• Journal of the Korea Society of Computer and Information
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• v.19 no.5
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• pp.61-69
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• 2014

Collaborative filtering recommendation creates similar item subset or similar user subset based on user preference about items and predict user preference to particular item by using them. Thus, if preference matrix has low density, reliability of recommendation will be sharply decreased. To solve these problems we suggest Hybrid Preference Prediction Technique Using Weighting based Data Reliability. Preference prediction is carried out by creating similar item subset and similar user subset and predicting user preference by each subset and merging each predictive value by weighting point applying model condition. According to this technique, we can increase accuracy of user preference prediction and implement recommendation system which can provide highly reliable recommendation when density of preference matrix is low. Efficiency of this system is verified by Mean Absolute Error. Proposed technique shows average 21.7% improvement than Hao Ji's technique when preference matrix sparsity is more than 84% through experiment.

• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.22-30
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• 2022

The reinforcement learning algorithm has proven its potential in solving sequential decision-making problems under uncertainties, such as finding paths to route data packets in wireless sensor networks. With reinforcement learning, the computation of the optimum path requires careful definition of the so-called reward function, which is defined as a linear function that aggregates multiple objective functions into a single objective to compute a numerical value (reward) to be maximized. In a typical defined linear reward function, the multiple objectives to be optimized are integrated in the form of a weighted sum with fixed weighting factors for all learning agents. This study proposes a reinforcement learning -based routing protocol for wireless sensor network, where different learning agents prioritize different objective goals by assigning weighting factors to the aggregated objectives of the reward function. We assign appropriate weighting factors to the objectives in the reward function of a sensor node according to its hop-count distance to the sink node. We expect this approach to enhance the effectiveness of multi-objective reinforcement learning for wireless sensor networks with a balanced trade-off among competing parameters. Furthermore, we propose SDN (Software Defined Networks) architecture with multiple controllers for constant network monitoring to allow learning agents to adapt according to the dynamics of the network conditions. Simulation results show that our proposed scheme enhances the performance of wireless sensor network under varied conditions, such as the node density and traffic intensity, with a good trade-off among competing performance metrics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.5
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• pp.549-560
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• 1989

In this paper, the method of determining the initial weighting vlaues fuctioning as a filter under the Directional Constrained Minimization of Power(DCMP) algorithm is presented. By analyzing the sideband beamformer with the Finite Impulse Response (FIR) filter concepts, the constraints of any desired directions are obtained and the initial weighing values with fast adaptation time are formulated from those constraints. By applying this proposed initial weighting values to the DCMP and the spatial averaging processor, the interference of a desired direction and the coherent noises are eliminated at the same time. The improvement of this method compared with the existing algorithm is confirmed by computer simulation.

• The Journal of the Acoustical Society of Korea
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• v.18 no.8
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• pp.61-67
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• 1999

This paper proposes a new beamforming algorithm for acoustic measurement by using the nested linear array. In this algorithm, the weighting is optimized by minimizing the LMS error with the initial value obtained by FIR filter design algorithm. The optimization process is applied to each sub-band, which is divided from the octave band, to produce the uniform directivity index. For the optimization pseudo inverse matrix is used for the transfer matrix. As the simulation results, it is found that the proposed algorithm can get the desired beam pattern and unform directivity index so as to be used efficiently for the acoustic measurement by using a nested linear array.

• Journal of the Society of Naval Architects of Korea
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• v.54 no.5
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• pp.368-377
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• 2017

Outfittings of offshore plants and high value-added vessels, such as FPSO, drillship, are much more than outfittings of general ships. So the complexity of the outfittings is increased and the importance of outfittings has also increased. But, there is no clear method to define the installation sequence of outfittings, yet. In this study, we developed the algorithm to define the installation sequence of outfittings by applying variables and constraints related to outfitting, such as process parameters, weighting coefficients, installation constraints. Also, we developed the application that applied the algorithm and compared cases by changing the weighting coefficients of process parameters. We verified the practicality of the algorithm by developing the application. The results of this study are that the accuracy of the outfitting planning is improved and efficient lead time can be predicted by defining the installation sequence of outfittings.

• Journal of Distribution Science
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• v.10 no.11
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• pp.31-37
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• 2012

Purpose - This study was conducted under the assumption that brand A, a store of company Z of Pangyo, with a new store at Pangyo station is targeting the Bundang-gu area of the newly developed city of Seongnam. Research design, data, methodology - As a result of demand forecasting using geometric series models, an extrapolation of past trends provided the coefficient estimates, without utilizing regression analysis on a constant increase in children's wear, for which the population size and estimated parameter were required. Results - Demand forecasting on the basis of past trends indicates the likelihood that sales of discount stores in the Bundang area, where brand A currently has a presence, would fetch a higher estimated value than that of the average discount store in the country during 2015. If past trends persist, future sales of operational stores are likely to increase. Conclusions - In evaluating location using the simple weighting model, Seohyun Lotte Mart obtained a high rating amongst new stores in Pangyo, on the basis of accessibility, demand class, and existing stores. Therefore, when opening a new counter at a relevant store, a positive effect can be predicted.

• Atmosphere
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• v.24 no.2
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• pp.235-243
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• 2014

Sources of aviation turbulence vary through the seasons, especially in the East Asia including Korean peninsula, associated primarily with the changes in the jet/front system and convective activities. For this reason, a seasonal Korean aviation Turbulence Guidance (KTG) system (seasonal-KTG) is developed in the present study by using pilot reports (PIREPs) and analysis data of the operational Unified Model (UM) of the Korea Meteorological Administration (KMA) for two years between June 2011 and May 2013. Twenty best diagnostics of aviation turbulence in each season are selected by the method of probability of detection (POD) using the PIREPs and UM data. After calculating a weighting value of each selected diagnostics using their area under curve (AUC), the 20 best diagnostics are combined with the weighting scores into a single ensemble-averaged index by season. Compared with the current operational-KTG system that is based on the diagnostics applying all seasons, the performances of the seasonal-KTG system are better in all seasons, except in fall.

• Journal of Korea Game Society
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• v.18 no.5
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• pp.59-66
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• 2018

In this paper, one of the traditional game, Gonu game, is implemented and experimented. The Minimax algorithm was applied as a technique to implement the Gonu game. We proposed an evaluation function to implement game in Minimax algorithm. We analyze the efficiency of algorithm for alpha beta pruning to improve the performance after implementation of Gonu game. Weights were analyzed for optimal analysis that affected the win or loss of the game. For the weighting analysis, a competition of human and computer was performed. We also experimented with computer and computer. As a result, we proposed a weighting value for optimal attack and defense.

• Journal of Korean Society of Rural Planning
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• v.12 no.4 s.33
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• pp.1-11
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• 2006

Recently many administrative institutes try to improve the viability of rural villages. For increasing the viability, not only infrastructures but internal vitality is necessary in rural villages. Nonetheless, most of governmental projects have been focused on infrastructures. For this reason, RDA(Rural Development Administration) designed and performed the RHL(Rural Healthy and Longevity village) project. This RHL project is not easy to evaluate the outcome because it consists of very intangible project items. In this paper, we developed a scoring model to evaluate the result of the RHL project. The scoring model based on DEA(Data Envelopment Analysis) was suggested to evaluate the quantity of personal activities in each village. Personal activities are classified into five categories: regional life, social life, productive life, outdoor life and indoor life. Evaluating indices of each category are developed and weighting values are evaluated by AHP(Analytic Hierarchy Process). The developed model was applied to Kumsan village and examined its applicability.

• Journal of Energy Engineering
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• v.8 no.4
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• pp.612-620
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• 1999

Environmental impact assessment in the step of the Life Cycle Assessment (LCA) measures relative values of importance or weight of the environmental load characterized in the inventory analysis. The weight measurements are used to evaluate the environmental load or the effect of the industrial product or technology. In this paper the Analytic Network Prpcess (ANP) is introduced to calculate a relative weighting of the environmental impact. The ANP is considered as one of the useful decision making framework and allow for more complex interrelationships, feedback, and inner/outer dependence among the decision level and factors. The weighting from the ANP may applied to obtain the overall evaluation value of environmental load.