Optimization on the orthogonal group for independent component analysis

This paper derives a new algorithm that performs independent component analysis (ICA) by optimizing the contrast function of the RADICAL algorithm. The core idea of the proposed optimization method is to combine the global search of a good initial condition with a gradient-descent algorithm. This new ICA algorithm performs faster than the RADICAL algorithm (based on Jacobi rotations) while still preserving, and even enhancing, the strong robustness properties that result from its contrast. © Springer-Verlag Berlin Heidelberg 2007.

Geometric optimization methods for independent component analysis applied on gene expression data

DNA microarrays provide a huge amount of data and require therefore dimensionality reduction methods to extract meaningful biological information. Independent Component Analysis (ICA) was proposed by several authors as an interesting means. Unfortunately, experimental data are usually of poor quality- because of noise, outliers and lack of samples. Robustness to these hurdles will thus be a key feature for an ICA algorithm. This paper identifies a robust contrast function and proposes a new ICA algorithm. © 2007 IEEE.

Sensitivity analysis and optimization of the nuclear fuel cycle

A sensitivity study has been conducted to assess the robustness of the conclusions presented in the MIT Fuel Cycle Study. The Once Through Cycle (OTC) is considered as the base-line case, while advanced technologies with fuel recycling characterize the alternative fuel cycles. The options include limited recycling in LWRs and full recycling in fast reactors and in high conversion LWRs. Fast reactor technologies studied include both oxide and metal fueled reactors. The analysis allowed optimization of the fast reactor conversion ratio with respect to desired fuel cycle performance characteristics. The following parameters were found to significantly affect the performance of recycling technologies and their penetration over time: Capacity Factors of the fuel cycle facilities, Spent Fuel Cooling Time, Thermal Reprocessing Introduction Date, and incore and Out-of-core TRU Inventory Requirements for recycling technology. An optimization scheme of the nuclear fuel cycle is proposed. Optimization criteria and metrics of interest for different stakeholders in the fuel cycle (economics, waste management, environmental impact, etc.) are utilized for two different optimization techniques (linear and stochastic). Preliminary results covering single and multi-variable and single and multi-objective optimization demonstrate the viability of the optimization scheme.

Optimization of an effective extraction procedure for the analysis of microcystins in soils and lake sediments

Microcystin analysis in sediments and soils is considered very difficult due to low recovery for extraction. This is the primary limiting factor for understanding the fate of toxins in the interface between water and sediment in both the aquatic ecosystem as well as in soils. In the present study, a wide range of extraction solvents were evaluated over a wide range of pH, extraction approaches and equilibration time to optimize an effective extraction procedure for the analysis of microcystins in soils and lake sediments. The number of extractions required and acids in extraction solutions were also studied. In this procedure, EDTA-sodium pyrophosphate solution was selected as an extraction solvent based on the adsorption mechanism study. The optimized procedure proved to be highly efficient and achieved over 90% recovery. Finally, the developed procedure was applied to field soil and sediment sample collected from Chinese lakes during bloom seasons and microcystins were determined in six of ten samples. (c) 2005 Elsevier Ltd. All rights reserved.

Optimization of RP-HPLC analysis of low molecular weight organic acids in soil

RP-HPLC analysis for low molecular weight organic acids in soil solution has been optimized. An Atlantis (TM) C-18 column was used for the analyses. An optimal determination for eleven organic acids in soil solution was found at room temperature (25 degrees C) and 220 nm detection wavelength, with a mobile phase of 10 mM KH2PO4 -CH3OH (955, pH 2.7), a flow rate of 0.8 mL/min and 10 mu L sample size. The detection limits ranged 3.2-619 ng/mL, the coefficients of variation ranged 1.3-4.6%, and the recoveries ranged 95.6-106.3% for soil solution with standard addition on the optimal conditions proposed.

The optimization of high performance liquid chromatographic method for analysis of trace microcystins in natural water bodies

The ratio of methanol., water and trifluoroacetic acid ( TFA) was regulated to change the polarity and the pH of the rinse solution and the eluent, so as to improve the high performance liquid chromatography HPLC) detection method for trace microcystines (MCs) in natural water bodies. The results showed that 40 % similar to 45 % methanol-water solution containing 0. 1 % TFA could get good effects on the rinse of impurity, and 70% methanol-water solution containing 0. 1% TFA could elute all the MCs in solid phase extraction ( SPE) cartridge ( C-18), In this way. it is suggested that, in analysis of environmental samples with high concentration of impurity, impurity should be washed with 40% similar to 45% methanol-water solution containing 0. 1% TFA, and MCs should be eluted with 70% similar to 100% methanol-water solution containing 0. 1% TFA.

Factor analysis used to peak position optimization and spectral interference correction in inductively coupled plasma atomic emission spectrometry

Target transformation factor analysis was used to correct spectral interference in inductively coupled plasma atomic emission spectrometry (ICP-BES) for the determination of rare earth impurities in high purity thulium oxide. Data matrix was constructed with pure and mixture vectors and background vector. A method based on an error evaluation function was proposed to optimize the peak position, so the influence of the peak position shift in spectral scans on the determination was eliminated or reduced. Satisfactory results were obtained using factor analysis and the proposed peak position optimization method.

Optimization and finite element analysis for reliable electronic packaging

This paper demonstrates a modeling and design approach that couples computational mechanics techniques with numerical optimisation and statistical models for virtual prototyping and testing in different application areas concerning reliability of eletronic packages. The integrated software modules provide a design engineer in the electronic manufacturing sector with fast design and process solutions by optimizing key parameters and taking into account complexity of certain operational conditions. The integrated modeling framework is obtained by coupling the multi-phsyics finite element framework - PHYSICA - with the numerical optimisation tool - VisualDOC into a fully automated design tool for solutions of electronic packaging problems. Response Surface Modeling Methodolgy and Design of Experiments statistical tools plus numerical optimisaiton techniques are demonstrated as a part of the modeling framework. Two different problems are discussed and solved using the integrated numerical FEM-Optimisation tool. First, an example of thermal management of an electronic package on a board is illustrated. Location of the device is optimized to ensure reduced junction temperature and stress in the die subject to certain cooling air profile and other heat dissipating active components. In the second example thermo-mechanical simulations of solder creep deformations are presented to predict flip-chip reliability and subsequently used to optimise the life-time of solder interconnects under thermal cycling.

Uncertainty and Sensitivity Analysis in Aircraft Operating Costs in Structural Design Optimization

The paper focuses on the development of an aircraft design optimization methodology that models uncertainty and sensitivity analysis in the tradeoff between manufacturing cost, structural requirements, andaircraft direct operating cost.Specifically,ratherthanonlylooking atmanufacturingcost, direct operatingcost is also consideredintermsof the impact of weight on fuel burn, in addition to the acquisition cost to be borne by the operator. Ultimately, there is a tradeoff between driving design according to minimal weight and driving it according to reduced manufacturing cost. Theanalysis of cost is facilitated withagenetic-causal cost-modeling methodology,andthe structural analysis is driven by numerical expressions of appropriate failure modes that use ESDU International reference data. However, a key contribution of the paper is to investigate the modeling of uncertainty and to perform a sensitivity analysis to investigate the robustness of the optimization methodology. Stochastic distributions are used to characterize manufacturing cost distributions, andMonteCarlo analysis is performed in modeling the impact of uncertainty on the cost modeling. The results are then used in a sensitivity analysis that incorporates the optimization methodology. In addition to investigating manufacturing cost variance, the sensitivity of the optimization to fuel burn cost and structural loading are also investigated. It is found that the consideration of manufacturing cost does make an impact and results in a different optimal design configuration from that delivered by the minimal-weight method. However, it was shown that at lower applied loads there is a threshold fuel burn cost at which the optimization process needs to reduce weight, and this threshold decreases with increasing load. The new optimal solution results in lower direct operating cost with a predicted savings of 640=m2 of fuselage skin over the life, relating to a rough order-of-magnitude direct operating cost savings of $500,000 for the fuselage alone of a small regional jet. Moreover, it was found through the uncertainty analysis that the principle was not sensitive to cost variance, although the margins do change.