• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.25-29
• /
• 2003

LQ actuator selection problem for multi-input system discussed in this paper is to determine optimal actuator out of many actuators and input sequences so as to minimize the quadratic control performance. The solution of this problem depends on initial values and has a combinatorial property, so it is extremely difficult to get an optimal solution. For this difficulty, we proposed the concept of comparability of actuators and showed the uniqueness of the solution[1] . Further, to get general optimal solution for LQ problem with actuator selection strategies, we derived the equivalent condition for the comparability of actuator in single-input system . In this paper we extend this result to the case of multi-input system. The derived sufficient condition is applicable in the case of positive semi-definite comparability matrices.

• Journal of applied mathematics & informatics
• /
• v.33 no.5_6
• /
• pp.517-530
• /
• 2015

In this paper, we establish a class of strong limit theorems, represented by inequalities, for the arbitrary random field with respect to the product binomial distributions indexed by the infinite tree on the generalized random selection system by constructing the consistent distri-bution and a nonnegative martingale with pure analytical methods. As corollaries, some limit properties for the Markov chain field with respect to the binomial distributions indexed by the infinite tree on the generalized random selection system are studied.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.12
• /
• pp.2511-2519
• /
• 2009

In this paper, we introduce the methodological system design via feature selection using Principal Component Analysis and Particle Swarm Optimization algorithms. The overall methodological system design comes from three kinds of modules such as preprocessing module, feature extraction module, and recognition module. First, Histogram equalization enhance the quality of image by exploiting contrast effect based on the normalized function generated from histogram distribution values of 2D face image. Secondly, PCA extracts feature vectors to be used for face recognition by using eigenvalues and eigenvectors obtained from covariance matrix. Finally the feature selection for face recognition among the entire feature vectors is considered by means of the Particle Swarm Optimization. The optimized Polynomial-based Radial Basis Function Neural Networks are used to evaluate the face recognition performance. This study shows that the proposed methodological system design is effective to the analysis of preferred face recognition.

• Journal of Korean Institute of Industrial Engineers
• /
• v.36 no.3
• /
• pp.164-175
• /
• 2010

In this study, we developed a genetic algorithm to find a near optimal solution of concurrent spare parts selection for the operational time period with limited information of weapon systems purchased from overseas. Through the analysis of time profiles related with system operations, we first define the optimization goal which maintains the expected system operating rate under the budget restrictions, and the number of failures and the lead time for each spare part are used to calculate the estimated total down time of the system. The genetic algorithm for CSP selection shows that the objective function minimizes the estimated total down time of systems with satisfying the restrictions. The method provided by this study can be applied to the generalized model of CSP selection for the systems purchased from overseas without provision of their full structure and adequate information.

• International conference on construction engineering and project management
• /
• 2009.05a
• /
• pp.1440-1445
• /
• 2009

Clients demands have been changed by construction circumstances such as high-technology, megaprojects, and the complexity of construction. Advanced foreign nations have already introduced and applied new project delivery systems (i.e, CM, DB, etc.) to deal with the change of such that. Korea has also promoted variation of the delivery systems for the progressive measure to the rapid changeable situation. Even though government has made his efforts as stated above, some clients have uniformly used those to public construction projects. That is because there are not selection criteria of project delivery system for clients. Therefore, this study presented the selection criteria of project delivery system based on project types in the public large construction projects. In addition, the study has verified the viability of the presented models through consultation with professionals and experts.

• The Journal of the Korean life insurance medical association
• /
• v.27 no.2
• /
• pp.85-95
• /
• 2008

When an insurance company receives an application for life or health insurance, the company must evaluate the degree of risk the individual for insurance coverage presents before the company agrees to issue the policy. A medical factor is a physical or psychological characteristic that may increases a hazard. A financial factor is financial information that is taken into account by underwriter to determine if a person is applying for more than he/she reasonably needs or can afford. A personal factor is a lifestyle choice. There are several medical risk selection systems in Korean life insurance market. They are attending physician's statement, direct examination by insurance doctors, and paramedic examination. However there is some dissatisfaction of current system. It is possible that cooperation of part-time insurance doctors system may be one of useful system of medical risk selection. Improvement of medical risk selection system will be an important matter of profitability of insurance company and it will contribute to sound life insurance system.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.10
• /
• pp.2587-2600
• /
• 2012

It has been demonstrated that choosing an appropriate relay node can improve the transmission rate for the system. However, such system improvement brought by the relay selection may be degraded with the presence of the malicious relay nodes, which are selected but refuse to cooperate for transmissions deliberately. In this paper, we formulate the relay selection issue as a restless bandit problem with the objective to maximize the average rate, while considering the credibility of each relay node, which may be different at each time instant. Then the optimization problem is solved by using the priority-index heuristic method effectively. Furthermore, a low complexity algorithm is offered in order to facilitate the practical implementations. Simulation results are conducted to demonstrate the effectiveness of the proposed trust-based relay selection scheme.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.190-195
• /
• 2004

We propose a pattern classification algorithm using self-nonself discrimination principle of immune cells and apply it to DNA pattern classification problem. Pattern classification problem in bioinformatics is very important and frequent one. In this paper, we propose a classification algorithm based on the negative selection of the immune system to classify DNA patterns. The negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes ${\eta}$ groups of antigenic receptor for ${\eta}$ different patterns, these receptor groups can classify into ${\eta}$ patterns. We propose a pattern classification algorithm based on the negative selection in nucleotide base level and amino acid level. Also to show the validity of our algorithm, experimental results of RNA group classification are presented.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.4 no.2
• /
• pp.231-235
• /
• 2004

According to revealing the DNA sequence of human and living things, it increases that a demand on a new computational processing method which utilizes DNA sequence information. In this paper we propose a classification algorithm based on negative selection of the immune system to classify DNA patterns. Negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes n group of antigenic receptor for n different patterns, they can classify into n patterns. In this paper we propose a pattern classification algorithm based on negative selection in nucleotide base level and amino acid level.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.8
• /
• pp.109-118
• /
• 1994

We proposed new field/frame mode selection quantization and buffer control strategy for interlaced digital HDTV image coding system. The field/frame mode selection is performed based on the mean square error and number of generated bits for each superblock. The quantization factor for each superblock is determined by the characteristics of human visual system and buffer status. The statistical characteristics of the number of generated bits for basis block and the prediction of buffer status are used for buffer control. Simulation results show that the proposed field/frame mode selection and rate buffer control. Simulation results show that the proposed field/frame mode selection and rate buffer control strategy have good subjective image quality and have stable buffer status.