and classification system to the prepreg fiber manufacturing process, which is in high demand in the field of producing composite materials. In order to apply it to toe prepreg manufacturing equipment that requires a solution due to the occurrence of a large amount of defects in various conditions, the optimal environment was first established by selecting cameras and lights necessary for defect detection and classification model production. In addition, data necessary for the production of multiple classification models were collected and labeled according to normal and defective conditions. The multi-classification model is made based on CNN and applies pre-learning models such as VGGNet, MobileNet, ResNet, etc. to compare performance and identify improvement directions with accuracy and loss graphs. Data augmentation and dropout techniques were applied to identify and improve overfitting problems as major problems. In order to evaluate the performance of the model, a performance evaluation was conducted using the confusion matrix as a performance indicator, and the performance of more than 99% was confirmed. In addition, it checks the classification results for images acquired in real time by applying them to the actual process to check whether the discrimination values are accurately derived.

• Journal of Hydrogen and New Energy
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• v.24 no.3
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• pp.264-274
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• 2013

Piping systems play an important role in gas and oil transferring system. In the piping system, there are many elements, such as valves and flow meters. In order to check their normal operating conditions, each signal from each element is displayed on the monitor in the pipe control room. By the way, there are several accidental cases in the piping system even if all signals from the local elements are judged to be normal on the monitor in the control room. Further, opposite cases often happen even the monitor shows abnormal while the local elements work normal. To overcome this abnormal functions, it is not so easy to construct the environment in which sensors detecting the working states of all elements installed in the piping system. In this paper, a new non-contact measurement technique which can calculate the elements' delicate displacements by using a PIV(particle image velocimetry) and diagnose their working states by using a neural network is proposed. The measurement system consists of a host computer, a micro system, a telescope and a high-resolution camera. As a preliminary test, the constructed measurement system was applied to measure delicate vibrations of mobile phones. For practical application, a pneumatic system was measured by the constructed system.

• Journal of Digital Contents Society
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• v.16 no.5
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• pp.815-822
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• 2015

By the growing of SMS phishing victims, applications for processing spam messages are being released in succession. However most spam messages that cleverly modified the content like separating the consonants and vowels are fail to be filtered. In this paper, we implemented an application 'AntiSpam' which is able to identify spam strings in the text message to solve this problem. 'AntiSpam' searches spam strings in the text message by using set-based POI search algorithm, and then calculate the possibility of whether it is spam or not in accordance with the search results. In addition, it catches skillfully disguised spam messages in order to avoid missing the spam filtering. Users, who received a message, can check the result in spam message possibility decision result and the contents of the message and they can choose how to handling the message.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.655-661
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• 2023

Big data, an important element of the 4th industrial revolution, is actively opening public data in public institutions and local governments. In the public data portal, everyone can conveniently search for data and check related data, but only those in ICT-related fields are using public data. Although data held by public institutions is open to citizens, it is difficult for anyone to easily utilize public data to develop applications. In this paper, data provided in open API format from public data portals has XML and JSON formats. In this study, we are a method of modularizing public data in XML format into a part that can be easily developed by linking it to a GUI interface. Based on the necessary public data, we propose a way to easily develop mobile programs and promote the use of public data.

• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.252-259
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• 2003

In the case of link congestion, most of the existing ad-hoc routing protocols like AODV and DSR do not try to discover a new route if there is no change in the network topology. Hence, with low mobility, traffic may get concentrated on some specific nodes. Since mobile devices have low battery power and low computing capability, traffic concentration on a specific node is not a desirable phenomenon. Therefore, in this paper, we propose a new protocol called SLAP (Simple Load-balancing Ad-hoc routing Protocol) which resolves the traffic concentration problem by letting each node check its own load situation and give up its role as a packet forwarder gracefully in the case of high traffic load. We compare the performance of SLAP with that of AODV and DSR in terms of the forwarding traffic distribution.

• Research in Community and Public Health Nursing
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• v.33 no.4
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• pp.357-371
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• 2022

Purpose: This study aims to investigate factors related to long-term length of stay (LOS) of patients with chronic diseases in Korean veterans hospitals. Methods: The subjects were 196 elderly patients with chronic disease staying in the hospital for more than 10 days, Data were collected by the survey of patients with structured questionnaires and medical records review by nurses from July 15 to August 10, 2019. Collected data were analyzed using t-test, ANOVA, Pearson's correlation coefficient and stepwise multiple regression. Results: The present and desired LOS were 37.78±32.66 days and 60.87±45.95 days, respectively. Factors affecting hospital LOS were found to be main disease (genitourinary) (p<.001), assistance in activities of daily living (p<.001), area of hospital (p<.001), payment of medical fees (p=.026), hospital satisfaction (p=.036) and the explanatory power of these variables was 26.4%. The most common health problems that need to be solved after discharge were symptom alleviation and health promotion. These problems can be solved using community-based facility services or visiting medical-welfare services (especially home care nursing). Conclusion: In order to reduce hospital LOS, the following measures are required: personalized self-management education, provision of transportation services for dialysis therapy of inactive patients, linking patients with visiting medical-welfare services including home care nursing and mobile healthcare services, operation of the case management system including the notice of the discharge date at admission, interim check of patient status, and connecting the patient with community resources or transferring the patient to long-term care facilities at discharge.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.256-264
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• 2023

Smart farm technology using IoT is one of the technologies that can increase productivity and improve the quality of agricultural products in agriculture, which is facing difficulties due to the decline in rural population, lack of rural manpower due to aging, and increase in diseases and pests due to climate change. . Smart farms using existing IoT simply monitor farms, implement smart plant growers, and have automatic greenhouse opening and closing systems. This paper implements a smart farm system based on MQTT, an industry standard protocol for the Internet of Things, and Node-RED, a representative development middleware for the Internet of Things. First, data is extracted from Arduino sensors, and data is collected and transmitted from IoT devices using the MQTT protocol. Then, Node-RED is used to process MQTT messages and store the sensing data in real time in MongoDB, a representative NoSQL, to store the data. Through this smart farm system, farm managers can use a computer or mobile phone to check sensing information on the smart farm in real time, anytime, anywhere, without restrictions on time and space.

• Journal of Society of Preventive Korean Medicine
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• v.24 no.2
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• pp.71-82
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• 2020

Objectives : The purpose of this study is to evaluate clinical utilization by measuring compliance with the use of mobile health applications (AtopyPHR developed in a previous study) for patients with atopic dermatitis. Methods : Based on the AtopyPHR and the input period and frequency survey results for each symptom item, a scenario for measuring compliance was derived. The study period was 4 weeks. Participants installed AtopyPHR app and Telegram app on their smartphones, conducted user training on the app, and recorded symptoms using the app for 4 weeks. At the 2nd and 4th week visits, the AtopyPHR data recorded by the user can be viewed on the web page and used for medical decision. Compliance was analyzed by the date the symptoms were recorded. Results : There were 28 participants, all (100%) were compliant, and the compliance was 96.8. The patients were 1 to 18 years old, and the average age was 8.2±5.7 years, 10 males and 18 females. The actual date of participation in recording symptoms was 28.6±0.56 on average. Compared to Week 1, compliance decreased at Week 2, and Week 4 had the highest compliance. Daily check, daily emotion, stool/urine/sleep, and meal management showed high compliance, SCORAD and quality of life were higher than required to record. Conclusions : AtopyPHR was effective in compliance. The results of this study could be used to collect personal health data in daily life through the AtopyPHR, improving participant compliance. It is considered to be meaningful because it measured the compliance with the symptom record actually recorded using the mobile app rather than a questionnaire. This study may be useful not only for personal health care but also for medical decisions, as opinions are given by experts who treat atopic dermatitis.