Comparative study of two CPU router time management algorithms in cellular IP networks

Providing good quality of service (QoS) in cellular IP networks is an important requirement for performance improvement of the cellular IP network. Resource reservation is one of the methods used in achieving this goal and is proven to be effective. The main resources to be reserved in a cellular IP network are bandwidth, buffer and central processing unit (CPU) cycles. Router CPU cycle is the time taken by the router to process the packet of the flow before forwarding it to the next router (hop). This paper proposes a model for CPU cycle optimization of routers for real‐time flows in a cellular IP network. The model applies both genetic algorithm (GA) and particle swarm optimization (PSO) as soft computing tools to optimize the CPU cycles and reduces the flow processing time at each router in the route taken by a flow. Simulation experiments illustrate a comparative study of the model.     

A Weighted Feature Voting Approach for Robust and Real‐Time Voice Activity Detection

This paper concerns a robust real‐time voice activity detection (VAD) approach which is easy to understand and implement. The proposed approach employs several short‐term speech/nonspeech discriminating features in a voting paradigm to achieve a reliable performance in different environments. This paper mainly focuses on the performance improvement of a recently proposed approach which uses spectral peak valley difference (SPVD) as a feature for silence detection. The main issue of this paper is to apply a set of features with SPVD to improve the VAD robustness. The proposed approach uses a weighted voting scheme in order to take the discriminative power of the employed feature set into account. The experiments show that the proposed approach is more robust than the baseline approach from different points of view, including channel distortion and threshold selection. The proposed approach is also compared with some other VAD techniques for better confirmation of its achievements. Using the proposed weighted voting approach, the average VAD performance is increased to 89.29% for 5 different noise types and 8 SNR levels. The resulting performance is 13.79% higher than the approach based only on SPVD and even 2.25% higher than the not‐weighted voting scheme.     

Heat transfer enhancement by metal screens and metal spheres in phase change energy storage systems

This study focuses on heat transfer enhancement in double pipe energy storage system. Enhancement is achieved by use of metal screens/spheres placed inside the phase change material (PCM), which is paraffin wax and results in increasing the effective thermal conductivity of the combined media of PCM and metal screens/spheres. The experiments are conducted as a function of the diameter and number of spheres inserted in the phase change material. Also, the experiments investigate the effect of increasing the temperature of the heat transfer fluid (HTF). Results are presented in terms of variations in the PCM Nusselt number and the melting Fourier number. Results indicate three-fold decrease in the Fourier number and similar increase in the Nusselt number. Replacing 2-volume percentage of the wax material by the metal spheres results in this large enhancement.     

Immobilization of a human epidermal growth factor receptor 2 mimotope-derived synthetic peptide on Au and its potential application for detection of herceptin in human serum by quartz crystal microbalance

Therapeutic antibodies are antigenically similar to human antibodies and are difficult to detect in assays of human serum samples without the use of the therapeutic antibody's complementary antigen. Herein for the first time, we established a platform to detect Herceptin in solutions by using a small (<2.2 kDa), inexpensive, highly stable human epidermal growth factor receptor (HER2) mimotope-derived synthetic peptide immobilized on the surface of a Au quartz electrode. We used the HER2 mimotope as a substitute for the HER2 receptor protein in piezoimmunosensor or quartz crystal microbalance (QCM) assays to detect Herceptin in human serum. We demonstrated that assay sensitivity was dependent upon the amino acids used to tether and link the peptide to the sensor surface and the buffers used to carry out the assays. The detection limit of the piezoimmunosensor assay was 0.038 nM with a linear operating range of 0.038-0.859 nM. Little nonspecific binding to other therapeutic antibodies (Avastin and Rituxan) was observed. Levels of Herceptin in serum samples obtained from treated patients, as ascertained using the synthetic peptide-based QCM assay, were typical for those treated with Herceptin. The findings of this study are significant in that low-cost synthetic peptides could be used in a QCM assay, in lieu of native or recombinant antigens or capture antibodies, to rapidly detect a therapeutic antibody in human serum. The results suggested that a synthetic peptide bearing a particular functional sequence could be applied for developing a new generation of affinity-based immunosensors to detect a broad range of clinical biomarkers.     

Dynamic analysis of an inclined Timoshenko beam traveled by successive moving masses/forces with inclusion of geometric nonlinearities

In the first part of this paper, the nonlinear coupled governing partial differential equations of vibrations by including the bending rotation of cross section, longitudinal and transverse displacements of an inclined pinned?Cpinned Timoshenko beam made of linear, homogenous and isotropic material with a constant cross section and finite length subjected to a traveling mass/force with constant velocity are derived. To do this, the energy method (Hamilton??s principle) based on the large deflection theory in conjuncture with the von-Karman strain-displacement relations is used. These equations are solved using the Galerkin??s approach via numerical integration methods to obtain dynamic responses of the beam under act of a moving mass/force. In the second part, the nonlinear coupled vibrations of the beam traveled by an arbitrary number of successive moving masses/forces are investigated. To do a thorough study on the subject at hand, a parametric sensitivity analysis by taking into account the effects of the magnitude of the traveling mass or equivalent concentrated force, the velocity of the traveling mass/force, beam??s inclination angle, length of the beam, height of the beam and spacing between successive moving masses/forces are carried out. Furthermore, the dynamic magnification factor and normalized time histories of the mid-point of the beam are obtained for various load velocity ratios, and the results are illustrated and compared to the results obtained from traditional linear solution. The influence of the large deflections caused by a stretching effect due to the beam??s immovable end supports is captured. It is seen that the existence of quadratic?Ccubic nonlinear terms in the coupled governing PDEs of motion renders stiffening (hardening) behavior of the dynamic responses of the beam under the action of a moving mass/force.     

Geometrical effect on SCF distribution in uni-planar tubular DKT-joints under axial loads

Despite the frequent use of DKT-joints in offshore structures, no parametric equation is available for determining the distribution of stress concentration factors (SCFs) along the brace-to-chord intersection of this type of tubular joints. In the present paper, the effect of non-dimensional geometrical parameters and brace-to-chord inclination angle on the distribution of SCFs and DKT-/KT-joint SCF ratios (SRs) along the weld toe of tubular DKT-joints under the balanced axial loads is studied. Thereafter, a parametric equation is proposed for predicting the distribution of SCFs along the 360° spatial curve of the weld toe. The proposed equation satisfies the acceptance criteria recommended by the UK Department of Energy (DoE), and consequently can reliably be used for design purposes.     

The S-transform using a new window to improve frequency and time resolutions

The S-transform presents arbitrary time series as localized invertible time–frequency spectra. This transformation improves the short-time Fourier transform and the wavelet transform by merging the multiresolution and frequency-dependent analysis properties of wavelet transform with the absolute phase retaining of Fourier transform. The generalized S-transform utilizes a combination of a Fourier transform kernel and a scalable-sliding window. The common S-transform applies a Gaussian window to provide appropriate time and frequency resolution and minimizes the product of these resolutions. However, the Gaussian S-transform is unable to obtain uniform time and frequency resolution for all frequency components. In this paper, a novel window based on the $t$ student distribution is proposed for the S-transform to achieve a more uniform resolution. Simulation results show that the S-transform with the proposed window provides in comparison with the Gaussian window a more uniform resolution for the entire time and frequency range. The result is suitable for applications such as spectrum sensing.     

Cooperative OFDM for semi distributed detection in wireless sensor networks

In this paper, parallel distributed detection in wireless sensor network (WSN) is investigated. Sensors are assumed to be transmitting their local decisions to a fusion center through a wireless fading channel using cooperative transmission. To enable cooperative transmission, sensors are divided into groups where sensors in each group help each other in transmitting their decisions in a way that the fusion center receives each local decision as an orthogonal frequency division multiplexed (OFDM) block. The fusion center detects all OFDM blocks sent by all groups to process them in order to obtain a final (global) decision. Using this cooperative transmission scheme enables the fusion center to apply diversity combining methods in order to reduce the fading effects of the channel. Optimal and sub-optimal fusion rules are derived for such system. Simulation results are provided to show the performance improvement that can be obtained compared to the conventional system where each local decision is transmitted to the fusion center individually and no diversity technique is applied at the fusion center.     

Performance of Object Classification Using Zernike Moment

Moments have been used in all sorts of object classification systems based on image. There are lots of moments studied by many researchers in the area of object classification and one of the most preference moments is the Zernike moment. In this paper, the performance of object classification using the Zernike moment has been explored. The classifier based on neural networks has been used in this study. The results indicate the best performance in identifying the aggregate is at 91.4% with a ten orders of the Zernike moment. This encouraging result has shown that the Zernike moment is a suitable moment to be used as a feature of object classification systems.