Coaxial Waveguide Slot Bridge Cell for Liquid Substances Study

The experimental method suggested suppose the studying of energy characteristics of slot bridge (SB) cells in the multi mode operating regime based on the preliminary numerical investigation of scattering resonant characteristics of SB (solution of boundary value problem and investigation of eigen frequencies and relevant field modes). The configuration of experimental model of SB cell is computed accordingly to required frequency band and preliminary information about dielectric parameters of materials chosen for tests. Ethanol scattering characteristics of SB cell are computed by software, developed on the base of rigorous solution of the boundary value problem, providing numerical data with any required accuracy.     

A fuzzy regression and optimization approach for setting target levels in software quality function deployment

With the rapid development of the software industry, improving the quality of software development has gained increasing importance. Software manufacturers have recently applied quality improvement techniques to software development to respond to the needs for software quality. Software quality function deployment (SQFD), as a technique for improving the quality of the software development process to create products responsive to customer expectations, is used to maximize customer satisfaction. This paper presents a fuzzy regression and optimization approach to determine target levels in SQFD. The inherent fuzziness of relationships in SQFD modeling justifies the use of fuzzy regression. Fuzzy regression is used to identify the functional relationships between customer requirements and technical attributes, and among technical attributes. Then, a mathematical programming model is developed to determine target levels of technical attributes using the functional relationships obtained by fuzzy regression. A search engine quality improvement problem is presented to illustrate the application of the proposed approach.     

Indirect rotor position sensing in real time for brushlesspermanent magnet motor drives

This paper describes a modern solution to the real-time rotor position estimation of brushless permanent magnet (PM) motor drives. The position estimation scheme, based on flux linkage and line-current estimation, is implemented in real-time by using the abc reference frame, and it is tested dynamically. The position estimation model of the test motor, development of hardware and basic operation of the digital signal processor (DSP) are discussed. The overall position estimation strategy is accomplished with a fast DSP (TMS320C30). The method is a shaft position sensorless method that is applicable to a wide range of excitation types in brushless PM motors without any restriction on the motor model and the current excitation. Both rectangular and sinewave-excited brushless PM motor drives are examined, and the results are given to demonstrate the effectiveness of the method with dynamic loads in closed estimated position loop     

Inverterless high-power interior permanent-magnet automotive alternator

This paper describes a high-power brushless interior permanent-magnet (PM) automotive alternator which does not use an inverter. The "inverterless" alternator is designed with a high back electromotive force voltage and high reactance, and acts as a constant current source over much of its wide constant power operating speed range. In this configuration, a switched-mode rectifier can be used to regulate the dc output voltage and current, which avoids the complexity and high cost of an inverter. An analysis of the modeling and performance of interior PM machines in this inverterless topology is described. Experimental results showing an outstanding constant power speed range are presented for a 6-kW concept demonstrator machine tested using a three-phase resistive load to simulate inverterless operation.     

Robot selection using an integrated approach based on quality function deployment and fuzzy regression

The decision-makers have been experiencing difficulties in determining the most suitable robot alternative due to the increase in number of robots and the diversity in their application areas. A robust decision framework for robot selection should consider multiple and conflicting criteria and the dependencies among them. This paper introduces a decision model for robot selection based on quality function deployment (QFD) and fuzzy linear regression. The proposed approach benefits from the fact that QFD focuses on delivering value by taking into account the customer requirements and then by deploying this information throughout the development process, and applies this perspective to robot selection. Fuzzy linear regression is considered as an alternative decision aid for robot selection problems where imprecise relationships among system parameters exist. An example robot selection problem is presented to illustrate the proposed decision-making approach.     

Synthesis,characterization, thermal stability and electrochemical properties of <Emphasis Type="Italic">ortho</Emphasis>-imine-functionalized oligophenol via enzymatic oxidative polycondensation

Ortho-imine functionalized oligophenol was synthesized via enzymatic polymerization of 2-((4-nitrophenylimino)methyl)phenol (NPIMP). Enzymatic polymerization was catalyzed by Horseradish peroxidase (HRP) enzyme and hydrogen peroxide (H₂O₂) oxidizer yielded oligophenol with imine functionality on the side-chain. Effects of various factors including reaction pH, temperature and solvent system on the polymerization were studied. Optimum polymerization with the highest yield (96 %) and number-average molecular weight (M _n = 7300 g/mol, degree of polymerization ≈ 30) was accomplished using equivolume mixture of acetone/pH 7.0 phosphate buffer medium at 35 °C in 24 h under air. Characterization of the resulting oligomer was accomplished by ultraviolet-visible spectroscopy (UV-Vis), fourier transform infrared spectroscopy (FT-IR), ¹H and ¹³C nuclear magnetic resonance (¹H and ¹³C NMR), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), cyclic voltammetry (CV) and gel permeation chromatography (GPC). The polymerization involved elimination of hydrogen from NPIMP, and the oligomer possessed phenolic –OH end groups. The oligomer backbone was composed of oxyphenylene and phenylene repeat units. The optical band gaps (Eg) of NPIMP and oligo(NPIMP) were measured as 3.21 and 3.39 Eg, respectively. Thermal stability of the oligo(NPIMP) was also found to be relatively high, and lost 5 % of its mass at 175 °C and lost 50 % of its mass at 600 °C.     

Nonlinear Efficiency of Bored Pile Group under Lateral Loading

A 3×3 bored pile group consisting of nine cast-in-drilled-hole reinforced concrete shafts and a comparable single-shaft were subjected to reversed cyclic, lateral head loading to investigate group interaction effects across a wide range of lateral displacements. The piles had the same diameter of d = 0.61?m and similar soil conditions; however, various equipment constraints led to two differences: (1) a fixed head (zero rotation) boundary condition for the single pile versus minor pile cap rotation in the vertical plane for the group and (2) shaft longitudinal reinforcement ratios of 1.8% for the single pile and 1% for the group piles. To enable comparisons between the test results, a calibrated model of the single pile (1.8% reinforcement) was developed and used to simulate the response of a single shaft with 1% reinforcement. Additional simulations of the pile group were performed to evaluate the effects of cap rotation on group response. By comparing the simulated responses for common conditions, i.e., 1% reinforcing ratio and zero head rotation, group efficiencies were found to range from unity at lateral displacements <0.004×d to 0.8 at small displacements ～ 0.01–0.02×d and up to 0.9 at failure (displacements >0.04×d). Hence, we find that group efficiency depends on the level of nonlinearity in the foundation system. The general group efficiency, although not its displacement-dependence, is captured by p-multipliers in the literature for reinforced concrete, fixed-head piles.     

Characterisation of esterolytic activity from two wild mushroom species, Amanita vaginata var. vaginata and Tricholoma terreum

Characterisation of esterase activities from the edible mushroom species, Amanita vaginata var. vaginata and Tricholoma terreum, were investigated. Native electrophoresis of the crude extracts prepared from both mushroom samples showed the presence of esterolytic activities. The extracts had the greatest activity in the presence of p-nitrophenyl butyrate (pNPB) as a substrate. pH and temperature optima were found to be 8.0 and 30 °C for both enzymes, respectively. V_max and K_m values were determined as 14.2 U/l and 71 μM for A. vaginata var. vaginata and 34.6 U/l and 9.6 μM for T. terreum, respectively. The pH-stability profile showed a stationary line between 3.0 and 10.0 for both enzymes. The esterolytic activities from the extracts were maintained between 10 and 40 °C for 4 h and started to decrease at 50 °C. The effects of EDTA, NaN₃, DTT and PMSF on the enzyme activity were also investigated.     

Development of a knowledge‐based medical expert system to infer supportive treatment suggestions for pediatric patients

This paper discusses the design, implementation, and potential use of an ontology‐based mobile pediatric consultation and monitoring system, which is a smart healthcare expert system for pediatric patients. The proposed system provides remote consultation and monitoring of pediatric patients during their illness at places distant from medical service areas. The system not only shares instant medical data with a pediatrician but also examines the data as a smart medical assistant to detect any emergency situation. In addition, it uses an inference engine to infer instant suggestions for performing certain initial medical treatment steps when necessary. The applied methodologies and main technical contributions have three aspects: (a) pediatric consultation and monitoring ontology, (b) semantic Web rule knowledge base, and (c) inference engine. Two case studies with real pediatric patients are provided and discussed. The reported results of the applied case studies are promising, and they demonstrate the applicability, effectiveness, and efficiency of the proposed approach.