Application of the output dependent feature scaling in modeling and prediction of performance of counter flow vortex tube having various nozzles numbers at different inlet pressures of air, oxygen, nitrogen and argon

In this study, the performance of the counter flow type vortex tube with the input parameters including the nozzle number (N), the densities of inlet gases (air, oxygen, nitrogen, and argon) and the inlet pressure (P_inlet) has been modeled with the proposed hybrid method combining a novel data preprocessing called output dependent feature scaling (ODFS) and adaptive network based fuzzy inference system (ANFIS) by using the experimentally obtained data. In the developed system, output parameter temperature gradient between the cold and hot outlets has been determined using input parameters comprising (P_inlet), (N), and the density of gases. In order to evaluate the performance of hybrid method, the mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), determination coefficient (R²), and Index of Agreement (IA) values have been used. The obtained results are 9.0670e-004 (MAE), 5.8563e-006 (MSE), 0.0024 (RMSE), 1.00 (R²), and 1.00 (IA) using the hybrid method.     

The optimization of welding parameters for friction stir spot welding of high density polyethylene sheets

Friction stir spot welding parameters affect the weld strength of thermoplastics, such as high density polyethylene (HDPE) sheets. The strength of a friction stir spot weld is usually determined by a lap-shear test. For maximizing the weld strength, the selection of welding parameters is very important. This paper presents an application of Taguchi method to friction stir spot welding strength of HDPE sheets. An orthogonal array, the signal to noise ratio (S/N), and the analysis of variance (ANOVA) are employed to investigate friction stir welding parameter effects on the weld strength. From the ANOVA and the S/N ratio response graphs, the significant parameters and the optimal combination level of welding parameters were obtained. Experimental results confirmed the effectiveness of the method.     

The elasto-plastic impact analysis of functionally graded circular plates under low-velocities

In this study, three-dimensional elasto-plastic analysis of functionally graded (FG) circular plates under low-velocity impact loads is presented. The FG circular plate is composed of ceramic (SiC) and metal (Al) phases, varying in a predetermined fashion through the plate thickness. The elasto-plastic behaviour of the FG circular plate is described by the TTO model. In the analyses, the ceramic phase is taken to be an isotropic elastic material whereas the metal phase is taken to be elasto-plastic material in accordance with the TTO model. The locally effective material properties were evaluated using homogenization method which is based on the Mori–Tanaka scheme. The effects of compositional gradient exponent and impactor velocity on the elasto-plastic impact response of the FG circular plates are investigated, and results are presented graphical form. The compositional gradient exponent and impactor velocity have significant effects on the elasto-plastic impact response of the FG circular plates. The elasto-plastic impact response of FG circular plates is similar to those of homogeneous plates. Therefore, the TTO model can be used to describe the mechanical behaviour of FG plates beyond the elastic range, assuming that the material response is essentially governed by the spreading of plasticity in the metal phase.     

Energy use and economical analysis of sugar beet production in Tokat province of Turkey

The purposes of this study were to determine energy consumption of input and output used in sugar beet production, and to make a cost analysis in Tokat, Turkey. Data were collected from 146 sugar beet farms in Tokat, Turkey by using a face-to-face questionnaire performed in January and February 2005. Farms were selected based on random sampling method. The results revealed that total energy consumption in sugar beet production was 39 685.51 MJ ha⁻¹, and accounted for 49.33% of fertilizer energy, and 24.16% of diesel energy. The output/input energy ratio was 25.75 and energy productivity was 1.53 kg MJ ha⁻¹. Results further indicated that 82.43% of total energy input was in non-renewable energy form, and only 12.82% was in renewable form. Economic analyses showed that profit–cost ratio of farms was 1.17. The highest energy cost items were labor, land renting, depreciation and fertilizers. Although intensive energy consumption in sugar beet production increased the yield, it also resulted in problems such as global warming, land degradation, nutrient loading and pesticide pollution. Therefore, there is a need to pursue a new policy to force producers to undertake energy-efficient practices to establish sustainable production systems without disrupting the natural resources. In addition, extension activities are needed to improve the efficiency of energy consumption and to sustain the natural resources.     

Performance enhancement of the DSRC system using frequency-domain equalization for 5.9 GHz DSRC applications

This paper proposes the use of equalization concepts in frequency domain that exploit the frequency domain channel matrix to combat inter-carrier interference (ICI) instead of inter-symbol interference (ISI) in 5.9 GHz Dedicated Short Range Communications (DSRC) systems. The physical layer (PHY) of DSRC is currently being developed by work group of IEEE 802.11p. The conventional system currently assumes static channel characteristics. Channel tracking schemes were investigated and the Viterbi-aided channel estimation scheme was proposed for DSRC systems that did not explicitly exploit the ICI components caused by the time-varying channels. The performance of the DSRC system is investigated for a time-varying channel using a conventional DSRC model, a decision-directed (Viterbi-aided) channel estimation model, and the frequency-domain equalization design. It is shown that the DSRC system with the frequency-domain equalization achieves a considerable performance enhancement compared to both the conventional and the Viterbi-aided channel estimation schemes in terms of both packet error rate (PER) and bit error rate (BER) at relatively high and low velocities.     

Mass-sensitive detection of gas-phase volatile organics using disk microresonators

The detection of volatile organic compounds (VOCs) in the gas phase by mass-sensitive disk microresonators is reported. The disk resonators were fabricated using a CMOS-compatible silicon micromachining process and subsequently placed in an amplifying feedback loop to sustain oscillation. Sensing of benzene, toluene, and xylene was conducted after applying controlled coatings of an analyte-absorbing polymer. An analytical model of the resonator's chemical sensing performance was developed and verified by the experimental data. Limits of detection for the analytes tested were obtained, modeled, and compared to values obtained from other mass-sensitive resonant gas sensors.     

Inverse dynamics of redundant manipulators using a minimum number of control forces

The number of the control actuators used by the inverse kinematics and dynamics algorithms that have been developed in the literature for generating redundant robot joint trajectories is equal to the number of the degrees of freedom of the manipulator. In this article, an inverse dynamics algorithm that performs the tasks using only a minimum number of actuators is proposed. The number of actuators is equal to the dimension of the task space, and the control forces are solved simultaneously with the corresponding system motion. It is shown that because all degrees of freedom are not actuated, the control forces may lose the ability to make an instantaneous effect on the end-effector acceleration at certain configurations, yielding the dynamical equation set of the system to be singular. The dynamical equations are modified in the neighborhood of the singular configurations by utilizing higher-order derivative information, so that the singularities in the numerical procedure are avoided. Asymptotically stable inverse dynamics closed-loop control in the presence of perturbations is also discussed. The algorithm is further generalized to closed chain manipulators. Three-link and two-link redundant planar manipulators are analyzed to illustrate the validity of the approach. © 2995 John Wiley & Sons, Inc.     

Power Reflection and Transmission Coefficients for Meander‐Line Polarizers with a Chiral Slab

This paper presents a theoretical investigation of power reflection and transmission coefficients for a meander‐line polarizer placed periodically on a chiral slab. It is assumed that a linearly polarized transverse magnetic wave is incident on a chiral slab from the air region. In the analysis, we derive the electric and magnetic fields in the modal form in the air and chiral regions. We obtain power reflection and transmission coefficients in a straightforward manner after matching the tangential components of the electric and magnetic fields at the boundaries. We present numerical results for the power reflection and transmission coefficients versus frequency and incident angle for different values of the chirality admittance. A meander‐line polarizer placed on a dielectric slab can convert a linearly polarized wave to a circularly polarized wave. The design parameters for a meander‐line polarizer are the dimensions of the meander‐line and the values of the dielectric slab. Replacing a dielectric slab with a chiral slab introduces a new independent parameter which controls the wave polarization.     

An IS&R system based on Turkish language

This paper reports an IS&R (Information Storage and Retrieval) system which has been developed to process data stored in two-dimensional tables using a well-defined subset of the Turkish Language. The language referred to as TURDIL is defined by a Regular grammar and is used on an interactive basis. The system has a fully integrated data dictionary which contains table definitions and views of tables, along with information on data-access privileges.     

Automatic recognition of vigilance state by using a wavelet-based artificial neural network

In this study, 5-s long sequences of full-spectrum electroencephalogram (EEG) recordings were used for classifying alert versus drowsy states in an arbitrary subject. EEG signals were obtained from 30 healthy subjects and the results were classified using a wavelet-based neural network. The wavelet-based neural network model, employing the multilayer perceptron (MLP), was used for the classification of EEG signals. A multilayer perceptron neural network (MLPNN) trained with the Levenberg–Marquardt algorithm was used to discriminate the alertness level of the subject. In order to determine the MLPNN inputs, spectral analysis of EEG signals was performed using the discrete wavelet transform (DWT) technique. The MLPNN was trained, cross-validated, and tested with training, cross-validation, and testing sets, respectively. The correct classification rate was 93.3% alert, 96.6% drowsy, and 90% sleep. The classification results showed that the MLPNN trained with the Levenberg–Marquardt algorithm was effective for discriminating the vigilance state of the subject.