• Bulletin of the Korean Chemical Society
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• v.16 no.9
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• pp.850-858
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• 1995

Golden-rule like formulas have been used without theoretical basis to calculate the resonance lifetimes and final state distributions in the predissociation of van der Waals molecules. Here we present their theoretical basis by extending Fano's configuration interaction theory. Such extensions were independently done by Farnonux [Phys. Rev. 1985, 25, 287] but his work, unfortunately, was not well known outside some small group of people in the field of Auger spectroscopy. Since my extension is easier to understand than his, it is presented here. Theoretical basis of Golden rule like formulas used in the predissociation of van der Waals molecules was obtained by using such extensions. Factors responsible for several aspects of predissociation dynamics, such as variations of dynamics as functions of resonance lifetimes, or variations in shapes of final quantum state distributions of photofragments around resonances, were identified. Parameters, or dynamical information that could be obtained from the measurement of partial cross section spectra were accordingly determined. The theory was applied to the vibrational predissociation of triatomic van der Waals molecules and its result was compared with those calculated by close-coupling method. An example where Golden-rule like expression fails and branching ratios vary greatly around a resonance was considered.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1254-1263
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• 1993

Representing knowledge uncertainty , aggregating evidence confidences , and propagation uncertainties are three key elements that effect the ability of a rule-based expert system to represent domains with uncertainty . Fuzzy set theory provide a good mathematical tool for representing the vagueness associated with a variable when , as the condition of a rule , it only partially corresponds to the input data. However, the aggregation of ANDed and Ored confidences is not as simple as the intersection and union operators defined for fuzzy set membership. There is, in fact, a certain degree of compensation that occurs when an expert aggregates confidences associated with compound evidence . Further, expert often consider individual evidences to be varying importance , or weight , in their support for a conclusion. This paper presents a flexible approach for evaluating evidence and conclusion confidences. Evidences may be represented as fuzzy or nonfuzzy variables with as associat d degree of certainty . different weight can also be associated degree of certainty. Different weights can also be assigned to the individual condition in determining the confidence of compound evidence . Conclusion confidence is calculated using a modified approach combining the evidence confidence and a rule strength. The techniques developed offer a flexible framework for representing knowledge and propagating uncertainties. This framework has the potention to reflect human aggregation of uncertain information more accurately than simple minimum and maximum operator do.

• The Transactions of the Korea Information Processing Society
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• v.5 no.1
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• pp.103-110
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• 1998

In case of traditional Rule-Based Reasoning(RBR) and Case-Based Reasoning(CBR), although knowledge is reasoned either by one of them or by the integration of RBR and CBR, there is a problem that much time should be consumed by numerous rules and cases. In order to improve this time-consuming problem, in this paper, a new type of reasoning technique, which is a kind of integration of reduced RB and CB, is to be introduced. Such a new type of reasoning uses Rough Set, by which we can represent multi-meaning and/or random knowledge easily. In Rough Set, solution is to be obtained by its own complementary rules, using the process of RB and CB into equivalence class by the classification and approximation of Rough Set. and then using reduced RB and CB through the integrated reasoning.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.5 no.1
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• pp.04-10
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• 1987

We consider a time sharing computer system with a single processor where tasks ofK different types arrive at the system according to independent time homogeneous Poisson processes from outside. A task, after given a quantum for processing, leaves the system, or changes the type and rejoins the system according to specified probabilitycs. While many existing priority time sharing models determine the priorities of tasks strictly by their service time requirements, this paper develops a new scheduling rule wherein the importances or urgencies in addition to the service time requirements of tasks are counted, by inposing an appropriate reward structure on the system. Also presented is the algorithm through which to determine the rankings of K types according to this new scheduling rule.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.872-878
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• 2013

In industrial control systems, flow measurement is a very important issue. It is frequently needed to calculate how much total fluid or gas flows through a cross-section. Flow volume measurement tools use simple sampling or rectangle methods. Actually, flow volume measurement process is an integration process. For this reason, measurement systems using instantaneous sampling technique cause considerably high errors. In order to make more accurate flow measurement, numerical integration methods should be used. Literally, for numerical integration method, Rectangular, Trapezoidal, Simpson, Romberg and Gaussian Quadrature methods are suggested. Among these methods, trapezoidal rule method is quite easy to calculate and is notably more accurate and contains no restrictive conditions. Therefore, it is especially convenient for the portable flow volume measurement systems. In this study, the volume measurement of air which is flowing through a cross-section is achieved by using PLC ladder diagram. The measurements are done using two different approaches. Trapezoidal rule method is proposed to measure the flow sensor signal to minimize measurement errors due to the classical sampling method as a different approach. It is concluded that the trapezoidal rule method is more effective than the classical sampling.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.126-128
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• 2004

As e-mail is becoming increasingly important in every day life activity, mail users spend more and more time organizing and classifying the e-mails they receive into folder. Many existing recommendation systems or text classification are mostly focused on recommending the products for the commercial purposes or web documents. So this study aims to apply these application to e-mail more necessary to users. This paper suggests a dynamic recommendation agent system based on Rule Filtering Component recommending the relevant category to enable users directly to manage the optimum classification when a new e-mail is received as the effective method for E-Mail Management. Moreover we try to improve the accuracy as eliminating the limits of misclassification that can be key in classifying e-mails by category. While the existing Bayesian Learning Algorithm mostly uses the fixed threshold, we prove to improve the satisfaction of users as increasing the accuracy by changing the fixed threshold to the dynamic threshold. We designed main modules by rule filtering component for enhanced scalability and reusability of our system.

• Korean Management Science Review
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• v.17 no.3
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• pp.19-30
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• 2000

Customization and personalization services are considered as a critical success factor to be a successful Internet store or web service provider. As a representative personalization technique, personalized recommendation techniques are studied and commercialized to suggest products or services to a customer of Internet storefronts based on demographics of the customer or based on an analysis of the past purchasing behavior of the customer. The underlining theories of recommendation techniques are statistics, data mining, artificial intelligence, and/or rule-based matching. In the rule-based approach for personalized recommendation, marketing rules for personalization are usually collected from marketing experts and are used to inference with customers data. however, it is difficult to extract marketing rules from marketing experts, and also difficult to validate and to maintain the constructed knowledge base. In this paper, we proposed a marketing rule extraction technique for personalized recommendation on Internet storefronts using market basket analysis technique, a well-known data mining technique. Using marketing basket analysis technique, marketing rules for cross sales are extracted, and are used to provide personalized advertisement selection when a customer visits in an Internet store. An experiment has been performed to evaluate the effectiveness of proposed approach comparing with preference scoring approach and random selection.

• ETRI Journal
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• v.41 no.2
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• pp.176-183
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• 2019

Spectrum sensing plays an important role in spectrum sharing. Energy detection is generally used because it does not require a priori knowledge of primary user (PU) signals; however, it is sensitive to noise uncertainty. An order statistics (OS) detector provides inherent protection against nonhomogeneous background signals. However, no analysis has been conducted yet to apply OS detection to spectrum sensing in a wireless channel to solve noise uncertainty. In this paper, we propose a robust spectrum sensing scheme based on generalized order statistics (GOS) and analyze the exact false alarm and detection probabilities under noise uncertainty. From the equation of the exact false alarm probability, the threshold value is calculated to maintain a constant false alarm rate. The detection probability is obtained from the calculated threshold under noise uncertainty. As a fusion rule for cooperative spectrum sensing, we adopt an OR rule, that is, a 1-out-of-N rule, and we call the proposed scheme GOS-OR. The analytical results show that the GOS-OR scheme can achieve optimum performance and maintain the desired false alarm rates if the coefficients of the GOS-OR detector can be correctly selected.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.2
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• pp.46-52
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• 2005

In this paper, we present a temporal association rule based on item time intervals. A temporal association rule is an association rule that holds specific time intervals. If we consider itemset in the frequently purchased period, we can discover more significant itemset satisfying minimum support. Because the previous study did not consider the time interval between purchased item, it could find itemset that did not satisfy the minimum support in case some item was frequently purchased in a specific period and rarely or not purchased in other period. Our approach uses interval support which is counted by period with support and confidence in the association rule to discovery large itemset.

• Korean Journal of Digital Imaging in Medicine
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• v.12 no.1
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• pp.5-8
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• 2010

Opened a court in February 10, 2006, a rule of safety management of the diagnosis radiation system was promulgated for safety of the radiation worker, patients and patients' family members. The purpose of this rule is to minimize the risk of being exposed to radiation during the process of handling X-ray. For this reason, we manufactured shielding device of mobile X-ray unit collimator for diminution of skin dose. Shielding device is made to a thickness of Pb 0.375mm. For portable chest radiography, we measured skin dose 50cm from center ray to 200cm at intervals of 20cm by Unfors Xi detector. As a result, a rule of safety management of the diagnosis radiation system has been strengthened. But there are exceptions, such as ER, OR, ICU to this rule. So shielding device could contribute to protect unnecessary radiation exposure and improve nation's health.