A robust and highly scalable technique for measuring DC currents is described. The circuit consists largely of digital electronics except for a comparator and a passive RC filter. This simple structure is able to forc...
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A robust and highly scalable technique for measuring DC currents is described. The circuit consists largely of digital electronics except for a comparator and a passive RC filter. This simple structure is able to force a voltage at a circuit node while measuring the current that flows into it. The technique has been successfully demonstrated using a prototype constructed using a 0.35/spl mu/m CMOS chip.
The object-oriented design methodology has been manipulated to model the standard CMOS fabrication technology. Detecting and characterizing the objects and classes within the basic object-oriented features of encapsul...
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The object-oriented design methodology has been manipulated to model the standard CMOS fabrication technology. Detecting and characterizing the objects and classes within the basic object-oriented features of encapsulation, inheritance and polymorphism, as well as discussing the model framework and model characterization has been the main pursuits of this works. This modeling approach puts forth the chance of a fully automated fabrication system, with well-characterized hardware and reusable software. This model is also a promising candidate for enhancing the system performance to the minimum level required for fully integrated agent-oriented entities, which can reconfigure themselves for future technology generations.
In this research it is claimed that engineering education increases the positivistic tendencies of students regarding to the social problems. A theoretical background is given in the introduction and literature review...
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In this research it is claimed that engineering education increases the positivistic tendencies of students regarding to the social problems. A theoretical background is given in the introduction and literature review. Two hypotheses are constructed and a micro-questionnaire survey is performed to test the hypotheses. In the survey positivistic tendencies of engineering students and social science students are compared. The results are depicted and discussed in detail. One of the hypotheses was approved by the results while the other was rejected. It is concluded that the rejected hypothesis was not in accordance with the claim since it overlooked some factors effecting positivism. The results of the survey support the claim by stating that ’engineering students are more positivist than social science students’.
Heterogeneous networked clusters are being increasingly used as platforms for resource-intensive parallel and distributed applications. The fundamental underlying idea is to provide large amounts of processing capacit...
Heterogeneous networked clusters are being increasingly used as platforms for resource-intensive parallel and distributed applications. The fundamental underlying idea is to provide large amounts of processing capacity over extended periods of time by harnessing the idle and available resources on the network in an opportunistic manner. In this paper we present the design, implementation and evaluation of a framework that uses JavaSpaces to support this type of opportunistic adaptive parallel/distributed computing over networked clusters in a non-intrusive manner. The framework targets applications exhibiting coarse grained parallelism and has three key features: (1) portability across heterogeneous platforms, (2) minimal configuration overheads for participating nodes, and (3) automated system state monitoring (using SNMP) to ensure non-intrusive behavior. Experimental results presented in this paper demonstrate that for applications that can be broken into coarse-grained, relatively independent tasks, the opportunistic adaptive parallel computing framework can provide performance gains. Furthermore, the results indicate that monitoring and reacting to the current system state minimizes the intrusiveness of the framework.
A new algorithm based on semidefinite programming is presented for estimation of distributed source fields measured through a sensor array. The problem can be viewed as a subclass of inverse problems, which have been ...
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A new algorithm based on semidefinite programming is presented for estimation of distributed source fields measured through a sensor array. The problem can be viewed as a subclass of inverse problems, which have been extensively investigated in the literature. Our approach is based on the so called information based complexity (IBC) paradigm, which formalizes the notion of seeking the set of all solutions that are consistent with the observed data. We formulate our problem as a question of estimating the source up to a prespecified resolution (average source field in a neighborhood) from the observed data with optimal accuracy. We show that this problem is convex and can be reformulated as a semidefinite program.
The ability to efficiently discover information using partial knowledge (for example keywords, attributes or ranges) is important in large, decentralized, resource sharing distributed environments such as computationa...
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ISBN:
(纸本)9780769519654
The ability to efficiently discover information using partial knowledge (for example keywords, attributes or ranges) is important in large, decentralized, resource sharing distributed environments such as computational grids and peer-to-peer (P2P) storage and retrieval systems. This paper presents a P2P information discovery system that supports flexible queries using partial keywords and wildcards, and range queries. It guarantees that all existing data elements that match a query are found with bounded costs in terms of number of messages and number of peers involved. The key innovation is a dimension reducing indexing scheme that effectively maps the multidimensional information space to physical peers. The design, implementation and experimental evaluation of the system are presented.
In this paper, we investigate the use of dynamic Bayesian networks (DBNs) to explicitly represent models of hidden features, such as articulatory or other phonological features, for automatic speech recognition. In pr...
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In this paper, we investigate the use of dynamic Bayesian networks (DBNs) to explicitly represent models of hidden features, such as articulatory or other phonological features, for automatic speech recognition. In previous work using the idea of hidden features, the representation has typically been implicit, relying on a single hidden state to represent a combination of features. We present a class of DBN-based hidden feature models, and show that such a representation can be not only more expressive but also more parsimonious. We also describe a way of representing the acoustic observation model with fewer distributions using a product of models, each corresponding to a subset of the features. Finally, we describe our recent experiments using hidden feature models on the Aurora 2.0 corpus.
The lossy earth return path influences significantly the electrical parameters of underground power cables, especially in cases where transient simulation models are of interest. The use of approximations for the calc...
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The lossy earth return path influences significantly the electrical parameters of underground power cables, especially in cases where transient simulation models are of interest. The use of approximations for the calculation of earth correction terms proves to be inaccurate at high frequencies or low earth resistivities. The infinite integral terms representing the earth influence are high oscillatory in cases of underground cables and therefore difficult to integrate numerically. The scope of this paper is to present and compare results, obtained by a novel numerically stable and efficient integration scheme to those obtained by a finite element method formulation for several single core cable configurations and for homogeneous and multi-layered earth. Significant differences between impedances are recorded, especially for high frequencies and low earth resistivities.
This paper presents a novel clustering technique known as adaptive double self-organizing map (ADSOM). ADSOM has a flexible topology and perform clustering and cluster visualization simultaneously, thereby requiring n...
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This paper presents a novel clustering technique known as adaptive double self-organizing map (ADSOM). ADSOM has a flexible topology and perform clustering and cluster visualization simultaneously, thereby requiring no a priori knowledge about the number of clusters. ADSOM combines features of the popular self-organizing map (SOM) with two-dimensional position vectors, which serve as a visualization tool to accurately determine the number of clusters present in the data. ADSOM updates its free parameters during training and it allows convergence of its position vectors to a fairly consistent number of clusters provided that its initial number of nodes is greater than the expected number of clusters. A novel index is introduced based on hierarchical clustering of the final locations of position vectors. The index allows automatic detection of the number of clusters, thereby reducing human error that could be incurred from counting cluster visually. The reliance of ADSOM in identifying the number of clusters is proven by applying it to publicly available yeast gene expression data.
DNA microarray technology enables a parallel analysis of the expression of genes in an organism. The wealth of spatio-temporal data generated by this technology allows researchers to potentially reverse engineer the g...
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DNA microarray technology enables a parallel analysis of the expression of genes in an organism. The wealth of spatio-temporal data generated by this technology allows researchers to potentially reverse engineer the genetic network. Fuzzy logic has been proposed as a method to analyze the relationships between genes. This method can identify interacting genes that fit a known fuzzy model of gene interaction by testing all combinations of gene expression profiles. However, this approach is slow and computationally complex. This paper introduces improvements made in terms of reducing computation time and generalizing the gene regulatory model to accommodate co-activators and co-repressors. Improvement in computation time is achieved by using clustering as a pre-processing method, thereby reducing the total number of gene combinations analyzed. This will allow the algorithm to run in a shorter amount of time with minimal effect on the results. The proposed technique will pave the way towards the creation of a generalized gene interaction model that can accommodate any combination of genes.
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