• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.1
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• pp.114-120
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• 2010

Optimization of the turning process has been concentrated on the selection of the optimal cutting parameters, such as cutting speed, feed rate and depth of cut. However, optimization of the cutting parameters does not necessarily guarantee the maximum profit. For the maximization of the profit, parameters other than cutting parameters have to be taken care of. In this study, 8 price-related parameters were considered to maximize the profit of the product. Regression equations obtained from RSM technique to relate the cutting parameters and maximum cutting volume with a given insert were used. The experiments with four combinations of cutting inserts and material were executed to compare the results that made the profit and cutting volume maximized. The results showed that the cutting parameters for volume and profit maximization were totally different. Contrary to our intuition, global optimization was achieved when the number of inserts change was larger than those for volume maximization. It is attributed to the faster cutting velocity, which decreases processing time and increasing the number of tool used and the total tool changing time.

• Journal of Environmental Science International
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• v.26 no.2
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• pp.249-256
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• 2017

In this study, we evaluated the potential of 70% ethanol extract from Persicaria nepalensis (PNE) as a cosmetic ingredient by primary skin irritation, ocular irritation, and maximization tests for delayed hypersensitivity in New Zealand white rabbits and Hartley guinea pig. Skin safety study was performed to evaluate the potential toxicity of PNE using the primary irritation test. In the primary irritation test, 50% PNE was applied to the skin, and no adverse reactions such as erythema and edema were observed at the intact skin sites. Therefore, PNE was classified as a practically non-irritating material based on a primary irritation index of "0.0.". In the ocular irritation test, the 50% PNE applied did not show any adverse reactions in the different parts of rabbit eyes, including the cornea, iris, and conjunctiva. Thus, PNE was classified as a practically non-irritating material based on an acute ocular irritation index of "0.0.". Skin sensitization was tested by the Guinea Pig Maximization Test (GPMT) and Freund's Complete Adjuvant (FCA) using an intradermal injection of 10% PNE. Edema and erythema were not observed 24 and 48 h after the topical application of PNE in skin sensitization test, which exhibited a sensitization score of "0.0.". Therefore, it can be suggested that P. nepalensis could be used as potential candidates for cosmoceutical ingredients, without any major side effects.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.57-64
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• 2019

We consider the D2D sum utility maximization in the cellular system. D2D links reuse the uplink resource of cellular system. This reuse may cause severe interference to cellular users. To protect the cellular users, interference limit from the D2D links is required. In this setting, D2D sum utility maximization problem is investigated. Each D2D link has limited transmit power budget. Because optimum solution may require global information between links and computational complexity, we propose the distributed algorithm which only require the local information from each D2D link and simple broadcasting. Simulation results are provided to verify the performance of the proposed algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.335-342
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• 2016

When dynamics changes occurred in an existing Bayesian Network (BN), the related parameters embedding on the BN have to be updated to new parameters adapting to changed patterns. In this case, these parameters have to be updated with the consideration of the causalities in the BN. This research suggests a framework for updating parameters dynamically using Expectation Maximization (EM) algorithm and Harmony Search (HS) algorithm among several Meta-Heuristics techniques. While EM is an effective algorithm for estimating hidden parameters, it has a limitation that the generated solution converges a local optimum in usual. In order to overcome the limitation, this paper applies HS for tracking the global optimum values of Maximum Likelihood Estimators (MLE) of parameters. The proposed method suggests a learning and propagation framework of BN with dynamic changes for overcoming disadvantages of EM algorithm and converging a global optimum value of MLE of parameters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5B
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• pp.295-303
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• 2007

An algorithm is proposed to seek a local optimal solution of the network utility maximization problem in a wireless mesh network, where the architecture being considered is an infrastructure/backbone wireless mesh network. The objective is to achieve proportional fairness amongst the end-to-end flows in wireless mesh networks. In order to establish the communication constraints of the flow rates in the network utility maximization problem, we have presented necessary and sufficient conditions for the achievability of the flow rates. Since wireless mesh networks are generally considered as a type of ad hoc networks, similarly as in wireless multi-hop network, the network utility maximization problem in wireless mesh network is a nonlinear nonconvex programming problem. Besides, the gateway/bridge functionalities in mesh routers enable the integration of wireless mesh networks with various existing wireless networks. Thus, the rate optimization problem in wireless mesh networks is more complex than in wireless multi-hop networks.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.4
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• pp.234-239
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• 2003

In recent decades, many countries have introduced competition in the electricity industry. Now, unit commitment becomes not a problem to be solved by a monopoly company but the one to be tackled by each generation company(GENCO). Its aim has been altered from the global cost minimization to the each GENCO's profit maximization. In this paper, the author proposes the scheme of unit commitment of a GENCO to maximize profit considering the uncertainty of market clearing price. The type of the assumed market is a uniform price market. A genetic algorithm is used for the maximization of the profit.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4357-4378
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• 2017

In cooperative multi-relay networks, the relay nodes which are selected are very important to the system performance. How to choose the best cooperative relay nodes is an optimization problem. In this paper, multi-relay selection schemes which consider either single objective or multi-objective are proposed based on evolutionary algorithms. Firstly, the single objective optimization problems of multi-relay selection considering signal to noise ratio (SNR) or power efficiency maximization are solved based on the quantum bee colony optimization (QBCO). Then the multi-objective optimization problems of multi-relay selection considering SNR maximization and power consumption minimization (two contradictive objectives) or SNR maximization and power efficiency maximization (also two contradictive objectives) are solved based on non-dominated sorting quantum bee colony optimization (NSQBCO), which can obtain the Pareto front solutions considering two contradictive objectives simultaneously. Simulation results show that QBCO based multi-relay selection schemes have the ability to search global optimal solution compared with other multi-relay selection schemes in literature, while NSQBCO based multi-relay selection schemes can obtain the same Pareto front solutions as exhaustive search when the number of relays is not very large. When the number of relays is very large, exhaustive search cannot be used due to complexity but NSQBCO based multi-relay selection schemes can still be used to solve the problems. All simulation results demonstrate the effectiveness of the proposed schemes.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.569-572
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• 1999

In this paper we present a color image segmentation algorithm based on statistical models. A novel deterministic annealing Expectation Maximization(EM) formula is derived to estimate the parameters of the Gaussian Mixture Model(GMM) which represents the multi-colored objects statistically. The experimental results show that the proposed deterministic annealing EM is a global optimal solution for the ML parameter estimation and the image field is segmented efficiently by using the parameter estimates.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.797-807
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• 2016

The discussion in this paper aims to introduce an approach to detect drowsiness with Android based smartphones using the OpenCV platform tools. OpenCV for Android actually provides powerful tools for real-time body's parts tracking. We discuss here about the maximization of the accuracy in real-time eye tracking. Then we try to develop an approach for detecting eye blink by analyzing the structure and color variations of human eyes. Finally, we introduce a time variable to capture drowsiness.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.161-169
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• 2022

With the development of mobile devices and global positioning systems, various location-based services can be utilized, which collects user's location information and provides services based on it. In this process, there is a risk of personal sensitive information being exposed to the outside, and thus Geo-indistinguishability (Geo-Ind), which protect location privacy of LBS users by perturbing their true location, is widely used. However, owing to the data perturbation mechanism of Geo-Ind, it is hard to accurately obtain the density distribution of LBS users from the collection of perturbed location data. Thus, in this paper, we aim to develop a novel method which enables to effectively compute the user density distribution from perturbed location dataset collected under Geo-Ind. In particular, the proposed method leverages Expectation-Maximization(EM) algorithm to precisely estimate the density disribution of LBS users from perturbed location dataset. Experimental results on real world datasets show that our proposed method achieves significantly better performance than a baseline approach.