• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.1-9
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• 2018

In the fourth industrial revolution, which has become an issue now, we have been able to receive instant analysis results faster than the existing slow speed through various Big Data technologies, and to conduct real-time monitoring on mobile and web. First, various irregular sensor Data is generated using IoT device, Raspberry Pi. Sensor Data is collected in real time, and the collected data is distributed and stored using several nodes. Then, the stored Sensor Data is processed and refined. Visualize and output the analysis result after analysis. By using these methods, we can train the human resources required for Big Data and mobile related fields using IoT, and process data efficiently and quickly. We also provide information that can confirm the reliability of research results through real time monitoring.

• Tunnel and Underground Space
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• v.31 no.1
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• pp.25-40
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• 2021

As the era of Industry 4.0 arrives, the researches using artificial intelligence in the field of rock engineering as well have increased. For a better understanding and availability of AI, this paper analyzed the types of algorithms and how to apply them to the research papers where AI is applied among domestic and international studies related to tunnels, blasting and mines that are major objects in which rock engineering techniques are applied. The analysis results show that the main specific fields in which AI is applied are rock mass classification and prediction of TBM advance rate as well as geological condition ahead of TBM in a tunnel field, prediction of fragmentation and flyrock in a blasting field, and the evaluation of subsidence risk in abandoned mines. Of various AI algorithms, an artificial neural network is overwhelmingly applied among investigated fields. To enhance the credibility and accuracy of a study result, an accurate and thorough understanding on AI algorithms that a researcher wants to use is essential, and it is expected that to solve various problems in the rock engineering fields which have difficulty in approaching or analyzing at present, research ideas using not only machine learning but also deep learning such as CNN or RNN will increase.

• Fire Science and Engineering
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• v.17 no.4
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• pp.76-85
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• 2003

In this study, we write down the definitions, their causes and the techniques of analysis as a theoretical consideration of common cause failures, and investigate the limitation and the importance of the common cause failures by applying to the analysis on the fire protection as a representative safety facility. As you can know in the reliability analysis, most impressive cause is the malfunctions of pumping operations; especially the common cause failure of two pumps is dominant. In other words, it is possible to assess system-reliability as twice as actual without CCF From these, CCF is extraordinarily important and the results are highly dependent on the CCF factor. And although it would increase with multiple installations, the reliability are not defined as linear with those multiplications. In addition, the differences in results due to the models for analysis are not significant, whereas the various sources of data produce highly different results. Therefore, we conclude that the reliabilities are dependent on the quality of the usable data much better than the variety of models. As a result, the basic and engineering device for the preventions of CCF of the multiple facilities is to design it as reliably as to design the fire-water pump. That is to say, we must assess those reliabilities using PFD whether they are appropriate to SIL (Safety Integrity Level) which is required for the reliability in SIS (Safety Instrumented System). The result of the analysis on the reliability of the fire-water supply with CCF shows that PFD is 3.80E-3, so that it cannot be said to be designed as safely as in the level of SIL5. However, without CCF, PFD is 1.82E-3 which means that they are designed as unsafely as before.

• Journal of Convergence for Information Technology
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• v.10 no.8
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• pp.53-59
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• 2020

This paper relates to an IoT device system that detects sound source and estimates the sound source location. More specifically, it is a system using a sound source direction detection device that can accurately detect the direction of a sound source by analyzing the difference of arrival time of a sound source signal collected from microphone sensors, and track the generation direction of a sound source using an IoT sensor. As a result of a performance test by generating a sound source, it was confirmed that it operates very accurately within 140dB of the acoustic detection area, within 1 second of response time, and within 1° of directional angle resolution. In the future, based on this design plan, we plan to commercialize it by improving the reliability by reflecting the artificial intelligence algorithm through big data analysis.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.444-455
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• 2013

The purpose of this study is to explore the selection attributes for parents of children with language disability when choosing a clinic. The data collection was carried out in 3 steps: the preliminary survey, first open survey and second survey in AHP(Analytic Hierarchy Process). The subjects of were 252 in total. The results were as follows: First, The order of priority attributes in superior categories for parents of children with language disability when selecting a clinic were 'therapist-related attributes', 'program-related attributes' and 'physical-related attributes' in turn. The top 5 priority attributes in subcategories were 'therapist's academic background and major', 'ability to make a rapport', 'clinical experience and qualification of therapist', 'kindness and confidence' and 'counseling program for parents'. Second, The parents of preschoolers age 6 and younger chose 'clinical experience and qualification of therapist', 'counseling program for parents' and 'learning materials' for the most priority attributes, whereas the parents of students age from 7 to 12, considered 'therapist's academic background and major', 'clinical fee' and 'distance transport parking' more importantly to select a clinic. The results of this study provided preliminary data for successful planning of speech and language therapy.

• Convergence Security Journal
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• v.23 no.1
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• pp.27-33
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• 2023

Digitalization due to COVID-19 has rapidly developed artificial intelligence-based voice recognition technology. However, this technology causes unfair social problems, such as race and gender discrimination if datasets are biased against some groups, and degrades the reliability and security of artificial intelligence services. In this work, we compare and analyze accuracy-based unfairness in biased data environments using VGGNet (Visual Geometry Group Network), ResNet (Residual Neural Network), and MobileNet, which are representative CNN (Convolutional Neural Network) models of artificial intelligence. Experimental results show that ResNet34 showed the highest accuracy for women and men at 91% and 89.9%in Top1-accuracy, while ResNet18 showed the slightest accuracy difference between genders at 1.8%. The difference in accuracy between genders by model causes differences in service quality and unfair results between men and women when using the service.

• Archives of design research
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• v.20
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• pp.51-58
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• 1997

This paper aims to aid a practical evaluation for screening out the design proposais under applying the IRDS system, which is developed a computer aided industrial design system as a computer application system. In this study, the author adopted 3 evaluation methods with criteria which have quantitative and qualitative attributes : the Intuitive Evaluation Methods(X), the Accumulative Evaluation Method(Y), the Benchmarking Evaluation Methods(Z). The results show that the 3 Methods have reciprocal relationships under reliability(r=0.0001). In analysis on the properties of the evaluation methods, the Evaluation Method (X) shows rapidity especially, the Evaluation Method (Y); relativity, the Evaluation Method(Z); importance respectively. The correlation analysis between the evaluation methods makes the null hypothesis denying, then we could adapt the research hypothesis. Therefore the correlation between them has positive relationship, and it shows thicker than the result of the 1st study.

• Electronics and Telecommunications Trends
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• v.27 no.1
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• pp.19-30
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• 2012

미사용 주파수 대역의 전파 자원인 테라헤르츠(THz)파의 특징을 살려서 고속 대용량 고신뢰 무선네트워크(인프라)의 구축, 끊김없는(seamless) 접속과 비압축 무선전송 기술 확보, 고도의 사회 보안 감시 기술을 확보하면, 비상사태(재해 및 재난) 시 안전 안심 사회를 실현하는 데 기여할 수 있는 새로운 THz 기술 및 서비스를 제공할 수 있다. 특히, 재해 및 재난 현장에서 확산되는 유독성 가스의 센싱이나 인명(생명체) 탐색용 이미지 확보에 THz 기술을 활용하여, 재난자 구조와 2차 재해 방지에서 중요한 역할을 하는 등, 재해 및 재난 현장에서 발생되는 피해를 최소화시키는 데에 공헌할 수 있다. 테라헤르츠 대역용 원격(remote) 분광 센싱 시스템과 이미징 시스템의 연구 결과(사례)와 이러한 THz 응용 시스템을 구성하는 중요한 요소기술들을 소개하고, 향후의 연구개발 내용 및 기술전망에 대해서 리뷰(평설)한다.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1-2
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• 2007

제3차 전력수급기본계획(산업자원부, '06.12 공고)에 의하면 전국 총수요의 43% 정도가 수도권에 집중될 것으로 전망되고, 또한 지역간 수급불균형 현상 심화 및 계통 고장전류 증대 등에 따른 수도권의 전력공급 신뢰도 확보가 우려됨에 따라 안정적 전력계통 구축을 위한 중장기적 대책 마련이 필요하다. 따라서 본 논문에서는 발전설비의 인천 서해안지역 집중 현상 및 한강 이북지역에 대한 전력공급 능력 등을 상세 검토 분석하였으며, 지역간의 원활한 전력융통을 위하여 발전설비가 집중된 인천지역에서 수도권 내륙으로의 신규 초고압 송전선로의 건설 필요성 및 고장전류 감소를 위한 수도권 환상망의 2원화 구성 등의 내용을 개략적으로 설명하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.184-187
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• 2009

현재 국내에는 수문자료 품질등급 및 품질관리 방법에 대한 기준과 인력 예산 시스템의 부재로 인해 수문자료 품질관리에 대한 지속적인 수행이 미흡한 실정이다. 이에 국토해양부에서는 국가 차원에서의 일관성 있는 수문자료 품질관리 기준을 제시하고, 현업에서 활용 가능한 시스템을 구축하기 위해 2007년 한강 수계를 대상으로 관측소별 품질관리 기준을 설정하고, 국가 수문자료 품질관리시스템 구축(I)을 추진하였다. 본 연구에서는 그 두 번째 단계인 낙동강 수계를 대상으로 하여 수문관측소의 기존 수문자료를 수집하여 자료 특성을 분석하고 지점별 자동 품질관리 기준을 설정하였다. 또한, 1차에서 구축한 우량 및 수위 자료의 품질관리에서 유량자료 품질관리를 추가하여 유량자료 품질관리의 절차와 자료 생성단계별 품질관리 수행에 대한방안을 수립하였다. 또한, 현업에서 적용이 가능하도록 수위 일치성 검토, 수위-유량관계곡선식 검토 및 유량환산 후의 상 하류 유량 비교 분석을 하여 과정의 적절성 등을 판단할 수 있는 지원 프로그램을 개발하였다. 이를 통해 수문자료에 대한 일상적인 품질관리가 가능하고 신뢰도 높은 수문자료 제공으로 인해 관련 분야의 정확도를 제고할 수 있으리라 사료된다.