NASA Astrophysics Data System (ADS)
Williams, Arnold C.; Pachowicz, Peter W.
2004-09-01
Current mine detection research indicates that no single sensor or single look from a sensor will detect mines/minefields in a real-time manner at a performance level suitable for a forward maneuver unit. Hence, the integrated development of detectors and fusion algorithms are of primary importance. A problem in this development process has been the evaluation of these algorithms with relatively small data sets, leading to anecdotal and frequently over trained results. These anecdotal results are often unreliable and conflicting among various sensors and algorithms. Consequently, the physical phenomena that ought to be exploited and the performance benefits of this exploitation are often ambiguous. The Army RDECOM CERDEC Night Vision Laboratory and Electron Sensors Directorate has collected large amounts of multisensor data such that statistically significant evaluations of detection and fusion algorithms can be obtained. Even with these large data sets care must be taken in algorithm design and data processing to achieve statistically significant performance results for combined detectors and fusion algorithms. This paper discusses statistically significant detection and combined multilook fusion results for the Ellipse Detector (ED) and the Piecewise Level Fusion Algorithm (PLFA). These statistically significant performance results are characterized by ROC curves that have been obtained through processing this multilook data for the high resolution SAR data of the Veridian X-Band radar. We discuss the implications of these results on mine detection and the importance of statistical significance, sample size, ground truth, and algorithm design in performance evaluation.
Least significant qubit algorithm for quantum images
NASA Astrophysics Data System (ADS)
Sang, Jianzhi; Wang, Shen; Li, Qiong
2016-08-01
To study the feasibility of the classical image least significant bit (LSB) information hiding algorithm on quantum computer, a least significant qubit (LSQb) information hiding algorithm of quantum image is proposed. In this paper, we focus on a novel quantum representation for color digital images (NCQI). Firstly, by designing the three qubits comparator and unitary operators, the reasonability and feasibility of LSQb based on NCQI are presented. Then, the concrete LSQb information hiding algorithm is proposed, which can realize the aim of embedding the secret qubits into the least significant qubits of RGB channels of quantum cover image. Quantum circuit of the LSQb information hiding algorithm is also illustrated. Furthermore, the secrets extracting algorithm and circuit are illustrated through utilizing control-swap gates. The two merits of our algorithm are: (1) it is absolutely blind and (2) when extracting secret binary qubits, it does not need any quantum measurement operation or any other help from classical computer. Finally, simulation and comparative analysis show the performance of our algorithm.
Algorithm for Detecting Significant Locations from Raw GPS Data
NASA Astrophysics Data System (ADS)
Kami, Nobuharu; Enomoto, Nobuyuki; Baba, Teruyuki; Yoshikawa, Takashi
We present a fast algorithm for probabilistically extracting significant locations from raw GPS data based on data point density. Extracting significant locations from raw GPS data is the first essential step of algorithms designed for location-aware applications. Assuming that a location is significant if users spend a certain time around that area, most current algorithms compare spatial/temporal variables, such as stay duration and a roaming diameter, with given fixed thresholds to extract significant locations. However, the appropriate threshold values are not clearly known in priori and algorithms with fixed thresholds are inherently error-prone, especially under high noise levels. Moreover, for N data points, they are generally O(N 2) algorithms since distance computation is required. We developed a fast algorithm for selective data point sampling around significant locations based on density information by constructing random histograms using locality sensitive hashing. Evaluations show competitive performance in detecting significant locations even under high noise levels.
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
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.
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.
The performance of asynchronous algorithms on hypercubes
Womble, D.E.
1988-12-01
Many asynchronous algorithms have been developed for parallel computers. Most implementations of asynchronous algorithms, however, have been for shared memory machines. In this paper, we study the implementation and performance of some common asynchronous algorithms on the NCUBE/ten, a 1024 node hypercube. In addition, we summarize existing theoretical work and discuss some classes of algorithms that can be made asynchronous and some that cannot. 16 refs., 3 figs.
Discovering sequence similarity by the algorithmic significance method
Milosavljevic, A.
1993-02-01
The minimal-length encoding approach is applied to define concept of sequence similarity. A sequence is defined to be similar to another sequence or to a set of keywords if it can be encoded in a small number of bits by taking advantage of common subwords. Minimal-length encoding of a sequence is computed in linear time, using a data compression algorithm that is based on a dynamic programming strategy and the directed acyclic word graph data structure. No assumptions about common word (``k-tuple``) length are made in advance, and common words of any length are considered. The newly proposed algorithmic significance method provides an exact upper bound on the probability that sequence similarity has occurred by chance, thus eliminating the need for any arbitrary choice of similarity thresholds. Preliminary experiments indicate that a small number of keywords can positively identify a DNA sequence, which is extremely relevant in the context of partial sequencing by hybridization.
Discovering sequence similarity by the algorithmic significance method
Milosavljevic, A.
1993-02-01
The minimal-length encoding approach is applied to define concept of sequence similarity. A sequence is defined to be similar to another sequence or to a set of keywords if it can be encoded in a small number of bits by taking advantage of common subwords. Minimal-length encoding of a sequence is computed in linear time, using a data compression algorithm that is based on a dynamic programming strategy and the directed acyclic word graph data structure. No assumptions about common word ( k-tuple'') length are made in advance, and common words of any length are considered. The newly proposed algorithmic significance method provides an exact upper bound on the probability that sequence similarity has occurred by chance, thus eliminating the need for any arbitrary choice of similarity thresholds. Preliminary experiments indicate that a small number of keywords can positively identify a DNA sequence, which is extremely relevant in the context of partial sequencing by hybridization.
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.
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.
Algorithms for Detecting Significantly Mutated Pathways in Cancer
NASA Astrophysics Data System (ADS)
Vandin, Fabio; Upfal, Eli; Raphael, Benjamin J.
Recent genome sequencing studies have shown that the somatic mutations that drive cancer development are distributed across a large number of genes. This mutational heterogeneity complicates efforts to distinguish functional mutations from sporadic, passenger mutations. Since cancer mutations are hypothesized to target a relatively small number of cellular signaling and regulatory pathways, a common approach is to assess whether known pathways are enriched for mutated genes. However, restricting attention to known pathways will not reveal novel cancer genes or pathways. An alterative strategy is to examine mutated genes in the context of genome-scale interaction networks that include both well characterized pathways and additional gene interactions measured through various approaches. We introduce a computational framework for de novo identification of subnetworks in a large gene interaction network that are mutated in a significant number of patients. This framework includes two major features. First, we introduce a diffusion process on the interaction network to define a local neighborhood of "influence" for each mutated gene in the network. Second, we derive a two-stage multiple hypothesis test to bound the false discovery rate (FDR) associated with the identified subnetworks. We test these algorithms on a large human protein-protein interaction network using mutation data from two recent studies: glioblastoma samples from The Cancer Genome Atlas and lung adenocarcinoma samples from the Tumor Sequencing Project. We successfully recover pathways that are known to be important in these cancers, such as the p53 pathway. We also identify additional pathways, such as the Notch signaling pathway, that have been implicated in other cancers but not previously reported as mutated in these samples. Our approach is the first, to our knowledge, to demonstrate a computationally efficient strategy for de novo identification of statistically significant mutated subnetworks. We
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!
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
The Real World Significance of Performance Prediction
ERIC Educational Resources Information Center
Pardos, Zachary A.; Wang, Qing Yang; Trivedi, Shubhendu
2012-01-01
In recent years, the educational data mining and user modeling communities have been aggressively introducing models for predicting student performance on external measures such as standardized tests as well as within-tutor performance. While these models have brought statistically reliable improvement to performance prediction, the real world…
Compression Techniques for Improved Algorithm Computational Performance
NASA Technical Reports Server (NTRS)
Zalameda, Joseph N.; Howell, Patricia A.; Winfree, William P.
2005-01-01
Analysis of thermal data requires the processing of large amounts of temporal image data. The processing of the data for quantitative information can be time intensive especially out in the field where large areas are inspected resulting in numerous data sets. By applying a temporal compression technique, improved algorithm performance can be obtained. In this study, analysis techniques are applied to compressed and non-compressed thermal data. A comparison is made based on computational speed and defect signal to noise.
A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features.
Amudha, P; Karthik, S; Sivakumari, S
2015-01-01
Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC) with Enhanced Particle Swarm Optimization (EPSO) to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup'99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different. PMID:26221625
A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features
Amudha, P.; Karthik, S.; Sivakumari, S.
2015-01-01
Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC) with Enhanced Particle Swarm Optimization (EPSO) to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup'99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different. PMID:26221625
Performance evaluation of SAR/GMTI algorithms
NASA Astrophysics Data System (ADS)
Garber, Wendy; Pierson, William; Mcginnis, Ryan; Majumder, Uttam; Minardi, Michael; Sobota, David
2016-05-01
There is a history and understanding of exploiting moving targets within ground moving target indicator (GMTI) data, including methods for modeling performance. However, many assumptions valid for GMTI processing are invalid for synthetic aperture radar (SAR) data. For example, traditional GMTI processing assumes targets are exo-clutter and a system that uses a GMTI waveform, i.e. low bandwidth (BW) and low pulse repetition frequency (PRF). Conversely, SAR imagery is typically formed to focus data at zero Doppler and requires high BW and high PRF. Therefore, many of the techniques used in performance estimation of GMTI systems are not valid for SAR data. However, as demonstrated by papers in the recent literature,1-11 there is interest in exploiting moving targets within SAR data. The techniques employed vary widely, including filter banks to form images at multiple Dopplers, performing smear detection, and attempting to address the issue through waveform design. The above work validates the need for moving target exploitation in SAR data, but it does not represent a theory allowing for the prediction or bounding of performance. This work develops an approach to estimate and/or bound performance for moving target exploitation specific to SAR data. Synthetic SAR data is generated across a range of sensor, environment, and target parameters to test the exploitation algorithms under specific conditions. This provides a design tool allowing radar systems to be tuned for specific moving target exploitation applications. In summary, we derive a set of rules that bound the performance of specific moving target exploitation algorithms under variable operating conditions.
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.
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.
Characterization of an advanced performance reticle defect inspection algorithm
NASA Astrophysics Data System (ADS)
Wiley, James N.; Aquino, Christopher M.; Burnham, Douglas V.; Vacca, Anthony
1997-07-01
KLA-Tencor has developed a new reticle defect inspection algorithm, APA (advanced performance algorithm), which replaces the current 300 series algorithm (P183), and offers significant improvements in the detection of important defect types on advanced reticles, including OPC reticles. The improvements with APA can also allow inspections with larger pixel sizes compared with P183, resulting in faster inspection times. A suite of test masks was used for evaluating APA's performance on a 351 reticle inspection system at 488 nm using 0.5, 0.375 and 0.25 micrometer pixel sizes. The test suite included a VeriThoroTM 890EX test reticle and a SEMI- standard programmed defect test pattern scaled by 50%, 33%, 25%, and 20% (producing nominal primary features sizes of 1.5, 1.0, 0.75 and 0.60 micrometer). APA's improved performance allowed the use of the 0.375 micrometer pixel size for the 1.5 and 1.0 micrometer linewidth patterns resulting in faster inspection times (compared with the 0.25 micrometer pixel size for P183); it further allowed the successful inspection of the 0.75 and 0.60 micrometer linewidth patterns. A methodology was developed to analyze, summarize and compare the performance results of APA and P183. Finally, APA successfully inspected various actual product reticles with patterns of 0.75 micrometer and below including an advanced MicroUnity OPC (optical proximity correction) reticle with 0.75 micrometer serif and 0.35 micrometer database neck dimensions.
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
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.
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.
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
Relative performance of algorithms for autonomous satellite orbit determination
NASA Technical Reports Server (NTRS)
Tapley, B. D.; Peters, J. G.; Schutz, B. E.
1981-01-01
Limited word size in contemporary microprocessors causes numerical problems in autonomous satellite navigation applications. Numerical error introduced in navigation computations performed on small wordlength machines can cause divergence of sequential estimation algorithms. To insure filter reliability, square root algorithms have been adopted in many applications. The optimal navigation algorithm requires a careful match of the estimation algorithm, dynamic model, and numerical integrator. In this investigation, the relationship of several square root filters and numerical integration methods is evaluated to determine their relative performance for satellite navigation applications. The numerical simulations are conducted using the Phase I GPS constellation to determine the orbit of a LANDSAT-D type satellite. The primary comparison is based on computation time and relative estimation accuracy.
A Hybrid Actuation System Demonstrating Significantly Enhanced Electromechanical Performance
NASA Technical Reports Server (NTRS)
Su, Ji; Xu, Tian-Bing; Zhang, Shujun; Shrout, Thomas R.; Zhang, Qiming
2004-01-01
A hybrid actuation system (HYBAS) utilizing advantages of a combination of electromechanical responses of an electroactive polymer (EAP), an electrostrictive copolymer, and an electroactive ceramic single crystal, PZN-PT single crystal, has been developed. The system employs the contribution of the actuation elements cooperatively and exhibits a significantly enhanced electromechanical performance compared to the performances of the device made of each constituting material, the electroactive polymer or the ceramic single crystal, individually. The theoretical modeling of the performances of the HYBAS is in good agreement with experimental observation. The consistence between the theoretical modeling and experimental test make the design concept an effective route for the development of high performance actuating devices for many applications. The theoretical modeling, fabrication of the HYBAS and the initial experimental results will be presented and discussed.
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
Statistical Evaluation of the Performance of Energy Surface Search Algorithms
NASA Astrophysics Data System (ADS)
Horoi, Mihai; Jackson, Koblar A.
2001-03-01
In the last few years several new energy surface search algorithms have been proposed, including Genetic Algorithms (GA), Basin-Hopping Monte Carlo, and a single parent GA (see I. Rata, et al., Phys. Rev. Lett. 85, 546(2000)). Each time a new algorithm was presented, the authors claimed better performance by finding lower minima for previously studied clusters. However, it was not clear if the better result was a consequence of a better algorithm or due to more patience in searching the configuration space. We have done a statistical evaluation of all these algorithms and find that the distribution of the number of search steps required to locate the global minimum from a random starting point is an exponential for each method, with the average equal to the variance. This behavior is a result of the random steps made by each method in searching the configuration space. Understanding the nature of the distribution allows the performance of the methods to be compared statistically and suggests possible improvements. We also show that in some cases (small clusters with Lennard-Jones interactions) a completely random search starting in a "small" box can be more efficient than any of the more complex algorithms.
Performance evaluation of image processing algorithms on the GPU.
Castaño-Díez, Daniel; Moser, Dominik; Schoenegger, Andreas; Pruggnaller, Sabine; Frangakis, Achilleas S
2008-10-01
The graphics processing unit (GPU), which originally was used exclusively for visualization purposes, has evolved into an extremely powerful co-processor. In the meanwhile, through the development of elaborate interfaces, the GPU can be used to process data and deal with computationally intensive applications. The speed-up factors attained compared to the central processing unit (CPU) are dependent on the particular application, as the GPU architecture gives the best performance for algorithms that exhibit high data parallelism and high arithmetic intensity. Here, we evaluate the performance of the GPU on a number of common algorithms used for three-dimensional image processing. The algorithms were developed on a new software platform called "CUDA", which allows a direct translation from C code to the GPU. The implemented algorithms include spatial transformations, real-space and Fourier operations, as well as pattern recognition procedures, reconstruction algorithms and classification procedures. In our implementation, the direct porting of C code in the GPU achieves typical acceleration values in the order of 10-20 times compared to a state-of-the-art conventional processor, but they vary depending on the type of the algorithm. The gained speed-up comes with no additional costs, since the software runs on the GPU of the graphics card of common workstations.
Significant Advances in the AIRS Science Team Version-6 Retrieval Algorithm
NASA Technical Reports Server (NTRS)
Susskind, Joel; Blaisdell, John; Iredell, Lena; Molnar, Gyula
2012-01-01
AIRS/AMSU is the state of the art infrared and microwave atmospheric sounding system flying aboard EOS Aqua. The Goddard DISC has analyzed AIRS/AMSU observations, covering the period September 2002 until the present, using the AIRS Science Team Version-S retrieval algorithm. These products have been used by many researchers to make significant advances in both climate and weather applications. The AIRS Science Team Version-6 Retrieval, which will become operation in mid-20l2, contains many significant theoretical and practical improvements compared to Version-5 which should further enhance the utility of AIRS products for both climate and weather applications. In particular, major changes have been made with regard to the algOrithms used to 1) derive surface skin temperature and surface spectral emissivity; 2) generate the initial state used to start the retrieval procedure; 3) compute Outgoing Longwave Radiation; and 4) determine Quality Control. This paper will describe these advances found in the AIRS Version-6 retrieval algorithm and demonstrate the improvement of AIRS Version-6 products compared to those obtained using Version-5,
Developmental Changes in Adolescents' Olfactory Performance and Significance of Olfaction
Klötze, Paula; Gerber, Friederike; Croy, Ilona; Hummel, Thomas
2016-01-01
Aim of the current work was to examine developmental changes in adolescents’ olfactory performance and personal significance of olfaction. In the first study olfactory identification abilities of 76 participants (31 males and 45 females aged between 10 and 18 years; M = 13.8, SD = 2.3) was evaluated with the Sniffin Stick identification test, presented in a cued and in an uncued manner. Verbal fluency was additionally examined for control purpose. In the second study 131 participants (46 males and 85 females aged between 10 and 18 years; (M = 14.4, SD = 2.2) filled in the importance of olfaction questionnaire. Odor identification abilities increased significantly with age and were significantly higher in girls as compared to boys. These effects were especially pronounced in the uncued task and partly related to verbal fluency. In line, the personal significance of olfaction increased with age and was generally higher among female compared to male participants. PMID:27332887
Informational properties of neural nets performing algorithmic and logical tasks.
Ritz, B M; Hofacker, G L
1996-06-01
It is argued that the genetic information necessary to encode an algorithmic neural processor tutoring an otherwise randomly connected biological neural net is represented by the entropy of the analogous minimal Turing machine. Such a near-minimal machine is constructed performing the whole range of bivalent propositional logic in n variables. Neural nets computing the same task are presented; their informational entropy can be gauged with reference to the analogous Turing machine. It is also shown that nets with one hidden layer can be trained to perform algorithms solving propositional logic by error back-propagation. PMID:8672562
Informational properties of neural nets performing algorithmic and logical tasks.
Ritz, B M; Hofacker, G L
1996-06-01
It is argued that the genetic information necessary to encode an algorithmic neural processor tutoring an otherwise randomly connected biological neural net is represented by the entropy of the analogous minimal Turing machine. Such a near-minimal machine is constructed performing the whole range of bivalent propositional logic in n variables. Neural nets computing the same task are presented; their informational entropy can be gauged with reference to the analogous Turing machine. It is also shown that nets with one hidden layer can be trained to perform algorithms solving propositional logic by error back-propagation.
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.
Epidemic features affecting the performance of outbreak detection algorithms
2012-01-01
Background Outbreak detection algorithms play an important role in effective automated surveillance. Although many algorithms have been designed to improve the performance of outbreak detection, few published studies have examined how epidemic features of infectious disease impact on the detection performance of algorithms. This study compared the performance of three outbreak detection algorithms stratified by epidemic features of infectious disease and examined the relationship between epidemic features and performance of outbreak detection algorithms. Methods Exponentially weighted moving average (EWMA), cumulative sum (CUSUM) and moving percentile method (MPM) algorithms were applied. We inserted simulated outbreaks into notifiable infectious disease data in China Infectious Disease Automated-alert and Response System (CIDARS), and compared the performance of the three algorithms with optimized parameters at a fixed false alarm rate of 5% classified by epidemic features of infectious disease. Multiple linear regression was adopted to analyse the relationship of the algorithms’ sensitivity and timeliness with the epidemic features of infectious diseases. Results The MPM had better detection performance than EWMA and CUSUM through all simulated outbreaks, with or without stratification by epidemic features (incubation period, baseline counts and outbreak magnitude). The epidemic features were associated with both sensitivity and timeliness. Compared with long incubation, short incubation had lower probability (β* = −0.13, P < 0.001) but needed shorter time to detect outbreaks (β* = −0.57, P < 0.001). Lower baseline counts were associated with higher probability (β* = −0.20, P < 0.001) and longer time (β* = 0.14, P < 0.001). The larger outbreak magnitude was correlated with higher probability (β* = 0.55, P < 0.001) and shorter time (β* = −0.23, P < 0.001). Conclusions The results of this study suggest
A high-performance FFT algorithm for vector supercomputers
NASA Technical Reports Server (NTRS)
Bailey, David H.
1988-01-01
Many traditional algorithms for computing the fast Fourier transform (FFT) on conventional computers are unacceptable for advanced vector and parallel computers because they involve nonunit, power-of-two memory strides. A practical technique for computing the FFT that avoids all such strides and appears to be near-optimal for a variety of current vector and parallel computers is presented. Performance results of a program based on this technique are given. Notable among these results is that a FORTRAN implementation of this algorithm on the CRAY-2 runs up to 77-percent faster than Cray's assembly-coded library routine.
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.
Multipole Algorithms for Molecular Dynamics Simulation on High Performance Computers.
NASA Astrophysics Data System (ADS)
Elliott, William Dewey
1995-01-01
A fundamental problem in modeling large molecular systems with molecular dynamics (MD) simulations is the underlying N-body problem of computing the interactions between all pairs of N atoms. The simplest algorithm to compute pair-wise atomic interactions scales in runtime {cal O}(N^2), making it impractical for interesting biomolecular systems, which can contain millions of atoms. Recently, several algorithms have become available that solve the N-body problem by computing the effects of all pair-wise interactions while scaling in runtime less than {cal O}(N^2). One algorithm, which scales {cal O}(N) for a uniform distribution of particles, is called the Greengard-Rokhlin Fast Multipole Algorithm (FMA). This work describes an FMA-like algorithm called the Molecular Dynamics Multipole Algorithm (MDMA). The algorithm contains several features that are new to N-body algorithms. MDMA uses new, efficient series expansion equations to compute general 1/r^{n } potentials to arbitrary accuracy. In particular, the 1/r Coulomb potential and the 1/r^6 portion of the Lennard-Jones potential are implemented. The new equations are based on multivariate Taylor series expansions. In addition, MDMA uses a cell-to-cell interaction region of cells that is closely tied to worst case error bounds. The worst case error bounds for MDMA are derived in this work also. These bounds apply to other multipole algorithms as well. Several implementation enhancements are described which apply to MDMA as well as other N-body algorithms such as FMA and tree codes. The mathematics of the cell -to-cell interactions are converted to the Fourier domain for reduced operation count and faster computation. A relative indexing scheme was devised to locate cells in the interaction region which allows efficient pre-computation of redundant information and prestorage of much of the cell-to-cell interaction. Also, MDMA was integrated into the MD program SIgMA to demonstrate the performance of the program over
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 of redirected walking algorithms in a constrained virtual world.
Hodgson, Eric; Bachmann, Eric; Thrash, Tyler
2014-04-01
Redirected walking algorithms imperceptibly rotate a virtual scene about users of immersive virtual environment systems in order to guide them away from tracking area boundaries. Ideally, these distortions permit users to explore large unbounded virtual worlds while walking naturally within a physically limited space. Many potential virtual worlds are composed of corridors, passageways, or aisles. Assuming users are not expected to walk through walls or other objects within the virtual world, these constrained worlds limit the directions of travel and as well as the number of opportunities to change direction. The resulting differences in user movement characteristics within the physical world have an impact on redirected walking algorithm performance. This work presents a comparison of generalized RDW algorithm performance within a constrained virtual world. In contrast to previous studies involving unconstrained virtual worlds, experimental results indicate that the steer-to-orbit keeps users in a smaller area than the steer-to-center algorithm. Moreover, in comparison to steer-to-center, steer-to-orbit is shown to reduce potential wall contacts by over 29%.
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.
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.
A DRAM compiler algorithm for high performance VLSI embedded memories
NASA Technical Reports Server (NTRS)
Eldin, A. G.
1992-01-01
In many applications, the limited density of the embedded SRAM does not allow integrating the memory on the same chip with other logic and functional blocks. In such cases, the embedded DRAM provides the optimum combination of very high density, low power, and high performance. For ASIC's to take full advantage of this design strategy, an efficient and highly reliable DRAM compiler must be used. The embedded DRAM architecture, cell, and peripheral circuit design considerations and the algorithm of a high performance memory compiler are presented .
S-index: Measuring significant, not average, citation performance
NASA Astrophysics Data System (ADS)
Antonoyiannakis, Manolis
2009-03-01
We recently [1] introduced the ``citation density curve'' (or cumulative impact factor curve) that captures the full citation performance of a journal: its size, impact factor, the maximum number of citations per paper, the relative size of the different-cited portions of the journal, etc. The citation density curve displays a universal behavior across journals. We exploit this universality to extract a simple metric (the ``S-index'') to characterize the citation impact of ``significant'' papers in each journal. In doing so, we go beyond the journal impact factor, which only measures the impact of the average paper. The conventional wisdom of ranking journals according to their impact factors is thus challenged. Having shown the utility and robustness of the S-index in comparing and ranking journals of different sizes but within the same field, we explore the concept further, going beyond a single field, and beyond journals. Can we compare different scientific fields, departments, or universities? And how should one generalize the citation density curve and the S-index to address these questions? [1] M. Antonoyiannakis and S. Mitra, ``Is PRL too large to have an `impact'?'', Editorial, Physical Review Letters, December 2008.
Performance analysis of approximate Affine Projection Algorithm in acoustic feedback cancellation.
Nikjoo S, Mohammad; Seyedi, Amir; Tehrani, Arash Saber
2008-01-01
Acoustic feedback is an annoying problem in several audio applications and especially in hearing aids. Adaptive feedback cancellation techniques have attracted recent attention and show great promise in reducing the deleterious effects of feedback. In this paper, we investigated the performance of a class of adaptive feedback cancellation algorithms viz. the approximated Affine Projection Algorithms (APA). Mixed results were obtained with the natural speech and music data collected from five different commercial hearing aids in a variety of sub-oscillatory and oscillatory feedback conditions. The performance of the approximated APA was significantly better with music stimuli than natural speech stimuli. PMID:19162642
A performance comparison of integration algorithms in simulating flexible structures
NASA Technical Reports Server (NTRS)
Howe, R. M.
1989-01-01
Asymptotic formulas for the characteristic root errors as well as transfer function gain and phase errors are presented for a number of traditional and new integration methods. Normalized stability regions in the lambda h plane are compared for the various methods. In particular, it is shown that a modified form of Euler integration with root matching is an especially efficient method for simulating lightly-damped structural modes. The method has been used successfully for structural bending modes in the real-time simulation of missiles. Performance of this algorithm is compared with other special algorithms, including the state-transition method. A predictor-corrector version of the modified Euler algorithm permits it to be extended to the simulation of nonlinear models of the type likely to be obtained when using the discretized structure approach. Performance of the different integration methods is also compared for integration step sizes larger than those for which the asymptotic formulas are valid. It is concluded that many traditional integration methods, such as RD-4, are not competitive in the simulation of lightly damped structures.
New Classification Method Based on Support-Significant Association Rules Algorithm
NASA Astrophysics Data System (ADS)
Li, Guoxin; Shi, Wen
One of the most well-studied problems in data mining is mining for association rules. There was also research that introduced association rule mining methods to conduct classification tasks. These classification methods, based on association rule mining, could be applied for customer segmentation. Currently, most of the association rule mining methods are based on a support-confidence structure, where rules satisfied both minimum support and minimum confidence were returned as strong association rules back to the analyzer. But, this types of association rule mining methods lack of rigorous statistic guarantee, sometimes even caused misleading. A new classification model for customer segmentation, based on association rule mining algorithm, was proposed in this paper. This new model was based on the support-significant association rule mining method, where the measurement of confidence for association rule was substituted by the significant of association rule that was a better evaluation standard for association rules. Data experiment for customer segmentation from UCI indicated the effective of this new model.
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
NASA Astrophysics Data System (ADS)
Habarulema, J. B.; McKinnell, L.-A.
2012-05-01
In this work, results obtained by investigating the application of different neural network backpropagation training algorithms are presented. This was done to assess the performance accuracy of each training algorithm in total electron content (TEC) estimations using identical datasets in models development and verification processes. Investigated training algorithms are standard backpropagation (SBP), backpropagation with weight delay (BPWD), backpropagation with momentum (BPM) term, backpropagation with chunkwise weight update (BPC) and backpropagation for batch (BPB) training. These five algorithms are inbuilt functions within the Stuttgart Neural Network Simulator (SNNS) and the main objective was to find out the training algorithm that generates the minimum error between the TEC derived from Global Positioning System (GPS) observations and the modelled TEC data. Another investigated algorithm is the MatLab based Levenberg-Marquardt backpropagation (L-MBP), which achieves convergence after the least number of iterations during training. In this paper, neural network (NN) models were developed using hourly TEC data (for 8 years: 2000-2007) derived from GPS observations over a receiver station located at Sutherland (SUTH) (32.38° S, 20.81° E), South Africa. Verification of the NN models for all algorithms considered was performed on both "seen" and "unseen" data. Hourly TEC values over SUTH for 2003 formed the "seen" dataset. The "unseen" dataset consisted of hourly TEC data for 2002 and 2008 over Cape Town (CPTN) (33.95° S, 18.47° E) and SUTH, respectively. The models' verification showed that all algorithms investigated provide comparable results statistically, but differ significantly in terms of time required to achieve convergence during input-output data training/learning. This paper therefore provides a guide to neural network users for choosing appropriate algorithms based on the availability of computation capabilities used for research.
Performance evaluation of operational atmospheric correction algorithms over the East China Seas
NASA Astrophysics Data System (ADS)
He, Shuangyan; He, Mingxia; Fischer, Jürgen
2016-04-01
To acquire high-quality operational data products for Chinese in-orbit and scheduled ocean color sensors, the performances of two operational atmospheric correction (AC) algorithms (ESA MEGS 7.4.1 and NASA SeaDAS 6.1) were evaluated over the East China Seas (ECS) using MERIS data. The spectral remote sensing reflectance R rs(λ), aerosol optical thickness (AOT), and Ångström exponent (α) retrieved using the two algorithms were validated using in situ measurements obtained between May 2002 and October 2009. Match-ups of R rs, AOT, and α between the in situ and MERIS data were obtained through strict exclusion criteria. Statistical analysis of R rs(λ) showed a mean percentage difference (MPD) of 9%-13% in the 490-560 nm spectral range, and significant overestimation was observed at 413 nm (MPD>72%). The AOTs were overestimated (MPD>32%), and although the ESA algorithm outperformed the NASA algorithm in the blue-green bands, the situation was reversed in the red-near-infrared bands. The value of α was obviously underestimated by the ESA algorithm (MPD=41%) but not by the NASA algorithm (MPD=35%). To clarify why the NASA algorithm performed better in the retrieval of α, scatter plots of the α single scattering albedo (SSA) density were prepared. These α-SSA density scatter plots showed that the applicability of the aerosol models used by the NASA algorithm over the ECS is better than that used by the ESA algorithm, although neither aerosol model is suitable for the ECS region. The results of this study provide a reference to both data users and data agencies regarding the use of operational data products and the investigation into the improvement of current AC schemes over the ECS.
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.
Assessing the performance of a covert automatic target recognition algorithm
NASA Astrophysics Data System (ADS)
Ehrman, Lisa M.; Lanterman, Aaron D.
2005-05-01
Passive radar systems exploit illuminators of opportunity, such as TV and FM radio, to illuminate potential targets. Doing so allows them to operate covertly and inexpensively. Our research seeks to enhance passive radar systems by adding automatic target recognition (ATR) capabilities. In previous papers we proposed conducting ATR by comparing the radar cross section (RCS) of aircraft detected by a passive radar system to the precomputed RCS of aircraft in the target class. To effectively model the low-frequency setting, the comparison is made via a Rician likelihood model. Monte Carlo simulations indicate that the approach is viable. This paper builds on that work by developing a method for quickly assessing the potential performance of the ATR algorithm without using exhaustive Monte Carlo trials. This method exploits the relation between the probability of error in a binary hypothesis test under the Bayesian framework to the Chernoff information. Since the data are well-modeled as Rician, we begin by deriving a closed-form approximation for the Chernoff information between two Rician densities. This leads to an approximation for the probability of error in the classification algorithm that is a function of the number of available measurements. We conclude with an application that would be particularly cumbersome to accomplish via Monte Carlo trials, but that can be quickly addressed using the Chernoff information approach. This application evaluates the length of time that an aircraft must be tracked before the probability of error in the ATR algorithm drops below a desired threshold.
NASA Astrophysics Data System (ADS)
Alexandre, E.; Cuadra, L.; Nieto-Borge, J. C.; Candil-García, G.; del Pino, M.; Salcedo-Sanz, S.
2015-08-01
Wave parameters computed from time series measured by buoys (significant wave height Hs, mean wave period, etc.) play a key role in coastal engineering and in the design and operation of wave energy converters. Storms or navigation accidents can make measuring buoys break down, leading to missing data gaps. In this paper we tackle the problem of locally reconstructing Hs at out-of-operation buoys by using wave parameters from nearby buoys, based on the spatial correlation among values at neighboring buoy locations. The novelty of our approach for its potential application to problems in coastal engineering is twofold. On one hand, we propose a genetic algorithm hybridized with an extreme learning machine that selects, among the available wave parameters from the nearby buoys, a subset FnSP with nSP parameters that minimizes the Hs reconstruction error. On the other hand, we evaluate to what extent the selected parameters in subset FnSP are good enough in assisting other machine learning (ML) regressors (extreme learning machines, support vector machines and gaussian process regression) to reconstruct Hs. The results show that all the ML method explored achieve a good Hs reconstruction in the two different locations studied (Caribbean Sea and West Atlantic).
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.
Zhang, Lei; Wang, Linlin; Du, Bochuan; Wang, Tianjiao; Tian, Pu
2016-01-01
Among non-small cell lung cancer (NSCLC), adenocarcinoma (AC), and squamous cell carcinoma (SCC) are two major histology subtypes, accounting for roughly 40% and 30% of all lung cancer cases, respectively. Since AC and SCC differ in their cell of origin, location within the lung, and growth pattern, they are considered as distinct diseases. Gene expression signatures have been demonstrated to be an effective tool for distinguishing AC and SCC. Gene set analysis is regarded as irrelevant to the identification of gene expression signatures. Nevertheless, we found that one specific gene set analysis method, significance analysis of microarray-gene set reduction (SAMGSR), can be adopted directly to select relevant features and to construct gene expression signatures. In this study, we applied SAMGSR to a NSCLC gene expression dataset. When compared with several novel feature selection algorithms, for example, LASSO, SAMGSR has equivalent or better performance in terms of predictive ability and model parsimony. Therefore, SAMGSR is a feature selection algorithm, indeed. Additionally, we applied SAMGSR to AC and SCC subtypes separately to discriminate their respective stages, that is, stage II versus stage I. Few overlaps between these two resulting gene signatures illustrate that AC and SCC are technically distinct diseases. Therefore, stratified analyses on subtypes are recommended when diagnostic or prognostic signatures of these two NSCLC subtypes are constructed. PMID:27446945
Zhang, Lei; Wang, Linlin; Du, Bochuan; Wang, Tianjiao; Tian, Pu; Tian, Suyan
2016-01-01
Among non-small cell lung cancer (NSCLC), adenocarcinoma (AC), and squamous cell carcinoma (SCC) are two major histology subtypes, accounting for roughly 40% and 30% of all lung cancer cases, respectively. Since AC and SCC differ in their cell of origin, location within the lung, and growth pattern, they are considered as distinct diseases. Gene expression signatures have been demonstrated to be an effective tool for distinguishing AC and SCC. Gene set analysis is regarded as irrelevant to the identification of gene expression signatures. Nevertheless, we found that one specific gene set analysis method, significance analysis of microarray-gene set reduction (SAMGSR), can be adopted directly to select relevant features and to construct gene expression signatures. In this study, we applied SAMGSR to a NSCLC gene expression dataset. When compared with several novel feature selection algorithms, for example, LASSO, SAMGSR has equivalent or better performance in terms of predictive ability and model parsimony. Therefore, SAMGSR is a feature selection algorithm, indeed. Additionally, we applied SAMGSR to AC and SCC subtypes separately to discriminate their respective stages, that is, stage II versus stage I. Few overlaps between these two resulting gene signatures illustrate that AC and SCC are technically distinct diseases. Therefore, stratified analyses on subtypes are recommended when diagnostic or prognostic signatures of these two NSCLC subtypes are constructed. PMID:27446945
Novel adaptive playout algorithm for voice over IP applications and performance assessment over WANs
NASA Astrophysics Data System (ADS)
Hintoglu, Mustafa H.; Ergul, Faruk R.
2001-07-01
Special purpose hardware and application software have been developed to implement and test Voice over IP protocols. The hardware has interface units to which ISDN telephone sets can be connected. It has Ethernet and RS-232 interfaces for connections to LANs and controlling PCs. The software has modules which are specific to telephone operations and simulation activities. The simulator acts as a WAN environment, generating delays in delivering speech packets according to delay distribution specified. By using WAN simulator, different algorithms can be tested and their performances can be compared. The novel algorithm developed correlates silence periods with received voice packets and delays play out until confidence is established that a significant phrase or sentence is stored in the playout buffer. The performance of this approach has been found to be either superior or comparable to performances of existing algorithms tested. This new algorithm has the advantage that at least a complete phrase or sentence is played out, thereby increasing the intelligibility considerably. The penalty of having larger delays compared to published algorithms operating under bursty traffic conditions is compensated by higher quality of service offered. In the paper, details of developed system and obtained test results will be presented.
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.
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
Performance Analysis of Apriori Algorithm with Different Data Structures on Hadoop Cluster
NASA Astrophysics Data System (ADS)
Singh, Sudhakar; Garg, Rakhi; Mishra, P. K.
2015-10-01
Mining frequent itemsets from massive datasets is always being a most important problem of data mining. Apriori is the most popular and simplest algorithm for frequent itemset mining. To enhance the efficiency and scalability of Apriori, a number of algorithms have been proposed addressing the design of efficient data structures, minimizing database scan and parallel and distributed processing. MapReduce is the emerging parallel and distributed technology to process big datasets on Hadoop Cluster. To mine big datasets it is essential to re-design the data mining algorithm on this new paradigm. In this paper, we implement three variations of Apriori algorithm using data structures hash tree, trie and hash table trie i.e. trie with hash technique on MapReduce paradigm. We emphasize and investigate the significance of these three data structures for Apriori algorithm on Hadoop cluster, which has not been given attention yet. Experiments are carried out on both real life and synthetic datasets which shows that hash table trie data structures performs far better than trie and hash tree in terms of execution time. Moreover the performance in case of hash tree becomes worst.
Graff, Mario; Poli, Riccardo; Flores, Juan J
2013-01-01
Modeling the behavior of algorithms is the realm of evolutionary algorithm theory. From a practitioner's point of view, theory must provide some guidelines regarding which algorithm/parameters to use in order to solve a particular problem. Unfortunately, most theoretical models of evolutionary algorithms are difficult to apply to realistic situations. However, in recent work (Graff and Poli, 2008, 2010), where we developed a method to practically estimate the performance of evolutionary program-induction algorithms (EPAs), we started addressing this issue. The method was quite general; however, it suffered from some limitations: it required the identification of a set of reference problems, it required hand picking a distance measure in each particular domain, and the resulting models were opaque, typically being linear combinations of 100 features or more. In this paper, we propose a significant improvement of this technique that overcomes the three limitations of our previous method. We achieve this through the use of a novel set of features for assessing problem difficulty for EPAs which are very general, essentially based on the notion of finite difference. To show the capabilities or our technique and to compare it with our previous performance models, we create models for the same two important classes of problems-symbolic regression on rational functions and Boolean function induction-used in our previous work. We model a variety of EPAs. The comparison showed that for the majority of the algorithms and problem classes, the new method produced much simpler and more accurate models than before. To further illustrate the practicality of the technique and its generality (beyond EPAs), we have also used it to predict the performance of both autoregressive models and EPAs on the problem of wind speed forecasting, obtaining simpler and more accurate models that outperform in all cases our previous performance models. PMID:23136918
Graff, Mario; Poli, Riccardo; Flores, Juan J
2013-01-01
Modeling the behavior of algorithms is the realm of evolutionary algorithm theory. From a practitioner's point of view, theory must provide some guidelines regarding which algorithm/parameters to use in order to solve a particular problem. Unfortunately, most theoretical models of evolutionary algorithms are difficult to apply to realistic situations. However, in recent work (Graff and Poli, 2008, 2010), where we developed a method to practically estimate the performance of evolutionary program-induction algorithms (EPAs), we started addressing this issue. The method was quite general; however, it suffered from some limitations: it required the identification of a set of reference problems, it required hand picking a distance measure in each particular domain, and the resulting models were opaque, typically being linear combinations of 100 features or more. In this paper, we propose a significant improvement of this technique that overcomes the three limitations of our previous method. We achieve this through the use of a novel set of features for assessing problem difficulty for EPAs which are very general, essentially based on the notion of finite difference. To show the capabilities or our technique and to compare it with our previous performance models, we create models for the same two important classes of problems-symbolic regression on rational functions and Boolean function induction-used in our previous work. We model a variety of EPAs. The comparison showed that for the majority of the algorithms and problem classes, the new method produced much simpler and more accurate models than before. To further illustrate the practicality of the technique and its generality (beyond EPAs), we have also used it to predict the performance of both autoregressive models and EPAs on the problem of wind speed forecasting, obtaining simpler and more accurate models that outperform in all cases our previous performance models.
Implementation and performance of a domain decomposition algorithm in Sisal
DeBoni, T.; Feo, J.; Rodrigue, G.; Muller, J.
1993-09-23
Sisal is a general-purpose functional language that hides the complexity of parallel processing, expedites parallel program development, and guarantees determinacy. Parallelism and management of concurrent tasks are realized automatically by the compiler and runtime system. Spatial domain decomposition is a widely-used method that focuses computational resources on the most active, or important, areas of a domain. Many complex programming issues are introduced in paralleling this method including: dynamic spatial refinement, dynamic grid partitioning and fusion, task distribution, data distribution, and load balancing. In this paper, we describe a spatial domain decomposition algorithm programmed in Sisal. We explain the compilation process, and present the execution performance of the resultant code on two different multiprocessor systems: a multiprocessor vector supercomputer, and cache-coherent scalar multiprocessor.
Detrending moving average algorithm: Frequency response and scaling performances.
Carbone, Anna; Kiyono, Ken
2016-06-01
The Detrending Moving Average (DMA) algorithm has been widely used in its several variants for characterizing long-range correlations of random signals and sets (one-dimensional sequences or high-dimensional arrays) over either time or space. In this paper, mainly based on analytical arguments, the scaling performances of the centered DMA, including higher-order ones, are investigated by means of a continuous time approximation and a frequency response approach. Our results are also confirmed by numerical tests. The study is carried out for higher-order DMA operating with moving average polynomials of different degree. In particular, detrending power degree, frequency response, asymptotic scaling, upper limit of the detectable scaling exponent, and finite scale range behavior will be discussed. PMID:27415389
Detrending moving average algorithm: Frequency response and scaling performances
NASA Astrophysics Data System (ADS)
Carbone, Anna; Kiyono, Ken
2016-06-01
The Detrending Moving Average (DMA) algorithm has been widely used in its several variants for characterizing long-range correlations of random signals and sets (one-dimensional sequences or high-dimensional arrays) over either time or space. In this paper, mainly based on analytical arguments, the scaling performances of the centered DMA, including higher-order ones, are investigated by means of a continuous time approximation and a frequency response approach. Our results are also confirmed by numerical tests. The study is carried out for higher-order DMA operating with moving average polynomials of different degree. In particular, detrending power degree, frequency response, asymptotic scaling, upper limit of the detectable scaling exponent, and finite scale range behavior will be discussed.
Burg algorithm for enhancing measurement performance in wavelength scanning interferometry
NASA Astrophysics Data System (ADS)
Woodcock, Rebecca; Muhamedsalih, Hussam; Martin, Haydn; Jiang, Xiangqian
2016-06-01
Wavelength scanning interferometry (WSI) is a technique for measuring surface topography that is capable of resolving step discontinuities and does not require any mechanical movement of the apparatus or measurand, allowing measurement times to be reduced substantially in comparison to related techniques. The axial (height) resolution and measurement range in WSI depends in part on the algorithm used to evaluate the spectral interferograms. Previously reported Fourier transform based methods have a number of limitations which is in part due to the short data lengths obtained. This paper compares the performance auto-regressive model based techniques for frequency estimation in WSI. Specifically, the Burg method is compared with established Fourier transform based approaches using both simulation and experimental data taken from a WSI measurement of a step-height sample.
Improving the performance of algorithms to find communities in networks.
Darst, Richard K; Nussinov, Zohar; Fortunato, Santo
2014-03-01
Most algorithms to detect communities in networks typically work without any information on the cluster structure to be found, as one has no a priori knowledge of it, in general. Not surprisingly, knowing some features of the unknown partition could help its identification, yielding an improvement of the performance of the method. Here we show that, if the number of clusters was known beforehand, standard methods, like modularity optimization, would considerably gain in accuracy, mitigating the severe resolution bias that undermines the reliability of the results of the original unconstrained version. The number of clusters can be inferred from the spectra of the recently introduced nonbacktracking and flow matrices, even in benchmark graphs with realistic community structure. The limit of such a two-step procedure is the overhead of the computation of the spectra.
Violante-Carvalho, Nelson
2005-12-01
Synthetic Aperture Radar (SAR) onboard satellites is the only source of directional wave spectra with continuous and global coverage. Millions of SAR Wave Mode (SWM) imagettes have been acquired since the launch in the early 1990's of the first European Remote Sensing Satellite ERS-1 and its successors ERS-2 and ENVISAT, which has opened up many possibilities specially for wave data assimilation purposes. The main aim of data assimilation is to improve the forecasting introducing available observations into the modeling procedures in order to minimize the differences between model estimates and measurements. However there are limitations in the retrieval of the directional spectrum from SAR images due to nonlinearities in the mapping mechanism. The Max-Planck Institut (MPI) scheme, the first proposed and most widely used algorithm to retrieve directional wave spectra from SAR images, is employed to compare significant wave heights retrieved from ERS-1 SAR against buoy measurements and against the WAM wave model. It is shown that for periods shorter than 12 seconds the WAM model performs better than the MPI, despite the fact that the model is used as first guess to the MPI method, that is the retrieval is deteriorating the first guess. For periods longer than 12 seconds, the part of the spectrum that is directly measured by SAR, the performance of the MPI scheme is at least as good as the WAM model.
NASA Technical Reports Server (NTRS)
Kobayashi, Takahisa; Simon, Donald L.
2002-01-01
As part of the NASA Aviation Safety Program, a unique model-based diagnostics method that employs neural networks and genetic algorithms for aircraft engine performance diagnostics has been developed and demonstrated at the NASA Glenn Research Center against a nonlinear gas turbine engine model. Neural networks are applied to estimate the internal health condition of the engine, and genetic algorithms are used for sensor fault detection, isolation, and quantification. This hybrid architecture combines the excellent nonlinear estimation capabilities of neural networks with the capability to rank the likelihood of various faults given a specific sensor suite signature. The method requires a significantly smaller data training set than a neural network approach alone does, and it performs the combined engine health monitoring objectives of performance diagnostics and sensor fault detection and isolation in the presence of nominal and degraded engine health conditions.
Brambley, Michael R.; Katipamula, Srinivas
2006-10-06
Pacific Northwest National Laboratory (PNNL) is assisting the U.S. Department of Energy (DOE) Distributed Energy (DE) Program by developing advanced control algorithms that would lead to development of tools to enhance performance and reliability, and reduce emissions of distributed energy technologies, including combined heat and power technologies. This report documents phase 2 of the program, providing a detailed functional specification for algorithms for performance monitoring and commissioning verification, scheduled for development in FY 2006. The report identifies the systems for which algorithms will be developed, the specific functions of each algorithm, metrics which the algorithms will output, and inputs required by each algorithm.
Angus, Simon D; Piotrowska, Monika Joanna
2014-01-01
Multi-dose radiotherapy protocols (fraction dose and timing) currently used in the clinic are the product of human selection based on habit, received wisdom, physician experience and intra-day patient timetabling. However, due to combinatorial considerations, the potential treatment protocol space for a given total dose or treatment length is enormous, even for relatively coarse search; well beyond the capacity of traditional in-vitro methods. In constrast, high fidelity numerical simulation of tumor development is well suited to the challenge. Building on our previous single-dose numerical simulation model of EMT6/Ro spheroids, a multi-dose irradiation response module is added and calibrated to the effective dose arising from 18 independent multi-dose treatment programs available in the experimental literature. With the developed model a constrained, non-linear, search for better performing cadidate protocols is conducted within the vicinity of two benchmarks by genetic algorithm (GA) techniques. After evaluating less than 0.01% of the potential benchmark protocol space, candidate protocols were identified by the GA which conferred an average of 9.4% (max benefit 16.5%) and 7.1% (13.3%) improvement (reduction) on tumour cell count compared to the two benchmarks, respectively. Noticing that a convergent phenomenon of the top performing protocols was their temporal synchronicity, a further series of numerical experiments was conducted with periodic time-gap protocols (10 h to 23 h), leading to the discovery that the performance of the GA search candidates could be replicated by 17-18 h periodic candidates. Further dynamic irradiation-response cell-phase analysis revealed that such periodicity cohered with latent EMT6/Ro cell-phase temporal patterning. Taken together, this study provides powerful evidence towards the hypothesis that even simple inter-fraction timing variations for a given fractional dose program may present a facile, and highly cost-effecitive means
Yeguas, Enrique; Joan-Arinyo, Robert; Victoria Luz N, Mar A
2011-01-01
The availability of a model to measure the performance of evolutionary algorithms is very important, especially when these algorithms are applied to solve problems with high computational requirements. That model would compute an index of the quality of the solution reached by the algorithm as a function of run-time. Conversely, if we fix an index of quality for the solution, the model would give the number of iterations to be expected. In this work, we develop a statistical model to describe the performance of PBIL and CHC evolutionary algorithms applied to solve the root identification problem. This problem is basic in constraint-based, geometric parametric modeling, as an instance of general constraint-satisfaction problems. The performance model is empirically validated over a benchmark with very large search spaces.
A Genetic Algorithm for Learning Significant Phrase Patterns in Radiology Reports
Patton, Robert M; Potok, Thomas E; Beckerman, Barbara G; Treadwell, Jim N
2009-01-01
Radiologists disagree with each other over the characteristics and features of what constitutes a normal mammogram and the terminology to use in the associated radiology report. Recently, the focus has been on classifying abnormal or suspicious reports, but even this process needs further layers of clustering and gradation, so that individual lesions can be more effectively classified. Using a genetic algorithm, the approach described here successfully learns phrase patterns for two distinct classes of radiology reports (normal and abnormal). These patterns can then be used as a basis for automatically analyzing, categorizing, clustering, or retrieving relevant radiology reports for the user.
Computational Performance Assessment of k-mer Counting Algorithms.
Pérez, Nelson; Gutierrez, Miguel; Vera, Nelson
2016-04-01
This article is about the assessment of several tools for k-mer counting, with the purpose to create a reference framework for bioinformatics researchers to identify computational requirements, parallelizing, advantages, disadvantages, and bottlenecks of each of the algorithms proposed in the tools. The k-mer counters evaluated in this article were BFCounter, DSK, Jellyfish, KAnalyze, KHMer, KMC2, MSPKmerCounter, Tallymer, and Turtle. Measured parameters were the following: RAM occupied space, processing time, parallelization, and read and write disk access. A dataset consisting of 36,504,800 reads was used corresponding to the 14th human chromosome. The assessment was performed for two k-mer lengths: 31 and 55. Obtained results were the following: pure Bloom filter-based tools and disk-partitioning techniques showed a lesser RAM use. The tools that took less execution time were the ones that used disk-partitioning techniques. The techniques that made the major parallelization were the ones that used disk partitioning, hash tables with lock-free approach, or multiple hash tables.
Computational Performance Assessment of k-mer Counting Algorithms.
Pérez, Nelson; Gutierrez, Miguel; Vera, Nelson
2016-04-01
This article is about the assessment of several tools for k-mer counting, with the purpose to create a reference framework for bioinformatics researchers to identify computational requirements, parallelizing, advantages, disadvantages, and bottlenecks of each of the algorithms proposed in the tools. The k-mer counters evaluated in this article were BFCounter, DSK, Jellyfish, KAnalyze, KHMer, KMC2, MSPKmerCounter, Tallymer, and Turtle. Measured parameters were the following: RAM occupied space, processing time, parallelization, and read and write disk access. A dataset consisting of 36,504,800 reads was used corresponding to the 14th human chromosome. The assessment was performed for two k-mer lengths: 31 and 55. Obtained results were the following: pure Bloom filter-based tools and disk-partitioning techniques showed a lesser RAM use. The tools that took less execution time were the ones that used disk-partitioning techniques. The techniques that made the major parallelization were the ones that used disk partitioning, hash tables with lock-free approach, or multiple hash tables. PMID:26982880
Shaswary, Elyas; Xu, Yuan; Tavakkoli, Jahan
2016-07-01
Time-delay estimation has countless applications in ultrasound medical imaging. Previously, we proposed a new time-delay estimation algorithm, which was based on the summation of the sign function to compute the time-delay estimate (Shaswary et al., 2015). We reported that the proposed algorithm performs similar to normalized cross-correlation (NCC) and sum squared differences (SSD) algorithms, even though it was significantly more computationally efficient. In this paper, we study the performance of the proposed algorithm using statistical analysis and image quality analysis in ultrasound elastography imaging. Field II simulation software was used for generation of ultrasound radio frequency (RF) echo signals for statistical analysis, and a clinical ultrasound scanner (Sonix® RP scanner, Ultrasonix Medical Corp., Richmond, BC, Canada) was used to scan a commercial ultrasound elastography tissue-mimicking phantom for image quality analysis. The statistical analysis results confirmed that, in overall, the proposed algorithm has similar performance compared to NCC and SSD algorithms. The image quality analysis results indicated that the proposed algorithm produces strain images with marginally higher signal-to-noise and contrast-to-noise ratios compared to NCC and SSD algorithms. PMID:27010697
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.
Performance of a parallel algorithm for standard cell placement on the Intel Hypercube
NASA Technical Reports Server (NTRS)
Jones, Mark; Banerjee, Prithviraj
1987-01-01
A parallel simulated annealing algorithm for standard cell placement on the Intel Hypercube is presented. A novel tree broadcasting strategy is used extensively for updating cell locations in the parallel environment. Studies on the performance of the algorithm on example industrial circuits show that it is faster and gives better final placement results than uniprocessor simulated annealing algorithms.
In-depth performance analysis of an EEG based neonatal seizure detection algorithm
Mathieson, S.; Rennie, J.; Livingstone, V.; Temko, A.; Low, E.; Pressler, R.M.; Boylan, G.B.
2016-01-01
Objective To describe a novel neurophysiology based performance analysis of automated seizure detection algorithms for neonatal EEG to characterize features of detected and non-detected seizures and causes of false detections to identify areas for algorithmic improvement. Methods EEGs of 20 term neonates were recorded (10 seizure, 10 non-seizure). Seizures were annotated by an expert and characterized using a novel set of 10 criteria. ANSeR seizure detection algorithm (SDA) seizure annotations were compared to the expert to derive detected and non-detected seizures at three SDA sensitivity thresholds. Differences in seizure characteristics between groups were compared using univariate and multivariate analysis. False detections were characterized. Results The expert detected 421 seizures. The SDA at thresholds 0.4, 0.5, 0.6 detected 60%, 54% and 45% of seizures. At all thresholds, multivariate analyses demonstrated that the odds of detecting seizure increased with 4 criteria: seizure amplitude, duration, rhythmicity and number of EEG channels involved at seizure peak. Major causes of false detections included respiration and sweat artefacts or a highly rhythmic background, often during intermediate sleep. Conclusion This rigorous analysis allows estimation of how key seizure features are exploited by SDAs. Significance This study resulted in a beta version of ANSeR with significantly improved performance. PMID:27072097
Sera White
2012-04-01
This thesis presents a research study using one year of driving data obtained from plug-in hybrid electric vehicles (PHEV) located in Sacramento and San Francisco, California to determine the effectiveness of incorporating geographic information into vehicle performance algorithms. Sacramento and San Francisco were chosen because of the availability of high resolution (1/9 arc second) digital elevation data. First, I present a method for obtaining instantaneous road slope, given a latitude and longitude, and introduce its use into common driving intensity algorithms. I show that for trips characterized by >40m of net elevation change (from key on to key off), the use of instantaneous road slope significantly changes the results of driving intensity calculations. For trips exhibiting elevation loss, algorithms ignoring road slope overestimated driving intensity by as much as 211 Wh/mile, while for trips exhibiting elevation gain these algorithms underestimated driving intensity by as much as 333 Wh/mile. Second, I describe and test an algorithm that incorporates vehicle route type into computations of city and highway fuel economy. Route type was determined by intersecting trip GPS points with ESRI StreetMap road types and assigning each trip as either city or highway route type according to whichever road type comprised the largest distance traveled. The fuel economy results produced by the geographic classification were compared to the fuel economy results produced by algorithms that assign route type based on average speed or driving style. Most results were within 1 mile per gallon ({approx}3%) of one another; the largest difference was 1.4 miles per gallon for charge depleting highway trips. The methods for acquiring and using geographic data introduced in this thesis will enable other vehicle technology researchers to incorporate geographic data into their research problems.
Performance of a parallel algorithm for standard cell placement on the Intel Hypercube
NASA Technical Reports Server (NTRS)
Jones, Mark; Banerjee, Prithviraj
1987-01-01
A parallel simulated annealing algorithm for standard cell placement that is targeted to run on the Intel Hypercube is presented. A tree broadcasting strategy that is used extensively in our algorithm for updating cell locations in the parallel environment is presented. Studies on the performance of our algorithm on example industrial circuits show that it is faster and gives better final placement results than the uniprocessor simulated annealing algorithms.
Hira, Zena M; Trigeorgis, George; Gillies, Duncan F
2014-01-01
Microarray databases are a large source of genetic data, which, upon proper analysis, could enhance our understanding of biology and medicine. Many microarray experiments have been designed to investigate the genetic mechanisms of cancer, and analytical approaches have been applied in order to classify different types of cancer or distinguish between cancerous and non-cancerous tissue. However, microarrays are high-dimensional datasets with high levels of noise and this causes problems when using machine learning methods. A popular approach to this problem is to search for a set of features that will simplify the structure and to some degree remove the noise from the data. The most widely used approach to feature extraction is principal component analysis (PCA) which assumes a multivariate Gaussian model of the data. More recently, non-linear methods have been investigated. Among these, manifold learning algorithms, for example Isomap, aim to project the data from a higher dimensional space onto a lower dimension one. We have proposed a priori manifold learning for finding a manifold in which a representative set of microarray data is fused with relevant data taken from the KEGG pathway database. Once the manifold has been constructed the raw microarray data is projected onto it and clustering and classification can take place. In contrast to earlier fusion based methods, the prior knowledge from the KEGG databases is not used in, and does not bias the classification process--it merely acts as an aid to find the best space in which to search the data. In our experiments we have found that using our new manifold method gives better classification results than using either PCA or conventional Isomap. PMID:24595155
Dual Engine application of the Performance Seeking Control algorithm
NASA Technical Reports Server (NTRS)
Mueller, F. D.; Nobbs, S. G.; Stewart, J. F.
1993-01-01
The Dual Engine Performance Seeking Control (PSC) flight/propulsion optimization program has been developed and will be flown during the second quarter of 1993. Previously, only single engine optimization was possible due to the limited capability of the on-board computer. The implementation of Dual Engine PSC has been made possible with the addition of a new state-of-the-art, higher throughput computer. As a result, the single engine PSC performance improvements already flown will be demonstrated on both engines, simultaneously. Dual Engine PSC will make it possible to directly compare aircraft performance with and without the improvements generated by PSC. With the additional thrust achieved with PSC, significant improvements in acceleration times and time to climb will be possible. PSC is also able to reduce deceleration time from supersonic speeds. This paper traces the history of the PSC program, describes the basic components of PSC, discusses the development and implementation of Dual Engine PSC including additions to the code, and presents predictions of the impact of Dual Engine PSC on aircraft performance.
Zhao, Wei; Niu, Tianye; Xing, Lei; Xie, Yaoqin; Xiong, Guanglei; Elmore, Kimberly; Zhu, Jun; Wang, Luyao; Min, James K
2016-02-01
Increased noise is a general concern for dual-energy material decomposition. Here, we develop an image-domain material decomposition algorithm for dual-energy CT (DECT) by incorporating an edge-preserving filter into the Local HighlY constrained backPRojection reconstruction (HYPR-LR) framework. With effective use of the non-local mean, the proposed algorithm, which is referred to as HYPR-NLM, reduces the noise in dual-energy decomposition while preserving the accuracy of quantitative measurement and spatial resolution of the material-specific dual-energy images. We demonstrate the noise reduction and resolution preservation of the algorithm with an iodine concentrate numerical phantom by comparing the HYPR-NLM algorithm to the direct matrix inversion, HYPR-LR and iterative image-domain material decomposition (Iter-DECT). We also show the superior performance of the HYPR-NLM over the existing methods by using two sets of cardiac perfusing imaging data. The DECT material decomposition comparison study shows that all four algorithms yield acceptable quantitative measurements of iodine concentrate. Direct matrix inversion yields the highest noise level, followed by HYPR-LR and Iter-DECT. HYPR-NLM in an iterative formulation significantly reduces image noise and the image noise is comparable to or even lower than that generated using Iter-DECT. For the HYPR-NLM method, there are marginal edge effects in the difference image, suggesting the high-frequency details are well preserved. In addition, when the search window size increases from to , there are no significant changes or marginal edge effects in the HYPR-NLM difference images. The reference drawn from the comparison study includes: (1) HYPR-NLM significantly reduces the DECT material decomposition noise while preserving quantitative measurements and high-frequency edge information, and (2) HYPR-NLM is robust with respect to parameter selection.
NASA Astrophysics Data System (ADS)
Zhao, Wei; Niu, Tianye; Xing, Lei; Xie, Yaoqin; Xiong, Guanglei; Elmore, Kimberly; Zhu, Jun; Wang, Luyao; Min, James K.
2016-02-01
Increased noise is a general concern for dual-energy material decomposition. Here, we develop an image-domain material decomposition algorithm for dual-energy CT (DECT) by incorporating an edge-preserving filter into the Local HighlY constrained backPRojection reconstruction (HYPR-LR) framework. With effective use of the non-local mean, the proposed algorithm, which is referred to as HYPR-NLM, reduces the noise in dual-energy decomposition while preserving the accuracy of quantitative measurement and spatial resolution of the material-specific dual-energy images. We demonstrate the noise reduction and resolution preservation of the algorithm with an iodine concentrate numerical phantom by comparing the HYPR-NLM algorithm to the direct matrix inversion, HYPR-LR and iterative image-domain material decomposition (Iter-DECT). We also show the superior performance of the HYPR-NLM over the existing methods by using two sets of cardiac perfusing imaging data. The DECT material decomposition comparison study shows that all four algorithms yield acceptable quantitative measurements of iodine concentrate. Direct matrix inversion yields the highest noise level, followed by HYPR-LR and Iter-DECT. HYPR-NLM in an iterative formulation significantly reduces image noise and the image noise is comparable to or even lower than that generated using Iter-DECT. For the HYPR-NLM method, there are marginal edge effects in the difference image, suggesting the high-frequency details are well preserved. In addition, when the search window size increases from 11× 11 to 19× 19 , there are no significant changes or marginal edge effects in the HYPR-NLM difference images. The reference drawn from the comparison study includes: (1) HYPR-NLM significantly reduces the DECT material decomposition noise while preserving quantitative measurements and high-frequency edge information, and (2) HYPR-NLM is robust with respect to parameter selection.
Subsonic flight test evaluation of a performance seeking control algorithm on an F-15 airplane
NASA Technical Reports Server (NTRS)
Gilyard, Glenn B.; Orme, John S.
1992-01-01
The subsonic flight test evaluation phase of the NASA F-15 (powered by F 100 engines) performance seeking control program was completed for single-engine operation at part- and military-power settings. The subsonic performance seeking control algorithm optimizes the quasi-steady-state performance of the propulsion system for three modes of operation. The minimum fuel flow mode minimizes fuel consumption. The minimum thrust mode maximizes thrust at military power. Decreases in thrust-specific fuel consumption of 1 to 2 percent were measured in the minimum fuel flow mode; these fuel savings are significant, especially for supersonic cruise aircraft. Decreases of up to approximately 100 degree R in fan turbine inlet temperature were measured in the minimum temperature mode. Temperature reductions of this magnitude would more than double turbine life if inlet temperature was the only life factor. Measured thrust increases of up to approximately 15 percent in the maximum thrust mode cause substantial increases in aircraft acceleration. The system dynamics of the closed-loop algorithm operation were good. The subsonic flight phase has validated the performance seeking control technology, which can significantly benefit the next generation of fighter and transport aircraft.
Diagnostic performance of line-immunoassay based algorithms for incident HIV-1 infection
2012-01-01
Background Serologic testing algorithms for recent HIV seroconversion (STARHS) provide important information for HIV surveillance. We have previously demonstrated that a patient's antibody reaction pattern in a confirmatory line immunoassay (INNO-LIA™ HIV I/II Score) provides information on the duration of infection, which is unaffected by clinical, immunological and viral variables. In this report we have set out to determine the diagnostic performance of Inno-Lia algorithms for identifying incident infections in patients with known duration of infection and evaluated the algorithms in annual cohorts of HIV notifications. Methods Diagnostic sensitivity was determined in 527 treatment-naive patients infected for up to 12 months. Specificity was determined in 740 patients infected for longer than 12 months. Plasma was tested by Inno-Lia and classified as either incident (< = 12 m) or older infection by 26 different algorithms. Incident infection rates (IIR) were calculated based on diagnostic sensitivity and specificity of each algorithm and the rule that the total of incident results is the sum of true-incident and false-incident results, which can be calculated by means of the pre-determined sensitivity and specificity. Results The 10 best algorithms had a mean raw sensitivity of 59.4% and a mean specificity of 95.1%. Adjustment for overrepresentation of patients in the first quarter year of infection further reduced the sensitivity. In the preferred model, the mean adjusted sensitivity was 37.4%. Application of the 10 best algorithms to four annual cohorts of HIV-1 notifications totalling 2'595 patients yielded a mean IIR of 0.35 in 2005/6 (baseline) and of 0.45, 0.42 and 0.35 in 2008, 2009 and 2010, respectively. The increase between baseline and 2008 and the ensuing decreases were highly significant. Other adjustment models yielded different absolute IIR, although the relative changes between the cohorts were identical for all models. Conclusions The method
Kossobokov, V.G.; Romashkova, L.L.; Keilis-Borok, V. I.; Healy, J.H.
1999-01-01
Algorithms M8 and MSc (i.e., the Mendocino Scenario) were used in a real-time intermediate-term research prediction of the strongest earthquakes in the Circum-Pacific seismic belt. Predictions are made by M8 first. Then, the areas of alarm are reduced by MSc at the cost that some earthquakes are missed in the second approximation of prediction. In 1992-1997, five earthquakes of magnitude 8 and above occurred in the test area: all of them were predicted by M8 and MSc identified correctly the locations of four of them. The space-time volume of the alarms is 36% and 18%, correspondingly, when estimated with a normalized product measure of empirical distribution of epicenters and uniform time. The statistical significance of the achieved results is beyond 99% both for M8 and MSc. For magnitude 7.5 + , 10 out of 19 earthquakes were predicted by M8 in 40% and five were predicted by M8-MSc in 13% of the total volume considered. This implies a significance level of 81% for M8 and 92% for M8-MSc. The lower significance levels might result from a global change in seismic regime in 1993-1996, when the rate of the largest events has doubled and all of them become exclusively normal or reversed faults. The predictions are fully reproducible; the algorithms M8 and MSc in complete formal definitions were published before we started our experiment [Keilis-Borok, V.I., Kossobokov, V.G., 1990. Premonitory activation of seismic flow: Algorithm M8, Phys. Earth and Planet. Inter. 61, 73-83; Kossobokov, V.G., Keilis-Borok, V.I., Smith, S.W., 1990. Localization of intermediate-term earthquake prediction, J. Geophys. Res., 95, 19763-19772; Healy, J.H., Kossobokov, V.G., Dewey, J.W., 1992. A test to evaluate the earthquake prediction algorithm, M8. U.S. Geol. Surv. OFR 92-401]. M8 is available from the IASPEI Software Library [Healy, J.H., Keilis-Borok, V.I., Lee, W.H.K. (Eds.), 1997. Algorithms for Earthquake Statistics and Prediction, Vol. 6. IASPEI Software Library]. ?? 1999 Elsevier
Helles, Glennie
2008-04-01
Protein structure prediction is one of the major challenges in bioinformatics today. Throughout the past five decades, many different algorithmic approaches have been attempted, and although progress has been made the problem remains unsolvable even for many small proteins. While the general objective is to predict the three-dimensional structure from primary sequence, our current knowledge and computational power are simply insufficient to solve a problem of such high complexity. Some prediction algorithms do, however, appear to perform better than others, although it is not always obvious which ones they are and it is perhaps even less obvious why that is. In this review, the reported performance results from 18 different recently published prediction algorithms are compared. Furthermore, the general algorithmic settings most likely responsible for the difference in the reported performance are identified, and the specific settings of each of the 18 prediction algorithms are also compared. The average normalized r.m.s.d. scores reported range from 11.17 to 3.48. With a performance measure including both r.m.s.d. scores and CPU time, the currently best-performing prediction algorithm is identified to be the I-TASSER algorithm. Two of the algorithmic settings--protein representation and fragment assembly--were found to have definite positive influence on the running time and the predicted structures, respectively. There thus appears to be a clear benefit from incorporating this knowledge in the design of new prediction algorithms.
Performance evaluation of relativistic electromagnetic particle in cell algorithms in CPU and GPU
NASA Astrophysics Data System (ADS)
Fonseca, Ricardo; Abreu, Paulo; Decyk, Viktor
2010-11-01
The complexity of the phenomena involved in several relevante plasma physics scenarios, where highly nonlinear and kinetic processes dominate, makes purely theoretical descriptions impossible. Further understanding of these scenarios requires detailed numerical modelling, but fully relativistic particle-in-cell codes such as OSIRIS [1] are computationally intensive. Recently graphics processing units (GPUs), offering peak theoretical performances of ˜ 1 TFlop/s for general purpose calculations, have received significant attention as an atractive alternative to CPUs for plasma modeling. In this work we perform a detailed performance evaluation of an electromagnetic fully relativistic particle in cell code in both GPUs and CPUs for production runs, focusing on the relative strengths and weaknesses of both architectures for all major algorithm sections, including particle push, current deposition, field solver, and also diagnostics. [4pt] [1] R. A. Fonseca et al., LNCS 2331, 342, (2002)
NASA Technical Reports Server (NTRS)
Kasturi, Rangachar; Camps, Octavia; Coraor, Lee
2000-01-01
The research reported here is a part of NASA's Synthetic Vision System (SVS) project for the development of a High Speed Civil Transport Aircraft (HSCT). One of the components of the SVS is a module for detection of potential obstacles in the aircraft's flight path by analyzing the images captured by an on-board camera in real-time. Design of such a module includes the selection and characterization of robust, reliable, and fast techniques and their implementation for execution in real-time. This report describes the results of our research in realizing such a design. It is organized into three parts. Part I. Data modeling and camera characterization; Part II. Algorithms for detecting airborne obstacles; and Part III. Real time implementation of obstacle detection algorithms on the Datacube MaxPCI architecture. A list of publications resulting from this grant as well as a list of relevant publications resulting from prior NASA grants on this topic are presented.
A high performance hardware implementation image encryption with AES algorithm
NASA Astrophysics Data System (ADS)
Farmani, Ali; Jafari, Mohamad; Miremadi, Seyed Sohrab
2011-06-01
This paper describes implementation of a high-speed encryption algorithm with high throughput for encrypting the image. Therefore, we select a highly secured symmetric key encryption algorithm AES(Advanced Encryption Standard), in order to increase the speed and throughput using pipeline technique in four stages, control unit based on logic gates, optimal design of multiplier blocks in mixcolumn phase and simultaneous production keys and rounds. Such procedure makes AES suitable for fast image encryption. Implementation of a 128-bit AES on FPGA of Altra company has been done and the results are as follow: throughput, 6 Gbps in 471MHz. The time of encrypting in tested image with 32*32 size is 1.15ms.
GOES-R Geostationary Lightning Mapper Performance Specifications and Algorithms
NASA Technical Reports Server (NTRS)
Mach, Douglas M.; Goodman, Steven J.; Blakeslee, Richard J.; Koshak, William J.; Petersen, William A.; Boldi, Robert A.; Carey, Lawrence D.; Bateman, Monte G.; Buchler, Dennis E.; McCaul, E. William, Jr.
2008-01-01
The Geostationary Lightning Mapper (GLM) is a single channel, near-IR imager/optical transient event detector, used to detect, locate and measure total lightning activity over the full-disk. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series will carry a GLM that will provide continuous day and night observations of lightning. The mission objectives for the GLM are to: (1) Provide continuous, full-disk lightning measurements for storm warning and nowcasting, (2) Provide early warning of tornadic activity, and (2) Accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997- present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 13 year data record of global lightning activity. GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms and applications. The science data will consist of lightning "events", "groups", and "flashes". The algorithm is being designed to be an efficient user of the computational resources. This may include parallelization of the code and the concept of sub-dividing the GLM FOV into regions to be processed in parallel. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds (e.g., Lightning Mapping Arrays in North Alabama, Oklahoma, Central Florida, and the Washington DC Metropolitan area) are being used to develop the prelaunch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution.
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.
Monte Carlo Particle Transport: Algorithm and Performance Overview
Gentile, N; Procassini, R; Scott, H
2005-06-02
Monte Carlo methods are frequently used for neutron and radiation transport. These methods have several advantages, such as relative ease of programming and dealing with complex meshes. Disadvantages include long run times and statistical noise. Monte Carlo photon transport calculations also often suffer from inaccuracies in matter temperature due to the lack of implicitness. In this paper we discuss the Monte Carlo algorithm as it is applied to neutron and photon transport, detail the differences between neutron and photon Monte Carlo, and give an overview of the ways the numerical method has been modified to deal with issues that arise in photon Monte Carlo simulations.
NASA Astrophysics Data System (ADS)
Zheng, Jun-Xi; Zhang, Ping; Li, Fang; Du, Guang-Long
2016-09-01
Although the sequence-dependent setup times flowshop problem with the total weighted tardiness minimization objective exists widely in industry, work on the problem has been scant in the existing literature. To the authors' best knowledge, the NEH?EWDD heuristic and the Iterated Greedy (IG) algorithm with descent local search have been regarded as the high performing heuristic and the state-of-the-art algorithm for the problem, which are both based on insertion search. In this article firstly, an efficient backtracking algorithm and a novel heuristic (HPIS) are presented for insertion search. Accordingly, two heuristics are introduced, one is NEH?EWDD with HPIS for insertion search, and the other is the combination of NEH?EWDD and both the two methods. Furthermore, the authors improve the IG algorithm with the proposed methods. Finally, experimental results show that both the proposed heuristics and the improved IG (IG*) significantly outperform the original ones.
2014-01-01
Background Eukaryotic transcriptional regulation is known to be highly connected through the networks of cooperative transcription factors (TFs). Measuring the cooperativity of TFs is helpful for understanding the biological relevance of these TFs in regulating genes. The recent advances in computational techniques led to various predictions of cooperative TF pairs in yeast. As each algorithm integrated different data resources and was developed based on different rationales, it possessed its own merit and claimed outperforming others. However, the claim was prone to subjectivity because each algorithm compared with only a few other algorithms and only used a small set of performance indices for comparison. This motivated us to propose a series of indices to objectively evaluate the prediction performance of existing algorithms. And based on the proposed performance indices, we conducted a comprehensive performance evaluation. Results We collected 14 sets of predicted cooperative TF pairs (PCTFPs) in yeast from 14 existing algorithms in the literature. Using the eight performance indices we adopted/proposed, the cooperativity of each PCTFP was measured and a ranking score according to the mean cooperativity of the set was given to each set of PCTFPs under evaluation for each performance index. It was seen that the ranking scores of a set of PCTFPs vary with different performance indices, implying that an algorithm used in predicting cooperative TF pairs is of strength somewhere but may be of weakness elsewhere. We finally made a comprehensive ranking for these 14 sets. The results showed that Wang J's study obtained the best performance evaluation on the prediction of cooperative TF pairs in yeast. Conclusions In this study, we adopted/proposed eight performance indices to make a comprehensive performance evaluation on the prediction results of 14 existing cooperative TFs identification algorithms. Most importantly, these proposed indices can be easily applied to
Performance evaluation of algorithms for SAW-based temperature measurement.
Schuster, Stefan; Scheiblhofer, Stefan; Reindl, Leonhard; Stelzer, Andreas
2006-06-01
Whenever harsh environmental conditions such as high temperatures, accelerations, radiation, etc., prohibit usage of standard temperature sensors, surface acoustic wave-based temperature sensors are the first choice for highly reliable wireless temperature measurement. Interrogation of these sensors is often based on frequency modulated or frequency stepped continuous wave-based radars (FMCW/FSCW). We investigate known algorithms regarding their achievable temperature accuracy and their applicability in practice. Furthermore, some general rules of thumb for FMCW/FSCW radar-based range estimation by means of the Cramer-Rao lower bound (CRLB) for frequency and phase estimation are provided. The theoretical results are verified on both simulated and measured data. PMID:16846150
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.
NASA Astrophysics Data System (ADS)
Korolev, A.; Field, P. R.
2014-10-01
Shattering presents a serious obstacle to current airborne in-situ methods of characterizing the microphysical properties of ice clouds. Small shattered fragments result from the impact of natural ice crystals with the forward parts of aircraft-mounted measurement probes. The presence of these shattered fragments may result in a significant overestimation of the measured concentration of small ice crystals, contaminating the measurement of the ice particle size distribution (PSD). One method of identifying shattered particles is to use an interarrival time algorithm. This method is based on the assumption that shattered fragments form spatial clusters that have short interarrival times between particles, relative to natural particles, when they pass through the sample volume of the probe. The interarrival time algorithm is a successful technique for the classification of shattering artifacts and natural particles. This study assesses the limitations and efficiency of the interarrival time algorithm. The analysis has been performed using simultaneous measurements of 2-D optical array probes with the standard and antishattering "K-tips" collected during the Airborne Icing Instrumentation Experiment (AIIE). It is shown that the efficiency of the algorithm depends on ice particle size, concentration and habit. Additional numerical simulations indicate that the effectiveness of the interarrival time algorithm to eliminate shattering artifacts can be significantly restricted in some cases. Improvements to the interarrival time algorithm are discussed.
On the estimation algorithm used in adaptive performance optimization of turbofan engines
NASA Technical Reports Server (NTRS)
Espana, Martin D.; Gilyard, Glenn B.
1993-01-01
The performance seeking control algorithm is designed to continuously optimize the performance of propulsion systems. The performance seeking control algorithm uses a nominal model of the propulsion system and estimates, in flight, the engine deviation parameters characterizing the engine deviations with respect to nominal conditions. In practice, because of measurement biases and/or model uncertainties, the estimated engine deviation parameters may not reflect the engine's actual off-nominal condition. This factor has a necessary impact on the overall performance seeking control scheme exacerbated by the open-loop character of the algorithm. The effects produced by unknown measurement biases over the estimation algorithm are evaluated. This evaluation allows for identification of the most critical measurements for application of the performance seeking control algorithm to an F100 engine. An equivalence relation between the biases and engine deviation parameters stems from an observability study; therefore, it is undecided whether the estimated engine deviation parameters represent the actual engine deviation or whether they simply reflect the measurement biases. A new algorithm, based on the engine's (steady-state) optimization model, is proposed and tested with flight data. When compared with previous Kalman filter schemes, based on local engine dynamic models, the new algorithm is easier to design and tune and it reduces the computational burden of the onboard computer.
Performance of Thorup's Shortest Path Algorithm for Large-Scale Network Simulation
NASA Astrophysics Data System (ADS)
Sakumoto, Yusuke; Ohsaki, Hiroyuki; Imase, Makoto
In this paper, we investigate the performance of Thorup's algorithm by comparing it to Dijkstra's algorithm for large-scale network simulations. One of the challenges toward the realization of large-scale network simulations is the efficient execution to find shortest paths in a graph with N vertices and M edges. The time complexity for solving a single-source shortest path (SSSP) problem with Dijkstra's algorithm with a binary heap (DIJKSTRA-BH) is O((M+N)log N). An sophisticated algorithm called Thorup's algorithm has been proposed. The original version of Thorup's algorithm (THORUP-FR) has the time complexity of O(M+N). A simplified version of Thorup's algorithm (THORUP-KL) has the time complexity of O(Mα(N)+N) where α(N) is the functional inverse of the Ackerman function. In this paper, we compare the performances (i.e., execution time and memory consumption) of THORUP-KL and DIJKSTRA-BH since it is known that THORUP-FR is at least ten times slower than Dijkstra's algorithm with a Fibonaccii heap. We find that (1) THORUP-KL is almost always faster than DIJKSTRA-BH for large-scale network simulations, and (2) the performances of THORUP-KL and DIJKSTRA-BH deviate from their time complexities due to the presence of the memory cache in the microprocessor.
NASA Astrophysics Data System (ADS)
Qureshi, Kalim; Rashid, Haroon
In this paper we practically compared the performance of three blocked based parallel multiplication algorithms with simple fixed size runtime task scheduling strategy on homogeneous cluster of workstations. Parallel Virtual Machine (PVM) was used for this study.
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.
Subsonic flight test evaluation of a performance seeking control algorithm on an F-15 airplane
NASA Technical Reports Server (NTRS)
Gilyard, Glenn B.; Orme, John S.
1992-01-01
The subsonic flight test evaluation phase of the NASA4 F-15 (powered by F100 engines) performance-seeking control program was completed for single-engine operation at part- and military-power settings. The subsonic performance-seeking control algorithm optimizes the quasi-steady-state performance of the propulsion system for three modes of operation: the minimum-fuel-flow mode, the minimum-temperature mode, and the maximum-thrust mode. Decreases in thrust-specific fuel consumption of 1 to 2 percent were measured in the minimum-fuel-flow mode; these fuel savings are significant especially for supersonic cruise aircraft. Decreases of up to approximately 100 R in fan turbine inlet temperature were measured in the minimum-temperature mode. Temperature reductions of this magnitude would more than double turbine life if inlet temperature was the only life factor. Measured thrust increases of up to approximately 15 percent in the maximum-thrust mode cause substantial increases in aircraft acceleration. The subsonic flight phase has validated the performance-seeking control technology which can significantly benefit the next generation of fighter and transport aircraft.
Modular architecture for high performance implementation of the FFT algorithm
Spiecha, K. ); Jarocki, R. )
1990-12-01
This paper presents a new VLSI-oriented architecture to compute discrete Fourier transform. It consists of a homogeneous structure of processing elements. The structure has a performance equal to 1/{ital t} transforms per second, where {ital t} is the time needed for the execution of a single butterfly computation or the time needed for the collection of a complete vector of samples, whichever occurs to be longer. Although the system is not optimal (it achieves {ital O(N}{sup 3} log{sup 4} {ital N)} area time{sup 2} performance), the architecture is modular and makes it possible to design a system which performs FFT of any size without any extra circuitry. Moreover, the system can provide a built-in self-test and self-restructuring. The system consists of only one type of integrated circuit, its structure being irrespective of the transform size, which considerably reduces the cost of implementation.
Algorithms and architectures for high performance analysis of semantic graphs.
Hendrickson, Bruce Alan
2005-09-01
analysis. Since intelligence datasets can be extremely large, the focus of this work is on the use of parallel computers. We have been working to develop scalable parallel algorithms that will be at the core of a semantic graph analysis infrastructure. Our work has involved two different thrusts, corresponding to two different computer architectures. The first architecture of interest is distributed memory, message passing computers. These machines are ubiquitous and affordable, but they are challenging targets for graph algorithms. Much of our distributed-memory work to date has been collaborative with researchers at Lawrence Livermore National Laboratory and has focused on finding short paths on distributed memory parallel machines. Our implementation on 32K processors of BlueGene/Light finds shortest paths between two specified vertices in just over a second for random graphs with 4 billion vertices.
Fong, Simon; Deb, Suash; Yang, Xin-She; Zhuang, Yan
2014-01-01
Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario. PMID:25202730
Deb, Suash; Yang, Xin-She
2014-01-01
Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario. PMID:25202730
Fong, Simon; Deb, Suash; Yang, Xin-She; Zhuang, Yan
2014-01-01
Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario.
NASA Technical Reports Server (NTRS)
Battiste, Vernol; Lawton, George; Lachter, Joel; Brandt, Summer; Koteskey, Robert; Dao, Arik-Quang; Kraut, Josh; Ligda, Sarah; Johnson, Walter W.
2012-01-01
Managing the interval between arrival aircraft is a major part of the en route and TRACON controller s job. In an effort to reduce controller workload and low altitude vectoring, algorithms have been developed to allow pilots to take responsibility for, achieve and maintain proper spacing. Additionally, algorithms have been developed to create dynamic weather-free arrival routes in the presence of convective weather. In a recent study we examined an algorithm to handle dynamic re-routing in the presence of convective weather and two distinct spacing algorithms. The spacing algorithms originated from different core algorithms; both were enhanced with trajectory intent data for the study. These two algorithms were used simultaneously in a human-in-the-loop (HITL) simulation where pilots performed weather-impacted arrival operations into Louisville International Airport while also performing interval management (IM) on some trials. The controllers retained responsibility for separation and for managing the en route airspace and some trials managing IM. The goal was a stress test of dynamic arrival algorithms with ground and airborne spacing concepts. The flight deck spacing algorithms or controller managed spacing not only had to be robust to the dynamic nature of aircraft re-routing around weather but also had to be compatible with two alternative algorithms for achieving the spacing goal. Flight deck interval management spacing in this simulation provided a clear reduction in controller workload relative to when controllers were responsible for spacing the aircraft. At the same time, spacing was much less variable with the flight deck automated spacing. Even though the approaches taken by the two spacing algorithms to achieve the interval management goals were slightly different they seem to be simpatico in achieving the interval management goal of 130 sec by the TRACON boundary.
St Hilaire, Melissa A; Sullivan, Jason P; Anderson, Clare; Cohen, Daniel A; Barger, Laura K; Lockley, Steven W; Klerman, Elizabeth B
2013-01-01
There is currently no "gold standard" marker of cognitive performance impairment resulting from sleep loss. We utilized pattern recognition algorithms to determine which features of data collected under controlled laboratory conditions could most reliably identify cognitive performance impairment in response to sleep loss using data from only one testing session, such as would occur in the "real world" or field conditions. A training set for testing the pattern recognition algorithms was developed using objective Psychomotor Vigilance Task (PVT) and subjective Karolinska Sleepiness Scale (KSS) data collected from laboratory studies during which subjects were sleep deprived for 26-52h. The algorithm was then tested in data from both laboratory and field experiments. The pattern recognition algorithm was able to identify performance impairment with a single testing session in individuals studied under laboratory conditions using PVT, KSS, length of time awake and time of day information with sensitivity and specificity as high as 82%. When this algorithm was tested on data collected under real-world conditions from individuals whose data were not in the training set, accuracy of predictions for individuals categorized with low performance impairment were as high as 98%. Predictions for medium and severe performance impairment were less accurate. We conclude that pattern recognition algorithms may be a promising method for identifying performance impairment in individuals using only current information about the individual's behavior. Single testing features (e.g., number of PVT lapses) with high correlation with performance impairment in the laboratory setting may not be the best indicators of performance impairment under real-world conditions. Pattern recognition algorithms should be further tested for their ability to be used in conjunction with other assessments of sleepiness in real-world conditions to quantify performance impairment in response to sleep loss.
St. Hilaire, Melissa A.; Sullivan, Jason P.; Anderson, Clare; Cohen, Daniel A.; Barger, Laura K.; Lockley, Steven W.; Klerman, Elizabeth B.
2012-01-01
There is currently no “gold standard” marker of cognitive performance impairment resulting from sleep loss. We utilized pattern recognition algorithms to determine which features of data collected under controlled laboratory conditions could most reliably identify cognitive performance impairment in response to sleep loss using data from only one testing session, such as would occur in the “real world” or field conditions. A training set for testing the pattern recognition algorithms was developed using objective Psychomotor Vigilance Task (PVT) and subjective Karolinska Sleepiness Scale (KSS) data collected from laboratory studies during which subjects were sleep deprived for 26 – 52 hours. The algorithm was then tested in data from both laboratory and field experiments. The pattern recognition algorithm was able to identify performance impairment with a single testing session in individuals studied under laboratory conditions using PVT, KSS, length of time awake and time of day information with sensitivity and specificity as high as 82%. When this algorithm was tested on data collected under real-world conditions from individuals whose data were not in the training set, accuracy of predictions for individuals categorized with low performance impairment were as high as 98%. Predictions for medium and severe performance impairment were less accurate. We conclude that pattern recognition algorithms may be a promising method for identifying performance impairment in individuals using only current information about the individual’s behavior. Single testing features (e.g., number of PVT lapses) with high correlation with performance impairment in the laboratory setting may not be the best indicators of performance impairment under real-world conditions. Pattern recognition algorithms should be further tested for their ability to be used in conjunction with other assessments of sleepiness in real-world conditions to quantify performance impairment in
Ding, Xiaoyu; Lee, Jong-Hwan; Lee, Seong-Whan
2013-04-01
Nonnegative matrix factorization (NMF) is a blind source separation (BSS) algorithm which is based on the distinct constraint of nonnegativity of the estimated parameters as well as on the measured data. In this study, according to the potential feasibility of NMF for fMRI data, the four most popular NMF algorithms, corresponding to the following two types of (1) least-squares based update [i.e., alternating least-squares NMF (ALSNMF) and projected gradient descent NMF] and (2) multiplicative update (i.e., NMF based on Euclidean distance and NMF based on divergence cost function), were investigated by using them to estimate task-related neuronal activities. These algorithms were applied firstly to individual data from a single subject and, subsequently, to group data sets from multiple subjects. On the single-subject level, although all four algorithms detected task-related activation from simulated data, the performance of multiplicative update NMFs was significantly deteriorated when evaluated using visuomotor task fMRI data, for which they failed in estimating any task-related neuronal activities. In group-level analysis on both simulated data and real fMRI data, ALSNMF outperformed the other three algorithms. The presented findings may suggest that ALSNMF appears to be the most promising option among the tested NMF algorithms to extract task-related neuronal activities from fMRI data.
Performance Assessment Method for a Forged Fingerprint Detection Algorithm
NASA Astrophysics Data System (ADS)
Shin, Yong Nyuo; Jun, In-Kyung; Kim, Hyun; Shin, Woochang
The threat of invasion of privacy and of the illegal appropriation of information both increase with the expansion of the biometrics service environment to open systems. However, while certificates or smart cards can easily be cancelled and reissued if found to be missing, there is no way to recover the unique biometric information of an individual following a security breach. With the recognition that this threat factor may disrupt the large-scale civil service operations approaching implementation, such as electronic ID cards and e-Government systems, many agencies and vendors around the world continue to develop forged fingerprint detection technology, but no objective performance assessment method has, to date, been reported. Therefore, in this paper, we propose a methodology designed to evaluate the objective performance of the forged fingerprint detection technology that is currently attracting a great deal of attention.
Performance of multiprocessors and parallel algorithms: Quick-sort, a case study
Patil, I.M.
1989-01-01
Performance of parallel algorithms on multiprocessors has been traditionally analyzed by looking at either the algorithm or the architecture of the multiprocessor system. However, it is important to study the combined effect of both these factors in order to evaluate and predict performance. A different methodology based on approximate trace-driven simulation is adopted in this thesis to study the performance of a class of non-numerical algorithms. Performance of parallel quick-sort and parallel quick-merge sort is investigated in order to demonstrate the methodology as well as develop an understanding of the limitations imposed by a cache-based single bus environment on achievable speedup. A wide range of issues including the effect of cache parameters, coherency protocol, scheduling mechanisms and technology effects are discussed in the context of performance of the two versions of parallel quick-sort.
Fateen, Seif-Eddeen K; Bonilla-Petriciolet, Adrian
2014-01-01
The search for reliable and efficient global optimization algorithms for solving phase stability and phase equilibrium problems in applied thermodynamics is an ongoing area of research. In this study, we evaluated and compared the reliability and efficiency of eight selected nature-inspired metaheuristic algorithms for solving difficult phase stability and phase equilibrium problems. These algorithms are the cuckoo search (CS), intelligent firefly (IFA), bat (BA), artificial bee colony (ABC), MAKHA, a hybrid between monkey algorithm and krill herd algorithm, covariance matrix adaptation evolution strategy (CMAES), magnetic charged system search (MCSS), and bare bones particle swarm optimization (BBPSO). The results clearly showed that CS is the most reliable of all methods as it successfully solved all thermodynamic problems tested in this study. CS proved to be a promising nature-inspired optimization method to perform applied thermodynamic calculations for process design. PMID:24967430
He, Lifeng; Chao, Yuyan
2015-09-01
Labeling connected components and calculating the Euler number in a binary image are two fundamental processes for computer vision and pattern recognition. This paper presents an ingenious method for identifying a hole in a binary image in the first scan of connected-component labeling. Our algorithm can perform connected component labeling and Euler number computing simultaneously, and it can also calculate the connected component (object) number and the hole number efficiently. The additional cost for calculating the hole number is only O(H) , where H is the hole number in the image. Our algorithm can be implemented almost in the same way as a conventional equivalent-label-set-based connected-component labeling algorithm. We prove the correctness of our algorithm and use experimental results for various kinds of images to demonstrate the power of our algorithm.
Psychometric correlates of the effects of image-enhancing algorithms on visual performance
NASA Astrophysics Data System (ADS)
Reis, George A.; Neriani, Kelly E.; Pinkus, Alan R.; Heft, Eric L.
2006-05-01
Future military imaging devices will have computational capabilities that will allow agile, real-time image enhancement. In preparing for such devices, numerous image enhancement algorithms should be studied. However, these algorithms need evaluating in terms of human visual performance using military-relevant imagery. Evaluating these algorithms through objective performance measures requires extensive time and resources. We investigated several subjective methodologies for down-selecting algorithms to be studied in future research. Degraded imagery was processed using six algorithms and then ranked along with the original non-degraded and degraded imagery through the method of paired comparisons and the method of magnitude estimation, in terms of subjective attitude. These rankings were then compared to objective performance measures: reaction times and errors in finding targets in the processed imagery. In general, we found associations between subjective and objective measures. This leads us to believe that subjective assessment may provide an easy and fast way for down-selecting algorithms but at the same time should not be used in place of objective performance-based measures.
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.
Gropp, William D.
2014-06-23
With the coming end of Moore's law, it has become essential to develop new algorithms and techniques that can provide the performance needed by demanding computational science applications, especially those that are part of the DOE science mission. This work was part of a multi-institution, multi-investigator project that explored several approaches to develop algorithms that would be effective at the extreme scales and with the complex processor architectures that are expected at the end of this decade. The work by this group developed new performance models that have already helped guide the development of highly scalable versions of an algebraic multigrid solver, new programming approaches designed to support numerical algorithms on heterogeneous architectures, and a new, more scalable version of conjugate gradient, an important algorithm in the solution of very large linear systems of equations.
Performance comparison of some evolutionary algorithms on job shop scheduling problems
NASA Astrophysics Data System (ADS)
Mishra, S. K.; Rao, C. S. P.
2016-09-01
Job Shop Scheduling as a state space search problem belonging to NP-hard category due to its complexity and combinational explosion of states. Several naturally inspire evolutionary methods have been developed to solve Job Shop Scheduling Problems. In this paper the evolutionary methods namely Particles Swarm Optimization, Artificial Intelligence, Invasive Weed Optimization, Bacterial Foraging Optimization, Music Based Harmony Search Algorithms are applied and find tuned to model and solve Job Shop Scheduling Problems. To compare about 250 Bench Mark instances have been used to evaluate the performance of these algorithms. The capabilities of each these algorithms in solving Job Shop Scheduling Problems are outlined.
Review of tandem repeat search tools: a systematic approach to evaluating algorithmic performance.
Lim, Kian Guan; Kwoh, Chee Keong; Hsu, Li Yang; Wirawan, Adrianto
2013-01-01
The prevalence of tandem repeats in eukaryotic genomes and their association with a number of genetic diseases has raised considerable interest in locating these repeats. Over the last 10-15 years, numerous tools have been developed for searching tandem repeats, but differences in the search algorithms adopted and difficulties with parameter settings have confounded many users resulting in widely varying results. In this review, we have systematically separated the algorithmic aspect of the search tools from the influence of the parameter settings. We hope that this will give a better understanding of how the tools differ in algorithmic performance, their inherent constraints and how one should approach in evaluating and selecting them.
Performance evaluation of recommendation algorithms on Internet of Things services
NASA Astrophysics Data System (ADS)
Mashal, Ibrahim; Alsaryrah, Osama; Chung, Tein-Yaw
2016-06-01
Internet of Things (IoT) is the next wave of industry revolution that will initiate many services, such as personal health care and green energy monitoring, which people may subscribe for their convenience. Recommending IoT services to the users based on objects they own will become very crucial for the success of IoT. In this work, we introduce the concept of service recommender systems in IoT by a formal model. As a first attempt in this direction, we have proposed a hyper-graph model for IoT recommender system in which each hyper-edge connects users, objects, and services. Next, we studied the usefulness of traditional recommendation schemes and their hybrid approaches on IoT service recommendation (IoTSRS) based on existing well known metrics. The preliminary results show that existing approaches perform reasonably well but further extension is required for IoTSRS. Several challenges were discussed to point out the direction of future development in IoTSR.
An evaluation method based on absolute difference to validate the performance of SBNUC algorithms
NASA Astrophysics Data System (ADS)
Jin, Minglei; Jin, Weiqi; Li, Yiyang; Li, Shuo
2016-09-01
Scene-based non-uniformity correction (SBNUC) algorithms are an important part of infrared image processing; however, SBNUC algorithms usually cause two defects: (1) ghosting artifacts and (2) over-correction. In this paper, we use the absolute difference based on guided image filter (AD-GF) method to validate the performance of SBNUC algorithms. We obtain a self-separation source using the improved guided image filter to process the input image, and use the self-separation source to obtain the space-high-frequency parts of the input image and the corrected image. Finally, we use the absolute difference between the two space-high-frequency parts as the evaluation result. Based on experimental results, the AD-GF method has better robustness and can validate the performance of SBNUC algorithms even if ghosting artifacts or over-correction occur. Also the AD-GF method can measure how SBNUC algorithms perform in the time domain, it's an effective evaluation method for SBNUC algorithm.
Performance evaluation of trigger algorithm for the MACE telescope
NASA Astrophysics Data System (ADS)
Yadav, Kuldeep; Yadav, K. K.; Bhatt, N.; Chouhan, N.; Sikder, S. S.; Behere, A.; Pithawa, C. K.; Tickoo, A. K.; Rannot, R. C.; Bhattacharyya, S.; Mitra, A. K.; Koul, R.
The MACE (Major Atmospheric Cherenkov Experiment) telescope with a light collector diameter of 21 m, is being set up at Hanle (32.80 N, 78.90 E, 4200m asl) India, to explore the gamma-ray sky in the tens of GeV energy range. The imaging camera of the telescope comprises 1088 pixels covering a total field-of-view of 4.30 × 4.00 with trigger field-of-view of 2.60 × 3.00 and an uniform pixel resolution of 0.120. In order to achieve low energy trigger threshold of less than 30 GeV, a two level trigger scheme is being designed for the telescope. The first level trigger is generated within 16 pixels of the Camera Integrated Module (CIM) based on 4 nearest neighbour (4NN) close cluster configuration within a coincidence gate window of 5 ns while the second level trigger is generated by combining the first level triggers from neighbouring CIMs. Each pixel of the telescope is expected to operate at a single pixel threshold between 8-10 photo-electrons where the single channel rate dominated by the after- pulsing is expected to be ˜500 kHz. The hardware implementation of the trigger logic is based on complex programmable logic devices (CPLD). The basic design concept, hardware implementation and performance evaluation of the trigger system in terms of threshold energy and trigger rate estimates based on Monte Carlo data for the MACE telescope will be presented in this meeting.
NASA Astrophysics Data System (ADS)
Kreuz, Thomas; Andrzejak, Ralph G.; Mormann, Florian; Kraskov, Alexander; Stögbauer, Harald; Elger, Christian E.; Lehnertz, Klaus; Grassberger, Peter
2004-06-01
In a growing number of publications it is claimed that epileptic seizures can be predicted by analyzing the electroencephalogram (EEG) with different characterizing measures. However, many of these studies suffer from a severe lack of statistical validation. Only rarely are results passed to a statistical test and verified against some null hypothesis H0 in order to quantify their significance. In this paper we propose a method to statistically validate the performance of measures used to predict epileptic seizures. From measure profiles rendered by applying a moving-window technique to the electroencephalogram we first generate an ensemble of surrogates by a constrained randomization using simulated annealing. Subsequently the seizure prediction algorithm is applied to the original measure profile and to the surrogates. If detectable changes before seizure onset exist, highest performance values should be obtained for the original measure profiles and the null hypothesis. “The measure is not suited for seizure prediction” can be rejected. We demonstrate our method by applying two measures of synchronization to a quasicontinuous EEG recording and by evaluating their predictive performance using a straightforward seizure prediction statistics. We would like to stress that the proposed method is rather universal and can be applied to many other prediction and detection problems.
NASA Astrophysics Data System (ADS)
Julge, Kalev; Ellmann, Artu; Gruno, Anti
2014-01-01
Numerous filtering algorithms have been developed in order to distinguish the ground surface from nonground points acquired by airborne laser scanning. These algorithms automatically attempt to determine the ground points using various features such as predefined parameters and statistical analysis. Their efficiency also depends on landscape characteristics. The aim of this contribution is to test the performance of six common filtering algorithms embedded in three freeware programs. The algorithms' adaptive TIN, elevation threshold with expand window, maximum local slope, progressive morphology, multiscale curvature, and linear prediction were tested on four relatively large (4 to 8 km2) and diverse landscape areas, which included steep sloped hills, urban areas, ridge-like eskers, and a river valley. The results show that in diverse test areas each algorithm yields various commission and omission errors. It appears that adaptive TIN is suitable in urban areas while the multiscale curvature algorithm is best suited in wooded areas. The multiscale curvature algorithm yielded the overall best results with average root-mean-square error values of 0.35 m.
Independent component analysis algorithm FPGA design to perform real-time blind source separation
NASA Astrophysics Data System (ADS)
Meyer-Baese, Uwe; Odom, Crispin; Botella, Guillermo; Meyer-Baese, Anke
2015-05-01
The conditions that arise in the Cocktail Party Problem prevail across many fields creating a need for of Blind Source Separation. The need for BSS has become prevalent in several fields of work. These fields include array processing, communications, medical signal processing, and speech processing, wireless communication, audio, acoustics and biomedical engineering. The concept of the cocktail party problem and BSS led to the development of Independent Component Analysis (ICA) algorithms. ICA proves useful for applications needing real time signal processing. The goal of this research was to perform an extensive study on ability and efficiency of Independent Component Analysis algorithms to perform blind source separation on mixed signals in software and implementation in hardware with a Field Programmable Gate Array (FPGA). The Algebraic ICA (A-ICA), Fast ICA, and Equivariant Adaptive Separation via Independence (EASI) ICA were examined and compared. The best algorithm required the least complexity and fewest resources while effectively separating mixed sources. The best algorithm was the EASI algorithm. The EASI ICA was implemented on hardware with Field Programmable Gate Arrays (FPGA) to perform and analyze its performance in real time.
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.
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
Lamberti, Alfredo; Vanlanduit, Steve; De Pauw, Ben; Berghmans, Francis
2014-01-01
The working principle of fiber Bragg grating (FBG) sensors is mostly based on the tracking of the Bragg wavelength shift. To accomplish this task, different algorithms have been proposed, from conventional maximum and centroid detection algorithms to more recently-developed correlation-based techniques. Several studies regarding the performance of these algorithms have been conducted, but they did not take into account spectral distortions, which appear in many practical applications. This paper addresses this issue and analyzes the performance of four different wavelength tracking algorithms (maximum detection, centroid detection, cross-correlation and fast phase-correlation) when applied to distorted FBG spectra used for measuring dynamic loads. Both simulations and experiments are used for the analyses. The dynamic behavior of distorted FBG spectra is simulated using the transfer-matrix approach, and the amount of distortion of the spectra is quantified using dedicated distortion indices. The algorithms are compared in terms of achievable precision and accuracy. To corroborate the simulation results, experiments were conducted using three FBG sensors glued on a steel plate and subjected to a combination of transverse force and vibration loads. The analysis of the results showed that the fast phase-correlation algorithm guarantees the best combination of versatility, precision and accuracy. PMID:25521386
Experimental Performance of a Genetic Algorithm for Airborne Strategic Conflict Resolution
NASA Technical Reports Server (NTRS)
Karr, David A.; Vivona, Robert A.; Roscoe, David A.; DePascale, Stephen M.; Consiglio, Maria
2009-01-01
The Autonomous Operations Planner, a research prototype flight-deck decision support tool to enable airborne self-separation, uses a pattern-based genetic algorithm to resolve predicted conflicts between the ownship and traffic aircraft. Conflicts are resolved by modifying the active route within the ownship s flight management system according to a predefined set of maneuver pattern templates. The performance of this pattern-based genetic algorithm was evaluated in the context of batch-mode Monte Carlo simulations running over 3600 flight hours of autonomous aircraft in en-route airspace under conditions ranging from typical current traffic densities to several times that level. Encountering over 8900 conflicts during two simulation experiments, the genetic algorithm was able to resolve all but three conflicts, while maintaining a required time of arrival constraint for most aircraft. Actual elapsed running time for the algorithm was consistent with conflict resolution in real time. The paper presents details of the genetic algorithm s design, along with mathematical models of the algorithm s performance and observations regarding the effectiveness of using complimentary maneuver patterns when multiple resolutions by the same aircraft were required.
Experimental Performance of a Genetic Algorithm for Airborne Strategic Conflict Resolution
NASA Technical Reports Server (NTRS)
Karr, David A.; Vivona, Robert A.; Roscoe, David A.; DePascale, Stephen M.; Consiglio, Maria
2009-01-01
The Autonomous Operations Planner, a research prototype flight-deck decision support tool to enable airborne self-separation, uses a pattern-based genetic algorithm to resolve predicted conflicts between the ownship and traffic aircraft. Conflicts are resolved by modifying the active route within the ownship's flight management system according to a predefined set of maneuver pattern templates. The performance of this pattern-based genetic algorithm was evaluated in the context of batch-mode Monte Carlo simulations running over 3600 flight hours of autonomous aircraft in en-route airspace under conditions ranging from typical current traffic densities to several times that level. Encountering over 8900 conflicts during two simulation experiments, the genetic algorithm was able to resolve all but three conflicts, while maintaining a required time of arrival constraint for most aircraft. Actual elapsed running time for the algorithm was consistent with conflict resolution in real time. The paper presents details of the genetic algorithm's design, along with mathematical models of the algorithm's performance and observations regarding the effectiveness of using complimentary maneuver patterns when multiple resolutions by the same aircraft were required.
NASA Astrophysics Data System (ADS)
Triana-Martinez, J.; Orjuela-Vargas, S. A.; Philips, W.
2013-03-01
This paper compares the speed performance of a set of classic image algorithms for evaluating texture in images by using CUDA programming. We include a summary of the general program mode of CUDA. We select a set of texture algorithms, based on statistical analysis, that allow the use of repetitive functions, such as the Coocurrence Matrix, Haralick features and local binary patterns techniques. The memory allocation time between the host and device memory is not taken into account. The results of this approach show a comparison of the texture algorithms in terms of speed when executed on CPU and GPU processors. The comparison shows that the algorithms can be accelerated more than 40 times when implemented using CUDA environment.
NASA Astrophysics Data System (ADS)
Angelis, G. I.; Reader, A. J.; Kotasidis, F. A.; Lionheart, W. R.; Matthews, J. C.
2011-07-01
Iterative expectation maximization (EM) techniques have been extensively used to solve maximum likelihood (ML) problems in positron emission tomography (PET) image reconstruction. Although EM methods offer a robust approach to solving ML problems, they usually suffer from slow convergence rates. The ordered subsets EM (OSEM) algorithm provides significant improvements in the convergence rate, but it can cycle between estimates converging towards the ML solution of each subset. In contrast, gradient-based methods, such as the recently proposed non-monotonic maximum likelihood (NMML) and the more established preconditioned conjugate gradient (PCG), offer a globally convergent, yet equally fast, alternative to OSEM. Reported results showed that NMML provides faster convergence compared to OSEM; however, it has never been compared to other fast gradient-based methods, like PCG. Therefore, in this work we evaluate the performance of two gradient-based methods (NMML and PCG) and investigate their potential as an alternative to the fast and widely used OSEM. All algorithms were evaluated using 2D simulations, as well as a single [11C]DASB clinical brain dataset. Results on simulated 2D data show that both PCG and NMML achieve orders of magnitude faster convergence to the ML solution compared to MLEM and exhibit comparable performance to OSEM. Equally fast performance is observed between OSEM and PCG for clinical 3D data, but NMML seems to perform poorly. However, with the addition of a preconditioner term to the gradient direction, the convergence behaviour of NMML can be substantially improved. Although PCG is a fast convergent algorithm, the use of a (bent) line search increases the complexity of the implementation, as well as the computational time involved per iteration. Contrary to previous reports, NMML offers no clear advantage over OSEM or PCG, for noisy PET data. Therefore, we conclude that there is little evidence to replace OSEM as the algorithm of choice for
Angelis, G I; Reader, A J; Kotasidis, F A; Lionheart, W R; Matthews, J C
2011-07-01
Iterative expectation maximization (EM) techniques have been extensively used to solve maximum likelihood (ML) problems in positron emission tomography (PET) image reconstruction. Although EM methods offer a robust approach to solving ML problems, they usually suffer from slow convergence rates. The ordered subsets EM (OSEM) algorithm provides significant improvements in the convergence rate, but it can cycle between estimates converging towards the ML solution of each subset. In contrast, gradient-based methods, such as the recently proposed non-monotonic maximum likelihood (NMML) and the more established preconditioned conjugate gradient (PCG), offer a globally convergent, yet equally fast, alternative to OSEM. Reported results showed that NMML provides faster convergence compared to OSEM; however, it has never been compared to other fast gradient-based methods, like PCG. Therefore, in this work we evaluate the performance of two gradient-based methods (NMML and PCG) and investigate their potential as an alternative to the fast and widely used OSEM. All algorithms were evaluated using 2D simulations, as well as a single [(11)C]DASB clinical brain dataset. Results on simulated 2D data show that both PCG and NMML achieve orders of magnitude faster convergence to the ML solution compared to MLEM and exhibit comparable performance to OSEM. Equally fast performance is observed between OSEM and PCG for clinical 3D data, but NMML seems to perform poorly. However, with the addition of a preconditioner term to the gradient direction, the convergence behaviour of NMML can be substantially improved. Although PCG is a fast convergent algorithm, the use of a (bent) line search increases the complexity of the implementation, as well as the computational time involved per iteration. Contrary to previous reports, NMML offers no clear advantage over OSEM or PCG, for noisy PET data. Therefore, we conclude that there is little evidence to replace OSEM as the algorithm of choice for
A fast and high performance multiple data integration algorithm for identifying human disease genes
2015-01-01
Background Integrating multiple data sources is indispensable in improving disease gene identification. It is not only due to the fact that disease genes associated with similar genetic diseases tend to lie close with each other in various biological networks, but also due to the fact that gene-disease associations are complex. Although various algorithms have been proposed to identify disease genes, their prediction performances and the computational time still should be further improved. Results In this study, we propose a fast and high performance multiple data integration algorithm for identifying human disease genes. A posterior probability of each candidate gene associated with individual diseases is calculated by using a Bayesian analysis method and a binary logistic regression model. Two prior probability estimation strategies and two feature vector construction methods are developed to test the performance of the proposed algorithm. Conclusions The proposed algorithm is not only generated predictions with high AUC scores, but also runs very fast. When only a single PPI network is employed, the AUC score is 0.769 by using F2 as feature vectors. The average running time for each leave-one-out experiment is only around 1.5 seconds. When three biological networks are integrated, the AUC score using F3 as feature vectors increases to 0.830, and the average running time for each leave-one-out experiment takes only about 12.54 seconds. It is better than many existing algorithms. PMID:26399620
Montilla, I; Béchet, C; Le Louarn, M; Reyes, M; Tallon, M
2010-11-01
Extremely Large Telescopes (ELTs) are very challenging with respect to their adaptive optics (AO) requirements. Their diameters and the specifications required by the astronomical science for which they are being designed imply a huge increment in the number of degrees of freedom in the deformable mirrors. Faster algorithms are needed to implement the real-time reconstruction and control in AO at the required speed. We present the results of a study of the AO correction performance of three different algorithms applied to the case of a 42-m ELT: one considered as a reference, the matrix-vector multiply (MVM) algorithm; and two considered fast, the fractal iterative method (FrIM) and the Fourier transform reconstructor (FTR). The MVM and the FrIM both provide a maximum a posteriori estimation, while the FTR provides a least-squares one. The algorithms are tested on the European Southern Observatory (ESO) end-to-end simulator, OCTOPUS. The performance is compared using a natural guide star single-conjugate adaptive optics configuration. The results demonstrate that the methods have similar performance in a large variety of simulated conditions. However, with respect to system misregistrations, the fast algorithms demonstrate an interesting robustness. PMID:21045895
Montilla, I; Béchet, C; Le Louarn, M; Reyes, M; Tallon, M
2010-11-01
Extremely Large Telescopes (ELTs) are very challenging with respect to their adaptive optics (AO) requirements. Their diameters and the specifications required by the astronomical science for which they are being designed imply a huge increment in the number of degrees of freedom in the deformable mirrors. Faster algorithms are needed to implement the real-time reconstruction and control in AO at the required speed. We present the results of a study of the AO correction performance of three different algorithms applied to the case of a 42-m ELT: one considered as a reference, the matrix-vector multiply (MVM) algorithm; and two considered fast, the fractal iterative method (FrIM) and the Fourier transform reconstructor (FTR). The MVM and the FrIM both provide a maximum a posteriori estimation, while the FTR provides a least-squares one. The algorithms are tested on the European Southern Observatory (ESO) end-to-end simulator, OCTOPUS. The performance is compared using a natural guide star single-conjugate adaptive optics configuration. The results demonstrate that the methods have similar performance in a large variety of simulated conditions. However, with respect to system misregistrations, the fast algorithms demonstrate an interesting robustness.
Performance Evaluation of the Cable Bundle Unique Power Back-Off Algorithm
NASA Astrophysics Data System (ADS)
Statovci, Driton; Nordström, Tomas
The latest digital subscriber line (DSL) technology, VDSL2, used for broadband access over twisted-pairs, promises up to 100 Mbit/s for both transmission directions on short loops. Since these systems are designed to operate in a far-end crosstalk (FEXT) limited environment, there is a severe performance degradation when deployed in distributed network scenarios. With power back-off (PBO) the network operators attempt to protect modems deployed on long loops by reducing the transmit power of the short ones. However, currently very little guidance has been given to operators on how to set and optimize the parameters for PBO. In this paper we explore one promising method, the cable bundle unique PBO (CUPBO), which optimizes these parameters according to the actual situation in the cable with regard to noise and network topology. Using real VDSL systems and cables we show that CUPBO algorithm achieves a significant increase in performance compared to the case when one naively takes the PBO values given in the VDSL standard.
Performance of the reconstruction algorithms of the FIRST experiment pixel sensors vertex detector
NASA Astrophysics Data System (ADS)
Rescigno, R.; Finck, Ch.; Juliani, D.; Spiriti, E.; Baudot, J.; Abou-Haidar, Z.; Agodi, C.; Alvarez, M. A. G.; Aumann, T.; Battistoni, G.; Bocci, A.; Böhlen, T. T.; Boudard, A.; Brunetti, A.; Carpinelli, M.; Cirrone, G. A. P.; Cortes-Giraldo, M. A.; Cuttone, G.; De Napoli, M.; Durante, M.; Gallardo, M. I.; Golosio, B.; Iarocci, E.; Iazzi, F.; Ickert, G.; Introzzi, R.; Krimmer, J.; Kurz, N.; Labalme, M.; Leifels, Y.; Le Fevre, A.; Leray, S.; Marchetto, F.; Monaco, V.; Morone, M. C.; Oliva, P.; Paoloni, A.; Patera, V.; Piersanti, L.; Pleskac, R.; Quesada, J. M.; Randazzo, N.; Romano, F.; Rossi, D.; Rousseau, M.; Sacchi, R.; Sala, P.; Sarti, A.; Scheidenberger, C.; Schuy, C.; Sciubba, A.; Sfienti, C.; Simon, H.; Sipala, V.; Tropea, S.; Vanstalle, M.; Younis, H.
2014-12-01
Hadrontherapy treatments use charged particles (e.g. protons and carbon ions) to treat tumors. During a therapeutic treatment with carbon ions, the beam undergoes nuclear fragmentation processes giving rise to significant yields of secondary charged particles. An accurate prediction of these production rates is necessary to estimate precisely the dose deposited into the tumours and the surrounding healthy tissues. Nowadays, a limited set of double differential carbon fragmentation cross-section is available. Experimental data are necessary to benchmark Monte Carlo simulations for their use in hadrontherapy. The purpose of the FIRST experiment is to study nuclear fragmentation processes of ions with kinetic energy in the range from 100 to 1000 MeV/u. Tracks are reconstructed using information from a pixel silicon detector based on the CMOS technology. The performances achieved using this device for hadrontherapy purpose are discussed. For each reconstruction step (clustering, tracking and vertexing), different methods are implemented. The algorithm performances and the accuracy on reconstructed observables are evaluated on the basis of simulated and experimental data.
NASA Astrophysics Data System (ADS)
Mantini, D.; Hild, K. E., II; Alleva, G.; Comani, S.
2006-02-01
Independent component analysis (ICA) algorithms have been successfully used for signal extraction tasks in the field of biomedical signal processing. We studied the performances of six algorithms (FastICA, CubICA, JADE, Infomax, TDSEP and MRMI-SIG) for fetal magnetocardiography (fMCG). Synthetic datasets were used to check the quality of the separated components against the original traces. Real fMCG recordings were simulated with linear combinations of typical fMCG source signals: maternal and fetal cardiac activity, ambient noise, maternal respiration, sensor spikes and thermal noise. Clusters of different dimensions (19, 36 and 55 sensors) were prepared to represent different MCG systems. Two types of signal-to-interference ratios (SIR) were measured. The first involves averaging over all estimated components and the second is based solely on the fetal trace. The computation time to reach a minimum of 20 dB SIR was measured for all six algorithms. No significant dependency on gestational age or cluster dimension was observed. Infomax performed poorly when a sub-Gaussian source was included; TDSEP and MRMI-SIG were sensitive to additive noise, whereas FastICA, CubICA and JADE showed the best performances. Of all six methods considered, FastICA had the best overall performance in terms of both separation quality and computation times.
Dórea, Fernanda C.; McEwen, Beverly J.; McNab, W. Bruce; Revie, Crawford W.; Sanchez, Javier
2013-01-01
Diagnostic test orders to an animal laboratory were explored as a data source for monitoring trends in the incidence of clinical syndromes in cattle. Four years of real data and over 200 simulated outbreak signals were used to compare pre-processing methods that could remove temporal effects in the data, as well as temporal aberration detection algorithms that provided high sensitivity and specificity. Weekly differencing demonstrated solid performance in removing day-of-week effects, even in series with low daily counts. For aberration detection, the results indicated that no single algorithm showed performance superior to all others across the range of outbreak scenarios simulated. Exponentially weighted moving average charts and Holt–Winters exponential smoothing demonstrated complementary performance, with the latter offering an automated method to adjust to changes in the time series that will likely occur in the future. Shewhart charts provided lower sensitivity but earlier detection in some scenarios. Cumulative sum charts did not appear to add value to the system; however, the poor performance of this algorithm was attributed to characteristics of the data monitored. These findings indicate that automated monitoring aimed at early detection of temporal aberrations will likely be most effective when a range of algorithms are implemented in parallel. PMID:23576782
Dórea, Fernanda C; McEwen, Beverly J; McNab, W Bruce; Revie, Crawford W; Sanchez, Javier
2013-06-01
Diagnostic test orders to an animal laboratory were explored as a data source for monitoring trends in the incidence of clinical syndromes in cattle. Four years of real data and over 200 simulated outbreak signals were used to compare pre-processing methods that could remove temporal effects in the data, as well as temporal aberration detection algorithms that provided high sensitivity and specificity. Weekly differencing demonstrated solid performance in removing day-of-week effects, even in series with low daily counts. For aberration detection, the results indicated that no single algorithm showed performance superior to all others across the range of outbreak scenarios simulated. Exponentially weighted moving average charts and Holt-Winters exponential smoothing demonstrated complementary performance, with the latter offering an automated method to adjust to changes in the time series that will likely occur in the future. Shewhart charts provided lower sensitivity but earlier detection in some scenarios. Cumulative sum charts did not appear to add value to the system; however, the poor performance of this algorithm was attributed to characteristics of the data monitored. These findings indicate that automated monitoring aimed at early detection of temporal aberrations will likely be most effective when a range of algorithms are implemented in parallel.
Performance Improvement of Algorithms Based on the Synthetic Aperture Focusing Technique
NASA Astrophysics Data System (ADS)
Acevedo, P.; Sotomayor, A.; Moreno, E.
An analysis to improve the performance of the ultrasonic synthetic aperture focusing technique (SAFT) on a PC platform is presented in this paper. Some useful processing techniques like apodization, dynamic focusing, envelope detection and image composition are used to improve the quality of the image. Finally, results of the algorithm implemented using MATLAB and C/C++ and the respective images are presented
Signal and image processing algorithm performance in a virtual and elastic computing environment
NASA Astrophysics Data System (ADS)
Bennett, Kelly W.; Robertson, James
2013-05-01
The U.S. Army Research Laboratory (ARL) supports the development of classification, detection, tracking, and localization algorithms using multiple sensing modalities including acoustic, seismic, E-field, magnetic field, PIR, and visual and IR imaging. Multimodal sensors collect large amounts of data in support of algorithm development. The resulting large amount of data, and their associated high-performance computing needs, increases and challenges existing computing infrastructures. Purchasing computer power as a commodity using a Cloud service offers low-cost, pay-as-you-go pricing models, scalability, and elasticity that may provide solutions to develop and optimize algorithms without having to procure additional hardware and resources. This paper provides a detailed look at using a commercial cloud service provider, such as Amazon Web Services (AWS), to develop and deploy simple signal and image processing algorithms in a cloud and run the algorithms on a large set of data archived in the ARL Multimodal Signatures Database (MMSDB). Analytical results will provide performance comparisons with existing infrastructure. A discussion on using cloud computing with government data will discuss best security practices that exist within cloud services, such as AWS.
High-performance modeling acoustic and elastic waves using the parallel Dichotomy Algorithm
Fatyanov, Alexey G.; Terekhov, Andrew V.
2011-03-01
A high-performance parallel algorithm is proposed for modeling the propagation of acoustic and elastic waves in inhomogeneous media. An initial boundary-value problem is replaced by a series of boundary-value problems for a constant elliptic operator and different right-hand sides via the integral Laguerre transform. It is proposed to solve difference equations by the conjugate gradient method for acoustic equations and by the GMRES(k) method for modeling elastic waves. A preconditioning operator was the Laplace operator that is inverted using the variable separation method. The novelty of the proposed algorithm is using the Dichotomy Algorithm , which was designed for solving a series of tridiagonal systems of linear equations, in the context of the preconditioning operator inversion. Via considering analytical solutions, it is shown that modeling wave processes for long instants of time requires high-resolution meshes. The proposed parallel fine-mesh algorithm enabled to solve real application seismic problems in acceptable time and with high accuracy. By solving model problems, it is demonstrated that the considered parallel algorithm possesses high performance and efficiency over a wide range of the number of processors (from 2 to 8192).
Significant Differences in Pediatric Psychotropic Side Effects: Implications for School Performance
ERIC Educational Resources Information Center
Kubiszyn, Thomas; Mire, Sarah; Dutt, Sonia; Papathopoulos, Katina; Burridge, Andrea Backsheider
2012-01-01
Some side effects (SEs) of increasingly prescribed psychotropic medications can impact student performance in school. SE risk varies, even among drugs from the same class (e.g., antidepressants). Knowing which SEs occur significantly more often than others may enable school psychologists to enhance collaborative risk-benefit analysis, medication…
Westover, Jennifer M; Martin, Emma J
2014-12-01
Literacy skills are fundamental for all learners. For students with significant disabilities, strong literacy skills provide a gateway to generative communication, genuine friendships, improved access to academic opportunities, access to information technology, and future employment opportunities. Unfortunately, many educators lack the knowledge to design or implement appropriate evidence-based literacy instruction for students with significant disabilities. Furthermore, students with significant disabilities often receive the majority of their instruction from paraeducators. This single-subject design study examined the effects of performance feedback on the delivery skills of paraeducators during systematic and explicit literacy instruction for students with significant disabilities. The specific skills targeted for feedback were planned opportunities for student responses and correct academic responses. Findings suggested that delivery of feedback on performance resulted in increased pacing, accuracy in student responses, and subsequent attainment of literacy skills for students with significant disabilities. Implications for the use of performance feedback as an evaluation and training tool for increasing effective instructional practices are provided. PMID:25271082
Performance of 12 DIR algorithms in low-contrast regions for mass and density conserving deformation
Yeo, U. J.; Supple, J. R.; Franich, R. D.; Taylor, M. L.; Smith, R.; Kron, T.
2013-10-15
Purpose: Deformable image registration (DIR) has become a key tool for adaptive radiotherapy to account for inter- and intrafraction organ deformation. Of contemporary interest, the application to deformable dose accumulation requires accurate deformation even in low contrast regions where dose gradients may exist within near-uniform tissues. One expects high-contrast features to generally be deformed more accurately by DIR algorithms. The authors systematically assess the accuracy of 12 DIR algorithms and quantitatively examine, in particular, low-contrast regions, where accuracy has not previously been established.Methods: This work investigates DIR algorithms in three dimensions using deformable gel (DEFGEL) [U. J. Yeo, M. L. Taylor, L. Dunn, R. L. Smith, T. Kron, and R. D. Franich, “A novel methodology for 3D deformable dosimetry,” Med. Phys. 39, 2203–2213 (2012)], for application to mass- and density-conserving deformations. CT images of DEFGEL phantoms with 16 fiducial markers (FMs) implanted were acquired in deformed and undeformed states for three different representative deformation geometries. Nonrigid image registration was performed using 12 common algorithms in the public domain. The optimum parameter setup was identified for each algorithm and each was tested for deformation accuracy in three scenarios: (I) original images of the DEFGEL with 16 FMs; (II) images with eight of the FMs mathematically erased; and (III) images with all FMs mathematically erased. The deformation vector fields obtained for scenarios II and III were then applied to the original images containing all 16 FMs. The locations of the FMs estimated by the algorithms were compared to actual locations determined by CT imaging. The accuracy of the algorithms was assessed by evaluation of three-dimensional vectors between true marker locations and predicted marker locations.Results: The mean magnitude of 16 error vectors per sample ranged from 0.3 to 3.7, 1.0 to 6.3, and 1.3 to 7
The effect of load imbalances on the performance of Monte Carlo algorithms in LWR analysis
Siegel, A.R.; Smith, K.; Romano, P.K.; Forget, B.; Felker, K.
2013-02-15
A model is developed to predict the impact of particle load imbalances on the performance of domain-decomposed Monte Carlo neutron transport algorithms. Expressions for upper bound performance “penalties” are derived in terms of simple machine characteristics, material characterizations and initial particle distributions. The hope is that these relations can be used to evaluate tradeoffs among different memory decomposition strategies in next generation Monte Carlo codes, and perhaps as a metric for triggering particle redistribution in production codes.
Global Precipitation Measurement (GPM) Microwave Imager Falling Snow Retrieval Algorithm Performance
NASA Astrophysics Data System (ADS)
Skofronick Jackson, Gail; Munchak, Stephen J.; Johnson, Benjamin T.
2015-04-01
Retrievals of falling snow from space represent an important data set for understanding the Earth's atmospheric, hydrological, and energy cycles. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new and retrievals are still undergoing development with challenges and uncertainties remaining. This work reports on the development and post-launch testing of retrieval algorithms for the NASA Global Precipitation Measurement (GPM) mission Core Observatory satellite launched in February 2014. In particular, we will report on GPM Microwave Imager (GMI) radiometer instrument algorithm performance with respect to falling snow detection and estimation. Since GPM's launch, the at-launch GMI precipitation algorithms, based on a Bayesian framework, have been used with the new GPM data. The at-launch database is generated using proxy satellite data merged with surface measurements (instead of models). One year after launch, the Bayesian database will begin to be replaced with the more realistic observational data from the GPM spacecraft radar retrievals and GMI data. It is expected that the observational database will be much more accurate for falling snow retrievals because that database will take full advantage of the 166 and 183 GHz snow-sensitive channels. Furthermore, much retrieval algorithm work has been done to improve GPM retrievals over land. The Bayesian framework for GMI retrievals is dependent on the a priori database used in the algorithm and how profiles are selected from that database. Thus, a land classification sorts land surfaces into ~15 different categories for surface-specific databases (radiometer brightness temperatures are quite dependent on surface characteristics). In addition, our work has shown that knowing if the land surface is snow-covered, or not, can improve the performance of the algorithm. Improvements were made to the algorithm that allow for daily inputs of ancillary snow cover
Assessing SWOT discharge algorithms performance across a range of river types
NASA Astrophysics Data System (ADS)
Durand, M. T.; Smith, L. C.; Gleason, C. J.; Bjerklie, D. M.; Garambois, P. A.; Roux, H.
2014-12-01
Scheduled for launch in 2020, the Surface Water and Ocean Topography (SWOT) satellite mission will measure river height, width, and slope, globally, as well as characterizing storage change in lakes, and ocean surface dynamics. Four discharge algorithms have been formulated to solve the inverse problem of river discharge from SWOT observations. Three of these approaches are based on Manning's equation, while the fourth utilizes at-many-stations hydraulic geometry relating width and discharge. In all cases, SWOT will provide some but not all of the information required to estimate discharge. The focus of the inverse approaches is estimation of the unknown parameters. The algorithms use a range of a priori information. This paper will generate synthetic measurements of height, width, and slope for a number of rivers, including reaches of the Sacramento, Ohio, Mississippi, Platte, Amazon, Garonne, Po, Severn, St. Lawrence, and Tanana. These rivers have a wide range of flows, geometries, hydraulic regimes, floodplain interactions, and planforms. One-year synthetic datasets will be generated in each case. We will add white noise to the simulated quantities and generate scenarios with different repeat time. The focus will be on retrievability of the hydraulic parameters across a range of space-time sampling, rather than on ability to retrieve under the specific SWOT orbit. We will focus on several specific research questions affecting algorithm performance, including river characteristics, temporal sampling, and algorithm accuracy. The overall goal is to be able to predict which algorithms will work better for different kinds of rivers, and potentially to combine the outputs of the various algorithms to obtain more robust estimates. Preliminary results on the Sacramento River indicate that all algorithms perform well for this single-channel river, with diffusive hydraulics, with relative RMSE values ranging from 9% to 26% for the various algorithms. Preliminary
Review of tandem repeat search tools: a systematic approach to evaluating algorithmic performance.
Lim, Kian Guan; Kwoh, Chee Keong; Hsu, Li Yang; Wirawan, Adrianto
2013-01-01
The prevalence of tandem repeats in eukaryotic genomes and their association with a number of genetic diseases has raised considerable interest in locating these repeats. Over the last 10-15 years, numerous tools have been developed for searching tandem repeats, but differences in the search algorithms adopted and difficulties with parameter settings have confounded many users resulting in widely varying results. In this review, we have systematically separated the algorithmic aspect of the search tools from the influence of the parameter settings. We hope that this will give a better understanding of how the tools differ in algorithmic performance, their inherent constraints and how one should approach in evaluating and selecting them. PMID:22648964
A Hybrid Neural Network-Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics
NASA Technical Reports Server (NTRS)
Kobayashi, Takahisa; Simon, Donald L.
2001-01-01
In this paper, a model-based diagnostic method, which utilizes Neural Networks and Genetic Algorithms, is investigated. Neural networks are applied to estimate the engine internal health, and Genetic Algorithms are applied for sensor bias detection and estimation. This hybrid approach takes advantage of the nonlinear estimation capability provided by neural networks while improving the robustness to measurement uncertainty through the application of Genetic Algorithms. The hybrid diagnostic technique also has the ability to rank multiple potential solutions for a given set of anomalous sensor measurements in order to reduce false alarms and missed detections. The performance of the hybrid diagnostic technique is evaluated through some case studies derived from a turbofan engine simulation. The results show this approach is promising for reliable diagnostics of aircraft engines.
Performance enhancement for crystallization unit of a sugar plant using genetic algorithm technique
NASA Astrophysics Data System (ADS)
Tewari, P. C.; Khanduja, Rajiv; Gupta, Mahesh
2012-05-01
This paper deals with the performance enhancement for crystallization unit of a sugar plant using genetic algorithm. The crystallization unit of a sugar industry has three main subsystems arranged in series. Considering exponential distribution for the probable failures and repairs, the mathematical formulation of the problem is done using probabilistic approach, and differential equations are developed on the basis of Markov birth-death process. These equations are then solved using normalizing conditions so as to determine the steady-state availability of the crystallization unit. The performance of each subsystem of crystallization unit in a sugar plant has also been optimized using genetic algorithm. Thus, the findings of the present paper will be highly useful to the plant management for the timely execution of proper maintenance decisions and, hence, to enhance the system performance.
Using modified fruit fly optimisation algorithm to perform the function test and case studies
NASA Astrophysics Data System (ADS)
Pan, Wen-Tsao
2013-06-01
Evolutionary computation is a computing mode established by practically simulating natural evolutionary processes based on the concept of Darwinian Theory, and it is a common research method. The main contribution of this paper was to reinforce the function of searching for the optimised solution using the fruit fly optimization algorithm (FOA), in order to avoid the acquisition of local extremum solutions. The evolutionary computation has grown to include the concepts of animal foraging behaviour and group behaviour. This study discussed three common evolutionary computation methods and compared them with the modified fruit fly optimization algorithm (MFOA). It further investigated the ability of the three mathematical functions in computing extreme values, as well as the algorithm execution speed and the forecast ability of the forecasting model built using the optimised general regression neural network (GRNN) parameters. The findings indicated that there was no obvious difference between particle swarm optimization and the MFOA in regards to the ability to compute extreme values; however, they were both better than the artificial fish swarm algorithm and FOA. In addition, the MFOA performed better than the particle swarm optimization in regards to the algorithm execution speed, and the forecast ability of the forecasting model built using the MFOA's GRNN parameters was better than that of the other three forecasting models.
Evaluating the accuracy performance of Lucas-Kanade algorithm in the circumstance of PIV application
NASA Astrophysics Data System (ADS)
Pan, Chong; Xue, Dong; Xu, Yang; Wang, JinJun; Wei, RunJie
2015-10-01
Lucas-Kanade (LK) algorithm, usually used in optical flow filed, has recently received increasing attention from PIV community due to its advanced calculation efficiency by GPU acceleration. Although applications of this algorithm are continuously emerging, a systematic performance evaluation is still lacking. This forms the primary aim of the present work. Three warping schemes in the family of LK algorithm: forward/inverse/symmetric warping, are evaluated in a prototype flow of a hierarchy of multiple two-dimensional vortices. Second-order Newton descent is also considered here. The accuracy & efficiency of all these LK variants are investigated under a large domain of various influential parameters. It is found that the constant displacement constraint, which is a necessary building block for GPU acceleration, is the most critical issue in affecting LK algorithm's accuracy, which can be somehow ameliorated by using second-order Newton descent. Moreover, symmetric warping outbids the other two warping schemes in accuracy level, robustness to noise, convergence speed and tolerance to displacement gradient, and might be the first choice when applying LK algorithm to PIV measurement.
NASA Technical Reports Server (NTRS)
Deavours, Daniel D.; Qureshi, M. Akber; Sanders, William H.
1997-01-01
Modeling tools and technologies are important for aerospace development. At the University of Illinois, we have worked on advancing the state of the art in modeling by Markov reward models in two important areas: reducing the memory necessary to numerically solve systems represented as stochastic activity networks and other stochastic Petri net extensions while still obtaining solutions in a reasonable amount of time, and finding numerically stable and memory-efficient methods to solve for the reward accumulated during a finite mission time. A long standing problem when modeling with high level formalisms such as stochastic activity networks is the so-called state space explosion, where the number of states increases exponentially with size of the high level model. Thus, the corresponding Markov model becomes prohibitively large and solution is constrained by the the size of primary memory. To reduce the memory necessary to numerically solve complex systems, we propose new methods that can tolerate such large state spaces that do not require any special structure in the model (as many other techniques do). First, we develop methods that generate row and columns of the state transition-rate-matrix on-the-fly, eliminating the need to explicitly store the matrix at all. Next, we introduce a new iterative solution method, called modified adaptive Gauss-Seidel, that exhibits locality in its use of data from the state transition-rate-matrix, permitting us to cache portions of the matrix and hence reduce the solution time. Finally, we develop a new memory and computationally efficient technique for Gauss-Seidel based solvers that avoids the need for generating rows of A in order to solve Ax = b. This is a significant performance improvement for on-the-fly methods as well as other recent solution techniques based on Kronecker operators. Taken together, these new results show that one can solve very large models without any special structure.
Performance Evaluation of Different Ground Filtering Algorithms for Uav-Based Point Clouds
NASA Astrophysics Data System (ADS)
Serifoglu, C.; Gungor, O.; Yilmaz, V.
2016-06-01
Digital Elevation Model (DEM) generation is one of the leading application areas in geomatics. Since a DEM represents the bare earth surface, the very first step of generating a DEM is to separate the ground and non-ground points, which is called ground filtering. Once the point cloud is filtered, the ground points are interpolated to generate the DEM. LiDAR (Light Detection and Ranging) point clouds have been used in many applications thanks to their success in representing the objects they belong to. Hence, in the literature, various ground filtering algorithms have been reported to filter the LiDAR data. Since the LiDAR data acquisition is still a costly process, using point clouds generated from the UAV images to produce DEMs is a reasonable alternative. In this study, point clouds with three different densities were generated from the aerial photos taken from a UAV (Unmanned Aerial Vehicle) to examine the effect of point density on filtering performance. The point clouds were then filtered by means of five different ground filtering algorithms as Progressive Morphological 1D (PM1D), Progressive Morphological 2D (PM2D), Maximum Local Slope (MLS), Elevation Threshold with Expand Window (ETEW) and Adaptive TIN (ATIN). The filtering performance of each algorithm was investigated qualitatively and quantitatively. The results indicated that the ATIN and PM2D algorithms showed the best overall ground filtering performances. The MLS and ETEW algorithms were found as the least successful ones. It was concluded that the point clouds generated from the UAVs can be a good alternative for LiDAR data.
NASA Astrophysics Data System (ADS)
Kim, Chul-Ho; Lee, Kee-Man; Lee, Sang-Heon
Power train system design is one of the key R&D areas on the development process of new automobile because an optimum size of engine with adaptable power transmission which can accomplish the design requirement of new vehicle can be obtained through the system design. Especially, for the electric vehicle design, very reliable design algorithm of a power train system is required for the energy efficiency. In this study, an analytical simulation algorithm is developed to estimate driving performance of a designed power train system of an electric. The principal theory of the simulation algorithm is conservation of energy with several analytical and experimental data such as rolling resistance, aerodynamic drag, mechanical efficiency of power transmission etc. From the analytical calculation results, running resistance of a designed vehicle is obtained with the change of operating condition of the vehicle such as inclined angle of road and vehicle speed. Tractive performance of the model vehicle with a given power train system is also calculated at each gear ratio of transmission. Through analysis of these two calculation results: running resistance and tractive performance, the driving performance of a designed electric vehicle is estimated and it will be used to evaluate the adaptability of the designed power train system on the vehicle.
Scott, Joshua I; Xue, Xiao; Wang, Ming; Kline, R Joseph; Hoffman, Benjamin C; Dougherty, Daniel; Zhou, Chuanzhen; Bazan, Guillermo; O'Connor, Brendan T
2016-06-01
Polymer semiconductors based on donor-acceptor monomers have recently resulted in significant gains in field effect mobility in organic thin film transistors (OTFTs). These polymers incorporate fused aromatic rings and have been designed to have stiff planar backbones, resulting in strong intermolecular interactions, which subsequently result in stiff and brittle films. The complex synthesis typically required for these materials may also result in increased production costs. Thus, the development of methods to improve mechanical plasticity while lowering material consumption during fabrication will significantly improve opportunities for adoption in flexible and stretchable electronics. To achieve these goals, we consider blending a brittle donor-acceptor polymer, poly[4-(4,4-dihexadecyl-4H-cyclopenta[1,2-b:5,4-b']dithiophen-2-yl)-alt-[1,2,5]thiadiazolo[3,4-c]pyridine] (PCDTPT), with ductile poly(3-hexylthiophene). We found that the ductility of the blend films is significantly improved compared to that of neat PCDTPT films, and when the blend film is employed in an OTFT, the performance is largely maintained. The ability to maintain charge transport character is due to vertical segregation within the blend, while the improved ductility is due to intermixing of the polymers throughout the film thickness. Importantly, the application of large strains to the ductile films is shown to orient both polymers, which further increases charge carrier mobility. These results highlight a processing approach to achieve high performance polymer OTFTs that are electrically and mechanically optimized. PMID:27200458
2010-01-01
Background Patients with diabetes mellitus (DM) have high risk of heart failure. Whether some of the risk is directly linked to metabolic derangements in the myocardium or whether the risk is primarily caused by coronary artery disease (CAD) and hypertension is incompletely understood. Echocardiographic tissue Doppler imaging was therefore performed in DM patients without significant CAD to examine whether DM per se influenced cardiac function. Methods Patients with a left ventricular (LV) ejection fraction (EF) > 35% and without significant CAD, prior myocardial infarction, cardiac pacemaker, atrial fibrillation, or significant valve disease were identified from a tertiary invasive center register. DM patients were matched with controls on age, gender and presence of hypertension. Results In total 31 patients with diabetes and 31 controls were included. Mean age was 58 ± 12 years, mean LVEF was 51 ± 7%, and 48% were women. No significant differences were found in LVEF, left atrial end systolic volume, or left ventricular dimensions. The global longitudinal strain was significantly reduced in patients with DM (15.9 ± 2.9 vs. 17.7 ± 2.9, p = 0.03), as were peak longitudinal systolic (S') and early diastolic (E') velocities (5.7 ± 1.1 vs. 6.4 ± 1.1 cm/s, p = 0.02 and 6.1 ± 1.7 vs. 7.7 ± 2.0 cm/s, p = 0.002). In multivariable regression analyses, DM remained significantly associated with impairments of S' and E', respectively. Conclusion In patients without significant CAD, DM is associated with an impaired systolic longitudinal LV function and global diastolic dysfunction. These abnormalities are likely to be markers of adverse prognosis. PMID:20082690
Evaluation of odometry algorithm performances using a railway vehicle dynamic model
NASA Astrophysics Data System (ADS)
Allotta, B.; Pugi, L.; Ridolfi, A.; Malvezzi, M.; Vettori, G.; Rindi, A.
2012-05-01
In modern railway Automatic Train Protection and Automatic Train Control systems, odometry is a safety relevant on-board subsystem which estimates the instantaneous speed and the travelled distance of the train; a high reliability of the odometry estimate is fundamental, since an error on the train position may lead to a potentially dangerous overestimation of the distance available for braking. To improve the odometry estimate accuracy, data fusion of different inputs coming from a redundant sensor layout may be used. Simplified two-dimensional models of railway vehicles have been usually used for Hardware in the Loop test rig testing of conventional odometry algorithms and of on-board safety relevant subsystems (like the Wheel Slide Protection braking system) in which the train speed is estimated from the measures of the wheel angular speed. Two-dimensional models are not suitable to develop solutions like the inertial type localisation algorithms (using 3D accelerometers and 3D gyroscopes) and the introduction of Global Positioning System (or similar) or the magnetometer. In order to test these algorithms correctly and increase odometry performances, a three-dimensional multibody model of a railway vehicle has been developed, using Matlab-Simulink™, including an efficient contact model which can simulate degraded adhesion conditions (the development and prototyping of odometry algorithms involve the simulation of realistic environmental conditions). In this paper, the authors show how a 3D railway vehicle model, able to simulate the complex interactions arising between different on-board subsystems, can be useful to evaluate the odometry algorithm and safety relevant to on-board subsystem performances.
NASA Astrophysics Data System (ADS)
Chen, Yanli; Du, Lianhuan; Yang, Peihua; Sun, Peng; Yu, Xiang; Mai, Wenjie
2015-08-01
Here, we report robust, flexible CNT-based supercapacitor (SC) electrodes fabricated by electrodepositing polypyrrole (PPy) on freestanding vacuum-filtered CNT film. These electrodes demonstrate significantly improved mechanical properties (with the ultimate tensile strength of 16 MPa), and greatly enhanced electrochemical performance (5.6 times larger areal capacitance). The major drawback of conductive polymer electrodes is the fast capacitance decay caused by structural breakdown, which decreases cycling stability but this is not observed in our case. All-solid-state SCs assembled with the robust CNT/PPy electrodes exhibit excellent flexibility, long lifetime (95% capacitance retention after 10,000 cycles) and high electrochemical performance (a total device volumetric capacitance of 4.9 F/cm3). Moreover, a flexible SC pack is demonstrated to light up 53 LEDs or drive a digital watch, indicating the broad potential application of our SCs for portable/wearable electronics.
Proper nozzle location, bit profile, and cutter arrangement affect PDC-bit performance significantly
Garcia-Gavito, D.; Azar, J.J.
1994-09-01
During the past 20 years, the drilling industry has looked to new technology to halt the exponentially increasing costs of drilling oil, gas, and geothermal wells. This technology includes bit design innovations to improve overall drilling performance and reduce drilling costs. These innovations include development of drag bits that use PDC cutters, also called PDC bits, to drill long, continuous intervals of soft to medium-hard formations more economically than conventional three-cone roller-cone bits. The cost advantage is the result of higher rates of penetration (ROP's) and longer bit life obtained with the PDC bits. An experimental study comparing the effects of polycrystalline-diamond-compact (PDC)-bit design features on the dynamic pressure distribution at the bit/rock interface was conducted on a full-scale drilling rig. Results showed that nozzle location, bit profile, and cutter arrangement are significant factors in PDC-bit performance.
Orion Guidance and Control Ascent Abort Algorithm Design and Performance Results
NASA Technical Reports Server (NTRS)
Proud, Ryan W.; Bendle, John R.; Tedesco, Mark B.; Hart, Jeremy J.
2009-01-01
During the ascent flight phase of NASA s Constellation Program, the Ares launch vehicle propels the Orion crew vehicle to an agreed to insertion target. If a failure occurs at any point in time during ascent then a system must be in place to abort the mission and return the crew to a safe landing with a high probability of success. To achieve continuous abort coverage one of two sets of effectors is used. Either the Launch Abort System (LAS), consisting of the Attitude Control Motor (ACM) and the Abort Motor (AM), or the Service Module (SM), consisting of SM Orion Main Engine (OME), Auxiliary (Aux) Jets, and Reaction Control System (RCS) jets, is used. The LAS effectors are used for aborts from liftoff through the first 30 seconds of second stage flight. The SM effectors are used from that point through Main Engine Cutoff (MECO). There are two distinct sets of Guidance and Control (G&C) algorithms that are designed to maximize the performance of these abort effectors. This paper will outline the necessary inputs to the G&C subsystem, the preliminary design of the G&C algorithms, the ability of the algorithms to predict what abort modes are achievable, and the resulting success of the abort system. Abort success will be measured against the Preliminary Design Review (PDR) abort performance metrics and overall performance will be reported. Finally, potential improvements to the G&C design will be discussed.
Hoisie, A.; Lubeck, O.; Wasserman, H.
1998-12-31
The authors develop a model for the parallel performance of algorithms that consist of concurrent, two-dimensional wavefronts implemented in a message passing environment. The model, based on a LogGP machine parameterization, combines the separate contributions of computation and communication wavefronts. They validate the model on three important supercomputer systems, on up to 500 processors. They use data from a deterministic particle transport application taken from the ASCI workload, although the model is general to any wavefront algorithm implemented on a 2-D processor domain. They also use the validated model to make estimates of performance and scalability of wavefront algorithms on 100-TFLOPS computer systems expected to be in existence within the next decade as part of the ASCI program and elsewhere. In this context, the authors analyze two problem sizes. Their model shows that on the largest such problem (1 billion cells), inter-processor communication performance is not the bottleneck. Single-node efficiency is the dominant factor.
NASA Astrophysics Data System (ADS)
Chatterjee, A.; Ghoshal, S. P.; Mukherjee, V.
In this paper, a conventional thermal power system equipped with automatic voltage regulator, IEEE type dual input power system stabilizer (PSS) PSS3B and integral controlled automatic generation control loop is considered. A distributed generation (DG) system consisting of aqua electrolyzer, photovoltaic cells, diesel engine generator, and some other energy storage devices like flywheel energy storage system and battery energy storage system is modeled. This hybrid distributed system is connected to the grid. While integrating this DG with the onventional thermal power system, improved transient performance is noticed. Further improvement in the transient performance of this grid connected DG is observed with the usage of superconducting magnetic energy storage device. The different tunable parameters of the proposed hybrid power system model are optimized by artificial bee colony (ABC) algorithm. The optimal solutions offered by the ABC algorithm are compared with those offered by genetic algorithm (GA). It is also revealed that the optimizing performance of the ABC is better than the GA for this specific application.
NASA Astrophysics Data System (ADS)
Rajalakshmi, N.; Padma Subramanian, D.; Thamizhavel, K.
2015-03-01
The extent of real power loss and voltage deviation associated with overloaded feeders in radial distribution system can be reduced by reconfiguration. Reconfiguration is normally achieved by changing the open/closed state of tie/sectionalizing switches. Finding optimal switch combination is a complicated problem as there are many switching combinations possible in a distribution system. Hence optimization techniques are finding greater importance in reducing the complexity of reconfiguration problem. This paper presents the application of firefly algorithm (FA) for optimal reconfiguration of radial distribution system with distributed generators (DG). The algorithm is tested on IEEE 33 bus system installed with DGs and the results are compared with binary genetic algorithm. It is found that binary FA is more effective than binary genetic algorithm in achieving real power loss reduction and improving voltage profile and hence enhancing the performance of radial distribution system. Results are found to be optimum when DGs are added to the test system, which proved the impact of DGs on distribution system.
Imbir, Kamil K
2016-01-01
Activation mechanisms such as arousal are known to be responsible for slowdown observed in the Emotional Stroop and modified Stroop tasks. Using the duality of mind perspective, we may conclude that both ways of processing information (automatic or controlled) should have their own mechanisms of activation, namely, arousal for an experiential mind, and subjective significance for a rational mind. To investigate the consequences of both, factorial manipulation was prepared. Other factors that influence Stroop task processing such as valence, concreteness, frequency, and word length were controlled. Subjective significance was expected to influence arousal effects. In the first study, the task was to name the color of font for activation charged words. In the second study, activation charged words were, at the same time, combined with an incongruent condition of the classical Stroop task around a fixation point. The task was to indicate the font color for color-meaning words. In both studies, subjective significance was found to shape the arousal impact on performance in terms of the slowdown reduction for words charged with subjective significance. PMID:26869974
Focused R&D For Electrochromic Smart Windowsa: Significant Performance and Yield Enhancements
Mark Burdis; Neil Sbar
2003-01-31
There is a need to improve the energy efficiency of building envelopes as they are the primary factor governing the heating, cooling, lighting and ventilation requirements of buildings--influencing 53% of building energy use. In particular, windows contribute significantly to the overall energy performance of building envelopes, thus there is a need to develop advanced energy efficient window and glazing systems. Electrochromic (EC) windows represent the next generation of advanced glazing technology that will (1) reduce the energy consumed in buildings, (2) improve the overall comfort of the building occupants, and (3) improve the thermal performance of the building envelope. ''Switchable'' EC windows provide, on demand, dynamic control of visible light, solar heat gain, and glare without blocking the view. As exterior light levels change, the window's performance can be electronically adjusted to suit conditions. A schematic illustrating how SageGlass{reg_sign} electrochromic windows work is shown in Figure I.1. SageGlass{reg_sign} EC glazings offer the potential to save cooling and lighting costs, with the added benefit of improving thermal and visual comfort. Control over solar heat gain will also result in the use of smaller HVAC equipment. If a step change in the energy efficiency and performance of buildings is to be achieved, there is a clear need to bring EC technology to the marketplace. This project addresses accelerating the widespread introduction of EC windows in buildings and thus maximizing total energy savings in the U.S. and worldwide. We report on R&D activities to improve the optical performance needed to broadly penetrate the full range of architectural markets. Also, processing enhancements have been implemented to reduce manufacturing costs. Finally, tests are being conducted to demonstrate the durability of the EC device and the dual pane insulating glass unit (IGU) to be at least equal to that of conventional windows.
Performance comparison of multi-label learning algorithms on clinical data for chronic diseases.
Zufferey, Damien; Hofer, Thomas; Hennebert, Jean; Schumacher, Michael; Ingold, Rolf; Bromuri, Stefano
2015-10-01
We are motivated by the issue of classifying diseases of chronically ill patients to assist physicians in their everyday work. Our goal is to provide a performance comparison of state-of-the-art multi-label learning algorithms for the analysis of multivariate sequential clinical data from medical records of patients affected by chronic diseases. As a matter of fact, the multi-label learning approach appears to be a good candidate for modeling overlapped medical conditions, specific to chronically ill patients. With the availability of such comparison study, the evaluation of new algorithms should be enhanced. According to the method, we choose a summary statistics approach for the processing of the sequential clinical data, so that the extracted features maintain an interpretable link to their corresponding medical records. The publicly available MIMIC-II dataset, which contains more than 19,000 patients with chronic diseases, is used in this study. For the comparison we selected the following multi-label algorithms: ML-kNN, AdaBoostMH, binary relevance, classifier chains, HOMER and RAkEL. Regarding the results, binary relevance approaches, despite their elementary design and their independence assumption concerning the chronic illnesses, perform optimally in most scenarios, in particular for the detection of relevant diseases. In addition, binary relevance approaches scale up to large dataset and are easy to learn. However, the RAkEL algorithm, despite its scalability problems when it is confronted to large dataset, performs well in the scenario which consists of the ranking of the labels according to the dominant disease of the patient.
Wolfe, Amy K.; Malone, Elizabeth L.; Heerwagen, Judith H.; Dion, Jerome P.
2014-04-01
The people who use Federal buildings — Federal employees, operations and maintenance staff, and the general public — can significantly impact a building’s environmental performance and the consumption of energy, water, and materials. Many factors influence building occupants’ use of resources (use behaviors) including work process requirements, ability to fulfill agency missions, new and possibly unfamiliar high-efficiency/high-performance building technologies; a lack of understanding, education, and training; inaccessible information or ineffective feedback mechanisms; and cultural norms and institutional rules and requirements, among others. While many strategies have been used to introduce new occupant use behaviors that promote sustainability and reduced resource consumption, few have been verified in the scientific literature or have properly documented case study results. This paper documents validated strategies that have been shown to encourage new use behaviors that can result in significant, persistent, and measureable reductions in resource consumption. From the peer-reviewed literature, the paper identifies relevant strategies for Federal facilities and commercial buildings that focus on the individual, groups of individuals (e.g., work groups), and institutions — their policies, requirements, and culture. The paper documents methods with evidence of success in changing use behaviors and enabling occupants to effectively interact with new technologies/designs. It also provides a case study of the strategies used at a Federal facility — Fort Carson, Colorado. The paper documents gaps in the current literature and approaches, and provides topics for future research.
Hare, P W; Morse, R E
1999-01-01
Under certain circumstances, wells in unconfined aquifers can display significant water level fluctuations in response to changes in barometric pressure. This is illustrated by Hare and Morse (1997) at a site where a portion of the unconfined aquifer is isolated by a soil-bentonite cutoff wall and clay cap. A relief well located within the containment system displays water level fluctuations that mirror barometric pressure changes. Water levels fluctuated 0.37 m in response to barometric pressure changes of 2.87 centimeters mercury (cm-Hg), representing a barometric efficiency of 93.6%. As described in this paper, the short-term variability in water level elevations inside the containment system had to be considered to develop a reliable post-enhancement performance monitoring program. The approach that was ultimately selected involves correcting the water level elevations obtained in the relief well within the containment system for the effects of barometric pressure changes prior to comparison with the water level elevations in an observation well in the aquifer outside the system. The reliability of the post-enhancement performance monitoring program is improved further by simply requiring that any decision to enhance the containment system be based on the water level measurements obtained during two consecutive months. Using this approach, the probability that the containment system's performance will erroneously be deemed unacceptable is low. The post-enhancement performance monitoring program also requires no extra field work and does not involve any specialized equipment, which helps to keep operation and maintenance costs to a minimum.
Xu, Hang; Su, Shi; Tang, Wuji; Wei, Meng; Wang, Tao; Wang, Dongjin; Ge, Weihong
2015-09-01
A large number of warfarin pharmacogenetics algorithms have been published. Our research was aimed to evaluate the performance of the selected pharmacogenetic algorithms in patients with surgery of heart valve replacement and heart valvuloplasty during the phase of initial and stable anticoagulation treatment. 10 pharmacogenetic algorithms were selected by searching PubMed. We compared the performance of the selected algorithms in a cohort of 193 patients during the phase of initial and stable anticoagulation therapy. Predicted dose was compared to therapeutic dose by using a predicted dose percentage that falls within 20% threshold of the actual dose (percentage within 20%) and mean absolute error (MAE). The average warfarin dose for patients was 3.05±1.23mg/day for initial treatment and 3.45±1.18mg/day for stable treatment. The percentages of the predicted dose within 20% of the therapeutic dose were 44.0±8.8% and 44.6±9.7% for the initial and stable phases, respectively. The MAEs of the selected algorithms were 0.85±0.18mg/day and 0.93±0.19mg/day, respectively. All algorithms had better performance in the ideal group than in the low dose and high dose groups. The only exception is the Wadelius et al. algorithm, which had better performance in the high dose group. The algorithms had similar performance except for the Wadelius et al. and Miao et al. algorithms, which had poor accuracy in our study cohort. The Gage et al. algorithm had better performance in both phases of initial and stable treatment. Algorithms had relatively higher accuracy in the >50years group of patients on the stable phase.
Assessment of next-best-view algorithms performance with various 3D scanners and manipulator
NASA Astrophysics Data System (ADS)
Karaszewski, M.; Adamczyk, M.; Sitnik, R.
2016-09-01
The problem of calculating three dimensional (3D) sensor position (and orientation) during the digitization of real-world objects (called next best view planning or NBV) has been an active topic of research for over 20 years. While many solutions have been developed, it is hard to compare their quality based only on the exemplary results presented in papers. We implemented 13 of the most popular NBV algorithms and evaluated their performance by digitizing five objects of various properties, using three measurement heads with different working volumes mounted on a 6-axis robot with a rotating table for placing objects. The results obtained for the 13 algorithms were then compared based on four criteria: the number of directional measurements, digitization time, total positioning distance, and surface coverage required to digitize test objects with available measurement heads.
NASA Technical Reports Server (NTRS)
Bohse, J. R.; Bewtra, M.; Barnes, W. L.
1979-01-01
The rationale and procedures used in the radiometric calibration and correction of Heat Capacity Mapping Mission (HCMM) data are presented. Instrument-level testing and calibration of the Heat Capacity Mapping Radiometer (HCMR) were performed by the sensor contractor ITT Aerospace/Optical Division. The principal results are included. From the instrumental characteristics and calibration data obtained during ITT acceptance tests, an algorithm for post-launch processing was developed. Integrated spacecraft-level sensor calibration was performed at Goddard Space Flight Center (GSFC) approximately two months before launch. This calibration provided an opportunity to validate the data calibration algorithm. Instrumental parameters and results of the validation are presented and the performances of the instrument and the data system after launch are examined with respect to the radiometric results. Anomalies and their consequences are discussed. Flight data indicates a loss in sensor sensitivity with time. The loss was shown to be recoverable by an outgassing procedure performed approximately 65 days after the infrared channel was turned on. It is planned to repeat this procedure periodically.
Palmer, M.P.; Abreu, E.L.; Mastrangelo, A.; Murray, M.M.
2009-01-01
Collagen-platelet composites have recently been successfully used as scaffolds to stimulate anterior cruciate ligament (ACL) wound healing in large animal models. These materials are typically kept on ice until use to prevent premature gelation; however, with surgical use, placement of a cold solution then requires up to an hour while the solution comes to body temperature (at which point gelation occurs). Bringing the solution to a higher temperature before injection would likely decrease this intra-operative wait; however, the effects of this on composite performance are not known. The hypothesis tested here was that increasing the temperature of the gel at the time of injection would significantly decrease the time to gelation, but would not significantly alter the mechanical properties of the composite or its ability to support functional tissue repair. Primary outcome measures included the maximum elastic modulus (stiffness) of the composite in vitro and the in vivo yield load of an ACL transection treated with an injected collagen-platelet composite. In vitro findings were that injection temperatures over 30°C resulted in a faster visco-elastic transition; however, the warmed composites had a 50% decrease in their maximum elastic modulus. In vivo studies found that warming the gels prior to injection also resulted in a decrease in the yield load of the healing ACL at 14 weeks. These studies suggest that increasing injection temperature of collagen-platelet composites results in a decrease in performance of the composite in vitro and in the strength of the healing ligament in vivo and this technique should be used only with great caution. PMID:19030174
He, Ting; Zu, Lianhai; Zhang, Yan; Mao, Chengliang; Xu, Xiaoxiang; Yang, Jinhu; Yang, Shihe
2016-08-23
Semiconductor nanowires that have been extensively studied are typically in a crystalline phase. Much less studied are amorphous semiconductor nanowires due to the difficulty for their synthesis, despite a set of characteristics desirable for photoelectric devices, such as higher surface area, higher surface activity, and higher light harvesting. In this work of combined experiment and computation, taking Zn2GeO4 (ZGO) as an example, we propose a site-specific heteroatom substitution strategy through a solution-phase ions-alternative-deposition route to prepare amorphous/crystalline Si-incorporated ZGO nanowires with tunable band structures. The substitution of Si atoms for the Zn or Ge atoms distorts the bonding network to a different extent, leading to the formation of amorphous Zn1.7Si0.3GeO4 (ZSGO) or crystalline Zn2(GeO4)0.88(SiO4)0.12 (ZGSO) nanowires, respectively, with different bandgaps. The amorphous ZSGO nanowire arrays exhibit significantly enhanced performance in photoelectrochemical water splitting, such as higher and more stable photocurrent, and faster photoresponse and recovery, relative to crystalline ZGSO and ZGO nanowires in this work, as well as ZGO photocatalysts reported previously. The remarkable performance highlights the advantages of the ZSGO amorphous nanowires for photoelectric devices, such as higher light harvesting capability, faster charge separation, lower charge recombination, and higher surface catalytic activity.
He, Ting; Zu, Lianhai; Zhang, Yan; Mao, Chengliang; Xu, Xiaoxiang; Yang, Jinhu; Yang, Shihe
2016-08-23
Semiconductor nanowires that have been extensively studied are typically in a crystalline phase. Much less studied are amorphous semiconductor nanowires due to the difficulty for their synthesis, despite a set of characteristics desirable for photoelectric devices, such as higher surface area, higher surface activity, and higher light harvesting. In this work of combined experiment and computation, taking Zn2GeO4 (ZGO) as an example, we propose a site-specific heteroatom substitution strategy through a solution-phase ions-alternative-deposition route to prepare amorphous/crystalline Si-incorporated ZGO nanowires with tunable band structures. The substitution of Si atoms for the Zn or Ge atoms distorts the bonding network to a different extent, leading to the formation of amorphous Zn1.7Si0.3GeO4 (ZSGO) or crystalline Zn2(GeO4)0.88(SiO4)0.12 (ZGSO) nanowires, respectively, with different bandgaps. The amorphous ZSGO nanowire arrays exhibit significantly enhanced performance in photoelectrochemical water splitting, such as higher and more stable photocurrent, and faster photoresponse and recovery, relative to crystalline ZGSO and ZGO nanowires in this work, as well as ZGO photocatalysts reported previously. The remarkable performance highlights the advantages of the ZSGO amorphous nanowires for photoelectric devices, such as higher light harvesting capability, faster charge separation, lower charge recombination, and higher surface catalytic activity. PMID:27494205
Nanoporosity Significantly Enhances the Biological Performance of Engineered Glass Tissue Scaffolds
Wang, Shaojie; Kowal, Tia J.; Marei, Mona K.
2013-01-01
Nanoporosity is known to impact the performance of implants and scaffolds such as bioactive glass (BG) scaffolds, either by providing a higher concentration of bioactive chemical species from enhanced surface area, or due to inherent nanoscale topology, or both. To delineate the role of these two characteristics, BG scaffolds have been fabricated with nearly identical surface area (81 and 83±2 m2/g) but significantly different pore size (av. 3.7 and 17.7 nm) by varying both the sintering temperature and the ammonia concentration during the solvent exchange phase of the sol-gel fabrication process. In vitro tests performed with MC3T3-E1 preosteoblast cells on such scaffolds show that initial cell attachment is increased on samples with the smaller nanopore size, providing the first direct evidence of the influence of nanopore topography on cell response to a bioactive structure. Furthermore, in vivo animal tests in New Zealand rabbits (subcutaneous implantation) indicate that nanopores promote colonization and cell penetration into these scaffolds, further demonstrating the favorable effects of nanopores in tissue-engineering-relevant BG scaffolds. PMID:23427819
Zeng, Zhiping; Yu, Dingshan; He, Ziming; Liu, Jing; Xiao, Fang-Xing; Zhang, Yan; Wang, Rong; Bhattacharyya, Dibakar; Tan, Timothy Thatt Yang
2016-01-01
Covalent bonding of graphene oxide quantum dots (GOQDs) onto amino modified polyvinylidene fluoride (PVDF) membrane has generated a new type of nano-carbon functionalized membrane with significantly enhanced antibacterial and antibiofouling properties. A continuous filtration test using E. coli containing feedwater shows that the relative flux drop over GOQDs modified PVDF is 23%, which is significantly lower than those over pristine PVDF (86%) and GO-sheet modified PVDF (62%) after 10 h of filtration. The presence of GOQD coating layer effectively inactivates E. coli and S. aureus cells, and prevents the biofilm formation on the membrane surface, producing excellent antimicrobial activity and potentially antibiofouling capability, more superior than those of previously reported two-dimensional GO sheets and one-dimensional CNTs modified membranes. The distinctive antimicrobial and antibiofouling performances could be attributed to the unique structure and uniform dispersion of GOQDs, enabling the exposure of a larger fraction of active edges and facilitating the formation of oxidation stress. Furthermore, GOQDs modified membrane possesses satisfying long-term stability and durability due to the strong covalent interaction between PVDF and GOQDs. This study opens up a new synthetic avenue in the fabrication of efficient surface-functionalized polymer membranes for potential waste water treatment and biomolecules separation. PMID:26832603
NASA Astrophysics Data System (ADS)
Zeng, Zhiping; Yu, Dingshan; He, Ziming; Liu, Jing; Xiao, Fang-Xing; Zhang, Yan; Wang, Rong; Bhattacharyya, Dibakar; Tan, Timothy Thatt Yang
2016-02-01
Covalent bonding of graphene oxide quantum dots (GOQDs) onto amino modified polyvinylidene fluoride (PVDF) membrane has generated a new type of nano-carbon functionalized membrane with significantly enhanced antibacterial and antibiofouling properties. A continuous filtration test using E. coli containing feedwater shows that the relative flux drop over GOQDs modified PVDF is 23%, which is significantly lower than those over pristine PVDF (86%) and GO-sheet modified PVDF (62%) after 10 h of filtration. The presence of GOQD coating layer effectively inactivates E. coli and S. aureus cells, and prevents the biofilm formation on the membrane surface, producing excellent antimicrobial activity and potentially antibiofouling capability, more superior than those of previously reported two-dimensional GO sheets and one-dimensional CNTs modified membranes. The distinctive antimicrobial and antibiofouling performances could be attributed to the unique structure and uniform dispersion of GOQDs, enabling the exposure of a larger fraction of active edges and facilitating the formation of oxidation stress. Furthermore, GOQDs modified membrane possesses satisfying long-term stability and durability due to the strong covalent interaction between PVDF and GOQDs. This study opens up a new synthetic avenue in the fabrication of efficient surface-functionalized polymer membranes for potential waste water treatment and biomolecules separation.
NASA Astrophysics Data System (ADS)
Korolev, A.; Field, P. R.
2015-02-01
Shattering presents a serious obstacle to current airborne in situ methods of characterizing the microphysical properties of ice clouds. Small shattered fragments result from the impact of natural ice crystals with the forward parts of aircraft-mounted measurement probes. The presence of these shattered fragments may result in a significant overestimation of the measured concentration of small ice crystals, contaminating the measurement of the ice particle size distribution (PSD). One method of identifying shattered particles is to use an inter-arrival time algorithm. This method is based on the assumption that shattered fragments form spatial clusters that have short inter-arrival times between particles, relative to natural particles, when they pass through the sample volume of the probe. The inter-arrival time algorithm is a successful technique for the classification of shattering artifacts and natural particles. This study assesses the limitations and efficiency of the inter-arrival time algorithm. The analysis has been performed using simultaneous measurements of two-dimensional (2-D) optical array probes with the standard and antishattering "K-tips" collected during the Airborne Icing Instrumentation Experiment (AIIE). It is shown that the efficiency of the algorithm depends on ice particle size, concentration and habit. Additional numerical simulations indicate that the effectiveness of the inter-arrival time algorithm to eliminate shattering artifacts can be significantly restricted in some cases. Improvements to the inter-arrival time algorithm are discussed. It is demonstrated that blind application of the inter-arrival time algorithm cannot filter out all shattered aggregates. To mitigate against the effects of shattering, the inter-arrival time algorithm should be used together with other means, such as antishattering tips and specially designed algorithms for segregation of shattered artifacts and natural particles.
Fuchs, M; Oeken, J; Hotopp, T; Täschner, R; Hentschel, B; Behrendt, W
2000-06-01
Auditory similarities in voices of monozygotic twins have already been described in the literature. However, is there a clinical relevance? Thus, the present study was designed to identify parameters of vocal performance and acoustic features which are significantly more similar in monozygotic twins than in non-related persons. In our hypothesis, comparable prerequisites for an increased vocal load in a profession or in an artistic education of the voice could be due to these similarities. We compared intra-pair differences with data from a control group. Moreover, we examined the correlation of intra-pair differences with the age of the monozygotic twins. A greater difference in older twin pairs than in younger pairs could show the effect of an exogene influence. In addition to the few phoniatric studies in twins in the literature, we used current methods for acoustic analysis. We examined seven parameters of vocal performance and three acoustic features in 31 monozygotic twin pairs (median age 36 years, range 18-75 years) and compared them with 30 control group pairs, which consisted of non-related persons of the same age and sex, newly combined from the group of monozygotic twins ("statistical twins"). We found significant differences in seven of ten parameters (vocal range, highest and lowest vocal fundamental frequency, fundamental speaking frequency, maximum voice intensity, number of partials, vibrato of intensity; U-test by Mann-Whitney). No correlation of the differences of the identical twins with age was found in the examined parameters. The voices of identical twins are significantly more similar than those of non-related persons regarding the above mentioned features. Thus, the suitability of the voices of monozygotic twins for professions with a high demand on voice is comparable. Results of the group comparison correlate largely with the literature. The missing correlation with age could be due to the fact that the environmental effects were not
Cottrell, R.Les; Logg, Connie; Chhaparia, Mahesh; Grigoriev, Maxim; Haro, Felipe; Nazir, Fawad; Sandford, Mark
2006-01-25
End-to-End fault and performance problems detection in wide area production networks is becoming increasingly hard as the complexity of the paths, the diversity of the performance, and dependency on the network increase. Several monitoring infrastructures are built to monitor different network metrics and collect monitoring information from thousands of hosts around the globe. Typically there are hundreds to thousands of time-series plots of network metrics which need to be looked at to identify network performance problems or anomalous variations in the traffic. Furthermore, most commercial products rely on a comparison with user configured static thresholds and often require access to SNMP-MIB information, to which a typical end-user does not usually have access. In our paper we propose new techniques to detect network performance problems proactively in close to realtime and we do not rely on static thresholds and SNMP-MIB information. We describe and compare the use of several different algorithms that we have implemented to detect persistent network problems using anomalous variations analysis in real end-to-end Internet performance measurements. We also provide methods and/or guidance for how to set the user settable parameters. The measurements are based on active probes running on 40 production network paths with bottlenecks varying from 0.5Mbits/s to 1000Mbit/s. For well behaved data (no missed measurements and no very large outliers) with small seasonal changes most algorithms identify similar events. We compare the algorithms' robustness with respect to false positives and missed events especially when there are large seasonal effects in the data. Our proposed techniques cover a wide variety of network paths and traffic patterns. We also discuss the applicability of the algorithms in terms of their intuitiveness, their speed of execution as implemented, and areas of applicability. Our encouraging results compare and evaluate the accuracy of our detection
ERIC Educational Resources Information Center
Clauser, Brian E.; Ross, Linette P.; Clyman, Stephen G.; Rose, Kathie M.; Margolis, Melissa J.; Nungester, Ronald J.; Piemme, Thomas E.; Chang, Lucy; El-Bayoumi, Gigi; Malakoff, Gary L.; Pincetl, Pierre S.
1997-01-01
Describes an automated scoring algorithm for a computer-based simulation examination of physicians' patient-management skills. Results with 280 medical students show that scores produced using this algorithm are highly correlated to actual clinician ratings. Scores were also effective in discriminating between case performance judged passing or…
Speakman, John R; Fletcher, Quinn; Vaanholt, Lobke
2013-03-01
The epidemics of obesity and diabetes have aroused great interest in the analysis of energy balance, with the use of organisms ranging from nematode worms to humans. Although generating energy-intake or -expenditure data is relatively straightforward, the most appropriate way to analyse the data has been an issue of contention for many decades. In the last few years, a consensus has been reached regarding the best methods for analysing such data. To facilitate using these best-practice methods, we present here an algorithm that provides a step-by-step guide for analysing energy-intake or -expenditure data. The algorithm can be used to analyse data from either humans or experimental animals, such as small mammals or invertebrates. It can be used in combination with any commercial statistics package; however, to assist with analysis, we have included detailed instructions for performing each step for three popular statistics packages (SPSS, MINITAB and R). We also provide interpretations of the results obtained at each step. We hope that this algorithm will assist in the statistically appropriate analysis of such data, a field in which there has been much confusion and some controversy.
Boosting runtime-performance of photon pencil beam algorithms for radiotherapy treatment planning.
Siggel, M; Ziegenhein, P; Nill, S; Oelfke, U
2012-10-01
Pencil beam algorithms are still considered as standard photon dose calculation methods in Radiotherapy treatment planning for many clinical applications. Despite their established role in radiotherapy planning their performance and clinical applicability has to be continuously adapted to evolving complex treatment techniques such as adaptive radiation therapy (ART). We herewith report on a new highly efficient version of a well-established pencil beam convolution algorithm which relies purely on measured input data. A method was developed that improves raytracing efficiency by exploiting the capability of modern CPU architecture for a runtime reduction. Since most of the current desktop computers provide more than one calculation unit we used symmetric multiprocessing extensively to parallelize the workload and thus decreasing the algorithmic runtime. To maximize the advantage of code parallelization, we present two implementation strategies - one for the dose calculation in inverse planning software, and one for traditional forward planning. As a result, we could achieve on a 16-core personal computer with AMD processors a superlinear speedup factor of approx. 18 for calculating the dose distribution of typical forward IMRT treatment plans. PMID:22071169
Performance evaluation of a routing algorithm based on Hopfield Neural Network for network-on-chip
NASA Astrophysics Data System (ADS)
Esmaelpoor, Jamal; Ghafouri, Abdollah
2015-12-01
Network on chip (NoC) has emerged as a solution to overcome the system on chip growing complexity and design challenges. A proper routing algorithm is a key issue of an NoC design. An appropriate routing method balances load across the network channels and keeps path length as short as possible. This survey investigates the performance of a routing algorithm based on Hopfield Neural Network. It is a dynamic programming to provide optimal path and network monitoring in real time. The aim of this article is to analyse the possibility of using a neural network as a router. The algorithm takes into account the path with the lowest delay (cost) form source to destination. In other words, the path a message takes from source to destination depends on network traffic situation at the time and it is the fastest one. The simulation results show that the proposed approach improves average delay, throughput and network congestion efficiently. At the same time, the increase in power consumption is almost negligible.
The royal road for genetic algorithms: Fitness landscapes and GA performance
Mitchell, M.; Holland, J.H. ); Forrest, S. . Dept. of Computer Science)
1991-01-01
Genetic algorithms (GAs) play a major role in many artificial-life systems, but there is often little detailed understanding of why the GA performs as it does, and little theoretical basis on which to characterize the types of fitness landscapes that lead to successful GA performance. In this paper we propose a strategy for addressing these issues. Our strategy consists of defining a set of features of fitness landscapes that are particularly relevant to the GA, and experimentally studying how various configurations of these features affect the GA's performance along a number of dimensions. In this paper we informally describe an initial set of proposed feature classes, describe in detail one such class ( Royal Road'' functions), and present some initial experimental results concerning the role of crossover and building blocks'' on landscapes constructed from features of this class. 27 refs., 1 fig., 5 tabs.
Tachikawa, Kenta; Izawa, Shun; Ono, Yumie; Kuriki, Shinya; Ishiyama, Atsushi
2015-08-01
Significant correlation exists in the blood-oxygen-level-dependent (BOLD) signals of resting-state fMRI across different regions in the brain. These regions form the default mode network (DMN), salience network (SN), sensory networks, and others. Among these, the DMN is widely investigated in relation to various mental diseases. Several analytic methods are available for obtaining the DMN activity from individuals' fMRI time-series signals, but a fully effective method has not yet been established. In the present study, we examined a functional connectivity analysis and three algorithms of blind source separation including independent component analysis, second-order blind identification, and non-negative matrix factorization using a set of resting-state fMRI data measured for twelve young participants. Results showed that the second-order blind identification yielded superior performance for the DMN detection, indicating significant activation in all DMN regions based on statistical parametric maps. PMID:26736630
K-Means Re-Clustering-Algorithmic Options with Quantifiable Performance Comparisons
Meyer, A W; Paglieroni, D; Asteneh, C
2002-12-17
This paper presents various architectural options for implementing a K-Means Re-Clustering algorithm suitable for unsupervised segmentation of hyperspectral images. Performance metrics are developed based upon quantitative comparisons of convergence rates and segmentation quality. A methodology for making these comparisons is developed and used to establish K values that produce the best segmentations with minimal processing requirements. Convergence rates depend on the initial choice of cluster centers. Consequently, this same methodology may be used to evaluate the effectiveness of different initialization techniques.
2014-01-01
Background We have previously validated administrative data algorithms to identify patients with rheumatoid arthritis (RA) using rheumatology clinic records as the reference standard. Here we reassessed the accuracy of the algorithms using primary care records as the reference standard. Methods We performed a retrospective chart abstraction study using a random sample of 7500 adult patients under the care of 83 family physicians contributing to the Electronic Medical Record Administrative data Linked Database (EMRALD) in Ontario, Canada. Using physician-reported diagnoses as the reference standard, we computed and compared the sensitivity, specificity, and predictive values for over 100 administrative data algorithms for RA case ascertainment. Results We identified 69 patients with RA for a lifetime RA prevalence of 0.9%. All algorithms had excellent specificity (>97%). However, sensitivity varied (75-90%) among physician billing algorithms. Despite the low prevalence of RA, most algorithms had adequate positive predictive value (PPV; 51-83%). The algorithm of “[1 hospitalization RA diagnosis code] or [3 physician RA diagnosis codes with ≥1 by a specialist over 2 years]” had a sensitivity of 78% (95% CI 69–88), specificity of 100% (95% CI 100–100), PPV of 78% (95% CI 69–88) and NPV of 100% (95% CI 100–100). Conclusions Administrative data algorithms for detecting RA patients achieved a high degree of accuracy amongst the general population. However, results varied slightly from our previous report, which can be attributed to differences in the reference standards with respect to disease prevalence, spectrum of disease, and type of comparator group. PMID:24956925
NASA Technical Reports Server (NTRS)
Orme, John S.; Schkolnik, Gerard S.
1995-01-01
Performance Seeking Control (PSC), an onboard, adaptive, real-time optimization algorithm, relies upon an onboard propulsion system model. Flight results illustrated propulsion system performance improvements as calculated by the model. These improvements were subject to uncertainty arising from modeling error. Thus to quantify uncertainty in the PSC performance improvements, modeling accuracy must be assessed. A flight test approach to verify PSC-predicted increases in thrust (FNP) and absolute levels of fan stall margin is developed and applied to flight test data. Application of the excess thrust technique shows that increases of FNP agree to within 3 percent of full-scale measurements for most conditions. Accuracy to these levels is significant because uncertainty bands may now be applied to the performance improvements provided by PSC. Assessment of PSC fan stall margin modeling accuracy was completed with analysis of in-flight stall tests. Results indicate that the model overestimates the stall margin by between 5 to 10 percent. Because PSC achieves performance gains by using available stall margin, this overestimation may represent performance improvements to be recovered with increased modeling accuracy. Assessment of thrust and stall margin modeling accuracy provides a critical piece for a comprehensive understanding of PSC's capabilities and limitations.
Stefaniak, Tomasz J.; Makarewicz, Wojciech; Proczko, Monika; Gruca, Zbigniew; Śledziński, Zbigniew
2011-01-01
Introduction In the era of flowering minimally invasive surgical techniques there is a need for new methods of teaching surgery and supervision of progress in skills and expertise. Virtual and physical box-trainers seem especially fit for this purpose, and allow for improvement of proficiency required in laparoscopic surgery. Material and methods The study included 34 students who completed the authors‘ laparoscopic training on physical train-boxes. Progress was monitored by accomplishment of 3 exercises: moving pellets from one place to another, excising and clipping. Analysed parameters included time needed to complete the exercise and right and left hand movement tracks. Students were asked to do assigned tasks prior to, in the middle and after the training. Results The duration of the course was 28 h in total. Significant shortening of the time to perform each exercise and reduction of the left hand track were achieved. The right hand track was shortened only in exercise number 1. Conclusions Exercises in the laboratory setting should be regarded as an important element of the process of skills acquisition by a young surgeon. Virtual reality laparoscopic training seems to be a new, interesting educational tool, and at the same time allows for reliable control and assessment of progress. PMID:23255997
NASA Astrophysics Data System (ADS)
Zittersteijn, Michiel; Schildknecht, Thomas; Vananti, Alessandro; Dolado Perez, Juan Carlos; Martinot, Vincent
2016-07-01
Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the correlation and orbit determination problems simultaneously, and is able to efficiently process large data sets with minimal manual intervention. This problem is also known as the Multiple Target Tracking (MTT) problem. The complexity of the MTT problem is defined by its dimension S. Current research tends to focus on the S = 2 MTT problem. The reason for this is that for S = 2 the problem has a P-complexity. However, with S = 2 the decision to associate a set of observations is based on the minimum amount of information, in ambiguous situations (e.g. satellite clusters) this will lead to incorrect associations. The S > 2 MTT problem is an NP-hard combinatorial optimization problem. In previous work an Elitist Genetic Algorithm (EGA) was proposed as a method to approximately solve this problem. It was shown that the EGA is able to find a good approximate solution with a polynomial time complexity. The EGA relies on solving the Lambert problem in order to perform the necessary orbit determinations. This means that the algorithm is restricted to orbits that are described by Keplerian motion. The work presented in this paper focuses on the impact that this restriction has on the algorithm performance.
NASA Technical Reports Server (NTRS)
Ramachandran, Ganesh K.; Akopian, David; Heckler, Gregory W.; Winternitz, Luke B.
2011-01-01
Location technologies have many applications in wireless communications, military and space missions, etc. US Global Positioning System (GPS) and other existing and emerging Global Navigation Satellite Systems (GNSS) are expected to provide accurate location information to enable such applications. While GNSS systems perform very well in strong signal conditions, their operation in many urban, indoor, and space applications is not robust or even impossible due to weak signals and strong distortions. The search for less costly, faster and more sensitive receivers is still in progress. As the research community addresses more and more complicated phenomena there exists a demand on flexible multimode reference receivers, associated SDKs, and development platforms which may accelerate and facilitate the research. One of such concepts is the software GPS/GNSS receiver (GPS SDR) which permits a facilitated access to algorithmic libraries and a possibility to integrate more advanced algorithms without hardware and essential software updates. The GNU-SDR and GPS-SDR open source receiver platforms are such popular examples. This paper evaluates the performance of recently proposed block-corelator techniques for acquisition and tracking of GPS signals using open source GPS-SDR platform.
Karayiannis, Nikos Ch.; Kröger, Martin
2009-01-01
We review the methodology, algorithmic implementation and performance characteristics of a hierarchical modeling scheme for the generation, equilibration and topological analysis of polymer systems at various levels of molecular description: from atomistic polyethylene samples to random packings of freely-jointed chains of tangent hard spheres of uniform size. Our analysis focuses on hitherto less discussed algorithmic details of the implementation of both, the Monte Carlo (MC) procedure for the system generation and equilibration, and a postprocessing step, where we identify the underlying topological structure of the simulated systems in the form of primitive paths. In order to demonstrate our arguments, we study how molecular length and packing density (volume fraction) affect the performance of the MC scheme built around chain-connectivity altering moves. In parallel, we quantify the effect of finite system size, of polydispersity, and of the definition of the number of entanglements (and related entanglement molecular weight) on the results about the primitive path network. Along these lines we approve main concepts which had been previously proposed in the literature. PMID:20087477
NASA Technical Reports Server (NTRS)
Vo, Q. D.
1984-01-01
A software package developed to simulate the performance of the byte-oriented Viterbi decoding algorithm for unit-memory (UM) codes on both 3-bit and 4-bit quantized AWGN channels is described. The simulation is shown to require negligible memory and less time than that for the RTMBEP algorith, although they both provide similar performance in terms of symbol-error probability. This makes it possible to compute the symbol-error probability of large codes and to determine the signal-to-noise ratio required to achieve a bit error rate (BER) of 0.000001 for corresponding concatenated systems. A (7, 10/48) UM code, 10-bit Reed-Solomon code combination achieves the required BER at 1.08 dB for a 3-bit quantized channel and at 0.91 dB for a 4-bit quantized channel.
The performance of phylogenetic algorithms in estimating haplotype genealogies with migration.
Salzburger, Walter; Ewing, Greg B; Von Haeseler, Arndt
2011-05-01
Genealogies estimated from haplotypic genetic data play a prominent role in various biological disciplines in general and in phylogenetics, population genetics and phylogeography in particular. Several software packages have specifically been developed for the purpose of reconstructing genealogies from closely related, and hence, highly similar haplotype sequence data. Here, we use simulated data sets to test the performance of traditional phylogenetic algorithms, neighbour-joining, maximum parsimony and maximum likelihood in estimating genealogies from nonrecombining haplotypic genetic data. We demonstrate that these methods are suitable for constructing genealogies from sets of closely related DNA sequences with or without migration. As genealogies based on phylogenetic reconstructions are fully resolved, but not necessarily bifurcating, and without reticulations, these approaches outperform widespread 'network' constructing methods. In our simulations of coalescent scenarios involving panmictic, symmetric and asymmetric migration, we found that phylogenetic reconstruction methods performed well, while the statistical parsimony approach as implemented in TCS performed poorly. Overall, parsimony as implemented in the PHYLIP package performed slightly better than other methods. We further point out that we are not making the case that widespread 'network' constructing methods are bad, but that traditional phylogenetic tree finding methods are applicable to haplotypic data and exhibit reasonable performance with respect to accuracy and robustness. We also discuss some of the problems of converting a tree to a haplotype genealogy, in particular that it is nonunique. PMID:21457168
Competing Sudakov veto algorithms
NASA Astrophysics Data System (ADS)
Kleiss, Ronald; Verheyen, Rob
2016-07-01
We present a formalism to analyze the distribution produced by a Monte Carlo algorithm. We perform these analyses on several versions of the Sudakov veto algorithm, adding a cutoff, a second variable and competition between emission channels. The formal analysis allows us to prove that multiple, seemingly different competition algorithms, including those that are currently implemented in most parton showers, lead to the same result. Finally, we test their performance in a semi-realistic setting and show that there are significantly faster alternatives to the commonly used algorithms.
Basic Performance of the Standard Retrieval Algorithm for the Dual-frequency Precipitation Radar
NASA Astrophysics Data System (ADS)
Seto, S.; Iguchi, T.; Kubota, T.
2013-12-01
applied again by using the adjusted k-Z relations. By iterating a combination of the HB method and the DFR method, k-Z relations are improved. This is termed HB-DFR method (Seto et al. 2013). Though k-Z relations are adjusted simultaneously for all range bins using SRT method, this method can adjust k-Z relation at a range bin independently of other range bins. Therefore, in this method, DSD is represented on a 2-dimensional plane. The HB-DFR method has been incorporated in the DPR Level 2 standard algorithm (L2). The basic performance of L2 is tested with synthetic dataset which were produced from the TRMM/PR standard product. In L2, when only KuPR radar measurement is used, precipitation estimates are in good agreement with the corresponding rain rate estimates in the PR standard product. However, when both KuPR and KaPR radars measurements are used and the HB-DFR method is applied, the precipitation rate estimates are deviated from the estimates in the PR standard product. This is partly because of the poor performance of the HB-DFR and is also partly because of the overestimation in PIA by the Dual-frequency SRT. Improvement of the standard algorithm particularly for the dual-frequency measurement will be presented.
NASA Astrophysics Data System (ADS)
Ha, S. H.; Choi, S. B.; Lee, G. S.; Yoo, W. H.
2013-02-01
This paper presents control performance evaluation of railway vehicle featured by semi-active suspension system using magnetorheological (MR) fluid damper. In order to achieve this goal, a nine degree of freedom of railway vehicle model, which includes car body and bogie, is established. The wheel-set data is loaded from measured value of railway vehicle. The MR damper system is incorporated with the governing equation of motion of the railway vehicle model which includes secondary suspension. To illustrate the effectiveness of the controlled MR dampers on suspension system of railway vehicle, the control law using the sky-ground hook controller is adopted. This controller takes into account for both vibration control of car body and increasing stability of bogie by adopting a weighting parameter between two performance requirements. The parameters appropriately determined by employing a fuzzy algorithm associated with two fuzzy variables: the lateral speed of the car body and the lateral performance of the bogie. Computer simulation results of control performances such as vibration control and stability analysis are presented in time and frequency domains.
NASA Astrophysics Data System (ADS)
Ciany, Charles M.; Zurawski, William C.
2009-05-01
Raytheon has extensively processed high-resolution sidescan sonar images with its CAD/CAC algorithms to provide classification of targets in a variety of shallow underwater environments. The Raytheon CAD/CAC algorithm is based on non-linear image segmentation into highlight, shadow, and background regions, followed by extraction, association, and scoring of features from candidate highlight and shadow regions of interest (ROIs). The targets are classified by thresholding an overall classification score, which is formed by summing the individual feature scores. The algorithm performance is measured in terms of probability of correct classification as a function of false alarm rate, and is determined by both the choice of classification features and the manner in which the classifier rates and combines these features to form its overall score. In general, the algorithm performs very reliably against targets that exhibit "strong" highlight and shadow regions in the sonar image- i.e., both the highlight echo and its associated shadow region from the target are distinct relative to the ambient background. However, many real-world undersea environments can produce sonar images in which a significant percentage of the targets exhibit either "weak" highlight or shadow regions in the sonar image. The challenge of achieving robust performance in these environments has traditionally been addressed by modifying the individual feature scoring algorithms to optimize the separation between the corresponding highlight or shadow feature scores of targets and non-targets. This study examines an alternate approach that employs principles of Fisher fusion to determine a set of optimal weighting coefficients that are applied to the individual feature scores before summing to form the overall classification score. The results demonstrate improved performance of the CAD/CAC algorithm on at-sea data sets.
NASA Astrophysics Data System (ADS)
Garcia, C. A.; Ferreira, A.; Dogliotti, A. I.; Tavano, V. M.; High Latitude Oceanography Group-GOAL
2011-12-01
The PATagonia EXperiment (PATEX) is a Brazilian research project, which has the overall objective of characterizing the environmental constraints, phytoplankton assemblages, primary production rates, bio-optical characteristics, and air-sea CO2 fluxes waters along the Argentinean shelf-break during austral spring and summer. A set of seven PATEX cruises has been conducted from 2004 to 2009 (total of 189 CTD stations) covering a broad region, in waters whose surface chlorophyll-a concentration (chla) varied from 0.10 to 22.30 mg m-3. This wide range of phytoplankton biomass reflected several stages of the phytoplankton blooms with relative higher chlorophyll associated to microplankton (picoplankton and/or nanoplankton) dominance during the spring (later summer) cruises in the shelf-break blooms. A special cruise (PATEX 5) was specially designed for sampling a coccolithophorid bloom in the Patagonia inner shelf (Garcia et al, 2011, JGR, 116, C03025). Overall, distinct efficiencies in absorption and scattering properties were observed due to differences in the algal cell size and pigment composition. Cluster analysis performed on both chla-specific absorption and scattering coefficients has shown the relative contributions by each of three cell-size classes. A hierarchical cluster analysis was also applied to "in situ" hyperspectral remote sensing reflectance spectra in order to classify the whole spectra set into coherent groups. Three spectrally distinct classes were well defined and they are significantly associated chla range. NASA OC4v6 chlorophyll algorithm has shown a relatively good performance when combining bio-optical data from all cruises (r2=0.78, slope of 0.86 and intercept of 0.03), with a positive bias (Mean Relative Percentage Difference, RPD=11.53%). The impact of chlorophyll-specific absorption and scattering coefficients on the performance of ocean empirical algorithms is also accessed.
Chen, Minhua; Silva, Jorge; Paisley, John; Wang, Chunping; Dunson, David; Carin, Lawrence
2013-01-01
Nonparametric Bayesian methods are employed to constitute a mixture of low-rank Gaussians, for data x ∈ ℝN that are of high dimension N but are constrained to reside in a low-dimensional subregion of ℝN. The number of mixture components and their rank are inferred automatically from the data. The resulting algorithm can be used for learning manifolds and for reconstructing signals from manifolds, based on compressive sensing (CS) projection measurements. The statistical CS inversion is performed analytically. We derive the required number of CS random measurements needed for successful reconstruction, based on easily-computed quantities, drawing on block-sparsity properties. The proposed methodology is validated on several synthetic and real datasets. PMID:23894225
Performance-Based Seismic Design of Steel Frames Utilizing Colliding Bodies Algorithm
Veladi, H.
2014-01-01
A pushover analysis method based on semirigid connection concept is developed and the colliding bodies optimization algorithm is employed to find optimum seismic design of frame structures. Two numerical examples from the literature are studied. The results of the new algorithm are compared to the conventional design methods to show the power or weakness of the algorithm. PMID:25202717
Suarez-Diez, Maria; Saccenti, Edoardo
2015-12-01
We investigated the effect of sample size and dimensionality on the performance of four algorithms (ARACNE, CLR, CORR, and PCLRC) when they are used for the inference of metabolite association networks. We report that as many as 100-400 samples may be necessary to obtain stable network estimations, depending on the algorithm and the number of measured metabolites. The CLR and PCLRC methods produce similar results, whereas network inference based on correlations provides sparse networks; we found ARACNE to be unsuitable for this application, being unable to recover the underlying metabolite association network. We recommend the PCLRC algorithm for the inference on metabolite association networks.
Student-Led Project Teams: Significance of Regulation Strategies in High- and Low-Performing Teams
ERIC Educational Resources Information Center
Ainsworth, Judith
2016-01-01
We studied group and individual co-regulatory and self-regulatory strategies of self-managed student project teams using data from intragroup peer evaluations and a postproject survey. We found that high team performers shared their research and knowledge with others, collaborated to advise and give constructive criticism, and demonstrated moral…
ERIC Educational Resources Information Center
Hilger, Allison I.; Zelaznik, Howard; Smith, Anne
2016-01-01
Purpose: Stuttering involves a breakdown in the speech motor system. We address whether stuttering in its early stage is specific to the speech motor system or whether its impact is observable across motor systems. Method: As an extension of Olander, Smith, and Zelaznik (2010), we measured bimanual motor timing performance in 115 children: 70…
Significant Returns in Engagement and Performance with a Free Teaching App
ERIC Educational Resources Information Center
Green, Alan
2016-01-01
Pedagogical research shows that teaching methods other than traditional lectures may result in better outcomes. However, lecture remains the dominant method in economics, likely due to high implementation costs of methods shown to be effective in the literature. In this article, the author shows significant benefits of using a teaching app for…
The cosmological and performative significance of a Thai cult of healing through meditation.
Tambiah, S J
1977-04-01
A cult of healing through meditation that was observed in Bangkok, Thailand in 1974 is described, and the cult is interpreted in terms of two axes, the cosmological and the performative, and the dialectical, reciprocal and complementary relations between them. The various ramifications of the cosmology are discussed--the categorization of the cosmos itself as a hierarchical scheme, the relations between man and non-human forms of existence, the ideas concerning power and its manner of acquisition and use, the relation between power and restraint, etc. The epistemological basis of the cult, which attempts cure through meditation, and the features of the ritual as they contribute to its performative efficacy are highlighted. The essay concludes by suggesting that there is a single scheme (episteme) underlying religious ideas and applications of knowledge such as meditation, medicine, alchemy, and astrology.
Performance analysis of hybrid algorithms for lossless compression of climate data
NASA Astrophysics Data System (ADS)
Mummadisetty, Bharath Chandra
Climate data is very important and at the same time, voluminous. Every minute a new entry is recorded for different climate parameters in climate databases around the world. Given the explosive growth of data that needs to be transmitted and stored, there is a necessity to focus on developing better transmission and storage technologies. Data compression is known to be a viable and effective solution to reduce bandwidth and storage requirements of bulk data. So, the goal is to develop the best compression methods for climate data. The methodology used is based on predictive analysis. The focus is to implement a hybrid algorithm which utilizes the functionality of Artificial Neural Networks (ANN) for prediction of climate data. ANN is a very efficient tool to generate models for predicting climate data with great accuracy. Two types of ANN's such as Multilayer Perceptron (MLP) and Cascade Feedforward Neural Network (CFNN) are used. It is beneficial to take advantage of ANN and combine its output with lossless compression algorithms such as differential encoding and Huffman coding to generate high compression ratios. The performance of the two techniques based on MLP and CFNN types are compared using metrics including compression ratio, Mean Square Error (MSE) and Root Mean Square Error (RMSE). The two methods are also compared with a conventional method of differential encoding followed by Huffman Coding. The results indicate that MLP outperforms CFNN. Also compression ratios of both the proposed methods are higher than those obtained by the standard method. Compression ratios as high as 10.3, 9.8, and 9.54 are obtained for precipitation, photosynthetically active radiation, and solar radiation datasets respectively.
Muller, Christophe; Marcou, Gilles; Horvath, Dragos; Aires-de-Sousa, João; Varnek, Alexandre
2012-12-21
Machine learning (SVM and JRip rule learner) methods have been used in conjunction with the Condensed Graph of Reaction (CGR) approach to identify errors in the atom-to-atom mapping of chemical reactions produced by an automated mapping tool by ChemAxon. The modeling has been performed on the three first enzymatic classes of metabolic reactions from the KEGG database. Each reaction has been converted into a CGR representing a pseudomolecule with conventional (single, double, aromatic, etc.) bonds and dynamic bonds characterizing chemical transformations. The ChemAxon tool was used to automatically detect the matching atom pairs in reagents and products. These automated mappings were analyzed by the human expert and classified as "correct" or "wrong". ISIDA fragment descriptors generated for CGRs for both correct and wrong mappings were used as attributes in machine learning. The learned models have been validated in n-fold cross-validation on the training set followed by a challenge to detect correct and wrong mappings within an external test set of reactions, never used for learning. Results show that both SVM and JRip models detect most of the wrongly mapped reactions. We believe that this approach could be used to identify erroneous atom-to-atom mapping performed by any automated algorithm.
Performance of rapid tests and algorithms for HIV screening in Abidjan, Ivory Coast.
Loukou, Y G; Cabran, M A; Yessé, Zinzendorf Nanga; Adouko, B M O; Lathro, S J; Agbessi-Kouassi, K B T
2014-01-01
Seven rapid diagnosis tests (RDTs) of HIV were evaluated by a panel group who collected serum samples from patients in Abidjan (HIV-1 = 203, HIV-2 = 25, HIV-dual = 25, HIV = 305). Kit performances were recorded after the reference techniques (enzyme-linked immunosorbent assay). The following RDTs showed a sensitivity of 100% and a specificity higher than 99%: Determine, Oraquick, SD Bioline, BCP, and Stat-Pak. These kits were used to establish infection screening strategies. The combination with 2 or 3 of these tests in series or parallel algorithms showed that series combinations with 2 tests (Oraquick and Bioline) and 3 tests (Determine, BCP, and Stat-Pak) gave the best performances (sensitivity, specificity, positive predictive value, and negative predictive value of 100%). However, the combination with 2 tests appeared to be more onerous than the combination with 3 tests. The combination with Determine, BCP, and Stat-Pak tests serving as a tiebreaker could be an alternative to the HIV/AIDS serological screening in Abidjan.
System Performance of an Integrated Airborne Spacing Algorithm with Ground Automation
NASA Technical Reports Server (NTRS)
Swieringa, Kurt A.; Wilson, Sara R.; Baxley, Brian T.
2016-01-01
The National Aeronautics and Space Administration's (NASA's) first Air Traffic Management (ATM) Technology Demonstration (ATD-1) was created to facilitate the transition of mature ATM technologies from the laboratory to operational use. The technologies selected for demonstration are the Traffic Management Advisor with Terminal Metering (TMA-TM), which provides precise time-based scheduling in the Terminal airspace; Controller Managed Spacing (CMS), which provides controllers with decision support tools to enable precise schedule conformance; and Interval Management (IM), which consists of flight deck automation that enables aircraft to achieve or maintain precise spacing behind another aircraft. Recent simulations and IM algorithm development at NASA have focused on trajectory-based IM operations where aircraft equipped with IM avionics are expected to achieve a spacing goal, assigned by air traffic controllers, at the final approach fix. The recently published IM Minimum Operational Performance Standards describe five types of IM operations. This paper discusses the results and conclusions of a human-in-the-loop simulation that investigated three of those IM operations. The results presented in this paper focus on system performance and integration metrics. Overall, the IM operations conducted in this simulation integrated well with ground-based decisions support tools and certain types of IM operational were able to provide improved spacing precision at the final approach fix; however, some issues were identified that should be addressed prior to implementing IM procedures into real-world operations.
FOCUSED R&D FOR ELECTROCHROMIC SMART WINDOWS: SIGNIFICANT PERFORMANCE AND YIELD ENHANCEMENTS
Marcus Milling
2004-09-23
Developments made under this program will play a key role in underpinning the technology for producing EC devices. It is anticipated that the work begun during this period will continue to improve materials properties, and drive yields up and costs down, increase durability and make manufacture simpler and more cost effective. It is hoped that this will contribute to a successful and profitable industry, which will help reduce energy consumption and improve comfort for building occupants worldwide. The first major task involved improvements to the materials used in the process. The improvements made as a result of the work done during this project have contributed to the enhanced performance, including dynamic range, uniformity and electrical characteristics. Another major objective of the project was to develop technology to improve yield, reduce cost, and facilitate manufacturing of EC products. Improvements directly attributable to the work carried out as part of this project and seen in the overall EC device performance, have been accompanied by an improvement in the repeatability and consistency of the production process. Innovative test facilities for characterizing devices in a timely and well-defined manner have been developed. The equipment has been designed in such a way as to make scaling-up to accommodate higher throughput necessary for manufacturing relatively straightforward. Finally, the third major goal was to assure the durability of the EC product, both by developments aimed at improving the product performance, as well as development of novel procedures to test the durability of this new product. Both aspects have been demonstrated, both by carrying out a number of different durability tests, both in-house and by independent third-party testers, and also developing several novel durability tests.
Asfour, Leila; Asfour, Victoria; McCormack, David; Attia, Rizwan
2014-09-01
A best evidence topic in cardiac surgery was written according to a structured protocol. The question addressed was: is there a difference in cardiothoracic surgery outcomes in terms of morbidity or mortality of patients operated on by a sleep-deprived surgeon compared with those operated by a non-sleep-deprived surgeon? Reported search criteria yielded 77 papers, of which 15 were deemed to represent the best evidence on the topic. Three studies directly related to cardiothoracic surgery and 12 studies related to non-cardiothoracic surgery. Recommendations are based on 18 121 cardiothoracic patients and 214 666 non-cardiothoracic surgical patients. Different definitions of sleep deprivation were used in the studies, either reviewing surgeon's sleeping hours or out-of-hours operating. Surgical outcomes reviewed included: mortality rate, neurological, renal, pulmonary, infectious complications, length of stay, length of intensive care stay, cardiopulmonary bypass times and aortic-cross-clamp times. There were no significant differences in mortality or intraoperative complications in the groups of patients operated on by sleep-deprived versus non-sleep-deprived surgeons in cardiothoracic studies. One study showed a significant increase in the rate of septicaemia in patients operated on by severely sleep-deprived surgeons (3.6%) compared with the moderately sleep-deprived (0.9%) and non-sleep-deprived groups (0.8%) (P = 0.03). In the non-cardiothoracic studies, 7 of the 12 studies demonstrated statistically significant higher reoperation rate in trauma cases (P <0.02) and kidney transplants (night = 16.8% vs day = 6.4%, P <0.01), as well as higher overall mortality (P = 0.028) and morbidity (P <0.0001). There is little direct evidence in the literature demonstrating the effect of sleep deprivation in cardiothoracic surgeons on morbidity or mortality. However, overall the non-cardiothoracic studies have demonstrated that operative time and sleep deprivation can have a
Liu, Jing; Cao, Hai-Ying; Wang, Xin-Ling; Xiao, Li-Jun
2016-12-01
Various lung diseases are the most common conditions and the leading cause of hospital admission and death in newborns. Historically, the diagnosis and differential diagnosis of lung diseases primarily relied on conventional chest X-ray and computed tomography (CT) scans, however, chest X-ray and CT scans suffer from obvious limitations, while lung ultrasound has many kinds of advantages for the diagnosis and differential diagnosis of lung diseases. The significance and the necessity of lung ultrasound in the diagnosis of neonatal lung diseases will be introduced in this paper.
Karafasoulis, K.; Zachariadou, K.; Seferlis, S.; Kaissas, I.; Potiriadis, C.; Lambropoulos, C.; Loukas, D.
2011-12-13
Simulation studies are presented regarding the performance of algorithms that localize point-like radioactive sources detected by a position sensitive portable radiation instrument (COCAE). The source direction is estimated by using the List Mode Maximum Likelihood Expectation Maximization (LM-ML-EM) imaging algorithm. Furthermore, the source-to-detector distance is evaluated by three different algorithms based on the photo-peak count information of each detecting layer, the quality of the reconstructed source image, and the triangulation method. These algorithms have been tested on a large number of simulated photons over a wide energy range (from 200 keV to 2 MeV) emitted by point-like radioactive sources located at different orientations and source-to-detector distances.
NASA Technical Reports Server (NTRS)
Yool, S. R.; Star, J. L.; Estes, J. E.; Botkin, D. B.; Eckhardt, D. W.
1986-01-01
The earth's forests fix carbon from the atmosphere during photosynthesis. Scientists are concerned that massive forest removals may promote an increase in atmospheric carbon dioxide, with possible global warming and related environmental effects. Space-based remote sensing may enable the production of accurate world forest maps needed to examine this concern objectively. To test the limits of remote sensing for large-area forest mapping, we use Landsat data acquired over a site in the forested mountains of southern California to examine the relative capacities of a variety of popular image processing algorithms to discriminate different forest types. Results indicate that certain algorithms are best suited to forest classification. Differences in performance between the algorithms tested appear related to variations in their sensitivities to spectral variations caused by background reflectance, differential illumination, and spatial pattern by species. Results emphasize the complexity between the land-cover regime, remotely sensed data and the algorithms used to process these data.
Enhanced Thermoelectric Performance of Nanostructured Bi2Te3 through Significant Phonon Scattering.
Yang, Lei; Chen, Zhi-Gang; Hong, Min; Han, Guang; Zou, Jin
2015-10-28
N-type Bi2Te3 nanostructures were synthesized using a solvothermal method and in turn sintered using sparking plasma sintering. The sintered n-type Bi2Te3 pellets reserved nanosized grains and showed an ultralow lattice thermal conductivity (∼0.2 W m(-1) K(-1)), which benefits from high-density small-angle grain boundaries accommodated by dislocations. Such a high phonon scattering leads an enhanced ZT of 0.88 at 400 K. This study provides an efficient method to enhance thermoelectric performance of thermoelectric nanomaterials through nanostructure engineering, making the as-prepared n-type nanostructured Bi2Te3 as a promising candidate for room-temperature thermoelectric power generation and Peltier cooling. PMID:26451626
Enhanced Thermoelectric Performance of Nanostructured Bi2Te3 through Significant Phonon Scattering.
Yang, Lei; Chen, Zhi-Gang; Hong, Min; Han, Guang; Zou, Jin
2015-10-28
N-type Bi2Te3 nanostructures were synthesized using a solvothermal method and in turn sintered using sparking plasma sintering. The sintered n-type Bi2Te3 pellets reserved nanosized grains and showed an ultralow lattice thermal conductivity (∼0.2 W m(-1) K(-1)), which benefits from high-density small-angle grain boundaries accommodated by dislocations. Such a high phonon scattering leads an enhanced ZT of 0.88 at 400 K. This study provides an efficient method to enhance thermoelectric performance of thermoelectric nanomaterials through nanostructure engineering, making the as-prepared n-type nanostructured Bi2Te3 as a promising candidate for room-temperature thermoelectric power generation and Peltier cooling.
Cramer, Michael J; Dumke, Charles L; Hailes, Walter S; Cuddy, John S; Ruby, Brent C
2015-10-01
A variety of dietary choices are marketed to enhance glycogen recovery after physical activity. Past research informs recommendations regarding the timing, dose, and nutrient compositions to facilitate glycogen recovery. This study examined the effects of isoenergetic sport supplements (SS) vs. fast food (FF) on glycogen recovery and exercise performance. Eleven males completed two experimental trials in a randomized, counterbalanced order. Each trial included a 90-min glycogen depletion ride followed by a 4-hr recovery period. Absolute amounts of macronutrients (1.54 ± 0.27 g·kg-1 carbohydrate, 0.24 ± 0.04 g·kg fat-1, and 0.18 ±0.03g·kg protein-1) as either SS or FF were provided at 0 and 2 hr. Muscle biopsies were collected from the vastus lateralis at 0 and 4 hr post exercise. Blood samples were analyzed at 0, 30, 60, 120, 150, 180, and 240 min post exercise for insulin and glucose, with blood lipids analyzed at 0 and 240 min. A 20k time-trial (TT) was completed following the final muscle biopsy. There were no differences in the blood glucose and insulin responses. Similarly, rates of glycogen recovery were not different across the diets (6.9 ± 1.7 and 7.9 ± 2.4 mmol·kg wet weight- 1·hr-1 for SS and FF, respectively). There was also no difference across the diets for TT performance (34.1 ± 1.8 and 34.3 ± 1.7 min for SS and FF, respectively. These data indicate that short-term food options to initiate glycogen resynthesis can include dietary options not typically marketed as sports nutrition products such as fast food menu items.
Tsiros, I X; Dimopoulos, I F
2007-04-01
Soil temperature simulation is an important component in environmental modeling since it is involved in several aspects of pollutant transport and fate. This paper deals with the performance of the soil temperature simulation algorithms of the well-known environmental model PRZM. Model results are compared and evaluated based on the basis of its ability to predict in situ measured soil temperature profiles in an experimental plot during a 3-year monitoring study. The evaluation of the performance is based on linear regression statistics and typical model statistical errors such as the root mean square error (RMSE) and the normalized objective function (NOF). Results show that the model required minimal calibration to match the observed response of the system. Values of the determination coefficient R(2) were found to be in all cases around the value of 0.98 indicating a very good agreement between measured and simulated data. Values of the RMSE were found to be in the range of 1.2 to 1.4 degrees C, 1.1 to 1.4 degrees C, 0.9 to 1.1 degrees C, and 0.8 to 1.1 degrees C, for the examined 2, 5, 10 and 20 cm soil depths, respectively. Sensitivity analyses were also performed to investigate the influence of various factors involved in the energy balance equation at the ground surface on the soil temperature profiles. The results showed that the model was able to represent important processes affecting the soil temperature regime such as the combined effect of the heat transfer by convection between the ground surface and the atmosphere and the latent heat flux due to soil water evaporation. PMID:17454373
Singh, Arvinder; Chandra, Amreesh
2015-01-01
Amongst the materials being investigated for supercapacitor electrodes, carbon based materials are most investigated. However, pure carbon materials suffer from inherent physical processes which limit the maximum specific energy and power that can be achieved in an energy storage device. Therefore, use of carbon-based composites with suitable nano-materials is attaining prominence. The synergistic effect between the pseudocapacitive nanomaterials (high specific energy) and carbon (high specific power) is expected to deliver the desired improvements. We report the fabrication of high capacitance asymmetric supercapacitor based on electrodes of composites of SnO2 and V2O5 with multiwall carbon nanotubes and neutral 0.5 M Li2SO4 aqueous electrolyte. The advantages of the fabricated asymmetric supercapacitors are compared with the results published in the literature. The widened operating voltage window is due to the higher over-potential of electrolyte decomposition and a large difference in the work functions of the used metal oxides. The charge balanced device returns the specific capacitance of ~198 F g−1 with corresponding specific energy of ~89 Wh kg−1 at 1 A g−1. The proposed composite systems have shown great potential in fabricating high performance supercapacitors. PMID:26494197
NASA Astrophysics Data System (ADS)
Singh, Arvinder; Chandra, Amreesh
2015-10-01
Amongst the materials being investigated for supercapacitor electrodes, carbon based materials are most investigated. However, pure carbon materials suffer from inherent physical processes which limit the maximum specific energy and power that can be achieved in an energy storage device. Therefore, use of carbon-based composites with suitable nano-materials is attaining prominence. The synergistic effect between the pseudocapacitive nanomaterials (high specific energy) and carbon (high specific power) is expected to deliver the desired improvements. We report the fabrication of high capacitance asymmetric supercapacitor based on electrodes of composites of SnO2 and V2O5 with multiwall carbon nanotubes and neutral 0.5 M Li2SO4 aqueous electrolyte. The advantages of the fabricated asymmetric supercapacitors are compared with the results published in the literature. The widened operating voltage window is due to the higher over-potential of electrolyte decomposition and a large difference in the work functions of the used metal oxides. The charge balanced device returns the specific capacitance of ~198 F g-1 with corresponding specific energy of ~89 Wh kg-1 at 1 A g-1. The proposed composite systems have shown great potential in fabricating high performance supercapacitors.
Yang, Jinhu; Li, Ying; Zu, Lianhai; Tong, Lianming; Liu, Guanglei; Qin, Yao; Shi, Donglu
2015-04-22
Noble metals are well-known for their surface plasmon resonance effect that enables strong light absorption typically in the visible regions for gold and silver. However, unlike semiconductors, noble metals are commonly considered incapable of catalyzing reactions via photogenerated electron-hole pairs due to their continuous energy band structures. So far, photonically activated catalytic system based on pure noble metal nanostructures has seldom been reported. Here, we report the development of three different novel plasmonic Au superstructures comprised of Au nanoparticles, multiple-twinned nanoparticles and nanoworms assembling on the surfaces of SiO2 nanospheres respectively via a well-designed synthetic strategy. It is found that these novel Au superstructures show enhanced broadband visible-light absorption due to the plasmon resonance coupling within the superstructures, and thus can effectively focus the energy of photon fluxes to generate much more excited hot electrons and holes for promoting catalytic reactions. Accordingly, these Au superstructures exhibit significantly visible-light-enhanced catalytic efficiency (up to ∼264% enhancement) for the commercial reaction of p-nitrophenol reduction. PMID:25840556
Liu, Hong; Wang, Jie; Xu, Xiangyang; Song, Enmin; Wang, Qian; Jin, Renchao; Hung, Chih-Cheng; Fei, Baowei
2014-11-01
A robust and accurate center-frequency (CF) estimation (RACE) algorithm for improving the performance of the local sine-wave modeling (SinMod) method, which is a good motion estimation method for tagged cardiac magnetic resonance (MR) images, is proposed in this study. The RACE algorithm can automatically, effectively and efficiently produce a very appropriate CF estimate for the SinMod method, under the circumstance that the specified tagging parameters are unknown, on account of the following two key techniques: (1) the well-known mean-shift algorithm, which can provide accurate and rapid CF estimation; and (2) an original two-direction-combination strategy, which can further enhance the accuracy and robustness of CF estimation. Some other available CF estimation algorithms are brought out for comparison. Several validation approaches that can work on the real data without ground truths are specially designed. Experimental results on human body in vivo cardiac data demonstrate the significance of accurate CF estimation for SinMod, and validate the effectiveness of RACE in facilitating the motion estimation performance of SinMod.
SU-E-T-605: Performance Evaluation of MLC Leaf-Sequencing Algorithms in Head-And-Neck IMRT
Jing, J; Lin, H; Chow, J
2015-06-15
Purpose: To investigate the efficiency of three multileaf collimator (MLC) leaf-sequencing algorithms proposed by Galvin et al, Chen et al and Siochi et al using external beam treatment plans for head-and-neck intensity modulated radiation therapy (IMRT). Methods: IMRT plans for head-and-neck were created using the CORVUS treatment planning system. The plans were optimized and the fluence maps for all photon beams determined. Three different MLC leaf-sequencing algorithms based on Galvin et al, Chen et al and Siochi et al were used to calculate the final photon segmental fields and their monitor units in delivery. For comparison purpose, the maximum intensity of fluence map was kept constant in different plans. The number of beam segments and total number of monitor units were calculated for the three algorithms. Results: From results of number of beam segments and total number of monitor units, we found that algorithm of Galvin et al had the largest number of monitor unit which was about 70% larger than the other two algorithms. Moreover, both algorithms of Galvin et al and Siochi et al have relatively lower number of beam segment compared to Chen et al. Although values of number of beam segment and total number of monitor unit calculated by different algorithms varied with the head-and-neck plans, it can be seen that algorithms of Galvin et al and Siochi et al performed well with a lower number of beam segment, though algorithm of Galvin et al had a larger total number of monitor units than Siochi et al. Conclusion: Although performance of the leaf-sequencing algorithm varied with different IMRT plans having different fluence maps, an evaluation is possible based on the calculated number of beam segment and monitor unit. In this study, algorithm by Siochi et al was found to be more efficient in the head-and-neck IMRT. The Project Sponsored by the Fundamental Research Funds for the Central Universities (J2014HGXJ0094) and the Scientific Research Foundation for the
NASA Astrophysics Data System (ADS)
Khodja, Mohamed; Belouchrani, Adel; Abed-Meraim, Karim
2012-12-01
This article deals with the application of Spatial Time-Frequency Distribution (STFD) to the direction finding problem using the Multiple Signal Classification (MUSIC)algorithm. A comparative performance analysis is performed for the method under consideration with respect to that using data covariance matrix when the received array signals are subject to calibration errors in a non-stationary environment. An unified analytical expression of the Direction Of Arrival (DOA) error estimation is derived for both methods. Numerical results show the effect of the parameters intervening in the derived expression on the algorithm performance. It is particularly observed that for low Signal to Noise Ratio (SNR) and high Signal to sensor Perturbation Ratio (SPR) the STFD method gives better performance, while for high SNR and for the same SPR both methods give similar performance.
Guelpa, Valérian; Laurent, Guillaume J; Sandoz, Patrick; Zea, July Galeano; Clévy, Cédric
2014-01-01
This paper presents a visual measurement method able to sense 1D rigid body displacements with very high resolutions, large ranges and high processing rates. Sub-pixelic resolution is obtained thanks to a structured pattern placed on the target. The pattern is made of twin periodic grids with slightly different periods. The periodic frames are suited for Fourier-like phase calculations-leading to high resolution-while the period difference allows the removal of phase ambiguity and thus a high range-to-resolution ratio. The paper presents the measurement principle as well as the processing algorithms (source files are provided as supplementary materials). The theoretical and experimental performances are also discussed. The processing time is around 3 µs for a line of 780 pixels, which means that the measurement rate is mostly limited by the image acquisition frame rate. A 3-σ repeatability of 5 nm is experimentally demonstrated which has to be compared with the 168 µm measurement range. PMID:24625736
A two-hydrophone range and bearing localization algorithm with performance analysis.
Gebbie, John; Siderius, Martin; Allen, John S
2015-03-01
An automated, passive algorithm for detecting and localizing small boats using two hydrophones mounted on the seabed is outlined. This extends previous work by Gebbie et al. [(2013). J. Acoust. Soc. Am. 134, EL77 - EL83] in which a similar two-hydrophone approach is used to produce an ambiguity surface of likely target locations leveraging multipath analysis and knowledge of the local bathymetry. The work presented here improves upon the prior approach using particle filtering to automate detection and localization processing. A detailed analysis has also been conducted to determine the conditions and limits under which the improved approach can be expected to yield accurate range and unambiguous bearing information. Experimental results in 12 m of water allow for a comparison of different separation distances between hydrophones, and the Bayesian Cramér-Rao lower bound is used to extrapolate the performance expected in 120 m water. This work demonstrates the conditions under which a low cost, passive, sparse array of hydrophones can provide a meaningful small boat detection and localization capability.
NASA Astrophysics Data System (ADS)
Erlingis, J. M.; Gourley, J. J.; Kirstetter, P.; Anagnostou, E. N.; Kalogiros, J. A.; Anagnostou, M.
2015-12-01
An Intensive Observation Period (IOP) for the Integrated Precipitation and Hydrology Experiment (IPHEx), part of NASA's Ground Validation campaign for the Global Precipitation Measurement Mission satellite took place from May-June 2014 in the Smoky Mountains of western North Carolina. The National Severe Storms Laboratory's mobile dual-pol X-band radar, NOXP, was deployed in the Pigeon River Basin during this time and employed various scanning strategies, including more than 1000 Range Height Indicator (RHI) scans in coordination with another radar and research aircraft. Rain gauges and disdrometers were also positioned within the basin to verify precipitation estimates and estimation of microphysical parameters. The performance of the SCOP-ME post-processing algorithm on NOXP data is compared with real-time and near real-time precipitation estimates with varying spatial resolutions and quality control measures (Stage IV gauge-corrected radar estimates, Multi-Radar/Multi-Sensor System Quantitative Precipitation Estimates, and CMORPH satellite estimates) to assess the utility of a gap-filling radar in complex terrain. Additionally, the RHI scans collected in this IOP provide a valuable opportunity to examine the evolution of microphysical characteristics of convective and stratiform precipitation as they impinge on terrain. To further the understanding of orographically enhanced precipitation, multiple storms for which RHI data are available are considered.
NASA Technical Reports Server (NTRS)
Adelman, H. M.; Haftka, R. T.; Robinson, J. C.
1982-01-01
The status of an effort to increase the efficiency of calculating transient temperature fields in complex aerospace vehicle structures is described. The advantages and disadvantages of explicit and implicit algorithms are discussed. A promising set of implicit algorithms with variable time steps, known as the GEAR package is described. Four test problems, used for evaluating and comparing various algorithms, were selected and finite element models of the configurations are described. These problems include a space shuttle frame component, an insulated cylinder, a metallic panel for a thermal protection system, and a model of the space shuttle orbiter wing. Results generally indicate a preference for implicit oer explicit algorithms for solution of transient structural heat transfer problems when the governing equations are stiff.
Some aspects of algorithm performance and modeling in transient thermal analysis of structures
NASA Technical Reports Server (NTRS)
Adelman, H. M.; Robinson, J. C.; Haftka, R. T.
1981-01-01
The status of an effort to increase the efficiency of calculating transient temperature fields in complex aerospace vehicle structures is described. The advantages and disadvantages of explicit and implicit algorithms are discussed. A promising set of implicit algorithms with variable time steps, known as the GEAR package is described. Four test problems, used for evaluating and comparing various algorithms, have been selected and finite-element models of the configurations are described. These problems include a Space Shuttle frame component, an insulated cylinder, a metallic panel for a thermal protection system, and a model of the Space Shuttle Orbiter wing. Results generally indicate a preference for implicit over explicit algorithms for solution of transient structural heat transfer problems when the governing equations are 'stiff' (typical of many practical problems such as insulated metal structures).
Performance of decoder-based algorithms for signal synchronization for DSSS waveforms
NASA Astrophysics Data System (ADS)
Matache, A.; Valles, E. L.
This paper presents results on the implementation of pilotless carrier synchronization algorithms at low SNRs using joint decoding and decision-directed tracking. A software test bed was designed to simulate the effects of decision-directed carrier synchronization (DDCS) techniques. These techniques are compared to non-decision directed algorithms used in phase-locked loops (PLLs) or Costas loops. In previous work by the authors, results for direct M-ARY modulation constellations, with no code spreading were introduced. This paper focuses on the application of the proposed family of decision directed algorithms to direct sequence spread spectrum (DSSS) waveforms, typical of GPS signals. The current algorithm can utilize feedback from turbo codes in addition to the prior support of LDPC codes.
Clustering performance comparison using K-means and expectation maximization algorithms
Jung, Yong Gyu; Kang, Min Soo; Heo, Jun
2014-01-01
Clustering is an important means of data mining based on separating data categories by similar features. Unlike the classification algorithm, clustering belongs to the unsupervised type of algorithms. Two representatives of the clustering algorithms are the K-means and the expectation maximization (EM) algorithm. Linear regression analysis was extended to the category-type dependent variable, while logistic regression was achieved using a linear combination of independent variables. To predict the possibility of occurrence of an event, a statistical approach is used. However, the classification of all data by means of logistic regression analysis cannot guarantee the accuracy of the results. In this paper, the logistic regression analysis is applied to EM clusters and the K-means clustering method for quality assessment of red wine, and a method is proposed for ensuring the accuracy of the classification results. PMID:26019610
NASA Astrophysics Data System (ADS)
Yoon, Jin-Seon; Kim, Nam; Suh, HoHyung; Jeon, Seok Hee
2000-03-01
In this paper, gratings to apply for the optical interconnection are designed using a genetic algorithm (GA) for a robust and efficient schema. The real-time optical interconnection system architecture is composed with LC-SLM, CCD array detector, IBM-PC, He-Ne laser, and Fourier transform lens. A pixelated binary phase grating is displayed on LC-SLM and could interconnect incoming beams to desired output spots freely by real-time. So as to adapt a GA for finding near globally-cost solutions, a chromosome is coded as a binary integer of length 32 X 32, the stochastic tournament method for decreasing the stochastic sampling error is performed, and a single-point crossover having 16 X 16 block size is used. The characteristics on the several parameters are analyzed in the desired grating design. Firstly, as the analysis of the effect on the probability of crossover, a designed grating when the probability of crossover is 0.75 has a 74.7[%] high diffraction efficiency and a 1.73 X 10-1 uniformity quantitatively, where the probability of mutation is 0.001 and the population size is 300. Secondly, on the probability of mutation, a designed grating when the probability of mutation is 0.001 has a 74.4[%] high efficiency and a 1.61 X 10-1 uniformity quantitatively, where the probability of crossover is 1.0 and the population size is 300. Thirdly, on the population size, a designed grating when the population size is 300 and the generation is 400 has above 74[%] diffraction efficiency, where the probability of mutation is 0.001 and the probability of crossover is 1.0.
Maier, Joscha; Sawall, Stefan; Kachelrieß, Marc
2014-05-15
Purpose: Phase-correlated microcomputed tomography (micro-CT) imaging plays an important role in the assessment of mouse models of cardiovascular diseases and the determination of functional parameters as the left ventricular volume. As the current gold standard, the phase-correlated Feldkamp reconstruction (PCF), shows poor performance in case of low dose scans, more sophisticated reconstruction algorithms have been proposed to enable low-dose imaging. In this study, the authors focus on the McKinnon-Bates (MKB) algorithm, the low dose phase-correlated (LDPC) reconstruction, and the high-dimensional total variation minimization reconstruction (HDTV) and investigate their potential to accurately determine the left ventricular volume at different dose levels from 50 to 500 mGy. The results were verified in phantom studies of a five-dimensional (5D) mathematical mouse phantom. Methods: Micro-CT data of eight mice, each administered with an x-ray dose of 500 mGy, were acquired, retrospectively gated for cardiac and respiratory motion and reconstructed using PCF, MKB, LDPC, and HDTV. Dose levels down to 50 mGy were simulated by using only a fraction of the projections. Contrast-to-noise ratio (CNR) was evaluated as a measure of image quality. Left ventricular volume was determined using different segmentation algorithms (Otsu, level sets, region growing). Forward projections of the 5D mouse phantom were performed to simulate a micro-CT scan. The simulated data were processed the same way as the real mouse data sets. Results: Compared to the conventional PCF reconstruction, the MKB, LDPC, and HDTV algorithm yield images of increased quality in terms of CNR. While the MKB reconstruction only provides small improvements, a significant increase of the CNR is observed in LDPC and HDTV reconstructions. The phantom studies demonstrate that left ventricular volumes can be determined accurately at 500 mGy. For lower dose levels which were simulated for real mouse data sets, the
NASA Astrophysics Data System (ADS)
Skofronick Jackson, G.; Munchak, S. J.; Johnson, B. T.
2013-12-01
Retrievals of falling snow from space represent an important data set for understanding the Earth's atmospheric, hydrological, and energy cycles. Estimates of falling snow must be captured to obtain the true global precipitation water cycle, snowfall accumulations are required for hydrological studies, and without knowledge of the frozen particles in clouds one cannot adequately understand the energy and radiation budgets. This work reports on the development and pre-launch testing of retrieval algorithms for the Global Precipitation Measurement (GPM) mission Core Observatory satellite, to be launched in early 2014. In particular, we will report on GPM Microwave Imager (GMI) radiometer instrument algorithm performance with respect to falling snow detection and estimation. While satellite-based remote sensing can provide global coverage of falling snow events, the science is relatively new and retrievals are still undergoing development with challenges remaining. Estimates of falling snow from ground and space based sensors have been difficult due to the physical characteristics of snowflakes including their complex shapes, sizes, fall patterns, melting fractions, and densities; and their remotely sensed radiative characteristics. While these challenges remain, knowledge of their impact on expected retrieval results is an important key for understanding falling snow retrieval estimations. Our earlier work in this field has shown, through both theoretical and observational studies, that falling snow rates of approximately 0.5 mm/hr (melted) can be detected from GMI (Skofronick-Jackson, et al., IEEE Trans. Geoscience and Remote Sensing, 2013, Munchak and Skofronick-Jackson, Atmospheric Research, 2013). Throughout 2013, the at-launch GMI precipitation algorithms (called GPROF2014), based on a Bayesian framework, have been revised and delivered to the GPM data processing center with the final algorithm to be delivered in September 2013. The Bayesian framework for GMI
Semioptimal practicable algorithmic cooling
NASA Astrophysics Data System (ADS)
Elias, Yuval; Mor, Tal; Weinstein, Yossi
2011-04-01
Algorithmic cooling (AC) of spins applies entropy manipulation algorithms in open spin systems in order to cool spins far beyond Shannon’s entropy bound. Algorithmic cooling of nuclear spins was demonstrated experimentally and may contribute to nuclear magnetic resonance spectroscopy. Several cooling algorithms were suggested in recent years, including practicable algorithmic cooling (PAC) and exhaustive AC. Practicable algorithms have simple implementations, yet their level of cooling is far from optimal; exhaustive algorithms, on the other hand, cool much better, and some even reach (asymptotically) an optimal level of cooling, but they are not practicable. We introduce here semioptimal practicable AC (SOPAC), wherein a few cycles (typically two to six) are performed at each recursive level. Two classes of SOPAC algorithms are proposed and analyzed. Both attain cooling levels significantly better than PAC and are much more efficient than the exhaustive algorithms. These algorithms are shown to bridge the gap between PAC and exhaustive AC. In addition, we calculated the number of spins required by SOPAC in order to purify qubits for quantum computation. As few as 12 and 7 spins are required (in an ideal scenario) to yield a mildly pure spin (60% polarized) from initial polarizations of 1% and 10%, respectively. In the latter case, about five more spins are sufficient to produce a highly pure spin (99.99% polarized), which could be relevant for fault-tolerant quantum computing.
NASA Technical Reports Server (NTRS)
Matic, Roy M.; Mosley, Judith I.
1994-01-01
Future space-based, remote sensing systems will have data transmission requirements that exceed available downlinks necessitating the use of lossy compression techniques for multispectral data. In this paper, we describe several algorithms for lossy compression of multispectral data which combine spectral decorrelation techniques with an adaptive, wavelet-based, image compression algorithm to exploit both spectral and spatial correlation. We compare the performance of several different spectral decorrelation techniques including wavelet transformation in the spectral dimension. The performance of each technique is evaluated at compression ratios ranging from 4:1 to 16:1. Performance measures used are visual examination, conventional distortion measures, and multispectral classification results. We also introduce a family of distortion metrics that are designed to quantify and predict the effect of compression artifacts on multi spectral classification of the reconstructed data.
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.
Performance analysis of a dual-tree algorithm for computing spatial distance histograms
Chen, Shaoping; Tu, Yi-Cheng; Xia, Yuni
2011-01-01
Many scientific and engineering fields produce large volume of spatiotemporal data. The storage, retrieval, and analysis of such data impose great challenges to database systems design. Analysis of scientific spatiotemporal data often involves computing functions of all point-to-point interactions. One such analytics, the Spatial Distance Histogram (SDH), is of vital importance to scientific discovery. Recently, algorithms for efficient SDH processing in large-scale scientific databases have been proposed. These algorithms adopt a recursive tree-traversing strategy to process point-to-point distances in the visited tree nodes in batches, thus require less time when compared to the brute-force approach where all pairwise distances have to be computed. Despite the promising experimental results, the complexity of such algorithms has not been thoroughly studied. In this paper, we present an analysis of such algorithms based on a geometric modeling approach. The main technique is to transform the analysis of point counts into a problem of quantifying the area of regions where pairwise distances can be processed in batches by the algorithm. From the analysis, we conclude that the number of pairwise distances that are left to be processed decreases exponentially with more levels of the tree visited. This leads to the proof of a time complexity lower than the quadratic time needed for a brute-force algorithm and builds the foundation for a constant-time approximate algorithm. Our model is also general in that it works for a wide range of point spatial distributions, histogram types, and space-partitioning options in building the tree. PMID:21804753
Performance analysis of a dual-tree algorithm for computing spatial distance histograms.
Chen, Shaoping; Tu, Yi-Cheng; Xia, Yuni
2011-08-01
Many scientific and engineering fields produce large volume of spatiotemporal data. The storage, retrieval, and analysis of such data impose great challenges to database systems design. Analysis of scientific spatiotemporal data often involves computing functions of all point-to-point interactions. One such analytics, the Spatial Distance Histogram (SDH), is of vital importance to scientific discovery. Recently, algorithms for efficient SDH processing in large-scale scientific databases have been proposed. These algorithms adopt a recursive tree-traversing strategy to process point-to-point distances in the visited tree nodes in batches, thus require less time when compared to the brute-force approach where all pairwise distances have to be computed. Despite the promising experimental results, the complexity of such algorithms has not been thoroughly studied. In this paper, we present an analysis of such algorithms based on a geometric modeling approach. The main technique is to transform the analysis of point counts into a problem of quantifying the area of regions where pairwise distances can be processed in batches by the algorithm. From the analysis, we conclude that the number of pairwise distances that are left to be processed decreases exponentially with more levels of the tree visited. This leads to the proof of a time complexity lower than the quadratic time needed for a brute-force algorithm and builds the foundation for a constant-time approximate algorithm. Our model is also general in that it works for a wide range of point spatial distributions, histogram types, and space-partitioning options in building the tree.
On the performance of explicit and implicit algorithms for transient thermal analysis
NASA Technical Reports Server (NTRS)
Adelman, H. M.; Haftka, R. T.
1980-01-01
The status of an effort to increase the efficiency of calculating transient temperature fields in complex aerospace vehicle structures is described. The advantages and disadvantages of explicit and implicit algorithms are discussed. A promising set of implicit algorithms, known as the GEAR package is described. Four test problems, used for evaluating and comparing various algorithms, have been selected and finite element models of the configurations are discribed. These problems include a space shuttle frame component, an insulated cylinder, a metallic panel for a thermal protection system and a model of the space shuttle orbiter wing. Calculations were carried out using the SPAR finite element program, the MITAS lumped parameter program and a special purpose finite element program incorporating the GEAR algorithms. Results generally indicate a preference for implicit over explicit algorithms for solution of transient structural heat transfer problems when the governing equations are stiff. Careful attention to modeling detail such as avoiding thin or short high-conducting elements can sometimes reduce the stiffness to the extent that explicit methods become advantageous.
NASA Astrophysics Data System (ADS)
Ciany, Charles M.; Zurawski, William; Kerfoot, Ian
2001-10-01
The performance of Computer Aided Detection/Computer Aided Classification (CAD/CAC) Fusion algorithms on side-scan sonar images was evaluated using data taken at the Navy's's Fleet Battle Exercise-Hotel held in Panama City, Florida, in August 2000. A 2-of-3 binary fusion algorithm is shown to provide robust performance. The algorithm accepts the classification decisions and associated contact locations form three different CAD/CAC algorithms, clusters the contacts based on Euclidian distance, and then declares a valid target when a clustered contact is declared by at least 2 of the 3 individual algorithms. This simple binary fusion provided a 96 percent probability of correct classification at a false alarm rate of 0.14 false alarms per image per side. The performance represented a 3.8:1 reduction in false alarms over the best performing single CAD/CAC algorithm, with no loss in probability of correct classification.
NASA Astrophysics Data System (ADS)
Chakraborty, Tamal; Saha Misra, Iti
2016-03-01
Secondary Users (SUs) in a Cognitive Radio Network (CRN) face unpredictable interruptions in transmission due to the random arrival of Primary Users (PUs), leading to spectrum handoff or dropping instances. An efficient spectrum handoff algorithm, thus, becomes one of the indispensable components in CRN, especially for real-time communication like Voice over IP (VoIP). In this regard, this paper investigates the effects of spectrum handoff on the Quality of Service (QoS) for VoIP traffic in CRN, and proposes a real-time spectrum handoff algorithm in two phases. The first phase (VAST-VoIP based Adaptive Sensing and Transmission) adaptively varies the channel sensing and transmission durations to perform intelligent dropping decisions. The second phase (ProReact-Proactive and Reactive Handoff) deploys efficient channel selection mechanisms during spectrum handoff for resuming communication. Extensive performance analysis in analytical and simulation models confirms a decrease in spectrum handoff delay for VoIP SUs by more than 40% and 60%, compared to existing proactive and reactive algorithms, respectively and ensures a minimum 10% reduction in call-dropping probability with respect to the previous works in this domain. The effective SU transmission duration is also maximized under the proposed algorithm, thereby making it suitable for successful VoIP communication.
Liu, Chun; Kroll, Andreas
2016-01-01
Multi-robot task allocation determines the task sequence and distribution for a group of robots in multi-robot systems, which is one of constrained combinatorial optimization problems and more complex in case of cooperative tasks because they introduce additional spatial and temporal constraints. To solve multi-robot task allocation problems with cooperative tasks efficiently, a subpopulation-based genetic algorithm, a crossover-free genetic algorithm employing mutation operators and elitism selection in each subpopulation, is developed in this paper. Moreover, the impact of mutation operators (swap, insertion, inversion, displacement, and their various combinations) is analyzed when solving several industrial plant inspection problems. The experimental results show that: (1) the proposed genetic algorithm can obtain better solutions than the tested binary tournament genetic algorithm with partially mapped crossover; (2) inversion mutation performs better than other tested mutation operators when solving problems without cooperative tasks, and the swap-inversion combination performs better than other tested mutation operators/combinations when solving problems with cooperative tasks. As it is difficult to produce all desired effects with a single mutation operator, using multiple mutation operators (including both inversion and swap) is suggested when solving similar combinatorial optimization problems.
Liu, Chun; Kroll, Andreas
2016-01-01
Multi-robot task allocation determines the task sequence and distribution for a group of robots in multi-robot systems, which is one of constrained combinatorial optimization problems and more complex in case of cooperative tasks because they introduce additional spatial and temporal constraints. To solve multi-robot task allocation problems with cooperative tasks efficiently, a subpopulation-based genetic algorithm, a crossover-free genetic algorithm employing mutation operators and elitism selection in each subpopulation, is developed in this paper. Moreover, the impact of mutation operators (swap, insertion, inversion, displacement, and their various combinations) is analyzed when solving several industrial plant inspection problems. The experimental results show that: (1) the proposed genetic algorithm can obtain better solutions than the tested binary tournament genetic algorithm with partially mapped crossover; (2) inversion mutation performs better than other tested mutation operators when solving problems without cooperative tasks, and the swap-inversion combination performs better than other tested mutation operators/combinations when solving problems with cooperative tasks. As it is difficult to produce all desired effects with a single mutation operator, using multiple mutation operators (including both inversion and swap) is suggested when solving similar combinatorial optimization problems. PMID:27588254
NASA Astrophysics Data System (ADS)
Yadav, Deepti; Arora, M. K.; Tiwari, K. C.; Ghosh, J. K.
2016-04-01
Hyperspectral imaging is a powerful tool in the field of remote sensing and has been used for many applications like mineral detection, detection of landmines, target detection etc. Major issues in target detection using HSI are spectral variability, noise, small size of the target, huge data dimensions, high computation cost, complex backgrounds etc. Many of the popular detection algorithms do not work for difficult targets like small, camouflaged etc. and may result in high false alarms. Thus, target/background discrimination is a key issue and therefore analyzing target's behaviour in realistic environments is crucial for the accurate interpretation of hyperspectral imagery. Use of standard libraries for studying target's spectral behaviour has limitation that targets are measured in different environmental conditions than application. This study uses the spectral data of the same target which is used during collection of the HSI image. This paper analyze spectrums of targets in a way that each target can be spectrally distinguished from a mixture of spectral data. Artificial neural network (ANN) has been used to identify the spectral range for reducing data and further its efficacy for improving target detection is verified. The results of ANN proposes discriminating band range for targets; these ranges were further used to perform target detection using four popular spectral matching target detection algorithm. Further, the results of algorithms were analyzed using ROC curves to evaluate the effectiveness of the ranges suggested by ANN over full spectrum for detection of desired targets. In addition, comparative assessment of algorithms is also performed using ROC.
The use of algorithmic behavioural transfer functions in parametric EO system performance models
NASA Astrophysics Data System (ADS)
Hickman, Duncan L.; Smith, Moira I.
2015-10-01
The use of mathematical models to predict the overall performance of an electro-optic (EO) system is well-established as a methodology and is used widely to support requirements definition, system design, and produce performance predictions. Traditionally these models have been based upon cascades of transfer functions based on established physical theory, such as the calculation of signal levels from radiometry equations, as well as the use of statistical models. However, the performance of an EO system is increasing being dominated by the on-board processing of the image data and this automated interpretation of image content is complex in nature and presents significant modelling challenges. Models and simulations of EO systems tend to either involve processing of image data as part of a performance simulation (image-flow) or else a series of mathematical functions that attempt to define the overall system characteristics (parametric). The former approach is generally more accurate but statistically and theoretically weak in terms of specific operational scenarios, and is also time consuming. The latter approach is generally faster but is unable to provide accurate predictions of a system's performance under operational conditions. An alternative and novel architecture is presented in this paper which combines the processing speed attributes of parametric models with the accuracy of image-flow representations in a statistically valid framework. An additional dimension needed to create an effective simulation is a robust software design whose architecture reflects the structure of the EO System and its interfaces. As such, the design of the simulator can be viewed as a software prototype of a new EO System or an abstraction of an existing design. This new approach has been used successfully to model a number of complex military systems and has been shown to combine improved performance estimation with speed of computation. Within the paper details of the approach
Some aspects of algorithm performance and modeling in transient analysis of structures
NASA Technical Reports Server (NTRS)
Adelman, H. M.; Haftka, R. T.; Robinson, J. C.
1981-01-01
The status of an effort to increase the efficiency of calculating transient temperature fields in complex aerospace vehicle structures is described. The advantages and disadvantages of explicit algorithms with variable time steps, known as the GEAR package, is described. Four test problems, used for evaluating and comparing various algorithms, were selected and finite-element models of the configurations are described. These problems include a space shuttle frame component, an insulated cylinder, a metallic panel for a thermal protection system, and a model of the wing of the space shuttle orbiter. Results generally indicate a preference for implicit over explicit algorithms for solution of transient structural heat transfer problems when the governing equations are stiff (typical of many practical problems such as insulated metal structures).
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
NASA Technical Reports Server (NTRS)
Braun, W. R.
1982-01-01
An approach is described for approximating the cumulative probability distribution of the acquisition time of the serial pseudonoise (PN) search algorithm. The results are applicable to both variable and fixed dwell time systems. The theory is developed for the case where some a priori information is available on the PN code epoch (reacquisition problem or acquisition of very long codes). Also considered is the special case of a search over the whole code. The accuracy of the approximation is demonstrated by comparisons with published exact results for the fixed dwell time algorithm.
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
CHEOPS Performance for Exomoons: The Detectability of Exomoons by Using Optimal Decision Algorithm
NASA Astrophysics Data System (ADS)
Simon, A. E.; Szabó, Gy. M.; Kiss, L. L.; Fortier, A.; Benz, W.
2015-10-01
Many attempts have already been made to detect exomoons around transiting exoplanets, but the first confirmed discovery is still pending. The experiences that have been gathered so far allow us to better optimize future space telescopes for this challenge already during the development phase. In this paper we focus on the forthcoming CHaraterising ExOPlanet Satellite (CHEOPS), describing an optimized decision algorithm with step-by-step evaluation, and calculating the number of required transits for an exomoon detection for various planet-moon configurations that can be observable by CHEOPS. We explore the most efficient way for such an observation to minimize the cost in observing time. Our study is based on PTV observations (photocentric transit timing variation) in simulated CHEOPS data, but the recipe does not depend on the actual detection method, and it can be substituted with, e.g., the photodynamical method for later applications. Using the current state-of-the-art level simulation of CHEOPS data we analyzed transit observation sets for different star-planet-moon configurations and performed a bootstrap analysis to determine their detection statistics. We have found that the detection limit is around an Earth-sized moon. In the case of favorable spatial configurations, systems with at least a large moon and a Neptune-sized planet, an 80% detection chance requires at least 5-6 transit observations on average. There is also a nonzero chance in the case of smaller moons, but the detection statistics deteriorate rapidly, while the necessary transit measurements increase quickly. After the CoRoT and Kepler spacecrafts, CHEOPS will be the next dedicated space telescope that will observe exoplanetary transits and characterize systems with known Doppler-planets. Although it has a smaller aperture than Kepler (the ratio of the mirror diameters is about 1/3) and is mounted with a CCD that is similar to Kepler's, it will observe brighter stars and operate with larger
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.
Performance Evaluation of Various STL File Mesh Refining Algorithms Applied for FDM-RP Process
NASA Astrophysics Data System (ADS)
Ledalla, Siva Rama Krishna; Tirupathi, Balaji; Sriram, Venkatesh
2016-06-01
Layered manufacturing machines use the stereolithography (STL) file to build parts. When a curved surface is converted from a computer aided design (CAD) file to STL, it results in a geometrical distortion and chordal error. Parts manufactured with this file, might not satisfy geometric dimensioning and tolerance requirements due to approximated geometry. Current algorithms built in CAD packages have export options to globally reduce this distortion, which leads to an increase in the file size and pre-processing time. In this work, different mesh subdivision algorithms are applied on STL file of a complex geometric features using MeshLab software. The mesh subdivision algorithms considered in this work are modified butterfly subdivision technique, loops sub division technique and general triangular midpoint sub division technique. A comparative study is made with respect to volume and the build time using the above techniques. It is found that triangular midpoint sub division algorithm is more suitable for the geometry under consideration. Only the wheel cap part is then manufactured on Stratasys MOJO FDM machine. The surface roughness of the part is measured on Talysurf surface roughness tester.
Cognitive Correlates of Performance in Algorithms in a Computer Science Course for High School
ERIC Educational Resources Information Center
Avancena, Aimee Theresa; Nishihara, Akinori
2014-01-01
Computer science for high school faces many challenging issues. One of these is whether the students possess the appropriate cognitive ability for learning the fundamentals of computer science. Online tests were created based on known cognitive factors and fundamental algorithms and were implemented among the second grade students in the…
NASA Technical Reports Server (NTRS)
Mach, Douglas M.; Christian, Hugh J.; Blakeslee, Richard; Boccippio, Dennis J.; Goodman, Steve J.; Boeck, William
2006-01-01
We describe the clustering algorithm used by the Lightning Imaging Sensor (LIS) and the Optical Transient Detector (OTD) for combining the lightning pulse data into events, groups, flashes, and areas. Events are single pixels that exceed the LIS/OTD background level during a single frame (2 ms). Groups are clusters of events that occur within the same frame and in adjacent pixels. Flashes are clusters of groups that occur within 330 ms and either 5.5 km (for LIS) or 16.5 km (for OTD) of each other. Areas are clusters of flashes that occur within 16.5 km of each other. Many investigators are utilizing the LIS/OTD flash data; therefore, we test how variations in the algorithms for the event group and group-flash clustering affect the flash count for a subset of the LIS data. We divided the subset into areas with low (1-3), medium (4-15), high (16-63), and very high (64+) flashes to see how changes in the clustering parameters affect the flash rates in these different sizes of areas. We found that as long as the cluster parameters are within about a factor of two of the current values, the flash counts do not change by more than about 20%. Therefore, the flash clustering algorithm used by the LIS and OTD sensors create flash rates that are relatively insensitive to reasonable variations in the clustering algorithms.
ERIC Educational Resources Information Center
Laakso, Mikko-Jussi; Myller, Niko; Korhonen, Ari
2009-01-01
In this paper, two emerging learning and teaching methods have been studied: collaboration in concert with algorithm visualization. When visualizations have been employed in collaborative learning, collaboration introduces new challenges for the visualization tools. In addition, new theories are needed to guide the development and research of the…
ERIC Educational Resources Information Center
Strecht, Pedro; Cruz, Luís; Soares, Carlos; Mendes-Moreira, João; Abreu, Rui
2015-01-01
Predicting the success or failure of a student in a course or program is a problem that has recently been addressed using data mining techniques. In this paper we evaluate some of the most popular classification and regression algorithms on this problem. We address two problems: prediction of approval/failure and prediction of grade. The former is…
NASA Technical Reports Server (NTRS)
Lyster, Peter M.; Guo, J.; Clune, T.; Larson, J. W.; Atlas, Robert (Technical Monitor)
2001-01-01
The computational complexity of algorithms for Four Dimensional Data Assimilation (4DDA) at NASA's Data Assimilation Office (DAO) is discussed. In 4DDA, observations are assimilated with the output of a dynamical model to generate best-estimates of the states of the system. It is thus a mapping problem, whereby scattered observations are converted into regular accurate maps of wind, temperature, moisture and other variables. The DAO is developing and using 4DDA algorithms that provide these datasets, or analyses, in support of Earth System Science research. Two large-scale algorithms are discussed. The first approach, the Goddard Earth Observing System Data Assimilation System (GEOS DAS), uses an atmospheric general circulation model (GCM) and an observation-space based analysis system, the Physical-space Statistical Analysis System (PSAS). GEOS DAS is very similar to global meteorological weather forecasting data assimilation systems, but is used at NASA for climate research. Systems of this size typically run at between 1 and 20 gigaflop/s. The second approach, the Kalman filter, uses a more consistent algorithm to determine the forecast error covariance matrix than does GEOS DAS. For atmospheric assimilation, the gridded dynamical fields typically have More than 10(exp 6) variables, therefore the full error covariance matrix may be in excess of a teraword. For the Kalman filter this problem can easily scale to petaflop/s proportions. We discuss the computational complexity of GEOS DAS and our implementation of the Kalman filter. We also discuss and quantify some of the technical issues and limitations in developing efficient, in terms of wall clock time, and scalable parallel implementations of the algorithms.
NASA Astrophysics Data System (ADS)
Berlich, Rüdiger; Kunze, Marcel
1997-02-01
The Supervised Growing Neural Gas algorithm (SGNG) provides an interesting alternative to standard Multi-Layer Perceptrons (MLP). A comparison is drawn between the performance of SGNG and MLP in the domain of function mapping. A further field of interest is classification power, which has been investigated with real data taken by PS197 at CERN. The characteristics of the two network models will be discussed from a practical point of view as well as their advantages and disadvantages.
CUDA-based high-performance computing of the S-BPF algorithm with no-waiting pipelining
NASA Astrophysics Data System (ADS)
Deng, Lin; Yan, Bin; Chang, Qingmei; Han, Yu; Zhang, Xiang; Xi, Xiaoqi; Li, Lei
2015-10-01
The backprojection-filtration (BPF) algorithm has become a good solution for local reconstruction in cone-beam computed tomography (CBCT). However, the reconstruction speed of BPF is a severe limitation for clinical applications. The selective-backprojection filtration (S-BPF) algorithm is developed to improve the parallel performance of BPF by selective backprojection. Furthermore, the general-purpose graphics processing unit (GP-GPU) is a popular tool for accelerating the reconstruction. Much work has been performed aiming for the optimization of the cone-beam back-projection. As the cone-beam back-projection process becomes faster, the data transportation holds a much bigger time proportion in the reconstruction than before. This paper focuses on minimizing the total time in the reconstruction with the S-BPF algorithm by hiding the data transportation among hard disk, CPU and GPU. And based on the analysis of the S-BPF algorithm, some strategies are implemented: (1) the asynchronous calls are used to overlap the implemention of CPU and GPU, (2) an innovative strategy is applied to obtain the DBP image to hide the transport time effectively, (3) two streams for data transportation and calculation are synchronized by the cudaEvent in the inverse of finite Hilbert transform on GPU. Our main contribution is a smart reconstruction of the S-BPF algorithm with GPU's continuous calculation and no data transportation time cost. a 5123 volume is reconstructed in less than 0.7 second on a single Tesla-based K20 GPU from 182 views projection with 5122 pixel per projection. The time cost of our implementation is about a half of that without the overlap behavior.
Feng, Lu; Fedrigo, Enrico; Béchet, Clémentine; Brunner, Elisabeth; Pirani, Werther
2012-06-01
The European Southern Observatory (ESO) is studying the next generation giant telescope, called the European Extremely Large Telescope (E-ELT). With a 42 m diameter primary mirror, it is a significant step from currently existing telescopes. Therefore, the E-ELT with its instruments poses new challenges in terms of cost and computational complexity for the control system, including its adaptive optics (AO). Since the conventional matrix-vector multiplication (MVM) method successfully used so far for AO wavefront reconstruction cannot be efficiently scaled to the size of the AO systems on the E-ELT, faster algorithms are needed. Among those recently developed wavefront reconstruction algorithms, three are studied in this paper from the point of view of design, implementation, and absolute speed on three multicore multi-CPU platforms. We focus on a single-conjugate AO system for the E-ELT. The algorithms are the MVM, the Fourier transform reconstructor (FTR), and the fractal iterative method (FRiM). This study enhances the scaling of these algorithms with an increasing number of CPUs involved in the computation. We discuss implementation strategies, depending on various CPU architecture constraints, and we present the first quantitative execution times so far at the E-ELT scale. MVM suffers from a large computational burden, making the current computing platform undersized to reach timings short enough for AO wavefront reconstruction. In our study, the FTR provides currently the fastest reconstruction. FRiM is a recently developed algorithm, and several strategies are investigated and presented here in order to implement it for real-time AO wavefront reconstruction, and to optimize its execution time. The difficulty to parallelize the algorithm in such architecture is enhanced. We also show that FRiM can provide interesting scalability using a sparse matrix approach. PMID:22695596
Feng, Lu; Fedrigo, Enrico; Béchet, Clémentine; Brunner, Elisabeth; Pirani, Werther
2012-06-01
The European Southern Observatory (ESO) is studying the next generation giant telescope, called the European Extremely Large Telescope (E-ELT). With a 42 m diameter primary mirror, it is a significant step from currently existing telescopes. Therefore, the E-ELT with its instruments poses new challenges in terms of cost and computational complexity for the control system, including its adaptive optics (AO). Since the conventional matrix-vector multiplication (MVM) method successfully used so far for AO wavefront reconstruction cannot be efficiently scaled to the size of the AO systems on the E-ELT, faster algorithms are needed. Among those recently developed wavefront reconstruction algorithms, three are studied in this paper from the point of view of design, implementation, and absolute speed on three multicore multi-CPU platforms. We focus on a single-conjugate AO system for the E-ELT. The algorithms are the MVM, the Fourier transform reconstructor (FTR), and the fractal iterative method (FRiM). This study enhances the scaling of these algorithms with an increasing number of CPUs involved in the computation. We discuss implementation strategies, depending on various CPU architecture constraints, and we present the first quantitative execution times so far at the E-ELT scale. MVM suffers from a large computational burden, making the current computing platform undersized to reach timings short enough for AO wavefront reconstruction. In our study, the FTR provides currently the fastest reconstruction. FRiM is a recently developed algorithm, and several strategies are investigated and presented here in order to implement it for real-time AO wavefront reconstruction, and to optimize its execution time. The difficulty to parallelize the algorithm in such architecture is enhanced. We also show that FRiM can provide interesting scalability using a sparse matrix approach.
Johnson, Robin R.; Popovic, Djordje P.; Olmstead, Richard E.; Stikic, Maja; Levendowski, Daniel J.; Berka, Chris
2011-01-01
A great deal of research over the last century has focused on drowsiness/alertness detection, as fatigue-related physical and cognitive impairments pose a serious risk to public health and safety. Available drowsiness/alertness detection solutions are unsatisfactory for a number of reasons: 1) lack of generalizability, 2) failure to address individual variability in generalized models, and/or 3) they lack a portable, un-tethered application. The current study aimed to address these issues, and determine if an individualized electroencephalography (EEG) based algorithm could be defined to track performance decrements associated with sleep loss, as this is the first step in developing a field deployable drowsiness/alertness detection system. The results indicated that an EEG-based algorithm, individualized using a series of brief "identification" tasks, was able to effectively track performance decrements associated with sleep deprivation. Future development will address the need for the algorithm to predict performance decrements due to sleep loss, and provide field applicability. PMID:21419826
Oryspayev, Dossay; Aktulga, Hasan Metin; Sosonkina, Masha; Maris, Pieter; Vary, James P.
2015-07-14
In this article, sparse matrix vector multiply (SpMVM) is an important kernel that frequently arises in high performance computing applications. Due to its low arithmetic intensity, several approaches have been proposed in literature to improve its scalability and efficiency in large scale computations. In this paper, our target systems are high end multi-core architectures and we use messaging passing interface + open multiprocessing hybrid programming model for parallelism. We analyze the performance of recently proposed implementation of the distributed symmetric SpMVM, originally developed for large sparse symmetric matrices arising in ab initio nuclear structure calculations. We also study important features of this implementation and compare with previously reported implementations that do not exploit underlying symmetry. Our SpMVM implementations leverage the hybrid paradigm to efficiently overlap expensive communications with computations. Our main comparison criterion is the "CPU core hours" metric, which is the main measure of resource usage on supercomputers. We analyze the effects of topology-aware mapping heuristic using simplified network load model. Furthermore, we have tested the different SpMVM implementations on two large clusters with 3D Torus and Dragonfly topology. Our results show that the distributed SpMVM implementation that exploits matrix symmetry and hides communication yields the best value for the "CPU core hours" metric and significantly reduces data movement overheads.
Oryspayev, Dossay; Aktulga, Hasan Metin; Sosonkina, Masha; Maris, Pieter; Vary, James P.
2015-07-14
In this article, sparse matrix vector multiply (SpMVM) is an important kernel that frequently arises in high performance computing applications. Due to its low arithmetic intensity, several approaches have been proposed in literature to improve its scalability and efficiency in large scale computations. In this paper, our target systems are high end multi-core architectures and we use messaging passing interface + open multiprocessing hybrid programming model for parallelism. We analyze the performance of recently proposed implementation of the distributed symmetric SpMVM, originally developed for large sparse symmetric matrices arising in ab initio nuclear structure calculations. We also study important featuresmore » of this implementation and compare with previously reported implementations that do not exploit underlying symmetry. Our SpMVM implementations leverage the hybrid paradigm to efficiently overlap expensive communications with computations. Our main comparison criterion is the "CPU core hours" metric, which is the main measure of resource usage on supercomputers. We analyze the effects of topology-aware mapping heuristic using simplified network load model. Furthermore, we have tested the different SpMVM implementations on two large clusters with 3D Torus and Dragonfly topology. Our results show that the distributed SpMVM implementation that exploits matrix symmetry and hides communication yields the best value for the "CPU core hours" metric and significantly reduces data movement overheads.« less
Performance of soil moisture retrieval algorithms using multiangular L band brightness temperatures
NASA Astrophysics Data System (ADS)
Piles, M.; Camps, A.; Vall-Llossera, M.; Monerris, A.; Talone, M.; Sabater, J. M.
2010-06-01
The Soil Moisture and Ocean Salinity (SMOS) mission of the European Space Agency was successfully launched in November 2009 to provide global surface soil moisture and sea surface salinity maps. The SMOS single payload is the Microwave Imaging Radiometer by Aperture Synthesis (MIRAS), an L band two-dimensional aperture synthesis interferometric radiometer with multiangular and polarimetric imaging capabilities. SMOS-derived soil moisture products are expected to have an accuracy of 0.04 m3/m3 over 50 × 50 km2 and a revisit time of 3 days. Previous studies have remarked the necessity of combining SMOS brightness temperatures with auxiliary data to achieve the required accuracy. However, the required auxiliary data and optimal soil moisture retrieval setup need yet to be optimized. Also, the satellite operation mode (dual polarization or full polarimetric) is an open issue to be addressed during the commissioning phase activities. In this paper, an in-depth study of the different retrieval configurations and ancillary data needed for the retrieval of soil moisture from future SMOS observations is presented. A dedicated L2 Processor Simulator software has been developed to obtain soil moisture estimates from SMOS-like brightness temperatures generated using the SMOS End-to-End Performance Simulator (SEPS). Full-polarimetric brightness temperatures are generated in SEPS, and soil moisture retrievals are performed using vertical (Tvv) and horizontal (Thh) brightness temperatures and using the first Stokes parameter (TI). Results show the accuracy obtained with the different retrieval setups for four main surface conditions combining wet and dry soils with bare and vegetation-covered surfaces. Soil moisture retrievals using TI exhibit a significantly better performance than using Thh and Tvv in all scenarios, which indicates that the dual-polarization mode should not be disregarded. The uncertainty of the ancillary data used in the minimization process and its effect on
NASA Astrophysics Data System (ADS)
Cho, Hoonkyung; Chun, Joohwan; Song, Sungchan
2016-09-01
The dim moving target tracking from the infrared image sequence in the presence of high clutter and noise has been recently under intensive investigation. The track-before-detect (TBD) algorithm processing the image sequence over a number of frames before decisions on the target track and existence is known to be especially attractive in very low SNR environments (⩽ 3 dB). In this paper, we shortly present a three-dimensional (3-D) TBD with dynamic programming (TBD-DP) algorithm using multiple IR image sensors. Since traditional two-dimensional TBD algorithm cannot track and detect the along the viewing direction, we use 3-D TBD with multiple sensors and also strictly analyze the detection performance (false alarm and detection probabilities) based on Fisher-Tippett-Gnedenko theorem. The 3-D TBD-DP algorithm which does not require a separate image registration step uses the pixel intensity values jointly read off from multiple image frames to compute the merit function required in the DP process. Therefore, we also establish the relationship between the pixel coordinates of image frame and the reference coordinates.
NASA Astrophysics Data System (ADS)
Yin, Zhendong; Zong, Zhiyuan; Sun, Hongjian; Wu, Zhilu; Yang, Zhutian
2012-12-01
In this article, an efficient multiuser detector based on the artificial fish swarm algorithm (AFSA-MUD) is proposed and investigated for direct-sequence ultrawideband systems under different channels: the additive white Gaussian noise channel and the IEEE 802.15.3a multipath channel. From the literature review, the issues that the computational complexity of classical optimum multiuser detection (OMD) rises exponentially with the number of users and the bit error rate (BER) performance of other sub-optimal multiuser detectors is not satisfactory, still need to be solved. This proposed method can make a good tradeoff between complexity and performance through the various behaviors of artificial fishes in the simplified Euclidean solution space, which is constructed by the solutions of some sub-optimal multiuser detectors. Here, these sub-optimal detectors are minimum mean square error detector, decorrelating detector, and successive interference cancellation detector. As a result of this novel scheme, the convergence speed of AFSA-MUD is greatly accelerated and the number of iterations is also significantly reduced. The experimental results demonstrate that the BER performance and the near-far effect resistance of this proposed algorithm are quite close to those of OMD, while its computational complexity is much lower than the traditional OMD. Moreover, as the number of active users increases, the BER performance of AFSA-MUD is almost the same as that of OMD.
NASA Astrophysics Data System (ADS)
Basu, S.; Ganguly, S.; Nemani, R. R.; Mukhopadhyay, S.; Milesi, C.; Votava, P.; Michaelis, A.; Zhang, G.; Cook, B. D.; Saatchi, S. S.; Boyda, E.
2014-12-01
Accurate tree cover delineation is a useful instrument in the derivation of Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) satellite imagery data. Numerous algorithms have been designed to perform tree cover delineation in high to coarse resolution satellite imagery, but most of them do not scale to terabytes of data, typical in these VHR datasets. In this paper, we present an automated probabilistic framework for the segmentation and classification of 1-m VHR data as obtained from the National Agriculture Imagery Program (NAIP) for deriving tree cover estimates for the whole of Continental United States, using a High Performance Computing Architecture. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field (CRF), which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by incorporating expert knowledge through the relabeling of misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the state of California, which covers a total of 11,095 NAIP tiles and spans a total geographical area of 163,696 sq. miles. Our framework produced correct detection rates of around 85% for fragmented forests and 70% for urban tree cover areas, with false positive rates lower than 3% for both regions. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR high-resolution canopy height model shows the effectiveness of our algorithm in generating accurate high-resolution tree cover maps.
Kececioglu, O Fatih; Gani, Ahmet; Sekkeli, Mustafa
2016-01-01
The main objective of the present paper is to introduce a new approach for measuring and calculation of fundamental power components in the case of various distorted waveforms including those containing harmonics. The parameters of active, reactive, apparent power and power factor, are measured and calculated by using Goertzel algorithm instead of fast Fourier transformation which is commonly used. The main advantage of utilizing Goertzel algorithm is to minimize computational load and trigonometric equations. The parameters measured in the new technique are applied to a fixed capacitor-thyristor controlled reactor based static VAr compensation system to achieve accurate power factor correction for the first time. This study is implemented both simulation and experimentally. PMID:27047717
Performance analysis results of a battery fuel gauge algorithm at multiple temperatures
NASA Astrophysics Data System (ADS)
Balasingam, B.; Avvari, G. V.; Pattipati, K. R.; Bar-Shalom, Y.
2015-01-01
Evaluating a battery fuel gauge (BFG) algorithm is a challenging problem due to the fact that there are no reliable mathematical models to represent the complex features of a Li-ion battery, such as hysteresis and relaxation effects, temperature effects on parameters, aging, power fade (PF), and capacity fade (CF) with respect to the chemical composition of the battery. The existing literature is largely focused on developing different BFG strategies and BFG validation has received little attention. In this paper, using hardware in the loop (HIL) data collected form three Li-ion batteries at nine different temperatures ranging from -20 °C to 40 °C, we demonstrate detailed validation results of a battery fuel gauge (BFG) algorithm. The BFG validation is based on three different BFG validation metrics; we provide implementation details of these three BFG evaluation metrics by proposing three different BFG validation load profiles that satisfy varying levels of user requirements.
Ball, R.M.; Madaras, J.J. . Space and Defense Systems); Trowbridge, F.R. Jr.; Talley, D.G.; Parma, E.J. Jr. )
1991-01-01
Experimental tests on the Annular Core Research Reactor have confirmed that the Three-Bean-Salad'' control algorithm based on the Pontryagin maximum principle can change the power of a nuclear reactor many decades with a very fast startup rate and minimal overshoot. The paper describes the results of simulations and operations up to 25 MW and 87 decades per minute. 3 refs., 4 figs., 1 tab.
NASA Technical Reports Server (NTRS)
Rogers, David
1991-01-01
G/SPLINES are a hybrid of Friedman's Multivariable Adaptive Regression Splines (MARS) algorithm with Holland's Genetic Algorithm. In this hybrid, the incremental search is replaced by a genetic search. The G/SPLINE algorithm exhibits performance comparable to that of the MARS algorithm, requires fewer least squares computations, and allows significantly larger problems to be considered.
Laloyaux, Julien; Pellegrini, Nadia; Mourad, Haitham; Bertrand, Hervé; Domken, Marc-André; Van der Linden, Martial; Larøi, Frank
2013-12-15
Persons diagnosed with bipolar disorder often suffer from cognitive impairments. However, little is known concerning how these cognitive deficits impact their real world functioning. We developed a computerized real-life activity task, where participants are required to shop for a list of grocery store items. Twenty one individuals diagnosed with bipolar disorder and 21 matched healthy controls were administered the computerized shopping task. Moreover, the patient group was assessed with a battery of cognitive tests and clinical scales. Performance on the shopping task significantly differentiated patients and healthy controls for two variables: Total time to complete the shopping task and Mean time spent to consult the shopping list. Moreover, in the patient group, performance on these variables from the shopping task correlated significantly with cognitive functioning (i.e. processing speed, verbal episodic memory, planning, cognitive flexibility, and inhibition) and with clinical variables including duration of illness and real world functioning. Finally, variables from the shopping task were found to significantly explain 41% of real world functioning of patients diagnosed with bipolar disorder. These findings suggest that the shopping task provides a good indication of real world functioning and cognitive functioning of persons diagnosed with bipolar disorder.
Sleiman, Z.; Tanos, V.; Van Belle, Y.; Carvalho, J.L.; Campo, R.
2015-01-01
The efficiency of suturing training and testing (SUTT) model by laparoscopy was evaluated, measuring the suturingskill acquisition of trainee gynecologists at the beginning and at the end of a teaching course. During a workshop organized by the European Academy of Gynecological Surgery (EAGS), 25 participants with three different experience levels in laparoscopy (minor, intermediate and major) performed the 4 exercises of the SUTT model (Ex 1: both hands stitching and continuous suturing, Ex 2: right hand stitching and intracorporeal knotting, Ex 3: left hand stitching and intracorporeal knotting, Ex 4: dominant hand stitching, tissue approximation and intracorporeal knotting). The time needed to perform the exercises is recorded for each trainee and group and statistical analysis used to note the differences. Overall, all trainees achieved significant improvement in suturing time (p < 0.005) as measured before and after completion of the training. Similar significantly improved suturing time differences (p < 0.005) were noted among the groups of trainees with different laparoscopic experience. In conclusion a short well-guided training course, using the SUTT model, improves significantly surgeon’s laparoscopic suturing ability, independently of the level of experience in laparoscopic surgery. Key words: Endoscopy, laparoscopic suturing, psychomotor skills, surgery, teaching, training suturing model. PMID:26977264
NASA Astrophysics Data System (ADS)
Hild, Kenneth E.; Alleva, Giovanna; Nagarajan, Srikantan; Comani, Silvia
2007-01-01
In this study we compare the performance of six independent components analysis (ICA) algorithms on 16 real fetal magnetocardiographic (fMCG) datasets for the application of extracting the fetal cardiac signal. We also compare the extraction results for real data with the results previously obtained for synthetic data. The six ICA algorithms are FastICA, CubICA, JADE, Infomax, MRMI-SIG and TDSEP. The results obtained using real fMCG data indicate that the FastICA method consistently outperforms the others in regard to separation quality and that the performance of an ICA method that uses temporal information suffers in the presence of noise. These two results confirm the previous results obtained using synthetic fMCG data. There were also two notable differences between the studies based on real and synthetic data. The differences are that all six ICA algorithms are independent of gestational age and sensor dimensionality for synthetic data, but depend on gestational age and sensor dimensionality for real data. It is possible to explain these differences by assuming that the number of point sources needed to completely explain the data is larger than the dimensionality used in the ICA extraction.
NASA Technical Reports Server (NTRS)
Guo, Liwen; Cardullo, Frank M.; Kelly, Lon C.
2007-01-01
This report summarizes the results of delay measurement and piloted performance tests that were conducted to assess the effectiveness of the adaptive compensator and the state space compensator for alleviating the phase distortion of transport delay in the visual system in the VMS at the NASA Langley Research Center. Piloted simulation tests were conducted to assess the effectiveness of two novel compensators in comparison to the McFarland predictor and the baseline system with no compensation. Thirteen pilots with heterogeneous flight experience executed straight-in and offset approaches, at various delay configurations, on a flight simulator where different predictors were applied to compensate for transport delay. The glideslope and touchdown errors, power spectral density of the pilot control inputs, NASA Task Load Index, and Cooper-Harper rating of the handling qualities were employed for the analyses. The overall analyses show that the adaptive predictor results in slightly poorer compensation for short added delay (up to 48 ms) and better compensation for long added delay (up to 192 ms) than the McFarland compensator. The analyses also show that the state space predictor is fairly superior for short delay and significantly superior for long delay than the McFarland compensator.
Guindon, Stéphane; Dufayard, Jean-François; Lefort, Vincent; Anisimova, Maria; Hordijk, Wim; Gascuel, Olivier
2010-05-01
PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.
Algorithms Performance Investigation of a Generalized Spreader-Bar Detection System
Robinson, Sean M.; Ashbaker, Eric D.; Hensley, Walter K.; Schweppe, John E.; Sandness, Gerald A.; Erikson, Luke E.; Ely, James H.
2010-10-01
A “generic” gantry-crane-mounted spreader bar detector has been simulated in the Monte-Carlo radiation transport code MCNP [1]. This model is intended to represent the largest realistically feasible number of detector crystals in a single gantry-crane model intended to sit atop an InterModal Cargo Container (IMCC). Detectors were chosen from among large commonly-available sodium iodide (NaI) crystal scintillators and spaced as evenly as is thought possible with a detector apparatus attached to a gantry crane. Several scenarios were simulated with this model, based on a single IMCC being moved between a ship’s deck or cargo hold and the dock. During measurement, the gantry crane will carry that IMCC through the air and lower it onto a receiving vehicle (e.g. a chassis or a bomb cart). The case of an IMCC being moved through the air from an unknown radiological environment to the ground is somewhat complex; for this initial study a single location was picked at which to simulate background. An HEU source based on earlier validated models was used, and placed at varying depths in a wood cargo. Many statistical realizations of these scenarios are constructed from simulations of the component spectra, simulated to have high statistics. The resultant data are analyzed with several different algorithms. The simulated data were evaluated by each algorithm, with a threshold set to a statistical-only false alarm probability of 0.001 and the resultant Minimum Detectable Amounts were generated for each Cargo depth possible within the IMCC. Using GADRAS as an anomaly detector provided the greatest detection sensitivity, and it is expected that an algorithm similar to this will be of great use to the detection of highly shielded sources.
Finan, Daniel A; McCann, Thomas W; Rhein, Kathleen; Dassau, Eyal; Breton, Marc D; Patek, Stephen D; Anhalt, Henry; Kovatchev, Boris P; Doyle, Francis J; Anderson, Stacey M; Zisser, Howard; Venugopalan, Ramakrishna
2014-07-01
The Hypoglycemia-Hyperglycemia Minimizer (HHM) System aims to mitigate glucose excursions by preemptively modulating insulin delivery based on continuous glucose monitor (CGM) measurements. The "aggressiveness factor" is a key parameter in the HHM System algorithm, affecting how readily the system adjusts insulin infusion in response to changing CGM levels. Twenty adults with type 1 diabetes were studied in closed-loop in a clinical research center for approximately 26 hours. This analysis focused on the effect of the aggressiveness factor on the insulin dosing characteristics of the algorithm and, to a lesser extent, on the glucose control results observed. As the aggressiveness factor increased from conservative to medium to aggressive: the maximum observed insulin dose delivered by the algorithm—which is designed to give doses that are corrective in nature every 5 minutes—increased (1.00 vs 1.15 vs 2.20 U, respectively); tendency to adhere to the subject's nominal basal dose decreased (61.9% vs 56.6% vs 53.4%); and readiness to decrease insulin below basal also increased (18.4% vs 19.4% vs 25.2%). Glucose analyses by both CGM and Yellow Springs Instruments (YSI) indicated that the aggressive setting of the algorithm resulted in the least time spent at levels >180 mg/dL, and the most time spent between 70-180 mg/dL. There was no severe hyperglycemia, diabetic ketoacidosis, or severe hypoglycemia for any of the aggressiveness values investigated. These analyses underscore the importance of investigating the sensitivity of the HHM System to its key parameters, such as the aggressiveness factor, to guide future development decisions. PMID:24876443
NASA Astrophysics Data System (ADS)
Radev, Dimitar; Lokshina, Izabella
2010-11-01
The paper examines self-similar (or fractal) properties of real communication network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Advanced fractal models of sequentional generators and fixed-length sequence generators, and efficient algorithms that are used to simulate self-similar behavior of IP network traffic data are developed and applied. Numerical examples are provided; and simulation results are obtained and analyzed.
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
Architecture-Aware Algorithms for Scalable Performance and Resilience on Heterogeneous Architectures
Dongarra, Jack
2013-03-14
There is a widening gap between the peak performance of high performance computers and the performance realized by full applications. Over the next decade, extreme-scale systems will present major new challenges to software development that could widen the gap so much that it prevents the productive use of future DOE Leadership computers.
Cloud Algorithm Design and Performance for the 2002 Geoscience Laser Altimeter System Mission
NASA Technical Reports Server (NTRS)
Spinhirne, J. D.; Palm, S. P.; Hart, W. D.; Hlavka, D. L.; Mahesh, A.; Starr, David (Technical Monitor)
2002-01-01
A satellite borne lidar instrument, the Geoscience Laser Altimeter System (GLAS), is to be launched in late 2002 and will provide continuous profiling of atmospheric clouds and aerosol on a global basis. Data processing algorithms have been developed to provide operational data products in near real time. Basic data products for cloud observations are the height of the top and bottom of single to multiple cloud layers and the lidar calibrated observed backscatter cross section up to the level of signal attenuation. In addition the optical depth and vertical profile of visible extinction cross section of many transmissive cloud layers and most haze layers are to be derived. The optical thickness is derivable in some cases from the attenuation of the molecular scattering below cloud base. In other cases an assumption of the scattering phase function is required. In both cases a estimated correction for multiple scattering is required. The data processing algorithms have been tested in part from aircraft measurements used to simulated satellite data. The GLAS lidar observations will be made from an orbit that will allow inter comparison with all other existing satellite cloud measurements.
NASA Astrophysics Data System (ADS)
Zhang, Yue; Yan, Baiqian; Ou-Yang, Jun; Wang, Xianghao; Zhu, Benpeng; Chen, Shi; Yang, Xiaofei
2016-01-01
Through principles of spin-valve giant magnetoresistance (SV-GMR) effect and its application in magnetic sensors, we have investigated electric-field control of the output performance of a bridge-structured Co/Cu/NiFe/IrMn SV-GMR sensor on a PZN-PT piezoelectric substrate using the micro-magnetic simulation. We centered on the influence of the variation of uniaxial magnetic anisotropy constant (K) of Co on the output of the bridge, and K was manipulated via the stress of Co, which is generated from the strain of a piezoelectric substrate under an electric field. The results indicate that when K varies between 2 × 104 J/m3 and 10 × 104 J/m3, the output performance can be significantly manipulated: The linear range alters from between -330 Oe and 330 Oe to between -650 Oe and 650 Oe, and the sensitivity is tuned by almost 7 times, making it possible to measure magnetic fields with very different ranges. According to the converse piezoelectric effect, we have found that this variation of K can be realized by applying an electric field with the magnitude of about 2-20 kV/cm on a PZN-PT piezoelectric substrate, which is realistic in application. This result means that electric-control of SV-GMR effect has potential application in developing SV-GMR sensors with improved performance.
Afik, Eldad
2015-01-01
Three-dimensional particle tracking is an essential tool in studying dynamics under the microscope, namely, fluid dynamics in microfluidic devices, bacteria taxis, cellular trafficking. The 3d position can be determined using 2d imaging alone by measuring the diffraction rings generated by an out-of-focus fluorescent particle, imaged on a single camera. Here I present a ring detection algorithm exhibiting a high detection rate, which is robust to the challenges arising from ring occlusion, inclusions and overlaps, and allows resolving particles even when near to each other. It is capable of real time analysis thanks to its high performance and low memory footprint. The proposed algorithm, an offspring of the circle Hough transform, addresses the need to efficiently trace the trajectories of many particles concurrently, when their number in not necessarily fixed, by solving a classification problem, and overcomes the challenges of finding local maxima in the complex parameter space which results from ring clusters and noise. Several algorithmic concepts introduced here can be advantageous in other cases, particularly when dealing with noisy and sparse data. The implementation is based on open-source and cross-platform software packages only, making it easy to distribute and modify. It is implemented in a microfluidic experiment allowing real-time multi-particle tracking at 70 Hz, achieving a detection rate which exceeds 94% and only 1% false-detection. PMID:26329642
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.
Kumaravel, Rasadurai; Narayanaswamy, Kumaratharan
2015-01-01
Multi carrier code division multiple access (MC-CDMA) system is a promising multi carrier modulation (MCM) technique for high data rate wireless communication over frequency selective fading channels. MC-CDMA system is a combination of code division multiple access (CDMA) and orthogonal frequency division multiplexing (OFDM). The OFDM parts reduce multipath fading and inter symbol interference (ISI) and the CDMA part increases spectrum utilization. Advantages of this technique are its robustness in case of multipath propagation and improve security with the minimize ISI. Nevertheless, due to the loss of orthogonality at the receiver in a mobile environment, the multiple access interference (MAI) appears. The MAI is one of the factors that degrade the bit error rate (BER) performance of MC-CDMA system. The multiuser detection (MUD) and turbo coding are the two dominant techniques for enhancing the performance of the MC-CDMA systems in terms of BER as a solution of overcome to MAI effects. In this paper a low complexity iterative soft sensitive bits algorithm (SBA) aided logarithmic-Maximum a-Posteriori algorithm (Log MAP) based turbo MUD is proposed. Simulation results show that the proposed method provides better BER performance with low complexity decoding, by mitigating the detrimental effects of MAI. PMID:25714917
Kumaravel, Rasadurai; Narayanaswamy, Kumaratharan
2015-01-01
Multi carrier code division multiple access (MC-CDMA) system is a promising multi carrier modulation (MCM) technique for high data rate wireless communication over frequency selective fading channels. MC-CDMA system is a combination of code division multiple access (CDMA) and orthogonal frequency division multiplexing (OFDM). The OFDM parts reduce multipath fading and inter symbol interference (ISI) and the CDMA part increases spectrum utilization. Advantages of this technique are its robustness in case of multipath propagation and improve security with the minimize ISI. Nevertheless, due to the loss of orthogonality at the receiver in a mobile environment, the multiple access interference (MAI) appears. The MAI is one of the factors that degrade the bit error rate (BER) performance of MC-CDMA system. The multiuser detection (MUD) and turbo coding are the two dominant techniques for enhancing the performance of the MC-CDMA systems in terms of BER as a solution of overcome to MAI effects. In this paper a low complexity iterative soft sensitive bits algorithm (SBA) aided logarithmic-Maximum a-Posteriori algorithm (Log MAP) based turbo MUD is proposed. Simulation results show that the proposed method provides better BER performance with low complexity decoding, by mitigating the detrimental effects of MAI.
Kumaravel, Rasadurai; Narayanaswamy, Kumaratharan
2015-01-01
Multi carrier code division multiple access (MC-CDMA) system is a promising multi carrier modulation (MCM) technique for high data rate wireless communication over frequency selective fading channels. MC-CDMA system is a combination of code division multiple access (CDMA) and orthogonal frequency division multiplexing (OFDM). The OFDM parts reduce multipath fading and inter symbol interference (ISI) and the CDMA part increases spectrum utilization. Advantages of this technique are its robustness in case of multipath propagation and improve security with the minimize ISI. Nevertheless, due to the loss of orthogonality at the receiver in a mobile environment, the multiple access interference (MAI) appears. The MAI is one of the factors that degrade the bit error rate (BER) performance of MC-CDMA system. The multiuser detection (MUD) and turbo coding are the two dominant techniques for enhancing the performance of the MC-CDMA systems in terms of BER as a solution of overcome to MAI effects. In this paper a low complexity iterative soft sensitive bits algorithm (SBA) aided logarithmic-Maximum a-Posteriori algorithm (Log MAP) based turbo MUD is proposed. Simulation results show that the proposed method provides better BER performance with low complexity decoding, by mitigating the detrimental effects of MAI. PMID:25714917
NASA Technical Reports Server (NTRS)
Skofronick-Jackson, Gail; Munchak, Stephen J.; Ringerud, Sarah
2016-01-01
Retrievals of falling snow from space represent an important data set for understanding the Earth's atmospheric, hydrological, and energy cycles, especially during climate change. Estimates of falling snow must be captured to obtain the true global precipitation water cycle, snowfall accumulations are required for hydrological studies, and without knowledge of the frozen particles in clouds one cannot adequately understand the energy and radiation budgets. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new and retrievals are still undergoing development with challenges remaining). This work reports on the development and testing of retrieval algorithms for the Global Precipitation Measurement (GPM) mission Core Satellite, launched February 2014.
Performance analysis of large-scale applications based on wavefront algorithms
Hoisie, A.; Lubeck, O.; Wasserman, H.
1998-12-31
The authors introduced a performance model for parallel, multidimensional, wavefront calculations with machine performance characterized using the LogGP framework. The model accounts for overlap in the communication and computation components. The agreement with experimental data is very good under a variety of model sizes, data partitionings, blocking strategies, and on three different parallel architectures. Using the model, the authors analyzed performance of a deterministic transport code on a hypothetical 100 Tflops future parallel system of interest to ASCI.
2011-01-01
Background Verbal autopsies provide valuable information for studying mortality patterns in populations that lack reliable vital registration data. Methods for transforming verbal autopsy results into meaningful information for health workers and policymakers, however, are often costly or complicated to use. We present a simple additive algorithm, the Tariff Method (termed Tariff), which can be used for assigning individual cause of death and for determining cause-specific mortality fractions (CSMFs) from verbal autopsy data. Methods Tariff calculates a score, or "tariff," for each cause, for each sign/symptom, across a pool of validated verbal autopsy data. The tariffs are summed for a given response pattern in a verbal autopsy, and this sum (score) provides the basis for predicting the cause of death in a dataset. We implemented this algorithm and evaluated the method's predictive ability, both in terms of chance-corrected concordance at the individual cause assignment level and in terms of CSMF accuracy at the population level. The analysis was conducted separately for adult, child, and neonatal verbal autopsies across 500 pairs of train-test validation verbal autopsy data. Results Tariff is capable of outperforming physician-certified verbal autopsy in most cases. In terms of chance-corrected concordance, the method achieves 44.5% in adults, 39% in children, and 23.9% in neonates. CSMF accuracy was 0.745 in adults, 0.709 in children, and 0.679 in neonates. Conclusions Verbal autopsies can be an efficient means of obtaining cause of death data, and Tariff provides an intuitive, reliable method for generating individual cause assignment and CSMFs. The method is transparent and flexible and can be readily implemented by users without training in statistics or computer science. PMID:21816107
Maiti, Abhik; Chakravarty, Debashish
2016-01-01
3D reconstruction of geo-objects from their digital images is a time-efficient and convenient way of studying the structural features of the object being modelled. This paper presents a 3D reconstruction methodology which can be used to generate photo-realistic 3D watertight surface of different irregular shaped objects, from digital image sequences of the objects. The 3D reconstruction approach described here is robust, simplistic and can be readily used in reconstructing watertight 3D surface of any object from its digital image sequence. Here, digital images of different objects are used to build sparse, followed by dense 3D point clouds of the objects. These image-obtained point clouds are then used for generation of photo-realistic 3D surfaces, using different surface reconstruction algorithms such as Poisson reconstruction and Ball-pivoting algorithm. Different control parameters of these algorithms are identified, which affect the quality and computation time of the reconstructed 3D surface. The effects of these control parameters in generation of 3D surface from point clouds of different density are studied. It is shown that the reconstructed surface quality of Poisson reconstruction depends on Samples per node (SN) significantly, greater SN values resulting in better quality surfaces. Also, the quality of the 3D surface generated using Ball-Pivoting algorithm is found to be highly depend upon Clustering radius and Angle threshold values. The results obtained from this study give the readers of the article a valuable insight into the effects of different control parameters on determining the reconstructed surface quality. PMID:27386376
Maiti, Abhik; Chakravarty, Debashish
2016-01-01
3D reconstruction of geo-objects from their digital images is a time-efficient and convenient way of studying the structural features of the object being modelled. This paper presents a 3D reconstruction methodology which can be used to generate photo-realistic 3D watertight surface of different irregular shaped objects, from digital image sequences of the objects. The 3D reconstruction approach described here is robust, simplistic and can be readily used in reconstructing watertight 3D surface of any object from its digital image sequence. Here, digital images of different objects are used to build sparse, followed by dense 3D point clouds of the objects. These image-obtained point clouds are then used for generation of photo-realistic 3D surfaces, using different surface reconstruction algorithms such as Poisson reconstruction and Ball-pivoting algorithm. Different control parameters of these algorithms are identified, which affect the quality and computation time of the reconstructed 3D surface. The effects of these control parameters in generation of 3D surface from point clouds of different density are studied. It is shown that the reconstructed surface quality of Poisson reconstruction depends on Samples per node (SN) significantly, greater SN values resulting in better quality surfaces. Also, the quality of the 3D surface generated using Ball-Pivoting algorithm is found to be highly depend upon Clustering radius and Angle threshold values. The results obtained from this study give the readers of the article a valuable insight into the effects of different control parameters on determining the reconstructed surface quality.
Stasiak, Grażyna; Mazur, Andrzej; Wielbo, Jerzy; Marczak, Małgorzata; Zebracki, Kamil; Koper, Piotr; Skorupska, Anna
2014-11-01
Rhizobium leguminosarum bv. trifolii TA1 (RtTA1) is a soil bacterium establishing a highly specific symbiotic relationship with clover, which is based on the exchange of molecular signals between the host plant and the microsymbiont. The RtTA1 genome is large and multipartite, composed of a chromosome and four plasmids, which comprise approximately 65 % and 35 % of the total genome, respectively. Extrachromosomal replicons were previously shown to confer significant metabolic versatility to bacteria, which is important for their adaptation in the soil and nodulation competitiveness. To investigate the contribution of individual RtTA1 plasmids to the overall cell phenotype, metabolic properties and symbiotic performance, a transposon-based elimination strategy was employed. RtTA1 derivatives cured of pRleTA1b or pRleTA1d and deleted in pRleTA1a were obtained. In contrast to the in silico predictions of pRleTA1b and pRleTA1d, which were described as chromid-like replicons, both appeared to be completely curable. On the other hand, for pRleTA1a (symbiotic plasmid) and pRleTA1c, which were proposed to be unessential for RtTA1 viability, it was not possible to eliminate them at all (pRleTA1c) or entirely (pRleTA1a). Analyses of the phenotypic traits of the RtTA1 derivatives obtained revealed the functional significance of individual plasmids and their indispensability for growth, certain metabolic pathways, production of surface polysaccharides, autoaggregation, biofilm formation, motility and symbiotic performance. Moreover, the results allow us to suggest broad functional cooperation among the plasmids in shaping the phenotypic properties and symbiotic capabilities of rhizobia.
Li, Hua; Dolly, Steven; Chen, Hsin-Chen; Anastasio, Mark A; Low, Daniel A; Li, Harold H; Michalski, Jeff M; Thorstad, Wade L; Gay, Hiram; Mutic, Sasa
2016-07-08
CT image reconstruction is typically evaluated based on the ability to reduce the radiation dose to as-low-as-reasonably-achievable (ALARA) while maintaining acceptable image quality. However, the determination of common image quality metrics, such as noise, contrast, and contrast-to-noise ratio, is often insufficient for describing clinical radiotherapy task performance. In this study we designed and implemented a new comparative analysis method associating image quality, radiation dose, and patient size with radiotherapy task performance, with the purpose of guiding the clinical radiotherapy usage of CT reconstruction algorithms. The iDose4 iterative reconstruction algorithm was selected as the target for comparison, wherein filtered back-projection (FBP) reconstruction was regarded as the baseline. Both phantom and patient images were analyzed. A layer-adjustable anthropomorphic pelvis phantom capable of mimicking 38-58 cm lateral diameter-sized patients was imaged and reconstructed by the FBP and iDose4 algorithms with varying noise-reduction-levels, respectively. The resulting image sets were quantitatively assessed by two image quality indices, noise and contrast-to-noise ratio, and two clinical task-based indices, target CT Hounsfield number (for electron density determination) and structure contouring accuracy (for dose-volume calculations). Additionally, CT images of 34 patients reconstructed with iDose4 with six noise reduction levels were qualitatively evaluated by two radiation oncologists using a five-point scoring mechanism. For the phantom experiments, iDose4 achieved noise reduction up to 66.1% and CNR improvement up to 53.2%, compared to FBP without considering the changes of spatial resolution among images and the clinical acceptance of reconstructed images. Such improvements consistently appeared across different iDose4 noise reduction levels, exhibiting limited interlevel noise (< 5 HU) and target CT number variations (< 1 HU). The radiation
Stapleton, Ann E; Cox, Marsha E; DiNello, Robert K; Geisberg, Mark; Abbott, April; Roberts, Pacita L; Hooton, Thomas M
2015-09-01
Urinary tract infections (UTIs) are frequently encountered in clinical practice and most commonly caused by Escherichia coli and other Gram-negative uropathogens. We tested RapidBac, a rapid immunoassay for bacteriuria developed by Silver Lake Research Corporation (SLRC), compared with standard bacterial culture using 966 clean-catch urine specimens submitted to a clinical microbiology laboratory in an urban academic medical center. RapidBac was performed in accordance with instructions, providing a positive or negative result in 20 min. RapidBac identified as positive 245/285 (sensitivity 86%) samples with significant bacteriuria, defined as the presence of a Gram-negative uropathogen or Staphylococcus saprophyticus at ≥10(3) CFU/ml. The sensitivities for Gram-negative bacteriuria at ≥10(4) CFU/ml and ≥10(5) CFU/ml were 96% and 99%, respectively. The specificity of the test, detecting the absence of significant bacteriuria, was 94%. The sensitivity and specificity of RapidBac were similar on samples from inpatient and outpatient settings, from male and female patients, and across age groups from 18 to 89 years old, although specificity was higher in men (100%) compared with that in women (92%). The RapidBac test for bacteriuria may be effective as an aid in the point-of-care diagnosis of UTIs especially in emergency and primary care settings. PMID:26063858
NASA Astrophysics Data System (ADS)
Ward, V. L.; Singh, R.; Reed, P. M.; Keller, K.
2014-12-01
As water resources problems typically involve several stakeholders with conflicting objectives, multi-objective evolutionary algorithms (MOEAs) are now key tools for understanding management tradeoffs. Given the growing complexity of water planning problems, it is important to establish if an algorithm can consistently perform well on a given class of problems. This knowledge allows the decision analyst to focus on eliciting and evaluating appropriate problem formulations. This study proposes a multi-objective adaptation of the classic environmental economics "Lake Problem" as a computationally simple but mathematically challenging MOEA benchmarking problem. The lake problem abstracts a fictional town on a lake which hopes to maximize its economic benefit without degrading the lake's water quality to a eutrophic (polluted) state through excessive phosphorus loading. The problem poses the challenge of maintaining economic activity while confronting the uncertainty of potentially crossing a nonlinear and potentially irreversible pollution threshold beyond which the lake is eutrophic. Objectives for optimization are maximizing economic benefit from lake pollution, maximizing water quality, maximizing the reliability of remaining below the environmental threshold, and minimizing the probability that the town will have to drastically change pollution policies in any given year. The multi-objective formulation incorporates uncertainty with a stochastic phosphorus inflow abstracting non-point source pollution. We performed comprehensive diagnostics using 6 algorithms: Borg, MOEAD, eMOEA, eNSGAII, GDE3, and NSGAII to ascertain their controllability, reliability, efficiency, and effectiveness. The lake problem abstracts elements of many current water resources and climate related management applications where there is the potential for crossing irreversible, nonlinear thresholds. We show that many modern MOEAs can fail on this test problem, indicating its suitability as a
Performance evaluation of an automated single-channel sleep–wake detection algorithm
Kaplan, Richard F; Wang, Ying; Loparo, Kenneth A; Kelly, Monica R; Bootzin, Richard R
2014-01-01
Background A need exists, from both a clinical and a research standpoint, for objective sleep measurement systems that are both easy to use and can accurately assess sleep and wake. This study evaluates the output of an automated sleep–wake detection algorithm (Z-ALG) used in the Zmachine (a portable, single-channel, electroencephalographic [EEG] acquisition and analysis system) against laboratory polysomnography (PSG) using a consensus of expert visual scorers. Methods Overnight laboratory PSG studies from 99 subjects (52 females/47 males, 18–60 years, median age 32.7 years), including both normal sleepers and those with a variety of sleep disorders, were assessed. PSG data obtained from the differential mastoids (A1–A2) were assessed by Z-ALG, which determines sleep versus wake every 30 seconds using low-frequency, intermediate-frequency, and high-frequency and time domain EEG features. PSG data were independently scored by two to four certified PSG technologists, using standard Rechtschaffen and Kales guidelines, and these score files were combined on an epoch-by-epoch basis, using a majority voting rule, to generate a single score file per subject to compare against the Z-ALG output. Both epoch-by-epoch and standard sleep indices (eg, total sleep time, sleep efficiency, latency to persistent sleep, and wake after sleep onset) were compared between the Z-ALG output and the technologist consensus score files. Results Overall, the sensitivity and specificity for detecting sleep using the Z-ALG as compared to the technologist consensus are 95.5% and 92.5%, respectively, across all subjects, and the positive predictive value and the negative predictive value for detecting sleep are 98.0% and 84.2%, respectively. Overall κ agreement is 0.85 (approaching the level of agreement observed among sleep technologists). These results persist when the sleep disorder subgroups are analyzed separately. Conclusion This study demonstrates that the Z-ALG automated sleep
Algorithms and Algorithmic Languages.
ERIC Educational Resources Information Center
Veselov, V. M.; Koprov, V. M.
This paper is intended as an introduction to a number of problems connected with the description of algorithms and algorithmic languages, particularly the syntaxes and semantics of algorithmic languages. The terms "letter, word, alphabet" are defined and described. The concept of the algorithm is defined and the relation between the algorithm and…
NASA Astrophysics Data System (ADS)
Yu, Xiaonan; Tong, Shoufeng; Dong, Yan; Song, Yansong; Hao, Shicong; Lu, Jing
2016-06-01
An avalanche photodiode (APD) receiver for intersatellite laser communication links is proposed and its performance is experimentally demonstrated. In the proposed system, a series of analog circuits are used not only to adjust the temperature and control the bias voltage but also to monitor the current and recover the clock from the communication data. In addition, the temperature compensation and multiplication gain control algorithm are embedded in the microcontroller to improve the performance of the receiver. As shown in the experiment, with the change of communication rate from 10 to 2000 Mbps, the detection sensitivity of the APD receiver varies from -47 to -34 dBm. Moreover, due to the existence of the multiplication gain control algorithm, the dynamic range of the APD receiver is effectively improved, while the dynamic range at 10, 100, and 1000 Mbps is 38.7, 37.7, and 32.8 dB, respectively. As a result, the experimental results agree well with the theoretical predictions, and the receiver will improve the flexibility of the intersatellite links without increasing the cost.
NASA Astrophysics Data System (ADS)
Yu, Xiaonan; Tong, Shoufeng; Dong, Yan; Song, Yansong; Hao, Shicong; Lu, Jing
2016-06-01
An avalanche photodiode (APD) receiver for intersatellite laser communication links is proposed and its performance is experimentally demonstrated. In the proposed system, a series of analog circuits are used not only to adjust the temperature and control the bias voltage but also to monitor the current and recover the clock from the communication data. In addition, the temperature compensation and multiplication gain control algorithm are embedded in the microcontroller to improve the performance of the receiver. As shown in the experiment, with the change of communication rate from 10 to 2000 Mbps, the detection sensitivity of the APD receiver varies from -47 to -34 dBm. Moreover, due to the existence of the multiplication gain control algorithm, the dynamic range of the APD receiver is effectively improved, while the dynamic range at 10, 100, and 1000 Mbps is 38.7, 37.7, and 32.8 dB, respectively. As a result, the experimental results agree well with the theoretical predictions, and the receiver will improve the flexibility of the intersatellite links without increasing the cost.
A framework for benchmarking of homogenisation algorithm performance on the global scale
NASA Astrophysics Data System (ADS)
Willett, K.; Williams, C.; Jolliffe, I. T.; Lund, R.; Alexander, L. V.; Brönnimann, S.; Vincent, L. A.; Easterbrook, S.; Venema, V. K. C.; Berry, D.; Warren, R. E.; Lopardo, G.; Auchmann, R.; Aguilar, E.; Menne, M. J.; Gallagher, C.; Hausfather, Z.; Thorarinsdottir, T.; Thorne, P. W.
2014-09-01
The International Surface Temperature Initiative (ISTI) is striving towards substantively improving our ability to robustly understand historical land surface air temperature change at all scales. A key recently completed first step has been collating all available records into a comprehensive open access, traceable and version-controlled databank. The crucial next step is to maximise the value of the collated data through a robust international framework of benchmarking and assessment for product intercomparison and uncertainty estimation. We focus on uncertainties arising from the presence of inhomogeneities in monthly mean land surface temperature data and the varied methodological choices made by various groups in building homogeneous temperature products. The central facet of the benchmarking process is the creation of global-scale synthetic analogues to the real-world database where both the "true" series and inhomogeneities are known (a luxury the real-world data do not afford us). Hence, algorithmic strengths and weaknesses can be meaningfully quantified and conditional inferences made about the real-world climate system. Here we discuss the necessary framework for developing an international homogenisation benchmarking system on the global scale for monthly mean temperatures. The value of this framework is critically dependent upon the number of groups taking part and so we strongly advocate involvement in the benchmarking exercise from as many data analyst groups as possible to make the best use of this substantial effort.
Concepts for benchmarking of homogenisation algorithm performance on the global scale
NASA Astrophysics Data System (ADS)
Willett, K.; Williams, C.; Jolliffe, I.; Lund, R.; Alexander, L.; Brönniman, S.; Vincent, L. A.; Easterbrook, S.; Venema, V.; Berry, D.; Warren, R.; Lopardo, G.; Auchmann, R.; Aguilar, E.; Menne, M.; Gallagher, C.; Hausfather, Z.; Thorarinsdottir, T.; Thorne, P. W.
2014-06-01
The International Surface Temperature Initiative (ISTI) is striving towards substantively improving our ability to robustly understand historical land surface air temperature change at all scales. A key recently completed first step has been collating all available records into a comprehensive open access, traceable and version-controlled databank. The crucial next step is to maximise the value of the collated data through a robust international framework of benchmarking and assessment for product intercomparison and uncertainty estimation. We focus on uncertainties arising from the presence of inhomogeneities in monthly surface temperature data and the varied methodological choices made by various groups in building homogeneous temperature products. The central facet of the benchmarking process is the creation of global scale synthetic analogs to the real-world database where both the "true" series and inhomogeneities are known (a luxury the real world data do not afford us). Hence algorithmic strengths and weaknesses can be meaningfully quantified and conditional inferences made about the real-world climate system. Here we discuss the necessary framework for developing an international homogenisation benchmarking system on the global scale for monthly mean temperatures. The value of this framework is critically dependent upon the number of groups taking part and so we strongly advocate involvement in the benchmarking exercise from as many data analyst groups as possible to make the best use of this substantial effort.
NASA Astrophysics Data System (ADS)
Bernabe, Sergio; Igual, Francisco D.; Botella, Guillermo; Garcia, Carlos; Prieto-Matias, Manuel; Plaza, Antonio
2015-10-01
Recent advances in heterogeneous high performance computing (HPC) have opened new avenues for demanding remote sensing applications. Perhaps one of the most popular algorithm in target detection and identification is the automatic target detection and classification algorithm (ATDCA) widely used in the hyperspectral image analysis community. Previous research has already investigated the mapping of ATDCA on graphics processing units (GPUs) and field programmable gate arrays (FPGAs), showing impressive speedup factors that allow its exploitation in time-critical scenarios. Based on these studies, our work explores the performance portability of a tuned OpenCL implementation across a range of processing devices including multicore processors, GPUs and other accelerators. This approach differs from previous papers, which focused on achieving the optimal performance on each platform. Here, we are more interested in the following issues: (1) evaluating if a single code written in OpenCL allows us to achieve acceptable performance across all of them, and (2) assessing the gap between our portable OpenCL code and those hand-tuned versions previously investigated. Our study includes the analysis of different tuning techniques that expose data parallelism as well as enable an efficient exploitation of the complex memory hierarchies found in these new heterogeneous devices. Experiments have been conducted using hyperspectral data sets collected by NASA's Airborne Visible Infra- red Imaging Spectrometer (AVIRIS) and the Hyperspectral Digital Imagery Collection Experiment (HYDICE) sensors. To the best of our knowledge, this kind of analysis has not been previously conducted in the hyperspectral imaging processing literature, and in our opinion it is very important in order to really calibrate the possibility of using heterogeneous platforms for efficient hyperspectral imaging processing in real remote sensing missions.
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)
Shrestha, Kalyan; Mompean, Gilmar; Calzavarini, Enrico
2016-02-01
A finite-volume (FV) discretization method for the lattice Boltzmann (LB) equation, which combines high accuracy with limited computational cost is presented. In order to assess the performance of the FV method we carry out a systematic comparison, focused on accuracy and computational performances, with the standard streaming lattice Boltzmann equation algorithm. In particular we aim at clarifying whether and in which conditions the proposed algorithm, and more generally any FV algorithm, can be taken as the method of choice in fluid-dynamics LB simulations. For this reason the comparative analysis is further extended to the case of realistic flows, in particular thermally driven flows in turbulent conditions. We report the successful simulation of high-Rayleigh number convective flow performed by a lattice Boltzmann FV-based algorithm with wall grid refinement.
ERIC Educational Resources Information Center
Clauser, Brian E.; Margolis, Melissa J.; Clyman, Stephen G.; Ross, Linette P.
1997-01-01
Research on automated scoring is extended by comparing alternative automated systems for scoring a computer simulation of physicians' patient management skills. A regression-based system is more highly correlated with experts' evaluations than a system that uses complex rules to map performances into score levels, but both approaches are feasible.…
Analysis of grid performance using an optical flow algorithm for medical image processing
NASA Astrophysics Data System (ADS)
Moreno, Ramon A.; Cunha, Rita de Cássio Porfírio; Gutierrez, Marco A.
2014-03-01
The development of bigger and faster computers has not yet provided the computing power for medical image processing required nowadays. This is the result of several factors, including: i) the increasing number of qualified medical image users requiring sophisticated tools; ii) the demand for more performance and quality of results; iii) researchers are addressing problems that were previously considered extremely difficult to achieve; iv) medical images are produced with higher resolution and on a larger number. These factors lead to the need of exploring computing techniques that can boost the computational power of Healthcare Institutions while maintaining a relative low cost. Parallel computing is one of the approaches that can help solving this problem. Parallel computing can be achieved using multi-core processors, multiple processors, Graphical Processing Units (GPU), clusters or Grids. In order to gain the maximum benefit of parallel computing it is necessary to write specific programs for each environment or divide the data in smaller subsets. In this article we evaluate the performance of the two parallel computing tools when dealing with a medical image processing application. We compared the performance of the EELA-2 (E-science grid facility for Europe and Latin- America) grid infrastructure with a small Cluster (3 nodes x 8 cores = 24 cores) and a regular PC (Intel i3 - 2 cores). As expected the grid had a better performance for a large number of processes, the cluster for a small to medium number of processes and the PC for few processes.
Dupuy, C; Morignat, E; Dorea, F; Ducrot, C; Calavas, D; Gay, E
2015-09-01
The objective of this study was to assess the performance of several algorithms for outbreak detection based on weekly proportions of whole carcass condemnations. Data from one French slaughterhouse over the 2005-2009 period were used (177 098 slaughtered cattle, 0.97% of whole carcass condemnations). The method involved three steps: (i) preparation of an outbreak-free historical baseline over 5 years, (ii) simulation of over 100 years of baseline time series with injection of artificial outbreak signals with several shapes, durations and magnitudes, and (iii) assessment of the performance (sensitivity, specificity, outbreak detection precocity) of several algorithms to detect these artificial outbreak signals. The algorithms tested included the Shewart p chart, confidence interval of the negative binomial model, the exponentially weighted moving average (EWMA); and cumulative sum (CUSUM). The highest sensitivity was obtained using a negative binomial algorithm and the highest specificity with CUSUM or EWMA. EWMA sensitivity was too low to select this algorithm for efficient outbreak detection. CUSUM's performance was complementary to the negative binomial algorithm. The use of both algorithms on real data for a prospective investigation of the whole carcass condemnation rate as a syndromic surveillance indicator could be relevant. Shewart could also be a good option considering its high sensitivity and simplicity of implementation.
NASA Astrophysics Data System (ADS)
Iguchi, Toshio; Seto, Shinta; Awaka, Jun; Meneghini, Robert; Kubota, Takuji; Chandra, V. Chandra; Yoshida, Naofumi; Urita, Shinji; Kwiatkowski, John; Hanado, Hiroshi
2014-05-01
The GPM core satellite is scheduled to be launched on February 28, 2014. This paper will report results of the early performance test of the Dual-Frequency Precipitation Radar (DPR) on the GPM core satellite in orbit. The DPR, which was developed by Japan Aerospace Exploration Agency (JAXA) and National Institute of Information and Communications Technology (NICT), consists of two radars: Ku-band precipitation radar (KuPR, 13.6 GHz) and Ka-band radar (KaPR, 35.5 GHz). KuPR is very similar to TRMM/PR, but its sensitivity is better than PR. The higher sensitivity is realized by the increase of the transmitting power and the increase of the independent samples. A technique of variable pulse repetition frequency (PRF) is used to optimize the sampling window for precipitation echoes and the number of independent samples. KaPR has a high sensitivity mode in order to detect light rain and some snow, which are predominant in high latitudes. The beams of KuPR and KaPR can be matched by adjusting the phase offset to each element of the phased array antenna in the across-track direction and the transmitting time offset between the two radars in the along-track direction. Beam matching is essential for the use of the dual-frequency algorithm to retrieve accurate rainfall rates. The hardware performance of DPR will be checked immediately after the launch. In addition to the basic characteristics of the radar such as the transmitting power, sensitivity, and resolutions, other characteristics peculiar to the DPR such as beam matching will be tested. The performance of the DPR algorithm will be evaluated by comparing the level 2 products with the corresponding TRMM/PR data in statistical ways. Such statistics include not only the radar reflectivity and rain rate histograms, but also precipitation detectability and rain classification.
Fox, Timothy; Huntzinger, Calvin; Johnstone, Peter; Ogunleye, Tomi; Elder, Eric
2006-01-01
Image-guided radiation therapy delivery may be used to assess the position of the tumor and anatomical structures within the body as opposed to relying on external marks. The purpose of this manuscript is to evaluate the performance of the image registration software for automatically detecting and repositioning a 3D offset of a phantom using a kilovoltage onboard imaging system. Verification tests were performed on both a geometric rigid phantom and an anthropomorphic head phantom containing a humanoid skeleton to assess the precision and accuracy of the automated positioning system. From the translation only studies, the average deviation between the detected and known offset was less than 0.75 mm for each of the three principal directions, and the shifts did not show any directional sensitivity. The results are given as the measurement with standard deviation in parentheses. The combined translations and rotations had the greatest average deviation in the lateral, longitudinal, and vertical directions. For all dimensions, the magnitude of the deviation does not appear to be correlated with the magnitude of the actual translation introduced. The On-Board Imager (OBI) system has been successfully integrated into a feasible online radiotherapy treatment guidance procedure. Evaluation of each patient's resulting automatch should be performed by therapists before each treatment session for adequate clinical oversight.
Genetic algorithm to design Laue lenses with optimal performance for focusing hard X- and γ-rays
NASA Astrophysics Data System (ADS)
Camattari, Riccardo; Guidi, Vincenzo
2014-10-01
To focus hard X- and γ-rays it is possible to use a Laue lens as a concentrator. With this optics it is possible to improve the detection of radiation for several applications, from the observation of the most violent phenomena in the sky to nuclear medicine applications for diagnostic and therapeutic purposes. We implemented a code named LaueGen, which is based on a genetic algorithm and aims to design optimized Laue lenses. The genetic algorithm was selected because optimizing a Laue lens is a complex and discretized problem. The output of the code consists of the design of a Laue lens, which is composed of diffracting crystals that are selected and arranged in such a way as to maximize the lens performance. The code allows managing crystals of any material and crystallographic orientation. The program is structured in such a way that the user can control all the initial lens parameters. As a result, LaueGen is highly versatile and can be used to design very small lenses, for example, for nuclear medicine, or very large lenses, for example, for satellite-borne astrophysical missions.
Implementing Legacy-C Algorithms in FPGA Co-Processors for Performance Accelerated Smart Payloads
NASA Technical Reports Server (NTRS)
Pingree, Paula J.; Scharenbroich, Lucas J.; Werne, Thomas A.; Hartzell, Christine
2008-01-01
Accurate, on-board classification of instrument data is used to increase science return by autonomously identifying regions of interest for priority transmission or generating summary products to conserve transmission bandwidth. Due to on-board processing constraints, such classification has been limited to using the simplest functions on a small subset of the full instrument data. FPGA co-processor designs for SVM1 classifiers will lead to significant improvement in on-board classification capability and accuracy.
Clarke, Frank Eldridge; Jones, Blair F.
1972-01-01
Nine ground-water samples from the principal shallow and deep North Sahara aquifers of Algeria and Tunisia were examined to determine the relation of their chemical composition to corrosion and mineral encrustation thought to be contributing to observed decline in well capacities within a UNESCO/UNDP Special Fund Project area. Although the shallow and deep waters differ significantly in certain quality factors, all are sulfochloride types with corrosion potentials ranging from moderate to extreme. None appear to be sufficiently supersaturated with troublesome mineral species to cause rapid or severe encrustation of filter pipes or other well parts. However, calcium carbonate encrustation of deep-well cooling towers and related irrigation pipes can be expected because of loss of carbon dioxide and water during evaporative cooling. Corrosion products, particularly iron sulfide, can be expected to deposit in wells producing waters from the deep aquifers. This could reduce filterpipe openings and increase casing roughness sufficiently to cause significant reduction in well capacity. It seems likely, however, that normal pressure reduction due to exploitation of the artesian systems is a more important control of well performance. If troublesome corrosion and related encrustation are confirmed by downhole inspection, use of corrosion-resisting materials, such as fiber-glass casing and saw-slotted filter pipe (shallow wells only), or stainless-steel screen, will minimize the effects of the waters represented by these samples. A combination of corrosion-resisting stainless steel filter pipe electrically insulated from the casing with a nonconductive spacer and cathodic protection will minimize external corrosion of steel casing, if this is found to be a problem. However, such installations are difficult to make in very deep wells and difficult to control in remote areas. Both the shallow waters and the deep waters examined in this study will tend to cause soil
Performance Evaluation of the Approaches and Algorithms for Hamburg Airport Operations
NASA Technical Reports Server (NTRS)
Zhu, Zhifan; Jung, Yoon; Lee, Hanbong; Schier, Sebastian; Okuniek, Nikolai; Gerdes, Ingrid
2016-01-01
In this work, fast-time simulations have been conducted using SARDA tools at Hamburg airport by NASA and real-time simulations using CADEO and TRACC with the NLR ATM Research Simulator (NARSIM) by DLR. The outputs are analyzed using a set of common metrics collaborated between DLR and NASA. The proposed metrics are derived from International Civil Aviation Organization (ICAO)s Key Performance Areas (KPAs) in capability, efficiency, predictability and environment, and adapted to simulation studies. The results are examined to explore and compare the merits and shortcomings of the two approaches using the common performance metrics. Particular attention is paid to the concept of the close-loop, trajectory-based taxi as well as the application of US concept to the European airport. Both teams consider the trajectory-based surface operation concept a critical technology advance in not only addressing the current surface traffic management problems, but also having potential application in unmanned vehicle maneuver on airport surface, such as autonomous towing or TaxiBot [6][7] and even Remote Piloted Aircraft (RPA). Based on this work, a future integration of TRACC and SOSS is described aiming at bringing conflict-free trajectory-based operation concept to US airport.
Performance Evaluation of the Approaches and Algorithms for Hamburg Airport Operations
NASA Technical Reports Server (NTRS)
Zhu, Zhifan; Okuniek, Nikolai; Gerdes, Ingrid; Schier, Sebastian; Lee, Hanbong; Jung, Yoon
2016-01-01
The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been independently developing and testing their own concepts and tools for airport surface traffic management. Although these concepts and tools have been tested individually for European and US airports, they have never been compared or analyzed side-by-side. This paper presents the collaborative research devoted to the evaluation and analysis of two different surface management concepts. Hamburg Airport was used as a common test bed airport for the study. First, two independent simulations using the same traffic scenario were conducted: one by the DLR team using the Controller Assistance for Departure Optimization (CADEO) and the Taxi Routing for Aircraft: Creation and Controlling (TRACC) in a real-time simulation environment, and one by the NASA team based on the Spot and Runway Departure Advisor (SARDA) in a fast-time simulation environment. A set of common performance metrics was defined. The simulation results showed that both approaches produced operational benefits in efficiency, such as reducing taxi times, while maintaining runway throughput. Both approaches generated the gate pushback schedule to meet the runway schedule, such that the runway utilization was maximized. The conflict-free taxi guidance by TRACC helped avoid taxi conflicts and reduced taxiing stops, but the taxi benefit needed be assessed together with runway throughput to analyze the overall performance objective.
An automatic and fast centerline extraction algorithm for virtual colonoscopy.
Jiang, Guangxiang; Gu, Lixu
2005-01-01
This paper introduces a new refined centerline extraction algorithm, which is based on and significantly improved from distance mapping algorithms. The new approach include three major parts: employing a colon segmentation method; designing and realizing a fast Euclidean Transform algorithm and inducting boundary voxels cutting (BVC) approach. The main contribution is the BVC processing, which greatly speeds up the Dijkstra algorithm and improves the whole performance of the new algorithm. Experimental results demonstrate that the new centerline algorithm was more efficient and accurate comparing with existing algorithms. PMID:17281406
Adams, Mark; Ku, Seung-Hoe; Worley, Patrick H; D'Azevedo, Eduardo; Cummings, Julian; Chang, C S
2009-01-01
Particle-in-cell (PIC) methods have proven to be effective in discretizing the Vlasov-Maxwell system of equations describing the core of toroidal burning plasmas for many decades. Recent physical understanding of the importance of edge physics for stability and transport in tokamaks has lead to development of the rst fully toroidal edge PIC code XGC1. The edge region poses special problems in meshing for PIC methods due to the lack of closed ux surfaces, which makes eld-line following meshes and coordinate systems problematic. We present a solution to this problem with a semi- eld line following mesh method in a cylindrical coordinate system. Additionally, modern supercomputers require highly concurrent algorithms and implementations, with all levels of the memory hierarchy being efficiently utilized to realize optimal code performance. This paper presents a mesh and particle partitioning method, suitable to our meshing strategy, for use on highly concurrent cache-based computing platforms.
NASA Astrophysics Data System (ADS)
Izzuan Jaafar, Hazriq; Mohd Ali, Nursabillilah; Mohamed, Z.; Asmiza Selamat, Nur; Faiz Zainal Abidin, Amar; Jamian, J. J.; Kassim, Anuar Mohamed
2013-12-01
This paper presents development of an optimal PID and PD controllers for controlling the nonlinear gantry crane system. The proposed Binary Particle Swarm Optimization (BPSO) algorithm that uses Priority-based Fitness Scheme is adopted in obtaining five optimal controller gains. The optimal gains are tested on a control structure that combines PID and PD controllers to examine system responses including trolley displacement and payload oscillation. The dynamic model of gantry crane system is derived using Lagrange equation. Simulation is conducted within Matlab environment to verify the performance of system in terms of settling time (Ts), steady state error (SSE) and overshoot (OS). This proposed technique demonstrates that implementation of Priority-based Fitness Scheme in BPSO is effective and able to move the trolley as fast as possible to the various desired position.
NASA Astrophysics Data System (ADS)
Streiter, R.; Wanielik, G.
2013-07-01
The construction of highways and federal roadways is subject to many restrictions and designing rules. The focus is on safety, comfort and smooth driving. Unfortunately, the planning information for roadways and their real constitution, course and their number of lanes and lane widths is often unsure or not available. Due to digital map databases of roads raised much interest during the last years and became one major cornerstone of innovative Advanced Driving Assistance Systems (ADASs), the demand for accurate and detailed road information increases considerably. Within this project a measurement system for collecting high accurate road data was developed. This paper gives an overview about the sensor configuration within the measurement vehicle, introduces the implemented algorithms and shows some applications implemented in the post processing platform. The aim is to recover the origin parametric description of the roadway and the performance of the measurement system is being evaluated against several original road construction information.
A parallel-vector algorithm for rapid structural analysis on high-performance computers
NASA Technical Reports Server (NTRS)
Storaasli, Olaf O.; Nguyen, Duc T.; Agarwal, Tarun K.
1990-01-01
A fast, accurate Choleski method for the solution of symmetric systems of linear equations is presented. This direct method is based on a variable-band storage scheme and takes advantage of column heights to reduce the number of operations in the Choleski factorization. The method employs parallel computation in the outermost DO-loop and vector computation via the loop unrolling technique in the innermost DO-loop. The method avoids computations with zeros outside the column heights, and as an option, zeros inside the band. The close relationship between Choleski and Gauss elimination methods is examined. The minor changes required to convert the Choleski code to a Gauss code to solve non-positive-definite symmetric systems of equations are identified. The results for two large scale structural analyses performed on supercomputers, demonstrate the accuracy and speed of the method.
Piro, M. H. A.; Simunovic, S.
2016-03-17
Several global optimization methods are reviewed that attempt to ensure that the integral Gibbs energy of a closed isothermal isobaric system is a global minimum to satisfy the necessary and sufficient conditions for thermodynamic equilibrium. In particular, the integral Gibbs energy function of a multicomponent system containing non-ideal phases may be highly non-linear and non-convex, which makes finding a global minimum a challenge. Consequently, a poor numerical approach may lead one to the false belief of equilibrium. Furthermore, confirming that one reaches a global minimum and that this is achieved with satisfactory computational performance becomes increasingly more challenging in systemsmore » containing many chemical elements and a correspondingly large number of species and phases. Several numerical methods that have been used for this specific purpose are reviewed with a benchmark study of three of the more promising methods using five case studies of varying complexity. A modification of the conventional Branch and Bound method is presented that is well suited to a wide array of thermodynamic applications, including complex phases with many constituents and sublattices, and ionic phases that must adhere to charge neutrality constraints. Also, a novel method is presented that efficiently solves the system of linear equations that exploits the unique structure of the Hessian matrix, which reduces the calculation from a O(N3) operation to a O(N) operation. As a result, this combined approach demonstrates efficiency, reliability and capabilities that are favorable for integration of thermodynamic computations into multi-physics codes with inherent performance considerations.« less
The Superior Lambert Algorithm
NASA Astrophysics Data System (ADS)
der, G.
2011-09-01
Lambert algorithms are used extensively for initial orbit determination, mission planning, space debris correlation, and missile targeting, just to name a few applications. Due to the significance of the Lambert problem in Astrodynamics, Gauss, Battin, Godal, Lancaster, Gooding, Sun and many others (References 1 to 15) have provided numerous formulations leading to various analytic solutions and iterative methods. Most Lambert algorithms and their computer programs can only work within one revolution, break down or converge slowly when the transfer angle is near zero or 180 degrees, and their multi-revolution limitations are either ignored or barely addressed. Despite claims of robustness, many Lambert algorithms fail without notice, and the users seldom have a clue why. The DerAstrodynamics lambert2 algorithm, which is based on the analytic solution formulated by Sun, works for any number of revolutions and converges rapidly at any transfer angle. It provides significant capability enhancements over every other Lambert algorithm in use today. These include improved speed, accuracy, robustness, and multirevolution capabilities as well as implementation simplicity. Additionally, the lambert2 algorithm provides a powerful tool for solving the angles-only problem without artificial singularities (pointed out by Gooding in Reference 16), which involves 3 lines of sight captured by optical sensors, or systems such as the Air Force Space Surveillance System (AFSSS). The analytic solution is derived from the extended Godal’s time equation by Sun, while the iterative method of solution is that of Laguerre, modified for robustness. The Keplerian solution of a Lambert algorithm can be extended to include the non-Keplerian terms of the Vinti algorithm via a simple targeting technique (References 17 to 19). Accurate analytic non-Keplerian trajectories can be predicted for satellites and ballistic missiles, while performing at least 100 times faster in speed than most
NASA Astrophysics Data System (ADS)
Kim, Kwansu; Kim, Hyungyu; Lee, Joonghyuk; Kim, Seockhyun; Paek, Insu
2016-09-01
A control algorithm for a floating wind turbine installed on a large semi-submersible platform is investigated in this study. The floating wind turbine is different from other typical semi-submersible floating wind turbines in that the platform is so large that the platform motion is not affected by the blade pitch control. For simulation, the hydrodynamic forces data were obtained from ANSYS/AQWA, and implemented to Bladed. For the basic pitch controller, the well-known technique to increase damping by reducing the bandwidth of the controller lower than the platform pitch mode was implemented. Also, to reduce the tower load in the pitch control region, a tower damper based on the nacelle angular acceleration signal was designed. Compared with the results obtained from an onshore wind turbine controller applied to the floating wind turbine, the floating wind turbine controller could reduce the tower moments effectively, however, the standard deviation in power increased significantly.
Dodge, Cristina T; Tamm, Eric P; Cody, Dianna D; Liu, Xinming; Jensen, Corey T; Wei, Wei; Kundra, Vikas; Rong, X John
2016-01-01
The purpose of this study was to characterize image quality and dose performance with GE CT iterative reconstruction techniques, adaptive statistical iterative recontruction (ASiR), and model-based iterative reconstruction (MBIR), over a range of typical to low-dose intervals using the Catphan 600 and the anthropomorphic Kyoto Kagaku abdomen phantoms. The scope of the project was to quantitatively describe the advantages and limitations of these approaches. The Catphan 600 phantom, supplemented with a fat-equivalent oval ring, was scanned using a GE Discovery HD750 scanner at 120 kVp, 0.8 s rotation time, and pitch factors of 0.516, 0.984, and 1.375. The mA was selected for each pitch factor to achieve CTDIvol values of 24, 18, 12, 6, 3, 2, and 1 mGy. Images were reconstructed at 2.5 mm thickness with filtered back-projection (FBP); 20%, 40%, and 70% ASiR; and MBIR. The potential for dose reduction and low-contrast detectability were evaluated from noise and contrast-to-noise ratio (CNR) measurements in the CTP 404 module of the Catphan. Hounsfield units (HUs) of several materials were evaluated from the cylinder inserts in the CTP 404 module, and the modulation transfer function (MTF) was calculated from the air insert. The results were con-firmed in the anthropomorphic Kyoto Kagaku abdomen phantom at 6, 3, 2, and 1mGy. MBIR reduced noise levels five-fold and increased CNR by a factor of five compared to FBP below 6mGy CTDIvol, resulting in a substantial improvement in image quality. Compared to ASiR and FBP, HU in images reconstructed with MBIR were consistently lower, and this discrepancy was reversed by higher pitch factors in some materials. MBIR improved the conspicuity of the high-contrast spatial resolution bar pattern, and MTF quantification confirmed the superior spatial resolution performance of MBIR versus FBP and ASiR at higher dose levels. While ASiR and FBP were relatively insensitive to changes in dose and pitch, the spatial resolution for MBIR
Depeursinge, Adrien; Iavindrasana, Jimison; Hidki, Asmâa; Cohen, Gilles; Geissbuhler, Antoine; Platon, Alexandra; Poletti, Pierre-Alexandre; Müller, Henning
2010-02-01
In this paper, we compare five common classifier families in their ability to categorize six lung tissue patterns in high-resolution computed tomography (HRCT) images of patients affected with interstitial lung diseases (ILD) and with healthy tissue. The evaluated classifiers are naive Bayes, k-nearest neighbor, J48 decision trees, multilayer perceptron, and support vector machines (SVM). The dataset used contains 843 regions of interest (ROI) of healthy and five pathologic lung tissue patterns identified by two radiologists at the University Hospitals of Geneva. Correlation of the feature space composed of 39 texture attributes is studied. A grid search for optimal parameters is carried out for each classifier family. Two complementary metrics are used to characterize the performances of classification. These are based on McNemar's statistical tests and global accuracy. SVM reached best values for each metric and allowed a mean correct prediction rate of 88.3% with high class-specific precision on testing sets of 423 ROIs.
NASA Astrophysics Data System (ADS)
Michel, Dominik; Miralles, Diego; Jimenez, Carlos; Ershadi, Ali; McCabe, Matthew F.; Hirschi, Martin; Seneviratne, Sonia I.; Jung, Martin; Wood, Eric F.; (Bob) Su, Z.; Timmermans, Joris; Chen, Xuelong; Fisher, Joshua B.; Mu, Quiaozen; Fernandez, Diego
2015-04-01
Research on climate variations and the development of predictive capabilities largely rely on globally available reference data series of the different components of the energy and water cycles. Several efforts have recently aimed at producing large-scale and long-term reference data sets of these components, e.g. based on in situ observations and remote sensing, in order to allow for diagnostic analyses of the drivers of temporal variations in the climate system. Evapotranspiration (ET) is an essential component of the energy and water cycle, which cannot be monitored directly on a global scale by remote sensing techniques. In recent years, several global multi-year ET data sets have been derived from remote sensing-based estimates, observation-driven land surface model simulations or atmospheric reanalyses. The LandFlux-EVAL initiative presented an ensemble-evaluation of these data sets over the time periods 1989-1995 and 1989-2005 (Mueller et al. 2013). The WACMOS-ET project (http://wacmoset.estellus.eu) started in the year 2012 and constitutes an ESA contribution to the GEWEX initiative LandFlux. It focuses on advancing the development of ET estimates at global, regional and tower scales. WACMOS-ET aims at developing a Reference Input Data Set exploiting European Earth Observations assets and deriving ET estimates produced by a set of four ET algorithms covering the period 2005-2007. The algorithms used are the SEBS (Su et al., 2002), Penman-Monteith from MODIS (Mu et al., 2011), the Priestley and Taylor JPL model (Fisher et al., 2008) and GLEAM (Miralles et al., 2011). The algorithms are run with Fluxnet tower observations, reanalysis data (ERA-Interim), and satellite forcings. They are cross-compared and validated against in-situ data. In this presentation the performance of the different ET algorithms with respect to different temporal resolutions, hydrological regimes, land cover types (including grassland, cropland, shrubland, vegetation mosaic, savanna
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.
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)
Biazzo, Indaco; Braunstein, Alfredo; Zecchina, Riccardo
2012-08-01
We study the behavior of an algorithm derived from the cavity method for the prize-collecting steiner tree (PCST) problem on graphs. The algorithm is based on the zero temperature limit of the cavity equations and as such is formally simple (a fixed point equation resolved by iteration) and distributed (parallelizable). We provide a detailed comparison with state-of-the-art algorithms on a wide range of existing benchmarks, networks, and random graphs. Specifically, we consider an enhanced derivative of the Goemans-Williamson heuristics and the dhea solver, a branch and cut integer linear programming based approach. The comparison shows that the cavity algorithm outperforms the two algorithms in most large instances both in running time and quality of the solution. Finally we prove a few optimality properties of the solutions provided by our algorithm, including optimality under the two postprocessing procedures defined in the Goemans-Williamson derivative and global optimality in some limit cases.
Biazzo, Indaco; Braunstein, Alfredo; Zecchina, Riccardo
2012-08-01
We study the behavior of an algorithm derived from the cavity method for the prize-collecting steiner tree (PCST) problem on graphs. The algorithm is based on the zero temperature limit of the cavity equations and as such is formally simple (a fixed point equation resolved by iteration) and distributed (parallelizable). We provide a detailed comparison with state-of-the-art algorithms on a wide range of existing benchmarks, networks, and random graphs. Specifically, we consider an enhanced derivative of the Goemans-Williamson heuristics and the dhea solver, a branch and cut integer linear programming based approach. The comparison shows that the cavity algorithm outperforms the two algorithms in most large instances both in running time and quality of the solution. Finally we prove a few optimality properties of the solutions provided by our algorithm, including optimality under the two postprocessing procedures defined in the Goemans-Williamson derivative and global optimality in some limit cases.
ERIC Educational Resources Information Center
Moffitt, Terrie E.; Silva, P. A.
1987-01-01
Examined children whose Wechsler Intelligence Scale for Children-Revised (WISC-R) verbal and performance Intelligence Quotient discrepancies placed them beyond the 90th percentile. Longitudinal study showed 23 percent of the discrepant cases to be discrepant at two or more ages. Studied frequency of perinatal difficulties, early childhood…
ERIC Educational Resources Information Center
Park, Sungho; Singer, George H. S.; Gibson, Mary
2005-01-01
The study uses an alternating treatment design to evaluate the functional effect of teacher's affect on students' task performance. Tradition in special education holds that teachers should engage students using positive and enthusiastic affect for task presentations and praise. To test this assumption, we compared two affective conditions. Three…
ERIC Educational Resources Information Center
Shiotsu, Toshihiko; Weir, Cyril J.
2007-01-01
In the componential approach to modelling reading ability, a number of contributory factors have been empirically validated. However, research on their relative contribution to explaining performance on second language reading tests is limited. Furthermore, the contribution of knowledge of syntax has been largely ignored in comparison with the…
Warshawsky, A.S.; Uzelac, M.J.; Pimper, J.E. )
1989-05-01
The Crew III algorithm for assessing time and dose dependent combat crew performance subsequent to nuclear irradiation was incorporated into the Janus combat simulation system. Battle outcomes using this algorithm were compared to outcomes based on the currently used time-independent cookie-cutter'' assessment methodology. The results illustrate quantifiable differences in battle outcome between the two assessment techniques. Results suggest that tactical nuclear weapons are more effective than currently assumed if performance degradation attributed to radiation doses between 150 to 3000 rad are taken into account. 6 refs., 9 figs.
2013-01-01
Background In a mass casualty situation, medical personnel must rapidly assess and prioritize patients for treatment and transport. Triage is an important tool for medical management in disaster situations. Lack of common international and Swedish triage guidelines could lead to confusion. Attending the Advanced Trauma Life Support (ATLS) provider course is becoming compulsory in the northern part of Europe. The aim of the ATLS guidelines is provision of effective management of single critically injured patients, not mass casualties incidents. However, the use of the ABCDE algorithms from ATLS, has been proposed to be valuable, even in a disaster environment. The objective for this study was to determine whether the mnemonic ABCDE as instructed in the ATLS provider course, affects the ability of Swedish physician’s to correctly triage patients in a simulated mass casualty incident. Methods The study group included 169 ATLS provider students from 10 courses and course sites in Sweden; 153 students filled in an anonymous test just before the course and just after the course. The tests contained 3 questions based on overall priority. The assignment was to triage 15 hypothetical patients who had been involved in a bus crash. Triage was performed according to the ABCDE algorithm. In the triage, the ATLS students used a colour-coded algorithm with red for priority 1, yellow for priority 2, green for priority 3 and black for dead. The students were instructed to identify and prioritize 3 of the most critically injured patients, who should be the first to leave the scene. The same test was used before and after the course. Results The triage section of the test was completed by 142 of the 169 participants both before and after the course. The results indicate that there was no significant difference in triage knowledge among Swedish physicians who attended the ATLS provider course. The results also showed that Swedish physicians have little experience of real mass
Osaka, Itaru; Saito, Masahiko; Koganezawa, Tomoyuki; Takimiya, Kazuo
2014-01-15
The backbone orientation in the thiophene-thiazolothiazole (TzTz) copolymer system can be altered by tuning of the alky side chain composition. We highlight that the orientation significantly impact their solar cell efficiency in particular when using thicker active layers.
Geisler, Matt; Kleczkowski, Leszek A; Karpinski, Stanislaw
2006-02-01
Short motifs of many cis-regulatory elements (CREs) can be found in the promoters of most Arabidopsis genes, and this raises the question of how their presence can confer specific regulation. We developed a universal algorithm to test the biological significance of CREs by first identifying every Arabidopsis gene with a CRE and then statistically correlating the presence or absence of the element with the gene expression profile on multiple DNA microarrays. This algorithm was successfully verified for previously characterized abscisic acid, ethylene, sucrose and drought responsive CREs in Arabidopsis, showing that the presence of these elements indeed correlates with treatment-specific gene induction. Later, we used standard motif sampling methods to identify 128 putative motifs induced by excess light, reactive oxygen species and sucrose. Our algorithm was able to filter 20 out of 128 novel CREs which significantly correlated with gene induction by either heat, reactive oxygen species and/or sucrose. The position, orientation and sequence specificity of CREs was tested in silicio by analyzing the expression of genes with naturally occurring sequence variations. In three novel CREs the forward orientation correlated with sucrose induction and the reverse orientation with sucrose suppression. The functionality of the predicted novel CREs was experimentally confirmed using Arabidopsis cell-suspension cultures transformed with short promoter fragments or artificial promoters fused with the GUS reporter gene. Our genome-wide analysis opens up new possibilities for in silicio verification of the biological significance of newly discovered CREs, and allows for subsequent selection of such CREs for experimental studies.
Andretta, I; Pomar, C; Rivest, J; Pomar, J; Radünz, J
2016-07-01
This study was developed to assess the impact on performance, nutrient balance, serum parameters and feeding costs resulting from the switching of conventional to precision-feeding programs for growing-finishing pigs. A total of 70 pigs (30.4±2.2 kg BW) were used in a performance trial (84 days). The five treatments used in this experiment were a three-phase group-feeding program (control) obtained with fixed blending proportions of feeds A (high nutrient density) and B (low nutrient density); against four individual daily-phase feeding programs in which the blending proportions of feeds A and B were updated daily to meet 110%, 100%, 90% or 80% of the lysine requirements estimated using a mathematical model. Feed intake was recorded automatically by a computerized device in the feeders, and the pigs were weighed weekly during the project. Body composition traits were estimated by scanning with an ultrasound device and densitometer every 28 days. Nitrogen and phosphorus excretions were calculated by the difference between retention (obtained from densitometer measurements) and intake. Feeding costs were assessed using 2013 ingredient cost data. Feed intake, feed efficiency, back fat thickness, body fat mass and serum contents of total protein and phosphorus were similar among treatments. Feeding pigs in a daily-basis program providing 110%, 100% or 90% of the estimated individual lysine requirements also did not influence BW, body protein mass, weight gain and nitrogen retention in comparison with the animals in the group-feeding program. However, feeding pigs individually with diets tailored to match 100% of nutrient requirements made it possible to reduce (P<0.05) digestible lysine intake by 26%, estimated nitrogen excretion by 30% and feeding costs by US$7.60/pig (-10%) relative to group feeding. Precision feeding is an effective approach to make pig production more sustainable without compromising growth performance.
Mark F. Adams; Seung-Hoe Ku; Patrick Worley; Ed D'Azevedo; Julian C. Cummings; C.S. Chang
2009-10-01
Particle-in-cell (PIC) methods have proven to be eft#11;ective in discretizing the Vlasov-Maxwell system of equations describing the core of toroidal burning plasmas for many decades. Recent physical understanding of the importance of edge physics for stability and transport in tokamaks has lead to development of the fi#12;rst fully toroidal edge PIC code - XGC1. The edge region poses special problems in meshing for PIC methods due to the lack of closed flux surfaces, which makes fi#12;eld-line following meshes and coordinate systems problematic. We present a solution to this problem with a semi-#12;field line following mesh method in a cylindrical coordinate system. Additionally, modern supercomputers require highly concurrent algorithms and implementations, with all levels of the memory hierarchy being effe#14;ciently utilized to realize optimal code performance. This paper presents a mesh and particle partitioning method, suitable to our meshing strategy, for use on highly concurrent cache-based computing platforms.
NASA Astrophysics Data System (ADS)
Behr, Yannik; Clinton, John; Cua, Georgia; Cauzzi, Carlo; Heimers, Stefan; Kästli, Philipp; Becker, Jan; Heaton, Thomas
2013-04-01
The Virtual Seismologist (VS) method is a Bayesian approach to regional network-based earthquake early warning (EEW) originally formulated by Cua and Heaton (2007). Implementation of VS into real-time EEW codes has been an on-going effort of the Swiss Seismological Service at ETH Zürich since 2006, with support from ETH Zürich, various European projects, and the United States Geological Survey (USGS). VS is one of three EEW algorithms that form the basis of the California Integrated Seismic Network (CISN) ShakeAlert system, a USGS-funded prototype end-to-end EEW system that could potentially be implemented in California. In Europe, VS is currently operating as a real-time test system in Switzerland. As part of the on-going EU project REAKT (Strategies and Tools for Real-Time Earthquake Risk Reduction), VS installations in southern Italy, western Greece, Istanbul, Romania, and Iceland are planned or underway. In Switzerland, VS has been running in real-time on stations monitored by the Swiss Seismological Service (including stations from Austria, France, Germany, and Italy) since 2010. While originally based on the Earthworm system it has recently been ported to the SeisComp3 system. Besides taking advantage of SeisComp3's picking and phase association capabilities it greatly simplifies the potential installation of VS at networks in particular those already running SeisComp3. We present the architecture of the new SeisComp3 based version and compare its results from off-line tests with the real-time performance of VS in Switzerland over the past two years. We further show that the empirical relationships used by VS to estimate magnitudes and ground motion, originally derived from southern California data, perform well in Switzerland.
Abdullah, Q N; Yam, F K; Hassan, Z; Bououdina, M
2015-12-15
Superior sensitivity towards H2 gas was successfully achieved with Pt-decorated GaN nanowires (NWs) gas sensor. GaN NWs were fabricated via chemical vapor deposition (CVD) route. Morphology (field emission scanning electron microscopy and transmission electron microscopy) and crystal structure (high resolution X-ray diffraction) characterizations of the as-synthesized nanostructures demonstrated the formation of GaN NWs having a wurtzite structure, zigzaged shape and an average diameter of 30-166nm. The Pt-decorated GaN NWs sensor shows a high response of 250-2650% upon exposure to H2 gas concentration from 7 to 1000ppm respectively at room temperature (RT), and then increases to about 650-4100% when increasing the operating temperature up to 75°C. The gas-sensing measurements indicated that the Pt-decorated GaN NWs based sensor exhibited efficient detection of H2 at low concentration with excellent sensitivity, repeatability, and free hysteresis phenomena over a period of time of 100min. The large surface-to-volume ratio of GaN NWs and the catalytic activity of Pt metal are the most influential factors leading to the enhancement of H2 gas-sensing performances through the improvement of the interaction between the target molecules (H2) and the sensing NWs surface. The attractive low-cost, low power consumption and high-performance of the resultant decorated GaN NWs gas sensor assure their uppermost potential for H2 gas sensor working at low operating temperature.
Ojala, Jarkko J; Kapanen, Mika K; Hyödynmaa, Simo J; Wigren, Tuija K; Pitkänen, Maunu A
2014-01-01
The accuracy of dose calculation is a key challenge in stereotactic body radiotherapy (SBRT) of the lung. We have benchmarked three photon beam dose calculation algorithms--pencil beam convolution (PBC), anisotropic analytical algorithm (AAA), and Acuros XB (AXB)--implemented in a commercial treatment planning system (TPS), Varian Eclipse. Dose distributions from full Monte Carlo (MC) simulations were regarded as a reference. In the first stage, for four patients with central lung tumors, treatment plans using 3D conformal radiotherapy (CRT) technique applying 6 MV photon beams were made using the AXB algorithm, with planning criteria according to the Nordic SBRT study group. The plans were recalculated (with same number of monitor units (MUs) and identical field settings) using BEAMnrc and DOSXYZnrc MC codes. The MC-calculated dose distributions were compared to corresponding AXB-calculated dose distributions to assess the accuracy of the AXB algorithm, to which then other TPS algorithms were compared. In the second stage, treatment plans were made for ten patients with 3D CRT technique using both the PBC algorithm and the AAA. The plans were recalculated (with same number of MUs and identical field settings) with the AXB algorithm, then compared to original plans. Throughout the study, the comparisons were made as a function of the size of the planning target volume (PTV), using various dose-volume histogram (DVH) and other parameters to quantitatively assess the plan quality. In the first stage also, 3D gamma analyses with threshold criteria 3%/3mm and 2%/2 mm were applied. The AXB-calculated dose distributions showed relatively high level of agreement in the light of 3D gamma analysis and DVH comparison against the full MC simulation, especially with large PTVs, but, with smaller PTVs, larger discrepancies were found. Gamma agreement index (GAI) values between 95.5% and 99.6% for all the plans with the threshold criteria 3%/3 mm were achieved, but 2%/2 mm
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
Lacasse, M.A.; Margeson, J.C.; Giffin, G.B.
1998-12-31
Standard test methods to assess the degree of movement capability of sealants are currently based on extreme values of amplitude, rate of movement and temperature change. The selection and derivation of these test parameters on the basis of field observations has yet to be fully explained. It appears that these parameters are not based on an understanding of the degree to which sealants undergo cyclic movement on buildings nor the likelihood of occurrence of extreme events. Although joint failure due to cyclic movement has been investigated, there is a need to consider how such models of deterioration can be used to establish test criteria for assessing the long-term performance of sealant products. To address some of these issues, a study was conducted to determine the nature of temperature fluctuations in a northerly climate. Hourly temperature data from the Ottawa international airport for a period of forty years was subjected to probability analysis. The analysis considered the likelihood of occurrence of periods of increasing or decreasing temperature. The occurrence of particular amplitudes ranges and rates of temperature change were also determined on both a seasonal and a yearly basis. Moreover, the annual and multi-year probability of temperature fluctuations at or above extreme values of either rate or amplitude were also assessed. In addition, the maximum and minimum temperatures of the 40 yearly periods were subjected to extremal analysis to determine the likelihood of annual periods covering larger than average temperature ranges. This analysis provides a basis from which to select test parameters.
ERIC Educational Resources Information Center
Harrison, Judith; Thompson, Bruce; Vannest, Kimberly J.
2009-01-01
This article reviews the literature on interventions targeting the academic performance of students with attention-deficit/hyperactivity disorder (ADHD) and does so within the context of the statistical significance testing controversy. Both the arguments for and against null hypothesis statistical significance tests are reviewed. Recent standards…
Jelliffe, Roger W.; Schumitzky, Alan; Bayard, David; Fu, Xiaowei; Neely, Michael
2015-01-01
Background Describing assay error as percent coefficient of variation (CV%) fails as measurements approach zero [1]. Results are censored if below some arbitrarily chosen lower limit of quantification (LLOQ). CV% gives incorrect weighting to data obtained by therapeutic drug monitoring (TDM), with incorrect parameter values in the resulting pharmacokinetic models, and incorrect dosage regimens for patient care. Methods CV% was compared with the reciprocal of the variance (1/var) of each assay measurement. This method [2] has not been considered by the laboratory community. A simple description of assay standard deviation (SD) as a polynomial function of the assay measurement over its working range was developed, the reciprocal of the assay variance determined, and its results compared with CV%. Results CV% does not provide correct weighting of measured serum concentrations as required for optimal TDM. It does not permit optimally individualized models of the behavior of a drug in a patient, resulting in incorrect dosage regimens. The assay error polynomial described here, using 1/var, provides correct weighting of such data, all the way down to and including zero. There is no need to censor low results, and no need to set any arbitrary lower limit of quantification (LLOQ). Conclusion Reciprocal of variance is the correct measure of assay precision, and should replace CV%. The information is easily stored as an assay error polynomial. The laboratory can serve the medical community better. There is no longer any need for LLOQ, a significant improvement. Regulatory agencies should implement this more informed policy. PMID:25970509
Cusella-De Angelis, Maria Gabriella; Laino, Gregorio; Piattelli, Adriano; Pacifici, Maurizio; De Rosa, Alfredo; Papaccio, Gianpaolo
2007-01-01
Background Scaffold surface features are thought to be important regulators of stem cell performance and endurance in tissue engineering applications, but details about these fundamental aspects of stem cell biology remain largely unclear. Methodology and Findings In the present study, smooth clinical-grade lactide-coglyolic acid 85:15 (PLGA) scaffolds were carved as membranes and treated with NMP (N-metil-pyrrolidone) to create controlled subtractive pits or microcavities. Scanning electron and confocal microscopy revealed that the NMP-treated membranes contained: (i) large microcavities of 80–120 µm in diameter and 40–100 µm in depth, which we termed primary; and (ii) smaller microcavities of 10–20 µm in diameter and 3–10 µm in depth located within the primary cavities, which we termed secondary. We asked whether a microcavity-rich scaffold had distinct bone-forming capabilities compared to a smooth one. To do so, mesenchymal stem cells derived from human dental pulp were seeded onto the two types of scaffold and monitored over time for cytoarchitectural characteristics, differentiation status and production of important factors, including bone morphogenetic protein-2 (BMP-2) and vascular endothelial growth factor (VEGF). We found that the microcavity-rich scaffold enhanced cell adhesion: the cells created intimate contact with secondary microcavities and were polarized. These cytological responses were not seen with the smooth-surface scaffold. Moreover, cells on the microcavity-rich scaffold released larger amounts of BMP-2 and VEGF into the culture medium and expressed higher alkaline phosphatase activity. When this type of scaffold was transplanted into rats, superior bone formation was elicited compared to cells seeded on the smooth scaffold. Conclusion In conclusion, surface microcavities appear to support a more vigorous osteogenic response of stem cells and should be used in the design of therapeutic substrates to improve bone repair and
Perrin, Jean-Baptiste; Durand, Benoît; Gay, Emilie; Ducrot, Christian; Hendrikx, Pascal; Calavas, Didier; Hénaux, Viviane
2015-01-01
We performed a simulation study to evaluate the performances of an anomaly detection algorithm considered in the frame of an automated surveillance system of cattle mortality. The method consisted in a combination of temporal regression and spatial cluster detection which allows identifying, for a given week, clusters of spatial units showing an excess of deaths in comparison with their own historical fluctuations. First, we simulated 1,000 outbreaks of a disease causing extra deaths in the French cattle population (about 200,000 herds and 20 million cattle) according to a model mimicking the spreading patterns of an infectious disease and injected these disease-related extra deaths in an authentic mortality dataset, spanning from January 2005 to January 2010. Second, we applied our algorithm on each of the 1,000 semi-synthetic datasets to identify clusters of spatial units showing an excess of deaths considering their own historical fluctuations. Third, we verified if the clusters identified by the algorithm did contain simulated extra deaths in order to evaluate the ability of the algorithm to identify unusual mortality clusters caused by an outbreak. Among the 1,000 simulations, the median duration of simulated outbreaks was 8 weeks, with a median number of 5,627 simulated deaths and 441 infected herds. Within the 12-week trial period, 73% of the simulated outbreaks were detected, with a median timeliness of 1 week, and a mean of 1.4 weeks. The proportion of outbreak weeks flagged by an alarm was 61% (i.e. sensitivity) whereas one in three alarms was a true alarm (i.e. positive predictive value). The performances of the detection algorithm were evaluated for alternative combination of epidemiologic parameters. The results of our study confirmed that in certain conditions automated algorithms could help identifying abnormal cattle mortality increases possibly related to unidentified health events. PMID:26536596
Benchmarking monthly homogenization algorithms
NASA Astrophysics Data System (ADS)
Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratianni, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.
2011-08-01
The COST (European Cooperation in Science and Technology) Action ES0601: Advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies and because they represent two important types of statistics (additive and multiplicative). The algorithms were validated against a realistic benchmark dataset. The benchmark contains real inhomogeneous data as well as simulated data with inserted inhomogeneities. Random break-type inhomogeneities were added to the simulated datasets modeled as a Poisson process with normally distributed breakpoint sizes. To approximate real world conditions, breaks were introduced that occur simultaneously in multiple station series within a simulated network of station data. The simulated time series also contained outliers, missing data periods and local station trends. Further, a stochastic nonlinear global (network-wide) trend was added. Participants provided 25 separate homogenized contributions as part of the blind study as well as 22 additional solutions submitted after the details of the imposed inhomogeneities were revealed. These homogenized datasets were assessed by a number of performance metrics including (i) the centered root mean square error relative to the true homogeneous value at various averaging scales, (ii) the error in linear trend estimates and (iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Contingency scores by themselves are not very informative. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data
Deng, Haishan; Shang, Erxin; Xiang, Bingren; Xie, Shaofei; Tang, Yuping; Duan, Jin-ao; Zhan, Ying; Chi, Yumei; Tan, Defei
2011-03-15
The stochastic resonance algorithm (SRA) has been developed as a potential tool for amplifying and determining weak chromatographic peaks in recent years. However, the conventional SRA cannot be applied directly to ultra-performance liquid chromatography/time-of-flight mass spectrometry (UPLC/TOFMS). The obstacle lies in the fact that the narrow peaks generated by UPLC contain high-frequency components which fall beyond the restrictions of the theory of stochastic resonance. Although there already exists an algorithm that allows a high-frequency weak signal to be detected, the sampling frequency of TOFMS is not fast enough to meet the requirement of the algorithm. Another problem is the depression of the weak peak of the compound with low concentration or weak detection response, which prevents the simultaneous determination of multi-component UPLC/TOFMS peaks. In order to lower the frequencies of the peaks, an interpolation and re-scaling frequency stochastic resonance (IRSR) is proposed, which re-scales the peak frequencies via linear interpolating sample points numerically. The re-scaled UPLC/TOFMS peaks could then be amplified significantly. By introducing an external energy field upon the UPLC/TOFMS signals, the method of energy gain was developed to simultaneously amplify and determine weak peaks from multi-components. Subsequently, a multi-component stochastic resonance algorithm was constructed for the simultaneous quantitative determination of multiple weak UPLC/TOFMS peaks based on the two methods. The optimization of parameters was discussed in detail with simulated data sets, and the applicability of the algorithm was evaluated by quantitative analysis of three alkaloids in human plasma using UPLC/TOFMS. The new algorithm behaved well in the improvement of signal-to-noise (S/N) compared to several normally used peak enhancement methods, including the Savitzky-Golay filter, Whittaker-Eilers smoother and matched filtration.
Performance evaluation and optimization of BM4D-AV denoising algorithm for cone-beam CT images
NASA Astrophysics Data System (ADS)
Huang, Kuidong; Tian, Xiaofei; Zhang, Dinghua; Zhang, Hua
2015-12-01
The broadening application of cone-beam Computed Tomography (CBCT) in medical diagnostics and nondestructive testing, necessitates advanced denoising algorithms for its 3D images. The block-matching and four dimensional filtering algorithm with adaptive variance (BM4D-AV) is applied to the 3D image denoising in this research. To optimize it, the key filtering parameters of the BM4D-AV algorithm are assessed firstly based on the simulated CBCT images and a table of optimized filtering parameters is obtained. Then, considering the complexity of the noise in realistic CBCT images, possible noise standard deviations in BM4D-AV are evaluated to attain the chosen principle for the realistic denoising. The results of corresponding experiments demonstrate that the BM4D-AV algorithm with optimized parameters presents excellent denosing effect on the realistic 3D CBCT images.
Im, Piljae; Munk, Jeffrey D; Gehl, Anthony C
2015-06-01
A research project “Evaluation of Variable Refrigerant Flow (VRF) Systems Performance and the Enhanced Control Algorithm on Oak Ridge National Laboratory’s (ORNL’s) Flexible Research Platform” was performed to (1) install and validate the performance of Samsung VRF systems compared with the baseline rooftop unit (RTU) variable-air-volume (VAV) system and (2) evaluate the enhanced control algorithm for the VRF system on the two-story flexible research platform (FRP) in Oak Ridge, Tennessee. Based on the VRF system designed by Samsung and ORNL, the system was installed from February 18 through April 15, 2014. The final commissioning and system optimization were completed on June 2, 2014, and the initial test for system operation was started the following day, June 3, 2014. In addition, the enhanced control algorithm was implemented and updated on June 18. After a series of additional commissioning actions, the energy performance data from the RTU and the VRF system were monitored from July 7, 2014, through February 28, 2015. Data monitoring and analysis were performed for the cooling season and heating season separately, and the calibrated simulation model was developed and used to estimate the energy performance of the RTU and VRF systems. This final report includes discussion of the design and installation of the VRF system, the data monitoring and analysis plan, the cooling season and heating season data analysis, and the building energy modeling study
Bowen, J.; Dozier, G.
1996-12-31
This paper introduces a hybrid evolutionary hill-climbing algorithm that quickly solves (Constraint Satisfaction Problems (CSPs)). This hybrid uses opportunistic arc and path revision in an interleaved fashion to reduce the size of the search space and to realize when to quit if a CSP is based on an inconsistent constraint network. This hybrid outperforms a well known hill-climbing algorithm, the Iterative Descent Method, on a test suite of 750 randomly generated CSPs.
Pronk, Sander; Pouya, Iman; Lundborg, Magnus; Rotskoff, Grant; Wesén, Björn; Kasson, Peter M; Lindahl, Erik
2015-06-01
Computational chemistry and other simulation fields are critically dependent on computing resources, but few problems scale efficiently to the hundreds of thousands of processors available in current supercomputers-particularly for molecular dynamics. This has turned into a bottleneck as new hardware generations primarily provide more processing units rather than making individual units much faster, which simulation applications are addressing by increasingly focusing on sampling with algorithms such as free-energy perturbation, Markov state modeling, metadynamics, or milestoning. All these rely on combining results from multiple simulations into a single observation. They are potentially powerful approaches that aim to predict experimental observables directly, but this comes at the expense of added complexity in selecting sampling strategies and keeping track of dozens to thousands of simulations and their dependencies. Here, we describe how the distributed execution framework Copernicus allows the expression of such algorithms in generic workflows: dataflow programs. Because dataflow algorithms explicitly state dependencies of each constituent part, algorithms only need to be described on conceptual level, after which the execution is maximally parallel. The fully automated execution facilitates the optimization of these algorithms with adaptive sampling, where undersampled regions are automatically detected and targeted without user intervention. We show how several such algorithms can be formulated for computational chemistry problems, and how they are executed efficiently with many loosely coupled simulations using either distributed or parallel resources with Copernicus. PMID:26575558
Pronk, Sander; Pouya, Iman; Lundborg, Magnus; Rotskoff, Grant; Wesén, Björn; Kasson, Peter M; Lindahl, Erik
2015-06-01
Computational chemistry and other simulation fields are critically dependent on computing resources, but few problems scale efficiently to the hundreds of thousands of processors available in current supercomputers-particularly for molecular dynamics. This has turned into a bottleneck as new hardware generations primarily provide more processing units rather than making individual units much faster, which simulation applications are addressing by increasingly focusing on sampling with algorithms such as free-energy perturbation, Markov state modeling, metadynamics, or milestoning. All these rely on combining results from multiple simulations into a single observation. They are potentially powerful approaches that aim to predict experimental observables directly, but this comes at the expense of added complexity in selecting sampling strategies and keeping track of dozens to thousands of simulations and their dependencies. Here, we describe how the distributed execution framework Copernicus allows the expression of such algorithms in generic workflows: dataflow programs. Because dataflow algorithms explicitly state dependencies of each constituent part, algorithms only need to be described on conceptual level, after which the execution is maximally parallel. The fully automated execution facilitates the optimization of these algorithms with adaptive sampling, where undersampled regions are automatically detected and targeted without user intervention. We show how several such algorithms can be formulated for computational chemistry problems, and how they are executed efficiently with many loosely coupled simulations using either distributed or parallel resources with Copernicus.
Automatic control algorithm effects on energy production
NASA Technical Reports Server (NTRS)
Mcnerney, G. M.
1981-01-01
A computer model was developed using actual wind time series and turbine performance data to simulate the power produced by the Sandia 17-m VAWT operating in automatic control. The model was used to investigate the influence of starting algorithms on annual energy production. The results indicate that, depending on turbine and local wind characteristics, a bad choice of a control algorithm can significantly reduce overall energy production. The model can be used to select control algorithms and threshold parameters that maximize long term energy production. The results from local site and turbine characteristics were generalized to obtain general guidelines for control algorithm design.
NASA Astrophysics Data System (ADS)
Primorac, E.; Kuhlenbeck, H.; Freund, H.-J.
2016-07-01
The structure of a thin MoO3 layer on Au(111) with a c(4 × 2) superstructure was studied with LEED I/V analysis. As proposed previously (Quek et al., Surf. Sci. 577 (2005) L71), the atomic structure of the layer is similar to that of a MoO3 single layer as found in regular α-MoO3. The layer on Au(111) has a glide plane parallel to the short unit vector of the c(4 × 2) unit cell and the molybdenum atoms are bridge-bonded to two surface gold atoms with the structure of the gold surface being slightly distorted. The structural refinement of the structure was performed with the CMA-ES evolutionary strategy algorithm which could reach a Pendry R-factor of ∼ 0.044. In the second part the performance of CMA-ES is compared with that of the differential evolution method, a genetic algorithm and the Powell optimization algorithm employing I/V curves calculated with tensor LEED.
Samei, Ehsan; Richard, Samuel
2015-01-15
Purpose: Different computed tomography (CT) reconstruction techniques offer different image quality attributes of resolution and noise, challenging the ability to compare their dose reduction potential against each other. The purpose of this study was to evaluate and compare the task-based imaging performance of CT systems to enable the assessment of the dose performance of a model-based iterative reconstruction (MBIR) to that of an adaptive statistical iterative reconstruction (ASIR) and a filtered back projection (FBP) technique. Methods: The ACR CT phantom (model 464) was imaged across a wide range of mA setting on a 64-slice CT scanner (GE Discovery CT750 HD, Waukesha, WI). Based on previous work, the resolution was evaluated in terms of a task-based modulation transfer function (MTF) using a circular-edge technique and images from the contrast inserts located in the ACR phantom. Noise performance was assessed in terms of the noise-power spectrum (NPS) measured from the uniform section of the phantom. The task-based MTF and NPS were combined with a task function to yield a task-based estimate of imaging performance, the detectability index (d′). The detectability index was computed as a function of dose for two imaging tasks corresponding to the detection of a relatively small and a relatively large feature (1.5 and 25 mm, respectively). The performance of MBIR in terms of the d′ was compared with that of ASIR and FBP to assess its dose reduction potential. Results: Results indicated that MBIR exhibits a variability spatial resolution with respect to object contrast and noise while significantly reducing image noise. The NPS measurements for MBIR indicated a noise texture with a low-pass quality compared to the typical midpass noise found in FBP-based CT images. At comparable dose, the d′ for MBIR was higher than those of FBP and ASIR by at least 61% and 19% for the small feature and the large feature tasks, respectively. Compared to FBP and ASIR, MBIR
NASA Astrophysics Data System (ADS)
Laban, Shaban; El-Desouky, Aly
2013-04-01
Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). The CLIPS expert system shell has been used as the main rule engine for implementing the algorithm rules. Python programming language and the module "PyCLIPS" are used for building the necessary code for algorithm implementation. More than 1.7 million intervals constitute the Concise List of Frames (CLF) from 20 different seismic stations have been used for evaluating the proposed algorithm and evaluating stations behaviour and performance. The initial results showed that proposed algorithm can help in better understanding of the operation and performance of those stations. Different important information, such as alerts and some station performance parameters, can be derived from the proposed algorithm. For IMS interval-based data and at any period of time it is possible to analyze station behavior, determine the missing data, generate necessary alerts, and to measure some of station performance attributes. The details of the proposed algorithm, methodology, implementation, experimental results, advantages, and limitations of this research are presented. Finally, future directions and recommendations are discussed.
NASA Astrophysics Data System (ADS)
Wang, L.; Wang, T. G.; Wu, J. H.; Cheng, G. P.
2016-09-01
A novel multi-objective optimization algorithm incorporating evolution strategies and vector mechanisms, referred as VD-MOEA, is proposed and applied in aerodynamic- structural integrated design of wind turbine blade. In the algorithm, a set of uniformly distributed vectors is constructed to guide population in moving forward to the Pareto front rapidly and maintain population diversity with high efficiency. For example, two- and three- objective designs of 1.5MW wind turbine blade are subsequently carried out for the optimization objectives of maximum annual energy production, minimum blade mass, and minimum extreme root thrust. The results show that the Pareto optimal solutions can be obtained in one single simulation run and uniformly distributed in the objective space, maximally maintaining the population diversity. In comparison to conventional evolution algorithms, VD-MOEA displays dramatic improvement of algorithm performance in both convergence and diversity preservation for handling complex problems of multi-variables, multi-objectives and multi-constraints. This provides a reliable high-performance optimization approach for the aerodynamic-structural integrated design of wind turbine blade.
ERIC Educational Resources Information Center
Gilger, J. W.; Geary, D. C.
1985-01-01
Compared the performance of 56 children on the 11 subscales of the Luria-Nebraska Neuropsychological Battery-Children's Revision. Results revealed significant differences on Receptive Speech and Expressive Language subscales, suggesting a possible differential sensitivity of the children's Luria-Nebraska to verbal and nonverbal cognitive deficits.…
ERIC Educational Resources Information Center
Robertson, Alexander M.; Willett, Peter
1996-01-01
Describes a genetic algorithm (GA) that assigns weights to query terms in a ranked-output document retrieval system. Experiments showed the GA often found weights slightly superior to those produced by deterministic weighting (F4). Many times, however, the two methods gave the same results and sometimes the F4 results were superior, indicating…
Offline Performance of the Filter Bank EEW Algorithm in the 2014 M6.0 South Napa Earthquake
NASA Astrophysics Data System (ADS)
Meier, M. A.; Heaton, T. H.; Clinton, J. F.
2014-12-01
Medium size events like the M6.0 South Napa earthquake are very challenging for EEW: the damage such events produce can be severe, but it is generally confined to relatively small zones around the epicenter and the shaking duration is short. This leaves a very short window for timely EEW alerts. Algorithms that wait for several stations to trigger before sending out EEW alerts are typically not fast enough for these kind of events because their blind zone (the zone where strong ground motions start before the warnings arrive) typically covers all or most of the area that experiences strong ground motions. At the same time, single station algorithms are often too unreliable to provide useful alerts. The filter bank EEW algorithm is a new algorithm that is designed to provide maximally accurate and precise earthquake parameter estimates with minimum data input, with the goal of producing reliable EEW alerts when only a very small number of stations have been reached by the p-wave. It combines the strengths of single station and network based algorithms in that it starts parameter estimates as soon as 0.5 seconds of data are available from the first station, but then perpetually incorporates additional data from the same or from any number of other stations. The algorithm analyzes the time dependent frequency content of real time waveforms with a filter bank. It then uses an extensive training data set to find earthquake records from the past that have had similar frequency content at a given time since the p-wave onset. The source parameters of the most similar events are used to parameterize a likelihood function for the source parameters of the ongoing event, which can then be maximized to find the most likely parameter estimates. Our preliminary results show that the filter bank EEW algorithm correctly estimated the magnitude of the South Napa earthquake to be ~M6 with only 1 second worth of data at the nearest station to the epicenter. This estimate is then
Passive microwave algorithm development and evaluation
NASA Technical Reports Server (NTRS)
Petty, Grant W.
1995-01-01
The scientific objectives of this grant are: (1) thoroughly evaluate, both theoretically and empirically, all available Special Sensor Microwave Imager (SSM/I) retrieval algorithms for column water vapor, column liquid water, and surface wind speed; (2) where both appropriate and feasible, develop, validate, and document satellite passive microwave retrieval algorithms that offer significantly improved performance compared with currently available algorithms; and (3) refine and validate a novel physical inversion scheme for retrieving rain rate over the ocean. This report summarizes work accomplished or in progress during the first year of a three year grant. The emphasis during the first year has been on the validation and refinement of the rain rate algorithm published by Petty and on the analysis of independent data sets that can be used to help evaluate the performance of rain rate algorithms over remote areas of the ocean. Two articles in the area of global oceanic precipitation are attached.
Sampling Within k-Means Algorithm to Cluster Large Datasets
Bejarano, Jeremy; Bose, Koushiki; Brannan, Tyler; Thomas, Anita; Adragni, Kofi; Neerchal, Nagaraj; Ostrouchov, George
2011-08-01
Due to current data collection technology, our ability to gather data has surpassed our ability to analyze it. In particular, k-means, one of the simplest and fastest clustering algorithms, is ill-equipped to handle extremely large datasets on even the most powerful machines. Our new algorithm uses a sample from a dataset to decrease runtime by reducing the amount of data analyzed. We perform a simulation study to compare our sampling based k-means to the standard k-means algorithm by analyzing both the speed and accuracy of the two methods. Results show that our algorithm is significantly more efficient than the existing algorithm with comparable accuracy. Further work on this project might include a more comprehensive study both on more varied test datasets as well as on real weather datasets. This is especially important considering that this preliminary study was performed on rather tame datasets. Also, these datasets should analyze the performance of the algorithm on varied values of k. Lastly, this paper showed that the algorithm was accurate for relatively low sample sizes. We would like to analyze this further to see how accurate the algorithm is for even lower sample sizes. We could find the lowest sample sizes, by manipulating width and confidence level, for which the algorithm would be acceptably accurate. In order for our algorithm to be a success, it needs to meet two benchmarks: match the accuracy of the standard k-means algorithm and significantly reduce runtime. Both goals are accomplished for all six datasets analyzed. However, on datasets of three and four dimension, as the data becomes more difficult to cluster, both algorithms fail to obtain the correct classifications on some trials. Nevertheless, our algorithm consistently matches the performance of the standard algorithm while becoming remarkably more efficient with time. Therefore, we conclude that analysts can use our algorithm, expecting accurate results in considerably less time.
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.
NASA Astrophysics Data System (ADS)
Yousfi, L.; Mansouri, N.
2008-06-01
The aim of this paper is the identification of the parameters in systems modeled by nonlinear differential equations. The proposed method is based on Genetic algorithms with domain's reduction and transformation strategies. The studied problems are successively solved using transformation technique, domain's reduction and a combination of the two strategies. The results obtained, using all these methods are comparables. The good results obtained by transformation seem to be related to the great degree of diversity that the mechanism introduces in population.
Chang, Yao-Tang; Wu, Chi-Lin; Cheng, Hsu-Chih
2014-01-01
The rapid development of wireless broadband communication technology has affected the location accuracy of worldwide radio monitoring stations that employ time-difference-of-arrival (TDOA) location technology. In this study, TDOA-based location technology was implemented in Taiwan for the first time according to International Telecommunications Union Radiocommunication (ITU-R) recommendations regarding monitoring and location applications. To improve location accuracy, various scenarios, such as a three-dimensional environment (considering an unequal locating antenna configuration), were investigated. Subsequently, the proposed integrated cross-correlation and genetic algorithm was evaluated in the metropolitan area of Tainan. The results indicated that the location accuracy at a circular error probability of 50% was less than 60 m when a multipath effect was present in the area. Moreover, compared with hyperbolic algorithms that have been applied in conventional TDOA-based location systems, the proposed algorithm yielded 17-fold and 19-fold improvements in the mean difference when the location position of the interference station was favorable and unfavorable, respectively. Hence, the various forms of radio interference, such as low transmission power, burst and weak signals, and metropolitan interference, was proved to be easily identified, located, and removed. PMID:24763254
Chang, Yao-Tang; Wu, Chi-Lin; Cheng, Hsu-Chih
2014-01-01
The rapid development of wireless broadband communication technology has affected the location accuracy of worldwide radio monitoring stations that employ time-difference-of-arrival (TDOA) location technology. In this study, TDOA-based location technology was implemented in Taiwan for the first time according to International Telecommunications Union Radiocommunication (ITU-R) recommendations regarding monitoring and location applications. To improve location accuracy, various scenarios, such as a three-dimensional environment (considering an unequal locating antenna configuration), were investigated. Subsequently, the proposed integrated cross-correlation and genetic algorithm was evaluated in the metropolitan area of Tainan. The results indicated that the location accuracy at a circular error probability of 50% was less than 60 m when a multipath effect was present in the area. Moreover, compared with hyperbolic algorithms that have been applied in conventional TDOA-based location systems, the proposed algorithm yielded 17-fold and 19-fold improvements in the mean difference when the location position of the interference station was favorable and unfavorable, respectively. Hence, the various forms of radio interference, such as low transmission power, burst and weak signals, and metropolitan interference, was proved to be easily identified, located, and removed. PMID:24763254
Inference from matrix products: a heuristic spin glass algorithm
Hastings, Matthew B
2008-01-01
We present an algorithm for finding ground states of two-dimensional spin-glass systems based on ideas from matrix product states in quantum information theory. The algorithm works directly at zero temperature and defines an approximation to the energy whose accuracy depends on a parameter k. We test the algorithm against exact methods on random field and random bond Ising models, and we find that accurate results require a k which scales roughly polynomially with the system size. The algorithm also performs well when tested on small systems with arbitrary interactions, where no fast, exact algorithms exist. The time required is significantly less than Monte Carlo schemes.
[An Algorithm for Correcting Fetal Heart Rate Baseline].
Li, Xiaodong; Lu, Yaosheng
2015-10-01
Fetal heart rate (FHR) baseline estimation is of significance for the computerized analysis of fetal heart rate and the assessment of fetal state. In our work, a fetal heart rate baseline correction algorithm was presented to make the existing baseline more accurate and fit to the tracings. Firstly, the deviation of the existing FHR baseline was found and corrected. And then a new baseline was obtained finally after treatment with some smoothing methods. To assess the performance of FHR baseline correction algorithm, a new FHR baseline estimation algorithm that combined baseline estimation algorithm and the baseline correction algorithm was compared with two existing FHR baseline estimation algorithms. The results showed that the new FHR baseline estimation algorithm did well in both accuracy and efficiency. And the results also proved the effectiveness of the FHR baseline correction algorithm.
Reasoning about systolic algorithms
Purushothaman, S.
1986-01-01
Systolic algorithms are a class of parallel algorithms, with small grain concurrency, well suited for implementation in VLSI. They are intended to be implemented as high-performance, computation-bound back-end processors and are characterized by a tesselating interconnection of identical processing elements. This dissertation investigates the problem of providing correctness of systolic algorithms. The following are reported in this dissertation: (1) a methodology for verifying correctness of systolic algorithms based on solving the representation of an algorithm as recurrence equations. The methodology is demonstrated by proving the correctness of a systolic architecture for optimal parenthesization. (2) The implementation of mechanical proofs of correctness of two systolic algorithms, a convolution algorithm and an optimal parenthesization algorithm, using the Boyer-Moore theorem prover. (3) An induction principle for proving correctness of systolic arrays which are modular. Two attendant inference rules, weak equivalence and shift transformation, which capture equivalent behavior of systolic arrays, are also presented.
Alan Black; Arnis Judzis
2005-09-30
This document details the progress to date on the OPTIMIZATION OF DEEP DRILLING PERFORMANCE--DEVELOPMENT AND BENCHMARK TESTING OF ADVANCED DIAMOND PRODUCT DRILL BITS AND HP/HT FLUIDS TO SIGNIFICANTLY IMPROVE RATES OF PENETRATION contract for the year starting October 2004 through September 2005. The industry cost shared program aims to benchmark drilling rates of penetration in selected simulated deep formations and to significantly improve ROP through a team development of aggressive diamond product drill bit--fluid system technologies. Overall the objectives are as follows: Phase 1--Benchmark ''best in class'' diamond and other product drilling bits and fluids and develop concepts for a next level of deep drilling performance; Phase 2--Develop advanced smart bit-fluid prototypes and test at large scale; and Phase 3--Field trial smart bit--fluid concepts, modify as necessary and commercialize products. As of report date, TerraTek has concluded all Phase 1 testing and is planning Phase 2 development.
NASA Astrophysics Data System (ADS)
Nechad, B.; Ruddick, K.; Schroeder, T.; Oubelkheir, K.; Blondeau-Patissier, D.; Cherukuru, N.; Brando, V.; Dekker, A.; Clementson, L.; Banks, A. C.; Maritorena, S.; Werdell, J.; Sá, C.; Brotas, V.; Caballero de Frutos, I.; Ahn, Y.-H.; Salama, S.; Tilstone, G.; Martinez-Vicente, V.; Foley, D.; McKibben, M.; Nahorniak, J.; Peterson, T.; Siliò-Calzada, A.; Röttgers, R.; Lee, Z.; Peters, M.; Brockmann, C.
2015-02-01
The use of in situ measurements is essential in the validation and evaluation of the algorithms that provide coastal water quality data products from ocean colour satellite remote sensing. Over the past decade, various types of ocean colour algorithms have been developed to deal with the optical complexity of coastal waters. Yet there is a lack of a comprehensive inter-comparison due to the availability of quality checked in situ databases. The CoastColour project Round Robin (CCRR) project funded by the European Space Agency (ESA) was designed to bring together a variety of reference datasets and to use these to test algorithms and assess their accuracy for retrieving water quality parameters. This information was then developed to help end-users of remote sensing products to select the most accurate algorithms for their coastal region. To facilitate this, an inter-comparison of the performance of algorithms for the retrieval of in-water properties over coastal waters was carried out. The comparison used three types of datasets on which ocean colour algorithms were tested. The description and comparison of the three datasets are the focus of this paper, and include the Medium Resolution Imaging Spectrometer (MERIS) Level 2 match-ups, in situ reflectance measurements and data generated by a radiative transfer model (HydroLight). These datasets are available from doi.pangaea.de/10.1594/PANGAEA.841950. The datasets mainly consisted of 6484 marine reflectance associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: Total Suspended Matter (TSM) and Chlorophyll a (CHL) concentrations, and the absorption of Coloured Dissolved Organic Matter (CDOM). Inherent optical properties were also provided in the simulated datasets (5000 simulations) and from 3054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL
Hu, Jia; Erdogan, Berrin; Bauer, Talya N; Jiang, Kaifeng; Liu, Songbo; Li, Yuhui
2015-07-01
Research has uncovered mixed results regarding the influence of overqualification on employee performance outcomes, suggesting the existence of boundary conditions for such an influence. Using relative deprivation theory (Crosby, 1976) as the primary theoretical basis, in the current research, we examine the moderating role of peer overqualification and provide insights to the questions regarding whether, when, and how overqualification relates to employee performance. We tested the theoretical model with data gathered across three phases over 6 months from 351 individuals and their supervisors in 72 groups. Results showed that when working with peers whose average overqualification level was high, as opposed to low, employees who felt overqualified for their jobs perceived greater task significance and person-group fit, and demonstrated higher levels of in-role and extra-role performance. We discuss theoretical and managerial implications for overqualification at the individual level and within the larger group context.
NASA Astrophysics Data System (ADS)
Malobabic, M.; Buttschardt, W.; Rautenberg, M.
The paper presents a theoretical derivation of the relationship between a variable geometry turbocharger and the combustion engine, using simplified boundary conditions and model restraints and taking into account the combustion process itself as well as the nonadiabatic operating conditions for the turbine and the compressor. The simulation algorithm is described, and the results computed using this algorithm are compared with measurements performed on a test engine in combination with a controllable turbocharger with adjustable turbine inlet guide vanes. In addition, the results of theoretical parameter studies are presented, which include the simulation of a given turbocharger with variable geometry in combination with different sized combustion engines and the simulation of different sized variable-geometry turbochargers in combination with a given combustion engine.
Bello, Katrina D; Goharpey, Nahal; Crewther, Sheila G; Crewther, David P
2008-01-01
Background Assessment of 'potential intellectual ability' of children with severe intellectual disability (ID) is limited, as current tests designed for normal children do not maintain their interest. Thus a manual puzzle version of the Raven's Coloured Progressive Matrices (RCPM) was devised to appeal to the attentional and sensory preferences and language limitations of children with ID. It was hypothesized that performance on the book and manual puzzle forms would not differ for typically developing children but that children with ID would perform better on the puzzle form. Methods The first study assessed the validity of this puzzle form of the RCPM for 76 typically developing children in a test-retest crossover design, with a 3 week interval between tests. A second study tested performance and completion rate for the puzzle form compared to the book form in a sample of 164 children with ID. Results In the first study, no significant difference was found between performance on the puzzle and book forms in typically developing children, irrespective of the order of completion. The second study demonstrated a significantly higher performance and completion rate for the puzzle form compared to the book form in the ID population. Conclusion Similar performance on book and puzzle forms of the RCPM by typically developing children suggests that both forms measure the same construct. These findings suggest that the puzzle form does not require greater cognitive ability but demands sensory-motor attention and limits distraction in children with severe ID. Thus, we suggest the puzzle form of the RCPM is a more reliable measure of the non-verbal mentation of children with severe ID than the book form. PMID:18671882
NASA Astrophysics Data System (ADS)
Jaenisch, Holger; Handley, James
2013-06-01
We introduce a generalized numerical prediction and forecasting algorithm. We have previously published it for malware byte sequence feature prediction and generalized distribution modeling for disparate test article analysis. We show how non-trivial non-periodic extrapolation of a numerical sequence (forecast and backcast) from the starting data is possible. Our ancestor-progeny prediction can yield new options for evolutionary programming. Our equations enable analytical integrals and derivatives to any order. Interpolation is controllable from smooth continuous to fractal structure estimation. We show how our generalized trigonometric polynomial can be derived using a Fourier transform.
Statistically significant relational data mining :
Berry, Jonathan W.; Leung, Vitus Joseph; Phillips, Cynthia Ann; Pinar, Ali; Robinson, David Gerald; Berger-Wolf, Tanya; Bhowmick, Sanjukta; Casleton, Emily; Kaiser, Mark; Nordman, Daniel J.; Wilson, Alyson G.
2014-02-01
This report summarizes the work performed under the project (3z(BStatitically significant relational data mining.(3y (BThe goal of the project was to add more statistical rigor to the fairly ad hoc area of data mining on graphs. Our goal was to develop better algorithms and better ways to evaluate algorithm quality. We concetrated on algorithms for community detection, approximate pattern matching, and graph similarity measures. Approximate pattern matching involves finding an instance of a relatively small pattern, expressed with tolerance, in a large graph of data observed with uncertainty. This report gathers the abstracts and references for the eight refereed publications that have appeared as part of this work. We then archive three pieces of research that have not yet been published. The first is theoretical and experimental evidence that a popular statistical measure for comparison of community assignments favors over-resolved communities over approximations to a ground truth. The second are statistically motivated methods for measuring the quality of an approximate match of a small pattern in a large graph. The third is a new probabilistic random graph model. Statisticians favor these models for graph analysis. The new local structure graph model overcomes some of the issues with popular models such as exponential random graph models and latent variable models.
NASA Astrophysics Data System (ADS)
Won, Jihye; Park, Kwan-Dong
2015-04-01
Real-time PPP-RTK positioning algorithms were developed for the purpose of getting precise coordinates of moving platforms. In this implementation, corrections for the satellite orbit and satellite clock were taken from the IGS-RTS products while the ionospheric delay was removed through ionosphere-free combination and the tropospheric delay was either taken care of using the Global Pressure and Temperature (GPT) model or estimated as a stochastic parameter. To improve the convergence speed, all the available GPS and GLONASS measurements were used and Extended Kalman Filter parameters were optimized. To validate our algorithms, we collected the GPS and GLONASS data from a geodetic-quality receiver installed on a roof of a moving vehicle in an open-sky environment and used IGS final products of satellite orbits and clock offsets. The horizontal positioning error got less than 10 cm within 5 minutes, and the error stayed below 10 cm even after the vehicle start moving. When the IGS-RTS product and the GPT model were used instead of the IGS precise product, the positioning accuracy of the moving vehicle was maintained at better than 20 cm once convergence was achieved at around 6 minutes.
Annealed Importance Sampling Reversible Jump MCMC algorithms
Karagiannis, Georgios; Andrieu, Christophe
2013-03-20
It will soon be 20 years since reversible jump Markov chain Monte Carlo (RJ-MCMC) algorithms have been proposed. They have significantly extended the scope of Markov chain Monte Carlo simulation methods, offering the promise to be able to routinely tackle transdimensional sampling problems, as encountered in Bayesian model selection problems for example, in a principled and flexible fashion. Their practical efficient implementation, however, still remains a challenge. A particular difficulty encountered in practice is in the choice of the dimension matching variables (both their nature and their distribution) and the reversible transformations which allow one to define the one-to-one mappings underpinning the design of these algorithms. Indeed, even seemingly sensible choices can lead to algorithms with very poor performance. The focus of this paper is the development and performance evaluation of a method, annealed importance sampling RJ-MCMC (aisRJ), which addresses this problem by mitigating the sensitivity of RJ-MCMC algorithms to the aforementioned poor design. As we shall see the algorithm can be understood as being an “exact approximation” of an idealized MCMC algorithm that would sample from the model probabilities directly in a model selection set-up. Such an idealized algorithm may have good theoretical convergence properties, but typically cannot be implemented, and our algorithms can approximate the performance of such idealized algorithms to an arbitrary degree while not introducing any bias for any degree of approximation. Our approach combines the dimension matching ideas of RJ-MCMC with annealed importance sampling and its Markov chain Monte Carlo implementation. We illustrate the performance of the algorithm with numerical simulations which indicate that, although the approach may at first appear computationally involved, it is in fact competitive.
NASA Astrophysics Data System (ADS)
Bressan, L.; Tinti, S.
2012-05-01
Real-time detection of a tsunami on instrumental sea-level records is quite an important task for a Tsunami Warning System (TWS), and in case of alert conditions for an ongoing tsunami it is often performed by visual inspection in operational warning centres. In this paper we stress the importance of automatic detection algorithms and apply the TEDA (Tsunami Early Detection Algorithm) to identify tsunami arrivals of the 2011 Tohoku tsunami in a real-time virtual exercise. TEDA is designed to work at station level, that is on sea-level data of a single station, and was calibrated on data from the Adak island, Alaska, USA, tide-gauge station. Using the parameters' configuration devised for the Adak station, the TEDA has been applied to 123 coastal sea-level records from the coasts of the Pacific Ocean, which enabled us to evaluate the efficiency and sensitivity of the algorithm on a wide range of background conditions and of signal-to-noise ratios. The result is that TEDA is able to detect quickly the majority of the tsunami signals and therefore proves to have the potential for being a valid tool in the operational TWS practice.
NASA Technical Reports Server (NTRS)
Fijany, Amir; Collier, James B.; Citak, Ari
1997-01-01
A team of US Army Corps of Engineers, Omaha District and Engineering and Support Center, Huntsville, let Propulsion Laboratory (JPL), Stanford Research Institute (SRI), and Montgomery Watson is currently in the process of planning and conducting the largest ever survey at the Former Buckley Field (60,000 acres), in Colorado, by using SRI airborne, ground penetrating, Synthetic Aperture Radar (SAR). The purpose of this survey is the detection of surface and subsurface Unexploded Ordnance (UXO) and in a broader sense the site characterization for identification of contaminated as well as clear areas. In preparation for such a large-scale survey, JPL has been developing advanced algorithms and a high-performance restbed for processing of massive amount of expected SAR data from this site. Two key requirements of this project are the accuracy (in terms of UXO detection) and speed of SAR data processing. The first key feature of this testbed is a large degree of automation and a minimum degree of the need for human perception in the processing to achieve an acceptable processing rate of several hundred acres per day. For accurate UXO detection, novel algorithms have been developed and implemented. These algorithms analyze dual polarized (HH and VV) SAR data. They are based on the correlation of HH and VV SAR data and involve a rather large set of parameters for accurate detection of UXO. For each specific site, this set of parameters can be optimized by using ground truth data (i.e., known surface and subsurface UXOs). In this paper, we discuss these algorithms and their successful application for detection of surface and subsurface anti-tank mines by using a data set from Yuma proving Ground, A7, acquired by SRI SAR.
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
NASA Astrophysics Data System (ADS)
Fijany, Amir; Collier, James B.; Citak, Ari
1999-08-01
A team of US Army Corps of Engineers, Omaha District and Engineering and Support Center, Huntsville, JPL, Stanford Research Institute (SRI), and Montgomery Watson is currently in the process of planning and conducting the largest ever survey at the Former Buckley Field, in Colorado, by using SRI airborne, ground penetrating, SAR. The purpose of this survey is the detection of surface and subsurface Unexploded Ordnance (UXO) and in a broader sense the site characterization for identification of contaminated as well as clear areas. In preparation for such a large-scale survey, JPL has been developing advanced algorithms and a high-performance testbed for processing of massive amount of expected SAR data from this site. Two key requirements of this project are the accuracy and speed of SAR data processing. The first key feature of this testbed is a large degree of automation and maximum degree of the need for human perception in the processing to achieve an acceptable processing rate of several hundred acres per day. For accuracy UXO detection, novel algorithms have been developed and implemented. These algorithms analyze dual polarized SAR data. They are based on the correlation of HH and VV SAR data and involve a rather large set of parameters for accurate detection of UXO. For each specific site, this set of parameters can be optimized by using ground truth data. In this paper, we discuss these algorithms and their successful application for detection of surface and subsurface anti-tank mines by using a data set from Yuma Proving Ground, AZ, acquired by SRI SAR.
A novel algorithm for Bluetooth ECG.
Pandya, Utpal T; Desai, Uday B
2012-11-01
In wireless transmission of ECG, data latency will be significant when battery power level and data transmission distance are not maintained. In applications like home monitoring or personalized care, to overcome the joint effect of previous issues of wireless transmission and other ECG measurement noises, a novel filtering strategy is required. Here, a novel algorithm, identified as peak rejection adaptive sampling modified moving average (PRASMMA) algorithm for wireless ECG is introduced. This algorithm first removes error in bit pattern of received data if occurred in wireless transmission and then removes baseline drift. Afterward, a modified moving average is implemented except in the region of each QRS complexes. The algorithm also sets its filtering parameters according to different sampling rate selected for acquisition of signals. To demonstrate the work, a prototyped Bluetooth-based ECG module is used to capture ECG with different sampling rate and in different position of patient. This module transmits ECG wirelessly to Bluetooth-enabled devices where the PRASMMA algorithm is applied on captured ECG. The performance of PRASMMA algorithm is compared with moving average and S-Golay algorithms visually as well as numerically. The results show that the PRASMMA algorithm can significantly improve the ECG reconstruction by efficiently removing the noise and its use can be extended to any parameters where peaks are importance for diagnostic purpose.
NASA Technical Reports Server (NTRS)
Wang, Lui; Bayer, Steven E.
1991-01-01
Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.
Efficient Homotopy Continuation Algorithms with Application to Computational Fluid Dynamics
NASA Astrophysics Data System (ADS)
Brown, David A.
New homotopy continuation algorithms are developed and applied to a parallel implicit finite-difference Newton-Krylov-Schur external aerodynamic flow solver for the compressible Euler, Navier-Stokes, and Reynolds-averaged Navier-Stokes equations with the Spalart-Allmaras one-equation turbulence model. Many new analysis tools, calculations, and numerical algorithms are presented for the study and design of efficient and robust homotopy continuation algorithms applicable to solving very large and sparse nonlinear systems of equations. Several specific homotopies are presented and studied and a methodology is presented for assessing the suitability of specific homotopies for homotopy continuation. . A new class of homotopy continuation algorithms, referred to as monolithic homotopy continuation algorithms, is developed. These algorithms differ from classical predictor-corrector algorithms by combining the predictor and corrector stages into a single update, significantly reducing the amount of computation and avoiding wasted computational effort resulting from over-solving in the corrector phase. The new algorithms are also simpler from a user perspective, with fewer input parameters, which also improves the user's ability to choose effective parameters on the first flow solve attempt. Conditional convergence is proved analytically and studied numerically for the new algorithms. The performance of a fully-implicit monolithic homotopy continuation algorithm is evaluated for several inviscid, laminar, and turbulent flows over NACA 0012 airfoils and ONERA M6 wings. The monolithic algorithm is demonstrated to be more efficient than the predictor-corrector algorithm for all applications investigated. It is also demonstrated to be more efficient than the widely-used pseudo-transient continuation algorithm for all inviscid and laminar cases investigated, and good performance scaling with grid refinement is demonstrated for the inviscid cases. Performance is also demonstrated
Konstantinidis, Anastasios C.; Olivo, Alessandro; Speller, Robert D.
2011-12-15
Purpose: The x-ray performance evaluation of digital x-ray detectors is based on the calculation of the modulation transfer function (MTF), the noise power spectrum (NPS), and the resultant detective quantum efficiency (DQE). The flat images used for the extraction of the NPS should not contain any fixed pattern noise (FPN) to avoid contamination from nonstochastic processes. The ''gold standard'' method used for the reduction of the FPN (i.e., the different gain between pixels) in linear x-ray detectors is based on normalization with an average reference flat-field. However, the noise in the corrected image depends on the number of flat frames used for the average flat image. The aim of this study is to modify the standard gain correction algorithm to make it independent on the used reference flat frames. Methods: Many publications suggest the use of 10-16 reference flat frames, while other studies use higher numbers (e.g., 48 frames) to reduce the propagated noise from the average flat image. This study quantifies experimentally the effect of the number of used reference flat frames on the NPS and DQE values and appropriately modifies the gain correction algorithm to compensate for this effect. Results: It is shown that using the suggested gain correction algorithm a minimum number of reference flat frames (i.e., down to one frame) can be used to eliminate the FPN from the raw flat image. This saves computer memory and time during the x-ray performance evaluation. Conclusions: The authors show that the method presented in the study (a) leads to the maximum DQE value that one would have by using the conventional method and very large number of frames and (b) has been compared to an independent gain correction method based on the subtraction of flat-field images, leading to identical DQE values. They believe this provides robust validation of the proposed method.
Feng, Y; Olsen, J.; Parikh, P.; Noel, C; Wooten, H; Du, D; Mutic, S; Hu, Y; Kawrakow, I; Dempsey, J
2014-06-01
Purpose: Evaluate commonly used segmentation algorithms on a commercially available real-time MR image guided radiotherapy (MR-IGRT) system (ViewRay), compare the strengths and weaknesses of each method, with the purpose of improving motion tracking for more accurate radiotherapy. Methods: MR motion images of bladder, kidney, duodenum, and liver tumor were acquired for three patients using a commercial on-board MR imaging system and an imaging protocol used during MR-IGRT. A series of 40 frames were selected for each case to cover at least 3 respiratory cycles. Thresholding, Canny edge detection, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE), along with the ViewRay treatment planning and delivery system (TPDS) were included in the comparisons. To evaluate the segmentation results, an expert manual contouring of the organs or tumor from a physician was used as a ground-truth. Metrics value of sensitivity, specificity, Jaccard similarity, and Dice coefficient were computed for comparison. Results: In the segmentation of single image frame, all methods successfully segmented the bladder and kidney, but only FKM, KHM and TPDS were able to segment the liver tumor and the duodenum. For segmenting motion image series, the TPDS method had the highest sensitivity, Jarccard, and Dice coefficients in segmenting bladder and kidney, while FKM and KHM had a slightly higher specificity. A similar pattern was observed when segmenting the liver tumor and the duodenum. The Canny method is not suitable for consistently segmenting motion frames in an automated process, while thresholding and RD-LSE cannot consistently segment a liver tumor and the duodenum. Conclusion: The study compared six different segmentation methods and showed the effectiveness of the ViewRay TPDS algorithm in segmenting motion images during MR-IGRT. Future studies include a selection of conformal segmentation methods based on image/organ-specific information
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
Calzado, A; Geleijns, J; Joemai, R M S; Veldkamp, W J H
2014-01-01
Objective: To compare low-contrast detectability (LCDet) performance between a model [non–pre-whitening matched filter with an eye filter (NPWE)] and human observers in CT images reconstructed with filtered back projection (FBP) and iterative [adaptive iterative dose reduction three-dimensional (AIDR 3D; Toshiba Medical Systems, Zoetermeer, Netherlands)] algorithms. Methods: Images of the Catphan® phantom (Phantom Laboratories, New York, NY) were acquired with Aquilion ONE™ 320-detector row CT (Toshiba Medical Systems, Tokyo, Japan) at five tube current levels (20–500 mA range) and reconstructed with FBP and AIDR 3D. Samples containing either low-contrast objects (diameters, 2–15 mm) or background were extracted and analysed by the NPWE model and four human observers in a two-alternative forced choice detection task study. Proportion correct (PC) values were obtained for each analysed object and used to compare human and model observer performances. An efficiency factor (η) was calculated to normalize NPWE to human results. Results: Human and NPWE model PC values (normalized by the efficiency, η = 0.44) were highly correlated for the whole dose range. The Pearson's product-moment correlation coefficients (95% confidence interval) between human and NPWE were 0.984 (0.972–0.991) for AIDR 3D and 0.984 (0.971–0.991) for FBP, respectively. Bland–Altman plots based on PC results showed excellent agreement between human and NPWE [mean absolute difference 0.5 ± 0.4%; range of differences (−4.7%, 5.6%)]. Conclusion: The NPWE model observer can predict human performance in LCDet tasks in phantom CT images reconstructed with FBP and AIDR 3D algorithms at different dose levels. Advances in knowledge: Quantitative assessment of LCDet in CT can accurately be performed using software based on a model observer. PMID:24837275
Ghekiere, Olivier; Dewilde, Willem; Bellekens, Michel; Hoa, Denis; Couvreur, Thierry; Djekic, Julien; Coolen, Tim; Mancini, Isabelle; Vanhoenacker, Piet K; Dendale, Paul; Nchimi, Alain
2015-12-01
Fractional flow reserve (FFR) during invasive coronary angiography has become an established tool for guiding treatment. However, only one-third of intermediate-grade coronary artery stenosis (ICAS) are hemodynamically significant and require coronary revascularization. Additionally, the severity of stenosis visually established by coronary computed tomography angiography (CCTA) does not reliably correlate with the functional severity. Therefore, additional angiographic morphologic descriptors affecting hemodynamic significance are required. To evaluate quantitative stenosis analysis and plaque descriptors by CCTA in predicting the hemodynamic significance of ICAS and to compare it with quantitative catheter coronary angiography (QCA). QCA was performed in 65 patients (mean age 63 ± 9 years; 47 men) with 76 ICAS (40-70%) on CCTA. Plaque descriptors were determined including circumferential extent of calcification, plaque composition, minimal lumen diameter (MLD) and area, diameter stenosis percentage (Ds %), area stenosis percentage and stenosis length on CCTA. MLD and Ds % were also analyzed on QCA. FFR was measured on 52 ICAS lesions on CCTA and QCA. The diagnostic values of the best CCTA and QCA descriptors were calculated for ICAS with FFR ≤ 0.80. Of the 76 ICAS on CCTA, 52 (68%) had a Ds % between 40 and 70% on QCA. Significant intertechnique correlations were found between CCTA and QCA for MLD and Ds % (p < 0.001). In 17 (33%) of the 52 ICAS lesions on QCA, FFR values were ≤ 0.80. Calcification circumference extent (p = 0.50) and plaque composition assessment (p = 0.59) did not correlate with the hemodynamic significance. Best predictors for FFR ≤ 0.80 stenosis were ≤ 1.35 mm MLD (82% sensitivity, 66% specificity), and ≤ 2.3 mm(²) minimal lumen area (88% sensitivity, 60% specificity) on CCTA, and ≤ 1.1 mm MLD (59% sensitivity, 77% specificity) on QCA. Quantitative CCTA and QCA poorly predict hemodynamic significance of ICAS, though CCTA seems to
Alan Black; Arnis Judzis
2004-10-01
The industry cost shared program aims to benchmark drilling rates of penetration in selected simulated deep formations and to significantly improve ROP through a team development of aggressive diamond product drill bit--fluid system technologies. Overall the objectives are as follows: Phase 1--Benchmark ''best in class'' diamond and other product drilling bits and fluids and develop concepts for a next level of deep drilling performance; Phase 2--Develop advanced smart bit-fluid prototypes and test at large scale; and Phase 3--Field trial smart bit-fluid concepts, modify as necessary and commercialize products. As of report date, TerraTek has concluded all major preparations for the high pressure drilling campaign. Baker Hughes encountered difficulties in providing additional pumping capacity before TerraTek's scheduled relocation to another facility, thus the program was delayed further to accommodate the full testing program.
Alan Black; Arnis Judzis
2003-10-01
This document details the progress to date on the OPTIMIZATION OF DEEP DRILLING PERFORMANCE--DEVELOPMENT AND BENCHMARK TESTING OF ADVANCED DIAMOND PRODUCT DRILL BITS AND HP/HT FLUIDS TO SIGNIFICANTLY IMPROVE RATES OF PENETRATION contract for the year starting October 2002 through September 2002. The industry cost shared program aims to benchmark drilling rates of penetration in selected simulated deep formations and to significantly improve ROP through a team development of aggressive diamond product drill bit--fluid system technologies. Overall the objectives are as follows: Phase 1--Benchmark ''best in class'' diamond and other product drilling bits and fluids and develop concepts for a next level of deep drilling performance; Phase 2--Develop advanced smart bit--fluid prototypes and test at large scale; and Phase 3--Field trial smart bit--fluid concepts, modify as necessary and commercialize products. Accomplishments to date include the following: 4Q 2002--Project started; Industry Team was assembled; Kick-off meeting was held at DOE Morgantown; 1Q 2003--Engineering meeting was held at Hughes Christensen, The Woodlands Texas to prepare preliminary plans for development and testing and review equipment needs; Operators started sending information regarding their needs for deep drilling challenges and priorities for large-scale testing experimental matrix; Aramco joined the Industry Team as DEA 148 objectives paralleled the DOE project; 2Q 2003--Engineering and planning for high pressure drilling at TerraTek commenced; 3Q 2003--Continuation of engineering and design work for high pressure drilling at TerraTek; Baker Hughes INTEQ drilling Fluids and Hughes Christensen commence planning for Phase 1 testing--recommendations for bits and fluids.
Xie, Jiale; Guo, Chunxian; Li, Chang Ming
2013-10-14
Cu2O-ZnO nanowire solar cells have the advantages of light weight and high stability while possessing a large active material interface for potentially high power conversion efficiencies. In particular, electrochemically fabricated devices have attracted increasing attention due to their low-cost and simple fabrication process. However, most of them are "partially" electrochemically fabricated by vacuum deposition onto a preexisting ZnO layer. There are a few examples made via all-electrochemical deposition, but the power conversion efficiency (PCE) is too low (0.13%) for practical applications. Herein we use an all-electrochemical approach to directly deposit ZnO NWs onto FTO followed by electrochemical doping with Ga to produce a heterojunction solar cell. The Ga doping greatly improves light utilization while significantly suppressing charge recombination. A 2.5% molar ratio of Ga to ZnO delivers the best performance with a short circuit current density (Jsc) of 3.24 mA cm(-2) and a PCE of 0.25%, which is significantly higher than in the absence of Ga doping. Moreover, the use of electrochemically deposited ZnO powder-buffered Cu2O from a mixed Cu(2+)-ZnO powder solution and oxygen plasma treatment could reduce the density of defect sites in the heterojunction interface to further increase Jsc and PCE to 4.86 mA cm(-2) and 0.34%, respectively, resulting in the highest power conversion efficiency among all-electrochemically fabricated Cu2O-ZnO NW solar cells. This approach offers great potential for a low-cost solution-based process to mass-manufacture high-performance Cu2O-ZnO NW solar cells. PMID:23945632
Ensemble algorithms in reinforcement learning.
Wiering, Marco A; van Hasselt, Hado
2008-08-01
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and final performance by combining the chosen actions or action probabilities of different RL algorithms. We designed and implemented four different ensemble methods combining the following five different RL algorithms: Q-learning, Sarsa, actor-critic (AC), QV-learning, and AC learning automaton. The intuitively designed ensemble methods, namely, majority voting (MV), rank voting, Boltzmann multiplication (BM), and Boltzmann addition, combine the policies derived from the value functions of the different RL algorithms, in contrast to previous work where ensemble methods have been used in RL for representing and learning a single value function. We show experiments on five maze problems of varying complexity; the first problem is simple, but the other four maze tasks are of a dynamic or partially observable nature. The results indicate that the BM and MV ensembles significantly outperform the single RL algorithms.
Ensemble algorithms in reinforcement learning.
Wiering, Marco A; van Hasselt, Hado
2008-08-01
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and final performance by combining the chosen actions or action probabilities of different RL algorithms. We designed and implemented four different ensemble methods combining the following five different RL algorithms: Q-learning, Sarsa, actor-critic (AC), QV-learning, and AC learning automaton. The intuitively designed ensemble methods, namely, majority voting (MV), rank voting, Boltzmann multiplication (BM), and Boltzmann addition, combine the policies derived from the value functions of the different RL algorithms, in contrast to previous work where ensemble methods have been used in RL for representing and learning a single value function. We show experiments on five maze problems of varying complexity; the first problem is simple, but the other four maze tasks are of a dynamic or partially observable nature. The results indicate that the BM and MV ensembles significantly outperform the single RL algorithms. PMID:18632380
NASA Astrophysics Data System (ADS)
Liu, Yu; Ran, Ran; Li, Sidian; Jiao, Yong; Tade, Moses O.; Shao, Zongping
2014-07-01
Proton-conducting perovskite oxides are excellent electrolyte materials for SOFCs that may improve power density at reduced temperatures and increase fuel efficiency, thus encouraging the widespread implementation of this attractive technology. The main challenges in the application of these oxides in SOFCs are difficult sintering and insufficient conductivity in real cells. In this study, we propose a novel method to significantly enhance the performance of a yttrium-doped barium cerate proton conductor as an electrolyte for SOFCs through a Pd ingress-egress approach to the development of BaCe0.8Y0.1Pd0.1O3-δ (BCYP10). The capability of the Pd egress from the BCYP10 perovskite lattice is demonstrated by H2-TPR, XRD, EDX mapping of STEM and XPS. Significant improvement in the sinterability is observed after the introduction of Pd due to the increased ionic conductivity and the sintering aid effect of egressed Pd. The formation of a B-site cation defect structure after Pd egress and the consequent modification of perovskite grain boundaries with Pd nanoparticles leads to a proton conductivity of BCYP10 that is approximately 3 times higher than that of BCY under a reducing atmosphere. A single cell with a thin film BCYP10 electrolyte reaches a peak power density as high as 645 mA cm-2 at 700 °C.
Culzoni, María J; Schenone, Agustina V; Llamas, Natalia E; Garrido, Mariano; Di Nezio, Maria S; Band, Beatriz S Fernández; Goicoechea, Héctor C
2009-10-16
A fast chromatographic methodology is presented for the analysis of three synthetic dyes in non-alcoholic beverages: amaranth (E123), sunset yellow FCF (E110) and tartrazine (E102). Seven soft drinks (purchased from a local supermarket) were homogenized, filtered and injected into the chromatographic system. Second order data were obtained by a rapid LC separation and DAD detection. A comparative study of the performance of two second order algorithms (MCR-ALS and U-PLS/RBL) applied to model the data, is presented. Interestingly, the data present time shift between different chromatograms and cannot be conveniently corrected to determine the above-mentioned dyes in beverage samples. This fact originates the lack of trilinearity that cannot be conveniently pre-processed and can hardly be modelled by using U-PLS/RBL algorithm. On the contrary, MCR-ALS has shown to be an excellent tool for modelling this kind of data allowing to reach acceptable figures of merit. Recovery values ranged between 97% and 105% when analyzing artificial and real samples were indicative of the good performance of the method. In contrast with the complete separation, which consumes 10 mL of methanol and 3 mL of 0.08 mol L(-1) ammonium acetate, the proposed fast chromatography method requires only 0.46 mL of methanol and 1.54 mL of 0.08 mol L(-1) ammonium acetate. Consequently, analysis time could be reduced up to 14.2% of the necessary time to perform the complete separation allowing saving both solvents and time, which are related to a reduction of both the costs per analysis and environmental impact.
Culzoni, María J; Schenone, Agustina V; Llamas, Natalia E; Garrido, Mariano; Di Nezio, Maria S; Band, Beatriz S Fernández; Goicoechea, Héctor C
2009-10-16
A fast chromatographic methodology is presented for the analysis of three synthetic dyes in non-alcoholic beverages: amaranth (E123), sunset yellow FCF (E110) and tartrazine (E102). Seven soft drinks (purchased from a local supermarket) were homogenized, filtered and injected into the chromatographic system. Second order data were obtained by a rapid LC separation and DAD detection. A comparative study of the performance of two second order algorithms (MCR-ALS and U-PLS/RBL) applied to model the data, is presented. Interestingly, the data present time shift between different chromatograms and cannot be conveniently corrected to determine the above-mentioned dyes in beverage samples. This fact originates the lack of trilinearity that cannot be conveniently pre-processed and can hardly be modelled by using U-PLS/RBL algorithm. On the contrary, MCR-ALS has shown to be an excellent tool for modelling this kind of data allowing to reach acceptable figures of merit. Recovery values ranged between 97% and 105% when analyzing artificial and real samples were indicative of the good performance of the method. In contrast with the complete separation, which consumes 10 mL of methanol and 3 mL of 0.08 mol L(-1) ammonium acetate, the proposed fast chromatography method requires only 0.46 mL of methanol and 1.54 mL of 0.08 mol L(-1) ammonium acetate. Consequently, analysis time could be reduced up to 14.2% of the necessary time to perform the complete separation allowing saving both solvents and time, which are related to a reduction of both the costs per analysis and environmental impact. PMID:19748097
New Effective Multithreaded Matching Algorithms
Manne, Fredrik; Halappanavar, Mahantesh
2014-05-19
Matching is an important combinatorial problem with a number of applications in areas such as community detection, sparse linear algebra, and network alignment. Since computing optimal matchings can be very time consuming, several fast approximation algorithms, both sequential and parallel, have been suggested. Common to the algorithms giving the best solutions is that they tend to be sequential by nature, while algorithms more suitable for parallel computation give solutions of less quality. We present a new simple 1 2 -approximation algorithm for the weighted matching problem. This algorithm is both faster than any other suggested sequential 1 2 -approximation algorithm on almost all inputs and also scales better than previous multithreaded algorithms. We further extend this to a general scalable multithreaded algorithm that computes matchings of weight comparable with the best sequential algorithms. The performance of the suggested algorithms is documented through extensive experiments on different multithreaded architectures.
NASA Astrophysics Data System (ADS)
Dhingra, Sunil; Bhushan, Gian; Dubey, Kashyap Kumar
2014-03-01
The present work studies and identifies the different variables that affect the output parameters involved in a single cylinder direct injection compression ignition (CI) engine using jatropha biodiesel. Response surface methodology based on Central composite design (CCD) is used to design the experiments. Mathematical models are developed for combustion parameters (Brake specific fuel consumption (BSFC) and peak cylinder pressure (Pmax)), performance parameter brake thermal efficiency (BTE) and emission parameters (CO, NO x , unburnt HC and smoke) using regression techniques. These regression equations are further utilized for simultaneous optimization of combustion (BSFC, Pmax), performance (BTE) and emission (CO, NO x , HC, smoke) parameters. As the objective is to maximize BTE and minimize BSFC, Pmax, CO, NO x , HC, smoke, a multiobjective optimization problem is formulated. Nondominated sorting genetic algorithm-II is used in predicting the Pareto optimal sets of solution. Experiments are performed at suitable optimal solutions for predicting the combustion, performance and emission parameters to check the adequacy of the proposed model. The Pareto optimal sets of solution can be used as guidelines for the end users to select optimal combination of engine output and emission parameters depending upon their own requirements.
Anglada-Escude, Guillem; Butler, R. Paul
2012-06-01
Doppler spectroscopy has uncovered or confirmed all the known planets orbiting nearby stars. Two main techniques are used to obtain precision Doppler measurements at optical wavelengths. The first approach is the gas cell method, which consists of least-squares matching of the spectrum of iodine imprinted on the spectrum of the star. The second method relies on the construction of a stabilized spectrograph externally calibrated in wavelength. The most precise stabilized spectrometer in operation is the High Accuracy Radial velocity Planet Searcher (HARPS), operated by the European Southern Observatory in La Silla Observatory, Chile. The Doppler measurements obtained with HARPS are typically obtained using the cross-correlation function (CCF) technique. This technique consists of multiplying the stellar spectrum by a weighted binary mask and finding the minimum of the product as a function of the Doppler shift. It is known that CCF is suboptimal in exploiting the Doppler information in the stellar spectrum. Here we describe an algorithm to obtain precision radial velocity measurements using least-squares matching of each observed spectrum to a high signal-to-noise ratio template derived from the same observations. This algorithm is implemented in our software HARPS-TERRA (Template-Enhanced Radial velocity Re-analysis Application). New radial velocity measurements on a representative sample of stars observed by HARPS are used to illustrate the benefits of the proposed method. We show that, compared with CCF, template matching provides a significant improvement in accuracy, especially when applied to M dwarfs.
NASA Astrophysics Data System (ADS)
Gilles, Luc; Ellerbroek, Brent
2013-12-01
This paper discusses a wind profile estimation algorithm for laser guide star tomography adaptiveoptics systems, which generalizes a previously published slope detection and ranging turbulence profiler [Gillesand Ellerbroek, J. Opt. Soc. Am. A27, A76 (2010)] to the case of spatio-temporal cross-correlations between asingle or multiple pairs of wavefront sensors. The estimated wind profile is fed to a computationally efficientDistributed Kalman Filter to perform atmospheric tomography. Residual wavefront error is assessed for the ThirtyMeter Telescope and compared to that of a static, single-frame, minimum mean square error estimator. We foundthat the superior turbulence rejection of the Kalman filter is a delicate feature requiring wind profile estimation tobetter than ~20% accuracy.
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.
Li, X. J.; Zhao, D. G. Jiang, D. S.; Liu, Z. S.; Chen, P.; Zhu, J. J.; Le, L. C.; Yang, J.; He, X. G.; Zhang, S. M.; Zhang, B. S.; Liu, J. P.; Yang, H.
2014-10-28
The significant effect of the thickness of Ni film on the performance of the Ohmic contact of Ni/Au to p-GaN is studied. The Ni/Au metal films with thickness of 15/50 nm on p-GaN led to better electrical characteristics, showing a lower specific contact resistivity after annealing in the presence of oxygen. Both the formation of a NiO layer and the evolution of metal structure on the sample surface and at the interface with p-GaN were checked by transmission electron microscopy and energy-dispersive x-ray spectroscopy. The experimental results indicate that a too thin Ni film cannot form enough NiO to decrease the barrier height and get Ohmic contact to p-GaN, while a too thick Ni film will transform into too thick NiO cover on the sample surface and thus will also deteriorate the electrical conductivity of sample.
NASA Technical Reports Server (NTRS)
Dieriam, Todd A.
1990-01-01
Future missions to Mars may require pin-point landing precision, possibly on the order of tens of meters. The ability to reach a target while meeting a dynamic pressure constraint to ensure safe parachute deployment is complicated at Mars by low atmospheric density, high atmospheric uncertainty, and the desire to employ only bank angle control. The vehicle aerodynamic performance requirements and guidance necessary for 0.5 to 1.5 lift drag ratio vehicle to maximize the achievable footprint while meeting the constraints are examined. A parametric study of the various factors related to entry vehicle performance in the Mars environment is undertaken to develop general vehicle aerodynamic design requirements. The combination of low lift drag ratio and low atmospheric density at Mars result in a large phugoid motion involving the dynamic pressure which complicates trajectory control. Vehicle ballistic coefficient is demonstrated to be the predominant characteristic affecting final dynamic pressure. Additionally, a speed brake is shown to be ineffective at reducing the final dynamic pressure. An adaptive precision entry atmospheric guidance scheme is presented. The guidance uses a numeric predictor-corrector algorithm to control downrange, an azimuth controller to govern crossrange, and analytic control law to reduce the final dynamic pressure. Guidance performance is tested against a variety of dispersions, and the results from selected tests are presented. Precision entry using bank angle control only is demonstrated to be feasible at Mars.
The evaluation of the OSGLR algorithm for restructurable controls
NASA Technical Reports Server (NTRS)
Bonnice, W. F.; Wagner, E.; Hall, S. R.; Motyka, P.
1986-01-01
The detection and isolation of commercial aircraft control surface and actuator failures using the orthogonal series generalized likelihood ratio (OSGLR) test was evaluated. The OSGLR algorithm was chosen as the most promising algorithm based on a preliminary evaluation of three failure detection and isolation (FDI) algorithms (the detection filter, the generalized likelihood ratio test, and the OSGLR test) and a survey of the literature. One difficulty of analytic FDI techniques and the OSGLR algorithm in particular is their sensitivity to modeling errors. Therefore, methods of improving the robustness of the algorithm were examined with the incorporation of age-weighting into the algorithm being the most effective approach, significantly reducing the sensitivity of the algorithm to modeling errors. The steady-state implementation of the algorithm based on a single cruise linear model was evaluated using a nonlinear simulation of a C-130 aircraft. A number of off-nominal no-failure flight conditions including maneuvers, nonzero flap deflections, different turbulence levels and steady winds were tested. Based on the no-failure decision functions produced by off-nominal flight conditions, the failure detection performance at the nominal flight condition was determined. The extension of the algorithm to a wider flight envelope by scheduling the linear models used by the algorithm on dynamic pressure and flap deflection was also considered. Since simply scheduling the linear models over the entire flight envelope is unlikely to be adequate, scheduling of the steady-state implentation of the algorithm was briefly investigated.
A segmentation algorithm for noisy images
Xu, Y.; Olman, V.; Uberbacher, E.C.
1996-12-31
This paper presents a 2-D image segmentation algorithm and addresses issues related to its performance on noisy images. The algorithm segments an image by first constructing a minimum spanning tree representation of the image and then partitioning the spanning tree into sub-trees representing different homogeneous regions. The spanning tree is partitioned in such a way that the sum of gray-level variations over all partitioned subtrees is minimized under the constraints that each subtree has at least a specified number of pixels and two adjacent subtrees have significantly different ``average`` gray-levels. Two types of noise, transmission errors and Gaussian additive noise. are considered and their effects on the segmentation algorithm are studied. Evaluation results have shown that the segmentation algorithm is robust in the presence of these two types of noise.
Adaptive computation algorithm for RBF neural network.
Han, Hong-Gui; Qiao, Jun-Fei
2012-02-01
A novel learning algorithm is proposed for nonlinear modelling and identification using radial basis function neural networks. The proposed method simplifies neural network training through the use of an adaptive computation algorithm (ACA). In addition, the convergence of the ACA is analyzed by the Lyapunov criterion. The proposed algorithm offers two important advantages. First, the model performance can be significantly improved through ACA, and the modelling error is uniformly ultimately bounded. Secondly, the proposed ACA can reduce computational cost and accelerate the training speed. The proposed method is then employed to model classical nonlinear system with limit cycle and to identify nonlinear dynamic system, exhibiting the effectiveness of the proposed algorithm. Computational complexity analysis and simulation results demonstrate its effectiveness.
A comprehensive review of swarm optimization algorithms.
Ab Wahab, Mohd Nadhir; Nefti-Meziani, Samia; Atyabi, Adham
2015-01-01
Many swarm optimization algorithms have been introduced since the early 60's, Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms have demonstrated their potential to solve many optimization problems. This paper provides an in-depth survey of well-known optimization algorithms. Selected algorithms are briefly explained and compared with each other comprehensively through experiments conducted using thirty well-known benchmark functions. Their advantages and disadvantages are also discussed. A number of statistical tests are then carried out to determine the significant performances. The results indicate the overall advantage of Differential Evolution (DE) and is closely followed by Particle Swarm Optimization (PSO), compared with other considered approaches. PMID:25992655
A Comprehensive Review of Swarm Optimization Algorithms
2015-01-01
Many swarm optimization algorithms have been introduced since the early 60’s, Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms have demonstrated their potential to solve many optimization problems. This paper provides an in-depth survey of well-known optimization algorithms. Selected algorithms are briefly explained and compared with each other comprehensively through experiments conducted using thirty well-known benchmark functions. Their advantages and disadvantages are also discussed. A number of statistical tests are then carried out to determine the significant performances. The results indicate the overall advantage of Differential Evolution (DE) and is closely followed by Particle Swarm Optimization (PSO), compared with other considered approaches. PMID:25992655
Attia, Khalid A M; Nassar, Mohammed W I; El-Zeiny, Mohamed B; Serag, Ahmed
2017-01-01
For the first time, a new variable selection method based on swarm intelligence namely firefly algorithm is coupled with three different multivariate calibration models namely, concentration residual augmented classical least squares, artificial neural network and support vector regression in UV spectral data. A comparative study between the firefly algorithm and the well-known genetic algorithm was developed. The discussion revealed the superiority of using this new powerful algorithm over the well-known genetic algorithm. Moreover, different statistical tests were performed and no significant differences were found between all the models regarding their predictabilities. This ensures that simpler and faster models were obtained without any deterioration of the quality of the calibration.
Zafonte, Ross; Krengel, Maxine H.; Martin, Paula I.; Frazier, Judith; Hamblin, Michael R.; Knight, Jeffrey A.; Meehan, William P.; Baker, Errol H.
2014-01-01
Abstract This pilot, open-protocol study examined whether scalp application of red and near-infrared (NIR) light-emitting diodes (LED) could improve cognition in patients with chronic, mild traumatic brain injury (mTBI). Application of red/NIR light improves mitochondrial function (especially in hypoxic/compromised cells) promoting increased adenosine triphosphate (ATP) important for cellular metabolism. Nitric oxide is released locally, increasing regional cerebral blood flow. LED therapy is noninvasive, painless, and non-thermal (cleared by the United States Food and Drug Administration [FDA], an insignificant risk device). Eleven chronic, mTBI participants (26–62 years of age, 6 males) with nonpenetrating brain injury and persistent cognitive dysfunction were treated for 18 outpatient sessions (Monday, Wednesday, Friday, for 6 weeks), starting at 10 months to 8 years post- mTBI (motor vehicle accident [MVA] or sports-related; and one participant, improvised explosive device [IED] blast injury). Four had a history of multiple concussions. Each LED cluster head (5.35 cm diameter, 500 mW, 22.2 mW/cm2) was applied for 10 min to each of 11 scalp placements (13 J/cm2). LEDs were placed on the midline from front-to-back hairline; and bilaterally on frontal, parietal, and temporal areas. Neuropsychological testing was performed pre-LED, and at 1 week, and 1 and 2 months after the 18th treatment. A significant linear trend was observed for the effect of LED treatment over time for the Stroop test for Executive Function, Trial 3 inhibition (p=0.004); Stroop, Trial 4 inhibition switching (p=0.003); California Verbal Learning Test (CVLT)-II, Total Trials 1–5 (p=0.003); and CVLT-II, Long Delay Free Recall (p=0.006). Participants reported improved sleep, and fewer post-traumatic stress disorder (PTSD) symptoms, if present. Participants and family reported better ability to perform social, interpersonal, and occupational functions. These open-protocol data suggest
Naeser, Margaret A; Zafonte, Ross; Krengel, Maxine H; Martin, Paula I; Frazier, Judith; Hamblin, Michael R; Knight, Jeffrey A; Meehan, William P; Baker, Errol H
2014-06-01
This pilot, open-protocol study examined whether scalp application of red and near-infrared (NIR) light-emitting diodes (LED) could improve cognition in patients with chronic, mild traumatic brain injury (mTBI). Application of red/NIR light improves mitochondrial function (especially in hypoxic/compromised cells) promoting increased adenosine triphosphate (ATP) important for cellular metabolism. Nitric oxide is released locally, increasing regional cerebral blood flow. LED therapy is noninvasive, painless, and non-thermal (cleared by the United States Food and Drug Administration [FDA], an insignificant risk device). Eleven chronic, mTBI participants (26-62 years of age, 6 males) with nonpenetrating brain injury and persistent cognitive dysfunction were treated for 18 outpatient sessions (Monday, Wednesday, Friday, for 6 weeks), starting at 10 months to 8 years post- mTBI (motor vehicle accident [MVA] or sports-related; and one participant, improvised explosive device [IED] blast injury). Four had a history of multiple concussions. Each LED cluster head (5.35 cm diameter, 500 mW, 22.2 mW/cm(2)) was applied for 10 min to each of 11 scalp placements (13 J/cm(2)). LEDs were placed on the midline from front-to-back hairline; and bilaterally on frontal, parietal, and temporal areas. Neuropsychological testing was performed pre-LED, and at 1 week, and 1 and 2 months after the 18th treatment. A significant linear trend was observed for the effect of LED treatment over time for the Stroop test for Executive Function, Trial 3 inhibition (p=0.004); Stroop, Trial 4 inhibition switching (p=0.003); California Verbal Learning Test (CVLT)-II, Total Trials 1-5 (p=0.003); and CVLT-II, Long Delay Free Recall (p=0.006). Participants reported improved sleep, and fewer post-traumatic stress disorder (PTSD) symptoms, if present. Participants and family reported better ability to perform social, interpersonal, and occupational functions. These open-protocol data suggest that placebo
Naeser, Margaret A; Zafonte, Ross; Krengel, Maxine H; Martin, Paula I; Frazier, Judith; Hamblin, Michael R; Knight, Jeffrey A; Meehan, William P; Baker, Errol H
2014-06-01
This pilot, open-protocol study examined whether scalp application of red and near-infrared (NIR) light-emitting diodes (LED) could improve cognition in patients with chronic, mild traumatic brain injury (mTBI). Application of red/NIR light improves mitochondrial function (especially in hypoxic/compromised cells) promoting increased adenosine triphosphate (ATP) important for cellular metabolism. Nitric oxide is released locally, increasing regional cerebral blood flow. LED therapy is noninvasive, painless, and non-thermal (cleared by the United States Food and Drug Administration [FDA], an insignificant risk device). Eleven chronic, mTBI participants (26-62 years of age, 6 males) with nonpenetrating brain injury and persistent cognitive dysfunction were treated for 18 outpatient sessions (Monday, Wednesday, Friday, for 6 weeks), starting at 10 months to 8 years post- mTBI (motor vehicle accident [MVA] or sports-related; and one participant, improvised explosive device [IED] blast injury). Four had a history of multiple concussions. Each LED cluster head (5.35 cm diameter, 500 mW, 22.2 mW/cm(2)) was applied for 10 min to each of 11 scalp placements (13 J/cm(2)). LEDs were placed on the midline from front-to-back hairline; and bilaterally on frontal, parietal, and temporal areas. Neuropsychological testing was performed pre-LED, and at 1 week, and 1 and 2 months after the 18th treatment. A significant linear trend was observed for the effect of LED treatment over time for the Stroop test for Executive Function, Trial 3 inhibition (p=0.004); Stroop, Trial 4 inhibition switching (p=0.003); California Verbal Learning Test (CVLT)-II, Total Trials 1-5 (p=0.003); and CVLT-II, Long Delay Free Recall (p=0.006). Participants reported improved sleep, and fewer post-traumatic stress disorder (PTSD) symptoms, if present. Participants and family reported better ability to perform social, interpersonal, and occupational functions. These open-protocol data suggest that placebo
Two Meanings of Algorithmic Mathematics.
ERIC Educational Resources Information Center
Maurer, Stephen B.
1984-01-01
Two mathematical topics are interpreted from the viewpoints of traditional (performing algorithms) and contemporary (creating algorithms and thinking in terms of them for solving problems and developing theory) algorithmic mathematics. The two topics are Horner's method for evaluating polynomials and Gauss's method for solving systems of linear…
Automatic design of decision-tree algorithms with evolutionary algorithms.
Barros, Rodrigo C; Basgalupp, Márcio P; de Carvalho, André C P L F; Freitas, Alex A
2013-01-01
This study reports the empirical analysis of a hyper-heuristic evolutionary algorithm that is capable of automatically designing top-down decision-tree induction algorithms. Top-down decision-tree algorithms are of great importance, considering their ability to provide an intuitive and accurate knowledge representation for classification problems. The automatic design of these algorithms seems timely, given the large literature accumulated over more than 40 years of research in the manual design of decision-tree induction algorithms. The proposed hyper-heuristic evolutionary algorithm, HEAD-DT, is extensively tested using 20 public UCI datasets and 10 microarray gene expression datasets. The algorithms automatically designed by HEAD-DT are compared with traditional decision-tree induction algorithms, such as C4.5 and CART. Experimental results show that HEAD-DT is capable of generating algorithms which are significantly more accurate than C4.5 and CART.
Asymmetric intimacy and algorithm for detecting communities in bipartite networks
NASA Astrophysics Data System (ADS)
Wang, Xingyuan; Qin, Xiaomeng
2016-11-01
In this paper, an algorithm to choose a good partition in bipartite networks has been proposed. Bipartite networks have more theoretical significance and broader prospect of application. In view of distinctive structure of bipartite networks, in our method, two parameters are defined to show the relationships between the same type nodes and heterogeneous nodes respectively. Moreover, our algorithm employs a new method of finding and expanding the core communities in bipartite networks. Two kinds of nodes are handled separately and merged, and then the sub-communities are obtained. After that, objective communities will be found according to the merging rule. The proposed algorithm has been simulated in real-world networks and artificial networks, and the result verifies the accuracy and reliability of the parameters on intimacy for our algorithm. Eventually, comparisons with similar algorithms depict that the proposed algorithm has better performance.
Analysis of image thresholding segmentation algorithms based on swarm intelligence
NASA Astrophysics Data System (ADS)
Zhang, Yi; Lu, Kai; Gao, Yinghui; Yang, Bo
2013-03-01
Swarm intelligence-based image thresholding segmentation algorithms are playing an important role in the research field of image segmentation. In this paper, we briefly introduce the theories of four existing image segmentation algorithms based on swarm intelligence including fish swarm algorithm, artificial bee colony, bacteria foraging algorithm and particle swarm optimization. Then some image benchmarks are tested in order to show the differences of the segmentation accuracy, time consumption, convergence and robustness for Salt & Pepper noise and Gaussian noise of these four algorithms. Through these comparisons, this paper gives qualitative analyses for the performance variance of the four algorithms. The conclusions in this paper would give a significant guide for the actual image segmentation.
Benchmarking homogenization algorithms for monthly data
NASA Astrophysics Data System (ADS)
Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M. J.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratiannil, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.; Willett, K.
2013-09-01
The COST (European Cooperation in Science and Technology) Action ES0601: Advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies. The algorithms were validated against a realistic benchmark dataset. Participants provided 25 separate homogenized contributions as part of the blind study as well as 22 additional solutions submitted after the details of the imposed inhomogeneities were revealed. These homogenized datasets were assessed by a number of performance metrics including i) the centered root mean square error relative to the true homogeneous values at various averaging scales, ii) the error in linear trend estimates and iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data. Moreover, state-of-the-art relative homogenization algorithms developed to work with an inhomogeneous reference are shown to perform best. The study showed that currently automatic algorithms can perform as well as manual ones.
TrackEye tracking algorithm characterization
NASA Astrophysics Data System (ADS)
Valley, Michael T.; Shields, Robert W.; Reed, Jack M.
2004-10-01
TrackEye is a film digitization and target tracking system that offers the potential for quantitatively measuring the dynamic state variables (e.g., absolute and relative position, orientation, linear and angular velocity/acceleration, spin rate, trajectory, angle of attack, etc.) for moving objects using captured single or dual view image sequences. At the heart of the system is a set of tracking algorithms that automatically find and quantify the location of user selected image details such as natural test article features or passive fiducials that have been applied to cooperative test articles. This image position data is converted into real world coordinates and rates with user specified information such as the image scale and frame rate. Though tracking methods such as correlation algorithms are typically robust by nature, the accuracy and suitability of each TrackEye tracking algorithm is in general unknown even under good imaging conditions. The challenges of optimal algorithm selection and algorithm performance/measurement uncertainty are even more significant for long range tracking of high-speed targets where temporally varying atmospheric effects degrade the imagery. This paper will present the preliminary results from a controlled test sequence used to characterize the performance of the TrackEye tracking algorithm suite.
New algorithms for the minimal form'' problem
Oliveira, J.S.; Cook, G.O. Jr. ); Purtill, M.R. . Center for Communications Research)
1991-12-20
It is widely appreciated that large-scale algebraic computation (performing computer algebra operations on large symbolic expressions) places very significant demands upon existing computer algebra systems. Because of this, parallel versions of many important algorithms have been successfully sought, and clever techniques have been found for improving the speed of the algebraic simplification process. In addition, some attention has been given to the issue of restructuring large expressions, or transforming them into minimal forms.'' By minimal form,'' we mean that form of an expression that involves a minimum number of operations in the sense that no simple transformation on the expression leads to a form involving fewer operations. Unfortunately, the progress that has been achieved to date on this very hard problem is not adequate for the very significant demands of large computer algebra problems. In response to this situation, we have developed some efficient algorithms for constructing minimal forms.'' In this paper, the multi-stage algorithm in which these new algorithms operate is defined and the features of these algorithms are developed. In a companion paper, we introduce the core algebra engine of a new tool that provides the algebraic framework required for the implementation of these new algorithms.
NASA Astrophysics Data System (ADS)
Ouyang, Liangqi; Shaw, Crystal L.; Kuo, Chin-chen; Griffin, Amy L.; Martin, David C.
2014-04-01
-polymerization time intervals, the polymerization did not cause significant deficits in performance of the DA task, suggesting that hippocampal function was not impaired by PEDOT deposition. However, GFAP+ and ED-1+ cells were also found at the deposition two weeks after the polymerization, suggesting potential secondary scarring. Therefore, less extensive deposition or milder deposition conditions may be desirable to minimize this scarring while maintaining decreased system impedance.
NASA Technical Reports Server (NTRS)
Luke, Edward Allen
1993-01-01
Two algorithms capable of computing a transonic 3-D inviscid flow field about rotating machines are considered for parallel implementation. During the study of these algorithms, a significant new method of measuring the performance of parallel algorithms is developed. The theory that supports this new method creates an empirical definition of scalable parallel algorithms that is used to produce quantifiable evidence that a scalable parallel application was developed. The implementation of the parallel application and an automated domain decomposition tool are also discussed.
2013-01-01
Background The High-Dimensional Propensity Score (hd-PS) algorithm can select and adjust for baseline confounders of treatment-outcome associations in pharmacoepidemiologic studies that use healthcare claims data. How hd-PS performance is affected by aggregating medications or medical diagnoses has not been assessed. Methods We evaluated the effects of aggregating medications or diagnoses on hd-PS performance in an empirical example using resampled cohorts with small sample size, rare outcome incidence, or low exposure prevalence. In a cohort study comparing the risk of upper gastrointestinal complications in celecoxib or traditional NSAIDs (diclofenac, ibuprofen) initiators with rheumatoid arthritis and osteoarthritis, we (1) aggregated medications and International Classification of Diseases-9 (ICD-9) diagnoses into hierarchies of the Anatomical Therapeutic Chemical classification (ATC) and the Clinical Classification Software (CCS), respectively, and (2) sampled the full cohort using techniques validated by simulations to create 9,600 samples to compare 16 aggregation scenarios across 50% and 20% samples with varying outcome incidence and exposure prevalence. We applied hd-PS to estimate relative risks (RR) using 5 dimensions, predefined confounders, ≤ 500 hd-PS covariates, and propensity score deciles. For each scenario, we calculated: (1) the geometric mean RR; (2) the difference between the scenario mean ln(RR) and the ln(RR) from published randomized controlled trials (RCT); and (3) the proportional difference in the degree of estimated confounding between that scenario and the base scenario (no aggregation). Results Compared with the base scenario, aggregations of medications into ATC level 4 alone or in combination with aggregation of diagnoses into CCS level 1 improved the hd-PS confounding adjustment in most scenarios, reducing residual confounding compared with the RCT findings by up to 19%. Conclusions Aggregation of codes using hierarchical coding
An efficient algorithm for calculating the exact Hausdorff distance.
Taha, Abdel Aziz; Hanbury, Allan
2015-11-01
The Hausdorff distance (HD) between two point sets is a commonly used dissimilarity measure for comparing point sets and image segmentations. Especially when very large point sets are compared using the HD, for example when evaluating magnetic resonance volume segmentations, or when the underlying applications are based on time critical tasks, like motion detection, then the computational complexity of HD algorithms becomes an important issue. In this paper we propose a novel efficient algorithm for computing the exact Hausdorff distance. In a runtime analysis, the proposed algorithm is demonstrated to have nearly-linear complexity. Furthermore, it has efficient performance for large point set sizes as well as for large grid size; performs equally for sparse and dense point sets; and finally it is general without restrictions on the characteristics of the point set. The proposed algorithm is tested against the HD algorithm of the widely used national library of medicine insight segmentation and registration toolkit (ITK) using magnetic resonance volumes with extremely large size. The proposed algorithm outperforms the ITK HD algorithm both in speed and memory required. In an experiment using trajectories from a road network, the proposed algorithm significantly outperforms an HD algorithm based on R-Trees. PMID:26440258
Rempp, Florian; Mahler, Guenter; Michel, Mathias
2007-09-15
We introduce a scheme to perform the cooling algorithm, first presented by Boykin et al. in 2002, for an arbitrary number of times on the same set of qbits. We achieve this goal by adding an additional SWAP gate and a bath contact to the algorithm. This way one qbit may repeatedly be cooled without adding additional qbits to the system. By using a product Liouville space to model the bath contact we calculate the density matrix of the system after a given number of applications of the algorithm.
Efficient implementation of the adaptive scale pixel decomposition algorithm
NASA Astrophysics Data System (ADS)
Zhang, L.; Bhatnagar, S.; Rau, U.; Zhang, M.
2016-08-01
Context. Most popular algorithms in use to remove the effects of a telescope's point spread function (PSF) in radio astronomy are variants of the CLEAN algorithm. Most of these algorithms model the sky brightness using the delta-function basis, which results in undesired artefacts when used to image extended emission. The adaptive scale pixel decomposition (Asp-Clean) algorithm models the sky brightness on a scale-sensitive basis and thus gives a significantly better imaging performance when imaging fields that contain both resolved and unresolved emission. Aims: However, the runtime cost of Asp-Clean is higher than that of scale-insensitive algorithms. In this paper, we identify the most expensive step in the original Asp-Clean algorithm and present an efficient implementation of it, which significantly reduces the computational cost while keeping the imaging performance comparable to the original algorithm. The PSF sidelobe levels of modern wide-band telescopes are significantly reduced, allowing us to make approximations to reduce the computational cost, which in turn allows for the deconvolution of larger images on reasonable timescales. Methods: As in the original algorithm, scales in the image are estimated through function fitting. Here we introduce an analytical method to model extended emission, and a modified method for estimating the initial values used for the fitting procedure, which ultimately leads to a lower computational cost. Results: The new implementation was tested with simulated EVLA data and the imaging performance compared well with the original Asp-Clean algorithm. Tests show that the current algorithm can recover features at different scales with lower computational cost.
An efficient algorithm for function optimization: modified stem cells algorithm
NASA Astrophysics Data System (ADS)
Taherdangkoo, Mohammad; Paziresh, Mahsa; Yazdi, Mehran; Bagheri, Mohammad
2013-03-01
In this paper, we propose an optimization algorithm based on the intelligent behavior of stem cell swarms in reproduction and self-organization. Optimization algorithms, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm and Artificial Bee Colony (ABC) algorithm, can give solutions to linear and non-linear problems near to the optimum for many applications; however, in some case, they can suffer from becoming trapped in local optima. The Stem Cells Algorithm (SCA) is an optimization algorithm inspired by the natural behavior of stem cells in evolving themselves into new and improved cells. The SCA avoids the local optima problem successfully. In this paper, we have made small changes in the implementation of this algorithm to obtain improved performance over previous versions. Using a series of benchmark functions, we assess the performance of the proposed algorithm and compare it with that of the other aforementioned optimization algorithms. The obtained results prove the superiority of the Modified Stem Cells Algorithm (MSCA).
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.
Learning evasive maneuvers using evolutionary algorithms and neural networks
NASA Astrophysics Data System (ADS)
Kang, Moung Hung
In this research, evolutionary algorithms and recurrent neural networks are combined to evolve control knowledge to help pilots avoid being struck by a missile, based on a two-dimensional air combat simulation model. The recurrent neural network is used for representing the pilot's control knowledge and evolutionary algorithms (i.e., Genetic Algorithms, Evolution Strategies, and Evolutionary Programming) are used for optimizing the weights and/or topology of the recurrent neural network. The simulation model of the two-dimensional evasive maneuver problem evolved is used for evaluating the performance of the recurrent neural network. Five typical air combat conditions were selected to evaluate the performance of the recurrent neural networks evolved by the evolutionary algorithms. Analysis of Variance (ANOVA) tests and response graphs were used to analyze the results. Overall, there was little difference in the performance of the three evolutionary algorithms used to evolve the control knowledge. However, the number of generations of each algorithm required to obtain the best performance was significantly different. ES converges the fastest, followed by EP and then by GA. The recurrent neural networks evolved by the evolutionary algorithms provided better performance than the traditional recommendations for evasive maneuvers, maximum gravitational turn, for each air combat condition. Furthermore, the recommended actions of the recurrent neural networks are reasonable and can be used for pilot training.
Atmospheric compensation in free space optical communication with simulated annealing algorithm
NASA Astrophysics Data System (ADS)
Li, Zhaokun; Cao, Jingtai; Zhao, Xiaohui; Liu, Wei
2015-03-01
As we know that the conventional adaptive optics (AO) systems can compensate atmospheric turbulence in free space optical (FSO) communication system. Since in strong scintillation conditions, wave-front measurements based on phase-conjugation principle are undesired. A novel global optimization simulated annealing (SA) algorithm is proposed in this paper to compensate wave-front aberration. With global optimization characteristics, SA algorithm is better than stochastic parallel gradient descent (SPGD) and other algorithms that already exist. Related simulations are conducted and the results show that the SA algorithm can significantly improve performance in FSO communication system and is better than SPGD algorithm with the increase of coupling efficiency.
NASA Astrophysics Data System (ADS)
Radac, Mircea-Bogdan; Precup, Radu-Emil
2016-05-01
This paper presents the design and experimental validation of a new model-free data-driven iterative reference input tuning (IRIT) algorithm that solves a reference trajectory tracking problem as an optimization problem with control signal saturation constraints and control signal rate constraints. The IRIT algorithm design employs an experiment-based stochastic search algorithm to use the advantages of iterative learning control. The experimental results validate the IRIT algorithm applied to a non-linear aerodynamic position control system. The results prove that the IRIT algorithm offers the significant control system performance improvement by few iterations and experiments conducted on the real-world process and model-free parameter tuning.
NASA Technical Reports Server (NTRS)
Xiong, Xiaoxiong; Wenny, Brian N.; Barnes, William L.
2009-01-01
Since launch, the Terra and Aqua moderate resolution imaging spectroradiometer (MODIS) instruments have successfully operated on-orbit for more than 9 and 6.5 years, respectively. Iv1ODIS, a key instrument for the NASA's Earth Observing System (EOS) missions, was designed to make continuous observations for studies of Earth's land, ocean, and atmospheric properties and to extend existing data records from heritage earth-observing sensors. In addition to frequent global coverage, MODIS observations are made in 36 spectral bands, covering both solar reflective and thermal emissive spectral regions. Nearly 40 data products are routinely generated from MODIS' observations and publicly distributed for a broad range of applications. Both instruments have produced an unprecedented amount of data in support of the science community. As a general reference for understanding sensor operation and calibration, and thus science data quality, we ;provide an overview of the MODIS instruments and their pre-launch calibration and characterization, and describe their on-orbit calibration algorithms and performance. On-orbit results from both Terra and Aqua MODIS radiometric, spectral, and "spatial calibration are discussed. Currently, both instruments, including their on-board calibration devices, are healthy and are expected to continue operation for several }rears to come.
NASA Astrophysics Data System (ADS)
Hsu, Kuo-Hsien
2012-11-01
Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel's method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu's, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu's and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu's method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.
Yu Lifeng; Leng Shuai; Chen Lingyun; Kofler, James M.; McCollough, Cynthia H.; Carter, Rickey E.
2013-04-15
Purpose: Efficient optimization of CT protocols demands a quantitative approach to predicting human observer performance on specific tasks at various scan and reconstruction settings. The goal of this work was to investigate how well a channelized Hotelling observer (CHO) can predict human observer performance on 2-alternative forced choice (2AFC) lesion-detection tasks at various dose levels and two different reconstruction algorithms: a filtered-backprojection (FBP) and an iterative reconstruction (IR) method. Methods: A 35 Multiplication-Sign 26 cm{sup 2} torso-shaped phantom filled with water was used to simulate an average-sized patient. Three rods with different diameters (small: 3 mm; medium: 5 mm; large: 9 mm) were placed in the center region of the phantom to simulate small, medium, and large lesions. The contrast relative to background was -15 HU at 120 kV. The phantom was scanned 100 times using automatic exposure control each at 60, 120, 240, 360, and 480 quality reference mAs on a 128-slice scanner. After removing the three rods, the water phantom was again scanned 100 times to provide signal-absent background images at the exact same locations. By extracting regions of interest around the three rods and on the signal-absent images, the authors generated 21 2AFC studies. Each 2AFC study had 100 trials, with each trial consisting of a signal-present image and a signal-absent image side-by-side in randomized order. In total, 2100 trials were presented to both the model and human observers. Four medical physicists acted as human observers. For the model observer, the authors used a CHO with Gabor channels, which involves six channel passbands, five orientations, and two phases, leading to a total of 60 channels. The performance predicted by the CHO was compared with that obtained by four medical physicists at each 2AFC study. Results: The human and model observers were highly correlated at each dose level for each lesion size for both FBP and IR. The
NASA Astrophysics Data System (ADS)
Ashbridge, Gayle Ann
Change management has become an imperative for organizations as they move into the 21st century; up to 75 percent of change initiatives fail. Nuclear power plants face the same challenges as industrial firms with the added challenge of deregulation. Faced with this challenge, restructuring the electric utility has raised a number of complex issues. Under traditional cost-of-service regulation, electric utilities were able to pass on their costs to consumers who absorbed them. In the new competitive environment, customers will now choose their suppliers based on the most competitive price. The purpose of this study is to determine the degree of congruence between non-supervisory and supervisory personnel regarding the perceived implementation of high performance workplace practices at a nuclear power plant. This study used as its foundation the practices identified in the Road to High Performance Workplaces: A Guide to Better Jobs and Better Business Results by the U.S. Department of Labor's Office of the American Workplace (1994). The population for this study consisted of organizational members at one nuclear power plant. Over 300 individuals completed surveys on high performance workplace practices. Two surveys were administered, one to non-supervisory personnel and one to first line supervisors and above. The determination of implementation levels was accomplished through descriptive statistical analysis. Results of the study revealed 32 areas of noncongruence between non-supervisory and supervisory personnel in regard to the perceived implementation level of the high performance workplace practices. Factor analysis further revealed that the order in which the respondents place emphasis on the variables varies between the two groups. This study provides recommendations that may improve the nuclear power plants alignment of activities. Recommendations are also provided for additional research on high-performance work practices.
ERIC Educational Resources Information Center
Lemons, Christopher J.; Zigmond, Naomi; Kloo, Amanda M.; Hill, David R.; Mrachko, Alicia A.; Paterra, Matthew F.; Bost, Thomas J.; Davis, Shawn M.
2013-01-01
Alternate assessments have been used for the last 10 years to evaluate schools' efforts to teach children with significant cognitive disabilities. However, few studies have examined the reading skills of children who participate in these assessments. The purpose of this study was to extend understanding of the reading skills of this…
a Distributed Polygon Retrieval Algorithm Using Mapreduce
NASA Astrophysics Data System (ADS)
Guo, Q.; Palanisamy, B.; Karimi, H. A.
2015-07-01
The burst of large-scale spatial terrain data due to the proliferation of data acquisition devices like 3D laser scanners poses challenges to spatial data analysis and computation. Among many spatial analyses and computations, polygon retrieval is a fundamental operation which is often performed under real-time constraints. However, existing sequential algorithms fail to meet this demand for larger sizes of terrain data. Motivated by the MapReduce programming model, a well-adopted large-scale parallel data processing technique, we present a MapReduce-based polygon retrieval algorithm designed with the objective of reducing the IO and CPU loads of spatial data processing. By indexing the data based on a quad-tree approach, a significant amount of unneeded data is filtered in the filtering stage and it reduces the IO overhead. The indexed data also facilitates querying the relationship between the terrain data and query area in shorter time. The results of the experiments performed in our Hadoop cluster demonstrate that our algorithm performs significantly better than the existing distributed algorithms.
Wang, Zongrui; Dong, Huanli; Zou, Ye; Zhao, Qiang; Tan, Jiahui; Liu, Jie; Lu, Xiuqiang; Xiao, Jinchong; Zhang, Qichun; Hu, Wenping
2016-03-01
Poor charge injection and transport at the electrode/semiconductor contacts has been so far a severe performance hurdle for bottom-contact bottom-gate (BCBG) organic field-effect transistors (OFETs). Here, we have developed a simple, economic, and effective method to improve the carrier injection efficiency and obtained high-performance devices with low cost and widely used source/drain (S/D) electrodes (Ag/Cu). Through the simple electrode etching process, the work function of the electrodes is more aligned with the semiconductors, which reduces the energy barrier and facilitates the charge injection. Besides, the formation of the thinned electrode edge with desirable micro/nanostructures not only leads to the enlarged contact side area beneficial for the carrier injection but also is in favor of the molecular self-organization for continuous crystal growth at the contact/active channel interface, which is better for the charge injection and transport. These effects give rise to the great reduction of contact resistance and the amazing improvement of the low-cost bottom-contact configuration OFETs performance.
A baseline algorithm for face detection and tracking in video
NASA Astrophysics Data System (ADS)
Manohar, Vasant; Soundararajan, Padmanabhan; Korzhova, Valentina; Boonstra, Matthew; Goldgof, Dmitry; Kasturi, Rangachar
2007-10-01
Establishing benchmark datasets, performance metrics and baseline algorithms have considerable research significance in gauging the progress in any application domain. These primarily allow both users and developers to compare the performance of various algorithms on a common platform. In our earlier works, we focused on developing performance metrics and establishing a substantial dataset with ground truth for object detection and tracking tasks (text and face) in two video domains -- broadcast news and meetings. In this paper, we present the results of a face detection and tracking algorithm on broadcast news videos with the objective of establishing a baseline performance for this task-domain pair. The detection algorithm uses a statistical approach that was originally developed by Viola and Jones and later extended by Lienhart. The algorithm uses a feature set that is Haar-like and a cascade of boosted decision tree classifiers as a statistical model. In this work, we used the Intel Open Source Computer Vision Library (OpenCV) implementation of the Haar face detection algorithm. The optimal values for the tunable parameters of this implementation were found through an experimental design strategy commonly used in statistical analyses of industrial processes. Tracking was accomplished as continuous detection with the detected objects in two frames mapped using a greedy algorithm based on the distances between the centroids of bounding boxes. Results on the evaluation set containing 50 sequences (~ 2.5 mins.) using the developed performance metrics show good performance of the algorithm reflecting the state-of-the-art which makes it an appropriate choice as the baseline algorithm for the problem.
Spatial compression algorithm for the analysis of very large multivariate images
Keenan, Michael R.
2008-07-15
A method for spatially compressing data sets enables the efficient analysis of very large multivariate images. The spatial compression algorithms use a wavelet transformation to map an image into a compressed image containing a smaller number of pixels that retain the original image's information content. Image analysis can then be performed on a compressed data matrix consisting of a reduced number of significant wavelet coefficients. Furthermore, a block algorithm can be used for performing common operations more efficiently. The spatial compression algorithms can be combined with spectral compression algorithms to provide further computational efficiencies.
Spectral compression algorithms for the analysis of very large multivariate images
Keenan, Michael R.
2007-10-16
A method for spectrally compressing data sets enables the efficient analysis of very large multivariate images. The spectral compression algorithm uses a factored representation of the data that can be obtained from Principal Components Analysis or other factorization technique. Furthermore, a block algorithm can be used for performing common operations more efficiently. An image analysis can be performed on the factored representation of the data, using only the most significant factors. The spectral compression algorithm can be combined with a spatial compression algorithm to provide further computational efficiencies.
Zhou, Yongquan; Xie, Jian; Li, Liangliang; Ma, Mingzhi
2014-01-01
Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of cloud model to depict the qualitative concept: "bats approach their prey." Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the cloud model bat algorithm has good performance on functions optimization. PMID:24967425
Shin, Ho-Cheol; Bae, Jong Seok; Jin, Han-Young; Seo, Jeong-Sook; Yang, Tae-Hyun; Kim, Dae-Kyeong; Cho, Kyoung-Im; Kim, Bo-Hyun; Park, Yong Hyun; Je, Hyung-Gon; Kim, Dong-Soo
2016-01-01
Background and Objectives Intravascular ultrasound (IVUS)-guided percutaneous coronary intervention frequently results in unnecessary stenting due to the low positive predictive value of IVUS-derived minimal lumen area (MLA) for identification of functionally significant coronary stenosis. We appraised the diagnostic accuracy of IVUS-derived MLA compared with the fractional flow reserve (FFR) to assess intermediate coronary stenosis. Subjects and Methods We searched MEDLINE and Cochrane databases for studies using IVUS and FFR methods to establish the best MLA cut-off values to predict significant non-left main coronary artery stenosis. Summary estimates were obtained using a random-effects model. Results The 17 studies used in our analysis enrolled 3920 patients with 4267 lesions. The weighted overall mean MLA cut-off value was 2.58 mm2. The pooled MLA sensitivity that predicted functionally significant coronary stenosis was 0.75 (confidence interval [CI]: 0.72 to 0.77) and the specificity was 0.66 (CI: 0.64 to 0.68). The positive likelihood ratio (LR) was 2.33 (CI: 2.06 to 2.63) and LR (-) was 0.33 (CI: 0.26 to 0.42). The pooled diagnostic odds ratio (DOR) was 7.53 (CI: 5.26 to 10.76) and the area under the summary receiver operating characteristic curve for all the trials was 0.782 with a Q point of 0.720. Meta-regression analysis demonstrated that an FFR cut-off point of 0.75 was associated with a four times higher diagnostic accuracy compared to that of 0.80 (relative DOR: 3.92; 95% CI: 1.25 to 12.34). Conclusion IVUS-derived MLA has limited diagnostic accuracy and needs careful interpretation to correlate with functionally significant non-left main coronary artery stenosis. PMID:27721852
Cuschieri, Kate; Geraets, Daan; Cuzick, Jack; Cadman, Louise; Moore, Catherine; Vanden Broeck, Davy; Padalko, Elisaveta; Quint, Wim; Arbyn, Marc
2016-09-01
The Validation of Human Papillomavirus (HPV) Genotyping Tests (VALGENT) studies offer an opportunity to clinically validate HPV assays for use in primary screening for cervical cancer and also provide a framework for the comparison of analytical and type-specific performance. Through VALGENT, we assessed the performance of the cartridge-based Xpert HPV assay (Xpert HPV), which detects 14 high-risk (HR) types and resolves HPV16 and HPV18/45. Samples from women attending the United Kingdom cervical screening program enriched with cytologically abnormal samples were collated. All had been previously tested by a clinically validated standard comparator test (SCT), the GP5+/6+ enzyme immunoassay (EIA). The clinical sensitivity and specificity of the Xpert HPV for the detection of cervical intraepithelial neoplasia grade 2 or higher (CIN2+) and CIN3+ relative to those of the SCT were assessed as were the inter- and intralaboratory reproducibilities according to international criteria for test validation. Type concordance for HPV16 and HPV18/45 between the Xpert HPV and the SCT was also analyzed. The Xpert HPV detected 94% of CIN2+ and 98% of CIN3+ lesions among all screened women and 90% of CIN2+ and 96% of CIN3+ lesions in women 30 years and older. The specificity for CIN1 or less (≤CIN1) was 83% (95% confidence interval [CI], 80 to 85%) in all women and 88% (95% CI, 86 to 91%) in women 30 years and older. Inter- and intralaboratory agreements for the Xpert HPV were 98% and 97%, respectively. The kappa agreements for HPV16 and HPV18/45 between the clinically validated reference test (GP5+/6+ LMNX) and the Xpert HPV were 0.92 and 0.91, respectively. The clinical performance and reproducibility of the Xpert HPV are comparable to those of well-established HPV assays and fulfill the criteria for use in primary cervical cancer screening.
Social significance of community structure: Statistical view
NASA Astrophysics Data System (ADS)
Li, Hui-Jia; Daniels, Jasmine J.
2015-01-01
Community structure analysis is a powerful tool for social networks that can simplify their topological and functional analysis considerably. However, since community detection methods have random factors and real social networks obtained from complex systems always contain error edges, evaluating the significance of a partitioned community structure is an urgent and important question. In this paper, integrating the specific characteristics of real society, we present a framework to analyze the significance of a social community. The dynamics of social interactions are modeled by identifying social leaders and corresponding hierarchical structures. Instead of a direct comparison with the average outcome of a random model, we compute the similarity of a given node with the leader by the number of common neighbors. To determine the membership vector, an efficient community detection algorithm is proposed based on the position of the nodes and their corresponding leaders. Then, using a log-likelihood score, the tightness of the community can be derived. Based on the distribution of community tightness, we establish a connection between p -value theory and network analysis, and then we obtain a significance measure of statistical form . Finally, the framework is applied to both benchmark networks and real social networks. Experimental results show that our work can be used in many fields, such as determining the optimal number of communities, analyzing the social significance of a given community, comparing the performance among various algorithms, etc.
Influence of timing algorithm on brachialankle pulse wave velocity measurement.
Sun, Xin; Li, Ke; Ren, Hongwei; Li, Peng; Wang, Xinpei; Liu, Changchun
2014-01-01
The baPWV measurement is a non-invasive and convenient technique in an assessment of arterial stiffness. Despite its widespread application, the influence of different timing algorithms is still unclear. The present study was conducted to investigate the influence of six timing algorithms (MIN, MAX, D1, D2, MDP and INS) on the baPWV measurement and to evaluate the performance of them. Forty-five CAD patients and fifty-five healthy subjects were recruited in this study. A PVR acquisition apparatus was built up for baPWV measurement. The baPWV and other related parameters were calculated separately by the six timing algorithms. The influence and performance of the six algorithms was analyzed. The six timing algorithms generate significantly different baPWV values (left: F=29.036, P<0.001; right: F=40.076, P<0.001). In terms of reproducibility, the MAX has significantly higher CV value (≥ 18.6%) than the other methods, while the INS has the lowest CV value (≤ 2.7%). On the performance of classification, the INS produces the highest AUC values (left: 0.854; right: 0.872). The MIN and D2 also have a passable performance (AUC > 0.8). The choice of timing algorithm affects baPWV values and the quality of measurement. The INS method is recommended for baPWV measurement.
Investigation of registration algorithms for the automatic tile processing system
NASA Technical Reports Server (NTRS)
Tamir, Dan E.
1995-01-01
The Robotic Tile Inspection System (RTPS), under development in NASA-KSC, is expected to automate the processes of post-flight re-water-proofing and the process of inspection of the Shuttle heat absorbing tiles. An important task of the robot vision sub-system is to register the 'real-world' coordinates with the coordinates of the robot model of the Shuttle tiles. The model coordinates relate to a tile data-base and pre-flight tile-images. In the registration process, current (post-flight) images are aligned with pre-flight images to detect the rotation and translation displacement required for the coordinate systems rectification. The research activities performed this summer included study and evaluation of the registration algorithm that is currently implemented by the RTPS, as well as, investigation of the utility of other registration algorithms. It has been found that the current algorithm is not robust enough. This algorithm has a success rate of less than 80% and is, therefore, not suitable for complying with the requirements of the RTPS. Modifications to the current algorithm has been developed and tested. These modifications can improve the performance of the registration algorithm in a significant way. However, this improvement is not sufficient to satisfy system requirements. A new algorithm for registration has been developed and tested. This algorithm presented very high degree of robustness with success rate of 96%.
Robust facial expression recognition algorithm based on local metric learning
NASA Astrophysics Data System (ADS)
Jiang, Bin; Jia, Kebin
2016-01-01
In facial expression recognition tasks, different facial expressions are often confused with each other. Motivated by the fact that a learned metric can significantly improve the accuracy of classification, a facial expression recognition algorithm based on local metric learning is proposed. First, k-nearest neighbors of the given testing sample are determined from the total training data. Second, chunklets are selected from the k-nearest neighbors. Finally, the optimal transformation matrix is computed by maximizing the total variance between different chunklets and minimizing the total variance of instances in the same chunklet. The proposed algorithm can find the suitable distance metric for every testing sample and improve the performance on facial expression recognition. Furthermore, the proposed algorithm can be used for vector-based and matrix-based facial expression recognition. Experimental results demonstrate that the proposed algorithm could achieve higher recognition rates and be more robust than baseline algorithms on the JAFFE, CK, and RaFD databases.
Development and Evaluation of Algorithms for Breath Alcohol Screening
Ljungblad, Jonas; Hök, Bertil; Ekström, Mikael
2016-01-01
Breath alcohol screening is important for traffic safety, access control and other areas of health promotion. A family of sensor devices useful for these purposes is being developed and evaluated. This paper is focusing on algorithms for the determination of breath alcohol concentration in diluted breath samples using carbon dioxide to compensate for the dilution. The examined algorithms make use of signal averaging, weighting and personalization to reduce estimation errors. Evaluation has been performed by using data from a previously conducted human study. It is concluded that these features in combination will significantly reduce the random error compared to the signal averaging algorithm taken alone. PMID:27043576
Development and Evaluation of Algorithms for Breath Alcohol Screening.
Ljungblad, Jonas; Hök, Bertil; Ekström, Mikael
2016-01-01
Breath alcohol screening is important for traffic safety, access control and other areas of health promotion. A family of sensor devices useful for these purposes is being developed and evaluated. This paper is focusing on algorithms for the determination of breath alcohol concentration in diluted breath samples using carbon dioxide to compensate for the dilution. The examined algorithms make use of signal averaging, weighting and personalization to reduce estimation errors. Evaluation has been performed by using data from a previously conducted human study. It is concluded that these features in combination will significantly reduce the random error compared to the signal averaging algorithm taken alone. PMID:27043576
NASA Astrophysics Data System (ADS)
Su, Yu-Huei; Liu, Ying-Ling; Sun, Yi-Ming; Lai, Juin-Yih; Guiver, Michael D.; Gao, Yan
Sulfonated poly(phthalazinone ether ketone) (sPPEK) with a degree of sulfonation of 1.23 was mixed with silica nanoparticles to form hybrid materials for using as proton exchange membranes. The nanoparticles were found homogeneously dispersed in the polymer matrix and a high 30 phr (parts per hundred resin) loading of silica nanoparticles can be achieved. The hybrid membranes exhibited improved swelling behavior, thermal stability, and mechanical properties. The methanol crossover behavior of the membrane was also depressed such that these membranes are suitable for a high methanol concentration in feed (3 M) in cell test. The membrane with 5 phr silica nanoparticles showed an open cell potential of 0.6 V and an optimum power density of 52.9 mW cm -2 at a current density of 264.6 mA cm -2, which is better than the performance of the pristine sPPEK membrane and Nafion ® 117.
Parallelization of Edge Detection Algorithm using MPI on Beowulf Cluster
NASA Astrophysics Data System (ADS)
Haron, Nazleeni; Amir, Ruzaini; Aziz, Izzatdin A.; Jung, Low Tan; Shukri, Siti Rohkmah
In this paper, we present the design of parallel Sobel edge detection algorithm using Foster's methodology. The parallel algorithm is implemented using MPI message passing library and master/slave algorithm. Every processor performs the same sequential algorithm but on different part of the image. Experimental results conducted on Beowulf cluster are presented to demonstrate the performance of the parallel algorithm.
Parallelism of the SANDstorm hash algorithm.
Torgerson, Mark Dolan; Draelos, Timothy John; Schroeppel, Richard Crabtree
2009-09-01
Mainstream cryptographic hashing algorithms are not parallelizable. This limits their speed and they are not able to take advantage of the current trend of being run on multi-core platforms. Being limited in speed limits their usefulness as an authentication mechanism in secure communications. Sandia researchers have created a new cryptographic hashing algorithm, SANDstorm, which was specifically designed to take advantage of multi-core processing and be parallelizable on a wide range of platforms. This report describes a late-start LDRD effort to verify the parallelizability claims of the SANDstorm designers. We have shown, with operating code and bench testing, that the SANDstorm algorithm may be trivially parallelized on a wide range of hardware platforms. Implementations using OpenMP demonstrates a linear speedup with multiple cores. We have also shown significant performance gains with optimized C code and the use of assembly instructions to exploit particular platform capabilities.
Kassianov, Evgueni I.; Flynn, Connor J.; Koontz, Annette S.; Sivaraman, Chitra; Barnard, James C.
2013-09-11
Well-known cloud-screening algorithms, which are designed to remove cloud-contaminated aerosol optical depths (AOD) from AOD measurements, have shown great performance at many middle-to-low latitude sites around the world. However, they may occasionally fail under challenging observational conditions, such as when the sun is low (near the horizon) or when optically thin clouds with small spatial inhomogeneity occur. Such conditions have been observed quite frequently at the high-latitude Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) sites. A slightly modified cloud-screening version of the standard algorithm is proposed here with a focus on the ARM-supported Multifilter Rotating Shadowband Radiometer (MFRSR) and Normal Incidence Multifilter Radiometer (NIMFR) data. The modified version uses approximately the same techniques as the standard algorithm, but it additionally examines the magnitude of the slant-path line of sight transmittance and eliminates points when the observed magnitude is below a specified threshold. Substantial improvement of the multi-year (1999-2012) aerosol product (AOD and its Angstrom exponent) is shown for the NSA sites when the modified version is applied. Moreover, this version reproduces the AOD product at the ARM Southern Great Plains (SGP) site, which was originally generated by the standard cloud-screening algorithms. The proposed minor modification is easy to implement and its application to existing and future cloud-screening algorithms can be particularly beneficial for challenging observational conditions.
Saleeb, A F; Dhakal, B; Owusu-Danquah, J S
2015-07-01
This work is focused on the detailed computer simulation of the key stages involved in a shape memory alloy (SMA) osteosynthesis bone stapling procedure. To this end, a recently developed three-dimensional constitutive SMA material model was characterized from test data of three simple uniaxial-isothermal-tension experiments for powder metallurgically processed nickel-rich NiTi (PM/NiTi-P) material. The calibrated model was subsequently used under the complex, thermomechanical loading conditions involved in the surgical procedure using the body-temperature-activated PM/NiTi-P bone staple. Our aim here is to assess the immediate and post-surgical performance characteristics of the stapling operation using the material model. From this study: (1) it was found that adequate compressive forces were developed by the PM/NiTi-P bone staple, with the tendency of this force to even increase under sustained thermal loading due to the intrinsic "inverse relaxation phenomena" in the SMA material, (2) the simulation results correlated well with those from experimental measurements, (3) the body-temperature-activated PM/NiTi-P staple was proved to be clinically viable, providing a stable clamping force needed for speedy coaptation of the fractured bones, and (4) these realistic assessments crucially depend on the use of suitable and comprehensive SMA material models.
Optimisation of nonlinear motion cueing algorithm based on genetic algorithm
NASA Astrophysics Data System (ADS)
Asadi, Houshyar; Mohamed, Shady; Rahim Zadeh, Delpak; Nahavandi, Saeid
2015-04-01
Motion cueing algorithms (MCAs) are playing a significant role in driving simulators, aiming to deliver the most accurate human sensation to the simulator drivers compared with a real vehicle driver, without exceeding the physical limitations of the simulator. This paper provides the optimisation design of an MCA for a vehicle simulator, in order to find the most suitable washout algorithm parameters, while respecting all motion platform physical limitations, and minimising human perception error between real and simulator driver. One of the main limitations of the classical washout filters is that it is attuned by the worst-case scenario tuning method. This is based on trial and error, and is effected by driving and programmers experience, making this the most significant obstacle to full motion platform utilisation. This leads to inflexibility of the structure, production of false cues and makes the resulting simulator fail to suit all circumstances. In addition, the classical method does not take minimisation of human perception error and physical constraints into account. Production of motion cues and the impact of different parameters of classical washout filters on motion cues remain inaccessible for designers for this reason. The aim of this paper is to provide an optimisation method for tuning the MCA parameters, based on nonlinear filtering and genetic algorithms. This is done by taking vestibular sensation error into account between real and simulated cases, as well as main dynamic limitations, tilt coordination and correlation coefficient. Three additional compensatory linear blocks are integrated into the MCA, to be tuned in order to modify the performance of the filters successfully. The proposed optimised MCA is implemented in MATLAB/Simulink software packages. The results generated using the proposed method show increased performance in terms of human sensation, reference shape tracking and exploiting the platform more efficiently without reaching
Xu, Nuoxin; Hu, Liang; Zhang, Qilong; Xiao, Xingrong; Yang, Hui; Yu, Enjie
2015-12-16
In this study, we report a feasible strategy for fabricating high-dielectric-constant polymer composites for applications in energy storage devices and embedded capacitors. Hierarchical flower-like TiO2 particles were prepared via a facile solvothermal process and incorporated into the P(VDF-HFP) matrix. The temperature and frequency dependent dielectric properties of flower-like TiO2/P(VDF-HFP) composites as well as commercial TiO2/P(VDF-HFP) composites were investigated. The results reveal that the flower-like TiO2 particles are more effective in increasing the dielectric constant of P(VDF-HFP) when compared with commercial TiO2. Typically, the dielectric constant of the P(VDF-HFP) composite filled with 20 vol % flower-like TiO2 reaches 83.1 at 100 Hz, in contrast to 43.4 for the composite filled with 20 vol % commercial TiO2 and 11.3 for pristine P(VDF-HFP). Also, the flower-like TiO2-filled composites exhibit similar characteristic breakdown strengths to their commercial TiO2-filled counterparts. The significant improvement in the dielectric constant could be attributed to the enhancement of Maxwell-Wagner-Sillars polarization, which originates from the sophisticated morphology of flower-like TiO2 particles.
Chen, Jun; Quan, Wenting; Cui, Tingwei
2015-01-01
In this study, two sample semi-analytical algorithms and one new unified multi-band semi-analytical algorithm (UMSA) for estimating chlorophyll-a (Chla) concentration were constructed by specifying optimal wavelengths. The three sample semi-analytical algorithms, including the three-band semi-analytical algorithm (TSA), four-band semi-analytical algorithm (FSA), and UMSA algorithm, were calibrated and validated by the dataset collected in the Yellow River Estuary between September 1 and 10, 2009. By comparing of the accuracy of assessment of TSA, FSA, and UMSA algorithms, it was found that the UMSA algorithm had a superior performance in comparison with the two other algorithms, TSA and FSA. Using the UMSA algorithm in retrieving Chla concentration in the Yellow River Estuary decreased by 25.54% NRMSE (normalized root mean square error) when compared with the FSA algorithm, and 29.66% NRMSE in comparison with the TSA algorithm. These are very significant improvements upon previous methods. Additionally, the study revealed that the TSA and FSA algorithms are merely more specific forms of the UMSA algorithm. Owing to the special form of the UMSA algorithm, if the same bands were used for both the TSA and UMSA algorithms or FSA and UMSA algorithms, the UMSA algorithm would theoretically produce superior results in comparison with the TSA and FSA algorithms. Thus, good results may also be produced if the UMSA algorithm were to be applied for predicting Chla concentration for datasets of Gitelson et al. (2008) and Le et al. (2009).
Parallel algorithms for unconstrained optimizations by multisplitting
He, Qing
1994-12-31
In this paper a new parallel iterative algorithm for unconstrained optimization using the idea of multisplitting is proposed. This algorithm uses the existing sequential algorithms without any parallelization. Some convergence and numerical results for this algorithm are presented. The experiments are performed on an Intel iPSC/860 Hyper Cube with 64 nodes. It is interesting that the sequential implementation on one node shows that if the problem is split properly, the algorithm converges much faster than one without splitting.
NASA Astrophysics Data System (ADS)
Bak, J.; Liu, X.; Kim, J. H.; Chance, K.; Haffner, D. P.
2015-01-01
The accuracy of total ozone computed from the Smithsonian Astrophysical Observatory (SAO) optimal estimation (OE) ozone profile algorithm (SOE) applied to the Ozone Monitoring Instrument (OMI) is assessed through comparisons with ground-based Brewer spectrometer measurements from 2005 to 2008. We also compare the three OMI operational ozone products, derived from the NASA Total Ozone Mapping Spectrometer (TOMS) algorithm, the KNMI (Royal Netherlands Meteorological Institute) differential optical absorption spectroscopy (DOAS) algorithm, and KNMI's Optimal Estimation (KOE) algorithm. The best agreement is observed between SAO and Brewer, with a mean difference of within 1% at most individual stations. The KNMI OE algorithm systematically overestimates Brewer total ozone by 2% at low and mid-latitudes and 5% at high latitudes while the TOMS and DOAS algorithms underestimate it by ~1.65% on average. Standard deviations of ~1.8% are calculated for both SOE and TOMS, but DOAS and KOE have higher values of 2.2% and 2.6%, respectively. The stability of the SOE algorithm is found to have insignificant dependence on viewing geometry, cloud parameters, or total ozone column. In comparison, the KOE-Brewer differences are significantly correlated with solar and viewing zenith angles and show significant deviations depending on cloud parameters and total ozone amount. The TOMS algorithm exhibits similar stability to SOE with respect to viewing geometry and total column ozone, but has stronger cloud parameter dependence. The dependence of DOAS on observational geometry and geophysical conditions is marginal compared to KOE, but is distinct compared to the SOE and TOMS algorithms. Comparisons of all four OMI products with Brewer show no apparent long-term drift, but seasonal features are evident, especially for KOE and TOMS. The substantial differences in the KOE vs. SOE algorithm performance cannot be sufficiently explained by the use of soft calibration (in SOE) and the use of
Hash based parallel algorithms for mining association rules
Shintani, Takahiko; Kitsuregawa, Masaru
1996-12-31
In this paper, we propose four parallel algorithms (NPA, SPA, HPA and RPA-ELD) for mining association rules on shared-nothing parallel machines to improve its performance. In NPA, candidate itemsets are just copied amongst all the processors, which can lead to memory overflow for large transaction databases. The remaining three algorithms partition the candidate itemsets over the processors. If it is partitioned simply (SPA), transaction data has to be broadcast to all processors. HPA partitions the candidate itemsets using a hash function to eliminate broadcasting, which also reduces the comparison workload significantly. HPA-ELD fully utilizes the available memory space by detecting the extremely large itemsets and copying them, which is also very effective at flattering the load over the processors. We implemented these algorithms in a shared-nothing environment. Performance evaluations show that the best algorithm, HPA-ELD, attains good linearity on speedup ratio and is effective for handling skew.
Evolutionary pattern search algorithms
Hart, W.E.
1995-09-19
This paper defines a class of evolutionary algorithms called evolutionary pattern search algorithms (EPSAs) and analyzes their convergence properties. This class of algorithms is closely related to evolutionary programming, evolutionary strategie and real-coded genetic algorithms. EPSAs are self-adapting systems that modify the step size of the mutation operator in response to the success of previous optimization steps. The rule used to adapt the step size can be used to provide a stationary point convergence theory for EPSAs on any continuous function. This convergence theory is based on an extension of the convergence theory for generalized pattern search methods. An experimental analysis of the performance of EPSAs demonstrates that these algorithms can perform a level of global search that is comparable to that of canonical EAs. We also describe a stopping rule for EPSAs, which reliably terminated near stationary points in our experiments. This is the first stopping rule for any class of EAs that can terminate at a given distance from stationary points.
NASA Technical Reports Server (NTRS)
Caglayan, A. K.; Godiwala, P. M.; Morrell, F. R.
1986-01-01
The modifications to the design of a fault inferring nonlinear detection system (FINDS) algorithm to accommodate flight computer constraints and the resulting impact on the algorithm performance are summarized. An overview of the flight data-driven FINDS algorithm is presented. This is followed by a brief analysis of the effects of modifications to the algorithm on program size and execution speed. Significant improvements in estimation performance for the aircraft states and normal operating sensor biases, which have resulted from improved noise design parameters and a new steady-state wind model, are documented. The aircraft state and sensor bias estimation performances of the algorithm's extended Kalman filter are presented as a function of update frequency of the piecewise constant filter gains. The results of a new detection system strategy and failure detection performance, as a function of gain update frequency, are also presented.
Significant Improvement of Semiconducting Performance of the Diketopyrrolopyrrole-Quate