• 한국정밀공학회지
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• 제22권1호
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• pp.19-25
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• 2005

• 한국컴퓨터정보학회논문지
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• 제9권4호
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• pp.49-54
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• 2004

규칙 기반 접근 제어가 신분 기반 접근 제어의 완전한 대체 방법이 아니듯이 직무 기반 접근 제어도 신분 기반 접근 제어와 규칙 기반 접근 제어의 병합이 아닌 상호 보완적인 방법이다. 본 논문에서는 기존의 접근 제어 메커니즘을 통합하여 보안성 무결성 및 흐름 제어 보안 기능을 제공하며 직무 중심 조직의 접근 제어 요구를 용이하게 수용할 수 있는 새로운 방식의 통합 접근 제어를 위한 시뮬레이션 모델을 설계하여 이를 실제의 응용 시스템에 적용할 수 있도록 한다.

• ETRI Journal
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• 제34권6호
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• pp.900-910
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• 2012

In this paper, a novel trellis-coded spatial modulation (TCSM) design method is presented and analyzed. Inspired by the key idea of trellis-coded modulation (TCM), the detailed analysis is firstly provided on the unequal error protection performance of spatial modulation constellation. Subsequently, the Ungerboeck set partitioning rule is proposed and applied to develop a general method to design the novel TCSM schemes. Different from the conventional TCSM approaches, the novel one based on the Ungerboeck set partitioning rule has similar properties as the classic TCM, which has simple but effective code design criteria. Moreover, the novel designed schemes are robust and adaptive to the generalized Rician fading channels, which outperform the traditional TCSM ones. For examples, the novel 4-, 8-, and 16-state TCSM schemes are constructed by employing different transmit antennas and different modulation schemes in different channel conditions. Simulation results clearly demonstrate the advantages of the novel TCSM schemes over the conventional ones.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 하계종합학술대회 논문집(1)
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• pp.171-174
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• 2004

Packet classification is an essential architectural component in implementing the quality-of-service (QoS) in today's Internet which provides a best-effort service to ail of its applications. Multiple header fields of incoming packets are compared against a set of rules in packet classification, the highest priority rule among matched rules is selected, and the packet is treated according to the action of the rule. In this Paper, we proposed a new packet classification scheme based on parallel multiple hashing on tuple spaces. Simulation results using real classifiers show that the proposed scheme provides very good performance on the required number of memory accesses and the memory size compared with previous works.

• 한국정밀공학회지
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• 제15권5호
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• pp.50-58
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• 1998

A proper model of expert system for the very thin sheet metal press die design has been suggested. Using the suggested model, an expert system of the very thin sheet metal press die has been developed. This study contains that the results from the developed system for three kinds of specimens have the adaptability in the actual site. In addition, the possibility for expansion of this system has been discussed. The developed system, which is based on the knowledge base, has been included in a lot of expert's technology in the practice field. C-language under the HP-UNIX system and CIS customer language of the EXCESS CAD/CAM system have been used as the overall CAD environment. Results from this system will provide effective aids to the designer in this field.

• 한국자동차공학회논문집
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• 제20권4호
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• pp.103-108
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• 2012

Fuel economy is an important factor in a vehicle owing to recent energy supply and environmental problems. This paper deals with fuel cell hybrid vehicles (FCHVs) and introduces a fuel economy evaluation method. The fuel economy of an FCHV depends on its power management strategy. Two rule-based power management strategies are applied to this paper and their fuel economy is evaluated based on the optimal control theory. The concept of the optimal line is also applied to this paper, which is used to compare the fuel consumption of a power management strategy to the optimal result. The two rule-based strategies are also compared to each other.

• 한국정밀공학회지
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• 제27권2호
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• pp.60-69
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• 2010

Lookup-Table (LUT) based fuzzy controller for obstacle avoidance enhances operations faster in multiple obstacles environment. An LUT based fuzzy controller with Positive/Negative (P/N) fuzzy rule base consisting of 18 rules was introduced in our paper$^1$ and this paper shows a 50-rule P/N fuzzy controller for enhancing performance in obstacle avoidance. As a rule, the more rules are necessary, the more buffers are required. This paper suggests LUT sharing method in order to reduce LUT buffer size without significant degradation of performance. The LUT sharing method makes buffer size independent of the whole fuzzy system's complexity. Simulation using MSRDS(MicroSoft Robotics Developer Studio) evaluates the proposed method, and in order to investigate its performance, experiments are carried out to Pioneer P3-DX in the LabVIEW environment. The simulation and experiments show little difference between the fully valued LUT-based method and the LUT sharing method in operation times. On the other hand, LUT sharing method reduced its buffer size by about 95% of full valued LUT-based design.

• 전기학회논문지
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• 제61권12호
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• pp.1791-1800
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• 2012

This paper presents effective design schemes for a photovoltaic (PV) and battery hybrid system that includes state-of-the-art technologies such as maximum power point tracking scheme for PV arrays, an effective charging/discharging circuit for batteries, and grid-interfacing power inverters. Compared to commonly-used PV systems, the proposed configuration has more flexibility and autonomy in controlling individual components of the PV-battery hybrid system. This paper also proposes an intelligent coordination scheme for the components of the PV-battery hybrid system to improve the efficiency of renewable energy resources and peak-load management. The proposed algorithm is based on a rule-based expert system that has excellent capability to optimize multi-objective functions. The proposed configuration and algorithms are investigated via switching-level simulation studies of the PV-battery hybrid system.

• International Journal of Control, Automation, and Systems
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• 제3권2호
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• pp.183-194
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• 2005

In this study, we introduce an advanced architecture of genetically optimized Hybrid Fuzzy Neural Networks (gHFNN) and develop a comprehensive design methodology supporting their construction. A series of numeric experiments is included to illustrate the performance of the networks. The construction of gHFNN exploits fundamental technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms (GAs). The architecture of the gHFNNs results from a synergistic usage of the genetic optimization-driven hybrid system generated by combining Fuzzy Neural Networks (FNN) with Polynomial Neural Networks (PNN). In this tandem, a FNN supports the formation of the premise part of the rule-based structure of the gHFNN. The consequence part of the gHFNN is designed using PNNs. We distinguish between two types of the linear fuzzy inference rule-based FNN structures showing how this taxonomy depends upon the type of a fuzzy partition of input variables. As to the consequence part of the gHFNN, the development of the PNN dwells on two general optimization mechanisms: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the gHFNN, the models are experimented with a representative numerical example. A comparative analysis demonstrates that the proposed gHFNN come with higher accuracy as well as superb predictive capabilities when comparing with other neurofuzzy models.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권6호
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• pp.415-424
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• 2004

In this paper, we introduce and investigate a new category of rule-based fuzzy inference system based on Information Granulation(IG). The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of “If..., then...” statements, and exploits the theory of system optimization and fuzzy implication rules. The form of the fuzzy rules comes with three types of fuzzy inferences: a simplified one that involves conclusions that are fixed numeric values, a linear one where the conclusion part is viewed as a linear function of inputs, and a regression polynomial one as the extended type of the linear one. By the nature of the rule-based fuzzy systems, these fuzzy models are geared toward capturing relationships between information granules. The form of the information granules themselves becomes an important design features of the fuzzy model. Information granulation with the aid of HCM(Hard C-Means) clustering algorithm hell)s determine the initial parameters of rule-based fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial function being used in the Premise and consequence Part of the fuzzy rules. And then the initial Parameters are tuned (adjusted) effectively with the aid of the improved complex method(ICM) and the standard least square method(LSM). In the sequel, the ICM and LSM lead to fine-tuning of the parameters of premise membership functions and consequent polynomial functions in the rules of fuzzy model. An aggregate objective function with a weighting factor is proposed in order to achieve a balance between performance of the fuzzy model. Numerical examples are included to evaluate the performance of the proposed model. They are also contrasted with the performance of the fuzzy models existing in the literature.