Applying MLP-ANN as a novel and accurate method to estimate gas density

In the gas industries, to increase the degree of accuracy of calculation and estimation in different processes, the importance of accurate prediction of gas properties is highlighted. The gas density, as one of the key properties in gas engineering, has a major effect in calculations. So, in the present paper, multi-layer perceptron artificial neural network (MLP-ANN) was used to predict the gas density based on molecular weight, critical pressure and critical temperature of gas, pressure, and temperature. To this end, a total number of 1240 reliable data of gas density were gathered from literature for the training and testing phases. The MLP-ANN outputs were compared with the actual data in different manners, such as statistical and graphical analyses. The coefficient of determination (R²), average absolute relative deviation (AARD), and root mean squared error (RMSE) for overall process were calculated as 1, 0.0088444, and 0.0259, respectively. The determined parameters and graphical analysis showed that the MLP-ANN has great potential and high degree of accuracy in gas density estimation.     

Piezoresistivity in Polymer-Ceramic Composites

Composite materials composed of randomly dispersed semiconducting ceramic particles in an insulating polymer matrix show a pronounced change in resistivity with pressure. Different amounts of iron oxide (Fe₃O₄) powder and antimony-doped tin oxide (SnO₂:Sb) powder were dispersed in an epoxy polymer matrix to form pressure-sensitive composites. In each family of materials, an insulator-to-semiconductor transition is observed in agreement with percolation theory. Composites within a certain range of filler content showed substantial piezoresistive effect under both uniaxial and hydrostatic pressure in which sensitivity is controlled by the choice of filler material and the volume fraction. The effect of temperature on the piezoresistance effect was also examined. Piezoresistors made from Fe₃O₄ composites showed larger temperature changes than those filled with Sb-doped SnO₂.     

Reliability and Mobility Load Balancing in Next Generation Self-organized Networks: Using Stochastic Learning Automata

Self-organizing networking (SON) is an automation technology designed to make the planning, configuration, management, optimization and healing of mobile radio access networks simpler and faster. Most current self-organization networking functions apply rule-based recommended systems to control network resources which seem too complicated and time-consuming to design in practical conditions. This research proposes a cognitive cellular network empowered by an efficient self-organization networking approach which enables SON functions to separately learn and find the best configuration setting. An effective learning approach is proposed for the functions of the cognitive cellular network, which exhibits how the framework is mapped to SON functions. One of the main functions applied in this framework is mobility load balancing. In this paper, a novel Stochastic Learning Automata has been suggested as the load balancing function in which approximately the same quality level is provided for each subscriber. This framework can also be effectively extended to cloud-based systems, where adaptive approaches are needed due to unpredictability of total accessible resources, considering cooperative nature of cloud environments. The results demonstrate that the function of mobility robustness optimization not only learns to optimize HO performance, but also it learns how to distribute excess load throughout the network. The experimental results demonstrate that the proposed scheme minimizes the number of unsatisfied subscribers (N_us) by moving some of the edge users served by overloaded cells towards one or more adjacent target cells. This solution can also guarantee a more balanced network using cell load sharing approach in addition to increase cell throughput outperform the current schemes.

     

A novel interference suppression scheme for global navigation satellite systems using antenna array

This paper considers interference suppression and multipath mitigation in Global Navigation Satellite Systems (GNSSs). In particular, a self-coherence anti-jamming scheme is introduced which relies on the unique structure of the coarse/acquisition (C/A) code of the satellite signals. Because of the repetition of the C/A-code within each navigation symbol, the satellite signals exhibit strong self-coherence between chip-rate samples separated by integer multiples of the spreading gain. The proposed scheme utilizes this inherent self-coherence property to excise interferers that have different temporal structures from that of the satellite signals. Using a multiantenna navigation receiver, the proposed approach obtains the optimal set of beamforming coefficients by maximizing the cross correlation between the output signal and a reference signal, which is generated from the received data. It is demonstrated that the proposed scheme can provide high gains toward all satellites in the field of view, while suppressing strong interferers. By imposing constraints on the beamformer, the proposed method is also capable of mitigating multipath that enters the receiver from or near the horizon. No knowledge of either the transmitted navigation symbols or the satellite positions is required.     

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.     

A New Union Bound on the Error Probability of Binary Coded OFDM Systems in Wireless Environments

Orthogonal Frequency Division Multiplexing (OFDM) systems are commonly used to mitigate frequency-selective multipath fading and provide high-speed data transmission. In this paper, we derive new union bounds on the error probability of a coded OFDM system in wireless environments. In particular, we consider convolutionally coded OFDM systems employing single and multiple transmit antennas over correlated block fading (CBF) channels with perfect channel state information (CSI). Results show that the new union bound is tight to simulation results. In addition, the bound accurately captures the effect of the correlation between sub-carriers channels. It is shown that as the channel becomes more frequency-selective, the performance get better due to the increased frequency diversity. Moreover, the bound also captures the effect of multi-antenna as space diversity. The proposed bounds can be applied for coded OFDM systems employing different coding schemes over different channel models.     

Optimal gate sizing using a self-tuning multi-objective framework

In this paper, we present a self-tuning multi-objective framework for geometric programming that provides a fine trade-off between the competing objectives. The significance of this framework is that the designer does not need to perform any tuning of weights of objectives. The proposed framework is applied to gate sizing and clock network buffer sizing problems. In gate sizing application, power consumption is reduced on average by 86% while delay sees only an increase of 34 ns. In clock network butter sizing application, our framework results in a significant reduction in power, 57%, and an improvement of 31 ps in skew.     

Neodymium-doped tantalum pentoxide waveguide lasers

The fabrication, spectroscopic properties, and laser performance of Nd/sup 3+/-doped Ta/sub 2/O/sub 5/ channel waveguide lasers are described. Lasing is obtained at both 1.066 and 1.375 /spl mu/m with threshold pump powers as low as 2.7 mW. The rib waveguides are reactive-ion-etched into Nd:Ta/sub 2/O/sub 5/ layers formed by reactive magnetron sputtering. These high-index low-loss rare-earth-doped waveguides are fabricated on silicon substrates and offer the potential for integration with photonic crystal structures for compact optical circuits.     

Efficient Image Transmission with Multi-Carrier CDMA

This paper presents a new approach for efficient image transmission over Multi-Carrier Code Division Multiple Access (MC-CDMA) systems using chaotic interleaving. The chaotic interleaving scheme based on Baker map is applied on the image data prior to transmission. The proposed approach transmits images over wireless channels, efficiently, without posing significant constraints on the wireless communication system bandwidth and noise. The performance of the proposed approach is further improved by applying Frequency-Domain Equalization (FDE) at the receiver. Two types of frequency-domain equalizers are considered and compared for performance evaluation of the proposed MC-CDMA system; the Zero-Forcing equalizer and the Linear Minimum Mean Square Error (LMMSE) equalizer. Several experiments are carried out to test the performance of the image transmission with different sizes over the proposed MC-CDMA system. Simulation results show that image transmission over wireless channels using the proposed chaotic interleaving approach is much more immune to noise and fading. Moreover this chaotic interleaving process adds a degree of encryption to the transmitted data. The results also show a noticeable performance improvement in terms of the Root Mean Square Error and Peak Signal-to-Noise Ratio values when applying FDE in the proposed approach, especially with the LMMSE equalizer.