Using multiplicative neuron model to establish fuzzy logic relationships

Determination of fuzzy logic relationships between observations is quite effective on the forecasting performance of fuzzy time series approaches. In various studies available in the literature, it has been seen that utilizing artificial neural networks for establishing fuzzy relations increase the forecasting accuracy. In this study, a novel high order fuzzy time series forecasting approach in which multiplicative neuron model is used to define fuzzy relations is proposed in order to reach high forecasting level. Also, particle swarm optimization method is utilized to train multiplicative neuron model. In order to show forecasting performance of the proposed method, it is applied to a well-known data Taiwan future exchange and the results produced by the proposed approach is compared to those obtained from other fuzzy time series forecasting models. As a result of the implementation, it is observed that the proposed approach gives the best forecasts for Taiwan future exchange time series.     

Tensile Bond Strength of a Highly Cross-Linked Denture Tooth to the Compression-Molded and Injection-Molded Denture Base Polymers

This study compared tensile bond strengths between conventional compression-molded heat (HC)-, auto (AP)-, and microwave-polymerized (MC) poly(methyl methacrylate)-based denture resins and a relatively new injection-molded, microwave-polymerized polyurethane based resin (MI) bonded to a highly cross-linked denture tooth. In the first part of the experiments, denture teeth were used as received. In the second part, they were treated with dichloromethane to see its effect on bonding of conventional denture bases (HCS and APS). Bond strength was tested in tension according to ADA specification No.15. The results showed that the HC group failed cohesively because of higher interface bonding (49.95 MPa) compared with those of the others (AP: 25.41 MPa; MC: 22.06 MPa; MI: 20.02 MPa). The application of dichloromethane improved bond strengths of HCS and APS groups (60.61 and 32.03 MPa, respectively). It was suggested that dichloromethane could be applied on the denture teeth ridge lap area prior to denture base processing to enhance adhesion between the tooth/resin.     

An experimental study on the bond strength between reinforcement bars and concrete as a function of concrete cover,strength and corrosion level

The effect of corrosion on the bond strength between reinforcement bars and concrete was studied in a series of experiments. An accelerated corrosion method was used to corrode the reinforcement bars embedded in concrete specimens. Pullout tests were performed to develop an empirical model for the ultimate bond strength by evaluating bond strengths in two different concrete mixes, three concrete cover depths and different mass losses of reinforcement bars after corrosion. Bond-slip relationships for the different corrosion levels were compared. It was found that the relationship between bond strength and concrete strength in uncorroded specimens differed from that of corroded specimens set in high-strength concrete because of brittleness in the corroded specimens, which caused a sudden loss of bond strength. The results revealed that specimens with higher concrete strength levels and corroded reinforcements showed a higher percentage of bond strength degradation due to concrete cracking during the pullout tests.     

The impact of a realistic packet traffic model on the performance of surveillance wireless sensor networks

It is quite common to see that classical periodic or Poisson packet traffic models are used for evaluating the performance of wireless sensor networks (WSNs). However, these models may not be appropriate for modeling the data traffic resulting from a particular application. Furthermore, they may be overestimating the performance of a WSN. In this paper, we show the significance of using a realistic and application-specific packet traffic model by comparing the performance of a well-known WSN protocol under the Surveillance WSN packet traffic model (SPTM), as well as under periodic and binomial traffic models. A packet traffic framework specific to surveillance applications is proposed which is then used for deriving SPTM analytically. In order to be adaptable and flexible, SPTM incorporates a probabilistic and parametric sensor detection model. Simulation results show that to employ an application-specific packet traffic model has significant impact on the performance evaluation of the WSN and ordinary traffic models may overestimate the capacity of the WSN.     

Impacts of impregnation with Imersol-Aqua on the compression strength of some solid wood materials

The aim of this study was to investigate the effects of impregnation with Imersol-Aqua on the compression strength of some solid wood materials. For this aim, Oriental beech (Fagus orientalis Lipsky), European oak (Quercus petrea Liebl.), Scotch pine (Pinus sylvestris Lipsky), Uludag fir (Abies Bornmülleriana Mattf.), Oriental spruce (Picea orientalis Lipsky) and Lombardy poplar (Populus nigra Lipsky) wood samples were prepared according to TS 2595 and impregnated with Imersol-Aqua, commonly being used in construction wood materials by the method of short, medium and long-term of dipping according to ASTM D 1413 and producers’ definition. After the impregnation process, compression strength was measured according to TS 2595. Consequently, among the non-impregnated wood materials, the highest compression strength was obtained in beech and pine samples. Compression strength at this situation from the highest to lowest can be enumerated beech, pine, oak, spruce, fir and poplar. With regard to the impregnation period, the sequence form the highest to lowest was as long-term, medium-term and short-term dipping. In the interaction of wood material and impregnation period, the highest compression strength values were obtained in Scotch pine (71.220 N mm⁻²) impregnated with long-term dipping method whereas the lowest in Lombardy poplar (35.710 N mm⁻²) impregnated with short-term dipping method.

In consequence, in the massive constructions and furniture elements that the compression strength after the impregnation is of great concern, long-term impregnation of solid wood material could be recommended.     

Electricity production from twelve monosaccharides using microbial fuel cells

Direct generation of electricity from monosaccharides of lignocellulosic biomass was examined using air cathode microbial fuel cells (MFCs). Electricity was generated from all carbon sources tested, including six hexoses (d-glucose, d-galactose, d(−)-levulose (fructose), l-fucose, l-rhamnose, and d-mannose), three pentoses (d-xylose, d(−)-arabinose, and d(−)-ribose), two uronic acids (d-galacturonic acid and d-glucuronic acid) and one aldonic acid (d-gluconic acid). The mixed bacterial culture, which was enriched using acetate as a carbon source, adapted well to all carbon sources tested, although the adaptation times varied from 1 to 70 h. The maximum power density obtained from these carbon sources ranged from 1240 ± 10 to 2770 ± 30 mW m⁻² at current density range of 0.76–1.18 mA cm⁻². d-Mannose resulted in the lowest maximum power density, whereas d-glucuronic acid generated the highest one. Coulombic efficiency ranged from 21 to 37%. For all carbon sources tested, the relationship between the maximum voltage output and the substrate concentration appeared to follow saturation kinetics at 120 Ω external resistance. The estimated maximum voltage output ranged between 0.26 and 0.44 V and half-saturation kinetic constants ranged from 111 to 725 mg L⁻¹. Chemical oxygen demand (COD) removal was over 80% for all carbon sources tested. Results from this study indicated that lignocellulosic biomass-derived monosaccharides might be a suitable resource for electricity generation using MFC technology.     

Adaptive random access algorithm with improved delay performance

We propose an adaptive random access algorithm for mobile environments with capture. The algorithm has a dynamic window size which is updated according to the traffic intensity. The packet arrival rate is tracked by employing sequential detection procedures. Simulations indicate that reducing the window size adaptively under heavy load conditions improves the average delay significantly. Copyright © 2001 John Wiley & Sons, Ltd.     

Switched-capacitor resonator structure with improved performance

A novel switched-capacitor resonator circuit is proposed. Its centre frequency is insensitive to the finite bandwidth and gain of the opamps used     

Statistical Design of Low Power Square-Law CMOS Cells for High Yield

A robust design of low voltage low power square law CMOS composite cells using statistical VLSI design techniques is presented. Since random device/process variations do not scale down with feature size or supply voltage, the statistical design of low voltage circuits is essential in order to keep functional yields of low voltage circuits at levels that are competitive and cost effective. The Response Surface Methodology and Design of Experiment techniques were used as statistical techniques. This article shows that statistical techniques will result in area/layout optimization which will enhance functional yield of low voltage analog ICs.