Abstract: We propose a fast and robust hierarchical face detection system which finds and localizes face images with a cascade of classifiers. Three modules contribute to the efficiency of our detector. First, heterogeneous feature descriptors are exploited to enrich feature types and feature numbers for face representation. Second, a PSO-Adaboost algorithm is proposed to efficiently select discriminative features from a large pool of available features and reinforce them into the final ensemble classifier. Compared with the standard exhaustive Adaboost for feature selection, the new PSOAdaboost algorithm reduces the training time up to 20 times. Finally, a three-stage hierarchical classifier framework is developed for rapid background removal. In particular, candidate face regions are detected more quickly by using a large size window in the first stage. Nonlinear SVM classifiers are used instead of decision stump functions in the last stage to remove those remaining complex nonface patterns that can not be rejected in the previous two stages. Experimental results show our detector achieves superior performance on the CMU+MIT frontal face dataset.
Abstract: Artificial Neural Network (ANN) has been
extensively used for classification of heart sounds for its
discriminative training ability and easy implementation. However, it
suffers from overparameterization if the number of nodes is not
chosen properly. In such cases, when the dataset has redundancy
within it, ANN is trained along with this redundant information that
results in poor validation. Also a larger network means more
computational expense resulting more hardware and time related
cost. Therefore, an optimum design of neural network is needed
towards real-time detection of pathological patterns, if any from heart
sound signal. The aims of this work are to (i) select a set of input
features that are effective for identification of heart sound signals and
(ii) make certain optimum selection of nodes in the hidden layer for a
more effective ANN structure. Here, we present an optimization
technique that involves Singular Value Decomposition (SVD) and
QR factorization with column pivoting (QRcp) methodology to
optimize empirically chosen over-parameterized ANN structure.
Input nodes present in ANN structure is optimized by SVD followed
by QRcp while only SVD is required to prune undesirable hidden
nodes. The result is presented for classifying 12 common
pathological cases and normal heart sound.
Abstract: To help the client to select a competent agent
construction enterprise (ACE), this study aims to investigate the
selection standards by using the Fuzzy Analytic Hierarchy Process
(FAHP) and build an evaluation mathematical model with Grey
Relational Analysis (GRA). According to the outputs of literature
review, four orderly levels are established within the model, taking the
consideration of various agent construction models in practice. Then,
the process of applying FAHP and GRA is discussed in detailed.
Finally, through a case study, this paper illustrates how to apply these
methods in getting the weights of each standard and the final
assessment result.
Abstract: In this paper, hybrid FDMA-TDMA access technique in a cooperative distributive fashion introducing and implementing a modified protocol introduced in [1] is analyzed termed as Power and Cooperation Diversity Gain Protocol (PCDGP). A wireless network consists of two users terminal , two relays and a destination terminal equipped with two antennas. The relays are operating in amplify-and-forward (AF) mode with a fixed gain. Two operating modes: cooperation-gain mode and powergain mode are exploited from source terminals to relays, as it is working in a best channel selection scheme. Vertical BLAST (Bell Laboratories Layered Space Time) or V-BLAST with minimum mean square error (MMSE) nulling is used at the relays to perfectly detect the joint signals from multiple source terminals. The performance is analyzed using binary phase shift keying (BPSK) modulation scheme and investigated over independent and identical (i.i.d) Rayleigh, Ricean-K and Nakagami-m fading environments. Subsequently, simulation results show that the proposed scheme can provide better signal quality of uplink users in a cooperative communication system using hybrid FDMATDMA technique.
Abstract: Selection of a project among a set of possible
alternatives is a difficult task that the decision maker (DM) has to
face. In this paper, by using a fuzzy TOPSIS technique we propose a
new method for a project selection problem. After reviewing four
common methods of comparing investment alternatives (net present
value, rate of return, benefit cost analysis and payback period) we
use them as criteria in a TOPSIS technique. First we calculate the
weight of each criterion by a pairwise comparison and then we utilize
the improved TOPSIS assessment for the project selection.
Abstract: In the past decade, because of wide applications of
hybrid systems, many researchers have considered modeling and
control of these systems. Since switching systems constitute an
important class of hybrid systems, in this paper a method for optimal
control of linear switching systems is described. The method is also
applied on the two-tank system which is a much appropriate system
to analyze different modeling and control techniques of hybrid
systems. Simulation results show that, in this method, the goals of
control and also problem constraints can be satisfied by an
appropriate selection of cost function.