Novel Relay Selection Rules for Average Interference-Constrained Cognitive AF Relay Networks

Cooperative relaying combined with selection exploits spatial diversity to significantly improve the performance of interference-constrained secondary users in an underlay cognitive radio (CR) network. However, unlike conventional relaying, the state of the links between the relay and the primary receiver affects the choice of the relay. Further, while the optimal amplify-and-forward (AF) relay selection rule for underlay CR is well understood for the peak interference-constraint, this is not so for the less conservative average interference constraint. For the latter, we present three novel AF relay selection (RS) rules, namely, symbol error probability (SEP)-optimal, inverse-of-affine (IOA), and linear rules. We analyze the SEPs of the IOA and linear rules and also develop a novel, accurate approximation technique for analyzing the performance of AF relays. Extensive numerical results show that all the three rules outperform several RS rules proposed in the literature and generalize the conventional AF RS rule.

Non-invasive pressure monitoring by hoop strain using Fiber Bragg Grating sensor

Non-invasive, real-time dynamic monitoring of pressure inside a column with the aid of Fiber Bragg Grating (FBG) sensor is presented in the present work. A bare FBG sensor is adhered on the circumference of a pressure column normal to its axis, which has the ability to acquire the hoop strain induced by the pressure variation inside the column. Pressure induced hoop strain response obtained using FBG sensor is validated against the pressure measurements obtained from conventional pressure gauge. Further, a protrusion setup on the outer surface of the column has been proposed over which a secondary FBG sensor is bonded normal to its axis, in order to increase the gauge length of this FBG sensor. This is carried out in order to validate the variation in sensitivity of the protrusion bonded FBG sensor compared to the bare FBG sensor bonded over the surface. A comparative study is done between the two FBG sensors and a conventional pressure gauge in order to establish the capacity of FBG sensor obtained hoop strain response for pressure monitoring inside the column.

Ultra-sensitive pressure dependence of bandgap of rutile-GeO2 revealed by many body perturbation theory

The reported values of bandgap of rutile GeO2 calculated by the standard density functional theory within local-density approximation (LDA)/generalized gradient approximation (GGA) show a wide variation (similar to 2 eV), whose origin remains unresolved. Here, we investigate the reasons for this variation by studying the electronic structure of rutile-GeO2 using many-body perturbation theory within the GW framework. The bandgap as well as valence bandwidth at Gamma-point of rutile phase shows a strong dependence on volume change, which is independent of bandgap underestimation problem of LDA/GGA. This strong dependence originates from a change in hybridization among O-p and Ge-(s and p) orbitals. Furthermore, the parabolic nature of first conduction band along X-Gamma-M direction changes towards a linear dispersion with volume expansion. (C) 2015 AIP Publishing LLC.

Combinatorial selection of molecular conformations and supramolecular synthons in quercetin cocrystal landscapes: a route to ternary solids

The crystallization of 28 binary and ternary cocrystals of quercetin with dibasic coformers is analyzed in terms of a combinatorial selection from a solution of preferred molecular conformations and supramolecular synthons. The crystal structures are characterized by distinctive O-H center dot center dot center dot N and O-H center dot center dot center dot O based synthons and are classified as nonporous, porous and helical. Variability in molecular conformation and synthon structure led to an increase in the energetic and structural space around the crystallization event. This space is the crystal structure landscape of the compound and is explored by fine-tuning the experimental conditions of crystallization. In the landscape context, we develop a strategy for the isolation of ternary cocrystals with the use of auxiliary template molecules to reduce the molecular and supramolecular `confusion' that is inherent in a molecule like quercetin. The absence of concomitant polymorphism in this study highlights the selectivity in conformation and synthon choice from the virtual combinatorial library in solution.

Sampling Period Selection of Control Application Connected to FlexRay Bus

Flexray is a high speed communication protocol designed for distributive control in automotive control applications. Control performance not only depends on the control algorithm but also on the scheduling constraints in communication. A balance between the control performance and communication constraints must required for the choice of the sampling rates of the control loops in a node. In this paper, an optimum sampling period of control loops to minimize the cost function, satisfying the scheduling constraints is obtained. An algorithm to obtain the delay in service of each task in a node of the control loop in the hyper period has been also developed. (C) 2015 The Authors. Published by Elsevier B.V.

Atmospheric pressure plasma chemical vapor deposition reactor for 100 mm wafers, optimized for minimum contamination at low gas flow rates

Gas discharge plasmas used for thinfilm deposition by plasma-enhanced chemical vapor deposition (PECVD) must be devoid of contaminants, like dust or active species which disturb the intended chemical reaction. In atmospheric pressure plasma systems employing an inert gas, the main source of such contamination is the residual air inside the system. To enable the construction of an atmospheric pressure plasma (APP) system with minimal contamination, we have carried out fluid dynamic simulation of the APP chamber into which an inert gas is injected at different mass flow rates. On the basis of the simulation results, we have designed and built a simple, scaled APP system, which is capable of holding a 100 mm substrate wafer, so that the presence of air (contamination) in the APP chamber is minimized with as low a flow rate of argon as possible. This is examined systematically by examining optical emission from the plasma as a function of inert gas flow rate. It is found that optical emission from the plasma shows the presence of atmospheric air, if the inlet argon flow rate is lowered below 300 sccm. That there is minimal contamination of the APP reactor built here, was verified by conducting an atmospheric pressure PECVD process under acetylene flow, combined with argon flow at 100 sccm and 500 sccm. The deposition of a polymer coating is confirmed by infrared spectroscopy. X-ray photoelectron spectroscopy shows that the polymer coating contains only 5% of oxygen, which is comparable to the oxygen content in polymer deposits obtained in low-pressure PECVD systems. (C) 2015 AIP Publishing LLC.

Optimum Parameter Selection in Sparse Reconstruction of Frequency-Domain Optical-Coherence Tomography Signals

For a multilayered specimen, the back-scattered signal in frequency-domain optical-coherence tomography (FDOCT) is expressible as a sum of cosines, each corresponding to a change of refractive index in the specimen. Each of the cosines represent a peak in the reconstructed tomogram. We consider a truncated cosine series representation of the signal, with the constraint that the coefficients in the basis expansion be sparse. An l(2) (sum of squared errors) data error is considered with an l(1) (summation of absolute values) constraint on the coefficients. The optimization problem is solved using Weiszfeld's iteratively reweighted least squares (IRLS) algorithm. On real FDOCT data, improved results are obtained over the standard reconstruction technique with lower levels of background measurement noise and artifacts due to a strong l(1) penalty. The previous sparse tomogram reconstruction techniques in the literature proposed collecting sparse samples, necessitating a change in the data capturing process conventionally used in FDOCT. The IRLS-based method proposed in this paper does not suffer from this drawback.

Training-Based Antenna Selection for PER Minimization: A POMDP Approach

This paper considers the problem of receive antenna selection (AS) in a multiple-antenna communication system having a single radio-frequency (RF) chain. The AS decisions are based on noisy channel estimates obtained using known pilot symbols embedded in the data packets. The goal here is to minimize the average packet error rate (PER) by exploiting the known temporal correlation of the channel. As the underlying channels are only partially observed using the pilot symbols, the problem of AS for PER minimization is cast into a partially observable Markov decision process (POMDP) framework. Under mild assumptions, the optimality of a myopic policy is established for the two-state channel case. Moreover, two heuristic AS schemes are proposed based on a weighted combination of the estimated channel states on the different antennas. These schemes utilize the continuous valued received pilot symbols to make the AS decisions, and are shown to offer performance comparable to the POMDP approach, which requires one to quantize the channel and observations to a finite set of states. The performance improvement offered by the POMDP solution and the proposed heuristic solutions relative to existing AS training-based approaches is illustrated using Monte Carlo simulations.

ADVANCED LOW PRESSURE CYCLE FOR CONCENTRATED SOLAR POWER GENERATION

Turbine inlet pressures of similar to 300 bar in case of CO2 based cycles call for redesigning the cycle in such a way that the optimum high side pressures are restricted to the discharge pressure limits imposed by currently available commercial compressors (similar to 150 bar) for distributed power generation. This leads to a cycle which is a combination of a transcritical condensing and a subcritical cycle with an intercooler and a bifurcation system in it. Using a realistic thermodynamic model, it is predicted that the cycle with the working fluid as a non-flammable mixture of 48.5 % propane and rest CO2 delivers similar to 37.2 % efficiency at 873 K with a high and a low side pressure of 150 and 26 bar respectively. This is in contrast to the best efficiency of similar to 36.1 % offered by a transcritical condensing cycle with the same working fluid at a high side pressure of similar to 300 bar

Comparative high pressure Raman studies on perfluorohexane and perfluoroheptane

High pressure Raman spectroscopic studies on perfluorohexane and perfluoroheptane have performed up to 12 GPa. Perfluorohexane under goes two pressure induced transitions: (1) liquid-solid transition at 1.6 GPa and (2) solid-solid transition at 8.2 GPa. On the contrary, perfluoroheptane under goes three phase transitions, they are as follows: (1) liquid-solid transition at 1.3 GPa, (2) intermediate solid I transition at 3 GPa, (3) solid II transition at 7 GPa. The change in slope (d omega/dP) shows that the solid I transition at 3.0 GPa could be the conversion of mid-gauche defect into trans conformers for perfluoroheptane. The pressure induced Raman spectra and the behavior of individual band with pressure shows that the solid phase comprises more than one conformer beyond crystallization. The intensity ratio for both the compounds shows that the high pressure phase beyond 8.2 and 7.0 GPa tends to have close packing with distorted all-trans conformers. (C) 2015 Elsevier B.V. All rights reserved.

Stabilization of the high-temperature and high-pressure cubic phase of ZnO by temperature-controlled milling

The reversible transition of wurtzite to rock salt phase under pressure is well reported in literature. The cubic phase is unstable under ambient conditions both in the bulk and in nanoparticles. This paper reports defect-induced stabilization of cubic ZnO phase in sub 20 nm ZnO particles and explores their optical properties. The size reduction was achieved by ball milling in a specially designed mill which allows a control of the milling temperature. The process of synthesis involved both variation of milling temperature (including low temperature similar to 150 K) and impact pressure. We show that these have profound influence in the introduction of defects and stabilization of the cubic phase. A molecular dynamics simulation is presented to explain the observed results. The measured optical properties have further supported the observations of defect-induced stabilization of cubic ZnO and reduction in particle size.

Die Filling Behaviour of Semi Solid A356 Al Alloy Slurry During Rheo Pressure Die Casting

The present work discusses the findings obtained from simulations of semi solid die filling of a steering knuckle, prior to actual component development using in-house developed rheo pressure die casting system. Die filling capability of A356 Al alloy at semi-solid state has been investigated using commercial software Flow-3Dcast to optimise the pouring temperature of semi-solid slurry into the die cavity, while all other variables such as gating design, die preheat temperature and injection velocity are kept constant based on the prior knowledge obtained from trial numerical simulations and experimentation. Efforts have been made to nullify the essence of costly, time consuming experiments towards obtaining high-quality castings out of the findings obtained from numerical simulations. The optimum pouring temperature identified in the present study is 610 A degrees C, which facilitates smoother slurry flow, minimum surface defect concentration, uniform temperature field and solid fraction distribution within the component cavity.

A Bacterial Foraging Optimization and Learning Automata Based Feature Selection for Motor Imagery EEG Classification

Selection of relevant features is an open problem in Brain-computer interfacing (BCI) research. Sometimes, features extracted from brain signals are high dimensional which in turn affects the accuracy of the classifier. Selection of the most relevant features improves the performance of the classifier and reduces the computational cost of the system. In this study, we have used a combination of Bacterial Foraging Optimization and Learning Automata to determine the best subset of features from a given motor imagery electroencephalography (EEG) based BCI dataset. Here, we have employed Discrete Wavelet Transform to obtain a high dimensional feature set and classified it by Distance Likelihood Ratio Test. Our proposed feature selector produced an accuracy of 80.291% in 216 seconds.

Effect of absolute pressure on flow through a textured hydrophobic microchannel

The potential of textured hydrophobic surfaces to provide substantial drag reduction has been attributed to the presence of air bubbles trapped on the surface cavities. In this paper, we present results on water flow past a textured hydrophobic surface, while systematically varying the absolute pressure close to the surface. Trapped air bubbles on the surface are directly visualized, along with simultaneous pressure drop measurements across the surface in a microchannel configuration. We find that varying the absolute pressure within the channel greatly influences the trapped air bubble behavior, causing a consequent effect on the pressure drop (drag). When the absolute pressure within the channel is maintained below atmospheric pressure, we find that the air bubbles grow in size, merge and eventually detach from the surface. This growth and subsequent merging of the air bubbles leads to a substantial increase in the pressure drop. On the other hand, a pressure above the atmospheric pressure within the channel leads to gradual shrinkage and eventual disappearance of trapped air bubbles. We find that in this case, air bubbles do cause reduction in the pressure drop with the minimum pressure drop (or maximum drag reduction) occurring when the bubbles are flush with the surface. These results show that the trapped air bubble dynamics and the pressure drop across a textured hydrophobic microchannel are very significantly dependent on the absolute pressure within the channel. The results obtained hold important implications toward achieving sustained drag reduction in microfluidic applications.

A Study of Pressure-Dependent Squeeze Film Stiffness as a Resonance Modulator Using Static and Dynamic Measurements

We report on the resonant frequency modulation of inertial microelectromechanical systems (MEMS) structures due to squeeze film stiffness over a range of working pressures. Squeeze film effects have been studied extensively, but mostly in the context of damping and Q-factor determination of dynamic MEMS structures, typically suspended over a fixed substrate with a very thin air gap. Here, we show with experimental measurements and analytical calculations how the pressure-dependent air springs (squeeze film stiffness) change the resonant frequency of an inertial MEMS structure by as much as five times. For capturing the isolated effect of the squeeze film stiffness, we first determine the static stiffness of our structure with atomic force microscope probing and then study the effect of the air spring by measuring the dynamic response of the structure, thus finding the resonant frequencies while varying the air pressure from 1 to 905 mbar. We also verify our results by analytical and Finite Element Method calculations. Our findings show that the pressure-dependent squeeze film stiffness can affect a rather huge range of frequency modulation (>400%) and, therefore, can be used as a design parameter for exploiting this effect in MEMS devices. 2014-0310]