In this paper, we propose three new tensor decompositions for even-order tensors corresponding respectively to the rank-one decompositions of some unfolded matrices. Consequently such new decompositions lead to three new notions of (even-order) tensor ranks, to be called the M-rank, the symmetric M-rank, and the strongly symmetric M-rank in this paper. We discuss the bounds between these new te...

We first develop a reduced-rank minimum mean square error (MMSE) detector for direct-sequence (DS) code division multiple access (CDMA) by forcing the linear MMSE detector to lie in a signal subspace of a reduced dimension. While a reduced-rank MMSE detector has lower complexity, it cannot outperform the full-rank MMSE detector. We then concentrate on the blind reduced-rank MMSE detector which ...

Standard face recognition algorithms that use standard feature extraction techniques always suffer from image performance degradation. Recently, singular value decomposition and low-rank matrix are applied in many applications,including pattern recognition and feature extraction. The main objective of this research is to design an efficient face recognition approach by combining many tech...

INTRBackground and Objectives: Good medical nutrition therapy (MNT) is crucial to inpatients' health and treatment, and is part of routine hospital cares. Surgery ward is a highly danger-prone section in any hospital. The present study was conducted for a proactive risk analysis of nutrition and food distribution in Mashhad Qaem Hospital’ Women’s Surgery Ward in 2013 through health care failure...

This study examined the effects of social housing manipulations on bodyweight, corticosterone levels, and performance of T-maze alternation in male CD-1 mice. Males that adopted a dominant social rank were heavier than those that adopted a subordinate social rank. Dominant males also had lower corticosterone concentrations than the subordinates. However, there was little to suggest that these p...

Pay for performance (PFP) search engines, like their “traditional” counterparts (e.g. Google), provide search services for documents on the World Wide Web. These search engines however rank documents not on content characteristics but according to the amount of money a vendor is willing to pay when a user visits a Web site appearing in the search results page. A study was conducted to compare t...

One of the central issues in learning to rank for information retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures used in information retrieval such as Mean Average Precision (MAP) and Normalized Discounted Cumulative Gain (NDCG). Several such algorithms including SVMmap and AdaRank have been proposed and their effectiveness has been verif...