The success of high-performance differential gel electrophoresis using fluorescent dyes (DIGE) depends on the quality of the digital image captured after electrophoresis, the DIGE enabled image analysis software tool ...
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The success of high-performance differential gel electrophoresis using fluorescent dyes (DIGE) depends on the quality of the digital image captured after electrophoresis, the DIGE enabled image analysis software tool chosen for highlighting the differences, and the statistical analysis. This study compares three commonly available DIGE enabled software packages for the first time: DeCyder V6.5 (GE-Healthcare), Progenesis SameSpots V3.0 (nonlinear Dynamics), and Dymension 3 (Syngene). DIGE gel images of cell culture media samples conditioned by HepG2 and END2 cell lines were used to evaluate the software packages both quantitatively and subjectively considering ease of use with minimal user intervention. Consistency of spot matching across the three software packages was compared, focusing on the top fifty spots ranked statistically by each package, In summary, Progenesis SameSpots outperformed the other two software packages in matching accuracy, possibly being benefited by its new approach: that is, identical spot outline across all the gels. Interestingly, the statistical analysis of the software packages was not consistent on account of differences in workflow, algorithms, and default settings. Results obtained for protein fold changes were substantially different in each package, which indicates that in spite of using internal standards, quantification is software dependent. A future research goal must be to reduce or eliminate user controlled settings, either by automatic sample-to-sample optimization by intelligent software, or by alternative parameter-free segmentation methods.
The Ε -Support Vector regression Machine is a promising artificial intelligence technique, in which the regression algorithm has already been used in solving the nonlinear function approach successfully. Most users s...
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We present an object oriented framework for designing and evaluating heuristic search algorithms that achieve a high level of generality and work well on a wide range of combinatorial optimization problems. Our framew...
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A new custom evolutionary algorithm was developed and implemented to solve multiple objective multi-state reliability optimization design problems. This new algorithm uses the universal moment generating function appr...
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ISBN:
(纸本)9780769539065
A new custom evolutionary algorithm was developed and implemented to solve multiple objective multi-state reliability optimization design problems. This new algorithm uses the universal moment generating function approach to evaluate the different reliability or availability indices of the system which have various levels of performance ranging from perfectly functioning to completely failed. And each component in sub-system has different performance levels, cost, weight, and reliability. Genetic algorithms are suited for solving reliability design problems because of their appropriate for high-dimension stochastic problems with many nonlinearities or discontinuities. The developed algorithm, MOMS-HDEA, combined the differential evolution algorithm with multi-parent crossover operator satisfying the ergodic and fast properties in searching simultaneously. Experiment also shows that the algorithm gets better Pareto-front solutions.
Since the scalability of logic circuits is becoming larger and more complex, the auto-design is becoming more and more difficult. In order to improve automatic design and performance evaluation of logic circuits in ef...
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ISBN:
(纸本)9781424446001
Since the scalability of logic circuits is becoming larger and more complex, the auto-design is becoming more and more difficult. In order to improve automatic design and performance evaluation of logic circuits in efficiency and capability of optimization, multiobjective simulated annealing (MSA) based increasable evolution approach is designed to evolve logic circuits automatically with an extended matrix encoding method, which can be able to reflect the potential performance of a circuit and reduce the risk of deleting a circuit with a good developing potential during evolution is devised. In the process of evolution, each individual is renewedly associated to a corresponding objective in terms of a novel adaptive evaluation method at each generation. In experiments, complicated arithmetic circuits are designed to assess the performance of MSA against other algorithms. Results indicate that the proposed method could design logic circuits efficiently.
Based on a kind of typical high speed monohull, the paper discusses an integrate optimization's method of navigational performance and structure characteristic with the materials of some ships and some relevant ex...
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ISBN:
(纸本)9781846260612
Based on a kind of typical high speed monohull, the paper discusses an integrate optimization's method of navigational performance and structure characteristic with the materials of some ships and some relevant experience expressions. There're 2 parts of synthetical optimization of mechanics properties for ships: navigation performances and structural mechanics properties .The authors use the weighted sum of rapidity, sea-keeping ability and maneuverability as the sub-objective function of navigation performances;use the weighted sum of static and dynamic properties as the sub-objective function of structural mechanics properties;The weighted sum of these 2 sub-objective functions is just the general objective function. Stability, buoyancy and some other characteristics as well as limits of design variables form the constraint conditions. The author constructed an new algorithm that is composed of the delamination-parallel thinking, maximal distance principle , the chaos algorithm and the genetic algorithm. Then the software with friendly interface is programmed by C++ language. A large number of calculation results show that: the algorithm(DP-GA-chaos) not only can conquer the prematurely problem of GA, but also consume little calculation time and has higher efficiency.
The sigma-delta cellular neural network (SD-CNN) is a complete framework of a spatial domain sigma-delta modulator, and has a very high image reconstruction (AD-to-DA) performance. In this architecture, the A-template...
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ISBN:
(纸本)9781424438952
The sigma-delta cellular neural network (SD-CNN) is a complete framework of a spatial domain sigma-delta modulator, and has a very high image reconstruction (AD-to-DA) performance. In this architecture, the A-template, given by a 2D low pass filter (LIT), is used for a digital to analogue converter (DAC), the C-template works as an integrator, and the nonlinear output function is for the bilevel output. By exploiting to the nonlinearoptimization ability of CNN spatio-temporal dynamics, optimal binary and reconstruction image can be obtained. However, in the conventional SD-CNN, the Gaussian LIT, whose coefficients are real number, is used as the A-template. This filter coefficients requirement is one of major factors that restricts a hardware implementation. In this paper, a SD-CNN having hardware-friendly filter coefficients is proposed. Moreover its AD and DA performance is confirmed by some experiments.
Business activity and engineering practice always produce large data sets carrying important information, but because of the data sets' largeness and frequent updating, if we apply the Apriori based algorithms to ...
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ISBN:
(纸本)9780769538167
Business activity and engineering practice always produce large data sets carrying important information, but because of the data sets' largeness and frequent updating, if we apply the Apriori based algorithms to them for incremental rules mining, it is not only inefficient, but also either redundant rules would be produced under low threshold of minimal support, which makes users hardly distinguish which rules arc really meaningful, or significant rules with low support in additional data set would possibly lost when the threshold is defined high. Motivated by these, therefore, following genetic principles, and combining with natural immune evolution theory and relevant bionic mechanism, this paper proposes an IOGA (Immune optimization based Genetic Algorithm) approach for incremental association rules mining to large and frequent updating data sets. Experiment demonstrates the method's efficiency and presents its good performance in pruning redundant rules and discovering meaningful rules, perceiving low support rules in additional data set.
A new structure of Yagi-Uda antenna is proposed that can improve the forward/backward ratio (f/b) significantly while maintaining a high gain. This structure involves the addition of two driven dipole elements to the ...
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ISBN:
(纸本)9780889867956
A new structure of Yagi-Uda antenna is proposed that can improve the forward/backward ratio (f/b) significantly while maintaining a high gain. This structure involves the addition of two driven dipole elements to the main Yagi-Uda array, the resulting antenna is denoted by augmented Yagi-Uda. The design of such antenna is performed using GA in conjunction with the SNEC software. Comparisons are made among the augmented and conventional Yagi-Uda configurations for different design parameters. It is observed that an improvement of at least 66dB in the f/b ratio is obtained. Moreover, the augmented antenna outperforms the conventional Yagi-Uda antenna, because it achieves higher performance standards over an extended bandwidth around 2.4GHz.
Providing quality of service (QoS) guarantees in networks gives rise to several challenging issues. One of them is how to determine a feasible path that satisfies a set of constraints while maintaining high utilizatio...
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