PURPOSE The goal of this paper is to extend our recently developed FBP (filtered backprojection) algorithm, which has the same characteristics of an iterative Landweber algorithm, to an FBP algorithm with the same characteristics of an iterative MAP (maximum a posteriori) algorithm. The newly developed FBP algorithm also works when the angular sampling interval is not uniform. The projection no...

Partial Transmit Sequence (PTS) is a promising technique to reduce Peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. However optimum PTS (OPTS) needs exhaustive search over all combinations of allowed phase weighting factors. It results in high computational complexity. Grouping Phase Weighting (GPW) technique is a method which has reduced computat...

In this paper the novel method of “weighted OFDM” is addressed. Different types of weighting factors (including Rectangular, Bartlett, Gaussian, Raised cosine, Half-sin and Shanon) are considered. The impact of weighting of OFDM on the peak-to-average power ratio (PAPR) is investigated by means of simulation and is compared for the above mentioned weighting factors. Results show that by weighti...

The assessment of social responsibility (SR) in organizations requires a hierarchy of requisitely holistic factors and indicators. This paper introduces the development of measuring instrument for this multidimensional problem. Differently from using factor analysis based on principal component analysis extraction method, it presents the use of exploratory factor analysis (EFA) to develop the m...

In this paper, we describe the IBM Research system for indexing, analysis, and retrieval of video as applied to the TRECVID-2009 video retrieval benchmark. A. High-Level Concept detection: This year, focus of the system improvement was on global and local feature combination, automatic training data construction from web domain, and large-scale detection using Hadoop. 1. A ibm.Global 6: Baselin...

Collaborative filtering uses a database about consumers’ preferences to make personal product recommendations and is achieving widespread success in E-Commerce nowadays. In this paper, we present several feature-weighting methods to improve the accuracy of collaborative filtering algorithms. Furthermore, we propose to reduce the training data set by selecting only highly relevant instances. We ...