Microcontrollers have been playing an important role in the embedded market. However, the designer of microcontroller based systems must deal with different languages and tools in the hardware and software development...
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We consider layered manufacturing as a fabrication technique for metallic, functional parts. While commercial machines still do not support metals, several research systems are already in existence in universities and...
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We consider layered manufacturing as a fabrication technique for metallic, functional parts. While commercial machines still do not support metals, several research systems are already in existence in universities and research laboratories. Such systems can create multi-material parts and can vary material composition within the layer. A key enabling technology for the automation of such layered manufacturing systems is heterogeneous solid modeling. Current CAD systems do not provide the capability to deal explicitly with material heterogeneity. We provide an overview of this new field, propose a method for modeling and representing material in addition to geometry and topology, and discuss some related research.
Patterns are reusable entities, which given solutions to generic and recurring problems. Patterns exist at different phases of Software Development Life Cycle (SDLC) namely analysis phase, design phase, coding phase e...
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Patterns are reusable entities, which given solutions to generic and recurring problems. Patterns exist at different phases of Software Development Life Cycle (SDLC) namely analysis phase, design phase, coding phase etc. Patterns in each phase are identified independently, though it is possible for patterns of one phase to be related to patterns in other phases. It is advantageous to capture the related patterns of different phases as a single unit. The paper proposes reusable Integrated Component (IC) of patterns to inter-relate patterns of different phases and to group them as a unit. This gives solutions for a recurring problem at various phases of SDLC.
The low power as a feature of a BIST scheme is a significant target due to quality as well as cost related issues. In this paper we examine the testability of multipliers based on Booth encoding and Wallace tree summa...
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ISBN:
(纸本)0769505252
The low power as a feature of a BIST scheme is a significant target due to quality as well as cost related issues. In this paper we examine the testability of multipliers based on Booth encoding and Wallace tree summation of the partial products and we present a methodology for deriving a low power Built In Self Test (BIST) scheme for them. We propose several design rules for designing the Wallace tree in order to be fully testable under the cell fault model. The proposed low power BIST scheme for the derived multipliers is achieved by: (a) introducing suitable Test Pattern Generators (TPG), (b) properly assigning the TPG outputs to the multiplier inputs and (c) significantly reducing the test set length with respect to earlier schemes. Our results indicate that the total power dissipated during test can be reduced from 64.8% to 72.8%, while the average power per test vector can be reduced from 19.6% to 27.4% and the peak power dissipation can be reduced from 16.8% to 36.0%, depending on the implementation of the basic cells and the size of the multiplier. The test application time is also significantly reduced, while the introduced BIST scheme implementation area is small.
Motivated by the problem of WDM routing in all–optical networks, we study the following NP–hard problem. We are given a directed binary tree T and a set R of directed paths on T. We wish to assign colors to paths in...
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This paper proposes a new method for block motion estimation based on center-biased hybrid search (CBHS) that employ a hybrid of a compact X-shaped search and a diamond search. It has only 9 search points per block fo...
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ISBN:
(纸本)0964345692
This paper proposes a new method for block motion estimation based on center-biased hybrid search (CBHS) that employ a hybrid of a compact X-shaped search and a diamond search. It has only 9 search points per block for the best case and, on average, 10.2 search points. CBHS is about 22.2 times faster than the full-search algorithm. This paper compares the popular suboptimal block-matching technique with CBHS in which both the processing speed and the accuracy of motion compensation are tested over widely used H.263 test video sequences.
In this paper, the hexagonal approach was proposed for modeling the functioning of cerebral cortex, especially, the processes of learning and recognition of visual information. This approach is based on the real neuro...
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In this paper, the hexagonal approach was proposed for modeling the functioning of cerebral cortex, especially, the processes of learning and recognition of visual information. This approach is based on the real neurophysiological data of the structure and functions of cerebral cortex. Distinctive characteristic of the proposed neural network is the hexagonal arrangement of excitatory connections between neurons that enable the spreading or cloning of information on the surface of neuronal layer. Cloning of information and modification of the weight of connections between neurons are used as the basic principles for learning and recognition processes. computer simulation of the hexagonal neural network indicated a suitability and prospectiveness of proposed approach in the creation, together with other modern concepts, of artificial neural network which will realize the most complicated processes that take place in the brain of living beings, such as short-term and long-term memory, episodic and declarative memory, recall, recognition, categorisation, thinking, and others. Described neural network was realized with computer program written on Delfi 3 language named the first order hexagon brainware (HBW-1).
Coherent random noise radar has been developed at the University of Nebraska for the detection and identification of shallow subsurface objects such as land mines. Other application ranges from remote sensing, synthet...
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Coherent random noise radar has been developed at the University of Nebraska for the detection and identification of shallow subsurface objects such as land mines. Other application ranges from remote sensing, synthetic aperture radar and high-resolution interferometer, to covert target tracking. In this paper, we describe the experimental investigation of a novel application of superfluorescent fiber or erbium doped fiber amplifier (EDFA) light sources(SFS) for random noise radar. The ultra-wide band noise coupled with the use of optical fiber delay lines makes SFS ideally suited for random noise radar applications. Optical fiber makes long and multiple-step delay lines of a few kilometers feasible. Its advantage includes being extremely low-loss, compact and light-weighted, and available at a much lower cost, while avoiding the dispersion and non-linearity associated with RF delay lines. We report the analysis and experimental results to characterize the resolution characteristics of the systems.
In this paper, we present a method for improving the performance of classical symbolic rules. This is achieved by introducing a type of hybrid rules, called neurules, which integrate neurocomputing into the symbolic f...
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In this paper, we present a method for improving the performance of classical symbolic rules. This is achieved by introducing a type of hybrid rules, called neurules, which integrate neurocomputing into the symbolic framework of production rules. Neurules are produced by converting existing symbolic rules. Each neurule is considered as an adaline unit, where weights are considered as significance factors. Each significance factor represents the significance of the associated condition in drawing the conclusion. A rule is fired when the corresponding adaline output becomes active. This significantly reduces the size of the rule base and, due to a number of heuristics used in the inference process, increases efficiency of the inferences.
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