A simplified method for modelling the effect of blinds on window thermal performance

An approximate method is presented for predicting the effect of a louvered blind on the centre‐glass thermal performance of a fenestration. The method combines a one‐dimensional heat transfer model with data from a numerical simulation of the window and blind. Sample results for a blind mounted on the indoor surface of a window show the effect of blind slat angle on heat transmission. Both summer and winter conditions are considered. The results show that a louvered blind can improve the U‐value of a standard double‐glazed window by up to 37%. Also, the radiation heat exchange with the room can be dramatically reduced (by up to 60%), which will improve the level of occupant comfort. However, there was found to be a trade‐off between U‐value and occupant comfort; placing the blind closer to the window improves the U‐value, but increases the radiation heat exchange with the room. The predictions from the present simplified method compare well with results from a full two‐dimensional computational fluid dynamics solution of the conjugate blind/window interaction. Copyright © 2005 John Wiley & Sons, Ltd.     

A fully integrated low-IF CMOS GPS radio with on-chip analog image rejection

A fully integrated Global Positioning System (GPS) radio is presented. Low-IF architecture was used for a high level of integration and low power consumption. An on-chip analog image-reject filter provides 18 dB of image-noise rejection to prevent noise figure (NF) degradation. With image rejection performed in the analog radio, a single-path (nonquadrature) output was used. The integrated synthesizer only requires an off-chip phase-locked loop-filter to function. Implemented in a 0.35-/spl mu/m 2P4M CMOS process, the integrated radio has a chip area of 9.5 mm/sup 2/. The radio operates over a wide range of voltage and temperature, from 2.2 to 3.6 V and from -40/spl deg/C to +85/spl deg/C and consumes 27 mW from a 2.2-V supply. The receiver has 4 dB NF.     

Indoor positioning: “an image-based crowdsource machine learning approach”

Multimedia Tools and Applications - Various technologies have been utilized today for recognizing client or user in the indoor areas. These technologies incorporate RSSI, Bluetooth Low Energy...     

Three-qubit Grover’s algorithm using superconducting quantum interference devices in cavity-QED

We present a scheme for the implementation of three-qubit Grover’s algorithm using four-level superconducting quantum interference devices (SQUIDs) coupled to a superconducting resonator. The scheme is based on resonant, off-resonant interaction of the cavity field with SQUIDs and application of classical microwave pulses. We show that adjustment of SQUID level spacings during the gate operations, adiabatic passage, and second-order detuning are not required that leads to faster implementation. We also show that the marked state can be searched with high fidelity even in the presence of unwanted off-resonant interactions, level decay, and cavity dissipation.     

Theoretical Investigation of Cubic BaVO<Subscript>3</Subscript> and LaVO<Subscript>3</Subscript> Perovskites via Tran–Blaha-Modified Becke–Johnson Exchange Potential Approach

The full potential linearized augmented plane wave method of density functional theory has been used to investigate the structural, electronic, magnetic and thermoelectric properties of cubic perovskites BaVO₃ and LaVO₃. The ferromagnetic ground state has been found to be stable by comparing the total energies of non-spin-polarized and spin-polarized calculations performed for optimized unit cells. For both compounds, the bond length and tolerance factor are also measured. From the band structures and density of states plots, it is found that both compounds are half-metallic. We found that the presence of V at the octahedral site of these perovskites develops exchange splitting through p-d hybridization, which results in a stable ferromagnetic state. The observed exchange splitting is further clarified from the magnetic moment, charge and spin of the anion and cations. Finally, we also presented the calculated thermoelectric properties of these materials, which show that half-metallic BaVO₃ and LaVO₃ materials are potential contenders for thermoelectric applications.     

Growth and optical properties of In x Ga1−x P nanowires synthesized by selective-area epitaxy

Ternary Ⅲ-Ⅴ nanowires (NWs) cover a wide range of wavelengths in the solar spectrum and would greatly benefit from being synthesized as position-controlled arrays for improved vertical yield,reprodudbility,and tunable optical absorption.Here,we report on successful selective-area epitaxy of metal-particle-free vertical InxGa1-xP NW arrays using metal-organic vapor phase epitaxy and detail their optical properties.A systematic growth study establishes the range of suitable growth parameters to obtain uniform NW growth over a large array.The optical properties of the NWs were characterized by room-temperature cathodoluminescence spectroscopy.Tunability of the emission wavelength from 870 nm to approximately 800 nm was achieved.Transmission electron microscopy and energy dispersive X-ray measurements performed on crosssection samples revealed a pure wurtzite crystal structure with very few stacking faults and a slight composition gradient along the NW growth axis.     

A new set of sufficient conditions based on coupling parameters for synchronization of Hopfield like Chaotic Neural Networks

In this paper, we consider a Hopfield like Chaotic Neural Networks which have both self-coupling and non-invertible activation functions. We show that the interactions between neurons can be used as a means of chaos generation or suppression to neuron’s outputs when more adaptability or stability is required. Furthermore, a new set of sufficient conditions based on coupling weights is proposed so that the synchronization of all neuron’s outputs with each other is guaranteed, when all neuron’s have identical activation functions. Finally, the effectiveness of the proposed approach is evaluated by performing simulations on three illustrative examples.     

Reinforcement Learning Based Algorithms for Average Cost Markov Decision Processes

This article proposes several two-timescale simulation-based actor-critic algorithms for solution of infinite horizon Markov Decision Processes with finite state-space under the average cost criterion. Two of the algorithms are for the compact (non-discrete) action setting while the rest are for finite-action spaces. On the slower timescale, all the algorithms perform a gradient search over corresponding policy spaces using two different Simultaneous Perturbation Stochastic Approximation (SPSA) gradient estimates. On the faster timescale, the differential cost function corresponding to a given stationary policy is updated and an additional averaging is performed for enhanced performance. A proof of convergence to a locally optimal policy is presented. Next, we discuss a memory efficient implementation that uses a feature-based representation of the state-space and performs TD(0) learning along the faster timescale. The TD(0) algorithm does not follow an on-line sampling of states but is observed to do well on our setting. Numerical experiments on a problem of rate based flow control are presented using the proposed algorithms. We consider here the model of a single bottleneck node in the continuous time queueing framework. We show performance comparisons of our algorithms with the two-timescale actor-critic algorithms of Konda and Borkar (1999) and Bhatnagar and Kumar (2004). Our algorithms exhibit more than an order of magnitude better performance over those of Konda and Borkar (1999).