• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.99-100
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• 2022

As the danger of exposure to the asbestos has been revealed, the importance of demolition asbestos in existing buildings has been raised. Extensive body of study has been conducted to evaluate the risk of demolition asbestos, but there were confined types of variables caused by not reflecting categorical information and limitations in collecting quantitative information. Thus, this study aims to derive a model that predicts the risk in workplace of demolition asbestos by collecting categorical and continuous variables. For this purpose, categorical and continuous variables were collected from asbestos demolition reports, and the risk assessment score was set as the dependent variable. In this study, the influence of each variable was identified using logistic regression, and the risk prediction model methodologies were compared through decision tree regression and artificial neural network. As a result, a conditional risk prediction model was derived to evaluate the risk of demolition asbestos, and this model is expected to be used to ensure the safety of asbestos demolition workers.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.223-224
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• 2023

Optimal fleet management in the planning stage is one of the most critical activities that guarantee successful construction projects. In South Korea, the construction standard production rate database (CSPRD) is normally employed. However, when it comes to a trade-off problem that involves decision-making on optimal sets of equipment to perform a certain task, the method will require the planners' in-depth knowledge and experience regarding the target process and a time consuming estimation of the performance of every possible scenario must be conducted for the deduction of the optimal fleet management. On this account, this research paper proposes a lightweight method of using mixed integer nonlinear programming (MINLP) in multi-objective problems based on CSPRD-based mathematical equations to assist planners in the preplanning stage of choosing the optimal sets of types and size machinery to efficiently arrange the construction scheduling and budgeting.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.161-169
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• 2023

Degenerative arthritis is a common joint disease that affects many elderly people and is typically diagnosed through radiography. However, the need for remote diagnosis is increasing because knee pain and walking disorders caused by degenerative arthritis make face-to-face treatment difficult. This study collects three-dimensional joint coordinates in real time using Azure Kinect DK and calculates 6 gait features through visualization and one-way ANOVA verification. The random forest classifier, trained with these characteristics, classified degenerative arthritis with an accuracy of 97.52%, and the model's basis for classification was identified through classification algorithm by features. Overall, this study not only compensated for the shortcomings of existing diagnostic methods, but also constructed a high-accuracy prediction model using statistically verified gait features and provided detailed prediction results.

• Journal of KIBIM
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• v.14 no.2
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• pp.1-12
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• 2024

The paper proposes a methodology that combines the Random Sample Consensus (RANSAC) algorithm and the Point Cloud Encoder-Decoder Network (PCEDNet) algorithm to automatically extract the length of infrastructure elements from point cloud data acquired through 3D LiDAR scans of retaining walls. This methodology is expected to significantly improve time and cost efficiency compared to traditional manual measurement techniques, which are crucial for the data-driven analysis required in the precision-demanding construction sector. Additionally, the extracted positional and dimensional data can contribute to enhanced accuracy and reliability in Scan-to-BIM processes. The results of this study are anticipated to provide important insights that could accelerate the digital transformation of the construction industry. This paper provides empirical data on how the integration of digital technologies can enhance efficiency and accuracy in the construction industry, and offers directions for future research and application.

• Annual Conference of KIPS
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• 2007.05a
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• pp.20-23
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• 2007

본 논문은 데이터 스트림의 저장을 위한 순환버퍼 기법을 제안한다. 빠르고 많은 입력을 가지는 데이터 스트림의 처리를 위해 DSMS(Data Stream Management System)란 새로운 시스템에 대한 연구가 활발히 진행되고 있다. 현재 입력되고 있는 데이터 스트림과 과거에 발생했던 데이터 스트림을 동시에 검색하는 하이브리드 질의를 위해서는 데이터 스트림이 디스크에 저장되어야 한다. 그러나 데이터 스트림의 빠른 입력 속도와 메모리와 디스크 공간의 한계 때문에 저장된 데이터 스트림에 대한 질의보다는, 현재 입력되고 있는 데이터 스트림에 대한 질의에 대한 연구들이 주로 이루어졌다. 본 논문에서는 제안하는 순환버퍼는 데이터 스트림의 입력과 출력을 비동기적으로 빠르게 실행할 수 있다. 또한 입력되는 네트워크 패킷의 감소와 출력 시 디스크 I/O의 감소를 위하여 순환버퍼에서는 데이터 스트림의 묶음 단위로 입출력이 진행된다. 실험을 통하여 기술이 대량으로 입력되는 데이터 스트림을 빠르게 저장시킬 수 있다는 것을 보인다.

• The Optical Journal
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• s.119
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• pp.24-29
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• 2009

인하대학교 광기술교육센터(센터장 황보창권 교수)와 한국광학기기협회(회장 박종우/삼성전자 DM총괄 사장)가 주최하고 지식경제부, 인하대학교 광과학기술연구소, 한국광학회 광기술분과, 광기술교육연구회 등이 후원하는 제6회 산학연 워크숍이 지난 12월 23일 인하대학교 광기술교육센터에서 열렸다. '한국 광학의 미래'라는 주제로 열린 이번 워크숍에서는 각계 분야의 전문가 7명을 초청하여 최근의 광학산업의 흐름 및 한국 광학기술 동향에 대해 짚어보고 미래 유망산업 및 산학연이 함께 나아가야 할 방향에 대해 전망해보는 의미 있는 시간이 마련되었다.

• Bulletin of the Korean Chemical Society
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• v.10 no.1
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• pp.47-50
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• 1989

The methanolysis reactions of phenylacetyl chlorides have been investigated in methanol-acetonitrile mixtures at temperatures ranging - $15.0-0.0^{\circ}C.$ Substituent and solvent effects on the rate supported an associative $S_N2$ mechanism for the solvolysis. Activation parameters indicated that the reaction is entropy controlled, while the a/s ratios of the Taft's solvactochromic correlation proved to be remarkably constant with a typical value of 0.50 that is consistent for the reactions proceeding by a typical $S_N2$ path.

• Bulletin of the Korean Chemical Society
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• v.19 no.10
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• pp.1042-1047
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• 1998

The fluorescence excitation (FE) spectrum of the S1-S0 (1B2-1A1) transition of dimethyldiazirine cooled in supersonic jet expansions has been obtained. Dispersed fluorescence (DF) spectra have also been taken for some prominent features of the FE spectrum. Vibrational analyses of the FE and DF spectra with the help of an ab initio molecular orbital calculation lead to some new vibrational assignments and refined fundamental frequencies.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.126-128
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• 2022

경량화 기법 중 하나인 Knowledge distillation 은 최근 object detection task 에 적용되고 있다. Knowledge distillation 은 3 가지 범주로 나뉘는데 그들 중에서 Self-Knowledge distillation 은 기존의 Knowledge distillation 에서의 pre-trained teacher 에 대한 의존성 문제를 완화시켜준다. Self-Knowledge distillation 또한 object detection task 에 적용되어 training cost 를 줄이고 고전적인 teacher-based methods 보다 좋은 성능을 성취했다.

• Bulletin of the Korean Chemical Society
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• v.18 no.2
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• pp.208-212
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• 1997

Theoretical AM1 MO studies are reported on the gas-phase deprotonations of N-methyl 4-((Y-phenylsulfonyl)pyridinium cations (Ⅳ) and N-(Y-benzyl) 4-((phenylsulfonyl)methyl pyridinium cations (Ⅴ) using NH3 as a base. Bronsted α values for deprotonation of Ⅳ and Ⅴ are 0.18 and 0.17, respectively. Bronsted β value of 0.53 is found for the deprotonation of Ⅳ and Ⅴ by substituted aniline bases. The negative transition state (TS) imbalances, Ⅰ(=α-β) < 0, are rationalized by the negative distance factor, Δd (=dp-dTS) < 0, where dp and dTS are the distance between anionic charge center and substituents in the product and in the TS, respectively. The inability of d-pπ-conjugation in Ⅳ, where instead n-σ* type sigma delocalization occurs, causes very little lag in the structural reorganization in the TS.