• Water Engineering Research
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• v.3 no.1
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• pp.57-62
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• 2002

This research is intended to integrate long-term operation rules and real time operation policy for conservation & flood control in a reservoir. The familiar Yield model has been modified and used to provide long-term rule curves. The model employs linear programming technique under given physical conditions, i.e., total capacity, dead storage, spillways, outlet capacity and their respective elevations to find required and desired minimum storage fur different demands. To investigate the system behavior resulting from the above-mentioned operating policy, i.e., the rule curves, the simulation model was used. Results of the simulation model show that the results of the optimization model are indeed valid. After confirmation of the above mentioned rule curves by the simulation models, gate operation procedure was merged with the long term operation rules to determine the optimum reservoir operating policy. In the gate operation procedure, operating policy in downstream flood plain, i.e., determination of damaging and non-damaging discharges in flood plain, peak floods, which could be routed by reservoir, are determined. Also outflow hydrograph and variations of water surface levels for two known hydrographs are determined. To examine efficiency of the above-mentioned models and their ability in determining the optimum operation policy, Esteghlal reservoir in Iran was analyzed as a case study. A numerical model fur the solution of two-dimensional dam break problems using fractional step method is developed on unstructured grid. The model is based on second-order Weighted Averaged Flux(WAF) scheme with HLLC approximate Riemann solver. To control the nonphysical oscillations associated with second-order accuracy, TVD scheme with SUPERBEE limiter is used. The developed model is verified by comparing the computational solutions with analytic solutions in idealized test cases. Very good agreements have been achieved in the verifications.

• Korean Business Review
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• v.15
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• pp.79-97
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• 2002

In this study, an analytical CRM for customer segmentation is exercised by integrating and analyzing the customer profile data and the access data to a particular web site. We believe that effective customer segmentation will be possible with a basis of the understanding of customer characteristics as well as behavior on the web. One of the critical tasks in the web data-mining is concerned with both 'how to collect the data from the web in an efficient manner?' and 'how to integrate the data(mostly in a variety of types) effectively for the analysis?' This study proposes a panel approach as an efficient data collection method in the web. For the customer data analysis, OLAF and a tree-structured algorithm are applied in this study. The results of the analysis with both techniques are compared, confirming the previous work which the two techniques are inter-complementary.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.5
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• pp.39-50
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• 2014

Today people use a smartphone as a tool for enjoying personal hobbies or entertaining contents as well as communication media. Most of the traditional game-specific platforms have transferred to smartphones equipped with social network games that integrate games with human relationships. As average life span of most games has been shortened gradually, game companies should be ready to develop new games to meet user needs. In this study we investigate the acceptance of social games, enjoyable by users and their friends linked in social networks. Since user behavior of social games may show cultural differences by country, we perform a comparative study on acceptance of social games between Korean and Chinese users. The structural relationships among factors affecting social game adoption have been analyzed focusing on differences between Korean and Chinese. We analyze similarities and differences of adoption mechanism in two countries and present some practical implications for related industry.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.327-341
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• 2021

The knowledge management was considered as the inevitable result of the rule of knowledge in this era, and its importance became clear in being the main source for achieving success, the need to consider and manage knowledge as an independent field that must be addressed with a clear scientific methodology has become intangible - they are very valuable and a strategic asset. On the other hand, the innovation process relates to all parts of the organization, and helps to improve the behavioral patterns of individuals and their attitudes towards adopting modern and innovative ideas, it is a purposeful process adopted by the senior management and works to provide the capabilities and requirements for embodying the innovative behavior in it. In the field of dealing with the market, it is a product of the organization's innovative approach, which aims at advancement, change, and intended and organized renewal. The main objective of this article is to determine the most appropriate ways to integrate knowledge management mechanisms to employ innovation factors within universities based on the role of universities in supporting innovation. This was achieved through reviewing many relevant research and listing the most prominent concepts of knowledge management, its importance, objectives, and processes determining the stages of knowledge management application, the requirements for applying knowledge management, and the obstacles that impede its application; Then the statement "Innovation in universities, through which it addressed the concept of innovation, its importance, stages, and requirements for its application, as well as identifying the most prominent models of innovation, and obstacles to innovation, in addition to that the role of universities in supporting innovation will be identified. From the surveyed study done in this article, we concluded that the relationship among organizational culture, knowledge management and innovation capability can provide useful insights for managers regarding developing a strong culture, promote knowledge management practices effectively and eventually enhance the whole organization's innovation capability. Also, we found that different components of Knowledge Management as Knowledge activities, Knowledge types, transformation of knowledge and technology have a significant positive effect in bringing innovation through transformation of knowledge into knowledge assets in universities.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.41-68
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• 2019

Multi-view learning considers data from various viewpoints as well as attempts to integrate various information from data. Multi-view learning has been studied recently and has showed superior performance to a model learned from only a single view. With the introduction of deep learning techniques to a multi-view learning approach, it has showed good results in various fields such as image, text, voice, and video. In this study, we introduce how multi-view learning methods solve various problems faced in human behavior recognition, medical areas, information retrieval and facial expression recognition. In addition, we review data integration principles of multi-view learning methods by classifying traditional multi-view learning methods into data integration, classifiers integration, and representation integration. Finally, we examine how CNN, RNN, RBM, Autoencoder, and GAN, which are commonly used among various deep learning methods, are applied to multi-view learning algorithms. We categorize CNN and RNN-based learning methods as supervised learning, and RBM, Autoencoder, and GAN-based learning methods as unsupervised learning.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.889-899
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• 2017

Various efforts and technical development for integrating the ICT technologies to the area of special needs education have been continuing. In this paper we have studied and implemented various ICT-based disability evaluation websites and mobile applications for special needs education and also verified their usefulness from the field test at disability schools. The valuer can access the websites and mobile applications for autistic behavior or learning disability evaluation at the any places and by any devices such as laptop, PC, smartphone and tablet PC. And all the evalation results are stored into and managed at the server database and shared with websites and mobile applications to integrate together easily. From the study about disability evaluation and implementation results we have a confidence that they will be useful to support the seamless evaluation and the continuous monitoring services for the disabled at the special needs education fields.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.357-359
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• 2023

This paper proposes a hybrid recommendation system (RS) model that overcomes the limitations of traditional approaches such as data sparsity, cold start, and scalability by combining collaborative filtering and context-aware techniques. The objective of this model is to enhance the accuracy of recommendations and provide personalized suggestions by leveraging the strengths of collaborative filtering and incorporating user context features to capture their preferences and behavior more effectively. The approach utilizes a novel method that combines contextual attributes with the original user-item rating matrix of CF-based algorithms. Furthermore, we integrate k-mean++ clustering to group users with similar preferences and finally recommend items that have highly rated by other users in the same cluster. The process of partitioning is the use of the rating matrix into clusters based on contextual information offers several advantages. First, it bypasses of the computations over the entire data, reducing runtime and improving scalability. Second, the partitioned clusters hold similar ratings, which can produce greater impacts on each other, leading to more accurate recommendations and providing flexibility in the clustering process. keywords: Context-aware Recommendation, Collaborative Filtering, Kmean++ Clustering.

• Journal of the Korean Geotechnical Society
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• v.39 no.10
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• pp.27-39
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• 2023

To effectively manage flood risk, it is crucial to assess the stability of flood defense structures like levees under extreme flood conditions. This study focuses on the time-dependent probabilistic assessment of embankment slope stability when subjected to rapid water level drops. We integrate seepage analysis results from finite element analysis with slope stability analysis and employ Monte Carlo simulations to investigate the time-dependent behavior of the slope during rapid drawdown. The resulting probability of failure is used to develop fragility curves for the levee slope. Notably, the probability of slope failure remains low up to a specific water level, sharply increasing beyond that threshold. Furthermore, the fragility curves are strongly influenced by the rate of drawdown, which is determined through hydraulic analysis based on flood scenarios. Climate change has a significant impact on the stability of the water-side slope of the embankment due to water level fluctuations.

• Smart Structures and Systems
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• v.32 no.5
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• pp.319-338
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• 2023

The study presents a new hybrid data-driven method by combining radial basis functions neural networks (RBF-NN) with the Jaya algorithm (JA) to provide effective structural health monitoring of arch dams. The novelty of this approach lies in that only one user-defined parameter is required and thus can increase its effectiveness and efficiency, as compared to other machine learning techniques that often require processing a large amount of training and testing model parameters and hyper-parameters, with high time-consuming. This approach seeks rapid damage detection in arch dams under dynamic conditions, to prevent potential disasters, by utilizing the RBF-NNN to seamlessly integrate the dynamic elastic modulus (DEM) and modal parameters (such as natural frequency and mode shape) as damage indicators. To determine the dynamic characteristics of the arch dam, the JA sequentially optimizes an objective function rooted in vibration-based data sets. Two case studies of hyperbolic concrete arch dams were carefully designed using finite element simulation to demonstrate the effectiveness of the RBF-NN model, in conjunction with the Jaya algorithm. The testing results demonstrated that the proposed methods could exhibit significant computational time-savings, while effectively detecting damage in arch dam structures with complex nonlinearities. Furthermore, despite training data contaminated with a high level of noise, the RBF-NN and JA fusion remained the robustness, with high accuracy.

• Journal of the Korean Geotechnical Society
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• v.30 no.1
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• pp.37-47
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• 2014

Unsaturated hydraulic conductivity (HC) is integrated theoretically from soil water retention curves (SWRC) by Mualem capillary model, but the prediction of HC is extremely sensitive to small variation of matric suction near saturation. Near saturation, the Mualem HC based on smooth SWRC decreases abruptly and has problems in the reliability of hydraulic behavior and the stability of numerical solutions. To improve van Genuchten-Mualem (VGM) HC, the van Genuchten SWRC model is modified within range of low matric suction (arbitrary air entry pressure). At an arbitrary air entry pressure, the VG SWRC is linearized in log scale until full saturation. The modified VG SWRC does not affect the fit of actual retention behavior and either the parameters of original VG SWRC fit. Using the modified VG SWRC, the VGM HC is modified to integrate for each interval decomposed by arbitrary air entry pressure. An analytical solution on modified VGM HC is proposed each interval, to protect the rapid change in HC near saturation. For silty soils, VGM models of HC function underestimate the unsaturated permeability characteristics and especially show rapid reduction near saturation. The modified VGM model predicts more accurate HC functions for Korean weathered soils. Furthermore, near saturation, the saturated HC is conserved by the modified VGM model. After 2-D infiltration analysis of an actual slope, the hydraulic behaviors are compared for VGM and the modified models. The prediction by the proposed model conserved the convergence of solutions on various rainfall conditions. However, the solution by VGM model did not converge since the conductivity near saturation reduced abruptly for heavy rainfall condition. Using VGM model, the factor of safety is overestimated in both initial and final stage during heavy rainfall. Stability analysis based on infiltration analysis could simulate the actual slope failure by the proposed model on HC.