• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.4
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• pp.388-398
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• 1998

In constructing fuzzy control systems. there are many parameters such as rule base. membership functions. inference m method. defuzzification. and I/O scaling factors. To control the system in properly using fuzzy logic. we have to consider t the correlation with those parameters. This paper deals with self-tuning of fuzzy control systems. The fuzzy controller h has parameters that are input and output scaling factors to effect control output. And we propose the looklongleftarrowup table b based self-tuning fuzy controller. We propose the PMTM(Plus-Minus Tuning Method) for self tuning method, self-tuning the initial look-up table to the appropriate table by adding and subtracting the values.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1262-1270
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• 2017

Among various decoding algorithms of low-density parity-check (LDPC) codes, the min-sum (MS) algorithm and its modified algorithms are widely adopted because of their computational simplicity compared to the sum-product (SP) algorithm with slight loss of decoding performance. In the MS algorithm, the magnitude of the output message from a check node (CN) processing unit is decided by either the smallest or the next smallest input message which are denoted as min1 and min2, respectively. It has been shown that multiplying a scaling factor to the output of CN message will improve the decoding performance. Further, Zhong et al. have shown that multiplying different scaling factors (called a 2-dimensional scaling) to min1 and min2 much increases the performance of the LDPC decoder. In this paper, the simplified 2-dimensional scaled (S2DS) MS algorithm is proposed. In the proposed algorithm, we figure out a pair of the most efficient scaling factors which multiplications can be replaced with combinations of addition and shift operations. Furthermore, one scaling operation is approximated by the difference between min1 and min2. The simulation results show that S2DS achieves the error correcting performance which is close to or outperforms the SP algorithm regardless of coding rates, and its computational complexity is the lowest comparing to modified versions of MS algorithms.

• Journal of Information Technology Services
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• v.18 no.5
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• pp.209-224
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• 2019

When evaluating the performance of a NPD(New Product Development) project, it is common to evaluate the project performance according to the achievement of the planned goal in terms of time, quality and cost management, which are usually three main constraints of the project. The evaluation of the financial factors by which sales contributed to the return of the company is more influential. This is why companies need to increase sales and raise profits. Therefore, it is more reasonable to evaluate the sales performance of NPD projects over a certain period of time against the input costs. At this time, we can analyze the causes of inefficient projects and compare them with other projects and find out how to improve the sales performance to help the company increase its competitiveness. In this paper, we analyze the relative efficiency of the sales performance on the input of the projects by using the actual sales in the period of one year after mass production of the NPD projects of 'S' company in ICT industry. Input factors include developer resource and development cost for the NPD reported after the project has been completed, the delay weeks for the schedule targeted at the project planning stage, and the number of quality issues due to development design faults during initial mass-production. The sales figure and the contribution margin of the product after one year from the start of mass production are defined as the output factors. In this paper, we analyze the efficiency of the projects by using data envelope analysis (DEA). As a result, we found out the reason of the inefficient project of DMUs according to the differences in the characteristics of the efficient and inefficient B2B markets based on the result of DEA of NPD projects. Thus, the goal of this paper is to identify strategies for improving sales performance of NPD projects in inefficient markets.

• IE interfaces
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• v.11 no.3
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• pp.23-40
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• 1998

In this paper, a method to determine the optimal configuration of operating policies in an integrated-automated manufacturing system using the Taguchi method and computer simulation experiments is presented. An integrated-automated manufacturing system called direct-input-output manufacturing system(DIOMS) is described. We only consider the operational aspect of the DIOMS. Four operating policies including input sequencing control, dispatching rule for the storage/retrieval(S/R) machine, machine center-based part type selection rule, and storage assignment policy are treated as design factors. The number of machine centers, the number of part types, demand rate, processing time and the rate of each part type, vertical and horizontal speed of the S/R machine, and the size of a local buffer in the machine centers are considered as noise factors in generating various manufacturing system environment. For the performance characteristics, mean flow time and throughput are adopted. A robust design experiment with inner and outer orthogonal arrays are conducted by computer simulation, and an optimal configuration of operating policies is presented which consists of a combination of the level of each design factor. The validity of the optimal configurations is investigated by comparing their signal-to-noise ratios with those obtained with full factorial designs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.3
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• pp.126-132
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• 2013

In this paper, efficiencies of core technology development projects, conducted by Ministry of Trade, Industry and Energy, are compared. In the process, DEA (Data Envelopment Analysis) is utilized as a main technique for comparing efficiencies. For DEA, input oriented BCC Model is adopted with government grant, recipient expenditure, the number of participating institutions, and project duration as input factors, and the number of patents, the number of papers, and occurred sales as output factors. As a result, next generation mobile communication project turns out to be the most efficient project of all. Therefore, next generation mobile communication project should be benchmarked for the other projects to follow. However, these results should be used only for reference data since every project has a different objective and, of course, is run under a different environment.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.81-85
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• 2021

The purpose of this paper is to measure the relative efficiency of the police agencies in Korea with data collected from 2018 to 2020, using data envelopment analysis (DEA), as put forward by Charnes et al., which is used to construct a scalar measure of efficiency for all police agencies. The results of this study can be used to assist police agencies in delivering better and more efficient services to the community. The analytical results based on DEA identify potentially weak and strong police agencies on policing performance, their efficient benchmarking, and the levels of clear-ups that would make inefficient police agencies efficient. We could suggest that higher levels of the police force are associated with higher performance efficiency against crimes. But, it is a little hard to say that higher levels of the police force can keep the local police agencies efficient without explaining the contribution of other input variables to criminal arrest and prevention. On the other hand, our analysis presents that differences in operating environments and socioeconomic factors do not have a significant influence on the efficiency of local police agencies. But, it is necessary to note that we need to examine the effect of environments and socioeconomic factors on crime to create the better-policing performance.

• Journal of Korea Port Economic Association
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• v.33 no.4
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• pp.117-134
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• 2017

The purpose of this research is to analyze the efficiency of the Chinese repair shipbuilding industry using a DEA model with 12 Chinese repair shipbuilding companies. Unlike preceding studies, this study has different research subjects as well as selected input and output variables. The research was conducted with competitive Chinese companies in the market. For the efficiency analysis, input variables included the number of technicians as well as facilities, and output variables were diversified with relevant factors using the number of repaired ships and service ranges as well as sales. The differences were analyzed by including only facilities as an input variable for the DEA model, and then both facilities and technicians. For inefficient DMUs, the strengths and weaknesses were analyzed by finding the causes through a reference group, which was developed into an efficient DMU. Moreover, public and private companies were separated to develop improvement measures.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.309-321
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• 2021

While total sales of broadcasting business have been increasing, terrestrial broadcasters' sales are stagnant and comprehensive programming program providers(PPs)' sales are increasing. The purpose of this study is to derive implications by analyzing the relative efficiency and super-efficiency of domestic broadcasters in such an asymmetric situation. In this study, we use input and output data of three central terrestrial broadcasters and four comprehensive programming PPs from 2012 to 2019. For the analysis, Additive DEA model and Additive super-efficiency DEA model are used with the assumption of VRS condition since the broadcasting industry is characterized by economies of scale. As a result, we find out that the input excess of tangible assets is the most decisive cause of inefficiency that reduces the efficiency of central terrestrial broadcasters. On the other hand, for the comprehensive programming PPs, the input excess of tangible assets and the output shortfall of total sales are important factors of inefficiency.

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.608-616
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• 2022

Power peaking factors (PPF) is an important parameter for safe and efficient reactor operation. There are several methods to calculate the PPF at TRIGA research reactors such as MCNP and TRIGLAV codes. However, these methods are time-consuming and required high specifications of a computer system. To overcome these limitations, artificial intelligence was introduced for parameter prediction. Previous studies applied the neural network method to predict the PPF, but the publications using the ANFIS method are not well developed yet. In this paper, the prediction of PPF using the ANFIS was conducted. Two input variables, control rod position, and neutron flux were collected while the PPF was calculated using TRIGLAV code as the data output. These input-output datasets were used for ANFIS model generation, training, and testing. In this study, four ANFIS model with two types of input space partitioning methods shows good predictive performances with R² values in the range of 96%-97%, reveals the strong relationship between the predicted and actual PPF values. The RMSE calculated also near zero. From this statistical analysis, it is proven that the ANFIS could predict the PPF accurately and can be used as an alternative method to develop a real-time monitoring system at TRIGA research reactors.

• Structural Engineering and Mechanics
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• v.85 no.5
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• pp.635-644
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• 2023

The design of honeycomb sandwich structures is often challenging because these structures can be tailored from a variety of possible cores and face sheets configurations, therefore, the design of sandwich structures is characterized as a time-consuming and complex task. A data-driven computational approach that integrates the analytical method and Artificial Neural Network (ANN) is developed by the authors to rapidly predict the design of sandwich structures for a targeted maximum structural deflection. The elaborated ANN reverse design approach is applied to obtain the thickness of the sandwich core, the thickness of the laminated face sheets, and safety factors for composite sandwich structure. The required data for building ANN model were obtained using the governing equations of sandwich components in conjunction with the Monte Carlo Method. Then, the functional relationship between the input and output features was created using the neural network Backpropagation (BP) algorithm. The input variables were the dimensions of the sandwich structure, the applied load, the core density, and the maximum deflection, which was the reverse input given by the designer. The outstanding performance of reverse ANN model revealed through a low value of mean square error (MSE) together with the coefficient of determination (R2) close to the unity. Furthermore, the output of the model was in good agreement with the analytical solution with a maximum error 4.7%. The combination of reverse concept and ANN may provide a potentially novel approach in designing of sandwich structures. The main added value of this study is the elaboration of a reverse ANN model, which provides a low computational technique as well as savestime in the design or redesign of sandwich structures compared to analytical and finite element approaches.