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Spectral analysis-based dimensionality reduction algorithms are important and have been popularly applied in data mining and computer vision applications. To date many algorithms have been developed, e.g., principal component anal...
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Spectral analysis-based dimensionality reduction algorithms are important and have been popularly applied in data mining and computer vision applications. To date many algorithms have been developed, e.g., principal component analysis, locally linear embedding, Laplacian eigenmaps, and local tangent space alignment. All of these algorithms have been designed intuitively and pragmatically, i.e., on the basis of the experience and knowledge of experts for their own purposes. Therefore, it will be more informative to provide a systematic framework for understanding the common properties and intrinsic difference in different algorithms. In this paper, we propose such a framework, named "patch alignment,rdquo which consists of two stages: part optimization and whole alignment. The framework reveals that (1) algorithms are intrinsically different in the patch optimization stage and (2) all algorithms share an almost identical whole alignment stage. As an application of this framework, we develop a new dimensionality reduction algorithm, termed discriminative locality alignment (DLA), by imposing discriminative information in the part optimization stage. DLA can (1) attack the distribution nonlinearity of measurements; (2) preserve the discriminative ability; and (3) avoid the small-sample-size problem. Thorough empirical studies demonstrate the effectiveness of DLA compared with representative dimensionality reduction algorithms.
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Business intelligence helps gather essential information from a wide variety of unstructured data and convert them into actionable information that allows firms to make informed policy decisions and improve business efficiency and...
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Business intelligence helps gather essential information from a wide variety of unstructured data and convert them into actionable information that allows firms to make informed policy decisions and improve business efficiency and productivity. The challenges facing any organization in business intelligence and decision-making include plan failure, lack of preparation, resource failure, and risk-taking capability.This paper proposes a framework of Optimized Data Management using Big Data Analytics (ODM-BDA) to increase the intelligent organizational effectiveness and decision-making analysis in organizations. A backtracking method is introduced in business intelligence and decision-making environments to enhance plan failure and risk-taking ability. The steep optimized strategy is incorporated in the ODM-BDA framework to improve the training plan and manage money. The research data provided an essential set of acceptance research for these models in increasing the relative level of effectiveness and performance.The simulation analysis is performed based on true positive analysis, performance analysis, error analysis, and accuracy analysis, proving the proposed framework's reliability.
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The microstructures and mechanical properties of Mg-6Zn-5Al-4Gd-lRE (RE = Ce or Y) alloys were investigated. The addition of Ce or Y obviously refines the grain size for the Mg-6Zn-5Al-4Gd-based alloy, while the Y element has a be...
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The microstructures and mechanical properties of Mg-6Zn-5Al-4Gd-lRE (RE = Ce or Y) alloys were investigated. The addition of Ce or Y obviously refines the grain size for the Mg-6Zn-5Al-4Gd-based alloy, while the Y element has a better refining effect. The Ce and Y show different grain-refining mechanisms: Ce addition mostly promotes the growth of secondary dendrite, while Y addition mainly increases the heterogeneous nucleation sites. The hardness-versus-aging time curves indicate that all the alloys have excellent aging-hardening behavior, but the response to maximum hardness was delayed by the Ce or Y addition. The microstructure observation of the peak-aged alloys indicated a large number of nanocrystalline τ-Mg_(32)(Al, Zn)_(49) precipitates in the matrix. The Y addition is beneficial to improve the mechanical properties, and the alloy has optimal values. However, the Ce addition decreases the ultimate tensile strength and elongation of the alloy due to formation of a lot of shrinkage porosities.
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Increasing shortages of fresh water has led to greater use of treated wastewater for irrigation of crops. This study evaluates the spatial variability of soil properties after irrigation with wastewater and freshwater. Geostatisti...
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Increasing shortages of fresh water has led to greater use of treated wastewater for irrigation of crops. This study evaluates the spatial variability of soil properties after irrigation with wastewater and freshwater. Geostatistical techniques were used to identify the variability of soil properties at the different sites. A set of physical and chemical soil properties were measured including total nitrogen (TN), total phosphorus (TP), organic matter (OM) and soil moisture. The TN concentration levels varied from 567 to 700 mg·kg~(-1), while OC levels ranged from 7.3 to 16.3mg·kg~(-1) in wastewater-irrigated zones. The concentration levels of TP were between 371.53 and 402.88 mg·kg~(-1) for the wastewater-irrigated sites. Wastewater irrigation resulted in higher TN, TP and OM concentrations by 18.4%, 8% and 25%, respectively. The highest TN and OM occurred along the wastewater trunk. It was also observed that nitrogen concentrations correlate with the soil's organic matter. The increase of salinity may be associated with the increase of pH, which might suggest that a reduction of pH will be beneficial for plant growth due to the decrease of salinity. The average concentrations of nitrogen in topsoil were higher than those in subsurface soils in irrigated areas. Such differences of the N profile might be due to variations in organic matter content and microbial populations. Consistent with TN and OM, soil C:N decreased significantly with an increase of depth. This phenomenon possibly reflects a greater degree of breakdown and the older age of humus stored in the deeper soil layers. The analysis of pH levels at different depths for the three sites showed that pH values for wastewater irrigation were slightly lower than the controlled sites at the same depths.
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In this paper, a new algorithm is proposed for linear instantaneous independent component analysis. This new algorithm is based on solving the gradient equation, and an iterative method is introduced to solve this equation efficie...
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In this paper, a new algorithm is proposed for linear instantaneous independent component analysis. This new algorithm is based on solving the gradient equation, and an iterative method is introduced to solve this equation efficiently. To make the proposed algorithm adaptive to source distributions, the density functions as well as their first and second derivatives are estimated by kernel density method. Empirical comparisons with several popular independent component analysis (ICA) algorithms confirm the efficiency and accuracy of the proposed algorithm.
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A reduced 1D dynamic model of a planar direct internal reforming SOFC (DIR-SOFC) is presented in this paper for system research by introducing two simplifications. The two simplification strategies employed are called Integration ...
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A reduced 1D dynamic model of a planar direct internal reforming SOFC (DIR-SOFC) is presented in this paper for system research by introducing two simplifications. The two simplification strategies employed are called Integration and Average, respectively. The present model is evaluated with a detailed 1D SOFC model, which does not introduce the two simplifications, and a lumped parameter (i.e., 0D) SOFC model. Results show that under the operating conditions investigated the accuracy of the reduced model is not significantly compromised by the two simplifications in prediction of the outlet gas flow rates and molar fractions, the outlet temperatures, and the cell voltage, while its computational time is significantly decreased by them. Moreover, it is quite simple in form. Therefore, the reduced SOFC model is attractive for system research. Compared with the lumped model, the reduced SOFC model is an improvement with regard to accuracy because it takes into account the spatially distributed nature of SOFCs to a certain extent. The discretized node number for solving the reduced model can be taken as an adjustable parameter in modeling, and is determined according to specific modeling requirements.
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The color similarity between the background and foreground causes serious misdetec-tions in moving object detection from video sequences. In this paper, we point out that the existence of a confusion point and the model inaccuracy...
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The color similarity between the background and foreground causes serious misdetec-tions in moving object detection from video sequences. In this paper, we point out that the existence of a confusion point and the model inaccuracy are the reasons for the misdetections due to the color similarity. Accordingly, the solutions of the color similarity are to shift the confusion point and to improve the model accuracy. Based on this conclusion, a simple algorithm by combining a weighting technique and a new foreground model is presented, and improved results are generated. More accurate weighting techniques and foreground models are expected to be developed in the future based on the solutions.
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Previous studies demonstrated that the bioleaching of municipal solid waste incinerator fly ash by Aspergillus niger was an efficient "green technology" for heavy metals removal, however, it demanded a long operational period. In ...
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Previous studies demonstrated that the bioleaching of municipal solid waste incinerator fly ash by Aspergillus niger was an efficient "green technology" for heavy metals removal, however, it demanded a long operational period. In this study, water-washing was used as a fly ash pretreatment before the bioleaching process (one-step and two-step). This pretreatment extracted 50.6% of K, 41.1% of Na, 5.2% of Ca and 1% of Cr from the fly ash. Due to the dissolution of alkali chlorides which hold particles together, fly ash particles were smashed into smaller granules by the hydraulic flushing action caused by vibration. After the pretreatment, the lag phase and bioleaching period were reduced by 45 and 30%, respectively, in one-step bioleaching of 1% (w/v) fly ash. Meanwhile, the metals extraction yield both in one-step and two-step bioleaching was increased markedly, e.g. in two-step bioleaching, 96% Cd, 91% Mn, 73% Pb, 68% Zn, 35% Cr and 30% Fe was extracted from 1% water-washed fly ash, respectively. The reduction of the bioleaching period and improvement of metals extraction yield will likely allow the practical application of the bioleaching technology for heavy metals removal from fly ash.
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Gait Energy Image (GEI) has been proved to be an effective identity signature in gait recognition. But previous approaches only treat this 2D image representation as a holistic feature and neglect the intrinsic dynamic characteris...
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Gait Energy Image (GEI) has been proved to be an effective identity signature in gait recognition. But previous approaches only treat this 2D image representation as a holistic feature and neglect the intrinsic dynamic characteristics of gait patterns. In this paper, we use variation analysis to obtain the dynamic region in GEI which reflects the walking manner of an individual. Based on this analysis, a dynamics weight mask is constructed to enhance the dynamic region and suppress the noises on the unimportant regions. The obtained gait representation called enhanced GEI (EGEI) is then represented in low dimensional subspace by Gabor-based discriminative common vectors analysis. We test the proposed approach on the USF HumanID Gait Database. Experimental results prove its effectiveness in terms of recognition rate.
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Matrix metalloproteinases (MMPs) are a kind of secretory proteinases. Degradation of the extracellular matrix (ECM) by MMPs enhances tumor invasion and metastasis. To monitor MMPs activity and assess the MMP inhibitor effects in v...
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Matrix metalloproteinases (MMPs) are a kind of secretory proteinases. Degradation of the extracellular matrix (ECM) by MMPs enhances tumor invasion and metastasis. To monitor MMPs activity and assess the MMP inhibitor effects in vivo, we constructed a plas-mid that encoded a secretory fluorescent sensor named DMC (DsRed2-MSS-CFP expressed from pDisplay vector) that DsRed2 and cyan fluorescent protein (CFP) linked by MMP substrate site (MSS). MDA-MB 435s cells highly expressing endogenetic secretory MMP were transfected with the DMC plasmid so that the DMC could be cleaved by endogenetic MMP and the fluorescence ratio of DsRed2 to CFP was decreased. Treating the cells with GM6001, an MMP inhibitor, blocked the cleavage of DMC and caused an increase of the DsRed2/CFP ratio. The same result was achieved by using an in vivo tumor model that stable DMC-expressing MDA-MB 435s cells inoculated onto the chorioallantoic membrane of developing chick embryos to form primary tumors on the membrane. Thus, the fluorescent sensor DMC is able to sensitively monitor MMP activity and assess MMP inhibitors for anticancer research in vivo. This proves a novel method to efficiently screen and assess the anticancer drug MMP inhibitor in living cells and in vivo tumor models.
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