• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.19 no.7
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• pp.500-511
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• 2007

The Optimal solutions of the design variables in internally finned tubes have been obtained for three-dimensional periodically fully developed turbulent flow and heat transfer. For a trapezoidal fin profile, performances of the heat exchanger are determined by considering the heat transfer rate and pressure drop, simultaneously, that are interdependent quantities. Therefore, Pareto frontier sets of a heat exchanger can be acquired by integrating CFD and a multi-objective optimization technique. The optimal values of fin widths $(d_1,\;d_2)$, fin height(h) and helix angle$(\gamma)$ are numerical1y obtained by minimizing the pressure loss and maximizing the heat transfer rate within ranges of $d_1=0.5\sim1.5mm$, $d_2=0.5\sim1.5mm$, $h=0.5\sim1.5mm$, and $\gamma=0\sim20^{\circ}$. For this, a general CFD code and a global genetic algorithm(GA) are used. The Pareto sets of the optimal solutions can be acquired after $30^{th}$ generation.

• Industry Promotion Research
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• v.3 no.1
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• pp.61-72
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• 2018

This study is to find out solutions to the problems of multicultural families which are becoming social problems. The results of this study are as follows : First, it is necessary to change government and public perception about multicultural families and society. Second, it is necessary to consider expanding and operating a counseling center for the support of multicultural families' human rights violations, labor issues, and life problems. Third, the efforts of related organizations and organizations including the government to diversify contents, subjects and programs of multicultural education are needed. Fourth, there is a need for a separate district development such as multicultural special zones.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.2
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• pp.48-55
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• 2010

Reliability has been considered as a one of the major design measures in various industrial and military systems. The main objective is to suggest a mathematical programming model and a hybrid parallel genetic algorithm(HPGA) for the problem that determines the optimal component reliability to maximize the system reliability under cost constraint in this study. Reliability optimization problem has been known as a NP-hard problem and normally formulated as a mixed binary integer programming model. Component structure, reliability, and cost were computed by using HPGA and compared with the results of existing meta-heuristic such as Ant Colony Optimization(ACO), Simulated Annealing(SA), Tabu Search(TS) and Reoptimization Procedure. The global optimal solutions of each problem are obtained by using CPLEX 11.1. The results of suggested algorithm give the same or better solutions than existing algorithms, because the suggested algorithm could paratactically evolved by operating several sub-populations and improving solution through swap and 2-opt processes.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.12
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• pp.935-942
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• 2002

When designing fluid mounts, design parameters can be varied in order to obtain a desired notch frequency and notch depth. The notch frequency is a function of the mount parameters and is typically selected by the designer to occur at the vibration disturbance frequency. Since the process of choosing these parameters can involve some trial and error, it seems to be a great application for obtaining optimal performance of the mount. Many combinations of parameters are possible to give us the desired notch frequency, but the question is which combination provides the lowest depth. Therefore. an automatic optimal technique is needed to optimize the performance of the fluid mount. In this study. the enhanced genetic algorithm (EGA) is applied to minimizing transmissibility of a fluid mount at the desired notch frequency, and at the notch and resonant frequencies. The EGA is modified genetic algorithm to search global and local optimal solutions of multi-modal function optimization. Furthermore. to reduce the searching time as compare to conventional genetic algorithm and Increase the precision of the solutions, the modified simplex method is combined with the algorithm. The results show that the performance of the optimized mount by using the hybrid algorithm is better than that of the conventional fluid mount.

• ETRI Journal
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• v.43 no.2
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• pp.260-271
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• 2021

This paper addresses Very large-scale integration (VLSI) placement optimization, which is important because of the rapid development of VLSI design technologies. The goal of this study is to develop a hybrid algorithm for VLSI placement. The proposed algorithm includes a sequential combination of a genetic algorithm and an evolutionary algorithm. It is commonly known that local search algorithms, such as random forest, hill climbing, and variable neighborhoods, can be effectively applied to NP-hard problem-solving. They provide improved solutions, which are obtained after a global search. The scientific novelty of this research is based on the development of systems, principles, and methods for creating a hybrid (combined) placement algorithm. The principal difference in the proposed algorithm is that it obtains a set of alternative solutions in parallel and then selects the best one. Nonstandard genetic operators, based on problem knowledge, are used in the proposed algorithm. An investigational study shows an objective-function improvement of 13%. The time complexity of the hybrid placement algorithm is O(N2).

• Structural Engineering and Mechanics
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• v.69 no.6
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• pp.615-626
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• 2019

The 3-noded metric Timoshenko beam element with an offset of the internal node from the element centre is used here to demonstrate the best-fit paradigm using function space formulation under locking and mesh distortion. The best-fit paradigm follows from the projection theorem describing finite element analysis which shows that the stresses computed by the displacement finite element procedure are the best approximation of the true stresses at an element level as well as global level. In this paper, closed form best-fit solutions are arrived for the 3-noded Timoshenko beam element through function space formulation by combining field consistency requirements and distortion effects for the element modelled in metric Cartesian coordinates. It is demonstrated through projection theorems how lock-free best-fit solutions are arrived even under mesh distortion by using a consistent definition for the shear strain field. It is shown how the field consistency enforced finite element solution differ from the best-fit solution by an extraneous response resulting from an additional spurious force vector. However, it can be observed that when the extraneous forces vanish fortuitously, the field consistent solution coincides with the best-fit strain solution.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.527-531
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• 2015

With the mounting concerns over environmental issues, green construction is gaining a place in the global construction industry. However, rare research has been conducted to analyze green construction projects, especially in the aspect of project schedule performance. As a result, this study aims to investigate the degree of project delay in green building construction, analyze the factors affecting schedule delay of green building projects, and finally provide recommendations to improve schedule performance of green building project. To achieve the objectives, a comprehensive literature review was carried out, followed by a survey conducted with 30 companies that provided data from 220 traditional and 96 green building projects. The analysis of the responses identified that 15.9% of the traditional building projects were delayed while 32.3% of the green building projects were completed behind schedule. Furthermore, the amount of the delays in green building projects was an average of 4.8% of their planned schedule. The top 5 critical factors that can cause delay in green building projects were identified as: (1) speed of decision-making by clients; (2) speed of decision-making involving all project teams; (3) communication/coordination between key parties; (4) level of experience of consultants; and (5) difficulties in contractors' project financing. Lastly, a list of recommendations was introduced, aiming to reduce schedule delay in green building construction projects based on the observations. This study will serve as s a base for further research on the enhancement of green building project schedule performance.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.44-55
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• 2024

High-utility itemset mining (HUIM) is a dominant technology that enables enterprises to make real-time decisions, including supply chain management, customer segmentation, and business analytics. However, classical support value-driven Apriori solutions are confined and unable to meet real-time enterprise demands, especially for large amounts of input data. This study introduces a groundbreaking model for top-N high utility itemset mining in real-time enterprise applications. Unlike traditional Apriori-based solutions, the proposed convolutional sequential embedding metrics-driven cosine-similarity-based multilayer perception learning model leverages global and contextual features, including semantic attributes, for enhanced top-N recommendations over sequential transactions. The MATLAB-based simulations of the model on diverse datasets, demonstrated an impressive precision (0.5632), mean absolute error (MAE) (0.7610), hit rate (HR)@K (0.5720), and normalized discounted cumulative gain (NDCG)@K (0.4268). The average MAE across different datasets and latent dimensions was 0.608. Additionally, the model achieved remarkable cumulative accuracy and precision of 97.94% and 97.04% in performance, respectively, surpassing existing state-of-the-art models. This affirms the robustness and effectiveness of the proposed model in real-time enterprise scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1198-1212
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• 2013

Network virtualization enables autonomous and heterogeneous Virtual Networks (VNs) to co-exist on a shared physical substrate. In a Network Virtualization Environment (NVE), the fact that individual VNs are underpinned by diverse naming mechanisms brings about an obvious challenge for transparent communication across multiple VN domains due to the complexity of uniquely identifying users. Existing solutions were mainly proposed compatible to Internet paradigm with little consideration of their applications in a virtualized environment. This calls for a scalable and efficient naming framework to enable consistent communication across a large user population (fixed or mobile) hosted by multiple VNs. This paper highlights the underlying technical requirements and presents a scalable Global Naming Framework (GNF), which (1) enables transparent communication across multiple VNs owned by the same or different SPs; (2) supports communication in the presence of dynamics induced from both VN and end users; and (3) greatly reduces the network operational complexity (space and time). The suggested approach is assessed through extensive simulation experiments for a range of network scenarios. The numerical result clearly verifies its effectiveness and scalability which enables its application in a large-scale NVE without significant deployment and management hurdles.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.22 no.1
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• pp.29-62
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• 2018

We investigate a class of HIV infection models with two kinds of target cells: $CD4^+$ T cells and macrophages. We incorporate three distributed time delays into the models. Moreover, we consider the effect of humoral immunity on the dynamical behavior of the HIV. The viruses are produced from four types of infected cells: short-lived infected $CD4^+$T cells, long-lived chronically infected $CD4^+$T cells, short-lived infected macrophages and long-lived chronically infected macrophages. The drug efficacy is assumed to be different for the two types of target cells. The HIV-target incidence rate is given by bilinear and saturation functional response while, for the third model, both HIV-target incidence rate and neutralization rate of viruses are given by nonlinear general functions. We show that the solutions of the proposed models are nonnegative and ultimately bounded. We derive two threshold parameters which fully determine the positivity and stability of the three steady states of the models. Using Lyapunov functionals, we established the global stability of the steady states of the models. The theoretical results are confirmed by numerical simulations.