• Journal of the Korean Wood Science and Technology
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• v.39 no.1
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• pp.1-7
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• 2011

Recently, the visual grading rule of Korea Forest Research Institute (KFRI) was revised and it is necessary to investigate the distribution characteristics of visual graded lumber in accordance with the revised rule. Therefore, in this study, the distribution characteristics of bending strength was investigated with revised visual grading rule and changed prior rule, respectively. The size of specimens was $38{\times}140{\times}3,000$ (mm) and the species were $Larix$ $kaempferi$ and $Pinus$ $koraiensis$. The moisture content was under 18% and the specimens were tested in accordance with ASTM D-198. The number of No. 1 and 2 grades, suitable for structural lumber, was increased when the revised visual grading rule was applied. Moreover, the revised rule was more effective to distinguish sharply between No. 1 and 2 grades and below No. 3 grade. Meanwhile, the lower 5% exclusion limit and allowable stresses were generally decreased when revised visual grading rule had been applied. However, the announcement of Korea Forest Service, tested with small clear specimen, was much lower than the allowable stresses of this test, tested with structural lumber. Therefore, the revision of allowable design values should be considered for more exact use and effective structural design.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.12
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• pp.429-460
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• 1999

The letter of credit is quintessentially international. In the absence of international legal system, a private system based on banking practices has evolved, commanding the adherence of the international letter of credit community and providing the foundation of th reputation of this instrument. To maintain this international system, it is vital that international standard banking practice should not be subject to local interpretations that misconstrue or distort it. The UCP is a formulation of international standard banking practice. It is neither positive law nor a "contract term" in any traditional sense and its interpretation must be consonant with its character as a living repositary of international understanding in this field. As a result, the interpretation and application of specific articles of the UCP must be consistent with its evolving character and history and with the principles upon which sound letter of credit practice is predicated. This study, especially, focuses on article 13 and article 14 of the UCP500. Article 13(b) of UCP500 stipulates that banks will have a reasonable time, not to exceed seven days, to examine documents to determine whether they comply facially with the terms of the credit. The seven-day provision is not designed as a safe harbor, because the rule requires the issuer to act within a reasonable time. But, by virtue of the deletion of the preclusion rule in the document examination article in UCP500, however, seven days may evolve as something of a safe harbor, especially for banks that engage in strategic behavior. True, under UCP500 banks are supposed to examine documents within a reasonable time, but there are no consequences in UCP500 for a bank's violation of that duty. It is only in the next provision. Courts might read the preclusion more broadly than the literal reading mentioned here or might fashion a common-law preclusion rule that does not require a showing of detriment. Absent that kind of development, the change in the preclusion rule could have adverse effects on the beneficiary. The penalty, strict estoppel or strict preclusion, under UCP500 and 95UCC differs from the classic estoppel. The classic estoppel rule requires a beneficiary to show three elements. 1. conduct on the part of the issuer that leads the beneficiary to believe that nonconforming documents do conform; 2. reasonable reliance by the beneficiary; and 3. detriment from that reliance. But stict preclusion rule needs not detrimental reliance. This strict estoppel rule is quite strict, and some see it as a fitting pro-beneficiary rule to counterbalance the usually pro-issuer rule of strict compliance.

• Journal of Korean Philosophical Society
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• v.139
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• pp.1-21
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• 2016

To quickly and accurately grasp the consistency and the true/false of sentence description, we may require the help of a computer. It is thus necessary to research and quickly and accurately grasp the consistency and the true/false of sentence description by computer processing techniques. This requires research and planning for the whole study, namely a plan for the necessary tables and those of processing, and development of the table of the five logic rules. In future research, it will be necessary to create and develop the table of ten basic inference rules and the eleven kinds of derived inference rules, and it will be necessary to build a DB of those tables and the computer processing of sentence logic using server programming JSP and client programming JAVA over its foundation. In this paper we present the overall research plan in referring to the logic operation table, dividing the logic and inference rules, and preparing the listed process sequentially by dividing the combination of their use. These jobs are shown as a variable table and a symbol table, and in subsequent studies, will input a processing table and will perform the utilization of server programming JSP, client programming JAVA in the construction of subject/predicate part activated DB, and will prove the true/false of a sentence. In considering the table prepared in chapter 2 as a guide, chapter 3 shows the creation and development of the table of the five logic rules, i.e, The Rule of Double Negation, De Morgan's Rule, The Commutative Rule, The Associative Rule, and The Distributive Rule. These five logic rules are used in Propositional Calculus, Sentential Logic Calculus, and Statement Logic Calculus for sentence logic.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.321-331
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• 2003

Experimental software datasets describing software projects in terms of their complexity and development time have been the subject of intensive modeling. A number of various modeling methodologies and modeling designs have been proposed including such approaches as neural networks, fuzzy, and fuzzy neural network models. In this study, we introduce the concept of the Rule-based fuzzy polynomial neural networks (RFPNN) as a hybrid modeling architecture and discuss its comprehensive design methodology. The development of the RFPNN dwells on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The architecture of the RFPNN results from a synergistic usage of RFNN and PNN. RFNN contribute to the formation of the premise part of the rule-based structure of the RFPNN. The consequence part of the RFPNN is designed using PNN. We discuss two kinds of RFPNN architectures and propose a comprehensive learning algorithm. In particular, it is shown that this network exhibits a dynamic structure. The experimental results include well-known software data such as the NASA dataset concerning software cost estimation and the one describing software modules of the Medical Imaging System (MIS).

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2897-2907
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• 1998

The production-rule generation from training examples is a hard problem that has large space and many local optimal solutions. Many learning methods are proposed for production-rule generation and genetic algorithms is an alternative learning method. However, traditional genetic algorithms has been known to have an obstacle in converging at the global solution area and show poor efficiency of production-rules generated. In this paper, we propose a production-rule generating method which uses genetic algorithm learning. By analyzing optimal sub-solutions captured by genetic algorithm learning, our method takes advantage of its schema structure and thus generates relatively small rule set.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.6
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• pp.110-120
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• 2008

Cognitive Radio (CR) technology is proposed for using the unused spectrum band efficiently because of the spectrum scarcity problems. Spectrum sensing technology is one of the key challenge issues in cognitive radio technologies, which enables unlicensed users to identify and utilize vacant spectrum resource allocated to primary users. In this paper, the cooperative spectrum sensing technologies apply the ITS(Intelligent Transport System) and performance of signal detection analyzes. Then, we utilize the OR-rule and AND-rule for the cooperative signal detection. These data fusion rules improve the performance and reliability of the signal detection.

• Journal of the Korea Convergence Society
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• v.8 no.2
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• pp.27-33
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• 2017

To efficiently provide cloud computing services to users over the Internet, IT resources must be configured in the data center based on virtualization and distributed computing technology. This paper focuses specifically on the problem that new training data can be added at any time in a wide range of fields, and new attributes can be added to training data at any time. In such a case, rule generated by the training data with the former attribute set can not be used. Moreover, the rule can not be combined with the new data set(with the newly added attributes). This paper proposes further development of the new inference engine that can handle the above case naturally. Rule generated from former data set can be combined with the new data set to form the refined rule.

• ETRI Journal
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• v.39 no.4
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• pp.592-604
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• 2017

Intrusion detection is very important for network situation awareness. While a few methods have been proposed to detect network intrusion, they cannot directly and effectively utilize semi-quantitative information consisting of expert knowledge and quantitative data. Hence, this paper proposes a new detection model based on a directed acyclic graph (DAG) and a belief rule base (BRB). In the proposed model, called DAG-BRB, the DAG is employed to construct a multi-layered BRB model that can avoid explosion of combinations of rule number because of a large number of types of intrusion. To obtain the optimal parameters of the DAG-BRB model, an improved constraint covariance matrix adaption evolution strategy (CMA-ES) is developed that can effectively solve the constraint problem in the BRB. A case study was used to test the efficiency of the proposed DAG-BRB. The results showed that compared with other detection models, the DAG-BRB model has a higher detection rate and can be used in real networks.

• Journal of the Korea Society of Computer and Information
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• v.6 no.2
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• pp.48-57
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• 2001

In a fuzzy connectionist expert system(FCES), the knowledge base can be constructed of neural logic networks to represent fuzzy rules and their relationship, We call it fuzzy rule inference network. To find out the belief value of a conclusion, the traditional inference strategy in a FCES will back-propagate from a rule term of the conclusion and follow through the entire network sequentially This sequential search strategy is very inefficient. In this paper, to improve the above search strategy, we proposed fuzzy rule inference rule used in a FCES was modified. The proposed adaptive search strategy in fuzzy rule inference network searches the network according to the search priorities.

• The KIPS Transactions:PartD
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• v.17D no.4
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• pp.311-316
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• 2010

This paper presents a weight adjusted association rule mining algorithm (WARM). Assigning weights to each strategic factor and normalizing raw scores within each strategic factor are the key ideas of the presented algorithm. It is an extension of the earlier algorithm TSAA (transitive support association Apriori) and strategic importance is reflected by considering factors such as profit, marketing value, and customer satisfaction of each item. Performance analysis based on a real world database has been made and comparison of the mining outcomes obtained from three association rule mining algorithms (Apriori, TSAA, and WARM) is provided. The result indicates that each algorithm gives distinct and characteristic behavior in association rule mining.