Noise–Power Optimization of Incremental Data Converters

Incremental data converters (IDCs) are useful in instrumentation and measurement applications, where low-frequency analog signals need to be converted into digital form with high accuracy and low power dissipation. They are particularly well suited for applications where a single analog-digital converter is multiplexed between many channels. This paper proposes an exact design methodology for IDCs, which optimizes the signal-to-noise ratio of the converter under practical design constraints. The process also allows the designer to apportion the noise budget in an arbitrary manner between thermal and quantization noise. The design process is illustrated by an example which describes the optimization of a third-order multiplexed IDC.     

Cost-Efficient SHA Hardware Accelerators

This paper presents a new set of techniques for hardware implementations of Secure Hash Algorithm (SHA) hash functions. These techniques consist mostly in operation rescheduling and hardware reutilization, therefore, significantly decreasing the critical path and required area. Throughputs from 1.3 Gbit/s to 1.8 Gbit/s were obtained for the SHA implementations on a Xilinx VIRTEX II Pro. Compared to commercial cores and previously published research, these figures correspond to an improvement in throughput/slice in the range of 29% to 59% for SHA-1 and 54% to 100% for SHA-2. Experimental results on hybrid hardware/software implementations of the SHA cores, have shown speedups up to 150 times for the proposed cores, compared to pure software implementations.      

Bistable amphoteric centers in semiconductors

It is shown that, at thermodynamic equilibrium, the release of charge carriers from the localized states of bistable amphoteric centers into quasi-free states depends on the degree of compensation. This brings about different functional dependences of the concentration of free charge carriers on temperature. It is found that, in uncompensated semiconductors, the concentration of free charge carriers follows the same dependence in the case of bistable amphoteric centers and bistable amphoteric U ^? centers, although the distributions of charge carriers over the charge states and configurations are different for these types of centers. The results can be used for interpreting various experimental data insufficiently explained in the context of the traditional approach.     

AlGaN-based quantum-well heterostructures for deep ultraviolet light-emitting diodes grown by submonolayer discrete plasma-assisted molecular-beam epitaxy

Features of plasma-assisted molecular-beam epitaxy of AlGaN compounds at relatively low temperatures of the substrate (no higher than 740°C) and various stoichiometric conditions for growth of the nitrogen- and metal-enriched layers are studied. Discrete submonolayer epitaxy for formation of quantum wells and n-type blocking layers without varying the fluxes of components was used for the first time in the case of molecular- beam epitaxy with plasma activation of nitrogen for the nanostructures with the Al _x Ga_{1 ? x} N/Al _y Ga_{1 ? y} N quantum wells. Structural and optical properties of the Al _x Ga_{1 ? x} N layers in the entire range of compositions (x = 0–1) and nanostructures based on these layers are studied; these studies indicate that there is photoluminescence at room temperature with minimum wavelength of 230 nm. Based on the analysis of the photoluminescence spectra for bulk layers and nanoheterostructures and their temperature dependences, it is concluded that there are localized states in quantum wells. Using the metal-enriched layers grown on the c-Al₂O₃ substrates, heterostructures for light-emitting diodes with Al _x Ga_{1 ? x} N/Al _y Ga_{1 ? y} N quantum wells (x = 0.4–0.5, y = x + 0.15) were obtained and demonstrated electroluminescence in the ultraviolet region of the spectrum at the wavelength of 320 nm.     

A robust algorithm for text region detection in natural scene images

In this paper, a new method for detecting text regions in natural scene images is presented. The proposed algorithm is based on the segmentation of objects in a scene, followed by the identification of text objects by a support vector machine (SVM). First, to segment objects in the scene, the input image is separated into chromatic and achromatic regions according to the distribution of red, green and blue (RGB) elements, and different clustering algorithms are applied. Second, each object is transformed into the wavelet domain for multi-resolution analysis, and moment features of the wavelet coefficients are used in the SVM for the classification of text objects. The proposed approach provides robustness to non-uniform illumination by using different clustering algorithms according to the characteristics of the colour components in the segmentation. Also, moment features, used for classification, are invariant to the size, direction, shape and other properties of texts. Experimental results demonstrate the effectiveness of this approach.     

Effect of Bonder at Skin/Core Interface on the Mechanical Performances of Sandwich Structures Used in Marine Industry

The present work is aimed to extend the knowledge of mechanical properties of sandwich structures used for marine applications focusing on the possibility to increase the performances of such structures by adding a bonder at the skin/core interface. Therefore, three sandwich structures that are utilised in different structural components of a yacht were realised by manual lay-up. The mechanical characterisation was performed by flatwise compressive, edgewise compressive and three point flexural tests. The tests execution has allowed both to determine the mechanical performances and to understand the fracture mechanisms that take place when the bonder is added in the stacking sequence of the samples.     

Heat Transfer Analysis for Gas-to-Liquids Transportation Through Trans Alaska Pipeline

Gas-to-liquids (GTL) technology involves the conversion of natural gas to liquid hydrocarbons. In this article, theoretical studies have been presented to determine the feasibility of transporting GTL products through the Trans-Alaska Pipeline System (TAPS). To successfully transport GTL through TAPS, heat loss along the route must be carefully determined. This study presents heat transfer and fluid dynamic calculations to evaluate this feasibility. Because of heat loss, the fluid temperature decreases in the direction of flow and this affects the fluid properties, which in turn influence convection coefficient and pumping power requirements. The temperature and heat loss distribution along the pipeline at different locations have been calculated. Fairly good agreement with measured oil temperatures is observed. The powers required to pump crude oil and GTL individually, against various losses have been calculated. Two GTL transportation modes have been considered; one as a pure stream of GTL and the second as a commingled mixture with crude oil. These results show that the pumping power and heat loss for GTL are less than that of the crude oil for the same volumetric flow rate. Therefore, GTL can be transported through TAPS using existing equipment at pump stations.     

Implementation of adaptive critic-based neurocontrollers for turbogenerators in a multimachine power system

This paper presents the design and practical hardware implementation of optimal neurocontrollers that replace the conventional automatic voltage regulator (AVR) and the turbine governor of turbogenerators on multimachine power systems. The neurocontroller design uses a powerful technique of the adaptive critic design (ACD) family called dual heuristic programming (DHP). The DHP neurocontrollers' training and testing are implemented on the Innovative Integration M67 card consisting of the TMS320C6701 processor. The measured results show that the DHP neurocontrollers are robust and their performance does not degrade unlike the conventional controllers even when a power system stabilizer (PSS) is included, for changes in system operating conditions and configurations. This paper also shows that it is possible to design and implement optimal neurocontrollers for multiple turbogenerators in real time, without having to do continually online training of the neural networks, thus avoiding risks of instability.