• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.475-481
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• 2023

Softwares, especially like machine learning applications, affect human's life style tremendously. Accordingly, the importance of the cost model for softwares increases rapidly. As cost models, LOC(Line of Code) and M/M(Man-Month) estimates the quantitative aspects of the software. Differently from them, FP(Function Point) focuses on estimating the functional characteristics of software. FP is efficient in the aspect that it estimates qualitative characteristics. FP, however, has a limit for evaluating machine learning softwares because FP does not evaluate the critical factors of machine learning software. In this paper, we propose an extended function point(ExFP) that extends FP to adopt hyper parameter and the complexity of its optimization as the characteristics of the machine learning applications. In the evaluation reflecting the characteristics of machine learning applications. we reveals the effectiveness of the proposed ExFP.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.647-654
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• 2023

Deep Learning is a useful method for classifying and recognizing complex data such as images and text, and the accuracy of the deep learning method is the basis for making artificial intelligence-based services on the Internet useful. However, the vast amount of user da vita used for training in deep learning has led to privacy violation problems, and it is worried that companies that have collected personal and sensitive data of users, such as photographs and voices, own the data indefinitely. Users cannot delete their data and cannot limit the purpose of use. For example, data owners such as medical institutions that want to apply deep learning technology to patients' medical records cannot share patient data because of privacy and confidentiality issues, making it difficult to benefit from deep learning technology. In this paper, we have designed a privacy preservation technique-applied deep learning technique that allows multiple workers to use a neural network model jointly, without sharing input datasets, in multi-party system. We proposed a method that can selectively share small subsets using an optimization algorithm based on modified stochastic gradient descent, confirming that it could facilitate training with increased learning accuracy while protecting private information.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.113-120
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• 2023

Smart farms are steadily increasing in research to minimize labor, energy, and quantity put into crops as IoT technology and artificial intelligence technology are combined. However, research on efficiently managing crop growth information in smart farms has been insufficient to date. In this paper, we propose a management technique that can efficiently monitor crop growth information by applying autonomous sensors to smart farms. The proposed technique focuses on collecting crop growth information through autonomous sensors and then recycling the growth information to crop cultivation. In particular, the proposed technique allocates crop growth information to one slot and then weights each crop to perform load balancing, minimizing interference between crop growth information. In addition, when processing crop growth information in four stages (sensing detection stage, sensing transmission stage, application processing stage, data management stage, etc.), the proposed technique computerizes important crop management points in real time, so an immediate warning system works outside of the management criteria. As a result of the performance evaluation, the accuracy of the autonomous sensor was improved by 22.9% on average compared to the existing technique, and the efficiency was improved by 16.4% on average compared to the existing technique.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1B
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• pp.21-32
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• 2008

Flood forecasting is a very important tool as one of nonstructural measures for reduction of flood damages in life and property and its accuracy is also an important factor. However, when we apply the Storage Function Model(SFM) which is mainly used for the flood forecasting system in Korea, the determination of the parameters is very important but it is difficult. So, the parameters have been calibrated by using an empirical formulas and judgement of hydrologist. Hence, in this study we perform the sensitivity analysis to understand the parameter characteristics and establish the ranges of parameters of the SFM. Also we do the parameter calibration by using the optimization techniques and objective functions, and evaluate their performances. Especially, we suggest a method to determine proper parameters by using a objective function which can be obtained from flood events. So, we use the suggested method for parameter estimation and compare the estimated parameters with the previously reported parameters. As a result of the application, the estimated parameters by the suggested method showed better than them from the previously reported parameters.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.747-754
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• 2006

Real-time traffic information disseminated through VMS is known to have effects not only on driver to plan a route choice, detour the congestion, and cope with incident, but also on VMS operator to manage the traffic volume indirectly. But, the dissemination of traffic information is operated in the side of provider, not of user. Importance-Performance analysis (IPA) offers a simple, useful method for simultaneously considering both the importance and performance dimensions when evaluating or improving strategy. This technique has been successfully used in a variety of settings to define priorities and guide resource optimization decisions. This study uses IPA to evaluate traffic information strategies through VMS to make resource improvement recommendations. It gained 760 samples by field surveys, which are conducted in Korean Thanksgiving Day, weekday and weekend at the service areas of expressways. The results indicate that the motivations in quadrant I (concentrate here) are dissemination of exactly information and quick transmission, while distance of VMS, most drivers are not satisfied with that is located in quadrant III (low priority).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2A
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• pp.285-292
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• 2006

In this study, a method determining the local bond-slip model from pure shear test results of CFRP sheet-concrete adhesive joints is proposed and local bond-slip models are presented. Adhesive joints with a specific bond-slip model, which is assumed as multi-linear curve in order to represent arbitary function, are solved numerically. The difference between the solution and test results are minimized for finding the bond-slip model. The model with bilinear curve is also optimized to verify the improvement of multi-linear model. The selected test results are ultimate load-adhesive length curves from a series of adhesive joints and load-displacement curves for each joint. The optimization problem is formulated by physical programming, and the optimized bond-slip model is found using genetic algorithm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3A
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• pp.229-239
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• 2010

For the purpose of improvement of the load carrying capacity and constructibility of the conventional steel-concrete composite girder through a effective appliance of the construction materials and optimization of the girder section, a new type section of composite girder and RC shear connection were proposed. In this study shear strength of the RC shear connection is estimated, and the characteristics of shear load-slip behaviour is analyzed. Push-out tests on shear specimens and FEM analysis with various design parameters are carried out, and results are analyzed. The results of test and FEM analysis showed that shear strength of RC shear connection is underestimated by the design provisions of the current design code. By regression analysis a empirical equation for the estimation of shear strength of RC shear connection is proposed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4A
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• pp.621-637
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• 2006

Although the approaches implementing strut-tie models are the valuable tools for designing discontinuity regions of structural concrete, the approaches of the current design codes have to be improved for the design of structural concrete subjected to complex loading and geometrical conditions because of the uncertainties in the selection of strut-tie model, in the use of an indeterminate strut-tie model, and in the effective strengths of struts and nodal zones. To improve the uncertainties, a grid struttie model approach is proposed in this study. The proposed approach, allowing to perform a consistent and effective design of structural concrete, employs an initial grid strut-tie model in which various load combinations can be considered. In addition, the approach performs an automatic selection of an optimal strut-tie model by evaluating the capacities of struts and ties using a simple optimization algorithm. The validity and effectiveness of the proposed approach is verified by conducting the analysis of the four reinforced concrete deep beams tested to failure and the design of shearwalls with two openings.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6A
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• pp.1023-1032
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• 2006

In this paper, a new method for the bridge maintenance is proposed to overcome the limit of the existing methods and to implement the preventive bridge maintenance system. The proposed method can establish the lifetime optimum maintenance strategy of the deteriorating bridges considering the life-cycle performance as well as the life-cycle cost. The lifetime performance of the deteriorating bridges is evaluated by the safety index based on the structural reliability and the condition index detailing the condition state. The life-cycle cost is estimated by considering not only the direct maintenance cost but also the user and failure cost. The genetic algorithm is applied to generate a set of maintenance scenarios which is the multi-objective combinatorial optimization problem related to the life-cycle cost and performance. The study examined the proposed method by establishing a maintenance strategy for the existing bridge and its advantages. The result shows that the proposed method can be effectively applied to deciding the bridge maintenance strategy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6B
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• pp.571-578
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• 2010

Manning's roughness coefficients were reevaluated for the computation of river flow of the Han River, the Nakdong River and the Geum River. The roughness coefficients were estimated by two methods. One is based on the assumption that roughness is primarily a function of grain diameter and the other is based on the findings that roughness may vary significantly with the flow discharge. The roughness coefficients adopted in each river improvement master plan have been compared with those obtained using the FLDWAV in this study, and their applicabilities have been reviewed, using the FLDWAV and HEC-RAS models. The design flood water levels computed by the abovementioned models with the roughness coefficients proposed in this study have shown good agreement with the measurements of time variation. The roughness coefficients computed using the FLDWAV model showed nearly no close correlation with the various hydraulic characteristic factors, such as grain size and river depth, etc.. Finally the design flood water levels and levee safety about the downstream part from the Paldang Dam of the Han River has been reviewed using HEC-2 model with roughness coefficients of this study and the results indicated that some parts of the existing levees were short of safety.