• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.191-202
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• 2023

This study aims to propose a framework for evaluating the impact of artificial intelligence (AI) services, based on the concept of AI service impact. It also suggests a model for evaluating this impact and identifies relevant factors and measurement approaches for each item of the model. The study classifies the impact of AI services into five categories: ethics, safety and reliability, compliance, user rights, and environmental friendliness. It discusses these five categories from a broad perspective and provides 21 detailed factors for evaluating each category. In terms of ethics, the study introduces three additional factors-accessibility, openness, and fairness-to the ten items initially developed by KISDI. In the safety and reliability category, the study excludes factors such as dependability, policy, compliance, and awareness improvement as they can be better addressed from a technical perspective. The compliance category includes factors such as human rights protection, privacy protection, non-infringement, publicness, accountability, safety, transparency, policy compliance, and explainability.For the user rights category, the study excludes factors such as publicness, data management, policy compliance, awareness improvement, recoverability, openness, and accuracy. The environmental friendliness category encompasses diversity, publicness, dependability, transparency, awareness improvement, recoverability, and openness.This study lays the foundation for further related research and contributes to the establishment of relevant policies by establishing a model for evaluating the impact of AI services. Future research is required to assess the validity of the developed indicators and provide specific evaluation items for practical use, based on expert evaluations.

• Korean Journal of Artificial Intelligence
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• v.11 no.3
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• pp.29-34
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• 2023

Recently, the rapid development of artificial intelligence technology, many studies are being conducted to predict the risk of heart disease in order to lower the mortality rate of cardiovascular diseases worldwide. This study presents exercise or dietary improvement contents in the form of a software app or web to patients with cardiovascular disease, and cardiovascular disease through digital devices such as mobile phones and PCs. LR, LDA, SVM, XGBoost for the purpose of developing "Life style Improvement Contents (Digital Therapy)" for cardiovascular disease care to help with management or treatment We compared and analyzed cardiovascular disease prediction models using machine learning algorithms. Research Results XGBoost. The algorithm model showed the best predictive model performance with overall accuracy of 80% before and after. Overall, accuracy was 80.0%, F1 Score was 0.77~0.79, and ROC-AUC was 80%~84%, resulting in predictive model performance. Therefore, it was found that the algorithm used in this study can be used as a reference model necessary to verify the validity and accuracy of cardiovascular disease prediction. A cardiovascular disease prediction analysis algorithm that can enter accurate biometric data collected in future clinical trials, add lifestyle management (exercise, eating habits, etc.) elements, and verify the effect and efficacy on cardiovascular-related bio-signals and disease risk. development, ultimately suggesting that it is possible to develop lifestyle improvement contents (Digital Therapy).

• Journal of Animal Science and Technology
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• v.50 no.2
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• pp.157-166
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• 2008

• Journal of Industrial Technology
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• v.25 no.B
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• pp.63-71
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• 2005

This paper is an experimental result of investigating lateral soil movements at piled bridge abutments by using the centrifuge model facility. Three different centrifuge model experiments, changing the methods of ground improvement at bridge abutment on the soft clayey soil (no improvement, preconsolidation and plastic board drains (PBD), sand compaction pile (SCP) + PBD), were carried out to figure out which method is the most appropriate for resisting against the lateral soil movements. In the centrifuge modelling, construction process in field was reconstructed as close as possible. Displacements of abutment model, ground movement, vertical earth pressure, cone resistance after soil improvement and distribution of water content were monitored during and after centrifuge model tests. As results of centrifuge model experiments, preconsolidation method with PBD was found to be the most effective against the lateral soil movement by analyzing results about displacements of abutment model, ground movement and cone resistance. Increase of shear strength by preconsolidation method resulted in increasing the resistance against lateral soil movement effectively although SCP could mobilize the resistance against lateral soil movement. It was also found that installment with PBD beneath the backfill of bridge abutment induced effective drainage of excess pore water pressure during the consolidation by embanking at the back of the abutment and resulted in increasing the shear strength of clay soil foundation and eventually increasing the resistance of lateral soil movement against piles of bridge abutment.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.487-489
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• 2004

소프트웨어 테스트는 소프트웨어 개발 과정에 매우 중요한 요소이다. 현재 많은 조직들이 테스트 성숙도를 높이기 위한 노력을 진행하고 있다. 그 중에서 일리노이공대의 TMM(Test Maturity Model)이 대표적이라고 볼 수 있다. 하지만 TMM은 바로 테스트 성숙수준을 측정하는데 문제가 있다. 그래서 TMM과 테스트 프로세스를 향상시킬 수 있는 TPI(Test Process Improvement) 모델을 통해, 우리는 Enhanced-TMM에 테스트 속성과 성숙도 상호관련 매트릭스를 사용한 테스트 성숙수준 측정 방법을 구체적으로 제안하고자 한다.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.691-694
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• 1999

This paper presents a performance improvement technique of 2-D towed array shape estimation using Kalman filters. The proposed algorithm by linear model approximation corrects the position errors caused by the Kalman filter results. However, since the assumed linear model makes errors at bending parts, the spline interpolation algorithm based on curve is proposed to reduce the errors.

• MALSORI
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• no.47
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• pp.121-129
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• 2003

This paper describes the use of pitch information for speaker identification. The recognition system is a GMM based one with 4 connected Korean digits speech database. The mean of the pitch period in voiced sections of speech are shown to be ,useful at discriminating between speakers. Utilizing this feature with Gaussian mixture model in the speaker identification system gave a marked improvement, maximum 6% improvement comparing to the baseline Gaussian mixture model.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.10a
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• pp.509-514
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• 2006

Considering the risk management, there are many examples and various studies for the corporation risk. However, I have never seen the project risk management that applied a construction site for practical approach. Therefore, I have developed a chart (I-Chart) for the project risk management, and also built a model (I-Chart scenario analysis) that I could use. I applied this model to container yard reclaimed land in harbor construction with approaching of geotechnical engineering.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.56
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• pp.1-8
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• 2000

We present in this paper an optimal stocking policy for a repairable inventory system under reliability improvement. For this purpose we illustrate commercial flight lines with a large number of planes. This model is supported by a central repair facility. For modeling the nonstationary M/M/s system we implemented SIMAN for computing the time dependent number of units in the repair facility with any number of units. In this model we provide the required inventory level at each location. 1y month. for various levels of associated stock-out risk.

• Journal of the Korea Safety Management & Science
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• v.17 no.3
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• pp.371-375
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• 2015

Smartphone industry grew rapidly enough to draw a close attention in a short period less than ten years. Accordingly, required camera module industry is getting increase. In this study, it will be shown how to improve the productivity of new product model for the camera module before the growth to maximize the company profits.