Algorithms for improved performance in cryptographic protocols.
Schroeppel, Richard Crabtree; Beaver, Cheryl Lynn
2003-11-01
Public key cryptographic algorithms provide data authentication and non-repudiation for electronic transmissions. The mathematical nature of the algorithms, however, means they require a significant amount of computation, and encrypted messages and digital signatures possess high bandwidth. Accordingly, there are many environments (e.g. wireless, ad-hoc, remote sensing networks) where public-key requirements are prohibitive and cannot be used. The use of elliptic curves in public-key computations has provided a means by which computations and bandwidth can be somewhat reduced. We report here on the research conducted in an LDRD aimed to find even more efficient algorithms and to make public-key cryptography available to a wider range of computing environments. We improved upon several algorithms, including one for which a patent has been applied. Further we discovered some new problems and relations on which future cryptographic algorithms may be based.
Turbopump Performance Improved by Evolutionary Algorithms
NASA Technical Reports Server (NTRS)
Oyama, Akira; Liou, Meng-Sing
2002-01-01
The development of design optimization technology for turbomachinery has been initiated using the multiobjective evolutionary algorithm under NASA's Intelligent Synthesis Environment and Revolutionary Aeropropulsion Concepts programs. As an alternative to the traditional gradient-based methods, evolutionary algorithms (EA's) are emergent design-optimization algorithms modeled after the mechanisms found in natural evolution. EA's search from multiple points, instead of moving from a single point. In addition, they require no derivatives or gradients of the objective function, leading to robustness and simplicity in coupling any evaluation codes. Parallel efficiency also becomes very high by using a simple master-slave concept for function evaluations, since such evaluations often consume the most CPU time, such as computational fluid dynamics. Application of EA's to multiobjective design problems is also straightforward because EA's maintain a population of design candidates in parallel. Because of these advantages, EA's are a unique and attractive approach to real-world design optimization problems.
Improved Ant Colony Clustering Algorithm and Its Performance Study.
Gao, Wei
2016-01-01
Clustering analysis is used in many disciplines and applications; it is an important tool that descriptively identifies homogeneous groups of objects based on attribute values. The ant colony clustering algorithm is a swarm-intelligent method used for clustering problems that is inspired by the behavior of ant colonies that cluster their corpses and sort their larvae. A new abstraction ant colony clustering algorithm using a data combination mechanism is proposed to improve the computational efficiency and accuracy of the ant colony clustering algorithm. The abstraction ant colony clustering algorithm is used to cluster benchmark problems, and its performance is compared with the ant colony clustering algorithm and other methods used in existing literature. Based on similar computational difficulties and complexities, the results show that the abstraction ant colony clustering algorithm produces results that are not only more accurate but also more efficiently determined than the ant colony clustering algorithm and the other methods. Thus, the abstraction ant colony clustering algorithm can be used for efficient multivariate data clustering. PMID:26839533
Improved Ant Colony Clustering Algorithm and Its Performance Study
Gao, Wei
2016-01-01
Clustering analysis is used in many disciplines and applications; it is an important tool that descriptively identifies homogeneous groups of objects based on attribute values. The ant colony clustering algorithm is a swarm-intelligent method used for clustering problems that is inspired by the behavior of ant colonies that cluster their corpses and sort their larvae. A new abstraction ant colony clustering algorithm using a data combination mechanism is proposed to improve the computational efficiency and accuracy of the ant colony clustering algorithm. The abstraction ant colony clustering algorithm is used to cluster benchmark problems, and its performance is compared with the ant colony clustering algorithm and other methods used in existing literature. Based on similar computational difficulties and complexities, the results show that the abstraction ant colony clustering algorithm produces results that are not only more accurate but also more efficiently determined than the ant colony clustering algorithm and the other methods. Thus, the abstraction ant colony clustering algorithm can be used for efficient multivariate data clustering. PMID:26839533
Dentate Gyrus Circuitry Features Improve Performance of Sparse Approximation Algorithms
Petrantonakis, Panagiotis C.; Poirazi, Panayiota
2015-01-01
Memory-related activity in the Dentate Gyrus (DG) is characterized by sparsity. Memory representations are seen as activated neuronal populations of granule cells, the main encoding cells in DG, which are estimated to engage 2–4% of the total population. This sparsity is assumed to enhance the ability of DG to perform pattern separation, one of the most valuable contributions of DG during memory formation. In this work, we investigate how features of the DG such as its excitatory and inhibitory connectivity diagram can be used to develop theoretical algorithms performing Sparse Approximation, a widely used strategy in the Signal Processing field. Sparse approximation stands for the algorithmic identification of few components from a dictionary that approximate a certain signal. The ability of DG to achieve pattern separation by sparsifing its representations is exploited here to improve the performance of the state of the art sparse approximation algorithm “Iterative Soft Thresholding” (IST) by adding new algorithmic features inspired by the DG circuitry. Lateral inhibition of granule cells, either direct or indirect, via mossy cells, is shown to enhance the performance of the IST. Apart from revealing the potential of DG-inspired theoretical algorithms, this work presents new insights regarding the function of particular cell types in the pattern separation task of the DG. PMID:25635776
Performance of recovery time improvement algorithms for software RAIDs
Riegel, J.; Menon, Jai
1996-12-31
A software RAID is a RAID implemented purely in software running on a host computer. One problem with software RAIDs is that they do not have access to special hardware such as NVRAM. Thus, software RAIDs may need to check every parity group of an array for consistency following a host crash or power failure. This process of checking parity groups is called recovery, and results in long delays when the software RAID is restarted. In this paper, we review two algorithms to reduce this recovery time for software RAIDs: the PGS Bitmap algorithm we proposed in and the List Algorithm proposed in. We compare the performance of these two algorithms using trace-driven simulations. Our results show that the PGS Bitmap Algorithm can reduce recovery time by a factor of 12 with a response time penalty of less than 1%, or by a factor of 50 with a response time penalty of less than 2%, and a memory requirement of around 9 Kbytes. The List Algorithm can reduce recovery time by a factor of 50 but cannot achieve a response time penalty of less than 16%.
Sankaran, Ramanan; Angel, Jordan; Brown, W. Michael
2015-04-08
The growth in size of networked high performance computers along with novel accelerator-based node architectures has further emphasized the importance of communication efficiency in high performance computing. The world's largest high performance computers are usually operated as shared user facilities due to the costs of acquisition and operation. Applications are scheduled for execution in a shared environment and are placed on nodes that are not necessarily contiguous on the interconnect. Furthermore, the placement of tasks on the nodes allocated by the scheduler is sub-optimal, leading to performance loss and variability. Here, we investigate the impact of task placement on themore » performance of two massively parallel application codes on the Titan supercomputer, a turbulent combustion flow solver (S3D) and a molecular dynamics code (LAMMPS). Benchmark studies show a significant deviation from ideal weak scaling and variability in performance. The inter-task communication distance was determined to be one of the significant contributors to the performance degradation and variability. A genetic algorithm-based parallel optimization technique was used to optimize the task ordering. This technique provides an improved placement of the tasks on the nodes, taking into account the application's communication topology and the system interconnect topology. As a result, application benchmarks after task reordering through genetic algorithm show a significant improvement in performance and reduction in variability, therefore enabling the applications to achieve better time to solution and scalability on Titan during production.« less
Sankaran, Ramanan; Angel, Jordan; Brown, W. Michael
2015-04-08
The growth in size of networked high performance computers along with novel accelerator-based node architectures has further emphasized the importance of communication efficiency in high performance computing. The world's largest high performance computers are usually operated as shared user facilities due to the costs of acquisition and operation. Applications are scheduled for execution in a shared environment and are placed on nodes that are not necessarily contiguous on the interconnect. Furthermore, the placement of tasks on the nodes allocated by the scheduler is sub-optimal, leading to performance loss and variability. Here, we investigate the impact of task placement on the performance of two massively parallel application codes on the Titan supercomputer, a turbulent combustion flow solver (S3D) and a molecular dynamics code (LAMMPS). Benchmark studies show a significant deviation from ideal weak scaling and variability in performance. The inter-task communication distance was determined to be one of the significant contributors to the performance degradation and variability. A genetic algorithm-based parallel optimization technique was used to optimize the task ordering. This technique provides an improved placement of the tasks on the nodes, taking into account the application's communication topology and the system interconnect topology. As a result, application benchmarks after task reordering through genetic algorithm show a significant improvement in performance and reduction in variability, therefore enabling the applications to achieve better time to solution and scalability on Titan during production.
Negri, Lucas; Nied, Ademir; Kalinowski, Hypolito; Paterno, Aleksander
2011-01-01
This paper presents a benchmark for peak detection algorithms employed in fiber Bragg grating spectrometric interrogation systems. The accuracy, precision, and computational performance of currently used algorithms and those of a new proposed artificial neural network algorithm are compared. Centroid and gaussian fitting algorithms are shown to have the highest precision but produce systematic errors that depend on the FBG refractive index modulation profile. The proposed neural network displays relatively good precision with reduced systematic errors and improved computational performance when compared to other networks. Additionally, suitable algorithms may be chosen with the general guidelines presented. PMID:22163806
NASA Astrophysics Data System (ADS)
Jia, Chun-Xiao; Liu, Run-Ran
2015-10-01
Recently, many scaling laws of interevent time distribution of human behaviors are observed and some quantitative understanding of human behaviors are also provided by researchers. In this paper, we propose a modified collaborative filtering algorithm by making use the scaling law of human behaviors for information filtering. Extensive experimental analyses demonstrate that the accuracies on MovieLensand Last.fm datasets could be improved greatly, compared with the standard collaborative filtering. Surprisingly, further statistical analyses suggest that the present algorithm could simultaneously improve the novelty and diversity of recommendations. This work provides a creditable way for highly efficient information filtering.
Improved multiprocessor garbage collection algorithms
Newman, I.A.; Stallard, R.P.; Woodward, M.C.
1983-01-01
Outlines the results of an investigation of existing multiprocessor garbage collection algorithms and introduces two new algorithms which significantly improve some aspects of the performance of their predecessors. The two algorithms arise from different starting assumptions. One considers the case where the algorithm will terminate successfully whatever list structure is being processed and assumes that the extra data space should be minimised. The other seeks a very fast garbage collection time for list structures that do not contain loops. Results of both theoretical and experimental investigations are given to demonstrate the efficacy of the algorithms. 7 references.
Thrust stand evaluation of engine performance improvement algorithms in an F-15 airplane
NASA Technical Reports Server (NTRS)
Conners, Timothy R.
1992-01-01
An investigation is underway to determine the benefits of a new propulsion system optimization algorithm in an F-15 airplane. The performance seeking control (PSC) algorithm optimizes the quasi-steady-state performance of an F100 derivative turbofan engine for several modes of operation. The PSC algorithm uses an onboard software engine model that calculates thrust, stall margin, and other unmeasured variables for use in the optimization. As part of the PSC test program, the F-15 aircraft was operated on a horizontal thrust stand. Thrust was measured with highly accurate load cells. The measured thrust was compared to onboard model estimates and to results from posttest performance programs. Thrust changes using the various PSC modes were recorded. Those results were compared to benefits using the less complex highly integrated digital electronic control (HIDEC) algorithm. The PSC maximum thrust mode increased intermediate power thrust by 10 percent. The PSC engine model did very well at estimating measured thrust and closely followed the transients during optimization. Quantitative results from the evaluation of the algorithms and performance calculation models are included with emphasis on measured thrust results. The report presents a description of the PSC system and a discussion of factors affecting the accuracy of the thrust stand load measurements.
An Improved Performance Frequency Estimation Algorithm for Passive Wireless SAW Resonant Sensors
Liu, Boquan; Zhang, Chenrui; Ji, Xiaojun; Chen, Jing; Han, Tao
2014-01-01
Passive wireless surface acoustic wave (SAW) resonant sensors are suitable for applications in harsh environments. The traditional SAW resonant sensor system requires, however, Fourier transformation (FT) which has a resolution restriction and decreases the accuracy. In order to improve the accuracy and resolution of the measurement, the singular value decomposition (SVD)-based frequency estimation algorithm is applied for wireless SAW resonant sensor responses, which is a combination of a single tone undamped and damped sinusoid signal with the same frequency. Compared with the FT algorithm, the accuracy and the resolution of the method used in the self-developed wireless SAW resonant sensor system are validated. PMID:25429410
Wang, C L
2016-05-01
Three high-resolution positioning methods based on the FluoroBancroft linear-algebraic method [S. B. Andersson, Opt. Express 16, 18714 (2008)] are proposed for wavelength-shifting fiber (WLSF) neutron detectors. Using a Gaussian or exponential-decay light-response function, the non-linear relation of photon-number profiles vs. x-pixels was linearized and neutron positions were determined. After taking the super-Poissonian photon noise into account, the proposed algorithms give an average of 0.03-0.08 pixel position error much smaller than that (0.29 pixel) from a traditional maximum photon algorithm (MPA). The new algorithms result in better detector uniformity, less position misassignment (ghosting), better spatial resolution, and an equivalent or better instrument resolution in powder diffraction than the MPA. These improvements will facilitate broader applications of WLSF detectors at time-of-flight neutron powder diffraction beamlines, including single-crystal diffraction and texture analysis. PMID:27250410
Wang, Mengjun; Devarajan, Karthik; Singal, Amit G; Marrero, Jorge A; Dai, Jianliang; Feng, Ziding; Rinaudo, Jo Ann S; Srivastava, Sudhir; Evans, Alison; Hann, Hie-Won; Lai, Yinzhi; Yang, Hushan; Block, Timothy M; Mehta, Anand
2016-02-01
Biomarkers for the early diagnosis of hepatocellular carcinoma (HCC) are needed to decrease mortality from this cancer. However, as new biomarkers have been slow to be brought to clinical practice, we have developed a diagnostic algorithm that utilizes commonly used clinical measurements in those at risk of developing HCC. Briefly, as α-fetoprotein (AFP) is routinely used, an algorithm that incorporated AFP values along with four other clinical factors was developed. Discovery analysis was performed on electronic data from patients who had liver disease (cirrhosis) alone or HCC in the background of cirrhosis. The discovery set consisted of 360 patients from two independent locations. A logistic regression algorithm was developed that incorporated log-transformed AFP values with age, gender, alkaline phosphatase, and alanine aminotransferase levels. We define this as the Doylestown algorithm. In the discovery set, the Doylestown algorithm improved the overall performance of AFP by 10%. In subsequent external validation in over 2,700 patients from three independent sites, the Doylestown algorithm improved detection of HCC as compared with AFP alone by 4% to 20%. In addition, at a fixed specificity of 95%, the Doylestown algorithm improved the detection of HCC as compared with AFP alone by 2% to 20%. In conclusion, the Doylestown algorithm consolidates clinical laboratory values, with age and gender, which are each individually associated with HCC risk, into a single value that can be used for HCC risk assessment. As such, it should be applicable and useful to the medical community that manages those at risk for developing HCC. PMID:26712941
Improving nonlinear performance of the HEPS baseline design with a genetic algorithm
NASA Astrophysics Data System (ADS)
Jiao, Yi
2016-07-01
A baseline design for the High Energy Photon Source has been proposed, with a natural emittance of 60 pm·rad within a circumference of about 1.3 kilometers. Nevertheless, the nonlinear performance of the design needs further improvements to increase both the dynamic aperture and the momentum acceptance. In this study, genetic optimization of the linear optics is performed, so as to find all the possible solutions with weaker sextupoles and hence weaker nonlinearities, while keeping the emittance at the same level as the baseline design. The solutions obtained enable us to explore the dependence of nonlinear dynamics on the working point. The result indicates that with the same layout, it is feasible to obtain much better nonlinear performance with a delicate tuning of the magnetic field strengths and a wise choice of the working point. Supported by NSFC (11475202, 11405187) and Youth Innovation Promotion Association CAS (2015009)
NASA Astrophysics Data System (ADS)
Wang, Xingwei; Song, XiaoFei; Chapman, Brian E.; Zheng, Bin
2012-03-01
We developed a new pulmonary vascular tree segmentation/extraction algorithm. The purpose of this study was to assess whether adding this new algorithm to our previously developed computer-aided detection (CAD) scheme of pulmonary embolism (PE) could improve the CAD performance (in particular reducing false positive detection rates). A dataset containing 12 CT examinations with 384 verified pulmonary embolism regions associated with 24 threedimensional (3-D) PE lesions was selected in this study. Our new CAD scheme includes the following image processing and feature classification steps. (1) A 3-D based region growing process followed by a rolling-ball algorithm was utilized to segment lung areas. (2) The complete pulmonary vascular trees were extracted by combining two approaches of using an intensity-based region growing to extract the larger vessels and a vessel enhancement filtering to extract the smaller vessel structures. (3) A toboggan algorithm was implemented to identify suspicious PE candidates in segmented lung or vessel area. (4) A three layer artificial neural network (ANN) with the topology 27-10-1 was developed to reduce false positive detections. (5) A k-nearest neighbor (KNN) classifier optimized by a genetic algorithm was used to compute detection scores for the PE candidates. (6) A grouping scoring method was designed to detect the final PE lesions in three dimensions. The study showed that integrating the pulmonary vascular tree extraction algorithm into the CAD scheme reduced false positive rates by 16.2%. For the case based 3D PE lesion detecting results, the integrated CAD scheme achieved 62.5% detection sensitivity with 17.1 false-positive lesions per examination.
Wang, C. L.
2016-05-17
On the basis of FluoroBancroft linear-algebraic method [S.B. Andersson, Opt. Exp. 16, 18714 (2008)] three highly-resolved positioning methodswere proposed for wavelength-shifting fiber (WLSF) neutron detectors. Using a Gaussian or exponential-decay light-response function (LRF), the non-linear relation of photon-number profiles vs. x-pixels was linearized and neutron positions were determined. The proposed algorithms give an average 0.03-0.08 pixel position error, much smaller than that (0.29 pixel) from a traditional maximum photon algorithm (MPA). The new algorithms result in better detector uniformity, less position misassignment (ghosting), better spatial resolution, and an equivalent or better instrument resolution in powder diffraction than the MPA. Moreover,more » these characters will facilitate broader applications of WLSF detectors at time-of-flight neutron powder diffraction beamlines, including single-crystal diffraction and texture analysis.« less
A Hybrid Feature Selection Method to Improve Performance of a Group of Classification Algorithms
NASA Astrophysics Data System (ADS)
Naseriparsa, Mehdi; Bidgoli, Amir-Masoud; Varaee, Touraj
2013-05-01
In this paper a hybrid feature selection method is proposed which takes advantages of wrapper subset evaluation with a lower cost and improves the performance of a group of classifiers. The method uses combination of sample domain filtering and resampling to refine the sample domain and two feature subset evaluation methods to select reliable features. This method utilizes both feature space and sample domain in two phases. The first phase filters and resamples the sample domain and the second phase adopts a hybrid procedure by information gain, wrapper subset evaluation and genetic search to find the optimal feature space. Experiments carried out on different types of datasets from UCI Repository of Machine Learning databases and the results show a rise in the average performance of five classifiers (Naive Bayes, Logistic, Multilayer Perceptron, Best First Decision Tree and JRIP) simultaneously and the classification error for these classifiers decreases considerably. The experiments also show that this method outperforms other feature selection methods with a lower cost.
ERIC Educational Resources Information Center
1996
This document contains four papers presented at a symposium on performance improvement moderated by Edward Schorer at the 1996 conference of the Academy of Human Resource Development (AHRD) "The Organizational Ecology of Ethical Problems: International Case Studies in the Light of HPT [Human Performance Technology]" (Peter J. Dean, Laurence…
Hernandez, Wilmar
2005-01-01
In this paper, a sensor to measure the rollover angle of a car under performance tests is presented. Basically, the sensor consists of a dual-axis accelerometer, analog-electronic instrumentation stages, a data acquisition system and an adaptive filter based on a recursive least-squares (RLS) lattice algorithm. In short, the adaptive filter is used to improve the performance of the rollover sensor by carrying out an optimal prediction of the relevant signal coming from the sensor, which is buried in a broad-band noise background where we have little knowledge of the noise characteristics. The experimental results are satisfactory and show a significant improvement in the signal-to-noise ratio at the system output.
NASA Astrophysics Data System (ADS)
Yeung, Wing-Keung; Chang, Rocky K. C.
1998-12-01
A drastic TCP performance degradation was reported when TCP is operated on the ATM networks. This deadlock problem is 'caused' by the high speed provided by the ATM networks. Therefore this deadlock problem is shared by any high-speed networking technologies when TCP is run on them. The problems are caused by the interaction of the sender-side and receiver-side Silly Window Syndrome (SWS) avoidance algorithms because the network's Maximum Segment Size (MSS) is no longer small when compared with the sender and receiver socket buffer sizes. Here we propose a new receiver-side adaptive acknowledgment algorithm (RSA3) to eliminate the deadlock problems while maintaining the SWS avoidance mechanisms. Unlike the current delayed acknowledgment strategy, the RSA3 does not rely on the exact value of MSS an the receiver's buffer size to determine the acknowledgement threshold.Instead the RSA3 periodically probes the sender to estimate the maximum amount of data that can be sent without receiving acknowledgement from the receiver. The acknowledgment threshold is computed as 35 percent of the estimate. In this way, deadlock-free TCP transmission is guaranteed. Simulation studies have shown that the RSA3 even improves the throughput performance in some non-deadlock regions. This is due to a quicker response taken by the RSA3 receiver. We have also evaluated different acknowledgment thresholds. It is found that the case of 35 percent gives the best performance when the sender and receiver buffer sizes are large.
NASA Astrophysics Data System (ADS)
Nejati, R.; Eshtehardiha, S.; Poudeh, M. Bayati
2008-10-01
The DC converter can be employed alone for the stabilization or the control of DC voltage of a battery or it can be a component of a complex converter to control the intermediate or output voltages. Due to the switching property included in their structure, DC-DC converters have a non-linear behavior and their controlling design is accompanied with complexities. But by employing the average method it is possible to approximate the system by a linear system and then linear control methods can be used. Dynamic performance of buck converters output voltage can be controlled by methods of Linear Quadratic Regulator (LQR) and PID. The former controller designing needs to positive definite matrix selection and the later is relative to desired pole places in complex coordinate. In this article, matrixes coefficients and the best constant values for PID controllers are selected based on Genetic algorithm method. The simulation results show an improvement in voltage control response.
Improved piecewise orthogonal signal correction algorithm.
Feudale, Robert N; Tan, Huwei; Brown, Steven D
2003-10-01
Piecewise orthogonal signal correction (POSC), an algorithm that performs local orthogonal filtering, was recently developed to process spectral signals. POSC was shown to improve partial leastsquares regression models over models built with conventional OSC. However, rank deficiencies within the POSC algorithm lead to artifacts in the filtered spectra when removing two or more POSC components. Thus, an updated OSC algorithm for use with the piecewise procedure is reported. It will be demonstrated how the mathematics of this updated OSC algorithm were derived from the previous version and why some OSC versions may not be as appropriate to use with the piecewise modeling procedure as the algorithm reported here. PMID:14639746
NASA Astrophysics Data System (ADS)
Jun, Xie Cheng; Su, Yan; Wei, Zhang
2006-08-01
In this paper, a modified algorithm was introduced to improve Rice coding algorithm and researches of image compression with the CDF (2,2) wavelet lifting scheme was made. Our experiments show that the property of the lossless image compression is much better than Huffman, Zip, lossless JPEG, RAR, and a little better than (or equal to) the famous SPIHT. The lossless compression rate is improved about 60.4%, 45%, 26.2%, 16.7%, 0.4% on average. The speed of the encoder is faster about 11.8 times than the SPIHT's and its efficiency in time can be improved by 162%. The speed of the decoder is faster about 12.3 times than that of the SPIHT's and its efficiency in time can be rasied about 148%. This algorithm, instead of largest levels wavelet transform, has high coding efficiency when the wavelet transform levels is larger than 3. For the source model of distributions similar to the Laplacian, it can improve the efficiency of coding and realize the progressive transmit coding and decoding.
An improved Camshift algorithm for target recognition
NASA Astrophysics Data System (ADS)
Fu, Min; Cai, Chao; Mao, Yusu
2015-12-01
Camshift algorithm and three frame difference algorithm are the popular target recognition and tracking methods. Camshift algorithm requires a manual initialization of the search window, which needs the subjective error and coherence, and only in the initialization calculating a color histogram, so the color probability model cannot be updated continuously. On the other hand, three frame difference method does not require manual initialization search window, it can make full use of the motion information of the target only to determine the range of motion. But it is unable to determine the contours of the object, and can not make use of the color information of the target object. Therefore, the improved Camshift algorithm is proposed to overcome the disadvantages of the original algorithm, the three frame difference operation is combined with the object's motion information and color information to identify the target object. The improved Camshift algorithm is realized and shows better performance in the recognition and tracking of the target.
High-performance combinatorial algorithms
Pinar, Ali
2003-10-31
Combinatorial algorithms have long played an important role in many applications of scientific computing such as sparse matrix computations and parallel computing. The growing importance of combinatorial algorithms in emerging applications like computational biology and scientific data mining calls for development of a high performance library for combinatorial algorithms. Building such a library requires a new structure for combinatorial algorithms research that enables fast implementation of new algorithms. We propose a structure for combinatorial algorithms research that mimics the research structure of numerical algorithms. Numerical algorithms research is nicely complemented with high performance libraries, and this can be attributed to the fact that there are only a small number of fundamental problems that underlie numerical solvers. Furthermore there are only a handful of kernels that enable implementation of algorithms for these fundamental problems. Building a similar structure for combinatorial algorithms will enable efficient implementations for existing algorithms and fast implementation of new algorithms. Our results will promote utilization of combinatorial techniques and will impact research in many scientific computing applications, some of which are listed.
Farsani, Mahsa Saffari; Sahhaf, Masoud Reza Aghabozorgi; Abootalebi, Vahid
2016-01-01
The aim of this paper is to improve the performance of the conventional Goertzel algorithm in determining the protein coding regions in deoxyribonucleic acid (DNA) sequences. First, the symbolic DNA sequences are converted into numerical signals using electron ion interaction potential method. Then by combining the modified anti-notch filter and linear predictive coding model, we proposed an efficient algorithm to achieve the performance improvement in the Goertzel algorithm for estimating genetic regions. Finally, a thresholding method is applied to precisely identify the exon and intron regions. The proposed algorithm is applied to several genes, including genes available in databases BG570 and HMR195 and the results are compared to other methods based on the nucleotide level evaluation criteria. Results demonstrate that our proposed method reduces the number of incorrect nucleotides which are estimated to be in the noncoding region. In addition, the area under the receiver operating characteristic curve has improved by the factor of 1.35 and 1.12 in HMR195 and BG570 datasets respectively, in comparison with the conventional Goertzel algorithm. PMID:27563569
Farsani, Mahsa Saffari; Sahhaf, Masoud Reza Aghabozorgi; Abootalebi, Vahid
2016-01-01
The aim of this paper is to improve the performance of the conventional Goertzel algorithm in determining the protein coding regions in deoxyribonucleic acid (DNA) sequences. First, the symbolic DNA sequences are converted into numerical signals using electron ion interaction potential method. Then by combining the modified anti-notch filter and linear predictive coding model, we proposed an efficient algorithm to achieve the performance improvement in the Goertzel algorithm for estimating genetic regions. Finally, a thresholding method is applied to precisely identify the exon and intron regions. The proposed algorithm is applied to several genes, including genes available in databases BG570 and HMR195 and the results are compared to other methods based on the nucleotide level evaluation criteria. Results demonstrate that our proposed method reduces the number of incorrect nucleotides which are estimated to be in the noncoding region. In addition, the area under the receiver operating characteristic curve has improved by the factor of 1.35 and 1.12 in HMR195 and BG570 datasets respectively, in comparison with the conventional Goertzel algorithm. PMID:27563569
Improved autonomous star identification algorithm
NASA Astrophysics Data System (ADS)
Luo, Li-Yan; Xu, Lu-Ping; Zhang, Hua; Sun, Jing-Rong
2015-06-01
The log-polar transform (LPT) is introduced into the star identification because of its rotation invariance. An improved autonomous star identification algorithm is proposed in this paper to avoid the circular shift of the feature vector and to reduce the time consumed in the star identification algorithm using LPT. In the proposed algorithm, the star pattern of the same navigation star remains unchanged when the stellar image is rotated, which makes it able to reduce the star identification time. The logarithmic values of the plane distances between the navigation and its neighbor stars are adopted to structure the feature vector of the navigation star, which enhances the robustness of star identification. In addition, some efforts are made to make it able to find the identification result with fewer comparisons, instead of searching the whole feature database. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition rate and robustness by the proposed algorithm are better than those by the LPT algorithm and the modified grid algorithm. Project supported by the National Natural Science Foundation of China (Grant Nos. 61172138 and 61401340), the Open Research Fund of the Academy of Satellite Application, China (Grant No. 2014_CXJJ-DH_12), the Fundamental Research Funds for the Central Universities, China (Grant Nos. JB141303 and 201413B), the Natural Science Basic Research Plan in Shaanxi Province, China (Grant No. 2013JQ8040), the Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20130203120004), and the Xi’an Science and Technology Plan, China (Grant. No CXY1350(4)).
Benchmarking image fusion algorithm performance
NASA Astrophysics Data System (ADS)
Howell, Christopher L.
2012-06-01
Registering two images produced by two separate imaging sensors having different detector sizes and fields of view requires one of the images to undergo transformation operations that may cause its overall quality to degrade with regards to visual task performance. This possible change in image quality could add to an already existing difference in measured task performance. Ideally, a fusion algorithm would take as input unaltered outputs from each respective sensor used in the process. Therefore, quantifying how well an image fusion algorithm performs should be base lined to whether the fusion algorithm retained the performance benefit achievable by each independent spectral band being fused. This study investigates an identification perception experiment using a simple and intuitive process for discriminating between image fusion algorithm performances. The results from a classification experiment using information theory based image metrics is presented and compared to perception test results. The results show an effective performance benchmark for image fusion algorithms can be established using human perception test data. Additionally, image metrics have been identified that either agree with or surpass the performance benchmark established.
Improved Heat-Stress Algorithm
NASA Technical Reports Server (NTRS)
Teets, Edward H., Jr.; Fehn, Steven
2007-01-01
NASA Dryden presents an improved and automated site-specific algorithm for heat-stress approximation using standard atmospheric measurements routinely obtained from the Edwards Air Force Base weather detachment. Heat stress, which is the net heat load a worker may be exposed to, is officially measured using a thermal-environment monitoring system to calculate the wet-bulb globe temperature (WBGT). This instrument uses three independent thermometers to measure wet-bulb, dry-bulb, and the black-globe temperatures. By using these improvements, a more realistic WBGT estimation value can now be produced. This is extremely useful for researchers and other employees who are working on outdoor projects that are distant from the areas that the Web system monitors. Most importantly, the improved WBGT estimations will make outdoor work sites safer by reducing the likelihood of heat stress.
NASA Astrophysics Data System (ADS)
Smith, R.; Kasprzyk, J. R.; Zagona, E. A.
2015-12-01
Instead of building new infrastructure to increase their supply reliability, water resource managers are often tasked with better management of current systems. The managers often have existing simulation models that aid their planning, and lack methods for efficiently generating and evaluating planning alternatives. This presentation discusses how multiobjective evolutionary algorithm (MOEA) decision support can be used with the sophisticated water infrastructure model, RiverWare, in highly constrained water planning environments. We first discuss a study that performed a many-objective tradeoff analysis of water supply in the Tarrant Regional Water District (TRWD) in Texas. RiverWare is combined with the Borg MOEA to solve a seven objective problem that includes systemwide performance objectives and individual reservoir storage reliability. Decisions within the formulation balance supply in multiple reservoirs and control pumping between the eastern and western parts of the system. The RiverWare simulation model is forced by two stochastic hydrology scenarios to inform how management changes in wet versus dry conditions. The second part of the presentation suggests how a broader set of RiverWare-MOEA studies can inform tradeoffs in other systems, especially in political situations where multiple actors are in conflict over finite water resources. By incorporating quantitative representations of diverse parties' objectives during the search for solutions, MOEAs may provide support for negotiations and lead to more widely beneficial water management outcomes.
NASA Astrophysics Data System (ADS)
Kartiwa, Iwa; Jung, Sang-Min; Hong, Moon-Ki; Han, Sang-Kook
2014-03-01
In this paper, we propose a novel fast adaptive approach that was applied to an OFDM-PON 20-km single fiber loopback transmission system to improve channel performance in term of stabilized BER below 2 × 10-3 and higher throughput beyond 10 Gb/s. The upstream transmission is performed through light source-seeded modulation using 1-GHz RSOA at the ONU. Experimental results indicated that the dynamic rate adaptation algorithm based on greedy Levin-Campello could be an effective solution to mitigate channel instability and data rate degradation caused by the Rayleigh back scattering effect and inefficient resource subcarrier allocation.
Improving Search Algorithms by Using Intelligent Coordinates
NASA Technical Reports Server (NTRS)
Wolpert, David H.; Tumer, Kagan; Bandari, Esfandiar
2004-01-01
We consider algorithms that maximize a global function G in a distributed manner, using a different adaptive computational agent to set each variable of the underlying space. Each agent eta is self-interested; it sets its variable to maximize its own function g (sub eta). Three factors govern such a distributed algorithm's performance, related to exploration/exploitation, game theory, and machine learning. We demonstrate how to exploit alI three factors by modifying a search algorithm's exploration stage: rather than random exploration, each coordinate of the search space is now controlled by a separate machine-learning-based player engaged in a noncooperative game. Experiments demonstrate that this modification improves simulated annealing (SA) by up to an order of magnitude for bin packing and for a model of an economic process run over an underlying network. These experiments also reveal interesting small-world phenomena.
An on-line template improvement algorithm
NASA Astrophysics Data System (ADS)
Yin, Yilong; Zhao, Bo; Yang, Xiukun
2005-03-01
In automatic fingerprint identification system, incomplete or rigid template may lead to false rejection and false matching. So, how to improve quality of the template, which is called template improvement, is important to automatic fingerprint identify system. In this paper, we propose a template improve algorithm. Based on the case-based method of machine learning and probability theory, we improve the template by deleting pseudo minutia, restoring lost genuine minutia and updating the information of minutia such as positions and directions. And special fingerprint image database is built for this work. Experimental results on this database indicate that our method is effective and quality of fingerprint template is improved evidently. Accordingly, performance of fingerprint matching is also improved stably along with the increase of using time.
Improved MFCC algorithm in speaker recognition system
NASA Astrophysics Data System (ADS)
Shi, Yibo; Wang, Li
2011-10-01
In speaker recognition systems, one of the key feature parameters is MFCC, which can be used for speaker recognition. So, how to extract MFCC parameter in speech signals more exactly and efficiently, decides the performance of the system. Theoretically, MFCC parameters are used to describe the spectrum envelope of the vocal tract characteristics and often ignore the impacts of fundamental frequency. But in practice, MFCC can be influenced by fundamental frequency which can cause palpable performance reduction. So, smoothing MFCC (SMFCC), which based on smoothing short-term spectral amplitude envelope, has been proposed to improve MFCC algorithm. Experimental results show that improved MFCC parameters---SMFCC can degrade the bad influences of fundamental frequency effectively and upgrade the performances of speaker recognition system. Especially for female speakers, who have higher fundamental frequency, the recognition rate improves more significantly.
Belief network algorithms: A study of performance
Jitnah, N.
1996-12-31
This abstract gives an overview of the work. We present a survey of Belief Network algorithms and propose a domain characterization system to be used as a basis for algorithm comparison and for predicting algorithm performance.
Lu, Bin; Yan, Hong-Bing; Mu, Chao-Wei; Gao, Yang; Hou, Zhi-Hui; Wang, Zhi-Qiang; Liu, Kun; Parinella, Ashley H.; Leipsic, Jonathon A.
2015-01-01
Objective To investigate the effect of a novel motion-correction algorithm (Snap-short Freeze, SSF) on image quality and diagnostic accuracy in patients undergoing prospectively ECG-triggered CCTA without administering rate-lowering medications. Materials and Methods Forty-six consecutive patients suspected of CAD prospectively underwent CCTA using prospective ECG-triggering without rate control and invasive coronary angiography (ICA). Image quality, interpretability, and diagnostic performance of SSF were compared with conventional multisegment reconstruction without SSF, using ICA as the reference standard. Results All subjects (35 men, 57.6 ± 8.9 years) successfully underwent ICA and CCTA. Mean heart rate was 68.8±8.4 (range: 50–88 beats/min) beats/min without rate controlling medications during CT scanning. Overall median image quality score (graded 1–4) was significantly increased from 3.0 to 4.0 by the new algorithm in comparison to conventional reconstruction. Overall interpretability was significantly improved, with a significant reduction in the number of non-diagnostic segments (690 of 694, 99.4% vs 659 of 694, 94.9%; P<0.001). However, only the right coronary artery (RCA) showed a statistically significant difference (45 of 46, 97.8% vs 35 of 46, 76.1%; P = 0.004) on a per-vessel basis in this regard. Diagnostic accuracy for detecting ≥50% stenosis was improved using the motion-correction algorithm on per-vessel [96.2% (177/184) vs 87.0% (160/184); P = 0.002] and per-segment [96.1% (667/694) vs 86.6% (601/694); P <0.001] levels, but there was not a statistically significant improvement on a per-patient level [97.8 (45/46) vs 89.1 (41/46); P = 0.203]. By artery analysis, diagnostic accuracy was improved only for the RCA [97.8% (45/46) vs 78.3% (36/46); P = 0.007]. Conclusion The intracycle motion correction algorithm significantly improved image quality and diagnostic interpretability in patients undergoing CCTA with prospective ECG triggering and
Ojala, Jarkko; Kapanen, Mika; Hyödynmaa, Simo
2016-06-01
New version 13.6.23 of the electron Monte Carlo (eMC) algorithm in Varian Eclipse™ treatment planning system has a model for 4MeV electron beam and some general improvements for dose calculation. This study provides the first overall accuracy assessment of this algorithm against full Monte Carlo (MC) simulations for electron beams from 4MeV to 16MeV with most emphasis on the lower energy range. Beams in a homogeneous water phantom and clinical treatment plans were investigated including measurements in the water phantom. Two different material sets were used with full MC: (1) the one applied in the eMC algorithm and (2) the one included in the Eclipse™ for other algorithms. The results of clinical treatment plans were also compared to those of the older eMC version 11.0.31. In the water phantom the dose differences against the full MC were mostly less than 3% with distance-to-agreement (DTA) values within 2mm. Larger discrepancies were obtained in build-up regions, at depths near the maximum electron ranges and with small apertures. For the clinical treatment plans the overall dose differences were mostly within 3% or 2mm with the first material set. Larger differences were observed for a large 4MeV beam entering curved patient surface with extended SSD and also in regions of large dose gradients. Still the DTA values were within 3mm. The discrepancies between the eMC and the full MC were generally larger for the second material set. The version 11.0.31 performed always inferiorly, when compared to the 13.6.23. PMID:27189311
Improved imaging algorithm for bridge crack detection
NASA Astrophysics Data System (ADS)
Lu, Jingxiao; Song, Pingli; Han, Kaihong
2012-04-01
This paper present an improved imaging algorithm for bridge crack detection, through optimizing the eight-direction Sobel edge detection operator, making the positioning of edge points more accurate than without the optimization, and effectively reducing the false edges information, so as to facilitate follow-up treatment. In calculating the crack geometry characteristics, we use the method of extracting skeleton on single crack length. In order to calculate crack area, we construct the template of area by making logical bitwise AND operation of the crack image. After experiment, the results show errors of the crack detection method and actual manual measurement are within an acceptable range, meet the needs of engineering applications. This algorithm is high-speed and effective for automated crack measurement, it can provide more valid data for proper planning and appropriate performance of the maintenance and rehabilitation processes of bridge.
Cheng, Wen-Chang
2012-01-01
In this paper we propose a robust lane detection and tracking method by combining particle filters with the particle swarm optimization method. This method mainly uses the particle filters to detect and track the local optimum of the lane model in the input image and then seeks the global optimal solution of the lane model by a particle swarm optimization method. The particle filter can effectively complete lane detection and tracking in complicated or variable lane environments. However, the result obtained is usually a local optimal system status rather than the global optimal system status. Thus, the particle swarm optimization method is used to further refine the global optimal system status in all system statuses. Since the particle swarm optimization method is a global optimization algorithm based on iterative computing, it can find the global optimal lane model by simulating the food finding way of fish school or insects under the mutual cooperation of all particles. In verification testing, the test environments included highways and ordinary roads as well as straight and curved lanes, uphill and downhill lanes, lane changes, etc. Our proposed method can complete the lane detection and tracking more accurately and effectively then existing options. PMID:23235453
Jerry L. Harbour; Julie L. Marble
2005-09-01
Countless articles and books have been written about and numerous programs have been developed to improve performance. Despite this plethora of activity on how to improve performance, we have largely failed to address the more fundamental question of how performance actually improves. To begin exploring this more basic question, we have plotted some 1,200 performance records to date and found that irrespective of venue, industry, or business, there seems to be a fundamental and repeatable set of concepts regarding how performance improves over time. Such gained insights represent both opportunities and challenges to the performance technologist. Differences in performance outcomes may, for example, be as much a function of the life cycle stage of a performance system as the efficacy of the selected improvement method itself. Accordingly, it may be more difficult to compare differing performance improvement methods than previously thought.
An improved algorithm for wildfire detection
NASA Astrophysics Data System (ADS)
Nakau, K.
2010-12-01
Satellite information of wild fire location has strong demands from society. Therefore, Understanding such demands is quite important to consider what to improve the wild fire detection algorithm. Interviews and considerations imply that the most important improvements are geographical resolution of the wildfire product and classification of fire; smoldering or flaming. Discussion with fire service agencies are performed with fire service agencies in Alaska and fire service volunteer groups in Indonesia. Alaska Fire Service (AFS) makes 3D-map overlaid by fire location every morning. Then, this 3D-map is examined by leaders of fire service teams to decide their strategy to fighting against wild fire. Especially, firefighters of both agencies seek the best walk path to approach the fire. Because of mountainous landscape, geospatial resolution is quite important for them. For example, walking in bush for 1km, as same as one pixel of fire product, is very tough for firefighters. Also, in case of remote wild fire, fire service agencies utilize satellite information to decide when to have a flight observation to confirm the status; expanding, flaming, smoldering or out. Therefore, it is also quite important to provide the classification of fire; flaming or smoldering. Not only the aspect of disaster management, wildfire emits huge amount of carbon into atmosphere as much as one quarter to one half of CO2 by fuel combustion (IPCC AR4). Reduction of the CO2 emission by human caused wildfire is important. To estimate carbon emission from wildfire, special resolution is quite important. To improve sensitivity of wild fire detection, author adopts radiance based wildfire detection. Different from the existing brightness temperature approach, we can easily consider reflectance of background land coverage. Especially for GCOM-C1/SGLI, band to detect fire with 250m resolution is 1.6μm wavelength. In this band, we have much more sunlight reflection. Therefore, we need to
Improvements of HITS Algorithms for Spam Links
NASA Astrophysics Data System (ADS)
Asano, Yasuhito; Tezuka, Yu; Nishizeki, Takao
The HITS algorithm proposed by Kleinberg is one of the representative methods of scoring Web pages by using hyperlinks. In the days when the algorithm was proposed, most of the pages given high score by the algorithm were really related to a given topic, and hence the algorithm could be used to find related pages. However, the algorithm and the variants including Bharat's improved HITS, abbreviated to BHITS, proposed by Bharat and Henzinger cannot be used to find related pages any more on today's Web, due to an increase of spam links. In this paper, we first propose three methods to find “linkfarms,” that is, sets of spam links forming a densely connected subgraph of a Web graph. We then present an algorithm, called a trust-score algorithm, to give high scores to pages which are not spam pages with a high probability. Combining the three methods and the trust-score algorithm with BHITS, we obtain several variants of the HITS algorithm. We ascertain by experiments that one of them, named TaN+BHITS using the trust-score algorithm and the method of finding linkfarms by employing name servers, is most suitable for finding related pages on today's Web. Our algorithms take time and memory no more than those required by the original HITS algorithm, and can be executed on a PC with a small amount of main memory.
An improvement on OCOG algorithm in satellite radar altimeter
NASA Astrophysics Data System (ADS)
Yu, Tao; Jiu, Dehang
The Offset Center of Gravity (OCOG) algorithm is a new tracking algorithm based on estimate of the pulse amplitude, the pulse width and the true center of area of the pulse. It's obvious that this algorithm is sufficiently robust to permit the altimeter to keep tracking many kinds of surfaces. Having analyzed the performance of this algorithm, it is discovered that the algorithm performs satisfactorily in high SNR environments, but fails in low SNR environments. The cause of the degradation of its performance is studied and it is pointed out that to the Brown return model and the sea ice return model, the performance of the OCOG algorithm can be improved in low SNR environments by using noise gate.
Improved algorithm for calculating the Chandrasekhar function
NASA Astrophysics Data System (ADS)
Jablonski, A.
2013-02-01
algorithms by selecting ranges of the argument omega in which the performance is the fastest. Reasons for the new version: Some of the theoretical models describing electron transport in condensed matter need a source of the Chandrasekhar H function values with an accuracy of at least 10 decimal places. Additionally, calculations of this function should be as fast as possible since frequent calls to a subroutine providing this function are made (e.g., numerical evaluation of a double integral with a complicated integrand containing the H function). Both conditions were satisfied in the algorithm previously published [1]. However, it has been found that a proper selection of the quadrature in an integral representation of the Chandrasekhar function may considerably decrease the running time. By suitable selection of the number of abscissas in Gauss-Legendre quadrature, the execution time was decreased by a factor of more than 20. Simultaneously, the accuracy of results has not been affected. Summary of revisions: (1) As in previous work [1], two integral representations of the Chandrasekhar function, H(x,omega), were considered: the expression published by Dudarev and Whelan [2] and the expression published by Davidović et al. [3]. The algorithms implementing these representations were designated A and B, respectively. All integrals in these implementations were previously calculated using Romberg quadrature. It has been found, however, that the use of Gauss-Legendre quadrature considerably improved the performance of both algorithms. Two conditions have to be satisfied. (i) The number of abscissas, N, has to be rather large, and (ii) the abscissas and corresponding weights should be determined with accuracy as high as possible. The abscissas and weights are available for N=16, 20, 24, 32, 40, 48, 64, 80, and 96 with accuracy of 20 decimal places [4], and all these values were introduced into a new procedure GAUSS replacing procedure ROMBERG. Due to the fact that the
Embarking on performance improvement.
Brown, Bobbi; Falk, Leslie Hough
2014-06-01
Healthcare organizations should approach performance improvement as a program, not a project. The program should be led by a guidance team that identifies goals, prioritizes work, and removes barriers to enable clinical improvement teams and work groups to realize performance improvements. A healthcare enterprise data warehouse can provide the initial foundation for the program analytics. Evidence-based best practices can help achieve improved outcomes and reduced costs. PMID:24968632
Optimization and Improvement of FOA Corner Cube Algorithm
McClay, W A; Awwal, A S; Burkhart, S C; Candy, J V
2004-10-01
Alignment of laser beams based on video images is a crucial task necessary to automate operation of the 192 beams at the National Ignition Facility (NIF). The final optics assembly (FOA) is the optical element that aligns the beam into the target chamber. This work presents an algorithm for determining the position of a corner cube alignment image in the final optics assembly. The improved algorithm was compared to the existing FOA algorithm on 900 noise-simulated images. While the existing FOA algorithm based on correlation with a synthetic template has a radial standard deviation of 1 pixel, the new algorithm based on classical matched filtering (CMF) and polynomial fit to the correlation peak improves the radial standard deviation performance to less than 0.3 pixels. In the new algorithm the templates are designed from real data stored during a year of actual operation.
Improved artificial bee colony algorithm based gravity matching navigation method.
Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang
2014-01-01
Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position. PMID:25046019
An Improved Back Propagation Neural Network Algorithm on Classification Problems
NASA Astrophysics Data System (ADS)
Nawi, Nazri Mohd; Ransing, R. S.; Salleh, Mohd Najib Mohd; Ghazali, Rozaida; Hamid, Norhamreeza Abdul
The back propagation algorithm is one the most popular algorithms to train feed forward neural networks. However, the convergence of this algorithm is slow, it is mainly because of gradient descent algorithm. Previous research demonstrated that in 'feed forward' algorithm, the slope of the activation function is directly influenced by a parameter referred to as 'gain'. This research proposed an algorithm for improving the performance of the back propagation algorithm by introducing the adaptive gain of the activation function. The gain values change adaptively for each node. The influence of the adaptive gain on the learning ability of a neural network is analysed. Multi layer feed forward neural networks have been assessed. Physical interpretation of the relationship between the gain value and the learning rate and weight values is given. The efficiency of the proposed algorithm is compared with conventional Gradient Descent Method and verified by means of simulation on four classification problems. In learning the patterns, the simulations result demonstrate that the proposed method converged faster on Wisconsin breast cancer with an improvement ratio of nearly 2.8, 1.76 on diabetes problem, 65% better on thyroid data sets and 97% faster on IRIS classification problem. The results clearly show that the proposed algorithm significantly improves the learning speed of the conventional back-propagation algorithm.
Performance Improvement Processes.
ERIC Educational Resources Information Center
1997
This document contains four papers from a symposium on performance improvement processes. In "Never the Twain Shall Meet?: A Glimpse into High Performance Work Practices and Downsizing" (Laurie J. Bassi, Mark E. Van Buren) evidence from a national cross-industry of more than 200 establishments is used to demonstrate that high-performance work…
Improving the algorithm of temporal relation propagation
NASA Astrophysics Data System (ADS)
Shen, Jifeng; Xu, Dan; Liu, Tongming
2005-03-01
In the military Multi Agent System, every agent needs to analyze the temporal relationships among the tasks or combat behaviors, and it"s very important to reflect the battlefield situation in time. The temporal relation among agents is usually very complex, and we model it with interval algebra (IA) network. Therefore an efficient temporal reasoning algorithm is vital in battle MAS model. The core of temporal reasoning is path consistency algorithm, an efficient path consistency algorithm is necessary. In this paper we used the Interval Matrix Calculus (IMC) method to represent the temporal relation, and optimized the path consistency algorithm by improving the efficiency of propagation of temporal relation based on the Allen's path consistency algorithm.
An improved edge detection algorithm for depth map inpainting
NASA Astrophysics Data System (ADS)
Chen, Weihai; Yue, Haosong; Wang, Jianhua; Wu, Xingming
2014-04-01
Three-dimensional (3D) measurement technology has been widely used in many scientific and engineering areas. The emergence of Kinect sensor makes 3D measurement much easier. However the depth map captured by Kinect sensor has some invalid regions, especially at object boundaries. These missing regions should be filled firstly. This paper proposes a depth-assisted edge detection algorithm and improves existing depth map inpainting algorithm using extracted edges. In the proposed algorithm, both color image and raw depth data are used to extract initial edges. Then the edges are optimized and are utilized to assist depth map inpainting. Comparative experiments demonstrate that the proposed edge detection algorithm can extract object boundaries and inhibit non-boundary edges caused by textures on object surfaces. The proposed depth inpainting algorithm can predict missing depth values successfully and has better performance than existing algorithm around object boundaries.
An improved dehazing algorithm of aerial high-definition image
NASA Astrophysics Data System (ADS)
Jiang, Wentao; Ji, Ming; Huang, Xiying; Wang, Chao; Yang, Yizhou; Li, Tao; Wang, Jiaoying; Zhang, Ying
2016-01-01
For unmanned aerial vehicle(UAV) images, the sensor can not get high quality images due to fog and haze weather. To solve this problem, An improved dehazing algorithm of aerial high-definition image is proposed. Based on the model of dark channel prior, the new algorithm firstly extracts the edges from crude estimated transmission map and expands the extracted edges. Then according to the expended edges, the algorithm sets a threshold value to divide the crude estimated transmission map into different areas and makes different guided filter on the different areas compute the optimized transmission map. The experimental results demonstrate that the performance of the proposed algorithm is substantially the same as the one based on dark channel prior and guided filter. The average computation time of the new algorithm is around 40% of the one as well as the detection ability of UAV image is improved effectively in fog and haze weather.
Performance analysis of cone detection algorithms.
Mariotti, Letizia; Devaney, Nicholas
2015-04-01
Many algorithms have been proposed to help clinicians evaluate cone density and spacing, as these may be related to the onset of retinal diseases. However, there has been no rigorous comparison of the performance of these algorithms. In addition, the performance of such algorithms is typically determined by comparison with human observers. Here we propose a technique to simulate realistic images of the cone mosaic. We use the simulated images to test the performance of three popular cone detection algorithms, and we introduce an algorithm which is used by astronomers to detect stars in astronomical images. We use Free Response Operating Characteristic (FROC) curves to evaluate and compare the performance of the four algorithms. This allows us to optimize the performance of each algorithm. We observe that performance is significantly enhanced by up-sampling the images. We investigate the effect of noise and image quality on cone mosaic parameters estimated using the different algorithms, finding that the estimated regularity is the most sensitive parameter. PMID:26366758
An improved harmony search algorithm with dynamically varying bandwidth
NASA Astrophysics Data System (ADS)
Kalivarapu, J.; Jain, S.; Bag, S.
2016-07-01
The present work demonstrates a new variant of the harmony search (HS) algorithm where bandwidth (BW) is one of the deciding factors for the time complexity and the performance of the algorithm. The BW needs to have both explorative and exploitative characteristics. The ideology is to use a large BW to search in the full domain and to adjust the BW dynamically closer to the optimal solution. After trying a series of approaches, a methodology inspired by the functioning of a low-pass filter showed satisfactory results. This approach was implemented in the self-adaptive improved harmony search (SIHS) algorithm and tested on several benchmark functions. Compared to the existing HS algorithm and its variants, SIHS showed better performance on most of the test functions. Thereafter, the algorithm was applied to geometric parameter optimization of a friction stir welding tool.
An improved HMM/SVM dynamic hand gesture recognition algorithm
NASA Astrophysics Data System (ADS)
Zhang, Yi; Yao, Yuanyuan; Luo, Yuan
2015-10-01
In order to improve the recognition rate and stability of dynamic hand gesture recognition, for the low accuracy rate of the classical HMM algorithm in train the B parameter, this paper proposed an improved HMM/SVM dynamic gesture recognition algorithm. In the calculation of the B parameter of HMM model, this paper introduced the SVM algorithm which has the strong ability of classification. Through the sigmoid function converted the state output of the SVM into the probability and treat this probability as the observation state transition probability of the HMM model. After this, it optimized the B parameter of HMM model and improved the recognition rate of the system. At the same time, it also enhanced the accuracy and the real-time performance of the human-computer interaction. Experiments show that this algorithm has a strong robustness under the complex background environment and the varying illumination environment. The average recognition rate increased from 86.4% to 97.55%.
MCNP Progress & Performance Improvements
Brown, Forrest B.; Bull, Jeffrey S.; Rising, Michael Evan
2015-04-14
Twenty-eight slides give information about the work of the US DOE/NNSA Nuclear Criticality Safety Program on MCNP6 under the following headings: MCNP6.1.1 Release, with ENDF/B-VII.1; Verification/Validation; User Support & Training; Performance Improvements; and Work in Progress. Whisper methodology will be incorporated into the code, and run speed should be increased.
Improving Surface Irrigation Performance
Technology Transfer Automated Retrieval System (TEKTRAN)
Surface irrigation systems often have a reputation for poor performance. One key feature of efficient surface irrigation systems is precision (e.g. laser-guided) land grading. Poor land grading can make other improvements ineffective. An important issue, related to land shaping, is developing the pr...
Improved Global Ocean Color Using Polymer Algorithm
NASA Astrophysics Data System (ADS)
Steinmetz, Francois; Ramon, Didier; Deschamps, ierre-Yves; Stum, Jacques
2010-12-01
A global ocean color product has been developed based on the use of the POLYMER algorithm to correct atmospheric scattering and sun glint and to process the data to a Level 2 ocean color product. Thanks to the use of this algorithm, the coverage and accuracy of the MERIS ocean color product have been significantly improved when compared to the standard product, therefore increasing its usefulness for global ocean monitor- ing applications like GLOBCOLOUR. We will present the latest developments of the algorithm, its first application to MODIS data and its validation against in-situ data from the MERMAID database. Examples will be shown of global NRT chlorophyll maps produced by CLS with POLYMER for operational applications like fishing or oil and gas industry, as well as its use by Scripps for a NASA study of the Beaufort and Chukchi seas.
An Improved Direction Finding Algorithm Based on Toeplitz Approximation
Wang, Qing; Chen, Hua; Zhao, Guohuang; Chen, Bin; Wang, Pichao
2013-01-01
In this paper, a novel direction of arrival (DOA) estimation algorithm called the Toeplitz fourth order cumulants multiple signal classification method (TFOC-MUSIC) algorithm is proposed through combining a fast MUSIC-like algorithm termed the modified fourth order cumulants MUSIC (MFOC-MUSIC) algorithm and Toeplitz approximation. In the proposed algorithm, the redundant information in the cumulants is removed. Besides, the computational complexity is reduced due to the decreased dimension of the fourth-order cumulants matrix, which is equal to the number of the virtual array elements. That is, the effective array aperture of a physical array remains unchanged. However, due to finite sampling snapshots, there exists an estimation error of the reduced-rank FOC matrix and thus the capacity of DOA estimation degrades. In order to improve the estimation performance, Toeplitz approximation is introduced to recover the Toeplitz structure of the reduced-dimension FOC matrix just like the ideal one which has the Toeplitz structure possessing optimal estimated results. The theoretical formulas of the proposed algorithm are derived, and the simulations results are presented. From the simulations, in comparison with the MFOC-MUSIC algorithm, it is concluded that the TFOC-MUSIC algorithm yields an excellent performance in both spatially-white noise and in spatially-color noise environments. PMID:23296331
An improved robust ADMM algorithm for quantum state tomography
NASA Astrophysics Data System (ADS)
Li, Kezhi; Zhang, Hui; Kuang, Sen; Meng, Fangfang; Cong, Shuang
2016-06-01
In this paper, an improved adaptive weights alternating direction method of multipliers algorithm is developed to implement the optimization scheme for recovering the quantum state in nearly pure states. The proposed approach is superior to many existing methods because it exploits the low-rank property of density matrices, and it can deal with unexpected sparse outliers as well. The numerical experiments are provided to verify our statements by comparing the results to three different optimization algorithms, using both adaptive and fixed weights in the algorithm, in the cases of with and without external noise, respectively. The results indicate that the improved algorithm has better performances in both estimation accuracy and robustness to external noise. The further simulation results show that the successful recovery rate increases when more qubits are estimated, which in fact satisfies the compressive sensing theory and makes the proposed approach more promising.
Improved motion information-based infrared dim target tracking algorithms
NASA Astrophysics Data System (ADS)
Lei, Liu; Zhijian, Huang
2014-11-01
Accurate and fast tracking of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. However, under complex backgrounds, such as clutter, varying illumination, and occlusion, the traditional tracking method often converges to a local maximum and loses the real infrared target. To cope with these problems, three improved tracking algorithm based on motion information are proposed in this paper, namely improved mean shift algorithm, improved Optical flow method and improved Particle Filter method. The basic principles and the implementing procedure of these modified algorithms for target tracking are described. Using these algorithms, the experiments on some real-life IR and color images are performed. The whole algorithm implementing processes and results are analyzed, and those algorithms for tracking targets are evaluated from the two aspects of subjective and objective. The results prove that the proposed method has satisfying tracking effectiveness and robustness. Meanwhile, it has high tracking efficiency and can be used for real-time tracking.
NASA Technical Reports Server (NTRS)
Lennard, D. J.
1978-01-01
Potential CF6 engine performance improvements directed at reduced fuel consumption were identified and screened relative to airline acceptability and are reviewed. The screening process developed to provide evaluations of fuel savings and economic factors including return on investment and direct operating cost is described. In addition, assessments of development risk and production potential are made. Several promising concepts selected for full-scale development based on a ranking involving these factors are discussed.
Passive MMW algorithm performance characterization using MACET
NASA Astrophysics Data System (ADS)
Williams, Bradford D.; Watson, John S.; Amphay, Sengvieng A.
1997-06-01
As passive millimeter wave sensor technology matures, algorithms which are tailored to exploit the benefits of this technology are being developed. The expedient development of such algorithms requires an understanding of not only the gross phenomenology, but also specific quirks and limitations inherent in sensors and the data gathering methodology specific to this regime. This level of understanding is approached as the technology matures and increasing amounts of data become available for analysis. The Armament Directorate of Wright Laboratory, WL/MN, has spearheaded the advancement of passive millimeter-wave technology in algorithm development tools and modeling capability as well as sensor development. A passive MMW channel is available within WL/MNs popular multi-channel modeling program Irma, and a sample passive MMW algorithm is incorporated into the Modular Algorithm Concept Evaluation Tool, an algorithm development and evaluation system. The Millimeter Wave Analysis of Passive Signatures system provides excellent data collection capability in the 35, 60, and 95 GHz MMW bands. This paper exploits these assets for the study of the PMMW signature of a High Mobility Multi- Purpose Wheeled Vehicle in the three bands mentioned, and the effect of camouflage upon this signature and autonomous target recognition algorithm performance.
Bootstrap performance profiles in stochastic algorithms assessment
Costa, Lino; Espírito Santo, Isabel A.C.P.; Oliveira, Pedro
2015-03-10
Optimization with stochastic algorithms has become a relevant research field. Due to its stochastic nature, its assessment is not straightforward and involves integrating accuracy and precision. Performance profiles for the mean do not show the trade-off between accuracy and precision, and parametric stochastic profiles require strong distributional assumptions and are limited to the mean performance for a large number of runs. In this work, bootstrap performance profiles are used to compare stochastic algorithms for different statistics. This technique allows the estimation of the sampling distribution of almost any statistic even with small samples. Multiple comparison profiles are presented for more than two algorithms. The advantages and drawbacks of each assessment methodology are discussed.
HALOE Algorithm Improvements for Upper Tropospheric Sounding
NASA Technical Reports Server (NTRS)
Thompson, Robert E.
2001-01-01
This report details the ongoing efforts by GATS, Inc., in conjunction with Hampton University and University of Wyoming, in NASA's Mission to Planet Earth UARS Science Investigator Program entitled "HALOE Algorithm Improvements for Upper Tropospheric Sounding." The goal of this effort is to develop and implement major inversion and processing improvements that will extend HALOE measurements further into the troposphere. In particular, O3, H2O, and CH4 retrievals may be extended into the middle troposphere, and NO, HCl and possibly HF into the upper troposphere. Key areas of research being carried out to accomplish this include: pointing/tracking analysis; cloud identification and modeling; simultaneous multichannel retrieval capability; forward model improvements; high vertical-resolution gas filter channel retrievals; a refined temperature retrieval; robust error analyses; long-term trend reliability studies; and data validation. The current (first year) effort concentrates on the pointer/tracker correction algorithms, cloud filtering and validation, and multichannel retrieval development. However, these areas are all highly coupled, so progress in one area benefits from and sometimes depends on work in others.
HALOE Algorithm Improvements for Upper Tropospheric Sounding
NASA Technical Reports Server (NTRS)
McHugh, Martin J.; Gordley, Larry L.; Russell, James M., III; Hervig, Mark E.
1999-01-01
This report details the ongoing efforts by GATS, Inc., in conjunction with Hampton University and University of Wyoming, in NASA's Mission to Planet Earth UARS Science Investigator Program entitled "HALOE Algorithm Improvements for Upper Tropospheric Soundings." The goal of this effort is to develop and implement major inversion and processing improvements that will extend HALOE measurements further into the troposphere. In particular, O3, H2O, and CH4 retrievals may be extended into the middle troposphere, and NO, HCl and possibly HF into the upper troposphere. Key areas of research being carried out to accomplish this include: pointing/tracking analysis; cloud identification and modeling; simultaneous multichannel retrieval capability; forward model improvements; high vertical-resolution gas filter channel retrievals; a refined temperature retrieval; robust error analyses; long-term trend reliability studies; and data validation. The current (first-year) effort concentrates on the pointer/tracker correction algorithms, cloud filtering and validation, and multi-channel retrieval development. However, these areas are all highly coupled, so progress in one area benefits from and sometimes depends on work in others.
HALOE Algorithm Improvements for Upper Tropospheric Sounding
NASA Technical Reports Server (NTRS)
Thompson, Robert Earl; McHugh, Martin J.; Gordley, Larry L.; Hervig, Mark E.; Russell, James M., III; Douglass, Anne (Technical Monitor)
2001-01-01
This report details the ongoing efforts by GATS, Inc., in conjunction with Hampton University and University of Wyoming, in NASA's Mission to Planet Earth Upper Atmospheric Research Satellite (UARS) Science Investigator Program entitled 'HALOE Algorithm Improvements for Upper Tropospheric Sounding.' The goal of this effort is to develop and implement major inversion and processing improvements that will extend Halogen Occultation Experiment (HALOE) measurements further into the troposphere. In particular, O3, H2O, and CH4 retrievals may be extended into the middle troposphere, and NO, HCl and possibly HF into the upper troposphere. Key areas of research being carried out to accomplish this include: pointing/tracking analysis; cloud identification and modeling; simultaneous multichannel retrieval capability; forward model improvements; high vertical-resolution gas filter channel retrievals; a refined temperature retrieval; robust error analyses; long-term trend reliability studies; and data validation. The current (first year) effort concentrates on the pointer/tracker correction algorithms, cloud filtering and validation, and multichannel retrieval development. However, these areas are all highly coupled, so progress in one area benefits from and sometimes depends on work in others.
Tuning target selection algorithms to improve galaxy redshift estimates
NASA Astrophysics Data System (ADS)
Hoyle, Ben; Paech, Kerstin; Rau, Markus Michael; Seitz, Stella; Weller, Jochen
2016-06-01
We showcase machine learning (ML) inspired target selection algorithms to determine which of all potential targets should be selected first for spectroscopic follow-up. Efficient target selection can improve the ML redshift uncertainties as calculated on an independent sample, while requiring less targets to be observed. We compare seven different ML targeting algorithms with the Sloan Digital Sky Survey (SDSS) target order, and with a random targeting algorithm. The ML inspired algorithms are constructed iteratively by estimating which of the remaining target galaxies will be most difficult for the ML methods to accurately estimate redshifts using the previously observed data. This is performed by predicting the expected redshift error and redshift offset (or bias) of all of the remaining target galaxies. We find that the predicted values of bias and error are accurate to better than 10-30 per cent of the true values, even with only limited training sample sizes. We construct a hypothetical follow-up survey and find that some of the ML targeting algorithms are able to obtain the same redshift predictive power with 2-3 times less observing time, as compared to that of the SDSS, or random, target selection algorithms. The reduction in the required follow-up resources could allow for a change to the follow-up strategy, for example by obtaining deeper spectroscopy, which could improve ML redshift estimates for deeper test data.
An improved back projection algorithm of ultrasound tomography
NASA Astrophysics Data System (ADS)
Xiaozhen, Chen; Mingxu, Su; Xiaoshu, Cai
2014-04-01
Binary logic back projection algorithm is improved in this work for the development of fast ultrasound tomography system with a better effect of image reconstruction. The new algorithm is characterized by an extra logical value `2' and dual-threshold processing of collected raw data. To compare with the original algorithm, a numerical simulation was conducted by the verification of COMSOL simulations formerly, and then a set of ultrasonic tomography system is established to perform the experiments of one, two and three cylindrical objects. The object images are reconstructed through the inversion of signals matrix acquired by the transducer array after a preconditioning, while the corresponding spatial imaging errors can obviously indicate that the improved back projection method can achieve modified inversion effect.
An improved back projection algorithm of ultrasound tomography
Xiaozhen, Chen; Mingxu, Su; Xiaoshu, Cai
2014-04-11
Binary logic back projection algorithm is improved in this work for the development of fast ultrasound tomography system with a better effect of image reconstruction. The new algorithm is characterized by an extra logical value ‘2’ and dual-threshold processing of collected raw data. To compare with the original algorithm, a numerical simulation was conducted by the verification of COMSOL simulations formerly, and then a set of ultrasonic tomography system is established to perform the experiments of one, two and three cylindrical objects. The object images are reconstructed through the inversion of signals matrix acquired by the transducer array after a preconditioning, while the corresponding spatial imaging errors can obviously indicate that the improved back projection method can achieve modified inversion effect.
TIRS stray light correction: algorithms and performance
NASA Astrophysics Data System (ADS)
Gerace, Aaron; Montanaro, Matthew; Beckmann, Tim; Tyrrell, Kaitlin; Cozzo, Alexandra; Carney, Trevor; Ngan, Vicki
2015-09-01
The Thermal Infrared Sensor (TIRS) onboard Landsat 8 was tasked with continuing thermal band measurements of the Earth as part of the Landsat program. From first light in early 2013, there were obvious indications that stray light was contaminating the thermal image data collected from the instrument. Traditional calibration techniques did not perform adequately as non-uniform banding was evident in the corrected data and error in absolute estimates of temperature over trusted buoys sites varied seasonally and, in worst cases, exceeded 9 K error. The development of an operational technique to remove the effects of the stray light has become a high priority to enhance the utility of the TIRS data. This paper introduces the current algorithm being tested by Landsat's calibration and validation team to remove stray light from TIRS image data. The integration of the algorithm into the EROS test system is discussed with strategies for operationalizing the method emphasized. Techniques for assessing the methodologies used are presented and potential refinements to the algorithm are suggested. Initial results indicate that the proposed algorithm significantly removes stray light artifacts from the image data. Specifically, visual and quantitative evidence suggests that the algorithm practically eliminates banding in the image data. Additionally, the seasonal variation in absolute errors is flattened and, in the worst case, errors of over 9 K are reduced to within 2 K. Future work focuses on refining the algorithm based on these findings and applying traditional calibration techniques to enhance the final image product.
Improved Algorithms Speed It Up for Codes
Hazi, A
2005-09-20
Huge computers, huge codes, complex problems to solve. The longer it takes to run a code, the more it costs. One way to speed things up and save time and money is through hardware improvements--faster processors, different system designs, bigger computers. But another side of supercomputing can reap savings in time and speed: software improvements to make codes--particularly the mathematical algorithms that form them--run faster and more efficiently. Speed up math? Is that really possible? According to Livermore physicist Eugene Brooks, the answer is a resounding yes. ''Sure, you get great speed-ups by improving hardware,'' says Brooks, the deputy leader for Computational Physics in N Division, which is part of Livermore's Physics and Advanced Technologies (PAT) Directorate. ''But the real bonus comes on the software side, where improvements in software can lead to orders of magnitude improvement in run times.'' Brooks knows whereof he speaks. Working with Laboratory physicist Abraham Szoeke and others, he has been instrumental in devising ways to shrink the running time of what has, historically, been a tough computational nut to crack: radiation transport codes based on the statistical or Monte Carlo method of calculation. And Brooks is not the only one. Others around the Laboratory, including physicists Andrew Williamson, Randolph Hood, and Jeff Grossman, have come up with innovative ways to speed up Monte Carlo calculations using pure mathematics.
Predicting the performance of a spatial gamut mapping algorithm
NASA Astrophysics Data System (ADS)
Bakke, Arne M.; Farup, Ivar; Hardeberg, Jon Y.
2009-01-01
Gamut mapping algorithms are currently being developed to take advantage of the spatial information in an image to improve the utilization of the destination gamut. These algorithms try to preserve the spatial information between neighboring pixels in the image, such as edges and gradients, without sacrificing global contrast. Experiments have shown that such algorithms can result in significantly improved reproduction of some images compared with non-spatial methods. However, due to the spatial processing of images, they introduce unwanted artifacts when used on certain types of images. In this paper we perform basic image analysis to predict whether a spatial algorithm is likely to perform better or worse than a good, non-spatial algorithm. Our approach starts by detecting the relative amount of areas in the image that are made up of uniformly colored pixels, as well as the amount of areas that contain details in out-of-gamut areas. A weighted difference is computed from these numbers, and we show that the result has a high correlation with the observed performance of the spatial algorithm in a previously conducted psychophysical experiment.
Quantitative comparison of the performance of SAR segmentation algorithms.
Caves, R; Quegan, S; White, R
1998-01-01
Methods to evaluate the performance of segmentation algorithms for synthetic aperture radar (SAR) images are developed, based on known properties of coherent speckle and a scene model in which areas of constant backscatter coefficient are separated by abrupt edges. Local and global measures of segmentation homogeneity are derived and applied to the outputs of two segmentation algorithms developed for SAR data, one based on iterative edge detection and segment growing, the other based on global maximum a posteriori (MAP) estimation using simulated annealing. The quantitative statistically based measures appear consistent with visual impressions of the relative quality of the segmentations produced by the two algorithms. On simulated data meeting algorithm assumptions, both algorithms performed well but MAP methods appeared visually and measurably better. On real data, MAP estimation was markedly the better method and retained performance comparable to that on simulated data, while the performance of the other algorithm deteriorated sharply. Improvements in the performance measures will require a more realistic scene model and techniques to recognize oversegmentation. PMID:18276219
CSA: An efficient algorithm to improve circular DNA multiple alignment
Fernandes, Francisco; Pereira, Luísa; Freitas, Ana T
2009-01-01
Background The comparison of homologous sequences from different species is an essential approach to reconstruct the evolutionary history of species and of the genes they harbour in their genomes. Several complete mitochondrial and nuclear genomes are now available, increasing the importance of using multiple sequence alignment algorithms in comparative genomics. MtDNA has long been used in phylogenetic analysis and errors in the alignments can lead to errors in the interpretation of evolutionary information. Although a large number of multiple sequence alignment algorithms have been proposed to date, they all deal with linear DNA and cannot handle directly circular DNA. Researchers interested in aligning circular DNA sequences must first rotate them to the "right" place using an essentially manual process, before they can use multiple sequence alignment tools. Results In this paper we propose an efficient algorithm that identifies the most interesting region to cut circular genomes in order to improve phylogenetic analysis when using standard multiple sequence alignment algorithms. This algorithm identifies the largest chain of non-repeated longest subsequences common to a set of circular mitochondrial DNA sequences. All the sequences are then rotated and made linear for multiple alignment purposes. To evaluate the effectiveness of this new tool, three different sets of mitochondrial DNA sequences were considered. Other tests considering randomly rotated sequences were also performed. The software package Arlequin was used to evaluate the standard genetic measures of the alignments obtained with and without the use of the CSA algorithm with two well known multiple alignment algorithms, the CLUSTALW and the MAVID tools, and also the visualization tool SinicView. Conclusion The results show that a circularization and rotation pre-processing step significantly improves the efficiency of public available multiple sequence alignment algorithms when used in the
Performance of a streaming mesh refinement algorithm.
Thompson, David C.; Pebay, Philippe Pierre
2004-08-01
In SAND report 2004-1617, we outline a method for edge-based tetrahedral subdivision that does not rely on saving state or communication to produce compatible tetrahedralizations. This report analyzes the performance of the technique by characterizing (a) mesh quality, (b) execution time, and (c) traits of the algorithm that could affect quality or execution time differently for different meshes. It also details the method used to debug the several hundred subdivision templates that the algorithm relies upon. Mesh quality is on par with other similar refinement schemes and throughput on modern hardware can exceed 600,000 output tetrahedra per second. But if you want to understand the traits of the algorithm, you have to read the report!
Empirical study of self-configuring genetic programming algorithm performance and behaviour
NASA Astrophysics Data System (ADS)
Semenkin, E.; Semenkina, M.
2015-01-01
The behaviour of the self-configuring genetic programming algorithm with a modified uniform crossover operator that implements a selective pressure on the recombination stage, is studied over symbolic programming problems. The operator's probabilistic rates interplay is studied and the role of operator variants on algorithm performance is investigated. Algorithm modifications based on the results of investigations are suggested. The performance improvement of the algorithm is demonstrated by the comparative analysis of suggested algorithms on the benchmark and real world problems.
Evaluating Algorithm Performance Metrics Tailored for Prognostics
NASA Technical Reports Server (NTRS)
Saxena, Abhinav; Celaya, Jose; Saha, Bhaskar; Saha, Sankalita; Goebel, Kai
2009-01-01
Prognostics has taken a center stage in Condition Based Maintenance (CBM) where it is desired to estimate Remaining Useful Life (RUL) of the system so that remedial measures may be taken in advance to avoid catastrophic events or unwanted downtimes. Validation of such predictions is an important but difficult proposition and a lack of appropriate evaluation methods renders prognostics meaningless. Evaluation methods currently used in the research community are not standardized and in many cases do not sufficiently assess key performance aspects expected out of a prognostics algorithm. In this paper we introduce several new evaluation metrics tailored for prognostics and show that they can effectively evaluate various algorithms as compared to other conventional metrics. Specifically four algorithms namely; Relevance Vector Machine (RVM), Gaussian Process Regression (GPR), Artificial Neural Network (ANN), and Polynomial Regression (PR) are compared. These algorithms vary in complexity and their ability to manage uncertainty around predicted estimates. Results show that the new metrics rank these algorithms in different manner and depending on the requirements and constraints suitable metrics may be chosen. Beyond these results, these metrics offer ideas about how metrics suitable to prognostics may be designed so that the evaluation procedure can be standardized. 1
Improvement of algorithms for digital real-time n-γ discrimination
NASA Astrophysics Data System (ADS)
Wang, Song; Xu, Peng; Lu, Chang-Bing; Huo, Yong-Gang; Zhang, Jun-Jie
2016-02-01
Three algorithms (the Charge Comparison Method, n-γ Model Analysis and the Centroid Algorithm) have been revised to improve their accuracy and broaden the scope of applications to real-time digital n-γ discrimination. To evaluate the feasibility of the revised algorithms, a comparison between the improved and original versions of each is presented. To select an optimal real-time discrimination algorithm from these six algorithms (improved and original), the figure-of-merit (FOM), Peak-Threshold Ratio (PTR), Error Probability (EP) and Simulation Time (ST) for each were calculated to obtain a quantitatively comprehensive assessment of their performance. The results demonstrate that the improved algorithms have a higher accuracy, with an average improvement of 10% in FOM, 95% in PTR and 25% in EP, but all the STs are increased. Finally, the Adjustable Centroid Algorithm (ACA) is selected as the optimal algorithm for real-time digital n-γ discrimination.
High-speed scanning: an improved algorithm
NASA Astrophysics Data System (ADS)
Nachimuthu, A.; Hoang, Khoi
1995-10-01
In using machine vision for assessing an object's surface quality, many images are required to be processed in order to separate the good areas from the defective ones. Examples can be found in the leather hide grading process; in the inspection of garments/canvas on the production line; in the nesting of irregular shapes into a given surface... . The most common method of subtracting the total area from the sum of defective areas does not give an acceptable indication of how much of the `good' area can be used, particularly if the findings are to be used for the nesting of irregular shapes. This paper presents an image scanning technique which enables the estimation of useable areas within an inspected surface in terms of the user's definition, not the supplier's claims. That is, how much useable area the user can use, not the total good area as the supplier estimated. An important application of the developed technique is in the leather industry where the tanner (the supplier) and the footwear manufacturer (the user) are constantly locked in argument due to disputed quality standards of finished leather hide, which disrupts production schedules and wasted costs in re-grading, re- sorting... . The developed basic algorithm for area scanning of a digital image will be presented. The implementation of an improved scanning algorithm will be discussed in detail. The improved features include Boolean OR operations and many other innovative functions which aim at optimizing the scanning process in terms of computing time and the accurate estimation of useable areas.
Chan, J.C.-W.; Huang, C.; DeFries, R.
2001-01-01
Two ensemble methods, bagging and boosting, were investigated for improving algorithm performance. Our results confirmed the theoretical explanation [1] that bagging improves unstable, but not stable, learning algorithms. While boosting enhanced accuracy of a weak learner, its behavior is subject to the characteristics of each learning algorithm.
Improvements to the stand and hit algorithm
Boneh, A.; Boneh, S.; Caron, R.; Jibrin, S.
1994-12-31
The stand and hit algorithm is a probabilistic algorithm for detecting necessary constraints. The algorithm stands at a point in the feasible region and hits constraints by moving towards the boundary along randomly generated directions. In this talk we discuss methods for choosing the standing point. As well, we present the undetected first rule for determining the hit constraints.
Performance Improvement Assuming Complexity
ERIC Educational Resources Information Center
Rowland, Gordon
2007-01-01
Individual performers, work teams, and organizations may be considered complex adaptive systems, while most current human performance technologies appear to assume simple determinism. This article explores the apparent mismatch and speculates on future efforts to enhance performance if complexity rather than simplicity is assumed. Included are…
Improved Bat Algorithm Applied to Multilevel Image Thresholding
2014-01-01
Multilevel image thresholding is a very important image processing technique that is used as a basis for image segmentation and further higher level processing. However, the required computational time for exhaustive search grows exponentially with the number of desired thresholds. Swarm intelligence metaheuristics are well known as successful and efficient optimization methods for intractable problems. In this paper, we adjusted one of the latest swarm intelligence algorithms, the bat algorithm, for the multilevel image thresholding problem. The results of testing on standard benchmark images show that the bat algorithm is comparable with other state-of-the-art algorithms. We improved standard bat algorithm, where our modifications add some elements from the differential evolution and from the artificial bee colony algorithm. Our new proposed improved bat algorithm proved to be better than five other state-of-the-art algorithms, improving quality of results in all cases and significantly improving convergence speed. PMID:25165733
Improved bat algorithm applied to multilevel image thresholding.
Alihodzic, Adis; Tuba, Milan
2014-01-01
Multilevel image thresholding is a very important image processing technique that is used as a basis for image segmentation and further higher level processing. However, the required computational time for exhaustive search grows exponentially with the number of desired thresholds. Swarm intelligence metaheuristics are well known as successful and efficient optimization methods for intractable problems. In this paper, we adjusted one of the latest swarm intelligence algorithms, the bat algorithm, for the multilevel image thresholding problem. The results of testing on standard benchmark images show that the bat algorithm is comparable with other state-of-the-art algorithms. We improved standard bat algorithm, where our modifications add some elements from the differential evolution and from the artificial bee colony algorithm. Our new proposed improved bat algorithm proved to be better than five other state-of-the-art algorithms, improving quality of results in all cases and significantly improving convergence speed. PMID:25165733
A clustering routing algorithm based on improved ant colony clustering for wireless sensor networks
NASA Astrophysics Data System (ADS)
Xiao, Xiaoli; Li, Yang
Because of real wireless sensor network node distribution uniformity, this paper presents a clustering strategy based on the ant colony clustering algorithm (ACC-C). To reduce the energy consumption of the head near the base station and the whole network, The algorithm uses ant colony clustering on non-uniform clustering. The improve route optimal degree is presented to evaluate the performance of the chosen route. Simulation results show that, compared with other algorithms, like the LEACH algorithm and the improve particle cluster kind of clustering algorithm (PSC - C), the proposed approach is able to keep away from the node with less residual energy, which can improve the life of networks.
Performance Improvement [in HRD].
ERIC Educational Resources Information Center
1995
These four papers are from a symposium that was facilitated by Richard J. Torraco at the 1995 conference of the Academy of Human Resource Development (HRD). "Performance Technology--Isn't It Time We Found Some New Models?" (William J. Rothwell) reviews briefly two classic models, describes criteria for the high performance workplace (HPW), and…
An improved distance matrix computation algorithm for multicore clusters.
Al-Neama, Mohammed W; Reda, Naglaa M; Ghaleb, Fayed F M
2014-01-01
Distance matrix has diverse usage in different research areas. Its computation is typically an essential task in most bioinformatics applications, especially in multiple sequence alignment. The gigantic explosion of biological sequence databases leads to an urgent need for accelerating these computations. DistVect algorithm was introduced in the paper of Al-Neama et al. (in press) to present a recent approach for vectorizing distance matrix computing. It showed an efficient performance in both sequential and parallel computing. However, the multicore cluster systems, which are available now, with their scalability and performance/cost ratio, meet the need for more powerful and efficient performance. This paper proposes DistVect1 as highly efficient parallel vectorized algorithm with high performance for computing distance matrix, addressed to multicore clusters. It reformulates DistVect1 vectorized algorithm in terms of clusters primitives. It deduces an efficient approach of partitioning and scheduling computations, convenient to this type of architecture. Implementations employ potential of both MPI and OpenMP libraries. Experimental results show that the proposed method performs improvement of around 3-fold speedup upon SSE2. Further it also achieves speedups more than 9 orders of magnitude compared to the publicly available parallel implementation utilized in ClustalW-MPI. PMID:25013779
Improving GPU-accelerated adaptive IDW interpolation algorithm using fast kNN search.
Mei, Gang; Xu, Nengxiong; Xu, Liangliang
2016-01-01
This paper presents an efficient parallel Adaptive Inverse Distance Weighting (AIDW) interpolation algorithm on modern Graphics Processing Unit (GPU). The presented algorithm is an improvement of our previous GPU-accelerated AIDW algorithm by adopting fast k-nearest neighbors (kNN) search. In AIDW, it needs to find several nearest neighboring data points for each interpolated point to adaptively determine the power parameter; and then the desired prediction value of the interpolated point is obtained by weighted interpolating using the power parameter. In this work, we develop a fast kNN search approach based on the space-partitioning data structure, even grid, to improve the previous GPU-accelerated AIDW algorithm. The improved algorithm is composed of the stages of kNN search and weighted interpolating. To evaluate the performance of the improved algorithm, we perform five groups of experimental tests. The experimental results indicate: (1) the improved algorithm can achieve a speedup of up to 1017 over the corresponding serial algorithm; (2) the improved algorithm is at least two times faster than our previous GPU-accelerated AIDW algorithm; and (3) the utilization of fast kNN search can significantly improve the computational efficiency of the entire GPU-accelerated AIDW algorithm. PMID:27610308
Improved restoration algorithm for weakly blurred and strongly noisy image
NASA Astrophysics Data System (ADS)
Liu, Qianshun; Xia, Guo; Zhou, Haiyang; Bai, Jian; Yu, Feihong
2015-10-01
In real applications, such as consumer digital imaging, it is very common to record weakly blurred and strongly noisy images. Recently, a state-of-art algorithm named geometric locally adaptive sharpening (GLAS) has been proposed. By capturing local image structure, it can effectively combine denoising and sharpening together. However, there still exist two problems in the practice. On one hand, two hard thresholds have to be constantly adjusted with different images so as not to produce over-sharpening artifacts. On the other hand, the smoothing parameter must be manually set precisely. Otherwise, it will seriously magnify the noise. However, these parameters have to be set in advance and totally empirically. In a practical application, this is difficult to achieve. Thus, it is not easy to use and not smart enough. In an effort to improve the restoration effect of this situation by way of GLAS, an improved GLAS (IGLAS) algorithm by introducing the local phase coherence sharpening Index (LPCSI) metric is proposed in this paper. With the help of LPCSI metric, the two hard thresholds can be fixed at constant values for all images. Compared to the original method, the thresholds in our new algorithm no longer need to change with different images. Based on our proposed IGLAS, its automatic version is also developed in order to compensate for the disadvantages of manual intervention. Simulated and real experimental results show that the proposed algorithm can not only obtain better performances compared with the original method, but it is very easy to apply.
An improved algorithm for geocentric to geodetic coordinate conversion
Toms, R.
1996-02-01
The problem of performing transformations from geocentric to geodetic coordinates has received an inordinate amount of attention in the literature. Numerous approximate methods have been published. Almost none of the publications address the issue of efficiency and in most cases there is a paucity of error analysis. Recently there has been a surge of interest in this problem aimed at developing more efficient methods for real time applications such as DIS. Iterative algorithms have been proposed that are not of optimal efficiency, address only one error component and require a small but uncertain number of relatively expensive iterations for convergence. In a recent paper published by the author a new algorithm was proposed for the transformation of geocentric to geodetic coordinates. The new algorithm was tested at the Visual Systems Laboratory at the Institute for Simulation and Training, the University of Central Florida, and found to be 30 percent faster than the best previously published algorithm. In this paper further improvements are made in terms of efficiency. For completeness and to make this paper more readable, it was decided to revise the previous paper and to publish it as a new report. The introduction describes the improvements in more detail.
Modeling and performance analysis of GPS vector tracking algorithms
NASA Astrophysics Data System (ADS)
Lashley, Matthew
This dissertation provides a detailed analysis of GPS vector tracking algorithms and the advantages they have over traditional receiver architectures. Standard GPS receivers use a decentralized architecture that separates the tasks of signal tracking and position/velocity estimation. Vector tracking algorithms combine the two tasks into a single algorithm. The signals from the various satellites are processed collectively through a Kalman filter. The advantages of vector tracking over traditional, scalar tracking methods are thoroughly investigated. A method for making a valid comparison between vector and scalar tracking loops is developed. This technique avoids the ambiguities encountered when attempting to make a valid comparison between tracking loops (which are characterized by noise bandwidths and loop order) and the Kalman filters (which are characterized by process and measurement noise covariance matrices) that are used by vector tracking algorithms. The improvement in performance offered by vector tracking is calculated in multiple different scenarios. Rule of thumb analysis techniques for scalar Frequency Lock Loops (FLL) are extended to the vector tracking case. The analysis tools provide a simple method for analyzing the performance of vector tracking loops. The analysis tools are verified using Monte Carlo simulations. Monte Carlo simulations are also used to study the effects of carrier to noise power density (C/N0) ratio estimation and the advantage offered by vector tracking over scalar tracking. The improvement from vector tracking ranges from 2.4 to 6.2 dB in various scenarios. The difference in the performance of the three vector tracking architectures is analyzed. The effects of using a federated architecture with and without information sharing between the receiver's channels are studied. A combination of covariance analysis and Monte Carlo simulation is used to analyze the performance of the three algorithms. The federated algorithm without
Improved hybrid optimization algorithm for 3D protein structure prediction.
Zhou, Changjun; Hou, Caixia; Wei, Xiaopeng; Zhang, Qiang
2014-07-01
A new improved hybrid optimization algorithm - PGATS algorithm, which is based on toy off-lattice model, is presented for dealing with three-dimensional protein structure prediction problems. The algorithm combines the particle swarm optimization (PSO), genetic algorithm (GA), and tabu search (TS) algorithms. Otherwise, we also take some different improved strategies. The factor of stochastic disturbance is joined in the particle swarm optimization to improve the search ability; the operations of crossover and mutation that are in the genetic algorithm are changed to a kind of random liner method; at last tabu search algorithm is improved by appending a mutation operator. Through the combination of a variety of strategies and algorithms, the protein structure prediction (PSP) in a 3D off-lattice model is achieved. The PSP problem is an NP-hard problem, but the problem can be attributed to a global optimization problem of multi-extremum and multi-parameters. This is the theoretical principle of the hybrid optimization algorithm that is proposed in this paper. The algorithm combines local search and global search, which overcomes the shortcoming of a single algorithm, giving full play to the advantage of each algorithm. In the current universal standard sequences, Fibonacci sequences and real protein sequences are certified. Experiments show that the proposed new method outperforms single algorithms on the accuracy of calculating the protein sequence energy value, which is proved to be an effective way to predict the structure of proteins. PMID:25069136
Helping Others Improve Performance
ERIC Educational Resources Information Center
Durfee, Arthur E.
1970-01-01
Because individuals are motivated by work which they regard as challenging and worthwhile, their motivation is increased as they are given clear-cut responsibility. A performance appraisal system based on these new insights is available and may be used by supervisors. (NL)
A multistrategy optimization improved artificial bee colony algorithm.
Liu, Wen
2014-01-01
Being prone to the shortcomings of premature and slow convergence rate of artificial bee colony algorithm, an improved algorithm was proposed. Chaotic reverse learning strategies were used to initialize swarm in order to improve the global search ability of the algorithm and keep the diversity of the algorithm; the similarity degree of individuals of the population was used to characterize the diversity of population; population diversity measure was set as an indicator to dynamically and adaptively adjust the nectar position; the premature and local convergence were avoided effectively; dual population search mechanism was introduced to the search stage of algorithm; the parallel search of dual population considerably improved the convergence rate. Through simulation experiments of 10 standard testing functions and compared with other algorithms, the results showed that the improved algorithm had faster convergence rate and the capacity of jumping out of local optimum faster. PMID:24982924
RSA cipher algorithm improvements and VC programming realization
NASA Astrophysics Data System (ADS)
Wei, Xianmin
2011-10-01
This paper discusses the RSA algorithm basic mathematical principle, on the basis to propose a faster design improvement. Programming with Visual C proved that the operation speed of improved RSA algorithm is greatly faster than the speed without improvement. However, the security of anti-crack ability has not been adversely affected.
Performance improvement on the battlefield.
De Jong, Marla J; Martin, Kathleen D; Huddleston, Michele; Spott, Mary Ann; McCoy, Jennifer; Black, Julie A; Bolenbaucher, Rose
2008-01-01
The Joint Theater Trauma System (JTTS) is a formal system of trauma care designed to improve the medical care and outcomes for combat casualties of Operation Iraqi Freedom and Operation Enduring Freedom. This article describes the JTTS Trauma Performance Improvement Plan and how JTTS personnel use it to facilitate performance improvement across the entire continuum of combat casualty care. PMID:19092506
Image segmentation using an improved differential algorithm
NASA Astrophysics Data System (ADS)
Gao, Hao; Shi, Yujiao; Wu, Dongmei
2014-10-01
Among all the existing segmentation techniques, the thresholding technique is one of the most popular due to its simplicity, robustness, and accuracy (e.g. the maximum entropy method, Otsu's method, and K-means clustering). However, the computation time of these algorithms grows exponentially with the number of thresholds due to their exhaustive searching strategy. As a population-based optimization algorithm, differential algorithm (DE) uses a population of potential solutions and decision-making processes. It has shown considerable success in solving complex optimization problems within a reasonable time limit. Thus, applying this method into segmentation algorithm should be a good choice during to its fast computational ability. In this paper, we first propose a new differential algorithm with a balance strategy, which seeks a balance between the exploration of new regions and the exploitation of the already sampled regions. Then, we apply the new DE into the traditional Otsu's method to shorten the computation time. Experimental results of the new algorithm on a variety of images show that, compared with the EA-based thresholding methods, the proposed DE algorithm gets more effective and efficient results. It also shortens the computation time of the traditional Otsu method.
Improved Algorithm For Finite-Field Normal-Basis Multipliers
NASA Technical Reports Server (NTRS)
Wang, C. C.
1989-01-01
Improved algorithm reduces complexity of calculations that must precede design of Massey-Omura finite-field normal-basis multipliers, used in error-correcting-code equipment and cryptographic devices. Algorithm represents an extension of development reported in "Algorithm To Design Finite-Field Normal-Basis Multipliers" (NPO-17109), NASA Tech Briefs, Vol. 12, No. 5, page 82.
Improving permafrost distribution modelling using feature selection algorithms
NASA Astrophysics Data System (ADS)
Deluigi, Nicola; Lambiel, Christophe; Kanevski, Mikhail
2016-04-01
The availability of an increasing number of spatial data on the occurrence of mountain permafrost allows the employment of machine learning (ML) classification algorithms for modelling the distribution of the phenomenon. One of the major problems when dealing with high-dimensional dataset is the number of input features (variables) involved. Application of ML classification algorithms to this large number of variables leads to the risk of overfitting, with the consequence of a poor generalization/prediction. For this reason, applying feature selection (FS) techniques helps simplifying the amount of factors required and improves the knowledge on adopted features and their relation with the studied phenomenon. Moreover, taking away irrelevant or redundant variables from the dataset effectively improves the quality of the ML prediction. This research deals with a comparative analysis of permafrost distribution models supported by FS variable importance assessment. The input dataset (dimension = 20-25, 10 m spatial resolution) was constructed using landcover maps, climate data and DEM derived variables (altitude, aspect, slope, terrain curvature, solar radiation, etc.). It was completed with permafrost evidences (geophysical and thermal data and rock glacier inventories) that serve as training permafrost data. Used FS algorithms informed about variables that appeared less statistically important for permafrost presence/absence. Three different algorithms were compared: Information Gain (IG), Correlation-based Feature Selection (CFS) and Random Forest (RF). IG is a filter technique that evaluates the worth of a predictor by measuring the information gain with respect to the permafrost presence/absence. Conversely, CFS is a wrapper technique that evaluates the worth of a subset of predictors by considering the individual predictive ability of each variable along with the degree of redundancy between them. Finally, RF is a ML algorithm that performs FS as part of its
An improved SIFT algorithm based on KFDA in image registration
NASA Astrophysics Data System (ADS)
Chen, Peng; Yang, Lijuan; Huo, Jinfeng
2016-03-01
As a kind of stable feature matching algorithm, SIFT has been widely used in many fields. In order to further improve the robustness of the SIFT algorithm, an improved SIFT algorithm with Kernel Discriminant Analysis (KFDA-SIFT) is presented for image registration. The algorithm uses KFDA to SIFT descriptors for feature extraction matrix, and uses the new descriptors to conduct the feature matching, finally chooses RANSAC to deal with the matches for further purification. The experiments show that the presented algorithm is robust to image changes in scale, illumination, perspective, expression and tiny pose with higher matching accuracy.
Improved branch-cut method algorithm applied in phase unwrapping
NASA Astrophysics Data System (ADS)
Hu, Jiayuan; Zhang, Yu; Wu, Jianle; Li, Jinlong; Wang, Haiqing
2015-12-01
Phase unwrapping is a common problem in many phase measuring techniques. Glodstein's branch-cut algorithm is one of classic ways of phase unwrapping, but it need rectifying. First the paper introduces the characteristics of residual points and describes Glodstein's branch-cut algorithm in detail. Then the paper discusses the improvements on the algorithm by changing branch setting and adding pretreatment. Last the paper summarizes the new algorithm and gets the better result by using computer emulation mode and validation test.
Missile placement analysis based on improved SURF feature matching algorithm
NASA Astrophysics Data System (ADS)
Yang, Kaida; Zhao, Wenjie; Li, Dejun; Gong, Xiran; Sheng, Qian
2015-03-01
The precious battle damage assessment by use of video images to analysis missile placement is a new study area. The article proposed an improved speeded up robust features algorithm named restricted speeded up robust features, which combined the combat application of TV-command-guided missiles and the characteristics of video image. Its restrictions mainly reflected in two aspects, one is to restrict extraction area of feature point; the second is to restrict the number of feature points. The process of missile placement analysis based on video image was designed and a video splicing process and random sample consensus purification were achieved. The RSURF algorithm is proved that has good realtime performance on the basis of guarantee the accuracy.
Two Improved Algorithms for Envelope and Wavefront Reduction
NASA Technical Reports Server (NTRS)
Kumfert, Gary; Pothen, Alex
1997-01-01
Two algorithms for reordering sparse, symmetric matrices or undirected graphs to reduce envelope and wavefront are considered. The first is a combinatorial algorithm introduced by Sloan and further developed by Duff, Reid, and Scott; we describe enhancements to the Sloan algorithm that improve its quality and reduce its run time. Our test problems fall into two classes with differing asymptotic behavior of their envelope parameters as a function of the weights in the Sloan algorithm. We describe an efficient 0(nlogn + m) time implementation of the Sloan algorithm, where n is the number of rows (vertices), and m is the number of nonzeros (edges). On a collection of test problems, the improved Sloan algorithm required, on the average, only twice the time required by the simpler Reverse Cuthill-Mckee algorithm while improving the mean square wavefront by a factor of three. The second algorithm is a hybrid that combines a spectral algorithm for envelope and wavefront reduction with a refinement step that uses a modified Sloan algorithm. The hybrid algorithm reduces the envelope size and mean square wavefront obtained from the Sloan algorithm at the cost of greater running times. We illustrate how these reductions translate into tangible benefits for frontal Cholesky factorization and incomplete factorization preconditioning.
Improving performance via mini-applications.
Crozier, Paul Stewart; Thornquist, Heidi K.; Numrich, Robert W.; Williams, Alan B.; Edwards, Harold Carter; Keiter, Eric Richard; Rajan, Mahesh; Willenbring, James M.; Doerfler, Douglas W.; Heroux, Michael Allen
2009-09-01
Application performance is determined by a combination of many choices: hardware platform, runtime environment, languages and compilers used, algorithm choice and implementation, and more. In this complicated environment, we find that the use of mini-applications - small self-contained proxies for real applications - is an excellent approach for rapidly exploring the parameter space of all these choices. Furthermore, use of mini-applications enriches the interaction between application, library and computer system developers by providing explicit functioning software and concrete performance results that lead to detailed, focused discussions of design trade-offs, algorithm choices and runtime performance issues. In this paper we discuss a collection of mini-applications and demonstrate how we use them to analyze and improve application performance on new and future computer platforms.
Vasan, S N Swetadri; Ionita, Ciprian N; Titus, A H; Cartwright, A N; Bednarek, D R; Rudin, S
2012-02-23
We present the image processing upgrades implemented on a Graphics Processing Unit (GPU) in the Control, Acquisition, Processing, and Image Display System (CAPIDS) for the custom Micro-Angiographic Fluoroscope (MAF) detector. Most of the image processing currently implemented in the CAPIDS system is pixel independent; that is, the operation on each pixel is the same and the operation on one does not depend upon the result from the operation on the other, allowing the entire image to be processed in parallel. GPU hardware was developed for this kind of massive parallel processing implementation. Thus for an algorithm which has a high amount of parallelism, a GPU implementation is much faster than a CPU implementation. The image processing algorithm upgrades implemented on the CAPIDS system include flat field correction, temporal filtering, image subtraction, roadmap mask generation and display window and leveling. A comparison between the previous and the upgraded version of CAPIDS has been presented, to demonstrate how the improvement is achieved. By performing the image processing on a GPU, significant improvements (with respect to timing or frame rate) have been achieved, including stable operation of the system at 30 fps during a fluoroscopy run, a DSA run, a roadmap procedure and automatic image windowing and leveling during each frame. PMID:24027619
NASA Astrophysics Data System (ADS)
Swetadri Vasan, S. N.; Ionita, Ciprian N.; Titus, A. H.; Cartwright, A. N.; Bednarek, D. R.; Rudin, S.
2012-03-01
We present the image processing upgrades implemented on a Graphics Processing Unit (GPU) in the Control, Acquisition, Processing, and Image Display System (CAPIDS) for the custom Micro-Angiographic Fluoroscope (MAF) detector. Most of the image processing currently implemented in the CAPIDS system is pixel independent; that is, the operation on each pixel is the same and the operation on one does not depend upon the result from the operation on the other, allowing the entire image to be processed in parallel. GPU hardware was developed for this kind of massive parallel processing implementation. Thus for an algorithm which has a high amount of parallelism, a GPU implementation is much faster than a CPU implementation. The image processing algorithm upgrades implemented on the CAPIDS system include flat field correction, temporal filtering, image subtraction, roadmap mask generation and display window and leveling. A comparison between the previous and the upgraded version of CAPIDS has been presented, to demonstrate how the improvement is achieved. By performing the image processing on a GPU, significant improvements (with respect to timing or frame rate) have been achieved, including stable operation of the system at 30 fps during a fluoroscopy run, a DSA run, a roadmap procedure and automatic image windowing and leveling during each frame.
Vasan, S.N. Swetadri; Ionita, Ciprian N.; Titus, A.H.; Cartwright, A.N.; Bednarek, D.R.; Rudin, S.
2012-01-01
We present the image processing upgrades implemented on a Graphics Processing Unit (GPU) in the Control, Acquisition, Processing, and Image Display System (CAPIDS) for the custom Micro-Angiographic Fluoroscope (MAF) detector. Most of the image processing currently implemented in the CAPIDS system is pixel independent; that is, the operation on each pixel is the same and the operation on one does not depend upon the result from the operation on the other, allowing the entire image to be processed in parallel. GPU hardware was developed for this kind of massive parallel processing implementation. Thus for an algorithm which has a high amount of parallelism, a GPU implementation is much faster than a CPU implementation. The image processing algorithm upgrades implemented on the CAPIDS system include flat field correction, temporal filtering, image subtraction, roadmap mask generation and display window and leveling. A comparison between the previous and the upgraded version of CAPIDS has been presented, to demonstrate how the improvement is achieved. By performing the image processing on a GPU, significant improvements (with respect to timing or frame rate) have been achieved, including stable operation of the system at 30 fps during a fluoroscopy run, a DSA run, a roadmap procedure and automatic image windowing and leveling during each frame. PMID:24027619
Learning to improve path planning performance
Chen, Pang C.
1995-04-01
In robotics, path planning refers to finding a short. collision-free path from an initial robot configuration to a desired configuratioin. It has to be fast to support real-time task-level robot programming. Unfortunately, current planning techniques are still too slow to be effective, as they often require several minutes, if not hours of computation. To remedy this situation, we present and analyze a learning algorithm that uses past experience to increase future performance. The algorithm relies on an existing path planner to provide solutions to difficult tasks. From these solutions, an evolving sparse network of useful robot configurations is learned to support faster planning. More generally, the algorithm provides a speedup-learning framework in which a slow but capable planner may be improved both cost-wise and capability-wise by a faster but less capable planner coupled with experience. The basic algorithm is suitable for stationary environments, and can be extended to accommodate changing environments with on-demand experience repair and object-attached experience abstraction. To analyze the algorithm, we characterize the situations in which the adaptive planner is useful, provide quantitative bounds to predict its behavior, and confirm our theoretical results with experiments in path planning of manipulators. Our algorithm and analysis are sufficiently, general that they may also be applied to other planning domains in which experience is useful.
An improved algorithm for pedestrian detection
NASA Astrophysics Data System (ADS)
Yousef, Amr; Duraisamy, Prakash; Karim, Mohammad
2015-03-01
In this paper we present a technique to detect pedestrian. Histogram of gradients (HOG) and Haar wavelets with the aid of support vector machines (SVM) and AdaBoost classifiers show good identification performance on different objects classification including pedestrians. We propose a new shape descriptor derived from the intra-relationship between gradient orientations in a way similar to the HOG. The proposed descriptor is a two 2-D grid of orientation similarities measured at different offsets. The gradient magnitudes and phases derived from a sliding window with different scales and sizes are used to construct two 2-D symmetric grids. The first grid measures the co-occurence of the phases while the other one measures the corresponding percentage of gradient magnitudes for the measured orientation similarity. Since the resultant matrices will be symmetric, the feature vector is formed by concatenating the upper diagonal grid coefficients collected in a raster way. Classification is done using SVM classifier with radial basis kernel. Experimental results show improved performance compared to the current state-of-art techniques.
Community detection based on modularity and an improved genetic algorithm
NASA Astrophysics Data System (ADS)
Shang, Ronghua; Bai, Jing; Jiao, Licheng; Jin, Chao
2013-03-01
Complex networks are widely applied in every aspect of human society, and community detection is a research hotspot in complex networks. Many algorithms use modularity as the objective function, which can simplify the algorithm. In this paper, a community detection method based on modularity and an improved genetic algorithm (MIGA) is put forward. MIGA takes the modularity Q as the objective function, which can simplify the algorithm, and uses prior information (the number of community structures), which makes the algorithm more targeted and improves the stability and accuracy of community detection. Meanwhile, MIGA takes the simulated annealing method as the local search method, which can improve the ability of local search by adjusting the parameters. Compared with the state-of-art algorithms, simulation results on computer-generated and four real-world networks reflect the effectiveness of MIGA.
An improved NAS-RIF algorithm for blind image restoration
NASA Astrophysics Data System (ADS)
Liu, Ning; Jiang, Yanbin; Lou, Shuntian
2007-01-01
Image restoration is widely applied in many areas, but when operating on images with different scales for the representation of pixel intensity levels or low SNR, the traditional restoration algorithm lacks validity and induces noise amplification, ringing artifacts and poor convergent ability. In this paper, an improved NAS-RIF algorithm is proposed to overcome the shortcomings of the traditional algorithm. The improved algorithm proposes a new cost function which adds a space-adaptive regularization term and a disunity gain of the adaptive filter. In determining the support region, a pre-segmentation is used to form it close to the object in the image. Compared with the traditional algorithm, simulations show that the improved algorithm behaves better convergence, noise resistance and provides a better estimate of original image.
Kuszewski, John J; Thottungal, Robin Augustine; Clore, G Marius; Schwieters, Charles D
2008-08-01
We report substantial improvements to the previously introduced automated NOE assignment and structure determination protocol known as PASD (Kuszewski et al. (2004) J Am Chem Soc 26:6258-6273). The improved protocol includes extensive analysis of input spectral data to create a low-resolution contact map of residues expected to be close in space. This map is used to obtain reasonable initial guesses of NOE assignment likelihoods which are refined during subsequent structure calculations. Information in the contact map about which residues are predicted to not be close in space is applied via conservative repulsive distance restraints which are used in early phases of the structure calculations. In comparison with the previous protocol, the new protocol requires significantly less computation time. We show results of running the new PASD protocol on six proteins and demonstrate that useful assignment and structural information is extracted on proteins of more than 220 residues. We show that useful assignment information can be obtained even in the case in which a unique structure cannot be determined. PMID:18668206
Che, Yanting; Wang, Qiuying; Gao, Wei; Yu, Fei
2015-01-01
In this paper, an improved inertial frame alignment algorithm for a marine SINS under mooring conditions is proposed, which significantly improves accuracy. Since the horizontal alignment is easy to complete, and a characteristic of gravity is that its component in the horizontal plane is zero, we use a clever method to improve the conventional inertial alignment algorithm. Firstly, a large misalignment angle model and a dimensionality reduction Gauss-Hermite filter are employed to establish the fine horizontal reference frame. Based on this, the projection of the gravity in the body inertial coordinate frame can be calculated easily. Then, the initial alignment algorithm is accomplished through an inertial frame alignment algorithm. The simulation and experiment results show that the improved initial alignment algorithm performs better than the conventional inertial alignment algorithm, and meets the accuracy requirements of a medium-accuracy marine SINS. PMID:26445048
Che, Yanting; Wang, Qiuying; Gao, Wei; Yu, Fei
2015-01-01
In this paper, an improved inertial frame alignment algorithm for a marine SINS under mooring conditions is proposed, which significantly improves accuracy. Since the horizontal alignment is easy to complete, and a characteristic of gravity is that its component in the horizontal plane is zero, we use a clever method to improve the conventional inertial alignment algorithm. Firstly, a large misalignment angle model and a dimensionality reduction Gauss-Hermite filter are employed to establish the fine horizontal reference frame. Based on this, the projection of the gravity in the body inertial coordinate frame can be calculated easily. Then, the initial alignment algorithm is accomplished through an inertial frame alignment algorithm. The simulation and experiment results show that the improved initial alignment algorithm performs better than the conventional inertial alignment algorithm, and meets the accuracy requirements of a medium-accuracy marine SINS. PMID:26445048
Performance Comparison Of Evolutionary Algorithms For Image Clustering
NASA Astrophysics Data System (ADS)
Civicioglu, P.; Atasever, U. H.; Ozkan, C.; Besdok, E.; Karkinli, A. E.; Kesikoglu, A.
2014-09-01
Evolutionary computation tools are able to process real valued numerical sets in order to extract suboptimal solution of designed problem. Data clustering algorithms have been intensively used for image segmentation in remote sensing applications. Despite of wide usage of evolutionary algorithms on data clustering, their clustering performances have been scarcely studied by using clustering validation indexes. In this paper, the recently proposed evolutionary algorithms (i.e., Artificial Bee Colony Algorithm (ABC), Gravitational Search Algorithm (GSA), Cuckoo Search Algorithm (CS), Adaptive Differential Evolution Algorithm (JADE), Differential Search Algorithm (DSA) and Backtracking Search Optimization Algorithm (BSA)) and some classical image clustering techniques (i.e., k-means, fcm, som networks) have been used to cluster images and their performances have been compared by using four clustering validation indexes. Experimental test results exposed that evolutionary algorithms give more reliable cluster-centers than classical clustering techniques, but their convergence time is quite long.
Improved Inversion Algorithms for Near Surface Characterization
NASA Astrophysics Data System (ADS)
Astaneh, Ali Vaziri; Guddati, Murthy N.
2016-05-01
Near-surface geophysical imaging is often performed by generating surface waves, and estimating the subsurface properties through inversion, i.e. iteratively matching experimentally observed dispersion curves with predicted curves from a layered half-space model of the subsurface. Key to the effectiveness of inversion is the efficiency and accuracy of computing the dispersion curves and their derivatives. This paper presents improved methodologies for both dispersion curve and derivative computation. First, it is shown that the dispersion curves can be computed more efficiently by combining an unconventional complex-length finite element method (CFEM) to model the finite depth layers, with perfectly matched discrete layers (PMDL) to model the unbounded half-space. Second, based on analytical derivatives for theoretical dispersion curves, an approximate derivative is derived for so-called effective dispersion curve for realistic geophysical surface response data. The new derivative computation has a smoothing effect on the computation of derivatives, in comparison with traditional finite difference (FD) approach, and results in faster convergence. In addition, while the computational cost of FD differentiation is proportional to the number of model parameters, the new differentiation formula has a computational cost that is almost independent of the number of model parameters. At the end, as confirmed by synthetic and real-life imaging examples, the combination of CFEM+PMDL for dispersion calculation and the new differentiation formula results in more accurate estimates of the subsurface characteristics than the traditional methods, at a small fraction of computational effort.
Improving CMD Areal Density Analysis: Algorithms and Strategies
NASA Astrophysics Data System (ADS)
Wilson, R. E.
2014-06-01
Essential ideas, successes, and difficulties of Areal Density Analysis (ADA) for color-magnitude diagrams (CMDÂ¡Â¯s) of resolved stellar populations are examined, with explanation of various algorithms and strategies for optimal performance. A CMDgeneration program computes theoretical datasets with simulated observational error and a solution program inverts the problem by the method of Differential Corrections (DC) so as to compute parameter values from observed magnitudes and colors, with standard error estimates and correlation coefficients. ADA promises not only impersonal results, but also significant saving of labor, especially where a given dataset is analyzed with several evolution models. Observational errors and multiple star systems, along with various single star characteristics and phenomena, are modeled directly via the Functional Statistics Algorithm (FSA). Unlike Monte Carlo, FSA is not dependent on a random number generator. Discussions include difficulties and overall requirements, such as need for fast evolutionary computation and realization of goals within machine memory limits. Degradation of results due to influence of pixelization on derivatives, Initial Mass Function (IMF) quantization, IMF steepness, low Areal Densities (A ), and large variation in A are reduced or eliminated through a variety of schemes that are explained sufficiently for general application. The Levenberg-Marquardt and MMS algorithms for improvement of solution convergence are contained within the DC program. An example of convergence, which typically is very good, is shown in tabular form. A number of theoretical and practical solution issues are discussed, as are prospects for further development.
An improved harmony search algorithm for emergency inspection scheduling
NASA Astrophysics Data System (ADS)
Kallioras, Nikos A.; Lagaros, Nikos D.; Karlaftis, Matthew G.
2014-11-01
The ability of nature-inspired search algorithms to efficiently handle combinatorial problems, and their successful implementation in many fields of engineering and applied sciences, have led to the development of new, improved algorithms. In this work, an improved harmony search (IHS) algorithm is presented, while a holistic approach for solving the problem of post-disaster infrastructure management is also proposed. The efficiency of IHS is compared with that of the algorithms of particle swarm optimization, differential evolution, basic harmony search and the pure random search procedure, when solving the districting problem that is the first part of post-disaster infrastructure management. The ant colony optimization algorithm is employed for solving the associated routing problem that constitutes the second part. The comparison is based on the quality of the results obtained, the computational demands and the sensitivity on the algorithmic parameters.
Improved local linearization algorithm for solving the quaternion equations
NASA Technical Reports Server (NTRS)
Yen, K.; Cook, G.
1980-01-01
The objective of this paper is to develop a new and more accurate local linearization algorithm for numerically solving sets of linear time-varying differential equations. Of special interest is the application of this algorithm to the quaternion rate equations. The results are compared, both analytically and experimentally, with previous results using local linearization methods. The new algorithm requires approximately one-third more calculations per step than the previously developed local linearization algorithm; however, this disadvantage could be reduced by using parallel implementation. For some cases the new algorithm yields significant improvement in accuracy, even with an enlarged sampling interval. The reverse is true in other cases. The errors depend on the values of angular velocity, angular acceleration, and integration step size. One important result is that for the worst case the new algorithm can guarantee eigenvalues nearer the region of stability than can the previously developed algorithm.
A new improved artificial bee colony algorithm for ship hull form optimization
NASA Astrophysics Data System (ADS)
Huang, Fuxin; Wang, Lijue; Yang, Chi
2016-04-01
The artificial bee colony (ABC) algorithm is a relatively new swarm intelligence-based optimization algorithm. Its simplicity of implementation, relatively few parameter settings and promising optimization capability make it widely used in different fields. However, it has problems of slow convergence due to its solution search equation. Here, a new solution search equation based on a combination of the elite solution pool and the block perturbation scheme is proposed to improve the performance of the algorithm. In addition, two different solution search equations are used by employed bees and onlooker bees to balance the exploration and exploitation of the algorithm. The developed algorithm is validated by a set of well-known numerical benchmark functions. It is then applied to optimize two ship hull forms with minimum resistance. The tested results show that the proposed new improved ABC algorithm can outperform the ABC algorithm in most of the tested problems.
Celik, Yuksel; Ulker, Erkan
2013-01-01
Marriage in honey bees optimization (MBO) is a metaheuristic optimization algorithm developed by inspiration of the mating and fertilization process of honey bees and is a kind of swarm intelligence optimizations. In this study we propose improved marriage in honey bees optimization (IMBO) by adding Levy flight algorithm for queen mating flight and neighboring for worker drone improving. The IMBO algorithm's performance and its success are tested on the well-known six unconstrained test functions and compared with other metaheuristic optimization algorithms. PMID:23935416
Celik, Yuksel; Ulker, Erkan
2013-01-01
Marriage in honey bees optimization (MBO) is a metaheuristic optimization algorithm developed by inspiration of the mating and fertilization process of honey bees and is a kind of swarm intelligence optimizations. In this study we propose improved marriage in honey bees optimization (IMBO) by adding Levy flight algorithm for queen mating flight and neighboring for worker drone improving. The IMBO algorithm's performance and its success are tested on the well-known six unconstrained test functions and compared with other metaheuristic optimization algorithms. PMID:23935416
Training Feedforward Neural Networks: An Algorithm Giving Improved Generalization.
Lee, Charles W.
1997-01-01
An algorithm is derived for supervised training in multilayer feedforward neural networks. Relative to the gradient descent backpropagation algorithm it appears to give both faster convergence and improved generalization, whilst preserving the system of backpropagating errors through the network. Copyright 1996 Elsevier Science Ltd. PMID:12662887
Improving Reading Performance through Hypnosis.
ERIC Educational Resources Information Center
Fillmer, H. Thompson; And Others
1981-01-01
Describes a study investigating the effects of group hypnosis on the reading performance of university students in a reading and writing center. Discusses study procedures and presents data on pretest scores and gains in vocabulary and comprehension scores. Concludes that regular use of self-hypnosis significantly improved performance. (DMM)
Evaluating and Improving Teacher Performance.
ERIC Educational Resources Information Center
Manatt, Richard P.
This workbook, coordinated with Manatt Teacher Performance Evaluation (TPE) workshops, summarizes large group presentation in sequence with the transparancies used. The first four modules of the workbook deal with the state of the art of evaluating and improving teacher performance; the development of the TPE system, including selection of…
Improving Performance Appraisal in Libraries.
ERIC Educational Resources Information Center
Vincelette, Joyce P.; Pfister, Fred C.
1984-01-01
This article identifies problems with current practice in evaluating employee performance and presents currently accepted performance appraisal methods (behaviorally anchored rating scales, management by objectives). A research project designed to improve appraisals for school media specialists which was field-tested in four Florida school…
Improved Bat algorithm for the detection of myocardial infarction.
Kora, Padmavathi; Kalva, Sri Ramakrishna
2015-01-01
The medical practitioners study the electrical activity of the human heart in order to detect heart diseases from the electrocardiogram (ECG) of the heart patients. A myocardial infarction (MI) or heart attack is a heart disease, that occurs when there is a block (blood clot) in the pathway of one or more coronary blood vessels (arteries) that supply blood to the heart muscle. The abnormalities in the heart can be identified by the changes in the ECG signal. The first step in the detection of MI is Preprocessing of ECGs which removes noise by using filters. Feature extraction is the next key process in detecting the changes in the ECG signals. This paper presents a method for extracting key features from each cardiac beat using Improved Bat algorithm. Using this algorithm best features are extracted, then these best (reduced) features are applied to the input of the neural network classifier. It has been observed that the performance of the classifier is improved with the help of the optimized features. PMID:26558169
An Improved Neutron Transport Algorithm for HZETRN
NASA Technical Reports Server (NTRS)
Slaba, Tony C.; Blattnig, Steve R.; Clowdsley, Martha S.; Walker, Steven A.; Badavi, Francis F.
2010-01-01
Long term human presence in space requires the inclusion of radiation constraints in mission planning and the design of shielding materials, structures, and vehicles. In this paper, the numerical error associated with energy discretization in HZETRN is addressed. An inadequate numerical integration scheme in the transport algorithm is shown to produce large errors in the low energy portion of the neutron and light ion fluence spectra. It is further shown that the errors result from the narrow energy domain of the neutron elastic cross section spectral distributions, and that an extremely fine energy grid is required to resolve the problem under the current formulation. Two numerical methods are developed to provide adequate resolution in the energy domain and more accurately resolve the neutron elastic interactions. Convergence testing is completed by running the code for various environments and shielding materials with various energy grids to ensure stability of the newly implemented method.
Improved 3-D turbomachinery CFD algorithm
NASA Technical Reports Server (NTRS)
Janus, J. Mark; Whitfield, David L.
1988-01-01
The building blocks of a computer algorithm developed for the time-accurate flow analysis of rotating machines are described. The flow model is a finite volume method utilizing a high resolution approximate Riemann solver for interface flux definitions. This block LU implicit numerical scheme possesses apparent unconditional stability. Multi-block composite gridding is used to orderly partition the field into a specified arrangement. Block interfaces, including dynamic interfaces, are treated such as to mimic interior block communication. Special attention is given to the reduction of in-core memory requirements by placing the burden on secondary storage media. Broad applicability is implied, although the results presented are restricted to that of an even blade count configuration. Several other configurations are presently under investigation, the results of which will appear in subsequent publications.
Proper bibeta ROC model: algorithm, software, and performance evaluation
NASA Astrophysics Data System (ADS)
Chen, Weijie; Hu, Nan
2016-03-01
Semi-parametric models are often used to fit data collected in receiver operating characteristic (ROC) experiments to obtain a smooth ROC curve and ROC parameters for statistical inference purposes. The proper bibeta model as recently proposed by Mossman and Peng enjoys several theoretical properties. In addition to having explicit density functions for the latent decision variable and an explicit functional form of the ROC curve, the two parameter bibeta model also has simple closed-form expressions for true-positive fraction (TPF), false-positive fraction (FPF), and the area under the ROC curve (AUC). In this work, we developed a computational algorithm and R package implementing this model for ROC curve fitting. Our algorithm can deal with any ordinal data (categorical or continuous). To improve accuracy, efficiency, and reliability of our software, we adopted several strategies in our computational algorithm including: (1) the LABROC4 categorization to obtain the true maximum likelihood estimation of the ROC parameters; (2) a principled approach to initializing parameters; (3) analytical first-order and second-order derivatives of the likelihood function; (4) an efficient optimization procedure (the L-BFGS algorithm in the R package "nlopt"); and (5) an analytical delta method to estimate the variance of the AUC. We evaluated the performance of our software with intensive simulation studies and compared with the conventional binormal and the proper binormal-likelihood-ratio models developed at the University of Chicago. Our simulation results indicate that our software is highly accurate, efficient, and reliable.
Improved genetic algorithm for fast path planning of USV
NASA Astrophysics Data System (ADS)
Cao, Lu
2015-12-01
Due to the complex constraints, more uncertain factors and critical real-time demand of path planning for USV(Unmanned Surface Vehicle), an approach of fast path planning based on voronoi diagram and improved Genetic Algorithm is proposed, which makes use of the principle of hierarchical path planning. First the voronoi diagram is utilized to generate the initial paths and then the optimal path is searched by using the improved Genetic Algorithm, which use multiprocessors parallel computing techniques to improve the traditional genetic algorithm. Simulation results verify that the optimal time is greatly reduced and path planning based on voronoi diagram and the improved Genetic Algorithm is more favorable in the real-time operation.
NASA Astrophysics Data System (ADS)
Qi, Wei; Zhang, Chi; Fu, Guangtao; Zhou, Huicheng
2016-02-01
It is widely recognized that optimization algorithm parameters have significant impacts on algorithm performance, but quantifying the influence is very complex and difficult due to high computational demands and dynamic nature of search parameters. The overall aim of this paper is to develop a global sensitivity analysis based framework to dynamically quantify the individual and interactive influence of algorithm parameters on algorithm performance. A variance decomposition sensitivity analysis method, Analysis of Variance (ANOVA), is used for sensitivity quantification, because it is capable of handling small samples and more computationally efficient compared with other approaches. The Shuffled Complex Evolution method developed at the University of Arizona algorithm (SCE-UA) is selected as an optimization algorithm for investigation, and two criteria, i.e., convergence speed and success rate, are used to measure the performance of SCE-UA. Results show the proposed framework can effectively reveal the dynamic sensitivity of algorithm parameters in the search processes, including individual influences of parameters and their interactive impacts. Interactions between algorithm parameters have significant impacts on SCE-UA performance, which has not been reported in previous research. The proposed framework provides a means to understand the dynamics of algorithm parameter influence, and highlights the significance of considering interactive parameter influence to improve algorithm performance in the search processes.
Improvement and implementation for Canny edge detection algorithm
NASA Astrophysics Data System (ADS)
Yang, Tao; Qiu, Yue-hong
2015-07-01
Edge detection is necessary for image segmentation and pattern recognition. In this paper, an improved Canny edge detection approach is proposed due to the defect of traditional algorithm. A modified bilateral filter with a compensation function based on pixel intensity similarity judgment was used to smooth image instead of Gaussian filter, which could preserve edge feature and remove noise effectively. In order to solve the problems of sensitivity to the noise in gradient calculating, the algorithm used 4 directions gradient templates. Finally, Otsu algorithm adaptively obtain the dual-threshold. All of the algorithm simulated with OpenCV 2.4.0 library in the environments of vs2010, and through the experimental analysis, the improved algorithm has been proved to detect edge details more effectively and with more adaptability.
Surviving Performance Improvement "Solutions": Aligning Performance Improvement Interventions
ERIC Educational Resources Information Center
Bernardez, Mariano L.
2009-01-01
How can organizations avoid the negative, sometimes chaotic, effects of multiple, poorly coordinated performance improvement interventions? How can we avoid punishing our external clients or staff with the side effects of solutions that might benefit our bottom line or internal efficiency at the expense of the value received or perceived by…
Improved ZigBee Network Routing Algorithm Based on LEACH
NASA Astrophysics Data System (ADS)
Zhao, Yawei; Zhang, Guohua; Xia, Zhongwu; Li, Xinhua
Energy efficiency design of routing protocol is a kind of the key technologies used to wireless sensor networks. The paper introduces the ZigBee technology, summarizes the current transmitting routing model in wireless sensor networks, and finds that the traditional LEACH protocol can lead to overload of some cluster head nodes. The paper suggested that the existing LEACH agreement was improved and the new algorithm was better than traditional LEACH routing algorithm by the comprasion of simulation. The improved routing algorithm can prolong the networks lifetime and effectively save the scarce energy.
A morphological algorithm for improving radio-frequency interference detection
NASA Astrophysics Data System (ADS)
Offringa, A. R.; van de Gronde, J. J.; Roerdink, J. B. T. M.
2012-03-01
A technique is described that is used to improve the detection of radio-frequency interference in astronomical radio observatories. It is applied on a two-dimensional interference mask after regular detection in the time-frequency domain with existing techniques. The scale-invariant rank (SIR) operator is defined, which is a one-dimensional mathematical morphology technique that can be used to find adjacent intervals in the time or frequency domain that are likely to be affected by RFI. The technique might also be applicable in other areas in which morphological scale-invariant behaviour is desired, such as source detection. A new algorithm is described, that is shown to perform quite well, has linear time complexity and is fast enough to be applied in modern high resolution observatories. It is used in the default pipeline of the LOFAR observatory.
An Efficient and Configurable Preprocessing Algorithm to Improve Stability Analysis.
Sesia, Ilaria; Cantoni, Elena; Cernigliaro, Alice; Signorile, Giovanna; Fantino, Gianluca; Tavella, Patrizia
2016-04-01
The Allan variance (AVAR) is widely used to measure the stability of experimental time series. Specifically, AVAR is commonly used in space applications such as monitoring the clocks of the global navigation satellite systems (GNSSs). In these applications, the experimental data present some peculiar aspects which are not generally encountered when the measurements are carried out in a laboratory. Space clocks' data can in fact present outliers, jumps, and missing values, which corrupt the clock characterization. Therefore, an efficient preprocessing is fundamental to ensure a proper data analysis and improve the stability estimation performed with the AVAR or other similar variances. In this work, we propose a preprocessing algorithm and its implementation in a robust software code (in MATLAB language) able to deal with time series of experimental data affected by nonstationarities and missing data; our method is properly detecting and removing anomalous behaviors, hence making the subsequent stability analysis more reliable. PMID:26540679
Improving Learning Performance Through Rational Resource Allocation
NASA Technical Reports Server (NTRS)
Gratch, J.; Chien, S.; DeJong, G.
1994-01-01
This article shows how rational analysis can be used to minimize learning cost for a general class of statistical learning problems. We discuss the factors that influence learning cost and show that the problem of efficient learning can be cast as a resource optimization problem. Solutions found in this way can be significantly more efficient than the best solutions that do not account for these factors. We introduce a heuristic learning algorithm that approximately solves this optimization problem and document its performance improvements on synthetic and real-world problems.
Case study of isosurface extraction algorithm performance
Sutton, P M; Hansen, C D; Shen, H; Schikore, D
1999-12-14
Isosurface extraction is an important and useful visualization method. Over the past ten years, the field has seen numerous isosurface techniques published leaving the user in a quandary about which one should be used. Some papers have published complexity analysis of the techniques yet empirical evidence comparing different methods is lacking. This case study presents a comparative study of several representative isosurface extraction algorithms. It reports and analyzes empirical measurements of execution times and memory behavior for each algorithm. The results show that asymptotically optimal techniques may not be the best choice when implemented on modern computer architectures.
Unsteady transonic algorithm improvements for realistic aircraft applications
NASA Technical Reports Server (NTRS)
Batina, John T.
1987-01-01
Improvements to a time-accurate approximate factorization (AF) algorithm were implemented for steady and unsteady transonic analysis of realistic aircraft configurations. These algorithm improvements were made to the CAP-TSD (Computational Aeroelasticity Program - Transonic Small Disturbance) code developed at the Langley Research Center. The code permits the aeroelastic analysis of complete aircraft in the flutter critical transonic speed range. The AF algorithm of the CAP-TSD code solves the unsteady transonic small-disturbance equation. The algorithm improvements include: an Engquist-Osher (E-O) type-dependent switch to more accurately and efficiently treat regions of supersonic flow; extension of the E-O switch for second-order spatial accuracy in these regions; nonreflecting far field boundary conditions for more accurate unsteady applications; and several modifications which accelerate convergence to steady-state. Calculations are presented for several configurations including the General Dynamics one-ninth scale F-16C aircraft model to evaluate the algorithm modifications. The modifications have significantly improved the stability of the AF algorithm and hence the reliability of the CAP-TSD code in general.
Li, Jun-Qing; Pan, Quan-Ke; Duan, Pei-Yong
2016-06-01
In this paper, we propose an improved discrete artificial bee colony (DABC) algorithm to solve the hybrid flexible flowshop scheduling problem with dynamic operation skipping features in molten iron systems. First, each solution is represented by a two-vector-based solution representation, and a dynamic encoding mechanism is developed. Second, a flexible decoding strategy is designed. Next, a right-shift strategy considering the problem characteristics is developed, which can clearly improve the solution quality. In addition, several skipping and scheduling neighborhood structures are presented to balance the exploration and exploitation ability. Finally, an enhanced local search is embedded in the proposed algorithm to further improve the exploitation ability. The proposed algorithm is tested on sets of the instances that are generated based on the realistic production. Through comprehensive computational comparisons and statistical analysis, the highly effective performance of the proposed DABC algorithm is favorably compared against several presented algorithms, both in solution quality and efficiency. PMID:26126292
Improved ant algorithms for software testing cases generation.
Yang, Shunkun; Man, Tianlong; Xu, Jiaqi
2014-01-01
Existing ant colony optimization (ACO) for software testing cases generation is a very popular domain in software testing engineering. However, the traditional ACO has flaws, as early search pheromone is relatively scarce, search efficiency is low, search model is too simple, positive feedback mechanism is easy to produce the phenomenon of stagnation and precocity. This paper introduces improved ACO for software testing cases generation: improved local pheromone update strategy for ant colony optimization, improved pheromone volatilization coefficient for ant colony optimization (IPVACO), and improved the global path pheromone update strategy for ant colony optimization (IGPACO). At last, we put forward a comprehensive improved ant colony optimization (ACIACO), which is based on all the above three methods. The proposed technique will be compared with random algorithm (RND) and genetic algorithm (GA) in terms of both efficiency and coverage. The results indicate that the improved method can effectively improve the search efficiency, restrain precocity, promote case coverage, and reduce the number of iterations. PMID:24883391
Improved Ant Algorithms for Software Testing Cases Generation
Yang, Shunkun; Xu, Jiaqi
2014-01-01
Existing ant colony optimization (ACO) for software testing cases generation is a very popular domain in software testing engineering. However, the traditional ACO has flaws, as early search pheromone is relatively scarce, search efficiency is low, search model is too simple, positive feedback mechanism is easy to porduce the phenomenon of stagnation and precocity. This paper introduces improved ACO for software testing cases generation: improved local pheromone update strategy for ant colony optimization, improved pheromone volatilization coefficient for ant colony optimization (IPVACO), and improved the global path pheromone update strategy for ant colony optimization (IGPACO). At last, we put forward a comprehensive improved ant colony optimization (ACIACO), which is based on all the above three methods. The proposed technique will be compared with random algorithm (RND) and genetic algorithm (GA) in terms of both efficiency and coverage. The results indicate that the improved method can effectively improve the search efficiency, restrain precocity, promote case coverage, and reduce the number of iterations. PMID:24883391
Stereo matching: performance study of two global algorithms
NASA Astrophysics Data System (ADS)
Arunagiri, Sarala; Jordan, Victor J.; Teller, Patricia J.; Deroba, Joseph C.; Shires, Dale R.; Park, Song J.; Nguyen, Lam H.
2011-06-01
Techniques such as clinometry, stereoscopy, interferometry, and polarimetry are used for Digital Elevation Model (DEM) generation from Synthetic Aperture Radar (SAR) images. The choice of technique depends on the SAR configuration, the means used for image acquisition, and the relief type. The most popular techniques are interferometry for regions of high coherence and stereoscopy for regions such as steep forested mountain slopes. Stereo matching, which is finds the disparity map or correspondence points between two images acquired from different sensor positions, is a core process in stereoscopy. Additionally, automatic stereo processing, which involves stereo matching, is an important process in other applications including vision-based obstacle avoidance for unmanned air vehicles (UAVs), extraction of weak targets in clutter, and automatic target detection. Due to its high computational complexity, stereo matching has traditionally been, and continues to be, one of the most heavily investigated topics in computer vision. A stereo matching algorithm performs a subset of the following four steps: cost computation, cost (support) aggregation, disparity computation/optimization, and disparity refinement. Based on the method used for cost computation, the algorithms are classified into feature-, phase-, and area-based algorithms; and they are classified as local or global based on how they perform disparity computation/optimization. We present a comparative performance study of two pairs, i.e., four versions, of global stereo matching codes. Each pair uses a different minimization technique: a simulated annealing or graph cut algorithm. And, the codes of a pair differ in terms of the employed global cost function: absolute difference (AD) or a variation of normalized cross correlation (NCC). The performance comparison is in terms of execution time, the global minimum cost achieved, power and energy consumption, and the quality of generated output. The results of
Visualizing and improving the robustness of phase retrieval algorithms
Tripathi, Ashish; Leyffer, Sven; Munson, Todd; Wild, Stefan M.
2015-06-01
Coherent x-ray diffractive imaging is a novel imaging technique that utilizes phase retrieval and nonlinear optimization methods to image matter at nanometer scales. We explore how the convergence properties of a popular phase retrieval algorithm, Fienup's HIO, behave by introducing a reduced dimensionality problem allowing us to visualize and quantify convergence to local minima and the globally optimal solution. We then introduce generalizations of HIO that improve upon the original algorithm's ability to converge to the globally optimal solution.
Economic load dispatch using improved gravitational search algorithm
NASA Astrophysics Data System (ADS)
Huang, Yu; Wang, Jia-rong; Guo, Feng
2016-03-01
This paper presents an improved gravitational search algorithm(IGSA) to solve the economic load dispatch(ELD) problem. In order to avoid the local optimum phenomenon, mutation processing is applied to the GSA. The IGSA is applied to solve the economic load dispatch problems with the valve point effects, which has 13 generators and a load demand of 2520 MW. Calculation results show that the algorithm in this paper can deal with the ELD problems with high stability.
An Improved Physarum polycephalum Algorithm for the Shortest Path Problem
Wang, Qing; Adamatzky, Andrew; Chan, Felix T. S.; Mahadevan, Sankaran
2014-01-01
Shortest path is among classical problems of computer science. The problems are solved by hundreds of algorithms, silicon computing architectures and novel substrate, unconventional, computing devices. Acellular slime mould P. polycephalum is originally famous as a computing biological substrate due to its alleged ability to approximate shortest path from its inoculation site to a source of nutrients. Several algorithms were designed based on properties of the slime mould. Many of the Physarum-inspired algorithms suffer from a low converge speed. To accelerate the search of a solution and reduce a number of iterations we combined an original model of Physarum-inspired path solver with a new a parameter, called energy. We undertook a series of computational experiments on approximating shortest paths in networks with different topologies, and number of nodes varying from 15 to 2000. We found that the improved Physarum algorithm matches well with existing Physarum-inspired approaches yet outperforms them in number of iterations executed and a total running time. We also compare our algorithm with other existing algorithms, including the ant colony optimization algorithm and Dijkstra algorithm. PMID:24982960
An improved Physarum polycephalum algorithm for the shortest path problem.
Zhang, Xiaoge; Wang, Qing; Adamatzky, Andrew; Chan, Felix T S; Mahadevan, Sankaran; Deng, Yong
2014-01-01
Shortest path is among classical problems of computer science. The problems are solved by hundreds of algorithms, silicon computing architectures and novel substrate, unconventional, computing devices. Acellular slime mould P. polycephalum is originally famous as a computing biological substrate due to its alleged ability to approximate shortest path from its inoculation site to a source of nutrients. Several algorithms were designed based on properties of the slime mould. Many of the Physarum-inspired algorithms suffer from a low converge speed. To accelerate the search of a solution and reduce a number of iterations we combined an original model of Physarum-inspired path solver with a new a parameter, called energy. We undertook a series of computational experiments on approximating shortest paths in networks with different topologies, and number of nodes varying from 15 to 2000. We found that the improved Physarum algorithm matches well with existing Physarum-inspired approaches yet outperforms them in number of iterations executed and a total running time. We also compare our algorithm with other existing algorithms, including the ant colony optimization algorithm and Dijkstra algorithm. PMID:24982960
Performance Trend of Different Algorithms for Structural Design Optimization
NASA Technical Reports Server (NTRS)
Patnaik, Surya N.; Coroneos, Rula M.; Guptill, James D.; Hopkins, Dale A.
1996-01-01
Nonlinear programming algorithms play an important role in structural design optimization. Fortunately, several algorithms with computer codes are available. At NASA Lewis Research Center, a project was initiated to assess performance of different optimizers through the development of a computer code CometBoards. This paper summarizes the conclusions of that research. CometBoards was employed to solve sets of small, medium and large structural problems, using different optimizers on a Cray-YMP8E/8128 computer. The reliability and efficiency of the optimizers were determined from the performance of these problems. For small problems, the performance of most of the optimizers could be considered adequate. For large problems however, three optimizers (two sequential quadratic programming routines, DNCONG of IMSL and SQP of IDESIGN, along with the sequential unconstrained minimizations technique SUMT) outperformed others. At optimum, most optimizers captured an identical number of active displacement and frequency constraints but the number of active stress constraints differed among the optimizers. This discrepancy can be attributed to singularity conditions in the optimization and the alleviation of this discrepancy can improve the efficiency of optimizers.
NASA Astrophysics Data System (ADS)
Zhang, B.; Qi, H.; Ren, Y. T.; Sun, S. C.; Ruan, L. M.
2014-01-01
As a heuristic intelligent optimization algorithm, the Ant Colony Optimization (ACO) algorithm was applied to the inverse problem of a one-dimensional (1-D) transient radiative transfer in present study. To illustrate the performance of this algorithm, the optical thickness and scattering albedo of the 1-D participating slab medium were retrieved simultaneously. The radiative reflectance simulated by Monte-Carlo Method (MCM) and Finite Volume Method (FVM) were used as measured and estimated value for the inverse analysis, respectively. To improve the accuracy and efficiency of the Basic Ant Colony Optimization (BACO) algorithm, three improved ACO algorithms, i.e., the Region Ant Colony Optimization algorithm (RACO), Stochastic Ant Colony Optimization algorithm (SACO) and Homogeneous Ant Colony Optimization algorithm (HACO), were developed. By the HACO algorithm presented, the radiative parameters could be estimated accurately, even with noisy data. In conclusion, the HACO algorithm is demonstrated to be effective and robust, which had the potential to be implemented in various fields of inverse radiation problems.
Recent Algorithmic and Computational Efficiency Improvements in the NIMROD Code
NASA Astrophysics Data System (ADS)
Plimpton, S. J.; Sovinec, C. R.; Gianakon, T. A.; Parker, S. E.
1999-11-01
Extreme anisotropy and temporal stiffness impose severe challenges to simulating low frequency, nonlinear behavior in magnetized fusion plasmas. To address these challenges in computations of realistic experiment configurations, NIMROD(Glasser, et al., Plasma Phys. Control. Fusion 41) (1999) A747. uses a time-split, semi-implicit advance of the two-fluid equations for magnetized plasmas with a finite element/Fourier series spatial representation. The stiffness and anisotropy lead to ill-conditioned linear systems of equations, and they emphasize any truncation errors that may couple different modes of the continuous system. Recent work significantly improves NIMROD's performance in these areas. Implementing a parallel global preconditioning scheme in structured-grid regions permits scaling to large problems and large time steps, which are critical for achieving realistic S-values. In addition, coupling to the AZTEC parallel linear solver package now permits efficient computation with regions of unstructured grid. Changes in the time-splitting scheme improve numerical behavior in simulations with strong flow, and quadratic basis elements are being explored for accuracy. Different numerical forms of anisotropic thermal conduction, critical for slow island evolution, are compared. Algorithms for including gyrokinetic ions in the finite element computations are discussed.
An improved filter-u least mean square vibration control algorithm for aircraft framework.
Huang, Quanzhen; Luo, Jun; Gao, Zhiyuan; Zhu, Xiaojin; Li, Hengyu
2014-09-01
Active vibration control of aerospace vehicle structures is very a hot spot and in which filter-u least mean square (FULMS) algorithm is one of the key methods. But for practical reasons and technical limitations, vibration reference signal extraction is always a difficult problem for FULMS algorithm. To solve the vibration reference signal extraction problem, an improved FULMS vibration control algorithm is proposed in this paper. Reference signal is constructed based on the controller structure and the data in the algorithm process, using a vibration response residual signal extracted directly from the vibration structure. To test the proposed algorithm, an aircraft frame model is built and an experimental platform is constructed. The simulation and experimental results show that the proposed algorithm is more practical with a good vibration suppression performance. PMID:25273765
A landmark matching algorithm using the improved generalised Hough transform
NASA Astrophysics Data System (ADS)
Chen, Binbin; Deng, Xingpu
2015-10-01
The paper addresses the issue on landmark matching of images from Geosynchronous Earth Orbit (GEO) satellites. In general, satellite imagery is matched against the base image, which is predefined. When the satellite imagery rotation occurs, the accuracy of many landmark matching algorithms deteriorates. To overcome this problem, generalised Hough transform (GHT) is employed for landmark matching. At first an improved GHT algorithm is proposed to enhance rotational invariance. Secondly a global coastline is processed to generate the test image as the satellite image and the base image. Then the test image is matched against the base image using the proposed algorithm. The matching results show that the proposed algorithm is rotation invariant and works well in landmark matching.
Generic algorithms for high performance scalable geocomputing
NASA Astrophysics Data System (ADS)
de Jong, Kor; Schmitz, Oliver; Karssenberg, Derek
2016-04-01
During the last decade, the characteristics of computing hardware have changed a lot. For example, instead of a single general purpose CPU core, personal computers nowadays contain multiple cores per CPU and often general purpose accelerators, like GPUs. Additionally, compute nodes are often grouped together to form clusters or a supercomputer, providing enormous amounts of compute power. For existing earth simulation models to be able to use modern hardware platforms, their compute intensive parts must be rewritten. This can be a major undertaking and may involve many technical challenges. Compute tasks must be distributed over CPU cores, offloaded to hardware accelerators, or distributed to different compute nodes. And ideally, all of this should be done in such a way that the compute task scales well with the hardware resources. This presents two challenges: 1) how to make good use of all the compute resources and 2) how to make these compute resources available for developers of simulation models, who may not (want to) have the required technical background for distributing compute tasks. The first challenge requires the use of specialized technology (e.g.: threads, OpenMP, MPI, OpenCL, CUDA). The second challenge requires the abstraction of the logic handling the distribution of compute tasks from the model-specific logic, hiding the technical details from the model developer. To assist the model developer, we are developing a C++ software library (called Fern) containing algorithms that can use all CPU cores available in a single compute node (distributing tasks over multiple compute nodes will be done at a later stage). The algorithms are grid-based (finite difference) and include local and spatial operations such as convolution filters. The algorithms handle distribution of the compute tasks to CPU cores internally. In the resulting model the low-level details of how this is done is separated from the model-specific logic representing the modeled system
Generic algorithms for high performance scalable geocomputing
NASA Astrophysics Data System (ADS)
de Jong, Kor; Schmitz, Oliver; Karssenberg, Derek
2016-04-01
During the last decade, the characteristics of computing hardware have changed a lot. For example, instead of a single general purpose CPU core, personal computers nowadays contain multiple cores per CPU and often general purpose accelerators, like GPUs. Additionally, compute nodes are often grouped together to form clusters or a supercomputer, providing enormous amounts of compute power. For existing earth simulation models to be able to use modern hardware platforms, their compute intensive parts must be rewritten. This can be a major undertaking and may involve many technical challenges. Compute tasks must be distributed over CPU cores, offloaded to hardware accelerators, or distributed to different compute nodes. And ideally, all of this should be done in such a way that the compute task scales well with the hardware resources. This presents two challenges: 1) how to make good use of all the compute resources and 2) how to make these compute resources available for developers of simulation models, who may not (want to) have the required technical background for distributing compute tasks. The first challenge requires the use of specialized technology (e.g.: threads, OpenMP, MPI, OpenCL, CUDA). The second challenge requires the abstraction of the logic handling the distribution of compute tasks from the model-specific logic, hiding the technical details from the model developer. To assist the model developer, we are developing a C++ software library (called Fern) containing algorithms that can use all CPU cores available in a single compute node (distributing tasks over multiple compute nodes will be done at a later stage). The algorithms are grid-based (finite difference) and include local and spatial operations such as convolution filters. The algorithms handle distribution of the compute tasks to CPU cores internally. In the resulting model the low-level details of how this is done is separated from the model-specific logic representing the modeled system
Copps, Kevin D.; Carnes, Brian R.
2008-04-01
We examine algorithms for the finite element approximation of thermal contact models. We focus on the implementation of thermal contact algorithms in SIERRA Mechanics. Following the mathematical formulation of models for tied contact and resistance contact, we present three numerical algorithms: (1) the multi-point constraint (MPC) algorithm, (2) a resistance algorithm, and (3) a new generalized algorithm. We compare and contrast both the correctness and performance of the algorithms in three test problems. We tabulate the convergence rates of global norms of the temperature solution on sequentially refined meshes. We present the results of a parameter study of the effect of contact search tolerances. We outline best practices in using the software for predictive simulations, and suggest future improvements to the implementation.
Improving Wordspotting Performance with Limited Training Data
NASA Astrophysics Data System (ADS)
Chang, Eric I.-Chao
1995-01-01
This thesis addresses the problem of limited training data in pattern detection problems where a small number of target classes must be detected in a varied background. There is typically limited training data and limited knowledge about class distributions in this type of spotting problem and in this case a statistical pattern classifier can not accurately model class distributions. The domain of wordspotting is used to explore new approaches that improve spotting system performance with limited training data. First, a high performance, state-of-the-art whole-word based wordspotter is developed. Two complementary approaches are then introduced to help compensate for the lack of data. Figure of Merit training, a new type of discriminative training algorithm, modifies the spotting system parameters according to the metric used to evaluate wordspotting systems. The effectiveness of discriminative training approaches may be limited due to overtraining a classifier on insufficient training data. While the classifier's performance on the training data improves, the classifier's performance on unseen test data degrades. To alleviate this problem, voice transformation techniques are used to generate more training examples that improve the robustness of the spotting system. The wordspotter is trained and tested on the Switchboard credit-card database, a database of spontaneous conversations recorded over the telephone. The baseline wordspotter achieves a Figure of Merit of 62.5% on a testing set. With Figure of Merit training, the Figure of Merit improves to 65.8%. When Figure of Merit training and voice transformations are used together, the Figure of Merit improves to 71.9%. The final wordspotter system achieves a Figure of Merit of 64.2% on the National Institute of Standards and Technology (NIST) September 1992 official benchmark, surpassing the 1992 results from other whole-word based wordspotting systems. (Copies available exclusively from MIT Libraries, Rm. 14
NASA Technical Reports Server (NTRS)
Zhou, Yaping; Kratz, David P.; Wilber, Anne C.; Gupta, Shashi K.; Cess, Robert D.
2007-01-01
Zhou and Cess [2001] developed an algorithm for retrieving surface downwelling longwave radiation (SDLW) based upon detailed studies using radiative transfer model calculations and surface radiometric measurements. Their algorithm linked clear sky SDLW with surface upwelling longwave flux and column precipitable water vapor. For cloudy sky cases, they used cloud liquid water path as an additional parameter to account for the effects of clouds. Despite the simplicity of their algorithm, it performed very well for most geographical regions except for those regions where the atmospheric conditions near the surface tend to be extremely cold and dry. Systematic errors were also found for scenes that were covered with ice clouds. An improved version of the algorithm prevents the large errors in the SDLW at low water vapor amounts by taking into account that under such conditions the SDLW and water vapor amount are nearly linear in their relationship. The new algorithm also utilizes cloud fraction and cloud liquid and ice water paths available from the Cloud and the Earth's Radiant Energy System (CERES) single scanner footprint (SSF) product to separately compute the clear and cloudy portions of the fluxes. The new algorithm has been validated against surface measurements at 29 stations around the globe for Terra and Aqua satellites. The results show significant improvement over the original version. The revised Zhou-Cess algorithm is also slightly better or comparable to more sophisticated algorithms currently implemented in the CERES processing and will be incorporated as one of the CERES empirical surface radiation algorithms.
Li, Yingsong; Hamamura, Masanori
2014-01-01
To make use of the sparsity property of broadband multipath wireless communication channels, we mathematically propose an l p -norm-constrained proportionate normalized least-mean-square (LP-PNLMS) sparse channel estimation algorithm. A general l p -norm is weighted by the gain matrix and is incorporated into the cost function of the proportionate normalized least-mean-square (PNLMS) algorithm. This integration is equivalent to adding a zero attractor to the iterations, by which the convergence speed and steady-state performance of the inactive taps are significantly improved. Our simulation results demonstrate that the proposed algorithm can effectively improve the estimation performance of the PNLMS-based algorithm for sparse channel estimation applications. PMID:24782663
2014-01-01
To make use of the sparsity property of broadband multipath wireless communication channels, we mathematically propose an lp-norm-constrained proportionate normalized least-mean-square (LP-PNLMS) sparse channel estimation algorithm. A general lp-norm is weighted by the gain matrix and is incorporated into the cost function of the proportionate normalized least-mean-square (PNLMS) algorithm. This integration is equivalent to adding a zero attractor to the iterations, by which the convergence speed and steady-state performance of the inactive taps are significantly improved. Our simulation results demonstrate that the proposed algorithm can effectively improve the estimation performance of the PNLMS-based algorithm for sparse channel estimation applications. PMID:24782663
NASA Astrophysics Data System (ADS)
Wang, Bingjie; Pi, Shaohua; Sun, Qi; Jia, Bo
2015-05-01
An improved classification algorithm that considers multiscale wavelet packet Shannon entropy is proposed. Decomposition coefficients at all levels are obtained to build the initial Shannon entropy feature vector. After subtracting the Shannon entropy map of the background signal, components of the strongest discriminating power in the initial feature vector are picked out to rebuild the Shannon entropy feature vector, which is transferred to radial basis function (RBF) neural network for classification. Four types of man-made vibrational intrusion signals are recorded based on a modified Sagnac interferometer. The performance of the improved classification algorithm has been evaluated by the classification experiments via RBF neural network under different diffusion coefficients. An 85% classification accuracy rate is achieved, which is higher than the other common algorithms. The classification results show that this improved classification algorithm can be used to classify vibrational intrusion signals in an automatic real-time monitoring system.
An Improved Wind Speed Retrieval Algorithm For The CYGNSS Mission
NASA Astrophysics Data System (ADS)
Ruf, C. S.; Clarizia, M. P.
2015-12-01
The NASA spaceborne Cyclone Global Navigation Satellite System (CYGNSS) mission is a constellation of 8 microsatellites focused on tropical cyclone (TC) inner core process studies. CYGNSS will be launched in October 2016, and will use GPS-Reflectometry (GPS-R) to measure ocean surface wind speed in all precipitating conditions, and with sufficient frequency to resolve genesis and rapid intensification. Here we present a modified and improved version of the current baseline Level 2 (L2) wind speed retrieval algorithm designed for CYGNSS. An overview of the current approach is first presented, which makes use of two different observables computed from 1-second Level 1b (L1b) delay-Doppler Maps (DDMs) of radar cross section. The first observable, the Delay-Doppler Map Average (DDMA), is the averaged radar cross section over a delay-Doppler window around the DDM peak (i.e. the specular reflection point coordinate in delay and Doppler). The second, the Leading Edge Slope (LES), is the leading edge of the Integrated Delay Waveform (IDW), obtained by integrating the DDM along the Doppler dimension. The observables are calculated over a limited range of time delays and Doppler frequencies to comply with baseline spatial resolution requirements for the retrieved winds, which in the case of CYGNSS is 25 km. In the current approach, the relationship between the observable value and the surface winds is described by an empirical Geophysical Model Function (GMF) that is characterized by a very high slope in the high wind regime, for both DDMA and LES observables, causing large errors in the retrieval at high winds. A simple mathematical modification of these observables is proposed, which linearizes the relationship between ocean surface roughness and the observables. This significantly reduces the non-linearity present in the GMF that relate the observables to the wind speed, and reduces the root-mean square error between true and retrieved winds, particularly in the high wind
Motion Cueing Algorithm Development: Piloted Performance Testing of the Cueing Algorithms
NASA Technical Reports Server (NTRS)
Houck, Jacob A. (Technical Monitor); Telban, Robert J.; Cardullo, Frank M.; Kelly, Lon C.
2005-01-01
The relative effectiveness in simulating aircraft maneuvers with both current and newly developed motion cueing algorithms was assessed with an eleven-subject piloted performance evaluation conducted on the NASA Langley Visual Motion Simulator (VMS). In addition to the current NASA adaptive algorithm, two new cueing algorithms were evaluated: the optimal algorithm and the nonlinear algorithm. The test maneuvers included a straight-in approach with a rotating wind vector, an offset approach with severe turbulence and an on/off lateral gust that occurs as the aircraft approaches the runway threshold, and a takeoff both with and without engine failure after liftoff. The maneuvers were executed with each cueing algorithm with added visual display delay conditions ranging from zero to 200 msec. Two methods, the quasi-objective NASA Task Load Index (TLX), and power spectral density analysis of pilot control, were used to assess pilot workload. Piloted performance parameters for the approach maneuvers, the vertical velocity upon touchdown and the runway touchdown position, were also analyzed but did not show any noticeable difference among the cueing algorithms. TLX analysis reveals, in most cases, less workload and variation among pilots with the nonlinear algorithm. Control input analysis shows pilot-induced oscillations on a straight-in approach were less prevalent compared to the optimal algorithm. The augmented turbulence cues increased workload on an offset approach that the pilots deemed more realistic compared to the NASA adaptive algorithm. The takeoff with engine failure showed the least roll activity for the nonlinear algorithm, with the least rudder pedal activity for the optimal algorithm.
An improved algorithm of a priori based on geostatistics
NASA Astrophysics Data System (ADS)
Chen, Jiangping; Wang, Rong; Tang, Xuehua
2008-12-01
In data mining one of the classical algorithms is Apriori which has been developed for association rule mining in large transaction database. And it cannot been directly used in spatial association rules mining. The main difference between data mining in relational DB and in spatial DB is that attributes of the neighbors of some object of interest may have an influence on the object and therefore have to be considered as well. The explicit location and extension of spatial objects define implicit relations of spatial neighborhood (such as topological, distance and direction relations) which are used by spatial data mining algorithms. Therefore, new techniques are required for effective and efficient spatial data mining. Geostatistics are statistical methods used to describe spatial relationships among sample data and to apply this analysis to the prediction of spatial and temporal phenomena. They are used to explain spatial patterns and to interpolate values at unsampled locations. This paper put forward an improved algorithm of Apriori about mining association rules with geostatistics. First the spatial autocorrelation of the attributes with location were estimated with the geostatistics methods such as kriging and Spatial Autoregressive Model (SAR). Then a spatial autocorrelation model of the attributes were built. Later an improved algorithm of apriori combined with the spatial autocorrelation model were offered to mine the spatial association rules. Last an experiment of the new algorithm were carried out on the hayfever incidence and climate factors in UK. The result shows that the output rules is matched with the references.
[An improved medical image fusion algorithm and quality evaluation].
Chen, Meiling; Tao, Ling; Qian, Zhiyu
2009-08-01
Medical image fusion is of very important value for application in medical image analysis and diagnosis. In this paper, the conventional method of wavelet fusion is improved,so a new algorithm of medical image fusion is presented and the high frequency and low frequency coefficients are studied respectively. When high frequency coefficients are chosen, the regional edge intensities of each sub-image are calculated to realize adaptive fusion. The choice of low frequency coefficient is based on the edges of images, so that the fused image preserves all useful information and appears more distinctly. We apply the conventional and the improved fusion algorithms based on wavelet transform to fuse two images of human body and also evaluate the fusion results through a quality evaluation method. Experimental results show that this algorithm can effectively retain the details of information on original images and enhance their edge and texture features. This new algorithm is better than the conventional fusion algorithm based on wavelet transform. PMID:19813594
Improved document image segmentation algorithm using multiresolution morphology
NASA Astrophysics Data System (ADS)
Bukhari, Syed Saqib; Shafait, Faisal; Breuel, Thomas M.
2011-01-01
Page segmentation into text and non-text elements is an essential preprocessing step before optical character recognition (OCR) operation. In case of poor segmentation, an OCR classification engine produces garbage characters due to the presence of non-text elements. This paper describes modifications to the text/non-text segmentation algorithm presented by Bloomberg,1 which is also available in his open-source Leptonica library.2The modifications result in significant improvements and achieved better segmentation accuracy than the original algorithm for UW-III, UNLV, ICDAR 2009 page segmentation competition test images and circuit diagram datasets.
Improvements in antenna coupling path algorithms for aircraft EMC analysis
NASA Astrophysics Data System (ADS)
Bogusz, Michael; Kibina, Stanley J.
The algorithms to calculate and display the path of maximum electromagnetic interference coupling along the perfectly conducting surface of a frustrum cone model of an aircraft nose are developed and revised for the Aircraft Inter-Antenna Propagation with Graphics (AAPG) electromagnetic compatibility analysis code. Analysis of the coupling problem geometry on the frustrum cone model and representative numerical test cases reveal how the revised algorithms are more accurate than their predecessors. These improvements in accuracy and their impact on realistic aircraft electromagnetic compatibility problems are outlined.
Improved MCA-TV algorithm for interference hyperspectral image decomposition
NASA Astrophysics Data System (ADS)
Wen, Jia; Zhao, Junsuo; Cailing, Wang
2015-12-01
The technology of interference hyperspectral imaging, which can get the spectral and spatial information of the observed targets, is a very powerful technology in the field of remote sensing. Due to the special imaging principle, there are many position-fixed interference fringes in each frame of the interference hyperspectral image (IHI) data. This characteristic will affect the result of compressed sensing theory and traditional compression algorithms used on IHI data. According to this characteristic of the IHI data, morphological component analysis (MCA) is adopted to separate the interference fringes layers and the background layers of the LSMIS (Large Spatially Modulated Interference Spectral Image) data, and an improved MCA and Total Variation (TV) combined algorithm is proposed in this paper. An update mode of the threshold in traditional MCA is proposed, and the traditional TV algorithm is also improved according to the unidirectional characteristic of the interference fringes in IHI data. The experimental results prove that the proposed improved MCA-TV (IMT) algorithm can get better results than the traditional MCA, and also can meet the convergence conditions much faster than the traditional MCA.
Masseter segmentation using an improved watershed algorithm with unsupervised classification.
Ng, H P; Ong, S H; Foong, K W C; Goh, P S; Nowinski, W L
2008-02-01
The watershed algorithm always produces a complete division of the image. However, it is susceptible to over-segmentation and sensitivity to false edges. In medical images this leads to unfavorable representations of the anatomy. We address these drawbacks by introducing automated thresholding and post-segmentation merging. The automated thresholding step is based on the histogram of the gradient magnitude map while post-segmentation merging is based on a criterion which measures the similarity in intensity values between two neighboring partitions. Our improved watershed algorithm is able to merge more than 90% of the initial partitions, which indicates that a large amount of over-segmentation has been reduced. To further improve the segmentation results, we make use of K-means clustering to provide an initial coarse segmentation of the highly textured image before the improved watershed algorithm is applied to it. When applied to the segmentation of the masseter from 60 magnetic resonance images of 10 subjects, the proposed algorithm achieved an overlap index (kappa) of 90.6%, and was able to merge 98% of the initial partitions on average. The segmentation results are comparable to those obtained using the gradient vector flow snake. PMID:17950265
Overlay improvements using a real time machine learning algorithm
NASA Astrophysics Data System (ADS)
Schmitt-Weaver, Emil; Kubis, Michael; Henke, Wolfgang; Slotboom, Daan; Hoogenboom, Tom; Mulkens, Jan; Coogans, Martyn; ten Berge, Peter; Verkleij, Dick; van de Mast, Frank
2014-04-01
While semiconductor manufacturing is moving towards the 14nm node using immersion lithography, the overlay requirements are tightened to below 5nm. Next to improvements in the immersion scanner platform, enhancements in the overlay optimization and process control are needed to enable these low overlay numbers. Whereas conventional overlay control methods address wafer and lot variation autonomously with wafer pre exposure alignment metrology and post exposure overlay metrology, we see a need to reduce these variations by correlating more of the TWINSCAN system's sensor data directly to the post exposure YieldStar metrology in time. In this paper we will present the results of a study on applying a real time control algorithm based on machine learning technology. Machine learning methods use context and TWINSCAN system sensor data paired with post exposure YieldStar metrology to recognize generic behavior and train the control system to anticipate on this generic behavior. Specific for this study, the data concerns immersion scanner context, sensor data and on-wafer measured overlay data. By making the link between the scanner data and the wafer data we are able to establish a real time relationship. The result is an inline controller that accounts for small changes in scanner hardware performance in time while picking up subtle lot to lot and wafer to wafer deviations introduced by wafer processing.
Image enhancement algorithm based on improved lateral inhibition network
NASA Astrophysics Data System (ADS)
Yun, Haijiao; Wu, Zhiyong; Wang, Guanjun; Tong, Gang; Yang, Hua
2016-05-01
There is often substantial noise and blurred details in the images captured by cameras. To solve this problem, we propose a novel image enhancement algorithm combined with an improved lateral inhibition network. Firstly, we built a mathematical model of a lateral inhibition network in conjunction with biological visual perception; this model helped to realize enhanced contrast and improved edge definition in images. Secondly, we proposed that the adaptive lateral inhibition coefficient adhere to an exponential distribution thus making the model more flexible and more universal. Finally, we added median filtering and a compensation measure factor to build the framework with high pass filtering functionality thus eliminating image noise and improving edge contrast, addressing problems with blurred image edges. Our experimental results show that our algorithm is able to eliminate noise and the blurring phenomena, and enhance the details of visible and infrared images.
Improving the trust algorithm of information in semantic web
NASA Astrophysics Data System (ADS)
Wan, Zong-bao; Min, Jiang
2012-01-01
With the rapid development of computer networks, especially with the introduction of the Semantic Web perspective, the problem of trust computation in the network has become an important research part of current computer system theoretical. In this paper, according the information properties of the Semantic Web and interact between nodes, the definition semantic trust as content trust of information and the node trust between the nodes of two parts. By Calculate the content of the trust of information and the trust between nodes, then get the final credibility num of information in semantic web. In this paper , we are improve the computation algorithm of the node trust .Finally, stimulations and analyses show that the improved algorithm can effectively improve the trust of information more accurately.
Improving the trust algorithm of information in semantic web
NASA Astrophysics Data System (ADS)
Wan, Zong-Bao; Min, Jiang
2011-12-01
With the rapid development of computer networks, especially with the introduction of the Semantic Web perspective, the problem of trust computation in the network has become an important research part of current computer system theoretical. In this paper, according the information properties of the Semantic Web and interact between nodes, the definition semantic trust as content trust of information and the node trust between the nodes of two parts. By Calculate the content of the trust of information and the trust between nodes, then get the final credibility num of information in semantic web. In this paper , we are improve the computation algorithm of the node trust .Finally, stimulations and analyses show that the improved algorithm can effectively improve the trust of information more accurately.
Improve Relationships to Improve Student Performance
ERIC Educational Resources Information Center
Arum, Richard
2011-01-01
Attempts to raise student performance have focused primarily on either relationships between adults in the system or formal curriculum. Relatively ignored has been a focus on what sociologists believe is the primary relationship of consequence for student outcomes--authority relationships between students and educators. Successful school reform is…
Performance study of LMS based adaptive algorithms for unknown system identification
Javed, Shazia; Ahmad, Noor Atinah
2014-07-10
Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.
Performance study of LMS based adaptive algorithms for unknown system identification
NASA Astrophysics Data System (ADS)
Javed, Shazia; Ahmad, Noor Atinah
2014-07-01
Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.
Performance characterization of a combined material identification and screening algorithm
NASA Astrophysics Data System (ADS)
Green, Robert L.; Hargreaves, Michael D.; Gardner, Craig M.
2013-05-01
Portable analytical devices based on a gamut of technologies (Infrared, Raman, X-Ray Fluorescence, Mass Spectrometry, etc.) are now widely available. These tools have seen increasing adoption for field-based assessment by diverse users including military, emergency response, and law enforcement. Frequently, end-users of portable devices are non-scientists who rely on embedded software and the associated algorithms to convert collected data into actionable information. Two classes of problems commonly encountered in field applications are identification and screening. Identification algorithms are designed to scour a library of known materials and determine whether the unknown measurement is consistent with a stored response (or combination of stored responses). Such algorithms can be used to identify a material from many thousands of possible candidates. Screening algorithms evaluate whether at least a subset of features in an unknown measurement correspond to one or more specific substances of interest and are typically configured to detect from a small list potential target analytes. Thus, screening algorithms are much less broadly applicable than identification algorithms; however, they typically provide higher detection rates which makes them attractive for specific applications such as chemical warfare agent or narcotics detection. This paper will present an overview and performance characterization of a combined identification/screening algorithm that has recently been developed. It will be shown that the combined algorithm provides enhanced detection capability more typical of screening algorithms while maintaining a broad identification capability. Additionally, we will highlight how this approach can enable users to incorporate situational awareness during a response.
Recent performance improvements on FXR
Kulke, B.; Kihara, R.
1983-01-01
The FXR machine is a nominal 4-kA, 20-MeV, linear-induction, electron accelerator for flash radiography at LLNL. The machine met its baseline requirements in March 1982. Since then, the performance has been greatly improved. We have achieved stable and repeatable beam acceleration and transport, with over 80% transmission to the tungsten bremsstrahlung target located some 35 m downstream. For best stability, external-beam steering has been eliminated almost entirely. We regularly produce over 500 Roentgen at 1 m from the target (TLD measurement), with a radiographic spot size of 3 to 5 mm. Present efforts are directed towards the development of a 4-kA tune, working interactively with particle-field and beam transport code models. A remaining uncertainty is the possible onset of RF instabilities at the higher current levels.
Efficient Improvement of Silage Additives by Using Genetic Algorithms
Davies, Zoe S.; Gilbert, Richard J.; Merry, Roger J.; Kell, Douglas B.; Theodorou, Michael K.; Griffith, Gareth W.
2000-01-01
The enormous variety of substances which may be added to forage in order to manipulate and improve the ensilage process presents an empirical, combinatorial optimization problem of great complexity. To investigate the utility of genetic algorithms for designing effective silage additive combinations, a series of small-scale proof of principle silage experiments were performed with fresh ryegrass. Having established that significant biochemical changes occur over an ensilage period as short as 2 days, we performed a series of experiments in which we used 50 silage additive combinations (prepared by using eight bacterial and other additives, each of which was added at six different levels, including zero [i.e., no additive]). The decrease in pH, the increase in lactate concentration, and the free amino acid concentration were measured after 2 days and used to calculate a “fitness” value that indicated the quality of the silage (compared to a control silage made without additives). This analysis also included a “cost” element to account for different total additive levels. In the initial experiment additive levels were selected randomly, but subsequently a genetic algorithm program was used to suggest new additive combinations based on the fitness values determined in the preceding experiments. The result was very efficient selection for silages in which large decreases in pH and high levels of lactate occurred along with low levels of free amino acids. During the series of five experiments, each of which comprised 50 treatments, there was a steady increase in the amount of lactate that accumulated; the best treatment combination was that used in the last experiment, which produced 4.6 times more lactate than the untreated silage. The additive combinations that were found to yield the highest fitness values in the final (fifth) experiment were assessed to determine a range of biochemical and microbiological quality parameters during full-term silage
An improved service-aware multipath algorithm for wireless multimedia sensor networks
NASA Astrophysics Data System (ADS)
Ding, Yongjie; Tang, Ruichun; Xu, Huimin; Liu, Yafang
2013-03-01
Study the multipath transmission problems of the different services in Wireless Multimedia Sensor Networks (WMSN). To further effectively utilize networks resources, the multipath mechanism and service-aware is used to improve performance of OLSR(Optimized Link State Routing). A SM-OLSR(Service-aware Multipath OLSR) algorithm is proposed. An efficiency model is introduced, then multipath is built according to the routing ID and energy efficiency. Compared with other routing algorithms, simulation results show that the algorithm can provide service support for different data.
Improved Snow Mapping Accuracy with Revised MODIS Snow Algorithm
NASA Technical Reports Server (NTRS)
Riggs, George; Hall, Dorothy K.
2012-01-01
The MODIS snow cover products have been used in over 225 published studies. From those reports, and our ongoing analysis, we have learned about the accuracy and errors in the snow products. Revisions have been made in the algorithms to improve the accuracy of snow cover detection in Collection 6 (C6), the next processing/reprocessing of the MODIS data archive planned to start in September 2012. Our objective in the C6 revision of the MODIS snow-cover algorithms and products is to maximize the capability to detect snow cover while minimizing snow detection errors of commission and omission. While the basic snow detection algorithm will not change, new screens will be applied to alleviate snow detection commission and omission errors, and only the fractional snow cover (FSC) will be output (the binary snow cover area (SCA) map will no longer be included).
The performance and development for the Inner Detector Trigger algorithms at ATLAS
NASA Astrophysics Data System (ADS)
Penc, Ondrej
2015-05-01
A redesign of the tracking algorithms for the ATLAS trigger for LHC's Run 2 starting in 2015 is in progress. The ATLAS HLT software has been restructured to run as a more flexible single stage HLT, instead of two separate stages (Level 2 and Event Filter) as in Run 1. The new tracking strategy employed for Run 2 will use a Fast Track Finder (FTF) algorithm to seed subsequent Precision Tracking, and will result in improved track parameter resolution and faster execution times than achieved during Run 1. The performance of the new algorithms has been evaluated to identify those aspects where code optimisation would be most beneficial. The performance and timing of the algorithms for electron and muon reconstruction in the trigger are presented. The profiling infrastructure, constructed to provide prompt feedback from the optimisation, is described, including the methods used to monitor the relative performance improvements as the code evolves.
Improved algorithm for solving nonlinear parabolized stability equations
NASA Astrophysics Data System (ADS)
Zhao, Lei; Zhang, Cun-bo; Liu, Jian-xin; Luo, Ji-sheng
2016-08-01
Due to its high computational efficiency and ability to consider nonparallel and nonlinear effects, nonlinear parabolized stability equations (NPSE) approach has been widely used to study the stability and transition mechanisms. However, it often diverges in hypersonic boundary layers when the amplitude of disturbance reaches a certain level. In this study, an improved algorithm for solving NPSE is developed. In this algorithm, the mean flow distortion is included into the linear operator instead of into the nonlinear forcing terms in NPSE. An under-relaxation factor for computing the nonlinear terms is introduced during the iteration process to guarantee the robustness of the algorithm. Two case studies, the nonlinear development of stationary crossflow vortices and the fundamental resonance of the second mode disturbance in hypersonic boundary layers, are presented to validate the proposed algorithm for NPSE. Results from direct numerical simulation (DNS) are regarded as the baseline for comparison. Good agreement can be found between the proposed algorithm and DNS, which indicates the great potential of the proposed method on studying the crossflow and streamwise instability in hypersonic boundary layers. Project supported by the National Natural Science Foundation of China (Grant Nos. 11332007 and 11402167).
Vyas, Bhargav Y; Das, Biswarup; Maheshwari, Rudra Prakash
2016-08-01
This paper presents the Chebyshev neural network (ChNN) as an improved artificial intelligence technique for power system protection studies and examines the performances of two ChNN learning algorithms for fault classification of series compensated transmission line. The training algorithms are least-square Levenberg-Marquardt (LSLM) and recursive least-square algorithm with forgetting factor (RLSFF). The performances of these algorithms are assessed based on their generalization capability in relating the fault current parameters with an event of fault in the transmission line. The proposed algorithm is fast in response as it utilizes postfault samples of three phase currents measured at the relaying end corresponding to half-cycle duration only. After being trained with only a small part of the generated fault data, the algorithms have been tested over a large number of fault cases with wide variation of system and fault parameters. Based on the studies carried out in this paper, it has been found that although the RLSFF algorithm is faster for training the ChNN in the fault classification application for series compensated transmission lines, the LSLM algorithm has the best accuracy in testing. The results prove that the proposed ChNN-based method is accurate, fast, easy to design, and immune to the level of compensations. Thus, it is suitable for digital relaying applications. PMID:25314714
An Improved Neutron Transport Algorithm for Space Radiation
NASA Technical Reports Server (NTRS)
Heinbockel, John H.; Clowdsley, Martha S.; Wilson, John W.
2000-01-01
A low-energy neutron transport algorithm for use in space radiation protection is developed. The algorithm is based upon a multigroup analysis of the straight-ahead Boltzmann equation by using a mean value theorem for integrals. This analysis is accomplished by solving a realistic but simplified neutron transport test problem. The test problem is analyzed by using numerical and analytical procedures to obtain an accurate solution within specified error bounds. Results from the test problem are then used for determining mean values associated with rescattering terms that are associated with a multigroup solution of the straight-ahead Boltzmann equation. The algorithm is then coupled to the Langley HZETRN code through the evaporation source term. Evaluation of the neutron fluence generated by the solar particle event of February 23, 1956, for a water and an aluminum-water shield-target configuration is then compared with LAHET and MCNPX Monte Carlo code calculations for the same shield-target configuration. The algorithm developed showed a great improvement in results over the unmodified HZETRN solution. In addition, a two-directional solution of the evaporation source showed even further improvement of the fluence near the front of the water target where diffusion from the front surface is important.
A strictly improving Phase 1 algorithm using least-squares subproblems
Leichner, S.A.; Dantzig, G.B.; Davis, J.W.
1992-04-01
Although the simplex method`s performance in solving linear programming problems is usually quite good, it does not guarantee strict improvement at each iteration on degenerate problems. Instead of trying to recognize and avoid degenerate steps in the simplex method, we have developed a new Phase I algorithm that is completely impervious to degeneracy, with strict improvement attained at each iteration. It is also noted that the new Phase I algorithm is closely related to a number of existing algorithms. When tested on the 30 smallest NETLIB linear programming test problems, the computational results for the new Phase I algorithm were almost 3.5 times faster than the simplex method; on some problems, it was over 10 times faster.
A strictly improving Phase 1 algorithm using least-squares subproblems
Leichner, S.A.; Dantzig, G.B.; Davis, J.W.
1992-04-01
Although the simplex method's performance in solving linear programming problems is usually quite good, it does not guarantee strict improvement at each iteration on degenerate problems. Instead of trying to recognize and avoid degenerate steps in the simplex method, we have developed a new Phase I algorithm that is completely impervious to degeneracy, with strict improvement attained at each iteration. It is also noted that the new Phase I algorithm is closely related to a number of existing algorithms. When tested on the 30 smallest NETLIB linear programming test problems, the computational results for the new Phase I algorithm were almost 3.5 times faster than the simplex method; on some problems, it was over 10 times faster.
Lytro camera technology: theory, algorithms, performance analysis
NASA Astrophysics Data System (ADS)
Georgiev, Todor; Yu, Zhan; Lumsdaine, Andrew; Goma, Sergio
2013-03-01
The Lytro camera is the first implementation of a plenoptic camera for the consumer market. We consider it a successful example of the miniaturization aided by the increase in computational power characterizing mobile computational photography. The plenoptic camera approach to radiance capture uses a microlens array as an imaging system focused on the focal plane of the main camera lens. This paper analyzes the performance of Lytro camera from a system level perspective, considering the Lytro camera as a black box, and uses our interpretation of Lytro image data saved by the camera. We present our findings based on our interpretation of Lytro camera file structure, image calibration and image rendering; in this context, artifacts and final image resolution are discussed.
Artificial Astrocytes Improve Neural Network Performance
Porto-Pazos, Ana B.; Veiguela, Noha; Mesejo, Pablo; Navarrete, Marta; Alvarellos, Alberto; Ibáñez, Oscar; Pazos, Alejandro; Araque, Alfonso
2011-01-01
Compelling evidence indicates the existence of bidirectional communication between astrocytes and neurons. Astrocytes, a type of glial cells classically considered to be passive supportive cells, have been recently demonstrated to be actively involved in the processing and regulation of synaptic information, suggesting that brain function arises from the activity of neuron-glia networks. However, the actual impact of astrocytes in neural network function is largely unknown and its application in artificial intelligence remains untested. We have investigated the consequences of including artificial astrocytes, which present the biologically defined properties involved in astrocyte-neuron communication, on artificial neural network performance. Using connectionist systems and evolutionary algorithms, we have compared the performance of artificial neural networks (NN) and artificial neuron-glia networks (NGN) to solve classification problems. We show that the degree of success of NGN is superior to NN. Analysis of performances of NN with different number of neurons or different architectures indicate that the effects of NGN cannot be accounted for an increased number of network elements, but rather they are specifically due to astrocytes. Furthermore, the relative efficacy of NGN vs. NN increases as the complexity of the network increases. These results indicate that artificial astrocytes improve neural network performance, and established the concept of Artificial Neuron-Glia Networks, which represents a novel concept in Artificial Intelligence with implications in computational science as well as in the understanding of brain function. PMID:21526157
Artificial astrocytes improve neural network performance.
Porto-Pazos, Ana B; Veiguela, Noha; Mesejo, Pablo; Navarrete, Marta; Alvarellos, Alberto; Ibáñez, Oscar; Pazos, Alejandro; Araque, Alfonso
2011-01-01
Compelling evidence indicates the existence of bidirectional communication between astrocytes and neurons. Astrocytes, a type of glial cells classically considered to be passive supportive cells, have been recently demonstrated to be actively involved in the processing and regulation of synaptic information, suggesting that brain function arises from the activity of neuron-glia networks. However, the actual impact of astrocytes in neural network function is largely unknown and its application in artificial intelligence remains untested. We have investigated the consequences of including artificial astrocytes, which present the biologically defined properties involved in astrocyte-neuron communication, on artificial neural network performance. Using connectionist systems and evolutionary algorithms, we have compared the performance of artificial neural networks (NN) and artificial neuron-glia networks (NGN) to solve classification problems. We show that the degree of success of NGN is superior to NN. Analysis of performances of NN with different number of neurons or different architectures indicate that the effects of NGN cannot be accounted for an increased number of network elements, but rather they are specifically due to astrocytes. Furthermore, the relative efficacy of NGN vs. NN increases as the complexity of the network increases. These results indicate that artificial astrocytes improve neural network performance, and established the concept of Artificial Neuron-Glia Networks, which represents a novel concept in Artificial Intelligence with implications in computational science as well as in the understanding of brain function. PMID:21526157
NASA Technical Reports Server (NTRS)
Lawton, Pat
2004-01-01
The objective of this work was to support the design of improved IUE NEWSIPS high dispersion extraction algorithms. The purpose of this work was to evaluate use of the Linearized Image (LIHI) file versus the Re-Sampled Image (SIHI) file, evaluate various extraction, and design algorithms for evaluation of IUE High Dispersion spectra. It was concluded the use of the Re-Sampled Image (SIHI) file was acceptable. Since the Gaussian profile worked well for the core and the Lorentzian profile worked well for the wings, the Voigt profile was chosen for use in the extraction algorithm. It was found that the gamma and sigma parameters varied significantly across the detector, so gamma and sigma masks for the SWP detector were developed. Extraction code was written.
Algorithmic improvements to an exact region-filling technique
NASA Astrophysics Data System (ADS)
Elias Fabris, Antonio; Ramos Batista, Valério
2015-09-01
We present many algorithmic improvements in our early region filling technique, which in a previous publication was already proved to be correct for all connected digital pictures. Ours is an integer-only method that also finds all interior points of any given digital picture by displaying and storing them in a locating matrix. Our filling/locating program is applicable both in computer graphics and image processing.
Flipperons for Improved Aerodynamic Performance
NASA Technical Reports Server (NTRS)
Mabe, James H.
2008-01-01
Lightweight, piezoelectrically actuated bending flight-control surfaces have shown promise as means of actively controlling airflows to improve the performances of transport airplanes. These bending flight-control surfaces are called flipperons because they look somewhat like small ailerons, but, unlike ailerons, are operated in an oscillatory mode reminiscent of the actions of biological flippers. The underlying concept of using flipperons and other flipperlike actuators to impart desired characteristics to flows is not new. Moreover, elements of flipperon-based active flow-control (AFC) systems for aircraft had been developed previously, but it was not until the development reported here that the elements have been integrated into a complete, controllable prototype AFC system for wind-tunnel testing to enable evaluation of the benefits of AFC for aircraft. The piezoelectric actuator materials chosen for use in the flipperons are single- crystal solid solutions of lead zinc niobate and lead titanate, denoted generically by the empirical formula (1-x)[Pb(Zn(1/3)Nb(2/3))O3]:x[PbTiO3] (where x<1) and popularly denoted by the abbreviation PZN-PT. These are relatively newly recognized piezoelectric materials that are capable of strain levels exceeding 1 percent and strain-energy densities 5 times greater than those of previously commercially available piezoelectric materials. Despite their high performance levels, (1-x)[Pb(Zn(1/3)Nb(2/3))O3]:x[PbTiO3] materials have found limited use until now because, relative to previously commercially available piezoelectric materials, they tend to be much more fragile.
NASA Astrophysics Data System (ADS)
Das, B.; Wilson, M.; Divakarla, M. G.; Chen, W.; Barnet, C.; Wolf, W.
2013-05-01
Algorithm Development Library (ADL) is a framework that mimics the operational system IDPS (Interface Data Processing Segment) that is currently being used to process data from instruments aboard Suomi National Polar-orbiting Partnership (S-NPP) satellite. The satellite was launched successfully in October 2011. The Cross-track Infrared and Microwave Sounder Suite (CrIMSS) consists of the Advanced Technology Microwave Sounder (ATMS) and Cross-track Infrared Sounder (CrIS) instruments that are on-board of S-NPP. These instruments will also be on-board of JPSS (Joint Polar Satellite System) that will be launched in early 2017. The primary products of the CrIMSS Environmental Data Record (EDR) include global atmospheric vertical temperature, moisture, and pressure profiles (AVTP, AVMP and AVPP) and Ozone IP (Intermediate Product from CrIS radiances). Several algorithm updates have recently been proposed by CrIMSS scientists that include fixes to the handling of forward modeling errors, a more conservative identification of clear scenes, indexing corrections for daytime products, and relaxed constraints between surface temperature and air temperature for daytime land scenes. We have integrated these improvements into the ADL framework. This work compares the results from ADL emulation of future IDPS system incorporating all the suggested algorithm updates with the current official processing results by qualitative and quantitative evaluations. The results prove these algorithm updates improve science product quality.
Reconstruction algorithm improving the spatial resolution of Micro-CT
NASA Astrophysics Data System (ADS)
Fu, Jian; Wei, Dongbo; Li, Bing; Zhang, Lei
2008-03-01
X-ray Micro computed tomography (Micro-CT) enables nondestructive visualization of the internal structure of objects with high-resolution images and plays an important role for industrial nondestructive testing, material evaluation and medical researches. Because the micro focus is much smaller than the ordinary focus, the geometry un-sharpness of Micro-CT projection is several decuples less than that of ordinary CT systems. So the scan conditions with high geometry magnification can be adopted to acquire the projection data with high sampling frequency. Based on this feature, a new filter back projection reconstruction algorithm is researched to improve the spatial resolution of Micro-CT. This algorithm permits the reconstruction center at any point on the line connecting the focus and the rotation center. It can reconstruct CT images with different geometry magnification by adjusting the position of the reconstruction center. So it can make the best of the above feature to improve the spatial resolution of Micro-CT. The computer simulation and the CT experiment of a special spatial resolution phantom are executed to check the validity of this method. The results demonstrate the effect of the new algorithm. Analysis shows that the spatial resolution can be improved 50%.
Segmentation of MRI Brain Images with an Improved Harmony Searching Algorithm.
Yang, Zhang; Shufan, Ye; Li, Guo; Weifeng, Ding
2016-01-01
The harmony searching (HS) algorithm is a kind of optimization search algorithm currently applied in many practical problems. The HS algorithm constantly revises variables in the harmony database and the probability of different values that can be used to complete iteration convergence to achieve the optimal effect. Accordingly, this study proposed a modified algorithm to improve the efficiency of the algorithm. First, a rough set algorithm was employed to improve the convergence and accuracy of the HS algorithm. Then, the optimal value was obtained using the improved HS algorithm. The optimal value of convergence was employed as the initial value of the fuzzy clustering algorithm for segmenting magnetic resonance imaging (MRI) brain images. Experimental results showed that the improved HS algorithm attained better convergence and more accurate results than those of the original HS algorithm. In our study, the MRI image segmentation effect of the improved algorithm was superior to that of the original fuzzy clustering method. PMID:27403428
Segmentation of MRI Brain Images with an Improved Harmony Searching Algorithm
Yang, Zhang; Li, Guo; Weifeng, Ding
2016-01-01
The harmony searching (HS) algorithm is a kind of optimization search algorithm currently applied in many practical problems. The HS algorithm constantly revises variables in the harmony database and the probability of different values that can be used to complete iteration convergence to achieve the optimal effect. Accordingly, this study proposed a modified algorithm to improve the efficiency of the algorithm. First, a rough set algorithm was employed to improve the convergence and accuracy of the HS algorithm. Then, the optimal value was obtained using the improved HS algorithm. The optimal value of convergence was employed as the initial value of the fuzzy clustering algorithm for segmenting magnetic resonance imaging (MRI) brain images. Experimental results showed that the improved HS algorithm attained better convergence and more accurate results than those of the original HS algorithm. In our study, the MRI image segmentation effect of the improved algorithm was superior to that of the original fuzzy clustering method. PMID:27403428
NASA Astrophysics Data System (ADS)
Goswami, D.; Chakraborty, S.
2014-11-01
Laser machining is a promising non-contact process for effective machining of difficult-to-process advanced engineering materials. Increasing interest in the use of lasers for various machining operations can be attributed to its several unique advantages, like high productivity, non-contact processing, elimination of finishing operations, adaptability to automation, reduced processing cost, improved product quality, greater material utilization, minimum heat-affected zone and green manufacturing. To achieve the best desired machining performance and high quality characteristics of the machined components, it is extremely important to determine the optimal values of the laser machining process parameters. In this paper, fireworks algorithm and cuckoo search (CS) algorithm are applied for single as well as multi-response optimization of two laser machining processes. It is observed that although almost similar solutions are obtained for both these algorithms, CS algorithm outperforms fireworks algorithm with respect to average computation time, convergence rate and performance consistency.
Hu, Ruiqiang; Li, Chengwei
2015-01-01
Automated closed-loop insulin infusion therapy has been studied for many years. In closed-loop system, the control algorithm is the key technique of precise insulin infusion. The control algorithm needs to be designed and validated. In this paper, an improved PID algorithm based on insulin-on-board estimate is proposed and computer simulations are done using a combinational mathematical model of the dynamics of blood glucose-insulin regulation in the blood system. The simulation results demonstrate that the improved PID algorithm can perform well in different carbohydrate ingestion and different insulin sensitivity situations. Compared with the traditional PID algorithm, the control performance is improved obviously and hypoglycemia can be avoided. To verify the effectiveness of the proposed control algorithm, in silico testing is done using the UVa/Padova virtual patient software. PMID:26550021
NASA Astrophysics Data System (ADS)
Hu, Hongda; Shu, Hong
2015-05-01
Heavy computation limits the use of Kriging interpolation methods in many real-time applications, especially with the ever-increasing problem size. Many researchers have realized that parallel processing techniques are critical to fully exploit computational resources and feasibly solve computation-intensive problems like Kriging. Much research has addressed the parallelization of traditional approach to Kriging, but this computation-intensive procedure may not be suitable for high-resolution interpolation of spatial data. On the basis of a more effective serial approach, we propose an improved coarse-grained parallel algorithm to accelerate ordinary Kriging interpolation. In particular, the interpolation task of each unobserved point is considered as a basic parallel unit. To reduce time complexity and memory consumption, the large right hand side matrix in the Kriging linear system is transformed and fixed at only two columns and therefore no longer directly relevant to the number of unobserved points. The MPI (Message Passing Interface) model is employed to implement our parallel programs in a homogeneous distributed memory system. Experimentally, the improved parallel algorithm performs better than the traditional one in spatial interpolation of annual average precipitation in Victoria, Australia. For example, when the number of processors is 24, the improved algorithm keeps speed-up at 20.8 while the speed-up of the traditional algorithm only reaches 9.3. Likewise, the weak scaling efficiency of the improved algorithm is nearly 90% while that of the traditional algorithm almost drops to 40% with 16 processors. Experimental results also demonstrate that the performance of the improved algorithm is enhanced by increasing the problem size.
Terra, Ricardo Mingarini; Waisberg, Daniel Reis; de Almeida, José Luiz Jesus; Devido, Marcela Santana; Pêgo-Fernandes, Paulo Manuel; Jatene, Fabio Biscegli
2012-01-01
OBJECTIVE: We aimed to evaluate whether the inclusion of videothoracoscopy in a pleural empyema treatment algorithm would change the clinical outcome of such patients. METHODS: This study performed quality-improvement research. We conducted a retrospective review of patients who underwent pleural decortication for pleural empyema at our institution from 2002 to 2008. With the old algorithm (January 2002 to September 2005), open decortication was the procedure of choice, and videothoracoscopy was only performed in certain sporadic mid-stage cases. With the new algorithm (October 2005 to December 2008), videothoracoscopy became the first-line treatment option, whereas open decortication was only performed in patients with a thick pleural peel (>2 cm) observed by chest scan. The patients were divided into an old algorithm (n = 93) and new algorithm (n = 113) group and compared. The main outcome variables assessed included treatment failure (pleural space reintervention or death up to 60 days after medical discharge) and the occurrence of complications. RESULTS: Videothoracoscopy and open decortication were performed in 13 and 80 patients from the old algorithm group and in 81 and 32 patients from the new algorithm group, respectively (p<0.01). The patients in the new algorithm group were older (41±1 vs. 46.3±16.7 years, p = 0.014) and had higher Charlson Comorbidity Index scores [0(0-3) vs. 2(0-4), p = 0.032]. The occurrence of treatment failure was similar in both groups (19.35% vs. 24.77%, p = 0.35), although the complication rate was lower in the new algorithm group (48.3% vs. 33.6%, p = 0.04). CONCLUSIONS: The wider use of videothoracoscopy in pleural empyema treatment was associated with fewer complications and unaltered rates of mortality and reoperation even though more severely ill patients were subjected to videothoracoscopic surgery. PMID:22760892
Improved Reversible Jump Algorithms for Bayesian Species Delimitation
Rannala, Bruce; Yang, Ziheng
2013-01-01
Several computational methods have recently been proposed for delimiting species using multilocus sequence data. Among them, the Bayesian method of Yang and Rannala uses the multispecies coalescent model in the likelihood framework to calculate the posterior probabilities for the different species-delimitation models. It has a sound statistical basis and is found to have nice statistical properties in simulation studies, such as low error rates of undersplitting and oversplitting. However, the method suffers from poor mixing of the reversible-jump Markov chain Monte Carlo (rjMCMC) algorithms. Here, we describe several modifications to the algorithms. We propose a flexible prior that allows the user to specify the probability that each node on the guide tree represents a true speciation event. We also introduce modifications to the rjMCMC algorithms that remove the constraint on the new species divergence time when splitting and alter the gene trees to remove incompatibilities. The new algorithms are found to improve mixing of the Markov chain for both simulated and empirical data sets. PMID:23502678
Binocular self-calibration performed via adaptive genetic algorithm based on laser line imaging
NASA Astrophysics Data System (ADS)
Apolinar Muñoz Rodríguez, J.; Mejía Alanís, Francisco Carlos
2016-07-01
An accurate technique to perform binocular self-calibration by means of an adaptive genetic algorithm based on a laser line is presented. In this calibration, the genetic algorithm computes the vision parameters through simulated binary crossover (SBX). To carry it out, the genetic algorithm constructs an objective function from the binocular geometry of the laser line projection. Then, the SBX minimizes the objective function via chromosomes recombination. In this algorithm, the adaptive procedure determines the search space via line position to obtain the minimum convergence. Thus, the chromosomes of vision parameters provide the minimization. The approach of the proposed adaptive genetic algorithm is to calibrate and recalibrate the binocular setup without references and physical measurements. This procedure leads to improve the traditional genetic algorithms, which calibrate the vision parameters by means of references and an unknown search space. It is because the proposed adaptive algorithm avoids errors produced by the missing of references. Additionally, the three-dimensional vision is carried out based on the laser line position and vision parameters. The contribution of the proposed algorithm is corroborated by an evaluation of accuracy of binocular calibration, which is performed via traditional genetic algorithms.
Recent ATR and fusion algorithm improvements for multiband sonar imagery
NASA Astrophysics Data System (ADS)
Aridgides, Tom; Fernández, Manuel
2009-05-01
An improved automatic target recognition processing string has been developed. The overall processing string consists of pre-processing, subimage adaptive clutter filtering, normalization, detection, data regularization, feature extraction, optimal subset feature selection, feature orthogonalization and classification processing blocks. The objects that are classified by the 3 distinct ATR strings are fused using the classification confidence values and their expansions as features, and using "summing" or log-likelihood-ratio-test (LLRT) based fusion rules. The utility of the overall processing strings and their fusion was demonstrated with new high-resolution three-frequency band sonar imagery. The ATR processing strings were individually tuned to the corresponding three-frequency band data, making use of the new processing improvement, data regularization; this improvement entails computing the input data mean, clipping the data to a multiple of its mean and scaling it, prior to feature extraction and resulted in a 3:1 reduction in false alarms. Two significant fusion algorithm improvements were made. First, a nonlinear exponential Box-Cox expansion (consisting of raising data to a to-be-determined power) feature LLRT fusion algorithm was developed. Second, a repeated application of a subset Box-Cox feature selection / feature orthogonalization / LLRT fusion block was utilized. It was shown that cascaded Box-Cox feature LLRT fusion of the ATR processing strings outperforms baseline "summing" and single-stage Box-Cox feature LLRT algorithms, yielding significant improvements over the best single ATR processing string results, and providing the capability to correctly call the majority of targets while maintaining a very low false alarm rate.
On improving linear solver performance: a block variant of GMRES
Baker, A H; Dennis, J M; Jessup, E R
2004-05-10
The increasing gap between processor performance and memory access time warrants the re-examination of data movement in iterative linear solver algorithms. For this reason, we explore and establish the feasibility of modifying a standard iterative linear solver algorithm in a manner that reduces the movement of data through memory. In particular, we present an alternative to the restarted GMRES algorithm for solving a single right-hand side linear system Ax = b based on solving the block linear system AX = B. Algorithm performance, i.e. time to solution, is improved by using the matrix A in operations on groups of vectors. Experimental results demonstrate the importance of implementation choices on data movement as well as the effectiveness of the new method on a variety of problems from different application areas.
Kidney segmentation in CT sequences using SKFCM and improved GrowCut algorithm
2015-01-01
Background Organ segmentation is an important step in computer-aided diagnosis and pathology detection. Accurate kidney segmentation in abdominal computed tomography (CT) sequences is an essential and crucial task for surgical planning and navigation in kidney tumor ablation. However, kidney segmentation in CT is a substantially challenging work because the intensity values of kidney parenchyma are similar to those of adjacent structures. Results In this paper, a coarse-to-fine method was applied to segment kidney from CT images, which consists two stages including rough segmentation and refined segmentation. The rough segmentation is based on a kernel fuzzy C-means algorithm with spatial information (SKFCM) algorithm and the refined segmentation is implemented with improved GrowCut (IGC) algorithm. The SKFCM algorithm introduces a kernel function and spatial constraint into fuzzy c-means clustering (FCM) algorithm. The IGC algorithm makes good use of the continuity of CT sequences in space which can automatically generate the seed labels and improve the efficiency of segmentation. The experimental results performed on the whole dataset of abdominal CT images have shown that the proposed method is accurate and efficient. The method provides a sensitivity of 95.46% with specificity of 99.82% and performs better than other related methods. Conclusions Our method achieves high accuracy in kidney segmentation and considerably reduces the time and labor required for contour delineation. In addition, the method can be expanded to 3D segmentation directly without modification. PMID:26356850
Logit Model based Performance Analysis of an Optimization Algorithm
NASA Astrophysics Data System (ADS)
Hernández, J. A.; Ospina, J. D.; Villada, D.
2011-09-01
In this paper, the performance of the Multi Dynamics Algorithm for Global Optimization (MAGO) is studied through simulation using five standard test functions. To guarantee that the algorithm converges to a global optimum, a set of experiments searching for the best combination between the only two MAGO parameters -number of iterations and number of potential solutions, are considered. These parameters are sequentially varied, while increasing the dimension of several test functions, and performance curves were obtained. The MAGO was originally designed to perform well with small populations; therefore, the self-adaptation task with small populations is more challenging while the problem dimension is higher. The results showed that the convergence probability to an optimal solution increases according to growing patterns of the number of iterations and the number of potential solutions. However, the success rates slow down when the dimension of the problem escalates. Logit Model is used to determine the mutual effects between the parameters of the algorithm.
Protein sequence classification with improved extreme learning machine algorithms.
Cao, Jiuwen; Xiong, Lianglin
2014-01-01
Precisely classifying a protein sequence from a large biological protein sequences database plays an important role for developing competitive pharmacological products. Comparing the unseen sequence with all the identified protein sequences and returning the category index with the highest similarity scored protein, conventional methods are usually time-consuming. Therefore, it is urgent and necessary to build an efficient protein sequence classification system. In this paper, we study the performance of protein sequence classification using SLFNs. The recent efficient extreme learning machine (ELM) and its invariants are utilized as the training algorithms. The optimal pruned ELM is first employed for protein sequence classification in this paper. To further enhance the performance, the ensemble based SLFNs structure is constructed where multiple SLFNs with the same number of hidden nodes and the same activation function are used as ensembles. For each ensemble, the same training algorithm is adopted. The final category index is derived using the majority voting method. Two approaches, namely, the basic ELM and the OP-ELM, are adopted for the ensemble based SLFNs. The performance is analyzed and compared with several existing methods using datasets obtained from the Protein Information Resource center. The experimental results show the priority of the proposed algorithms. PMID:24795876
An improved piecewise linear chaotic map based image encryption algorithm.
Hu, Yuping; Zhu, Congxu; Wang, Zhijian
2014-01-01
An image encryption algorithm based on improved piecewise linear chaotic map (MPWLCM) model was proposed. The algorithm uses the MPWLCM to permute and diffuse plain image simultaneously. Due to the sensitivity to initial key values, system parameters, and ergodicity in chaotic system, two pseudorandom sequences are designed and used in the processes of permutation and diffusion. The order of processing pixels is not in accordance with the index of pixels, but it is from beginning or end alternately. The cipher feedback was introduced in diffusion process. Test results and security analysis show that not only the scheme can achieve good encryption results but also its key space is large enough to resist against brute attack. PMID:24592159
An Improved Piecewise Linear Chaotic Map Based Image Encryption Algorithm
Hu, Yuping; Wang, Zhijian
2014-01-01
An image encryption algorithm based on improved piecewise linear chaotic map (MPWLCM) model was proposed. The algorithm uses the MPWLCM to permute and diffuse plain image simultaneously. Due to the sensitivity to initial key values, system parameters, and ergodicity in chaotic system, two pseudorandom sequences are designed and used in the processes of permutation and diffusion. The order of processing pixels is not in accordance with the index of pixels, but it is from beginning or end alternately. The cipher feedback was introduced in diffusion process. Test results and security analysis show that not only the scheme can achieve good encryption results but also its key space is large enough to resist against brute attack. PMID:24592159
Preliminary flight evaluation of an engine performance optimization algorithm
NASA Technical Reports Server (NTRS)
Lambert, H. H.; Gilyard, G. B.; Chisholm, J. D.; Kerr, L. J.
1991-01-01
A performance seeking control (PSC) algorithm has undergone initial flight test evaluation in subsonic operation of a PW 1128 engined F-15. This algorithm is designed to optimize the quasi-steady performance of an engine for three primary modes: (1) minimum fuel consumption; (2) minimum fan turbine inlet temperature (FTIT); and (3) maximum thrust. The flight test results have verified a thrust specific fuel consumption reduction of 1 pct., up to 100 R decreases in FTIT, and increases of as much as 12 pct. in maximum thrust. PSC technology promises to be of value in next generation tactical and transport aircraft.
Improving Performance in a Nuclear Cardiology Department
ERIC Educational Resources Information Center
LaFleur, Doug; Smalley, Karolyn; Austin, John
2005-01-01
Improving performance in the medical industry is an area that is ideally suited for the tools advocated by the International Society of Performance Improvement (ISPI). This paper describes an application of the tools that have been developed by Dale Brethower and Geary Rummler, two pillars of the performance improvement industry. It allows the…
Improvement of Passive Microwave Rainfall Retrieval Algorithm over Mountainous Terrain
NASA Astrophysics Data System (ADS)
Shige, S.; Yamamoto, M.
2015-12-01
The microwave radiometer (MWR) algorithms underestimate heavy rainfall associated with shallow orographic rainfall systems owing to weak ice scattering signatures. Underestimation of the Global Satellite Mapping of Precipitation (GSMaP) MWR has been mitigated by an orographic/nonorographic rainfall classification scheme (Shige et al. 2013, 2015; Taniguchi et al. 2013; Yamamoto and Shige 2015). The orographic/nonorographic rainfall classification scheme is developed on the basis of orographically forced upward vertical motion and the convergence of surface moisture flux estimated from ancillary data. Lookup tables derived from orographic precipitation profiles are used to estimate rainfall for an orographic rainfall pixel, whereas those derived from original precipitation profiles are used to estimate rainfall for a nonorographic rainfall pixel. The orographic/nonorographic rainfall classification scheme has been used by the version of GSMaP products, which are available in near real time (about 4 h after observation) via the Internet (http://sharaku.eorc.jaxa.jp/GSMaP/index.htm). The current version of GSMaP MWR algorithm with the orographic/nonorographic rainfall classification scheme improves rainfall estimation over the entire tropical region, but there is still room for improvement. In this talk, further improvement of orographic rainfall retrievals will be shown.
NASA Technical Reports Server (NTRS)
Zhou, Yaping; Kratz, David P.; Wilber, Anne C.; Gupta, Shashi K.; Cess, Robert D.
2006-01-01
Retrieving surface longwave radiation from space has been a difficult task since the surface downwelling longwave radiation (SDLW) are integrations from radiation emitted by the entire atmosphere, while those emitted from the upper atmosphere are absorbed before reaching the surface. It is particularly problematic when thick clouds are present since thick clouds will virtually block all the longwave radiation from above, while satellites observe atmosphere emissions mostly from above the clouds. Zhou and Cess developed an algorithm for retrieving SDLW based upon detailed studies using radiative transfer model calculations and surface radiometric measurements. Their algorithm linked clear sky SDLW with surface upwelling longwave flux and column precipitable water vapor. For cloudy sky cases, they used cloud liquid water path as an additional parameter to account for the effects of clouds. Despite the simplicity of their algorithm, it performed very well for most geographical regions except for those regions where the atmospheric conditions near the surface tend to be extremely cold and dry. Systematic errors were also found for areas that were covered with ice clouds. An improved version of the algorithm was developed that prevents the large errors in the SDLW at low water vapor amounts. The new algorithm also utilizes cloud fraction and cloud liquid and ice water paths measured from the Cloud and the Earth's Radiant Energy System (CERES) satellites to separately compute the clear and cloudy portions of the fluxes. The new algorithm has been validated against surface measurements at 29 stations around the globe for the Terra and Aqua satellites. The results show significant improvement over the original version. The revised Zhou-Cess algorithm is also slightly better or comparable to more sophisticated algorithms currently implemented in the CERES processing. It will be incorporated in the CERES project as one of the empirical surface radiation algorithms.
Performance Pay Path to Improvement
ERIC Educational Resources Information Center
Gratz, Donald B.
2011-01-01
The primary goal of performance pay for the past decade has been higher test scores, and the most prominent strategy has been to increase teacher performance through financial incentives. If teachers are rewarded for success, according to this logic, they will try harder. If they try harder, more children will achieve higher test scores. The…
An improved sink particle algorithm for SPH simulations
NASA Astrophysics Data System (ADS)
Hubber, D. A.; Walch, S.; Whitworth, A. P.
2013-04-01
Numerical simulations of star formation frequently rely on the implementation of sink particles: (a) to avoid expending computational resource on the detailed internal physics of individual collapsing protostars, (b) to derive mass functions, binary statistics and clustering kinematics (and hence to make comparisons with observation), and (c) to model radiative and mechanical feedback; sink particles are also used in other contexts, for example to represent accreting black holes in galactic nuclei. We present a new algorithm for creating and evolving sink particles in smoothed particle hydrodynamic (SPH) simulations, which appears to represent a significant improvement over existing algorithms - particularly in situations where sinks are introduced after the gas has become optically thick to its own cooling radiation and started to heat up by adiabatic compression. (i) It avoids spurious creation of sinks. (ii) It regulates the accretion of matter on to a sink so as to mitigate non-physical perturbations in the vicinity of the sink. (iii) Sinks accrete matter, but the associated angular momentum is transferred back to the surrounding medium. With the new algorithm - and modulo the need to invoke sufficient resolution to capture the physics preceding sink formation - the properties of sinks formed in simulations are essentially independent of the user-defined parameters of sink creation, or the number of SPH particles used.
An improved Richardson-Lucy algorithm based on local prior
NASA Astrophysics Data System (ADS)
Yongpan, Wang; Huajun, Feng; Zhihai, Xu; Qi, Li; Chaoyue, Dai
2010-07-01
Ringing is one of the most common disturbing artifacts in image deconvolution. With a totally known kernel, the standard Richardson-Lucy (RL) algorithm succeeds in many motion deblurring processes, but the resulting images still contain visible ringing. When the estimated kernel is different from the real one, the result of the standard RL iterative algorithm will be worse. To suppress the ringing artifacts caused by failures in the blur kernel estimation, this paper improves the RL algorithm based on the local prior. Firstly, the standard deviation of pixels in the local window is computed to find the smooth region and the image gradient in the region is constrained to make its distribution consistent with the deblurring image gradient. Secondly, in order to suppress the ringing near the edge of a rigid body in the image, a new mask was obtained by computing the sharp edge of the image produced using the first step. If the kernel is large-scale, where the foreground is rigid and the background is smoothing, this step could produce a significant inhibitory effect on ringing artifacts. Thirdly, the boundary constraint is strengthened if the boundary is relatively smooth. As a result of the steps above, high-quality deblurred images can be obtained even when the estimated kernels are not perfectly accurate. On the basis of blurred images and the related kernel information taken by the additional hardware, our approach proved to be effective.
An improved algorithm of fiber tractography demonstrates postischemic cerebral reorganization
NASA Astrophysics Data System (ADS)
Liu, Xiao-dong; Lu, Jie; Yao, Li; Li, Kun-cheng; Zhao, Xiao-jie
2008-03-01
In vivo white matter tractography by diffusion tensor imaging (DTI) accurately represents the organizational architecture of white matter in the vicinity of brain lesions and especially ischemic brain. In this study, we suggested an improved fiber tracking algorithm based on TEND, called TENDAS, for tensor deflection with adaptive stepping, which had been introduced a stepping framework for interpreting the algorithm behavior as a function of the tensor shape (linear-shaped or not) and tract history. The propagation direction at each step was given by the deflection vector. TENDAS tractography was used to examine a 17-year-old recovery patient with congenital right hemisphere artery stenosis combining with fMRI. Meaningless picture location was used as spatial working memory task in this study. We detected the shifted functional localization to the contralateral homotypic cortex and more prominent and extensive left-sided parietal and medial frontal cortical activations which were used directly as seed mask for tractography for the reconstruction of individual spatial parietal pathways. Comparing with the TEND algorithms, TENDAS shows smoother and less sharp bending characterization of white matter architecture of the parietal cortex. The results of this preliminary study were twofold. First, TENDAS may provide more adaptability and accuracy in reconstructing certain anatomical features, whereas it is very difficult to verify tractography maps of white matter connectivity in the living human brain. Second, our study indicates that combination of TENDAS and fMRI provide a unique image of functional cortical reorganization and structural modifications of postischemic spatial working memory.
Spatial Modulation Improves Performance in CTIS
NASA Technical Reports Server (NTRS)
Bearman, Gregory H.; Wilson, Daniel W.; Johnson, William R.
2009-01-01
Suitably formulated spatial modulation of a scene imaged by a computed-tomography imaging spectrometer (CTIS) has been found to be useful as a means of improving the imaging performance of the CTIS. As used here, "spatial modulation" signifies the imposition of additional, artificial structure on a scene from within the CTIS optics. The basic principles of a CTIS were described in "Improvements in Computed- Tomography Imaging Spectrometry" (NPO-20561) NASA Tech Briefs, Vol. 24, No. 12 (December 2000), page 38 and "All-Reflective Computed-Tomography Imaging Spectrometers" (NPO-20836), NASA Tech Briefs, Vol. 26, No. 11 (November 2002), page 7a. To recapitulate: A CTIS offers capabilities for imaging a scene with spatial, spectral, and temporal resolution. The spectral disperser in a CTIS is a two-dimensional diffraction grating. It is positioned between two relay lenses (or on one of two relay mirrors) in a video imaging system. If the disperser were removed, the system would produce ordinary images of the scene in its field of view. In the presence of the grating, the image on the focal plane of the system contains both spectral and spatial information because the multiple diffraction orders of the grating give rise to multiple, spectrally dispersed images of the scene. By use of algorithms adapted from computed tomography, the image on the focal plane can be processed into an image cube a three-dimensional collection of data on the image intensity as a function of the two spatial dimensions (x and y) in the scene and of wavelength (lambda). Thus, both spectrally and spatially resolved information on the scene at a given instant of time can be obtained, without scanning, from a single snapshot; this is what makes the CTIS such a potentially powerful tool for spatially, spectrally, and temporally resolved imaging. A CTIS performs poorly in imaging some types of scenes in particular, scenes that contain little spatial or spectral variation. The computed spectra of
Performance improvement. The American way.
Walker, Karen
2007-02-15
The role of a US-style 'improvement adviser' is to ensure chages are successfully implemented. They use coaching and facilitation to support project teams and are trained to overcome common obstacles. The advisers have advantages over traditional consultants, as they work with full inside knowledge of the organization and are there for the long-term. PMID:17380971
NASA Astrophysics Data System (ADS)
Zhao, Zhanlue
This dissertation consists of two parts. The first part deals with the performance appraisal of estimation algorithms. The second part focuses on the application of estimation algorithms to target tracking. Performance appraisal is crucial for understanding, developing and comparing various estimation algorithms. In particular, with the evolvement of estimation theory and the increase of problem complexity, performance appraisal is getting more and more challenging for engineers to make comprehensive conclusions. However, the existing theoretical results are inadequate for practical reference. The first part of this dissertation is dedicated to performance measures which include local performance measures, global performance measures and model distortion measure. The second part focuses on application of the recursive best linear unbiased estimation (BLUE) or linear minimum mean square error (LIB-M-ISE) estimation to nonlinear measurement problem in target tracking. Kalman filter has been the dominant basis for dynamic state filtering for several decades. Beyond Kalman filter, a more fundamental basis for the recursive best linear unbiased filtering has been thoroughly investigated in a series of papers by my advisor Dr. X. Rong Li. Based on the so-called quasi-recursive best linear unbiased filtering technique, the constraints of the Kalman filter Linear-Gaussian assumptions can be relaxed such that a general linear filtering technique for nonlinear systems can be achieved. An approximate optimal BLUE filter is implemented for nonlinear measurements in target tracking which outperforms the existing method significantly in terms of accuracy, credibility and robustness.
Jimenez, Edward Steven,
2013-09-01
The goal of this work is to develop a fast computed tomography (CT) reconstruction algorithm based on graphics processing units (GPU) that achieves significant improvement over traditional central processing unit (CPU) based implementations. The main challenge in developing a CT algorithm that is capable of handling very large datasets is parallelizing the algorithm in such a way that data transfer does not hinder performance of the reconstruction algorithm. General Purpose Graphics Processing (GPGPU) is a new technology that the Science and Technology (S&T) community is starting to adopt in many fields where CPU-based computing is the norm. GPGPU programming requires a new approach to algorithm development that utilizes massively multi-threaded environments. Multi-threaded algorithms in general are difficult to optimize since performance bottlenecks occur that are non-existent in single-threaded algorithms such as memory latencies. If an efficient GPU-based CT reconstruction algorithm can be developed; computational times could be improved by a factor of 20. Additionally, cost benefits will be realized as commodity graphics hardware could potentially replace expensive supercomputers and high-end workstations. This project will take advantage of the CUDA programming environment and attempt to parallelize the task in such a way that multiple slices of the reconstruction volume are computed simultaneously. This work will also take advantage of the GPU memory by utilizing asynchronous memory transfers, GPU texture memory, and (when possible) pinned host memory so that the memory transfer bottleneck inherent to GPGPU is amortized. Additionally, this work will take advantage of GPU-specific hardware (i.e. fast texture memory, pixel-pipelines, hardware interpolators, and varying memory hierarchy) that will allow for additional performance improvements.
Impact of Multiscale Retinex Computation on Performance of Segmentation Algorithms
NASA Technical Reports Server (NTRS)
Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.; Hines, Glenn D.
2004-01-01
Classical segmentation algorithms subdivide an image into its constituent components based upon some metric that defines commonality between pixels. Often, these metrics incorporate some measure of "activity" in the scene, e.g. the amount of detail that is in a region. The Multiscale Retinex with Color Restoration (MSRCR) is a general purpose, non-linear image enhancement algorithm that significantly affects the brightness, contrast and sharpness within an image. In this paper, we will analyze the impact the MSRCR has on segmentation results and performance.
Multi-expert tracking algorithm based on improved compressive tracker
NASA Astrophysics Data System (ADS)
Feng, Yachun; Zhang, Hong; Yuan, Ding
2015-12-01
Object tracking is a challenging task in computer vision. Most state-of-the-art methods maintain an object model and update the object model by using new examples obtained incoming frames in order to deal with the variation in the appearance. It will inevitably introduce the model drift problem into the object model updating frame-by-frame without any censorship mechanism. In this paper, we adopt a multi-expert tracking framework, which is able to correct the effect of bad updates after they happened such as the bad updates caused by the severe occlusion. Hence, the proposed framework exactly has the ability which a robust tracking method should process. The expert ensemble is constructed of a base tracker and its formal snapshot. The tracking result is produced by the current tracker that is selected by means of a simple loss function. We adopt an improved compressive tracker as the base tracker in our work and modify it to fit the multi-expert framework. The proposed multi-expert tracking algorithm significantly improves the robustness of the base tracker, especially in the scenes with frequent occlusions and illumination variations. Experiments on challenging video sequences with comparisons to several state-of-the-art trackers demonstrate the effectiveness of our method and our tracking algorithm can run at real-time.
Improving synthetical stellar libraries using the cross-entropy algorithm
NASA Astrophysics Data System (ADS)
Martins, L. P.; Vitoriano, R.; Coelho, P.; Caproni, A.
Stellar libraries are fundamental tools for the study of stellar populations since they are one of the fundamental ingredients for stellar population synthesis codes. We have implemented an innovative method to perform the calibration of atomic line lists used to generate the synthetic spectra of theoretical libraries, much more robust and efficient than the methods so far used. Here we present the adaptation and validation of this method, called Cross-Entropy algorithm, to the calibration of atomic line list. We show that the method is extremely efficient for calibration of atomic line lists when the transition contributes with at least 10^{-4} of the continuum flux.
Improved performance in NASTRAN (R)
NASA Technical Reports Server (NTRS)
Chan, Gordon C.
1989-01-01
Three areas of improvement in COSMIC/NASTRAN, 1989 release, were incorporated recently that make the analysis program run faster on large problems. Actual log files and actual timings on a few test samples that were run on IBM, CDC, VAX, and CRAY computers were compiled. The speed improvement is proportional to the problem size and number of continuation cards. Vectorizing certain operations in BANDIT, makes BANDIT run twice as fast in some large problems using structural elements with many node points. BANDIT is a built-in NASTRAN processor that optimizes the structural matrix bandwidth. The VAX matrix packing routine BLDPK was modified so that it is now packing a column of a matrix 3 to 9 times faster. The denser and bigger the matrix, the greater is the speed improvement. This improvement makes a host of routines and modules that involve matrix operation run significantly faster, and saves disc space for dense matrices. A UNIX version, converted from 1988 COSMIC/NASTRAN, was tested successfully on a Silicon Graphics computer using the UNIX V Operating System, with Berkeley 4.3 Extensions. The Utility Modules INPUTT5 and OUTPUT5 were expanded to handle table data, as well as matrices. Both INPUTT5 and OUTPUT5 are general input/output modules that read and write FORTRAN files with or without format. More user informative messages are echoed from PARAMR, PARAMD, and SCALAR modules to ensure proper data values and data types being handled. Two new Utility Modules, GINOFILE and DATABASE, were written for the 1989 release. Seven rigid elements are added to COSMIC/NASTRAN. They are: CRROD, CRBAR, CRTRPLT, CRBE1, CRBE2, CRBE3, and CRSPLINE.
Atmospheric turbulence and sensor system effects on biometric algorithm performance
NASA Astrophysics Data System (ADS)
Espinola, Richard L.; Leonard, Kevin R.; Byrd, Kenneth A.; Potvin, Guy
2015-05-01
Biometric technologies composed of electro-optical/infrared (EO/IR) sensor systems and advanced matching algorithms are being used in various force protection/security and tactical surveillance applications. To date, most of these sensor systems have been widely used in controlled conditions with varying success (e.g., short range, uniform illumination, cooperative subjects). However the limiting conditions of such systems have yet to be fully studied for long range applications and degraded imaging environments. Biometric technologies used for long range applications will invariably suffer from the effects of atmospheric turbulence degradation. Atmospheric turbulence causes blur, distortion and intensity fluctuations that can severely degrade image quality of electro-optic and thermal imaging systems and, for the case of biometrics technology, translate to poor matching algorithm performance. In this paper, we evaluate the effects of atmospheric turbulence and sensor resolution on biometric matching algorithm performance. We use a subset of the Facial Recognition Technology (FERET) database and a commercial algorithm to analyze facial recognition performance on turbulence degraded facial images. The goal of this work is to understand the feasibility of long-range facial recognition in degraded imaging conditions, and the utility of camera parameter trade studies to enable the design of the next generation biometrics sensor systems.
Object-Oriented Performance Improvement.
ERIC Educational Resources Information Center
Douglas, Ian; Schaffer, Scott P.
2002-01-01
Describes a framework to support an object-oriented approach to performance analysis and instructional design that includes collaboration, automation, visual modeling, and reusable Web-based repositories of analysis knowledge. Relates the need for a new framework to the increasing concern with the cost effectiveness of student and employee…
On the performances of computer vision algorithms on mobile platforms
NASA Astrophysics Data System (ADS)
Battiato, S.; Farinella, G. M.; Messina, E.; Puglisi, G.; Ravì, D.; Capra, A.; Tomaselli, V.
2012-01-01
Computer Vision enables mobile devices to extract the meaning of the observed scene from the information acquired with the onboard sensor cameras. Nowadays, there is a growing interest in Computer Vision algorithms able to work on mobile platform (e.g., phone camera, point-and-shot-camera, etc.). Indeed, bringing Computer Vision capabilities on mobile devices open new opportunities in different application contexts. The implementation of vision algorithms on mobile devices is still a challenging task since these devices have poor image sensors and optics as well as limited processing power. In this paper we have considered different algorithms covering classic Computer Vision tasks: keypoint extraction, face detection, image segmentation. Several tests have been done to compare the performances of the involved mobile platforms: Nokia N900, LG Optimus One, Samsung Galaxy SII.
Performance impact of dynamic parallelism on different clustering algorithms
NASA Astrophysics Data System (ADS)
DiMarco, Jeffrey; Taufer, Michela
2013-05-01
In this paper, we aim to quantify the performance gains of dynamic parallelism. The newest version of CUDA, CUDA 5, introduces dynamic parallelism, which allows GPU threads to create new threads, without CPU intervention, and adapt to its data. This effectively eliminates the superfluous back and forth communication between the GPU and CPU through nested kernel computations. The change in performance will be measured using two well-known clustering algorithms that exhibit data dependencies: the K-means clustering and the hierarchical clustering. K-means has a sequential data dependence wherein iterations occur in a linear fashion, while the hierarchical clustering has a tree-like dependence that produces split tasks. Analyzing the performance of these data-dependent algorithms gives us a better understanding of the benefits or potential drawbacks of CUDA 5's new dynamic parallelism feature.
Madenjian, Charles P.; David, Solomon R.; Pothoven, Steven A.
2012-01-01
We evaluated the performance of the Wisconsin bioenergetics model for lake trout Salvelinus namaycush that were fed ad libitum in laboratory tanks under regimes of low activity and high activity. In addition, we compared model performance under two different model algorithms: (1) balancing the lake trout energy budget on day t based on lake trout energy density on day t and (2) balancing the lake trout energy budget on day t based on lake trout energy density on day t + 1. Results indicated that the model significantly underestimated consumption for both inactive and active lake trout when algorithm 1 was used and that the degree of underestimation was similar for the two activity levels. In contrast, model performance substantially improved when using algorithm 2, as no detectable bias was found in model predictions of consumption for inactive fish and only a slight degree of overestimation was detected for active fish. The energy budget was accurately balanced by using algorithm 2 but not by using algorithm 1. Based on the results of this study, we recommend the use of algorithm 2 to estimate food consumption by fish in the field. Our study results highlight the importance of accurately accounting for changes in fish energy density when balancing the energy budget; furthermore, these results have implications for the science of evaluating fish bioenergetics model performance and for more accurate estimation of food consumption by fish in the field when fish energy density undergoes relatively rapid changes.
Large-Scale Organizational Performance Improvement.
ERIC Educational Resources Information Center
Pilotto, Rudy; Young, Jonathan O'Donnell
1999-01-01
Describes the steps involved in a performance improvement program in the context of a large multinational corporation. Highlights include a training program for managers that explained performance improvement; performance matrices; divisionwide implementation, including strategic planning; organizationwide training of all personnel; and the…
Performance evaluation of image segmentation algorithms on microscopic image data.
Beneš, Miroslav; Zitová, Barbara
2015-01-01
In our paper, we present a performance evaluation of image segmentation algorithms on microscopic image data. In spite of the existence of many algorithms for image data partitioning, there is no universal and 'the best' method yet. Moreover, images of microscopic samples can be of various character and quality which can negatively influence the performance of image segmentation algorithms. Thus, the issue of selecting suitable method for a given set of image data is of big interest. We carried out a large number of experiments with a variety of segmentation methods to evaluate the behaviour of individual approaches on the testing set of microscopic images (cross-section images taken in three different modalities from the field of art restoration). The segmentation results were assessed by several indices used for measuring the output quality of image segmentation algorithms. In the end, the benefit of segmentation combination approach is studied and applicability of achieved results on another representatives of microscopic data category - biological samples - is shown. PMID:25233873
An improved bi-level algorithm for partitioning dynamic grid hierarchies.
Deiterding, Ralf (California Institute of Technology, Pasadena, CA); Johansson, Henrik (Uppsala University, Uppsala, Sweden); Steensland, Johan; Ray, Jaideep
2006-05-01
Structured adaptive mesh refinement methods are being widely used for computer simulations of various physical phenomena. Parallel implementations potentially offer realistic simulations of complex three-dimensional applications. But achieving good scalability for large-scale applications is non-trivial. Performance is limited by the partitioner's ability to efficiently use the underlying parallel computer's resources. Designed on sound SAMR principles, Nature+Fable is a hybrid, dedicated SAMR partitioning tool that brings together the advantages of both domain-based and patch-based techniques while avoiding their drawbacks. But the original bi-level partitioning approach in Nature+Fable is insufficient as it for realistic applications regards frequently occurring bi-levels as ''impossible'' and fails. This document describes an improved bi-level partitioning algorithm that successfully copes with all possible bi-levels. The improved algorithm uses the original approach side-by-side with a new, complementing approach. By using a new, customized classification method, the improved algorithm switches automatically between the two approaches. This document describes the algorithms, discusses implementation issues, and presents experimental results. The improved version of Nature+Fable was found to be able to handle realistic applications and also to generate less imbalances, similar box count, but more communication as compared to the native, domain-based partitioner in the SAMR framework AMROC.
An improved bi-level algorithm for partitioning dynamic structured grid hierarchies.
Deiterding, Ralf; Steensland, Johan; Ray, Jaideep
2006-02-01
Structured adaptive mesh refinement methods are being widely used for computer simulations of various physical phenomena. Parallel implementations potentially offer realistic simulations of complex three-dimensional applications. But achieving good scalability for large-scale applications is non-trivial. Performance is limited by the partitioner's ability to efficiently use the underlying parallel computer's resources. Designed on sound SAMR principles, Nature+Fable is a hybrid, dedicated SAMR partitioning tool that brings together the advantages of both domain-based and patch-based techniques while avoiding their drawbacks. But the original bi-level partitioning approach in Nature+Fable is insufficient as it for realistic applications regards frequently occurring bi-levels as 'impossible' and fails. This document describes an improved bi-level partitioning algorithm that successfully copes with all possible hi-levels. The improved algorithm uses the original approach side-by-side with a new, complementing approach. By using a new, customized classification method, the improved algorithm switches automatically between the two approaches. This document describes the algorithms, discusses implementation issues, and presents experimental results. The improved version of Nature+Fable was found to be able to handle realistic applications and also to generate less imbalances, similar box count, but more communication as compared to the native, domain-based partitioner in the SAMR framework AMROC.
Sung, Wen-Tsai; Chiang, Yen-Chun
2012-12-01
This study examines wireless sensor network with real-time remote identification using the Android study of things (HCIOT) platform in community healthcare. An improved particle swarm optimization (PSO) method is proposed to efficiently enhance physiological multi-sensors data fusion measurement precision in the Internet of Things (IOT) system. Improved PSO (IPSO) includes: inertia weight factor design, shrinkage factor adjustment to allow improved PSO algorithm data fusion performance. The Android platform is employed to build multi-physiological signal processing and timely medical care of things analysis. Wireless sensor network signal transmission and Internet links allow community or family members to have timely medical care network services. PMID:22492176
Performance analysis of bearing-only target location algorithms
NASA Astrophysics Data System (ADS)
Gavish, Motti; Weiss, Anthony J.
1992-07-01
The performance of two well known bearing only location techniques, the maximum likelihood (ML) and the Stansfield estimators, is examined. Analytical expressions are obtained for the bias and the covariance matrix of the estimation error, which permit performance comparison for any case of interest. It is shown that the Stansfield algorithm provides biased estimates even for large numbers of measurements, in contrast with the ML method. The rms error of the Stansfield technique is not necessarily larger than the rms of the ML technique. However, it is shown that the ML technique is superior to the Stansfield method when the number of measurements is large enough. Simulation results verify the predicted theoretical performance.
A performance improvement of Dömösi's cryptosystem
NASA Astrophysics Data System (ADS)
Khaleel, Gh.; Turaev, S.; Tamrin, M. I. Mohd; Al-Shaikhli, I. F.
2016-02-01
Dömösi's cryptosystem [2, 3] is a new stream cipher based on finite automata. The cryptosystem uses specific deterministic finite accepters as secret keys for the encryption and decryption. Though this cryptosystem has been proven to be secure against different standard attacks (see [8]), the proposed encryption algorithms in [2, 3] involve exhaustive backtracking in order to generate ciphertexts. In this research, we propose a modified encryption algorithm to improve performance of the system up to a better linear-time without effecting its security.
NASA Astrophysics Data System (ADS)
Cosofret, Bogdan R.; Shokhirev, Kirill; Mulhall, Phil; Payne, David; Harris, Bernard
2014-05-01
Technology development efforts seek to increase the capability of detection systems in low Signal-to-Noise regimes encountered in both portal and urban detection applications. We have recently demonstrated significant performance enhancement in existing Advanced Spectroscopic Portals (ASP), Standoff Radiation Detection Systems (SORDS) and handheld isotope identifiers through the use of new advanced detection and identification algorithms. The Poisson Clutter Split (PCS) algorithm is a novel approach for radiological background estimation that improves the detection and discrimination capability of medium resolution detectors. The algorithm processes energy spectra and performs clutter suppression, yielding de-noised gamma-ray spectra that enable significant enhancements in detection and identification of low activity threats with spectral target recognition algorithms. The performance is achievable at the short integration times (0.5 - 1 second) necessary for operation in a high throughput and dynamic environment. PCS has been integrated with ASP, SORDS and RIID units and evaluated in field trials. We present a quantitative analysis of algorithm performance against data collected by a range of systems in several cluttered environments (urban and containerized) with embedded check sources. We show that the algorithm achieves a high probability of detection/identification with low false alarm rates under low SNR regimes. For example, utilizing only 4 out of 12 NaI detectors currently available within an ASP unit, PCS processing demonstrated Pd,ID > 90% at a CFAR (Constant False Alarm Rate) of 1 in 1000 occupancies against weak activity (7 - 8μCi) and shielded sources traveling through the portal at 30 mph. This vehicle speed is a factor of 6 higher than was previously possible and results in significant increase in system throughput and overall performance.
Improvement of Service Searching Algorithm in the JVO Portal Site
NASA Astrophysics Data System (ADS)
Eguchi, S.; Shirasak, Y.; Komiya, Y.; Ohishi, M.; Mizumoto, Y.; Ishihara, Y.; Tsutsumi, J.; Hiyama, T.; Nakamoto, H.; Sakamoto, M.
2012-09-01
The Virtual Observatory (VO) consists of a huge amount of astronomical databases which contain both of theoretical and observational data obtained with various methods, telescopes, and instruments. Since VO provides raw and processed observational data, astronomers can concentrate themselves on their scientific interests without awareness of instruments; all they have to know is which service provides their interested data. On the other hand, services on the VO system will be better used if queries can be made by means of telescopes, wavelengths, and object types; currently it is difficult for newcomers to find desired ones. We have recently started a project towards improving the data service functionality and usability on the Japanese VO (JVO) portal site. We are now working on implementation of a function to automatically classify all services on VO in terms of telescopes and instruments without referring to the facility and instrument keywords, which are not always filled in most cases. In the paper, we report a new algorithm towards constructing the facility and instrument keywords from other information of a service, and discuss its effectiveness. We also propose a new user interface of the portal site with this algorithm.
Protein-fold recognition using an improved single-source K diverse shortest paths algorithm.
Lhota, John; Xie, Lei
2016-04-01
Protein structure prediction, when construed as a fold recognition problem, is one of the most important applications of similarity search in bioinformatics. A new protein-fold recognition method is reported which combines a single-source K diverse shortest path (SSKDSP) algorithm with Enrichment of Network Topological Similarity (ENTS) algorithm to search a graphic feature space generated using sequence similarity and structural similarity metrics. A modified, more efficient SSKDSP algorithm is developed to improve the performance of graph searching. The new implementation of the SSKDSP algorithm empirically requires 82% less memory and 61% less time than the current implementation, allowing for the analysis of larger, denser graphs. Furthermore, the statistical significance of fold ranking generated from SSKDSP is assessed using ENTS. The reported ENTS-SSKDSP algorithm outperforms original ENTS that uses random walk with restart for the graph search as well as other state-of-the-art protein structure prediction algorithms HHSearch and Sparks-X, as evaluated by a benchmark of 600 query proteins. The reported methods may easily be extended to other similarity search problems in bioinformatics and chemoinformatics. The SSKDSP software is available at http://compsci.hunter.cuny.edu/~leixie/sskdsp.html. Proteins 2016; 84:467-472. © 2016 Wiley Periodicals, Inc. PMID:26800480
Simple and Efficient Algorithm for Improving the MDL Estimator of the Number of Sources
Guimarães, Dayan A.; de Souza, Rausley A. A.
2014-01-01
We propose a simple algorithm for improving the MDL (minimum description length) estimator of the number of sources of signals impinging on multiple sensors. The algorithm is based on the norms of vectors whose elements are the normalized and nonlinearly scaled eigenvalues of the received signal covariance matrix and the corresponding normalized indexes. Such norms are used to discriminate the largest eigenvalues from the remaining ones, thus allowing for the estimation of the number of sources. The MDL estimate is used as the input data of the algorithm. Numerical results unveil that the so-called norm-based improved MDL (iMDL) algorithm can achieve performances that are better than those achieved by the MDL estimator alone. Comparisons are also made with the well-known AIC (Akaike information criterion) estimator and with a recently-proposed estimator based on the random matrix theory (RMT). It is shown that our algorithm can also outperform the AIC and the RMT-based estimator in some situations. PMID:25330050
An improved algorithm for the automatic detection and characterization of slow eye movements.
Cona, Filippo; Pizza, Fabio; Provini, Federica; Magosso, Elisa
2014-07-01
Slow eye movements (SEMs) are typical of drowsy wakefulness and light sleep. SEMs still lack of systematic physical characterization. We present a new algorithm, which substantially improves our previous one, for the automatic detection of SEMs from the electro-oculogram (EOG) and extraction of SEMs physical parameters. The algorithm utilizes discrete wavelet decomposition of the EOG to implement a Bayes classifier that identifies intervals of slow ocular activity; each slow activity interval is segmented into single SEMs via a template matching method. Parameters of amplitude, duration, velocity are automatically extracted from each detected SEM. The algorithm was trained and validated on sleep onsets and offsets of 20 EOG recordings visually inspected by an expert. Performances were assessed in terms of correctly identified slow activity epochs (sensitivity: 85.12%; specificity: 82.81%), correctly segmented single SEMs (89.08%), and time misalignment (0.49 s) between the automatically and visually identified SEMs. The algorithm proved reliable even in whole sleep (sensitivity: 83.40%; specificity: 72.08% in identifying slow activity epochs; correctly segmented SEMs: 93.24%; time misalignment: 0.49 s). The algorithm, being able to objectively characterize single SEMs, may be a valuable tool to improve knowledge of normal and pathological sleep. PMID:24768562
A new multiobjective performance criterion used in PID tuning optimization algorithms
Sahib, Mouayad A.; Ahmed, Bestoun S.
2015-01-01
In PID controller design, an optimization algorithm is commonly employed to search for the optimal controller parameters. The optimization algorithm is based on a specific performance criterion which is defined by an objective or cost function. To this end, different objective functions have been proposed in the literature to optimize the response of the controlled system. These functions include numerous weighted time and frequency domain variables. However, for an optimum desired response it is difficult to select the appropriate objective function or identify the best weight values required to optimize the PID controller design. This paper presents a new time domain performance criterion based on the multiobjective Pareto front solutions. The proposed objective function is tested in the PID controller design for an automatic voltage regulator system (AVR) application using particle swarm optimization algorithm. Simulation results show that the proposed performance criterion can highly improve the PID tuning optimization in comparison with traditional objective functions. PMID:26843978
A new multiobjective performance criterion used in PID tuning optimization algorithms.
Sahib, Mouayad A; Ahmed, Bestoun S
2016-01-01
In PID controller design, an optimization algorithm is commonly employed to search for the optimal controller parameters. The optimization algorithm is based on a specific performance criterion which is defined by an objective or cost function. To this end, different objective functions have been proposed in the literature to optimize the response of the controlled system. These functions include numerous weighted time and frequency domain variables. However, for an optimum desired response it is difficult to select the appropriate objective function or identify the best weight values required to optimize the PID controller design. This paper presents a new time domain performance criterion based on the multiobjective Pareto front solutions. The proposed objective function is tested in the PID controller design for an automatic voltage regulator system (AVR) application using particle swarm optimization algorithm. Simulation results show that the proposed performance criterion can highly improve the PID tuning optimization in comparison with traditional objective functions. PMID:26843978
Improve online boosting algorithm from self-learning cascade classifier
NASA Astrophysics Data System (ADS)
Luo, Dapeng; Sang, Nong; Huang, Rui; Tong, Xiaojun
2010-04-01
Online boosting algorithm has been used in many vision-related applications, such as object detection. However, in order to obtain good detection result, combining a large number of weak classifiers into a strong classifier is required. And those weak classifiers must be updated and improved online. So the training and detection speed will be reduced inevitably. This paper proposes a novel online boosting based learning method, called self-learning cascade classifier. Cascade decision strategy is integrated with the online boosting procedure. The resulting system contains enough number of weak classifiers while keeping computation cost low. The cascade structure is learned and updated online. And the structure complexity can be increased adaptively when detection task is more difficult. Moreover, most of new samples are labeled by tracking automatically. This can greatly reduce the effort by labeler. We present experimental results that demonstrate the efficient and high detection rate of the method.