We present the use of molecular beacons as sensitive indicators in microfluidic bioMEM devices. A method has been developed to study mixing and hybridization of molecular beacons to target nucleic acids in real time i...
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We present the use of molecular beacons as sensitive indicators in microfluidic bioMEM devices. A method has been developed to study mixing and hybridization of molecular beacons to target nucleic acids in real time in a microfluidic channel. This method allows quantification of DNA and RNA molecules in solution, i.e., without the prerequisite of an immobilization step necessary in most other hybridization formats. The detection limit for DNA was determined to be in the order of femtomoles. Our results suggest the feasibility of using molecular beacon hybridization in microfluidic devices for the detection of pathogenic bacteria in environmental and medical fluids.
Energy-efficient communication is critical for increasing life of power limited wireless ad hoc networks. There has been considerable interest in minimum energy broadcast operations. In this paper, we develop bounds a...
Energy-efficient communication is critical for increasing life of power limited wireless ad hoc networks. There has been considerable interest in minimum energy broadcast operations. In this paper, we develop bounds and an algorithm for minimizing energy cost for broadcasting from any source to all other nodes in the network. Most prior work have used simpler model for energy cost for wireless communications by accounting only the analog radiation cost for transmission and ignored the fixed cost for electronics in transmission and reception circuitry in nodes. Furthermore, in a network it is possible for some node pairs not be able to communicate directly even though they are in their radio ranges due to obstacles present in the terrain of the network.
作者：
Vieira, Luis CarlosPrograma de Pós-Graduação em Engenharia Elétrica e Informática Industrial
Departamento de Eletrônica e Telecomunicações (Graduate Program in Electrical Engineering and Industrial Computer Science Department of Electronics and Telecommunications) Centro Federal de Educação Tecnológica do Paraná (Federal Center of Technological Education of Paraná) Curitiba Brazil
We classify an input space according to the outputs of a real-valued function. The function is not given, but rather examples of the function. We contribute a consistent classifier that avoids the unnecessary complexi...
ISBN:
(纸本)0262122413
We classify an input space according to the outputs of a real-valued function. The function is not given, but rather examples of the function. We contribute a consistent classifier that avoids the unnecessary complexity of estimating the function.
In this work-in-progress paper, we report on a rigorous, time-condensed program to prepare graduates with a Bachelor of Science in physics for graduate study in electrical, computer, and telecommunications engineering...
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In this work-in-progress paper, we report on a rigorous, time-condensed program to prepare graduates with a Bachelor of Science in physics for graduate study in electrical, computer, and telecommunications engineering. Due to the ongoing favorable job market for engineers, we have found it increasingly difficult to recruit quality students into our graduate programs. In fact, this is recognized as a nationwide problem. We have identified the national pool of undergraduate physics majors as a prospective group of students who can excel in graduate engineering studies. We have established a rigorous eight-week curriculum, to be offered during the summer term, that provides the necessary prerequisite material, including: microprocessors, signals and systems, electronics, and an integrated laboratory experience. This "summer academy" is designed to eliminate the need for normal session leveling classes that students without electrical or computerengineering degrees are required to complete, thereby reducing the overall time required to get a graduate degree.
The low voltage customers of an electric energy distribution system have today a great variety of modern consumption products in their homes, which may be considered as potential sources of harmonic current generation...
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A new model describing the temporal transitions of atmospheric tilt is described and utilized in a Bayesian tilt-estimation algorithm. Using this model, images are synthesized from short-exposure data demonstrating th...
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This paper addresses the problem of robust /spl Hscr//sub /spl infin// filtering for linear discrete-time systems subject to parameter uncertainties in the system state-space model and with multiple time delays in the...
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This paper addresses the problem of robust /spl Hscr//sub /spl infin// filtering for linear discrete-time systems subject to parameter uncertainties in the system state-space model and with multiple time delays in the state variables. The uncertain parameters are supposed to belong to a given convex bounded polyhedral domain. A methodology is developed to design a stable linear filter that assures asymptotic stability and a prescribed /spl Hscr//sub /spl infin// performance for the filtering error, irrespective of the uncertainty and the time delays. The proposed design is given in terms of linear matrix inequalities, which has the advantage in that it can be implemented numerically very efficiently.
A neural-statistical approach to biomedical image interpolation using generalized regression neural networks is presented. These networks are basis function architectures that approximate any arbitrary function betwee...
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ISBN:
(纸本)0780370449
A neural-statistical approach to biomedical image interpolation using generalized regression neural networks is presented. These networks are basis function architectures that approximate any arbitrary function between input and output vectors directly from training samples, and with any desired degree of smoothness, and thus can be used for multidimensional interpolation. Experimental results compare favorably with other interpolation techniques. Because of their flexibility and ease of training, generalized regression networks can be used to complement existing approaches, and can be especially useful for post-registration image fusion and visualization.
A non-uniform subband adaptive structure with critical sampling of the subband signals is derived. With the assumption of non-overlapping between non-adjacent analysis filters, the resulting structure yields exact mod...
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A non-uniform subband adaptive structure with critical sampling of the subband signals is derived. With the assumption of non-overlapping between non-adjacent analysis filters, the resulting structure yields exact modeling of an arbitrary FIR system. An LMS-type adaptation algorithm, which minimizes the sum of the subband squared-errors, is obtained for updating the coefficients of the proposed structure, resulting in significant convergence rate improvement for colored input signals when compared to the fullband LMS algorithm. computer simulations illustrate the convergence behavior of the proposed non-uniform subband adaptive filter in the applications of system identification and acoustic echo cancellation.
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