• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.1277-1282
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• 2008

Recently LCD panels have becom very important components for portable electronics. In the high density interconnection material, ACF's are used to connect the outer lead of the tape automated bonding to the transparent indium tin oxide electrodes of the LCD panel. ACF consists of an adhesive polymer matrix and randomly dispersed conductive balls. In this study, we analyzed Failure Mode / Mechanism of ACF which is identified Conductive ball Corrsion, Delamination, Crack and Polymer Expansion / Swelling. In ALT(Accelerated Life Test), we select primary stress factors as temperature and humidity. As time passes by, an increase of connection resistance was observed. In conclusion, we have found that high temperature / humidity affects the adhesion.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2012년도 한국컴퓨터종합학술대회논문집 Vol.39 No.1(B)
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• pp.438-440
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• 2012

대용량 데이터를 효율적으로 군집화하기위해 개발된 Canopy Clustering은 2개의 파라미터 (T1, T2)에 기반하여 Canopy 형성이 결정되며, 결과적으로 이들 파라미터에 의해 군집화 결과가 크게 달라질 수 있다. 이에 따라 데이터의 특성을 잘 반영하는 파라미터 값을 적절히 선택하는 것이 매우 중요하지만, 자동화된 파라미터 설정 기법의 부재로 인하여, 기존 연구에서는 사용자의 경험에 의하여 Canopy Clustering의 파라미터 값을 설정하는 것이 일반적이었다. 본 논문에서는 통계적 샘플링을 이용하여 T1, T2의 값을 효과적으로 설정하는 방법을 제안한다.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2016년도 춘계 학술논문 발표대회
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• pp.162-163
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• 2016

This paper presents a mathematical model for optimizing earthwork allocation plan that minimizes earthwork cost. The model takes into account operational constraints in the real-world earthwork such as material-type (i.e., quality level of material) and quantities excavated from cut-sections, required quality of material and quantities for each embankment layer, top-down cutting and bottom-up filling constraints, and allocation orders. These constraints are successfully handled by assuming the rock-earth material as the three dimensional (3D) blocks. The study is of value to project scheduler because the model identifies the optimal earth allocation plan (i.e., haul direction (cut and fill pairs), quantities of soil, type of material, and order of allocations) expeditiously and is developed as an automated system for usability. It is also relevant to estimator in that it computes more realistic earthworks costs estimation. The economic impact and validity of the mathematical model was confirmed by performing test cases.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.519-521
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• 1998

Fuzzy inference systems have found many applications in recent years. The fuzzy inference system design procedure is related to an expert or a skilled human operator in many fields. Various attempts have been made in optimizing its structure using genetic algorithm automated designs. This paper presents a new approach to structurally optimized designs of FNN models. The messy genetic algorithm is used to obtain structurally optimized fuzzy neural network models. Structural optimization is regarded important before neural network based learning is switched into. We have applied the method to the problem of a time series estimation.

• 소성∙가공
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• 제12권4호
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• pp.328-333
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• 2003

Ball indentation tests have been used to estimate the mechanical properties of materials by several investigators. In this study, load-depth curves from ball indentation tests were analyzed using the geometric conditions of the contact between ball and specimen. A series of numerical calculations and experimental results showed that the contact load-depth curves could be simplified by linear functions. Once we obtained the contact indentation depth from linearizing the experimental indentation curves, the estimation process of the flow properties became straight-forward and the scatter of results could be drastically reduced.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.450-452
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• 2003

In the present investigation, an estimation of the growth of heat island development of Tokyo metropolis which accounts nearly 100 sq. km of areal spread has been carried out. Band 6 data of LANDSAT TM (Thematic Mapper) data acquired on August 1984 and 1994 have been used for estimating the expansion of the heat island development. Since the vegetation decrease is usually associated with the heat island development, a ratio of green covering has also been assessed using TM data. In order to establish the relationship with the air temperature, AMeDAS(Automated Meteorological Data Acquisition System) data have been correlated.

• 국제학술발표논문집
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• The 2th International Conference on Construction Engineering and Project Management
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• pp.239-248
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• 2007

In the highly competitive construction industry, a slight inaccuracy of estimation can easily cause the loss of a project. Erroneous experience-based cost estimates or allocations of on-site supervisory manpower often offset the profit gained from the project and may jeopardize the management processes. To counter these types of problems, we develop a model using mathematical analysis and case-based reasoning to automate the allocation of on-site supervisory manpower and estimate construction site costs. The method is founded upon laborious data collection processes and analysis by matching statistical assumptions, and is applicable to construction projects. In the modeling the costs and allocation of on-site supervisory manpower are quantified for both owners and contractors before initiating or bidding on the projects. The findings confirm that the degree of variation of the model predictions has an accuracy rate at 88.47%. Single-site construction projects can be accurately predicted and the assignment of supervisory manpower feasibly automated.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2021년도 가을 학술논문 발표대회
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• pp.221-222
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• 2021

Conventionally, in material management at a construction site, the type, size, and quantity of materials are identified by the eyes of the worker. Labor-intensive material management by manpower is slow, requires a lot of manpower, is prone to errors, and has limitations in that computerization of information on the identified types and quantities is additionally required. Therefore, a method that can quickly and accurately determine the type, size, and quantity of materials with a minimum number of workers is required to reduce labor costs at the construction site and improve work efficiency. In this study, we developed an automated convolution neural network(CNN) and computer vision technology-based rebar size and quantity estimation system that can quickly and accurately determine the type, size, and quantity of materials through images.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.248-251
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• 2015

High injury and fatality rates remain a serious problem in the construction industry. Many construction injuries and fatalities can be prevented if workers can recognize potential hazards and take actions in time. Many efforts have been devoted in improving workers' ability of hazard recognition through various safety training and education methods. However, a reliable approach for evaluating this ability is missing. Previous studies in the field of human behavior and phycology indicate that the visual focus of attention (VFOA) is a good indicator of worker's actual focus. Towards this direction, this study introduces an automated approach for estimating the VFOA of equipment operators using a head orientation-based VFOA estimation method. The proposed method is validated in a virtual reality scenario using an immersive head mounted display. Results show that the proposed method can effectively estimate the VFOA of test subjects in different test scenarios. The findings in this study broaden the knowledge of detecting the visual focus and distraction of construction workers, and envision the future work in improving work's ability of hazard recognition.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.187-194
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• 2024

For precise cardiac diagnostics and treatment, we introduce a novel method for patient-specific mapping between myocardial and coronary anatomy, leveraging local variations in myocardial thickness. This complex system integrates and automates multiple sophisticated components, including left ventricle segmentation, myocardium segmentation, long-axis estimation, coronary artery tracking, and advanced geodesic Voronoi distance mapping. It meticulously accounts for variations in myocardial thickness and precisely delineates the boundaries between coronary territories according to the conventional 17-segment myocardial model. Each phase of the system provides a step-by-step approach to automate coronary artery mapping onto the myocardium. This innovative method promises to transform cardiac imaging by offering highly precise, automated, and patient-specific analyses, potentially enhancing the accuracy of diagnoses and the effectiveness of therapeutic interventions for various cardiac conditions.