• Korean Journal of Food Science and Technology
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• v.40 no.4
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• pp.406-411
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• 2008

This study was conducted to examine the quality enhancement of fermented soybean pastes (cheonggukjang) using microorganisms with high enzyme activities and proper experimental design. The microorganisms for soybean paste fermentation were selected from a specific area of Gyeonggi and were idenlified by 16S rDNA sequence analysis. To prepare the cheonggukjang, an optimum mixing ratio of selected microorganisms was determined using contour plots and numerical optimization methods. A total of 39 microorganisms were isolated from the soybean paste, consisting primarily of Bacillus subtilis and Bacillus licheniformis, and no mold was found. Three microorganisms showing high enzyme activities were selected and used to formulate an optimum mixing ratio for cheonggukjang preparation. Based on levels of amino-nitrogen, ammonium-nitrogen, antioxidant activity values, and sensory preference results, the optimum mixing ratio of 50% of Bacillus sp. SC-1 and 50% SC-3 was suggested for the manufacture of high quality of cheonggukjang.

• Journal of Korea Multimedia Society
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• v.10 no.1
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• pp.13-25
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• 2007

A cache is used for optimization of query forwarding in the Grid database. To decrease network transmission cost, frequently used data is cached from meta database. Existing cache management method has a unbalanced resource problem, because it doesn't manage replicated data in each node. Also, it increases network cost by cache misses. In the case of data modification, if cache is not updated, queries can be transferred to wrong nodes and it can be occurred others nodes which have same cache. Therefore, it is necessary to solve the problems of existing method that are using unbalanced resource of replica and increasing network cost by cache misses. In this paper, cache management method for query forwarding optimization is proposed. The proposed method manages caches through cache manager. To optimize query forwarding, the cache manager makes caching data from lower loaded replicated node. The query processing cost and the network cost will decrease for the reducing of wrong query forwarding. The performance evaluation shows that proposed method performs better than the existing method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.8
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• pp.1393-1400
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• 2006

This paper optimizes the access probabilities (APs) in a network resource allocation scheme based on access probabilities in order that the waiting time and the blocking probability are minimized under the given constraints, and obtains its performance. In order to optimize APs, an infinite number of balance equations is reduced to a finite number of balance equations by applying Neuts matrix geometric method. And the nonlinear programming problem is converted into a linear programming problem. As a numerical example, the performance measures of waiting time and blocking probability for optimal access probabilities and the maximum utilization under the given constraints are obtained. And it is shown that the scheme with optimal APs gives more performance build-up than the strategy without optimization.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.2
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• pp.33-40
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• 2018

There are lots of literature about connected car system from industry and academia. The connected car is a smart car integrated with IT technology that is connected to people, vehicles and traffic management systems. It is important to V2I (vehicle to infrastructure) communication which is the connection between the vehicle and the infrastructure. CIM (cooperative intersection management) is a device to manage the communication between vehicle and infrastructure. In this paper, we analyze two intelligent vehicle control methods using CIM at non-signalized intersections. In the first method, a vehicle to pass through intersection needs to reserve a resource of intersection. In the second method, trajectory patterns on pre-planned vehicles are classified to pass through intersection. We analyze case studies of two methods to be implemented by DP(dynamic programming) and ACO(ant colony optimization) algorithms. The methods can be reasonably improved by placing importance on vehicles or controlling speeds of vehicles.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.9
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• pp.1300-1305
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• 2014

In this paper, we suggest an optimization method which can save about 5[%] of the cost though the optimizing of configuration and capacity for the facility. To achieve this goal, we compared the design data of the power, motor and drive system with the actual operation data of the plate mill plant in K-Steelworks. Therefore we measured the actual loading data by facilities considering the operating conditions of the plate mill plant in K-Steelworks, after that analyzed these data. In addition, we review the optimal capacity for transformer, switchgear and drive, and also reconfigured the electrical room and power single line diagram through the validation of motor data by equipment and the confirmation of process data considering the load characteristics. Consequently, the optimization method of capacity for the facilities shall have effectiveness in building new plate mill plant to further reduce costs at future.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.2
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• pp.173-181
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• 2001

This paper presents an artificial life algorithm which is remarkable in the area of engineering for functions optimization. As artificial life organisms have a sensing system, they can find the resource which they want to find and metabolize. And the characteristics of artificial life are emergence and dynamic interaction with environment. In other words, the micro-interaction with each other in the artificial lifes group results in emergent colonization in the whole system. In this paper, therefore, artificial life algorithm by using above characteristics is employed into functions optimization. The optimizing ability and convergent characteristics of this proposed algorithm is verified by using three test functions. The numerical results also show that the proposed algorithm is superior to genetic algorithms and immune algorithms for the multimodal functions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.3
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• pp.149-155
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• 2005

In this paper, we optimize simulation model of a manufacturing system using the real-coded genetic algorithm. Because the manufacturing system expressed by simulation model has stochastic process, the objective functions such as the throughput of a manufacturing system or the resource utilization are not optimized by simulation itself. So, in order to solve it, we apply optimization methods such as a genetic algorithm to simulation method. Especially, the genetic algorithm is known to more effective method than other methods to find global optimum, because the genetic algorithm uses entity pools to find the optimum. In this study, therefore, we apply the real-coded genetic algorithm to simulation optimization of a manufacturing system, which is known to more effective method than the binary-coded genetic algorithm when we optimize the constraint problems. We use the reproduction operator of the applied real-coded genetic algorithm as technique of the remainder stochastic sample with replacement and the crossover operator as the technique of simple crossover. Also, we use the mutation operator as the technique of the dynamic mutation that configures the searching area with generations.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.615-629
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• 2021

With the development of mobile edge computing, how to utilize the computing power of edge computing to effectively and efficiently offload data and to compute offloading is of great research value. This paper studies the computation offloading problem of multi-user and multi-server in mobile edge computing. Firstly, in order to minimize system energy consumption, the problem is modeled by considering the joint optimization of the offloading strategy and the wireless and computing resource allocation in a multi-user and multi-server scenario. Additionally, this paper explores the computation offloading scheme to optimize the overall cost. As the centralized optimization method is an NP problem, the game method is used to achieve effective computation offloading in a distributed manner. The decision problem of distributed computation offloading between the mobile equipment is modeled as a multi-user computation offloading game. There is a Nash equilibrium in this game, and it can be achieved by a limited number of iterations. Then, we propose a distributed computation offloading algorithm, which first calculates offloading weights, and then distributedly iterates by the time slot to update the computation offloading decision. Finally, the algorithm is verified by simulation experiments. Simulation results show that our proposed algorithm can achieve the balance by a limited number of iterations. At the same time, the algorithm outperforms several other advanced computation offloading algorithms in terms of the number of users and overall overheads for beneficial decision-making.

• Steel and Composite Structures
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• v.51 no.4
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• pp.363-375
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• 2024

Within the optimization field, addressing the intricate posed by fluidic pressure loads on functionally graded structures with frequency-related designs is a kind of complex design challenges. This paper thus introduces an innovative density-based topology optimization strategy for frequency-constraint functionally graded structures incorporating Darcy's law and a drainage term. It ensures consistent treatment of design-dependent fluidic pressure loads to frequency-related structures that dynamically adjust their direction and location throughout the design evolution. The porosity of each finite element, coupled with its drainage term, is intricately linked to its density variable through a Heaviside function, ensuring a seamless transition between solid and void phases. A design-specific pressure field is established by employing Darcy's law, and the associated partial differential equation is solved using finite element analysis. Subsequently, this pressure field is utilized to ascertain consistent nodal loads, enabling an efficient evaluation of load sensitivities through the adjoint-variable method. Moreover, this novel approach incorporates load-dependent structures, frequency constraints, functionally graded material models, and polygonal meshes, expanding its applicability and flexibility to a broader range of engineering scenarios. The proposed methodology's effectiveness and robustness are demonstrated through numerical examples, including fluidic pressure-loaded frequency-constraint structures undergoing small deformations, where compliance is minimized for structures optimized within specified resource constraints.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.6
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• pp.440-448
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• 2022

Recently, due to the introduction of distributed energy resources, the optimal resource allocation problem of the power network is more and more important, and the distributed resource allocation method is required to process huge amount of data in large-scale power networks. In the optimal resource allocation problem, many studies have been conducted on the case when the supply-demand balance is satisfied due to the limitation of the generation capacity of each generator, but the studies considering the supply-demand imbalance, that total demand exceeds the maximum generation capacity, have rarely been considered. In this paper, we propose the consensus-based distributed algorithm for the optimal resource allocation of power network considering the supply-demand imbalance condition as well as the supply-demand balance condition. The proposed distributed algorithm is designed to allocate the optimal resources when the supply-demand balance condition is satisfied, and to measure the amount of required resources when the supply-demand is imbalanced. Finally, we conduct the simulations to verify the performance of the proposed algorithm.