Hierarchical semi-numeric method for pairwise fuzzy group decision making

Gradual improvements to a single-level semi-numeric method, i.e., linguistic labels preference representation by fuzzy sets computation for pairwise fuzzy group decision making are summarized. The method is extended to solve multiple criteria hierarchical structure pairwise fuzzy group decision-making problems. The problems are hierarchically structured into focus, criteria, and alternatives. Decision makers express their evaluations of criteria and alternatives based on each criterion by using linguistic labels. The labels are converted into and processed in triangular fuzzy numbers (TFNs). Evaluations of criteria yield relative criteria weights. Evaluations of the alternatives, based on each criterion, yield a degree of preference for each alternative or a degree of satisfaction for each preference value. By using a neat ordered weighted average (OWA) or a fuzzy weighted average operator, solutions obtained based on each criterion are aggregated into final solutions. The hierarchical semi-numeric method is suitable for solving a larger and more complex pairwise fuzzy group decision-making problem. The proposed method has been verified and applied to solve some real cases and is compared to Saaty's (1996) analytic hierarchy process (AHP) method.     

Hepatic actinomycosis infiltrating the diaphragm and right lung

Hepatic actinomycosis is a rare infectious disease caused by an anaerobic gram-positive bacterium of the genus Actinomyces. Herein, we describe an unusual case of hepatic actinomycosis involving the diaphragm and right lung. A 41-yr-old man was admitted to Wakayama Medical School Hospital presenting with right back pain and cough. Computed tomography and magnetic resonance image revealed a 5 x 10 cm tumor in the anterior superior segment of the liver, which extended to the diaphragm and right lung. Angiography demonstrated a hypervascular tumor and the enlarged right inferior phrenic artery feeding around the tumor. The patient underwent a hepatectomy with partial resections of the diaphragm and the right middle pulmonary lobe. Microscopically, the specimen showed sulfur granules and was positive for Gram stain and Grocott stain and negative for Ziehl-Neelsen stain. These findings were consistent with actinomycosis of the liver. His postoperative course was uneventful and no recurrence was observed 1 yr postoperatively. Although there are at least 36 well-documented cases until 1993, no other report has been found infiltrating the diaphragm and lung.     

Neuro-fuzzy hybrid control system of tank level in petroleum plant

Shown in this paper is a practical method of control using neural network and fuzzy control techniques, where a neural network estimates the target of fuzzy control. The neural network is used to estimate the transient state of a plant which has nonlinear processes such as refrigerating and filtering. The suitable control target pattern for fuzzy control is selected according to this estimation. This method is applied to control the tank level of a solvent dewaxing plant for: 1) changing the tank outflow rate smoothly, and 2) keeping the tank level stable. The results show that this system can control the tank level effectively in both steady state and transient state     

Fuzzy relational algebra for possibility-distribution-fuzzy-relational model of fuzzy data

In the real world, there exist a lot of fuzzy data which cannot or need not be precisely defined. We distinguish two types of fuzziness: one in an attribute value itself and the other in an association of them. For such fuzzy data, we propose a possibility-distribution-fuzzy-relational model, in which fuzzy data are represented by fuzzy relations whose grades of membership and attribute values are possibility distributions. In this model, the former fuzziness is represented by a possibility distribution and the latter by a grade of membership. Relational algebra for the ordinary relational database as defined by Codd includes the traditional set operations and the special relational operations. These operations are classified into the primitive operations, namely, union, difference, extended Cartesian product, selection and projection, and the additional operations, namely, intersection, join, and division. We define the relational algebra for the possibility-distribution-fuzzy-relational model of fuzzy databases.     

Linguistic labels for expressing fuzzy preference relations infuzzy group decision making

This paper proposes improvements to pairwise group decision making based on fuzzy preference relations in three ways. First, it extends the fuzzy preference relation representation using linguistic labels. Decision makers may express their preference relations in linguistic labels which are more practically implementable for solving group decision making problems. Second, it modifies the computational procedures by using fuzzy sets representation and computation, and by avoiding the use of strict threshold values. This allows natural representation, preserves the preference accuracy, and produces more intuitively meaningful solutions. Finally, it considers fuzzy criteria of the alternatives explicitly. Solutions are first derived based on each criterion, and then by using neat ordered weighted average (OWA) operator the final solutions which accommodate all criteria are determined. The proposed method is verified for solving fuzzy group decision making problems, i.e., advertising media selection cases.     

fstds System: A fuzzy-set manipulation system

This paper describes an implementation of a system for fuzzy sets manipulation which is based on fstds (Fuzzy-Set-Theoretic Data Structure), an extended version of Childs's stds (Set-Theoretic Data Structure). The fstds language is considered as a fuzzy-set-theoretically oriented language which can deal, for example, with ordinary sets, ordinary relations, fuzzy sets, fuzzy relations, L-fuzzy sets, level-m fuzzy sets and type-n fuzzy sets. The system consists of an interpreter, a collection of fuzzy-set operations and the data structure, fstds, for representing fuzzy sets. fstds is made up of eight areas, namely, the fuzzy-set area, fuzzy-set representation area, grade area, grade-tuple area, element area, element-tuple area, fuzzy-set name area and fuzzy-set operator name area. The fstds system, in which 52 fuzzy-set operations are available, is implemented in fortran, and is currently running on a FACOM 230-45S computer.     

Antioxidant and anti‐inflammatory activities of water distillate and its dichloromethane extract from licorice root (Glycyrrhiza uralensis) and chemical composition of dichloromethane extract

BACKGROUND: Licorice root is one of the most widely used medicinal herbs and its medicinal properties, such as antibacterial, anti‐ulcer, anti‐tumorigenic and anti‐atherosclerotic activities, have been widely reported. However, there are only a few reports on basic chemical and biological studies of the water distilled components of licorice root. RESULTS: Chinese licorice root was water distilled and the distillate was subsequently extracted with dichloromethane. Residual aqueous solution from the extraction was fractionated using column chromatography. A total of 127 chemicals were identified in the dichloromethane extract, which inhibited hexanal oxidation by over 90% for 45 days at the level of 50 µg mL^?1. A fraction eluted from the residual aqueous solution with acetone exhibited potent antioxidant activities both in a thiobarbituric acid assay and in a malonaldehyde/gas chromatography assay. The acetone fraction also exhibited strong anti‐inflammatory activity (77.9% inhibition at the level of 62 µg mL^?1) in a lipoxygenenase inhibitor screening anti‐inflammatory assay. CONCLUSION: This study demonstrated the antioxidant and anti‐inflammatory activities of the water distillate obtained from Chinese licorice root. Some volatile chemicals among the many components identified in the water distillate exhibited antioxidant activity, suggesting that many medicinal compounds escape with water vapor into the ambient air during the preparation of herbal medicine. Copyright © 2008 Society of Chemical Industry     

Development of a “best representativity” method for experimental data analysis and an application to the critical experiments at the Toshiba NCA facility

For nuclear critical experiments, it is essential to certify similarities of the experiment with the objective of the actual reactor conditions or actual reactor equipment. To judge the applicability of the experimental data, the concept of a “representativity factor” has recently been adopted in the critical experiment field, particularly for fast breeder reactors and future reactor studies. In this study, we extended this concept to the design of a light water reactor system. We developed a new numerical evaluation method and a calculation system. The method is based on a linear combination of the sensitivity coefficient vector of an experiment in which the representativity factor to the target system is maximized to utilize experimental data effectively. Simultaneously, using the measurement data of critical experiments, the method enables us to evaluate calculation errors caused by errors or uncertainties of physical parameters. The derivation of the new calculation method is explained first. We then qualify it with a sample calculation, presenting numerical results for three kinds of critical experiments conducted at the Toshiba Nuclear Critical Assembly facility. Finally, the results are compared with those of an extended bias factor method to clarify the performance of the new method.     

Void reactivity evaluation by modified conversion ratio measurements in LWR critical experiments

We have developed a void reactivity evaluation method by using modified conversion ratio measurements in a light water reactor (LWR) critical lattice. Assembly-wise void reactivity is evaluated from the “finite neutron multiplication factor”, k*, deduced from the modified conversion ratio of each fuel rod. The distributions of modified conversion ratio and k* on a reduced-moderation LWR lattice, for which the improvement of negative void reactivity is a serious issue, were measured. Measured values were analyzed with a continuous-energy Monte Carlo method. The measurements and analyses agreed within the measurement uncertainty.

The developed method is useful for validating the nuclear design methodology concerning void reactivity.