A linguistic modeling of consensus in group decision making basedon OWA operators

In this paper, a model for group decision-making is proposed and defined in a linguistic context. A multiperson multicriteria decision problem is considered, in which a group of experts is involved in the evaluation of the performances of a set of alternatives with respect to a predefined set of criteria. The objective is to evaluate a consensual judgement and a consensus degree on each alternative. Both the experts' evaluations of the alternatives and the degree of consensus are expressed linguistically. A “soft” consensus degree referred to a fuzzy majority of the experts is proposed based on the concept of linguistic quantifier. The entire process is defined in a linguistic domain and modeled within fuzzy set theory by ordered weighted average (OWA) operators     

Classification based on fuzzy robust PCA algorithms and similarity classifier

In this article, classification method is proposed where data is first preprocessed using fuzzy robust principal component analysis (FRPCA) algorithms to obtain data in a more feasible form. After this we use similarity classifier for the classification. We tested this procedure for breast cancer data and liver-disorder data. The results were quite promising and better classification accuracy was achieved than using traditional PCA and similarity classifier. Fuzzy robust principal component analysis algorithms seem to have the effect that they project these data sets in a more feasible form, and together with similarity classifier classification on accuracy of 70.25% was achieved with liver-disorder data and 98.19% accuracy was achieved with breast cancer data. Compared to the results achieved with traditional PCA and similarity classifier about 4% higher accuracy was achieved with liver-disorder data and about 0.5% higher accuracy was achieved with breast cancer data.     

Modelling of airborne dust emissions in CNC MDF milling

All dust control measures are necessary to reduce dust exposure in MDF (Medium Density Fibreboard)-milling, because of the high amount and fineness of the dust produced and a potential risk of exposure to formaldehyde or other glue chemicals during the machining of MDF. The most effective way of reducing dust exposure is to reduce the emission of dust at the source. Airborne dust emission was studied and modelled in the milling. In the milling of MDF, airborne dust emission was much higher than in the milling of solid materials. Milling of MDF produced airborne particles with a mass median diameter of 6–7 µm. The most significant factor affecting the amount of dust created from milling was average chip thickness. In order to reduce the amount of dust, milling parameters should be chosen so that the average chip thickness is greater than 0.05 mm. The average chip thickness could be obtained with different milling parameters, for example with different combinations of feed and traverse rates. The same chip thicknesses resulted in around the same percentage fraction of fine dust mass regardless of how the average chip thickness was obtained. The relationship between the percentage fraction of fine dust mass from the removed mass (c_%) and the chip thickness (h_m) was modelled and presented in the form of c_% = 0.194 h _m ^-1. The model developed can be used to estimate the percentage fraction of fine dust mass as a function of chip thickness. The model can be used in optimisation programs for CNC milling machines to minimize the airborne dust generated and to reduce dust exposure.     

Aggregated search of data and services

From a user perspective, data and services provide a complementary view of an information source: data provide detailed information about specific needs, while services execute processes involving data and returning an informative result as well. For this reason, users need to perform aggregated searches to identify not only relevant data, but also services able to operate on them. At the current state of the art such aggregated search can be only manually performed by expert users, who first identify relevant data, and then identify existing relevant services.     

Knee extension dynamometer: a new device for dynamic isokinetic magnetic resonance spectroscopy experiments

In the present study we introduce a new device for exercise magnetic resonance spectroscopy (MRS). It operates in a standard whole-body scanner. Mechanical exertion unit allows maximal 10° to 15° short-arc knee extensions. The device operates hydraulically and is based on isokinetic movement. The force and work conducted are automatically controlled by the electronic control and computer unit. A small surface coil placed on the vastus medialis muscle allows the collection of spectra without interfering spectra from nearby resting muscles. The force used for the extensions can be followed simultaneously as a curve on the screen in the operator's room and the data is transferred to a personal computer for later analysis. Total work and fatigue percentage are also calculated by the device. It also allows the use of different isokinetic exercise protocols. The measurements of force proved reliable in repeat measurements using an isokinetic test device as a control.This device has been used clinically for over a year, is easy to operate, and offers reliable measurements. It is well suited to trials where muscle energy states versus time are followed since it allows noninvasive simultaneous quantification of muscle performance and collecting MRS spectra at rest, during exercise, and in the recovery phase.     

Context‐based compression of binary images in parallel

Binary images can be compressed efficiently using context‐based statistical modeling and arithmetic coding. However, this approach is fully sequential and therefore additional computing power from parallel computers cannot be utilized. We attack this problem and show how to implement the context‐based compression in parallel. Our approach is to segment the image into non‐overlapping blocks, which are compressed independently by the processors. We give two alternative solutions about how to construct, distribute and utilize the model in parallel, and study the effect on the compression performance and execution time. We show by experiments that the proposed approach achieves speedup that is proportional to the number of processors. The work efficiency exceeds 50% with any reasonable number of processors. Copyright © 2002 John Wiley & Sons, Ltd.     

EEG and MEG brain-computer interface for tetraplegic patients.

We characterized features of magnetoencephalographic (MEG) and electroencephalographic (EEG) signals generated in the sensorimotor cortex of three tetraplegics attempting index finger movements. Single MEG and EEG trials were classified offline into two classes using two different classifiers, a batch trained classifier and a dynamic classifier. Classification accuracies obtained with dynamic classifier were better, at 75%, 89%, and 91% in different subjects, when features were in the 0.5-3.0-Hz frequency band. Classification accuracies of EEG and MEG did not differ.     

A study of guidelines for the conduct and analysis of simultaneous clinical replications.

Examined the development, implementation, and evaluation of guidelines for the simultaneous application of clinical replications. The 15 authors served as Ss. Success of the guidelines was evaluated by their ability to yield (1) information concerning the probability of the treatment's success, and (2) hypotheses concerning uncontrolled variables that may limit generalization of the treatment. Results support the validity of the guidelines in accomplishing these purposes. The use of such guidelines may serve as a vehicle for the integration of the roles of researcher and practitioner. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Polarization conversion in conical diffraction by metallic and dielectric subwavelength gratings

Subwavelength metallic and dielectric diffraction gratings which rotate the linear polarization of incident light by 90 degrees are examined. Using rigorous diffraction theory in total-internal-reflection configuration, it is shown that full conversion from incident transverse electric field to transverse magnetic zero-order field can be achieved with both dielectric and metallic elements, but dielectric gratings provide higher efficiency and are thus preferable. The fabrication aspects and constraints are discussed in detail and the behavior of the gratings over broad wavelength bands is presented.     

A decision support system for paper making based on simulation and optimization

In this paper a model-driven decision support system related to paper making is introduced. The intention is to emphasize the necessity of coupling different modeling techniques, multiobjective optimization, and software engineering in order to make the end user application realistic, practical and usable. Firstly the paper making process and selected aspects concerning its mathematical modeling, numerical simulation, and multiobjective optimization are introduced, then the related computerized system, called a virtual paper making line, is described. In addition, the associated decision support system, which provides a suitable level of automation to improve the quality of decision making and support the user’s expertise is discussed. Finally, an example presents different ways of using such a software tool.