7440868
Hybrid quantum probabilistic coding genetic algorithm for large scale hardware-software co-synthesis of embedded systems
Hardware-software co-synthesis is a key step of future design of embedded systems. It involves three interdependent subproblems: allocation of resources, assignment of tasks to resources, and scheduling the execution of tasks. Both assignment and scheduling are known to be NP-complete. So it is a really hard and challenging task to optimization algorithms. Both heuristic and evolutionary algorithms are commonly used in real world. Heuristic algorithms converge rapidly but often be trapped in local minima and evolutionary algorithms own high exploration capacity but become time-consuming when handling large-scale systems. In this paper, a new hybrid evolutionary algorithm, called Hybrid Quantum probabilistic coding Genetic Algorithm, is proposed to implement the co-synthesis of large scale multiprocessor embedded systems, in which a heuristic algorithm is combined with the Quantum probabilistic coding Genetic Algorithm to enhance the performance on the hard task. The experimental results show that HQGA has better performance than both HA and QGA on large scale HW/SW co-synthesis problems.
15998088
Understand behavior and performance of Real Coded Optimization Algorithms via NK-linkage model
Classical NK-landcape model was designed for analyzing optimization and evolution process in binary solution space, so it can not be used to analyze real coded optimization algorithms (RCOAs) directly, which work in continuous solution space directly. In this paper, the concept of NK-landscape model is extended to the continuous space, and a new NK-landscape model with continuous space is proposed. The new model is powerful and comprehensive with simple structure and flexible formula. Therefore, it can be used to construct test functions of various types of linkages for analyzing various performances of RCOAs. The feasibility of the proposed model is testified via experiments with 3 well-known RCOAs, ( i.e. covariance matrix adapting evolutionary strategy (CMA-ES), differential evolution (DE), neighborhood search differential evolution (NSDE)). The results show that the new model can reveal the merits and demerits of RCOAs effectively.
26519336
Iris Recognition Algorithm Using Modified Log-Gabor Filters
In this paper, we presented an iris recognition algorithm based on modified Log-Gabor filters. The algorithm is similar as the method proposed by Daugman in general procedure while modified Log-Gabor filters are adopted to extract the iris phase information instead of complex Gabor filters used in Daugman's method. The advantage of Log-Gabor filters over complex Gabor filters is the former are strictly bandpass filters and the latter are not. The property of strictly bandpass makes the Log-Gabor filters more suitable to extract the iris phase features regardless of the background brightness. The comparison experiments between complex Gabor filters based methods and the proposed method are also presented in this paper
14435465
A hardware/software partitioning algorithm based on artificial immune principles
Hardware/software codesign is the main approach to designing the embedded systems. One of the primary steps of the hardware/software codesign is the hardware/software partitioning. A good partitioning scheme is a tradeoff of some constraints, such as power, size, performance, and so on. Inspired by both negative selection model and evolutionary mechanism of the biological immune system, an evolutionary negative selection algorithm for hardware/software partitioning, namely ENSA-HSP, is proposed in this paper. This ENSA-HSP algorithm is proved to be convergent, and its ability to escape from the local optimum is also analyzed. The experimental results demonstrate that ENSA-HSP is more efficient than traditional evolutionary algorithm.
9214943
A restart univariate estimation of distribution algorithm: sampling under mixed Gaussian and Lévy probability distribution
A univariate EDA denoted as ldquoLSEDA-glrdquo for large scale global optimization (LSGO) problems is proposed in this paper. Three efficient strategies: sampling under mixed Gaussian and Levy probability distribution, standard deviation control strategy and restart strategy are adopted to improve the performance of classical univariate EDA on LSGO problems. The motivation of such work is to extend EDAs to LSGO domain reasonably. Comparison among LSEDA-gl, EDA with standard deviation control strategy only (EDA-STDC) and similar EDA version ldquocontinuous univariate marginal distribution algorithmrdquo UMDAc is carried out on classical test functions. Based on the general comparison standard, the strengths and weaknesses of the algorithms are discussed. Besides, LSEDA-gl is tested on 7 functions with 100, 500, 1000 dimensions provided in the CECpsila2008 Special Session on LSGO. This work is also expected to provide a comparison result for the CECpsila2008 special session.
27086487
A Robust Iris Localization Algorithm via Radial Symmetry for Nonideal Capturing Condition
Iris localization is a key component of practical iris recognition system. Previous algorithms show good localization performances for iris images captured in the ideal conditions. However, in practice, the quality of iris image is greatly influenced by luminance, eyelashes, hair or glasses frame, which will cause mislocalization. In order to improve the robustness of iris localization, this paper proposes a new localization algorithm based on the radial symmetry transform, in which the radial symmetry characteristic of the pupil is utilized to realize iris localization. Experimental results show that the proposed algorithm can efficiently avoid the interference of luminance and other bad conditions, and realize robust precise localization in a real-time system.
16922329
A New Transmit Scheme Combining Beamforming with Space-Time Block Coding
In this paper, a new transmit scheme combining beamforming (BF) with space-time block coding (STBC) is proposed for correlated fading channels. Based on maximizing the output mean signal-to-noise ratio (SNR) at the receiver, the transmitter BF weight vectors are first derived. Then, utilizing the minimal bit error rate (BER) upper bound as the design criterion, a simple power allocation algorithm is developed. Next, the BER performance of the system with the proposed transmit scheme is analyzed by considering an M-QAM constellation. Finally, computer simulation results are given to verify the effectiveness of the proposed scheme.
30055456
A new block detection receiver for noncoherent orthogonal CDMA system
A new block detection receiver is presented for noncoherent orthogonal CDMA (such as the CDMA IS-95A reverse link). This new receiver uses multiple Hadamard (or Walsh) codes for joint detection instead of using a single Walsh code as conventional receivers do. The simulation results show that the new block detection receiver is significantly better than the conventional non-block detection receivers in both additive white Gaussian noise and flat Rayleigh fading channels. A reduced-complexity algorithm for the block detection is also presented with significant complexity reduction and negligible performance degradation.
10717067
3D-SURFER: software for high-throughput protein surface comparison and analysis
SUMMARY
We present 3D-SURFER, a web-based tool designed to facilitate high-throughput comparison and characterization of proteins based on their surface shape. As each protein is effectively represented by a vector of 3D Zernike descriptors, comparison times for a query protein against the entire PDB take, on an average, only a couple of seconds. The web interface has been designed to be as interactive as possible with displays showing animated protein rotations, CATH codes and structural alignments using the CE program. In addition, geometrically interesting local features of the protein surface, such as pockets that often correspond to ligand binding sites as well as protrusions and flat regions can also be identified and visualized.


AVAILABILITY
3D-SURFER is a web application that can be freely accessed from: http://dragon.bio.purdue.edu/3d-surfer


CONTACT
dkihara@purdue.edu


SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
10259496
An E-Government Platform Based on Multi-Tier Architecture
With the development of dynamic e-government and the network, the application system becomes more complicated. Traditional e-government system will have an inherent scalability problem as the number of applications increases continuously. To solve this problem, an e-government platform based on multi-tier architecture is presented. By integrating applications, resources and system modules, the platform provides an effective mechanism to reduce the development and communication cost. This paper intensively discusses the design rationale and practical solutions of the platform, including structured data models, a secure data exchange model, uniform interface specifications, a topic based publish/subscribe communication mechanism and an asynchronous execution mechanism. The security of the platform is also evaluated by formal logic method.
2288383
An Improved FCM Algorithm Incorporating Spatial Information for Image Segmentation
Fuzzy c-means (FCM) clustering algorithm is a popular model widely used in segmentation of magnetic imaging (MRI) data. The conventional FCM does not take into account the spatial information of image and get the unexpected results of segmentation when dealing with some MRI contaminated by noise. Considering the intensities of ideal MRI are piecewise constant, we present an improved model to fuzzy c-means algorithm using membership smoothing constraint. The proposed algorithm can reasonably use the spatial information of image and improve the accuracy of segmentation. Simulation MR brain image with different noise levels and real MR brain image are presented in the experiments. The results of experiments show better robustness of our algorithms to noise than other segmentation algorithms.