• Proceedings of the IEEK Conference
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• 2004.06a
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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.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11b
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• pp.1221-1224
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• 2003

본 논문은 RBR(Rule-Based Reasoning) 기법과 RBR 기법에 적용될 규칙에 대한 우선순위를 둠으로써 효율적인 네트워크 설정을 만드는 동시에 네트워크 장애 발생시 장애를 진단 검출복구하는 에이전트 시스템에 관한 연구이다. 논문에서 제시하는 시스템은 AS 내에서 동작하는 것을 원칙으로 하며 각 네트워크의 에이전트들은 우선 순위 장애 탐지 및 복구를 위해 우선 순위에 따라 규칙을 적용한다. 장애 발생시 진단 검출 복구를 위해 에이전트는 상호 협력하며 장애 검출 및 진단 도구로써 ping, traceroute 등을 이용한다.

• The Journal of Engineering Research
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• v.2 no.1
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• pp.13-21
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• 1997

This paper describes how to represent varations of feature parameters to improve recognition of continuous speech. For speech recognition, feature parameters, which are formant frequencies, pitches, logarithmic energies and zero crossing retes are used in general. But, their values and variations depend on speakers, for example disparities between man and woman, and on their age. It is difficult to decide a priority the value of the variation width. Hence, we try to represent this variation by introducing fuzziness and recognize a continuous speech by fuzzy inference using fuzzy production rules.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.6
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• pp.870-875
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• 2013

After introducing diagnosis equipment power failure prevention activities for distribution system have become more active. To do facility diagnosis and maintenance work more efficiently we need to evaluate reliability for the system and should determine the priority line with appropriate criteria. Thus, to calculate risk factor for the power distribution line that are composed of many component facilities its historical failure events for the last 5 years are collected and analysed. The failure statics show that more than 60% of various failures are related to environment factors randomly and about 20% of the failures are refer to the aging. As a strategic evaluation system reflecting these environmental influence is needed, a system on the basis of the probabilistic approach related statical variables in terms of failure rate and failure probability of electrical components is proposed. The figures for the evaluation are derived from the field failure DB. With adopting Bayesian rule we can calculate easily about conditional probability query. The proposed evaluation system is demonstrated with model system and the calculated indices representing the properties of the model line are discussed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.142-148
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• 1993

Recectly, development of expert system utilizing the domain specific knowledge focuses upon the machining operations. This paper describes an expert system for selecting the optimum grinding wheel based on the Analytic Hierarchy Process and Fuzzy Logic. Knowledge-base, in this system, for selecting of grinding wheel is designed to appling the knowhow and experience knowledge of skilled hands. In this paper, firstly determination method of fuzzy membership function utilizing the qualitative knowledge, and then selection of the optimum wheel from among the available components according to Saaty's priority rule are described. Lastly,some implementation results are suggested.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.04b
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• pp.370-374
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• 1993

This paper describes a study on the expert system based process planning of the block division process in shipbuilding. The prototype system developed deterines the block division line of the midship of crude-oil tanker. Case-based reasoning (CBR) approach relying on previous similar cases to solve the problem is applied instead of rule-based reasoning (RBR). Similar cases are retrieved from case base according to the similarity metrics between input problem and cases. The retrieved case with the highest priority is then adapted to fit to the input problem buy adaptation rules. The adapted solution is proposed as the division line for the input problem.

• IE interfaces
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• v.14 no.1
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• pp.30-38
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• 2001

Logistics network management has become one of the most important sources of competitive advantage regarding logistics cost and customer service in numerous business segments. Logistics network simulation is a powerful analysis method for designing and planning the logistics network optimally in an integrated way. This paper introduces a logistics network simulator, LONSIM, developed by author. LONSIM deploys a mix of simulation and optimization functions to model and analysis logistics network issues such as facility location, inventory policy, manufacturing policy, transportation mode, warehouse assignment, supplier assignment, order processing priority rule, and vehicle routes. LONSIM is built with AweSim 2.1 and Visual Basic 6.0, and executed in windows environment.

• Journal of KIISE
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• v.42 no.8
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• pp.961-971
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• 2015

As a representative area-decomposed algorithm, an area-based quad-trie (AQT) has an issue of search performance. The search procedure must continue to follow the path to its end, due to the possibility of the higher priority-matching rule, even though a matching rule is encountered in a node. A leaf-pushing AQT improves the search performance of the AQT by making a single rule node exist in each search path. This paper proposes a new algorithm to further improve the search performance of the leaf-pushing AQT. The proposed algorithm implements a leaf-pushing AQT using a hash table and an on-chip Bloom filter. In the proposed algorithm, by sequentially querying the Bloom filter, the level of the rule node in the leaf-pushing AQT is identified first. After this procedure, the rule database, which is usually stored in an off-chip memory, is accessed. Simulation results show that packet classification can be performed through a single hash table access using a reasonable sized Bloom filter. The proposed algorithm is compared with existing algorithms in terms of the memory requirement and the search performance.

• Journal of the Korea Society for Simulation
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• v.28 no.3
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• pp.25-40
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• 2019

Today, container terminals are fiercely competing to attract an increasing number of containers. As a way to improve terminal productivity, this study proposes two dispatching rules for yard truck allocation priorities. First, Multi-Attribute Dispatching Rule(MADR) is an allocation method to calculate the weighted sum of multiple factors affecting container terminal productivity and priority them. Especially, the workload of the quay crane was considered one of the factors to reduce the residence time of the ship. Second, Cycling Dispatching Rule(CDR) is the effective way to increase the number of double cycles that directly affect terminal productivity. To identify the effects of combinations of pooling and dispatching, a comparative experiments was performed on 8 scenarios that combined them. A simulation environment has been developed for experiments and the results have demonstrated that the combination of terminal level pooling and Multi-attribute Dispatching could be an excellent combination in KPIs consisting of GCR and delayed departure of ships, etc.

• Korean Journal of Cognitive Science
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• v.13 no.1
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• pp.13-21
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• 2002

Fuzzy logic ignores some information in the reasoning process. Neural network is powerful tools for the pattern processing, but, not appropriate for the logical reasoning. To model human knowledge, besides pattern processing capability, the logical reasoning capability is equally important. Another new neural network called neural logic network is able to do the logical reasoning. Because the fuzzy inference is a fuzzy logical reasoning, we construct fuzzy inference network based on the neural logic network, extending the existing rule-inference network. And the traditional propagation rule is modified. Experiments are performed to compare search costs by sequential searching and searching by priority. The experimental results show that the searching by priority is more efficient than the sequential searching as the size of the fuzzy inference network becomes larder and an the number of searching increases.