• Asian Pacific Journal of Cancer Prevention
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• v.13 no.12
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• pp.6133-6137
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• 2012

Purpose: To study the effect of bolus versus no bolus in the coverage of the nodal tumour volume with intensity-modulated radiotherapy (IMRT) for the treatment of nasopharyngeal carcinoma (NPC). Methods and Materials: This retrospective study used data from 5 consecutive patients with NPC who were treated with bolus for large neck nodes using IMRT from November 2011-January 2012 in our institute. All these patients were treated radically with IMRT according to our institution's protocol. Re-planning with IMRT without bolus for these patients with exactly the same target volumes were done for comparison. Comparison of the plans was done by comparing the V70 of PTV70-N, V66.5 of PTV70-N, V65.1 of PTV70-N and the surface dose of the PTV70-N. Results: The mean size of the largest diameter of the enlarged lymph nodes for the 5 patients was 3.9 cm. The mean distance of the GTV-N to the skin surface was 0.6 cm. The mean V70 of PTV70-N for the 5 patients showed an absolute advantage of 10.8% (92.4% vs. 81.6%) for the plan with bolus while the V66.5 of PTV70-N had an advantage of 8.1% (97.0% vs. 88.9%). The mean V65.1 also had an advantage of 7.1% (97.6% vs. 90.5%). The mean surface dose for the PTV70-N was also much higher at 61.1 Gy for the plans with bolus compared to only 23.5 Gy for the plans without bolus. Conclusion: Neck node bolus technique should be strongly considered in the treatment of NPC with enlarged lymph nodes treated with IMRT. It yields a superior dosimetry compared t o non-bolus plans with acceptable skin toxicity.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1991.10a
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• pp.261-267
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• 1991

다품종소량생산의 특징을 갖고 있는 금형공업에서 컴퓨터통합생산시스템(Computer Integrated Manufacturing System;CIMS)의 실현을 위한 중요한 분야의 하나는 부품설계도면으로부터 최종제품을 생산하는데 필요한 공정계획의 자동화, 즉 컴퓨터를 이용하여 공정계획을 자동적으로 생성하는 자동공정계획시스템(Computer Aided Process Planning;CAPP) 기술의 개발이다. 국내외적으로 CAPP분야의 연구는 컴퓨터 지원에 의한 자동화 기술의 급속한 발전과 더불어 지난 20여년 동안에 기계가공품에 관한 CAPP은 약 150여가지가 개발되었으나, 이는 컴퓨터 지원에 의한 설계의 자동화(Computer Aided Design;CAD)나 컴퓨터 지원에 의한 제조의 자동화(Computer Aided Manufacturing;CAM)분야에 비해 상대적으로 저조한 형편이다. 특히 금형을 대상으로 한 CAPP시스템의 개발은 아직 초기단계에 있기 때문에, 본 연구에서는 사출금형을 대상으로 하여 실용성이 있는 공정설계시스템을 개발함을 목적으로 한다. 일반적으로 공정계획은 "소재로부터 제품을 경제적, 효율적으로 생산하는데 필요한 제조공정의 체계적인 결정"이라고 정의할 수 있다. 공정계획은 제품의 종류와 수량, 재료와 부품의 종류, 보유 생산설비와 제조기술의 수준에 따라 다르나, 공정설계(Process Design)와 작업설계(Operation Design)로 구분할 수 있다. 본 연구에서는 공정계획을 광의의 공정설계로 정의하고, 공정설계와 공정계획을 동의어로 통용토록 한다. 기존의 CAPP시스템의 개발에 관한 기본적인 접근방법은 변성형방법(Variant method), 창성형방법(Generative method) 및 자동화방법(Automatic method)이 있다. 이들 CAPP시스템을 개발할 때 사용하는 기법은 크게 5가지- (1) GT(group Technology) 접근기법, (2) Bottom-up 접근기법, (3) Top-down 접근기법, (4) AI와 전문가시스템(Expert System) 접근기법, (5) 컴퓨터 프로그래밍 언어 - 로 분류할 수 있다. 본 연구에서는 전문가시스템 기법을 도입해서 사출금형 공정계획전문가의 지식과 경험을 획득하여 지식베이스를 구축하고, 전문가시스템 셀(shell)중 CLIPS를 이용하여 자동공정계획시스템인 Mold CAPP을 개발하였다.PP을 개발하였다.

• The Journal of Korean Academic Society of Nursing Education
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• v.23 no.4
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• pp.419-429
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• 2017

Purpose: The purpose of this study was to investigate the effect of the development and application of the new nurses' core skill program on the clinical skill, confidence, knowledge and performance of new nurses. Methods: This study was a nonequivalent control group post-test design on 46 new nurses with 3 to 6 months work experience in a general hospital. Data were collected from August 2015 to August 2016. A training program of core fundamental nursing skills was applied on 23 new nurses from 2016 in the experiment group, and an existing training method was applied on 23 new nurses from 2015 in the comparison group. The collected data were analyzed using SPSS/WIN 23.0. Results: The experimental group ($89{\pm}4.29$) showed higher score in practical skill assessment compared to the control group ($85.09{\pm}3.99$) and showed a statistically significant difference (p<001). Conclusion: A training program of core fundamental nursing skills for new nurses proved effective in improving practical skills. Further research on the development of a systemic training program that can improve clinical nursing knowledge and work ability for new nurses according to the extended enforcement of a Nursing Care Integrated Service ward is needed.

• Journal of the Korean Geosynthetics Society
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• v.19 no.1
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• pp.45-53
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• 2020

There is an increasing tendency to try to make predictive analysis using measurement data based on machine learning techniques in the railway industries. In this paper, it was predicted that Track quality index (TQI) using vehicle acceleration data based on the machine learning method. The XGB (XGBoost) was the most accurate with 85% in the all data sets. Unlike the SVM model with a single algorithm, the RF and XGB model with a ensemble system were considered to be good at the prediction performance. In the case of the Surface TQI, it is shown that the acceleration of the z axis is highly related to the vertical direction and is in good agreement with the previous studies. Therefore, it is appropriate to apply the model with the ensemble algorithm to predict the track quality index using the vehicle vibration acceleration data because the accuracy may vary depending on the applied model in the machine learning methods.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.4
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• pp.445-450
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• 2018

AIS is the most important navigation equipment for the identification of other ships, etc. However, the AIS overload problem has been raised recently due to an increase in AIS equipped vessels. The government is planning to introduce the wireless LTE network at 100 km offshore as part of the SMART-Navigation project. Continuous development and dissemination of the services available through such platforms will be necessary to achieve major goals such as marine accident prevention and environmental protection. In this study, we applied a WAVE communication system, which could be the basis for the development of such services. As a result, reliable data transmission was confirmed for a range of communication of approx. 5 miles, although the service was limited to 1 km in road traffic. Therefore, it is expected that WAVE communication technology will be used to prevent marine accidents through such efforts as collision avoidance and the transfer of marine safety information between ships.

• Journal of Agricultural Extension & Community Development
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• v.27 no.4
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• pp.173-184
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• 2020

Is the Fourth Industrial Revolution a revolution for cities only? Through the Fourth Industrial Revolution, Korea has entered quickly in the influence area of intelligent information technology such as IoT, AI, Big data, Cloud, ICT, Digital twin. However, as the information gap between the rural zone and the urban zone worsens, a policy was needed to reduce such a gap. Therefore, this research analyzed EU's smart village project, and investigated the problem and improvement of the actual smart village through the interview and field study with the person in charge of the actual smart village project in Korea. Based on the analytic result, 5 plans were deduced to improve Korea's smart village project. First, make the realistic adjustment of project period to assure the sustainability of smart village; second, make the new establishment of the department in charge of smart village project; third, construct the system of integrating and cooperating the policy that can embrace all the rural zone and the urban zone; the fourth, expand the application area of customized ICT technology according to the new rural policy environment; and finally introduce the residents' capacity development project through the rural guidance project.

• Journal of Information Technology Services
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• v.19 no.6
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• pp.145-159
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• 2020

Because of the recent development of information and communication technology, companies are exposed to various media such as blogs, social media, and YouTube. In particular, exposed news affects the company's reputation. So, while positive news can improve corporate value, negative news can lead to financial losses for the company. In this study, we redefine corporate reputation as social responsibility, vision and leadership, financial performance, products and services through existing literature, and conducted an AHP survey with a total of four components to calculate the weight of each factor. As a result of the calculation, the proportion of financial performance was the highest at 0.41, and products and services, vision and leadership, and social responsibility were the lowest. In addition, in order to measure the reputation of a company, it is classified as a component that defines online news using the LDA technique. In addition, through sentiment analysis, an index for each corporate reputation factor was derived, and the reputation index was calculated by combining it with the AHP analysis result, and Spearman ranking correlation analysis was performed to secure the validity of the research results. Therefore, the significance of this study is that the definition and importance of the constituent factors can contribute to the future planning and development direction of the company, and also contribute to the derivation of the corporate reputation index. This study is significant in that a new analysis methodology that applied AHP analysis results to sentiment analysis was suggested.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.205-211
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• 2023

In this study, we analyzed the potential application and validity of ChatGPT, an artificial intelligence technology currently gaining attention across various fields, for the creation of advertising photographs. To do this, we examined the relationship between the visual elements of advertising photographs and language, and investigated use cases of ChatGPT in advertising. Furthermore, we analyzed the elements of each stage in the advertising photograph creation process and conducted expert interviews to determine the validity of ChatGPT's application in these stages. The results revealed that, although somewhat limited, the feasibility of using ChatGPT was found to be high in the planning stage of advertising photographs, but lower in the actual shooting and post-production stages. Considering these findings, it is necessary to continuously monitor the progress of AI technology and strive to enhance the creativity and efficiency of advertising photograph production through collaboration between technology and humans.

• Dementia and Neurocognitive Disorders
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• v.23 no.3
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• pp.146-160
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• 2024

Background and Purpose: The emotions of people at various stages of dementia need to be effectively utilized for prevention, early intervention, and care planning. With technology available for understanding and addressing the emotional needs of people, this study aims to develop speech emotion recognition (SER) technology to classify emotions for people at high risk of dementia. Methods: Speech samples from people at high risk of dementia were categorized into distinct emotions via human auditory assessment, the outcomes of which were annotated for guided deep-learning method. The architecture incorporated convolutional neural network, long short-term memory, attention layers, and Wav2Vec2, a novel feature extractor to develop automated speech-emotion recognition. Results: Twenty-seven kinds of Emotions were found in the speech of the participants. These emotions were grouped into 6 detailed emotions: happiness, interest, sadness, frustration, anger, and neutrality, and further into 3 basic emotions: positive, negative, and neutral. To improve algorithmic performance, multiple learning approaches were applied using different data sources-voice and text-and varying the number of emotions. Ultimately, a 2-stage algorithm-initial text-based classification followed by voice-based analysis-achieved the highest accuracy, reaching 70%. Conclusions: The diverse emotions identified in this study were attributed to the characteristics of the participants and the method of data collection. The speech of people at high risk of dementia to companion robots also explains the relatively low performance of the SER algorithm. Accordingly, this study suggests the systematic and comprehensive construction of a dataset from people with dementia.

• Smart Structures and Systems
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• v.33 no.4
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• pp.291-300
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• 2024

Uncertainty of the model, system delay and drive dynamics can be considered as normal uncertainties, and the main source of uncertainty in the seismic control system is related to the nature of the simulated seismic error. In this case, optimizing the management strategy for one particular seismic record will not yield the best results for another. In this article, we propose a framework for online management of active structural management systems with seismic uncertainty. For this purpose, the concept of reinforcement learning is used for online optimization of active crowd management software. The controller consists of a differential controller, an unplanned gain ratio, the gain of which is enhanced using an online reinforcement learning algorithm. In addition, the proposed controller includes a dynamic status forecaster to solve the delay problem. To evaluate the performance of the proposed controllers, thousands of ground motion data sets were processed and grouped according to their spectrum using fuzzy clustering techniques with spatial hazard estimation. Finally, the controller is implemented in a laboratory scale configuration and its operation is simulated on a vibration table using cluster location and some actual seismic data. The test results show that the proposed controller effectively withstands strong seismic interference with delay. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results is believed to achieved in the near future by the ongoing development of AI and control theory.