• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.175-184
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• 2008

Uncertainties are unavoidable in engineering applications. In this paper we propose an alpha reliable multi-variable network design problem under demand uncertainty. In order to decide the optimal capacity enhancement, three performance measures based on 3E(Efficiency, Equity, and Environmental) are considered. The objective is to minimize the total budget required to satisfy alpha reliability constraint of total travel time, equity ratio, and total emission, while considering the route choice behavior of network users. The problem is formulated as the chance-constrained model for application of alpha confidence level and solved as a lexicographic optimization problem to consider the multi-variable. A simulation-based genetic algorithm procedure is developed to solve this complex network design problem(NDP). A simple numerical example ispresented to illustrate the features of the proposed NDP model.

• Korean journal of applied entomology
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• v.31 no.3
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• pp.314-327
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• 1992

Insecticide resistance is a serious is a serious threat to IPM, resulting in various adverse effects not to mention the loss of yield in agriculture. One approach to counter the problem is the disruption of resistance mechanisms. This can be achieved by (1) compounds which show a negative correlation with resistance at the site of action, (2) specific metabolic inhibitors which serve as synergists, or (3) a certain combination of two insecticides producing a joint action. This approach, however, requires certain precautions for the side effects may cause an increase in toxicity to mammals. Owing to the recent advances in theoretical studies on resistance management employing computer simulation and mathematical models, a few principles to reduce the risk of development of resistance have been clarified. They are helpful in designing operational strategies with regard to, for instance, insecticide doses to be applied, mode of application, and choice and nature of the insecticide(s) to be used. For restoration of insecticide susceptibility of a resistant population, reintroduction of susceptible individuals to the resistant population is feasible when certain conditions are met. Natural enemies which developed resistance to insecticides can be an important component of IPM as has been shown in the pest management in apple orchards. After all, the implementation of a successful resistance management program depends upon cooperation between different sigments of the agricutural community. Although resistance is a preadaptive phenomenon, in some cases spontaneous loss of resistance does occur without contamination by susceptible individuals. The instability of resistance in these insects implies the possible existence of a switch machanism controlling the expression of resistance gene(s). Elucidation of such a mechanism may eventually provide us with a new technical approach with which we can combat the problem of insecticide resistance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.1
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• pp.82-91
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• 2009

Routing (or path selection) is one of the key issues of multi-hop relay networks such as the IEEE 802.16j. Moreover, the allocation of appropriate resource such as bandwidth should not only be made in accordance with the paths selected, but the utilization of radio resource of an entire cell should also be maximized. Due to this interdependency between the problems of resource allocation and routing, it is desired these two problems are addressed simultaneously. In this paper, we propose a joint resource allocation and routing scheme for an OFDMA-based multi-hop cellular system. This scheme uses a polynomial time heuristic algorithm called Multi-Dimensional Multi-choice Knapsack Problem (MMKP) in order to find an approximate solution maximizing the total downlink throughput. In the simulation results, we show that the proposed scheme finds a sub-optimal solution which is superior to a link quality-based routing scheme, but slightly worse than the optimal solution.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.9
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• pp.7-13
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• 2010

In this paper, we proposed a processor architecture that is suitable for next generation embedded applications, especially for personal information devices such as smart phones, tablet PC. Latest high performance embedded processors are developed to achieve high clock speed. Because increasing performance makes design more difficult and induces large overhead, architectural evolution in embedded processor field is necessary. Among more enhanced processor types, out-of-order superscalar cannot be a candidate for embedded applications due to its excessive complexity and relatively low performance gain compared to its overhead. Therefore, new architecture with moderate complexity must be designed. In this paper, we developed a low-cost SMT architecture model and compared its performance to other architectures including scalar, superscalar and multiprocessor. Because current personal information devices have a tendency to execute multiple tasks simultaneously, SMT or CMP can be a good choice. And our simulation result shows that the efficiency of SMT is the best among the architectures considered.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.08a
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• pp.175-183
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• 2004

In hot strip rolling, a capability for precisely predicting roll force is crucial for sound process control. In the past, on-line prediction models have been developed mostly on the basis of Orowan's theory and its variation. However, the range of process conditions in which desired prediction accuracy could be achieved was rather limited, mainly due to many simplifying assumptions inherent to Orowan's theory. As far as the prediction accuracy is concerned, a rigorously formulated finite element(FE) process model is perhaps the best choice. However, a FE process model in general requires a large CPU time, rendering itself inadequate for on-line purpose. In this report, we present a FE-based on-line prediction model applicable to precision process control in a finishing mill(FM). Described was an integrated FE process model capable of revealing the detailed aspects of the thermo-mechanical behavior of the roll-strip system. Using the FE process model, a series of process simulation was conducted to investigate the effect of diverse process variables on some selected non-dimensional parameters characterizing the thermo-mechanical behavior of the strip. Then, it was shown that an on-line model for the prediction of roll force could be derived on the basis of these parameters. The prediction accuracy of the proposed model was examined through comparison with measurements from the hot strip mill.

• Journal of Environmental Science International
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• v.25 no.1
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• pp.67-83
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• 2016

In order to improve the prediction of the regional air quality modeling in the Seoul metropolitan area, a sensitivity analysis using two PBL and microphysics (MP) options of the WRF model was performed during four seasons. The results from four sets of the simulation experiments (EXPs) showed that meteorological variables (especially wind field) were highly sensitive to the choice of PBL options (YSU or MYJ) and no significant differences were found depending on MP options (WDM6 or Morrison) regardless of specific time periods, i.e. day and night, during four seasons. Consequently, the EXPs being composed of YSU PBL option were identified to produce better results for meteorological elements (especially wind field) regardless of seasons. On the other hand, the accuracy of all simulations for summer and winter was somewhat lower than those for spring and autumn and the effect according to physics options was highly volatile by geographical characteristics of the observation site.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.2972-2991
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• 2016

WLAN is the best choice in the place where complex network is hard to set up. Intelligent terminals are more and more assembled in some areas now. However, according to IEEE 802.11n/802.11ac, the access-point (AP) can only serve one user at a single frequency channel. The spectrum efficiency urgently needs to be improved. In theory, AP with multi-antenna can serve multiple users if these users do not interfere with each other. In this paper, we propose a user clustering scheme that could achieve multi-user selection through the mutual cooperation among users. We focus on two points, one is to achieve multi-user communication with multiple antennas technique at a single frequency channel, and the other one is to use a way of distributed users' collaboration to determine the multi-user selection for user clustering. Firstly, we use the CSMA/CA protocol to select the first user, and then we set this user as a source node using users' cooperation to search other proper users. With the help of the users' broadcast cooperation, we can search and select other appropriate user (while the number of access users is limited by the number of antennas in AP) to access AP with the first user simultaneously. In the network node searching, we propose a maximum degree energy routing searching algorithm, which uses the shortest time and traverses as many users as possible. We carried out the necessary analysis and simulation to prove the feasibility of the scheme. We hope this work may provide a new idea for the solution of the multiple access problem.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.33-43
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• 2002

Various kinds of estimation methods have been developed for imputation of categorical missing data. They include category method, logistic regression, and association rule. In this study, we propose two fusions algorithms based on both neural network and voting scheme that combine the results of individual imputation methods. A Mont-Carlo simulation is used to compare the performance of these methods. Five factors used to simulate the missing data pattern are (1) input-output function, (2) data size, (3) noise of input-output function (4) proportion of missing data, and (5) pattern of missing data. Experimental study results indicate the following: when the data size is small and missing data proportion is large, modal category method, association rule, and neural network based fusion have better performances than the other methods. However, when the data size is small and correlation between input and missing output is strong, logistic regression and neural network barred fusion algorithm appear better than the others. When data size is large with low missing data proportion, a large noise, and strong correlation between input and missing output, neural networks based fusion algorithm turns out to be the best choice.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.8
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• pp.774-780
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• 2010

This paper deals with the choice of guidance gain for the time-to-go polynomial (POLY) guidance law when the acceleration limit is existed. POLY is derived based on the assumption that guidance commands are formed by a time-to-go polynomial function. The main characteristic of POLY is that any positive values can be used for its guidance gain. For this reason, it is ambiguous to choose a proper guidance gain. To relieve this difficulty, we firstly derive the closed-form solution of acceleration command and figure out the relationship between the maximum acceleration and guidance gain. From this analysis, we provide a guideline for choosing a guidance gain which satisfies the desired acceleration limit. Finally, the proposed method is demonstrated by simulation study.

• The Journal of Engineering Geology
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• v.25 no.3
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• pp.369-376
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• 2015

Numerical models simulating groundwater flow are often used to estimate groundwater discharge into a tunnel. In designing numerical models, the grid size should be carefully considered to ensure that groundwater discharge is accurately predicted. However, several recent studies have employed various grid sizes without providing an adequate explanation for their choice. This paper suggests the optimal grid size based on a comparison of numerical models with analytical solutions. Discrepancies between numerical and analytical solutions result from the effect of model boundaries as well as the grid size. By nullifying boundary effects, the errors solely associated with the grid size could be analyzed. The optimal grid size yielding accurate numerical solutions was thus derived. The suggested relationship between tunnel radius and optimal grid size is analogous to the relationship between the equivalent well block radius and grid size.