• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.5
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• pp.186-194
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• 2006

Traffic accident involved with the vulnerable pedestrian is one of the significant concerns, which has higher possibility of fatality than any other accident types. Worldwide significant efforts have been made to establish a vehicle safety regulation, which is internationally agreed, in order to reduce pedestrian casualties in pedestrian-vehicle collisions. One of the key issues in deriving the regulation is how to effectively select the parameter values associated with the regulation. This study firstly develops a method to optimize parameter values. An optimizing problem in terms of maximizing safety benefits, which are life-saving effects by the regulation, is formulated. Extensive actual accident data analysis and simulations are conducted to establish several statistical models to be used in the proposed optimization procedure. A set of parameter values that can produce maximizing life-saving effects is presented as the outcome of this study. It is expected that the proposed method would play a significant role in determining parameters as a decision support tool toward ensuring better pedestrian safety.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.9
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• pp.1202-1209
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• 2018

This paper is concerned with the problem of setting controller's parameters when applying the intelligent PID (i-PID), which has recently been proposed and had many successful results, to the two-degree-of-freedom (2DoF) PID controller structure. Generally, the parameter settings of conventional PID controllers are known to be quite difficult and be dependent on the characteristics of the plants. In addition, it is less known how the two 2DoF parameters are set up for the improvement of transient characteristics. Here, we are going to present one of the criteria for parameter setting in the case of using a 2DoF i-PID, by evaluating the error signals to the set-point and disturbance. That is, we first, obtain parameters of i-PID by optimizing the disturbance responses, and then determine two parameters of 2DoF component through optimizing set-point response. The standard values of all parameters are calculated for the 7 types of test batches and rounded up as a table.

• Journal of the Korea Safety Management & Science
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• v.14 no.4
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• pp.177-184
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• 2012

Logistics cost of domestic company has been improved continuously and annually, it is still higher than other main comparative countries. So, in this study, as optimizing the logistic network of distribution, it was trying to find methods decreasing logistics cost and storage cost, which occupies 86% of logistics cost of companies. through the efficiency of transportation and delivery routing, it could be also possible to decrease the logistics cost. And, it is also checked to find the logistics cost could be decreased by 10% by optimizing the routes of transportation and delivery, improving the transportation mode, etc.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.83-90
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• 2010

The number of searched nodes and the computation time in an index should be minimized for optimizing the processing cost of the nearest neighbor query. The Measurement of search distance considered a circular location property of objects is required to accurately select the nodes which will be searched in the nearest neighbor query. In this paper, we propose the processing method of the nearest neighbor query be considered a circular location property of object where the search space consists of a circular domain and show its performance by experiments. The proposed method uses the circular minimum distance and the circular optimal distance which are the search measurements for optimizing the processing cost of the nearest neighbor query.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.04a
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• pp.98-98
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• 2019

This study was expand the use of Citrus madurensis (Citrofortunella microcarpa), which is a good source of skin whitening and antioxidants activation cosmetics. The goal was to provide cosmeceutical activity data about the extraction yield and total phenol of this calamondin orange by optimizing the focused high ultrasound(INEFU) and ultrasound extraction(UE) conditions. Under optimal extraction conditions, which consisted of 1800W for 45min and 500W for 45 min, 21.55 and 13.27 % (w/w) of the highest extractions yield and polyphenol contents were obtained. For the skin whitening activity, tyrosinase inhibitory activity was observed at 69.24 % in the INEFU extracts, which was ca. 18 % higher than that of the UE extracts (58.82 %). To reduce melanin production in Clone M-3 cells, 86.9 % melanin production was observed following the addition of control, WE(water extraction) relative to the control without a sample, and 81.2 and 78.9 % were found in the UE and INEFU conditions. The highest total phenol secretion was conclusively obtained under the optimal conditions and resulted in a significant improvement of the cosmetic activities of Citrus madurensis(Citrofortunella microcarpa) extracts.

• Structural Engineering and Mechanics
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• v.69 no.1
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• pp.21-31
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• 2019

Optimizing composite structures to exploit their maximum potential is a realistic application with promising returns. In this research, simultaneous maximization of the fundamental frequency and frequency separation between the first two modes by optimizing the fiber angles is considered. A high-fidelity design optimization methodology is developed by combining the high-accuracy of finite element method with iterative improvement capability of metaheuristic algorithms. Three powerful nature-inspired optimization algorithms viz. a genetic algorithm (GA), a particle swarm optimization (PSO) variant and a cuckoo search (CS) variant are used. Advanced memetic features are incorporated in the PSO and CS to form their respective variants-RPSOLC (repulsive particle swarm optimization with local search and chaotic perturbation) and CHP (co-evolutionary host-parasite). A comprehensive set of benchmark solutions on several new problems are reported. Statistical tests and comprehensive assessment of the predicted results show CHP comprehensively outperforms RPSOLC and GA, while RPSOLC has a little superiority over GA. Extensive simulations show that the on repeated trials of the same experiment, CHP has very low variability. About 50% fewer variations are seen in RPSOLC as compared to GA on repeated trials.

• Knowledge Management Research
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• v.20 no.3
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• pp.39-47
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• 2019

Response surface methodology (RSM) is a group of statistical modeling and optimization methods to improve the quality of design systematically in the quality engineering field. Its final goal is to identify the optimal setting of input variables optimizing a response. RSM is a kind of knowledge management tool since it studies a manufacturing or service process and extracts an important knowledge about it. In a real problem of RSM, it is a quite frequent situation that considers multiple responses simultaneously. To date, many approaches are proposed for solving (i.e., optimizing) a multi-response problem: process capability function approach, desirability function approach, loss function approach, and so on. The process capability function approach first estimates the mean and standard deviation models of each response. Then, it derives an individual process capability function for each response. The overall process capability function is obtained by aggregating the individual process capability function. The optimal setting is given by maximizing the overall process capability function. The existing process capability function methods usually use the arithmetic mean or geometric mean as an aggregation operator. However, these operators do not guarantee the Pareto optimality of their solution. Moreover, they may bring out an unacceptable result in terms of individual process capability function values. In this paper, we propose a maximin-based process capability function method which uses a maximin criterion as an aggregation operator. The proposed method is illustrated through a well-known multiresponse problem.

• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.27-33
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• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.4
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• pp.103-111
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• 2020

Perforated metal sheets are used as panels of facades for controlling environmental factors while ensuring user's visibility. Despite their functional potentials, only a specific direction of facades or an orientation of a building was considered in the relevant studies. This study proposed a design methodology for the perforated panel facades that reflects the location on the facades and the user's requirements. The optimization of quantitative and qualitative performance is achieved through communication between designers and users in a VR system. In optimizing quantitative performances, designers use machine learning techniques such as clustering and genetic algorithm to allocate optimal panels on the facades. In optimizing qualitative performances, through the VR system, users intervene in evaluating performances whose preferences are depending on them. The experiment using the office project showed that designers were able to make decisions based on clustering using GMM to optimize multiple quantitative performances. The gap between the target and final performance could be narrowed by limiting the types of perforated panels considering mass customization. In assessing visibility as a qualitative performance, users were able to participate in the design process using the VR system.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.183-186
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• 2013

Modern day despite technology advancements that manufacture a new generation of mobile devices with generous resources, the fact that they can offer only limited processing capacity still remains a painful experience. So far, a number of research studies have been carried out, trying to eliminate problems arising from shortcomings in the connection between thin clients and cloud networks, yet little have been found efficient. In this paper, we present a novel approach, taking advantage of collaboration of thin and thick clients, particularly aiming at optimizing data distribution by splitting data and utilizing cloud computing (CC) resources so that expected Quality-of-Service (QoS) requirements can be met. Moreover, we conduct simulations to evaluate our approach. Our results evaluation shows that our approach has better performance than existing approaches.