Current mammographic screening for breast cancer is less effective for younger women. To complement mammography for premenopausal women, we investigated the feasibility screening test using 98 blood serum proteins. Be...
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Current mammographic screening for breast cancer is less effective for younger women. To complement mammography for premenopausal women, we investigated the feasibility screening test using 98 blood serum proteins. Because the data set was very noisy and contained only weak features, we used a classifier designed for noisy data: decision fusion. Decision fusion outperformed both a support vector machine (SVM) and linear regression with forward stepwise feature selection on all three two-class classification tasks: normal tissue vs. cancer, normal tissue vs. benign lesions, and benign lesions vs. cancer. Decision fusion detected cancer moderately well (AUC=0.84 on normal vs. cancer), demonstrating promise as a screening tool. Decision fusion also detected benign lesions similarly well (AUC=0.83 on normal vs. benign lesions) and was the only classifier to achieve any success in separating benign from malignant lesions (AUC=0.64 on benign vs. cancer). The classification results suggest that the assayed proteins are more indicative of a secondary effect, such as immune response, rather than specific for breast cancer. In conclusion, the decision fusion classifier demonstrated some promise in detecting breast lesions and outperformed other classifiers, especially for the very noisy classification problem of distinguishing benign from malignant lesions.
The microwave plasma chemical vapor deposition (MPCVD) method is capable of synthesizing various forms of carbon allotropes such as diamond, carbon nanotubes (CNTs), and diamondlike carbon (DLC) while varying the grow...
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We present an evolutionary algorithm for the inference of context-free grammars from positive and negative examples. The algorithm is based on genetic programming and uses a local optimization operator that is capable...
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OBF (Orthonormal Basis Function) Fuzzy models have shown to be a promising approach to the areas of nonlinear system identification and control since they exhibit several advantages over those dynamic model topologies...
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Historically, electricalengineering students have been very proficient in the application of mathematics. At California State University we have experienced, recently, a negative shift of mathematical interest and th...
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We present an evolutionary algorithm for the inference of context-free grammars from positive and negative examples. The algorithm is based on genetic programming and uses a local optimization operator that is capable...
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We present an evolutionary algorithm for the inference of context-free grammars from positive and negative examples. The algorithm is based on genetic programming and uses a local optimization operator that is capable of improving the learning task. Ordinary genetic operators are modified so as to bias the search. The system was evaluated using Tomitas language examples and results were compared with another similar approach. Results show that the proposed approach is promising and more robust than the other one.
OBF (Orthonormal Basis Function) Fuzzy models have shown to be a promising approach to the areas of nonlinear system identification and control since they exhibit several advantages over those dynamic model topologies...
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ISBN:
(纸本)9780769531960
OBF (Orthonormal Basis Function) Fuzzy models have shown to be a promising approach to the areas of nonlinear system identification and control since they exhibit several advantages over those dynamic model topologies usually adopted in the literature. Although encouraging application results have been obtained, no automatic procedure had yet been developed to optimize the design parameters of these models. This paper elaborates on the use of a genetic algorithm (GA) especially designed for this task, in which a fitness function based on the Akaike information criterion plays a key role by considering both model accuracy and parsimony aspects. The use of linear (actually affine) and nonlinear local models is also investigated. The proposed methodology is evaluated in the modeling of a real nonlinear magnetic levitation system.
This paper presents the proposal and development of a reconfigurable crossbar switch (RCS) architecture for network processors. Its main purpose is to increase the performance, and flexibility for environments with mu...
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This paper presents the proposal and development of a reconfigurable crossbar switch (RCS) architecture for network processors. Its main purpose is to increase the performance, and flexibility for environments with multiprocessors and computer clusters. The results include VHDL simulation of RCS and the use of it in a broadcast function implementation, found in message passing support middleware
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