Urban radiowave propagation: a 3-D path-integral wave analysis

A discussion concerning the need for three-dimensional (3-D) urban radiowave propagation models is presented and followed by a review of previously published work on this topic using the asymptotic path-integral technique. The limitations and advantages of this technique are explained and it is applied to study diffraction by a small number of canonical geometries. The validity of this technique is verified by comparison with controlled laboratory measurements taken at millimetric wave frequencies. Finally, its ability to classify field components according to their distribution in space is employed in order to analyze the observed field strength distributions in the model environments     

A technique for extracting physiological parameters and therequired input function simultaneously from PET image measurements:theory and simulation study

Positron emission tomography (PET) is an important tool for enabling quantification of human brain function. However, quantitative studies using tracer kinetic modeling require the measurement of the tracer time-activity curve in plasma (PTAC) as the model input function. It is widely believed that the insertion of arterial lines and the subsequent collection and processing of the biomedical signal sampled from the arterial blood are not compatible with the practice of clinical PET, as it is invasive and exposes personnel to the risks associated with the handling of patient blood and radiation dose. Therefore, it is of interest to develop practical noninvasive measurement techniques for tracer kinetic modeling with PET. In this paper, a technique is proposed to extract the input function together with the physiological parameters from the brain dynamic images alone. The identifiability of this method is tested rigorously by using Monte Carlo simulation. The results show that the proposed method is able to quantify all the required parameters by using the information obtained from two or more regions of interest (ROIs) with very different dynamics in the PET dynamic images. There is no significant improvement in parameter estimation for the local cerebral metabolic rate of glucose (LCMRGlc) if there are more than three ROIs. The proposed method can provide very reliable estimation of LCMRGlc, which is our primary interest in this study     

Performance analysis of adaptive interleaving for OFDM systems

We proposed a novel interleaving technique for orthogonal frequency division multiplexing (OFDM), namely adaptive interleaving, which can break the bursty channel errors more effectively than traditional block interleaving. The technique rearranges the symbols according to instantaneous channel state information of the OFDM subcarriers so as to reduce or minimize the bit error rate (BER) of each OFDM frame. It is well suited to OFDM systems because the channel state information (CSI) values of the whole frame could be estimated at once when transmitted symbols are framed in the frequency dimension. Extensive simulations show that the proposed scheme can greatly improve the performance of the coded modulation systems utilizing block interleaving. Furthermore, we show that the adaptive interleaving out performs any other static interleaving schemes, even in the fast fading channel (with independent fading between symbols). We derived a semi-analytical bound for the BER of the adaptive interleaving scheme under correlated Rayleigh fading channels. Furthermore, we discussed the transmitter-receiver (interleaving pattern) synchronization problem     

Semiautomatic implementation of protocols using an Estelle-Ccompiler

The basic ideas underlying an Estelle-C compiler, which accepts an Estelle protocol specification and produces a protocol implementation in C, are presented. The implementation of the ISO (International Organization for Standardization) class-2 transparent protocol, using the semiautomatic approach, is discussed. A manual implementation of the protocol is performed and compared to the semiautomatic implementation. The semiautomatic approach to protocol implementation offers several advantages over the conventional manual one, including correctness and modularity in protocol implementation code, conformance to the specification, and reduction in implementation time. Finally, ongoing development of a new Estelle-C compiler is presented     

The application of nonlinear structures to the reconstruction ofbinary signals

The problem of reconstructing digital signals which have been passed through a dispersive channel and corrupted with additive noise is discussed. The problems encountered by linear equalizers under adverse conditions on the signal-to-noise ratio and channel phase are described. By considering the equalization problem as a geometric classification problem the authors demonstrate how these difficulties can be overcome by utilizing nonlinear classifiers as channel equalizers. The manner in which neural networks can be utilized as adaptive channel equalizers is described, and simulation results which suggest that the neural network equalizers offer a performance which exceeds that of the linear structures, particularly in the high-noise environment, are presented     

Pressurized fluidized-bed hydro retort ing of raw and beneficiated Eastern oil shales

Bench-scale tests were conducted with raw and beneficiated shales in an advanced multi-purpose research reactor. Raw Alabama shale and raw and beneficiated Indiana shales were retorted at 515 °C using hydrogen pressures of 4 and 7 MPa. Shale feed rates were 15 to 34 kg h⁻¹. High oil yields and carbon conversions were achieved in all tests. Oil yield from Alabama shale hydroretorted at 7 MPa was 200% of Fischer assay. Raw and beneficiated Indiana shales hydroretorted at 7 MPa produced oil yields of 170 and 195% of Fischer assay respectively. Total carbon conversions were >70% for all tests conducted at 7 MPa.     

Architectures for Silicon Nanoelectronics and Beyond

Although nanoelectronics won't replace CMOS for some time, research is needed now to develop the architectures, methods, and tools to maximally leverage nanoscale devices and terascale capacity. Addressing the complementary architectural and system issues involved requires greater collaboration at all levels. The effective use of nanotechnology calls for total system solutions     

Articulatory-feature-based confidence measures

Confidence measures are computed to estimate the certainty that target acoustic units are spoken in specific speech segments. They are applied in tasks such as keyword verification or utterance verification. Because many of the confidence measures use the same set of models and features as in recognition, the resulting scores may not provide an independent measure of reliability. In this paper, we propose two articulatory feature (AF) based phoneme confidence measures that estimate the acoustic reliability based on the match in AF properties. While acoustic-based features, such as Mel-frequency cepstral coefficients (MFCC), are widely used in speech processing, some recent works have focus on linguistically based features, such as the articulatory features that relate directly to the human articulatory process which may better capture speech characteristics. The articulatory features can either replace or complement the acoustic-based features in speech processing. The proposed AF-based measures in this paper were evaluated, in comparison and in combination, with the HMM-based scores on phoneme and keyword verification tasks using children’s speech collected for a computer-based English pronunciation learning project. To fully evaluate their usefulness, the proposed measures and combinations were evaluated on both native and non-native data; and under field test conditions that mis-matches with the training condition. The experimental results show that under the different environments, combinations of the AF scores with the HMM-based scores outperforms HMM-based scores alone on phoneme and keyword verification.     

On a responsive replenishment system: a fuzzy logic approach

In today's competitive business environment, it is important that customers are able to obtain their preferred items in the shops they visit, particularly for convenience store chains such as 7–Eleven where popular items are expected to be readily available on the shelves of the stores for buyers. To minimize the cost of running such store chains, it is essential that stocks be kept to a minimum and at the same time large varieties of popular items are available for customers. In this respect, the replenishment system needs to be able to cope with the taxing demands of minimal inventory but at the same time keeping large varieties of needed items. This paper proposes a replenishment system which is able to respond to the fluctuating demands of customers and provide a timely supply of needed items in a cost–effective way. The proposed system embraces the principle of fuzzy logic which is able to deal with uncertainties by virtue of its fuzzy rules reasoning mechanism, thereby leveraging the responsiveness of the entire replenishment system for the chain stores. To validate the feasibility of the approach, a case study has been conducted in an emulated environment with promising results.