IDR-QR: Incremental Dimension Reduction Algorithm via QR Decomposition (Java)
IEE Transactions on Knowledge and Data Engineering, Vol. 17, No. 9,

Abstract:
Dimension reduction is a critical data preprocessing step for many database and data mining applications, such as efficient storage and retrieval of high-dimensional data. In the literature, a well-known dimension reduction algorithm is Linear Discriminant Analysis (LDA). The common aspect of previously proposed LDA-based algorithms is the use of Singular Value Decomposition (S ....etc

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Abstract:
Intel announced a new brand name for its next generation mobile processor technology: Centrino. It was designed to help manufactures to build notebooks that use less power and offer extended battery life along with better wireless networking facilities.

CONTENT
Introduction
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Notebook PCs: Two Distinct Segments
Configuration
Intel Centrino Mobile Technology
New Centrino technology
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Abstract Dimensionality reduction is an important step in knowledge discovery in databases. Intrinsic dimension indicates the number of variables necessary to describe a data set. Two methods, box-counting dimension and correlation dimension, are commonly used for intrinsic dimension estimation. However, the robustness of these two methods has not been rigorously studied. This paper demonstrates that correlation dimension is more robust with respect to data sample size. In addition, instead of using a user selected distance , we propose a new ....etc

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Authors:
Emmanuel Asuming Frimpong
Philip Yaw Okyere

Abstract:
Load forecasting helps electricity utilities make important decisions such as purchasing and generating electric power, load switching and infrastructure development. Energy suppliers, financial institutions and other participants in electric energy generation, transmission, distribution and markets benefit from load forecasts. This paper proposes the combination of wavelet analysis and radial basis function (RBF) neural network as tools for STLF. The forecasting model ....etc

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