• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.30-39
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• 2006

Iris recognition is that identifies a user based on the unique iris texture patterns which has the functionalities of dilating or contracting pupil region. Iris recognition systems extract the iris pattern in iris image captured by iris recognition camera. Therefore performance of iris recognition is affected by the quality of iris image which includes iris pattern. If iris image is blurred, iris pattern is transformed. It causes FRR(False Rejection Error) to be increased. Optical defocusing is the main factor to make blurred iris images. In conventional iris recognition camera, they use two kinds of focusing methods such as lilted and auto-focusing method. In case of fixed focusing method, the users should repeatedly align their eyes in DOF(Depth of Field), while the iris recognition system acquires good focused is image. Therefore it can give much inconvenience to the users. In case of auto-focusing method, the iris recognition camera moves focus lens with auto-focusing algorithm for capturing the best focused image. However, that needs additional H/W equipment such as distance measuring sensor between users and camera lens, and motor to move focus lens. Therefore the size and cost of iris recognition camera are increased and this kind of camera cannot be used for small sized mobile device. To overcome those problems, we propose method to increase DOF by iris image restoration algorithm based on focus value of iris image. When we tested our proposed algorithm with BM-ET100 made by Panasonic, we could increase operation range from 48-53cm to 46-56cm.

• Korean Journal of Construction Engineering and Management
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• v.17 no.3
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• pp.71-80
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• 2016

PERT(Project Evaluation and Review Technique) is typical method in order to probabilistically establish the schedule plan for large scale complex project or mega project. PERT technique is impossible to estimate relationship of each activity probabilistically when there are overlapping relationships because it is limited to Finish-to-Start(FS) relationship. In order to overcome this kind of limitation of PERT technique, PLET(Probabilistic Linkage Evaluation Technique) has been suggested to probabilistically estimate project duration for various overlapping relationships for each activity. However, estimating project duration by PLET technique only considers uncertainty of relationship between activities and not activity time, thus it is not the perfect duration estimating method. The main objective of this research is to propose the integration model of PERT and PLET and verify its probabilistic validity. By verifying application of time calculation method of integration model in practical case, this research will suggest probabilistic project duration estimating method in schedule plan of high-risk construction industry.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.4
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• pp.941-951
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• 2015

In the recent years, Korean construction companies have been awarded 680 billion USD in the oversea projects which lead to a successful quantitative growth. However, due to the lack of capability in the core technology and project management compared to the leading companies, in addition to low-price bidding, massive deficit projects have caused problems to the companies. In order to overcome the limitations of the lack of capabilities, the term constructability has been researched recently by developed countries to apply in the practical use. The concept of constructability must be applied for Korean companies to compete in the EPC construction projects. The term constructability is defined as the factor that affect the overall construction process of a project which is defined by the ease of construction and to secure the project quality. Therefore, this study aims to develop a constructability assessment model using the structural equation to assess the factors that affect the constructability in the design and construction stage. The purpose of using the structural equation is to analyze the direct and indirect correlation between each factor that affects the international construction projects. Total of 8 latent variables and 34 measured variables are derived through literature review, corporate reports, experts' interview and surveys. The result of the model suggests the constructability factors that are to be managed the most efficiently to reduce cost, time and improve the quality as well as a countermeasure strategy to successfully execute the target international construction projects.

• Development and Reproduction
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• v.11 no.1
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• pp.1-11
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• 2007

Specific endometrial preparation should occur during periimplantation period. That is a progress of serial differentiation and is absolute in implantation of embryo and successful pregnancy. Remodeling of tissues shown during embryogenesis is regulated by various factors including extracellular matrix (ECM). Marked changes during pregnancy are including embryo migration, decidual response, and differentiation of placenta in placental animals including human. These changes to successful implantation in embryo and uterus have to prepare the competence for attachment of embryo and uterus, and invasion defense of uterus. During these changes, ECM dramatically changes for maintaining the uterine and embryonic functions. The major component of most connective tissue is collagens. It is very complex and hard to explore the mechanisms for ECM modulation. Recently using high throughput methodology, PCR-select cDNA subtraction method, microarray, many candidate genes have been identified. Steroid hormones have fundamental role in implantation and maintenance of pregnancy. Dermatopontin, a regulator of collagen accumulation, is regulated spatio-temporally in the uterus by primarily progesterone through progesterone receptors at the time of implantation. Modulation of extracellular matrix is critically regulated by cascade of gene net-works which are regulated by cascade of sex steroid hormones. Pathological regulation of uterine extracellular matrix reported in diabetic patients. To know the extracellular modulation is essential to understanding implantation, feto-placental development and overcome the paths involved in female reproduction. Though ECM composed with very various components and it is complex, the present review focused on the fate of collagens during periimplantation period.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.1 s.94
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• pp.20-28
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• 2005

This paper addresses uncertainty issues encountered recently in measuring head vibration using the conventional 6-axis or 9-axis bite-bar model. Those conventional bite-bar models are shown to present insufficient information to evaluate a generalized motion of head vibration. In order to overcome such limit, a new theoretical measurement model that consists of four 3-axis linear accelerometers is suggested. It is shown to enable the measurement of three angular acceleration components and six second-order angular velocity-dependent terms. Those nine angular motion-related ones, in addition to the three linear acceleration terms at the origin, are found to make it possible to evaluate the generalized head vibration for a given position. To examine the feasibility of the proposed method, a newly designed 12-axis bite-bar was developed. Detailed experimental results obtained from the developed 12-axis bite-bar are demonstrated in this paper. They illustrate that the popular 6-axis bite-bar model yield about $4.0\%$ relative measurement uncertainty for the pitch component of head vibration, $14\%$ and $10\%$ relative measurement uncertainty for the roll and yaw components of head vibration, respectively. Furthermore, this paper proposes other uncertainty factors to be considered in the future.

• Journal of Korean Society of Transportation
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• v.32 no.4
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• pp.369-379
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• 2014

The Statistical regression model has been used to construct crash prediction models, despite its limitations in assuming data distribution and functional form. In response to the limitations associated with the statistical regression models, a few studies based on non-parametric methods such as neural networks have been proposed to develop crash prediction models. However, these models have a major limitation in that they work as black boxes, and therefore cannot be directly used to identify the relationships between crash frequency and crash factors. A genetic programming model can find a solution to a problem without any specified assumptions and remove the black box effect. Hence, this paper investigates the application of the genetic programming technique to develope the crash prediction model. The data collected from the Gyeongbu expressway during the past three years (2010-2012), were separated into straight and curve sections. The random forest technique was applied to select the important variables that affect crash occurrence. The genetic programming model was developed based on the variables that were selected by the random forest. To test the goodness of fit of the genetic programming model, the RMSE of each model was compared to that of the negative binomial regression model. The test results indicate that the goodness of fit of the genetic programming models is superior to that of the negative binomial models.

• Management & Information Systems Review
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• v.28 no.4
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• pp.27-44
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• 2009

Economic value of a certain technology is of great interest and importance in a wide variety of investment circumstances. These vary from companies considering investing in R&D projects, to venture capitalists funding start-up companies. However, such valuation is extremely difficult in any case, and the cost of failure can be very high. Many techniques have been proposed to assist managers facing this issue, from traditional discounted cash flow analysis to more recent methods based on real options. In the meantime, the discounted cash flow method has limitations in applying the valuation of technology. At the same time, there have been various solutions to overcome theoretical problems of the method. Real options have been thought as a solution. However, there are another problems in using them in real world. This paper reviews the previous studies on the valuation of technology in several aspects, discusses the practicability of the various methods available, and explore the application of a hybrid model, which aims to make these rather aore the ideas more accessible to practicing managers.

• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.61-74
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• 2010

ITS (Intelligent transportation systems) collects real-time traffic data, and accumulates vest historical data. But tremendous historical data has not been managed and employed efficiently. With the introduction of data management systems like ADMS (Archived Data Management System), the potentiality of huge historical data dramatically surfs up. However, traffic data in any data management system includes missing values in nature, and one of major obstacles in applying these data has been the missing data because it makes an entire dataset useless every so often. For these reasons, imputation techniques take a key role in data management systems. To address these limitations, this paper presents a promising imputation technique which could be mounted in data management systems and robustly generates the estimations for missing values included in historical data. The developed model, based on NPR (Non-Parametric Regression) approach, employs various traffic data patterns in historical data and is designated for practical requirements such as the minimization of parameters, computational speed, the imputation of various types of missing data, and multiple imputation. The model was tested under the conditions of various missing data types. The results showed that the model outperforms reported existing approaches in the side of prediction accuracy, and meets the computational speed required to be mounted in traffic data management systems.

• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.169-183
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• 2010

Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a freeway and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, existing technologies, this freeway attribute, velocity changes, volume changes, occupancy changes reflect judge the primary. Furthermore, We pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian Mixture model analytical method which has been considered the best among well-known environmental obstacle reduction methods. Therefore, in this way, the accident was the final decision. Also, environmental factors occur frequently, and with the index finger situations, effectively reducing that can actively and environmentally adaptive techniques through accident final judgment. This implementation of the evaluate performance of the experiment road of 12 incidents in simulated and the jang-hang IC's real-time accident experiment. As a result, the do well detection 93.33%, false alarm 6.7% as showed high reliability.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.884-891
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• 2020

The collapse of bridges can cause massive casualties and economic losses. Therefore, it is thus essential to evaluate the structural safety of bridges. For this task, structural reliability analysis, considering various bridge-related uncertainty factors, is often used. This paper proposes a new computational platform to perform structural reliability analysis for bridges and evaluate their structural safety under various loading conditions. For this purpose, a software package of reliability analysis, Finite Element Reliability Using MATLAB (FERUM), was integrated with MIDAS/CIVIL, which is a widely-used commercial software package specialized for bridges. Furthermore, a graphical user interface (GUI) control module has been added to FERUM to overcome the limitations of software operation. In this study, the proposed platform was applied to a simple frame structure, and the analysis results of the FORM (First-Order Reliability Method) and MCS (Monte Carlo simulation), which are representative reliability analysis methods, were compared. The proposed platform was verified by confirming that the calculated failure probability difference was less than 5%. In addition, the structural safety of a pre-stressed concrete (PSC) bridge was evaluated considering the KL-510 vehicle model. The proposed new structural reliability analysis platform is expected to enable an effective reliability-based safety evaluation of bridges.