Characterization of residual stresses from cold expansion using spatial statistics

Residual stress fields from cold expansion have been widely used to extend the fatigue life of aircraft structures. However, the spatial statistical character of these residual stress fields has not been established and has not been incorporated in current analysis methods. The objective of this study was to establish a spatial statistical method to quantify the residual stress field around a cold expanded hole. A framework called the Spatial Analysis of Residual Stress (SpARS) was developed utilizing spatial correlation, response surface modelling techniques and statistical resampling methods to characterize the residual stress field. Our results showed that tolerance bounds on residual stress can be quantified using this method. We also demonstrated the SpARS method using recently published round robin case studies. The newly developed model will be useful for aircraft structural fatigue crack growth analyses to incorporate residual stress fields for extending inspection intervals for fatigue and fracture critical structures.     

A bipolar implementation of the Beta neuron

The great flexibility of the Beta function and its universal approximation characteristics, make Beta basis function neural networks (BBFNNs) very useful. We present a hardware implementation of the Beta neuron. The proposed circuit was designed by using a standard bipolar technology. PSPICE simulations show the good concordance of the output of our circuit with the analytic Beta function. We also successfully integrated the electronic Beta neuron in the design of a BBFNN that approximates a nonlinear mapping.     

Cad for analysis and synthesis of MM-wave transmission lines

This work presents a software for analysis and synthesis of four types of planar lines used on the millimeter wave band: Suspended Microstrip Line, Inverted Microstrip Line, Suspended Stripline and Broadside Coupled Stripline. Conceived for IBM/PG or compatible microcomputers, the program, (MMWL), can study each configuration at a time or all of them at once, and it does not matter if it is synthesis or analysis for each line at the same time. The results are presented in Tables shown in the same screen. The program also provides curves of characteristic impedances against conducting strip width for each one of studied structures. Therefore, it allows choosing the best combination for circuit realization, becoming a helpful tool for projects and with acceptable results.

     

Impact of Offloading on the Efficiency of Wireless Access Networks

International Journal of Wireless Information Networks - Wireless access networks need to deliver a satisfactory level of Quality of Service (QoS) to their subscribers. The service quality can be...     

Feasibility and performance evaluation of a 6LoWPAN‐enabled platform for ubiquitous healthcare monitoring

Technology has revolutionized medical practices by enabling more convenient and non‐intrusive monitoring of patient's health, leading to next generation ubiquitous healthcare (u‐healthcare). The exploitation of the Internet protocol version 6 addressing space along with the miniaturization of electronic devices has fostered providing interoperability and connectivity of wearable sensor devices in wireless body area networks to the Internet of Things. In this paper, we propose to integrate the IPv6 over low power wireless personal area network (6LoWPAN) to the u‐healthcare monitoring system architecture. The main objective is to study the feasibility of the 6LoWPAN‐enabled platform in real‐world scenarios dealing with medical data. The performance evaluation of this platform is carried out initially through simulations using OMNet++ and then supported by an experimental study using sensor motes and a customized micro‐computing unit. Performance metrics such as throughput, end‐to‐end delay, packet error rate, and energy consumption are investigated under acute health conditions, where patient's health information has to be sent continuously and at maximum rate to the care provider. The obtained results show that the proposed 6LoWPAN solution fulfills the main quality of service requirements of u‐healthcare applications. Copyright © 2015 John Wiley & Sons, Ltd.     

RTDGPS Accuracy Improvement Using PSO-LSWSVM and Low-Cost GPS Receivers

Wireless Personal Communications - The position of mobile devices is determined by Real Time Differential Global Positioning System (RTDGPS). This system is composed of fixed and mobile station....     

Misalignment controller in wireless battery charger for electric vehicle based on MPPT method and metaheuristic algorithm

This paper focuses on applying a wireless power transfer WPT technology in an electric vehicle battery charger. The wireless charger system is based on the principle of resonance inductive coupling power through a coreless transformer. The WPT system is considered as a multi parameter and multi constrained nonlinear system. The main contribution in this paper is the use of PSO and GA metaheuristic algorithms in the optimization of a transformer design regarding the impact of a lateral misalignment and the separation distance between the primary and secondary coils. To find the best global solution which is considered as the maximum efficiency in the complex system, both algorithms are compared. A perturbation-and-observation-based tracking system is developed through an efficiency sensing system to act on the misalignment issue and the car position. An additional PSO controller is performed to control the duty cycle of the boost converter in order to follows the maximum efficiency operating points of a WPT system. The discrepancy is the use of the resonant inductive coupling as a source of the MPPT so as to perturb the car position and observe the transferred. Furthermore, the modeling of a contactless transformer is optimized using metaheuristic algorithm.     

Compact all-diode-pumped femtosecond laser source based on chirpedpulse optical parametric amplification in periodically poledKTiOPO4

1 kHz chirped pulse optical parametric amplification in periodically poled KTiOPO₄ achieving 20 μJ amplified signal pulse energy at 1.573 μm and 320 fs pulse duration after recompression is reported     

On the Performance of FFT/DWT/DCT-based OFDM Systems with Chaotic Interleaving and Channel Estimation Algorithms

The efficiency of data transmission over fading channels in orthogonal frequency division multiplexing (OFDM) systems depends on the employed interleaving method. In this study, we propose an improved chaotic interleaving scheme which aims to improve the performance of OFDM system under fading channel. In the proposed scheme, the binary data is interleaved with chaotic Baker map prior to the modulation process. In the sequel, significant degree of encryption is being added during data transmission. The performance of the proposed approach is tested on the conventional fast Fourier transform OFDM, discrete wavelet transform OFDM, and discrete cosine transform OFDM with and without chaotic interleaving. Furthermore, an expectation–maximization (EM) algorithm is proposed for improving channel impulse response (CIR) estimation based on a maximum likelihood principle. The proposed scheme makes use of EM algorithm to update the channel estimates until convergence is reached. The simulation results show the efficiency of the proposed algorithms under Rayleigh fading environments where the symbol error rate essentially coincides with that of the perfect channel case after the fifth EM iteration.     

Hilbert Transform and Statistical Analysis for Channel Selection and Epileptic Seizure Prediction

This paper is concerned with Electroencephalography (EEG) seizure prediction, which means the detection of the pre-ictal state prior to ictal activity occurrence. The basic idea of the proposed approach for EEG seizure prediction is to work on the signals in the Hilbert domain. The operation in the Hilbert domain guarantees working on the low-pass spectra of EEG signal segments to avoid artifacts. Signal attributes in the Hilbert domain including amplitude, derivative, local mean, local variance, and median are analyzed statistically to perform the channel selection and seizure prediction tasks. Pre-defined prediction and false-alarm probabilities are set to select the channels, the attributes, and bins of probability density functions (PDFs) that can be useful for seizure prediction. Due to the multi-channel nature of this process, there is a need for a majority voting strategy to take a decision for each signal segment. Simulation results reveal an average prediction rate of 96.46%, an average false-alarm rate of 0.028077/h and an average prediction time of 60.1595 min for a 90-min prediction horizon.