• Progress in Superconductivity and Cryogenics
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• v.24 no.3
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• pp.19-23
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• 2022

We have been developing a magnetic separation device that can be used in low magnetic fields for paramagnetic materials. Magnetic separation of paramagnetic particles with a small particle size is desired for volume reduction of contaminated soil in Fukushima or separation of iron scale from water supply system in power plants. However, the implementation of the system has been difficult due to the needed magnetic fields is high for paramagnetic materials. This is because there was a problem in installing such a magnet in the site. Therefore, we have developed a magnetic separation system that combines a selection tube and magnetic separation that can separate small sized paramagnetic particles in a low magnetic field. The selection tube is a technique for classifying the suspended particles by utilizing the phenomenon that the suspended particles come to rest when the gravity acting on the particles and the drag force are balanced when the suspension is flowed upward. In the balanced condition, they can be captured with even small magnetic forces. In this study, we calculated the particle size of paramagnetic particles trapped in a selection tube in a high gradient magnetic field. As a result, the combination of the selection tube and HGMS (High Gradient Magnetic Separation-system) can separate small sized paramagnetic particles under low magnetic field with high efficiency, and this paper shows its potential application.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.4
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• pp.282-287
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• 2006

This paper presents an original feature selection method for Emotion Recognition which includes many original elements. Feature selection has some merits regarding pattern recognition performance. Thus, we developed a method called thee 'Interactive Feature Selection' and the results (selected features) of the IFS were applied to an emotion recognition system (ERS), which was also implemented in this research. The innovative feature selection method was based on a Reinforcement Learning Algorithm and since it required responses from human users, it was denoted an 'Interactive Feature Selection'. By performing an IFS, we were able to obtain three top features and apply them to the ERS. Comparing those results from a random selection and Sequential Forward Selection (SFS) and Genetic Algorithm Feature Selection (GAFS), we verified that the top three features were better than the randomly selected feature set.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.265-277
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• 1998

The control chart has been used widely and importantly as a tool for statistical process control(SPC). Most companies are concerned with improving the quality and the productivity as well as reducing the cost, especially in today's highly competitive environment. Though SPC is known as a technique for consistent quality, it is not used properly due to lack of knowledge about it. It is required to develop a support system for control chart selection and interpretation that can be utilized by non-specialist without hard training or experiences. The support system was developed by applying the expert system tool to popular control charts. Though some researches on this area has been performed, the implemented results expose many problems in field applications due to the unsatisfactory explanation of the selected control chart and limited knowledge base for resolving the problems. This thesis presented an expert system for control chart as solution for these problems. The expert system for the control chart selection and interpretation is developed by using Turbo C and EXSYS which is an expert system development tool.

• Journal of the Korean Society for Library and Information Science
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• v.27
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• pp.291-339
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• 1994

The purpose of this study is to find personal characteristics that affect users' cognitive characteristics of system, and to verify correlations between this users' cognitive characteristics and selection of system usage in using end -user searching systems (EUSS), For corroborative analysis of this study, preliminary model was constructed referring to Davis' Technology Acceptance Model. The model consists of exogenous variables (personal characteristics) , parameter variables (perceived usefulness, perceived ease of use), and effect variables (selection of system usage), When exogenous variables affect parameter variables, exogenous variables are independent variables and parameter variables are dependent variables. In addition, in correlation of parameter variables, which have been affected by exogenous variables, with effect variables, parameter variables are independent variables and effect variables are dependent variables, As for the research methodology, this study regards the Academic Information System connected with the Internet as EUSS, So questionnaires have been sent to researchers in universities who were conducting direct searching for the system. 229 valid responses to questionnaires have been analyzed according to Pearson Correlation Analysis and Stepwise Selection of Multiple Regression in the statistical software packages, 'SPSS PC+'. The findings and conclusions made in this study are summarized as follows; 1. Among the personal characteristics (age, disciplinary, computer literacy level, perceived usefulness of use education and training, perceived satisfaction of end-user searching, perceived satisfaction of system characteristics), all characteristics but age affect perceived usefulness and perceived ease of use. Specifically, perceived satisfaction of end user searching and perceived satisfaction of system characteristics most affect perceived usefulness and perceived ease of use respectively. 2. Perceived usefulness and perceived ease of use have a direct effect on selection of system usage in using EUSS. 3, Perceived usefulness more affect selection of system usage than perceived ease of use in using EUSS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.1828-1847
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• 2014

Coordinated multi-point (CoMP) transmission has been regarded as a potential technology for LTE-Advanced. In frequency division duplexing systems, channel quantization is applied for reporting channel state information (CSI). Considering the dynamic number of cooperation base stations (BSs), asymmetry feature of CoMP channels and high searching complexity, simply increasing the size of the codebook used in traditional multiple antenna systems to quantize the global CSI of CoMP systems directly is infeasible. Per-cell codebook based channel quantization to quantize local CSI for each BS separately is an effective method. In this paper, the theoretical upper bounds of system throughput are derived for two codeword selection schemes, independent codeword selection (ICS) and joint codeword selection (JCS), respectively. The feedback overhead and selection complexity of these two schemes are analyzed. In the simulation, the system throughput of ICS and JCS is compared. Both analysis and simulation results show that JCS has a better tradeoff between system throughput and feedback overhead. The ICS has obvious advantage in complexity, but it needs additional phase information (PI) feedback for obtaining the approximate system throughput with JCS. Under the same number of feedback bits constraint, allocating the number of bits for channel direction information (CDI) and PI quantization can increase the system throughput, but ICS is still inferior to JCS. Based on theoretical analysis and simulation results, some recommendations are given with regard to the application of each scheme respectively.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.3
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• pp.3-10
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• 1993

The main propulsion system may be the most complicated of the shipboard systems. Many factors such as fuel economy, weight, space, first cost, reliability, vibration and noise must be considered when selecting the prime mover of the main propulsion system for ships. An expert system is a computer program that represents and reasons with knowledge of some specialist subject with a view to solving problems or giving advice. Recently, it is being developed increasingly with wider applications in many industries. This paper describes development of knowledge-based system for main engine selection of ships using general purpose expert system development tool, Nexpert Object. Developed system is consist of ship performance estimation module such as resistance and propulsion, data base for main engine, knowledge base for main engine selection in Nexpert Object and graphic user interface.

• Journal of the Korea Safety Management & Science
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• v.8 no.4
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• pp.181-193
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• 2006

The purpose of this thesis addresses a development of an expert system to support a decision making of the vender selection. The researches related to the vender selection problems have been studied and they provide 23 criteria to select proper venders. In this thesis, 8 criteria have been used to construct a knowledge base of the expert system. The system in this thesis consists of 6 steps in its procedure. Step 1 decides a specification that satisfies customer's needs and Step 2 chooses a part supplied by a vender. The type of an outside order is decided in Step 3 and some venders satisfying the customer's needs are selected in Step 4. Some of the venders chosen from step 4 which do not satisfy the fatal cirteria(that is Quality, Delivery, Price) can be deleted in Step 5. In the last step, 8 cirteria is used to select 3 venders according to their ranking. Consequently, this program provides for a man, who does not have the experiances, an efficient way to select appropriate venders in the vender selection problems.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.265-267
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• 2012

This paper analyzes network selection issues of secondary users (SUs) in Cooperative Cognitive Radio Networks (CRNs) by utilizing Queuing Model. Coordinating with Handover Cost-Based Network selection, this paper also addresses an opportunity for the secondary users (SUs) to enhance QoS as well as economics efficiency. In this paper, network selection of SUs is the optimal association between Overall System Time Minimization Problem evaluation of Secondary Connection (SC) and Handover Cost-Based Network selection. This will be illustrated by simulation results.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.264-267
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• 2002

This paper proposed a effective priority selection algorithm named weighted round-robin algorithm and show the implementation result of DMAC priority selection module using prosed weighted round-robin algorithm. I parameterize timing constraints of each functional module, which decide the effectiveness of system. Proposed weighted round-robin algorithm decide the most effective module for data transmission using parameterize timing constraints and update timing parameter of each module for next transmission module selection. I implement DMAC priority selection module using this weighted round-robin algorithm and can improve the timing effective for data transmission from memory to functional module or one functional module to another functional module.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.553-562
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• 2004

In this short communication we discuss the bias problems of CART in split variable selection and suggest a method to reduce the variable selection bias. Penalties proportional to the number of categories or distinct values are applied to the splitting criteria of CART. The results of empirical comparisons show that the proposed modification of CART reduces the bias in variable selection.