Algorithmic commonalities in the parallel environment

NASA Technical Reports Server (NTRS)

Mcanulty, Michael A.; Wainer, Michael S.

1987-01-01

The ultimate aim of this project was to analyze procedures from substantially different application areas to discover what is either common or peculiar in the process of conversion to the Massively Parallel Processor (MPP). Three areas were identified: molecular dynamic simulation, production systems (rule systems), and various graphics and vision algorithms. To date, only selected graphics procedures have been investigated. They are the most readily available, and produce the most visible results. These include simple polygon patch rendering, raycasting against a constructive solid geometric model, and stochastic or fractal based textured surface algorithms. Only the simplest of conversion strategies, mapping a major loop to the array, has been investigated so far. It is not entirely satisfactory.

On recent advances and future research directions for computational fluid dynamics

NASA Technical Reports Server (NTRS)

Baker, A. J.; Soliman, M. O.; Manhardt, P. D.

1986-01-01

This paper highlights some recent accomplishments regarding CFD numerical algorithm constructions for generation of discrete approximate solutions to classes of Reynolds-averaged Navier-Stokes equations. Following an overview of turbulent closure modeling, and development of appropriate conservation law systems, a Taylor weak-statement semi-discrete approximate solution algorithm is developed. Various forms for completion to the final linear algebra statement are cited, as are a range of candidate numerical linear algebra solution procedures. This development sequence emphasizes the key building blocks of a CFD RNS algorithm, including solution trial and test spaces, integration procedure and added numerical stability mechanisms. A range of numerical results are discussed focusing on key topics guiding future research directions.

78 FR 57639 - Request for Comments on Pediatric Planned Procedure Algorithm

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-19

... Comments on Pediatric Planned Procedure Algorithm AGENCY: Agency for Healthcare Research and Quality (AHRQ), HHS. ACTION: Notice of request for comments on pediatric planned procedure algorithm from the members... Quality (AHRQ) is requesting comments from the public on an algorithm for identifying pediatric planned...

Online Calibration of Polytomous Items Under the Generalized Partial Credit Model

PubMed Central

Zheng, Yi

2016-01-01

Online calibration is a technology-enhanced architecture for item calibration in computerized adaptive tests (CATs). Many CATs are administered continuously over a long term and rely on large item banks. To ensure test validity, these item banks need to be frequently replenished with new items, and these new items need to be pretested before being used operationally. Online calibration dynamically embeds pretest items in operational tests and calibrates their parameters as response data are gradually obtained through the continuous test administration. This study extends existing formulas, procedures, and algorithms for dichotomous item response theory models to the generalized partial credit model, a popular model for items scored in more than two categories. A simulation study was conducted to investigate the developed algorithms and procedures under a variety of conditions, including two estimation algorithms, three pretest item selection methods, three seeding locations, two numbers of score categories, and three calibration sample sizes. Results demonstrated acceptable estimation accuracy of the two estimation algorithms in some of the simulated conditions. A variety of findings were also revealed for the interacted effects of included factors, and recommendations were made respectively. PMID:29881063

Self-Cohering Airborne Distributed Array

DTIC Science & Technology

1988-06-01

F19628-84- C -0080 ft. ADDRESS (City, State, and ZIP Code) 10. SOURCE OF FUNDING NUMBERS PROGRAM PROJECT JTASK JWORK UNIT Hanscom APE MA 01731-5000...algorithms under consideration (including the newly developed algorithms). The algorithms are classified both according to the type c -f processing and...4.1 RADIO CAMERA DATA FORMAT AND PROCEDURES (FROM C -23) The range trace delivered by each antenna element is stonred as a rc’w of coimplex number-s

Comparison between variable and fixed dwell-time PN acquisition algorithms. [for synchronization in pseudonoise spread spectrum systems

NASA Technical Reports Server (NTRS)

Braun, W. R.

1981-01-01

Pseudo noise (PN) spread spectrum systems require a very accurate alignment between the PN code epochs at the transmitter and receiver. This synchronism is typically established through a two-step algorithm, including a coarse synchronization procedure and a fine synchronization procedure. A standard approach for the coarse synchronization is a sequential search over all code phases. The measurement of the power in the filtered signal is used to either accept or reject the code phase under test as the phase of the received PN code. This acquisition strategy, called a single dwell-time system, has been analyzed by Holmes and Chen (1977). A synopsis of the field of sequential analysis as it applies to the PN acquisition problem is provided. From this, the implementation of the variable dwell time algorithm as a sequential probability ratio test is developed. The performance of this algorithm is compared to the optimum detection algorithm and to the fixed dwell-time system.

Feature Screening in Ultrahigh Dimensional Cox's Model.

PubMed

Yang, Guangren; Yu, Ye; Li, Runze; Buu, Anne

Survival data with ultrahigh dimensional covariates such as genetic markers have been collected in medical studies and other fields. In this work, we propose a feature screening procedure for the Cox model with ultrahigh dimensional covariates. The proposed procedure is distinguished from the existing sure independence screening (SIS) procedures (Fan, Feng and Wu, 2010, Zhao and Li, 2012) in that the proposed procedure is based on joint likelihood of potential active predictors, and therefore is not a marginal screening procedure. The proposed procedure can effectively identify active predictors that are jointly dependent but marginally independent of the response without performing an iterative procedure. We develop a computationally effective algorithm to carry out the proposed procedure and establish the ascent property of the proposed algorithm. We further prove that the proposed procedure possesses the sure screening property. That is, with the probability tending to one, the selected variable set includes the actual active predictors. We conduct Monte Carlo simulation to evaluate the finite sample performance of the proposed procedure and further compare the proposed procedure and existing SIS procedures. The proposed methodology is also demonstrated through an empirical analysis of a real data example.

The development of flux-split algorithms for flows with non-equilibrium thermodynamics and chemical reactions

NASA Technical Reports Server (NTRS)

Grossman, B.; Cinella, P.

1988-01-01

A finite-volume method for the numerical computation of flows with nonequilibrium thermodynamics and chemistry is presented. A thermodynamic model is described which simplifies the coupling between the chemistry and thermodynamics and also results in the retention of the homogeneity property of the Euler equations (including all the species continuity and vibrational energy conservation equations). Flux-splitting procedures are developed for the fully coupled equations involving fluid dynamics, chemical production and thermodynamic relaxation processes. New forms of flux-vector split and flux-difference split algorithms are embodied in a fully coupled, implicit, large-block structure, including all the species conservation and energy production equations. Several numerical examples are presented, including high-temperature shock tube and nozzle flows. The methodology is compared to other existing techniques, including spectral and central-differenced procedures, and favorable comparisons are shown regarding accuracy, shock-capturing and convergence rates.

In-Trail Procedure (ITP) Algorithm Design

NASA Technical Reports Server (NTRS)

Munoz, Cesar A.; Siminiceanu, Radu I.

2007-01-01

The primary objective of this document is to provide a detailed description of the In-Trail Procedure (ITP) algorithm, which is part of the Airborne Traffic Situational Awareness In-Trail Procedure (ATSA-ITP) application. To this end, the document presents a high level description of the ITP Algorithm and a prototype implementation of this algorithm in the programming language C.

An affine projection algorithm using grouping selection of input vectors

NASA Astrophysics Data System (ADS)

Shin, JaeWook; Kong, NamWoong; Park, PooGyeon

2011-10-01

This paper present an affine projection algorithm (APA) using grouping selection of input vectors. To improve the performance of conventional APA, the proposed algorithm adjusts the number of the input vectors using two procedures: grouping procedure and selection procedure. In grouping procedure, the some input vectors that have overlapping information for update is grouped using normalized inner product. Then, few input vectors that have enough information for for coefficient update is selected using steady-state mean square error (MSE) in selection procedure. Finally, the filter coefficients update using selected input vectors. The experimental results show that the proposed algorithm has small steady-state estimation errors comparing with the existing algorithms.

The design of digital-adaptive controllers for VTOL aircraft

NASA Technical Reports Server (NTRS)

Stengel, R. F.; Broussard, J. R.; Berry, P. W.

1976-01-01

Design procedures for VTOL automatic control systems have been developed and are presented. Using linear-optimal estimation and control techniques as a starting point, digital-adaptive control laws have been designed for the VALT Research Aircraft, a tandem-rotor helicopter which is equipped for fully automatic flight in terminal area operations. These control laws are designed to interface with velocity-command and attitude-command guidance logic, which could be used in short-haul VTOL operations. Developments reported here include new algorithms for designing non-zero-set-point digital regulators, design procedures for rate-limited systems, and algorithms for dynamic control trim setting.

Surgical motion characterization in simulated needle insertion procedures

NASA Astrophysics Data System (ADS)

Holden, Matthew S.; Ungi, Tamas; Sargent, Derek; McGraw, Robert C.; Fichtinger, Gabor

2012-02-01

PURPOSE: Evaluation of surgical performance in image-guided needle insertions is of emerging interest, to both promote patient safety and improve the efficiency and effectiveness of training. The purpose of this study was to determine if a Markov model-based algorithm can more accurately segment a needle-based surgical procedure into its five constituent tasks than a simple threshold-based algorithm. METHODS: Simulated needle trajectories were generated with known ground truth segmentation by a synthetic procedural data generator, with random noise added to each degree of freedom of motion. The respective learning algorithms were trained, and then tested on different procedures to determine task segmentation accuracy. In the threshold-based algorithm, a change in tasks was detected when the needle crossed a position/velocity threshold. In the Markov model-based algorithm, task segmentation was performed by identifying the sequence of Markov models most likely to have produced the series of observations. RESULTS: For amplitudes of translational noise greater than 0.01mm, the Markov model-based algorithm was significantly more accurate in task segmentation than the threshold-based algorithm (82.3% vs. 49.9%, p<0.001 for amplitude 10.0mm). For amplitudes less than 0.01mm, the two algorithms produced insignificantly different results. CONCLUSION: Task segmentation of simulated needle insertion procedures was improved by using a Markov model-based algorithm as opposed to a threshold-based algorithm for procedures involving translational noise.

Parabolized Navier-Stokes solutions of separation and trailing-edge flows

NASA Technical Reports Server (NTRS)

Brown, J. L.

1983-01-01

A robust, iterative solution procedure is presented for the parabolized Navier-Stokes or higher order boundary layer equations as applied to subsonic viscous-inviscid interaction flows. The robustness of the present procedure is due, in part, to an improved algorithmic formulation. The present formulation is based on a reinterpretation of stability requirements for this class of algorithms and requires only second order accurate backward or central differences for all streamwise derivatives. Upstream influence is provided for through the algorithmic formulation and iterative sweeps in x. The primary contribution to robustness, however, is the boundary condition treatment, which imposes global constraints to control the convergence path. Discussed are successful calculations of subsonic, strong viscous-inviscid interactions, including separation. These results are consistent with Navier-Stokes solutions and triple deck theory.

Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities

PubMed Central

Li, Jun-qing; Pan, Quan-ke; Mao, Kun

2014-01-01

A hybrid algorithm which combines particle swarm optimization (PSO) and iterated local search (ILS) is proposed for solving the hybrid flowshop scheduling (HFS) problem with preventive maintenance (PM) activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron's benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm. PMID:24883414

Model of ballistic targets' dynamics used for trajectory tracking algorithms

NASA Astrophysics Data System (ADS)

Okoń-FÄ fara, Marta; Kawalec, Adam; Witczak, Andrzej

2017-04-01

There are known only few ballistic object tracking algorithms. To develop such algorithms and to its further testing, it is necessary to implement possibly simple and reliable objects' dynamics model. The article presents the dynamics' model of a tactical ballistic missile (TBM) including the three stages of flight: the boost stage and two passive stages - the ascending one and the descending one. Additionally, the procedure of transformation from the local coordinate system to the polar-radar oriented and the global is presented. The prepared theoretical data may be used to determine the tracking algorithm parameters and to its further verification.

An unsupervised classification approach for analysis of Landsat data to monitor land reclamation in Belmont county, Ohio

NASA Technical Reports Server (NTRS)

Brumfield, J. O.; Bloemer, H. H. L.; Campbell, W. J.

1981-01-01

Two unsupervised classification procedures for analyzing Landsat data used to monitor land reclamation in a surface mining area in east central Ohio are compared for agreement with data collected from the corresponding locations on the ground. One procedure is based on a traditional unsupervised-clustering/maximum-likelihood algorithm sequence that assumes spectral groupings in the Landsat data in n-dimensional space; the other is based on a nontraditional unsupervised-clustering/canonical-transformation/clustering algorithm sequence that not only assumes spectral groupings in n-dimensional space but also includes an additional feature-extraction technique. It is found that the nontraditional procedure provides an appreciable improvement in spectral groupings and apparently increases the level of accuracy in the classification of land cover categories.

Evaluation of algorithms to identify incident cancer cases by using French health administrative databases.

PubMed

Ajrouche, Aya; Estellat, Candice; De Rycke, Yann; Tubach, Florence

2017-08-01

Administrative databases are increasingly being used in cancer observational studies. Identifying incident cancer in these databases is crucial. This study aimed to develop algorithms to estimate cancer incidence by using health administrative databases and to examine the accuracy of the algorithms in terms of national cancer incidence rates estimated from registries. We identified a cohort of 463 033 participants on 1 January 2012 in the Echantillon Généraliste des Bénéficiaires (EGB; a representative sample of the French healthcare insurance system). The EGB contains data on long-term chronic disease (LTD) status, reimbursed outpatient treatments and procedures, and hospitalizations (including discharge diagnoses, and costly medical procedures and drugs). After excluding cases of prevalent cancer, we applied 15 algorithms to estimate the cancer incidence rates separately for men and women in 2012 and compared them to the national cancer incidence rates estimated from French registries by indirect age and sex standardization. The most accurate algorithm for men combined information from LTD status, outpatient anticancer drugs, radiotherapy sessions and primary or related discharge diagnosis of cancer, although it underestimated the cancer incidence (standardized incidence ratio (SIR) 0.85 [0.80-0.90]). For women, the best algorithm used the same definition of the algorithm for men but restricted hospital discharge to only primary or related diagnosis with an additional inpatient procedure or drug reimbursement related to cancer and gave comparable estimates to those from registries (SIR 1.00 [0.94-1.06]). The algorithms proposed could be used for cancer incidence monitoring and for future etiological cancer studies involving French healthcare databases. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Characterization of robotics parallel algorithms and mapping onto a reconfigurable SIMD machine

NASA Technical Reports Server (NTRS)

Lee, C. S. G.; Lin, C. T.

1989-01-01

The kinematics, dynamics, Jacobian, and their corresponding inverse computations are six essential problems in the control of robot manipulators. Efficient parallel algorithms for these computations are discussed and analyzed. Their characteristics are identified and a scheme on the mapping of these algorithms to a reconfigurable parallel architecture is presented. Based on the characteristics including type of parallelism, degree of parallelism, uniformity of the operations, fundamental operations, data dependencies, and communication requirement, it is shown that most of the algorithms for robotic computations possess highly regular properties and some common structures, especially the linear recursive structure. Moreover, they are well-suited to be implemented on a single-instruction-stream multiple-data-stream (SIMD) computer with reconfigurable interconnection network. The model of a reconfigurable dual network SIMD machine with internal direct feedback is introduced. A systematic procedure internal direct feedback is introduced. A systematic procedure to map these computations to the proposed machine is presented. A new scheduling problem for SIMD machines is investigated and a heuristic algorithm, called neighborhood scheduling, that reorders the processing sequence of subtasks to reduce the communication time is described. Mapping results of a benchmark algorithm are illustrated and discussed.

TRACON Aircraft Arrival Planning and Optimization Through Spatial Constraint Satisfaction

NASA Technical Reports Server (NTRS)

Bergh, Christopher P.; Krzeczowski, Kenneth J.; Davis, Thomas J.; Denery, Dallas G. (Technical Monitor)

1995-01-01

A new aircraft arrival planning and optimization algorithm has been incorporated into the Final Approach Spacing Tool (FAST) in the Center-TRACON Automation System (CTAS) developed at NASA-Ames Research Center. FAST simulations have been conducted over three years involving full-proficiency, level five air traffic controllers from around the United States. From these simulations an algorithm, called Spatial Constraint Satisfaction, has been designed, coded, undergone testing, and soon will begin field evaluation at the Dallas-Fort Worth and Denver International airport facilities. The purpose of this new design is an attempt to show that the generation of efficient and conflict free aircraft arrival plans at the runway does not guarantee an operationally acceptable arrival plan upstream from the runway -information encompassing the entire arrival airspace must be used in order to create an acceptable aircraft arrival plan. This new design includes functions available previously but additionally includes necessary representations of controller preferences and workload, operationally required amounts of extra separation, and integrates aircraft conflict resolution. As a result, the Spatial Constraint Satisfaction algorithm produces an optimized aircraft arrival plan that is more acceptable in terms of arrival procedures and air traffic controller workload. This paper discusses the current Air Traffic Control arrival planning procedures, previous work in this field, the design of the Spatial Constraint Satisfaction algorithm, and the results of recent evaluations of the algorithm.

Parallel Algorithms and Patterns

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robey, Robert W.

2016-06-16

This is a powerpoint presentation on parallel algorithms and patterns. A parallel algorithm is a well-defined, step-by-step computational procedure that emphasizes concurrency to solve a problem. Examples of problems include: Sorting, searching, optimization, matrix operations. A parallel pattern is a computational step in a sequence of independent, potentially concurrent operations that occurs in diverse scenarios with some frequency. Examples are: Reductions, prefix scans, ghost cell updates. We only touch on parallel patterns in this presentation. It really deserves its own detailed discussion which Gabe Rockefeller would like to develop.

A selective-update affine projection algorithm with selective input vectors

NASA Astrophysics Data System (ADS)

Kong, NamWoong; Shin, JaeWook; Park, PooGyeon

2011-10-01

This paper proposes an affine projection algorithm (APA) with selective input vectors, which based on the concept of selective-update in order to reduce estimation errors and computations. The algorithm consists of two procedures: input- vector-selection and state-decision. The input-vector-selection procedure determines the number of input vectors by checking with mean square error (MSE) whether the input vectors have enough information for update. The state-decision procedure determines the current state of the adaptive filter by using the state-decision criterion. As the adaptive filter is in transient state, the algorithm updates the filter coefficients with the selected input vectors. On the other hand, as soon as the adaptive filter reaches the steady state, the update procedure is not performed. Through these two procedures, the proposed algorithm achieves small steady-state estimation errors, low computational complexity and low update complexity for colored input signals.

featsel: A framework for benchmarking of feature selection algorithms and cost functions

NASA Astrophysics Data System (ADS)

Reis, Marcelo S.; Estrela, Gustavo; Ferreira, Carlos Eduardo; Barrera, Junior

In this paper, we introduce featsel, a framework for benchmarking of feature selection algorithms and cost functions. This framework allows the user to deal with the search space as a Boolean lattice and has its core coded in C++ for computational efficiency purposes. Moreover, featsel includes Perl scripts to add new algorithms and/or cost functions, generate random instances, plot graphs and organize results into tables. Besides, this framework already comes with dozens of algorithms and cost functions for benchmarking experiments. We also provide illustrative examples, in which featsel outperforms the popular Weka workbench in feature selection procedures on data sets from the UCI Machine Learning Repository.

A systematic review of validated methods for identifying patients with rheumatoid arthritis using administrative or claims data.

PubMed

Chung, Cecilia P; Rohan, Patricia; Krishnaswami, Shanthi; McPheeters, Melissa L

2013-12-30

To review the evidence supporting the validity of billing, procedural, or diagnosis code, or pharmacy claim-based algorithms used to identify patients with rheumatoid arthritis (RA) in administrative and claim databases. We searched the MEDLINE database from 1991 to September 2012 using controlled vocabulary and key terms related to RA and reference lists of included studies were searched. Two investigators independently assessed the full text of studies against pre-determined inclusion criteria and extracted the data. Data collected included participant and algorithm characteristics. Nine studies reported validation of computer algorithms based on International Classification of Diseases (ICD) codes with or without free-text, medication use, laboratory data and the need for a diagnosis by a rheumatologist. These studies yielded positive predictive values (PPV) ranging from 34 to 97% to identify patients with RA. Higher PPVs were obtained with the use of at least two ICD and/or procedure codes (ICD-9 code 714 and others), the requirement of a prescription of a medication used to treat RA, or requirement of participation of a rheumatologist in patient care. For example, the PPV increased from 66 to 97% when the use of disease-modifying antirheumatic drugs and the presence of a positive rheumatoid factor were required. There have been substantial efforts to propose and validate algorithms to identify patients with RA in automated databases. Algorithms that include more than one code and incorporate medications or laboratory data and/or required a diagnosis by a rheumatologist may increase the PPV. Copyright © 2013 Elsevier Ltd. All rights reserved.

Motion Cueing Algorithm Development: New Motion Cueing Program Implementation and Tuning

NASA Technical Reports Server (NTRS)

Houck, Jacob A. (Technical Monitor); Telban, Robert J.; Cardullo, Frank M.; Kelly, Lon C.

2005-01-01

A computer program has been developed for the purpose of driving the NASA Langley Research Center Visual Motion Simulator (VMS). This program includes two new motion cueing algorithms, the optimal algorithm and the nonlinear algorithm. A general description of the program is given along with a description and flowcharts for each cueing algorithm, and also descriptions and flowcharts for subroutines used with the algorithms. Common block variable listings and a program listing are also provided. The new cueing algorithms have a nonlinear gain algorithm implemented that scales each aircraft degree-of-freedom input with a third-order polynomial. A description of the nonlinear gain algorithm is given along with past tuning experience and procedures for tuning the gain coefficient sets for each degree-of-freedom to produce the desired piloted performance. This algorithm tuning will be needed when the nonlinear motion cueing algorithm is implemented on a new motion system in the Cockpit Motion Facility (CMF) at the NASA Langley Research Center.

Cloud Screening and Quality Control Algorithm for Star Photometer Data: Assessment with Lidar Measurements and with All-sky Images

NASA Technical Reports Server (NTRS)

Ramirez, Daniel Perez; Lyamani, H.; Olmo, F. J.; Whiteman, D. N.; Navas-Guzman, F.; Alados-Arboledas, L.

2012-01-01

This paper presents the development and set up of a cloud screening and data quality control algorithm for a star photometer based on CCD camera as detector. These algorithms are necessary for passive remote sensing techniques to retrieve the columnar aerosol optical depth, delta Ae(lambda), and precipitable water vapor content, W, at nighttime. This cloud screening procedure consists of calculating moving averages of delta Ae() and W under different time-windows combined with a procedure for detecting outliers. Additionally, to avoid undesirable Ae(lambda) and W fluctuations caused by the atmospheric turbulence, the data are averaged on 30 min. The algorithm is applied to the star photometer deployed in the city of Granada (37.16 N, 3.60 W, 680 ma.s.l.; South-East of Spain) for the measurements acquired between March 2007 and September 2009. The algorithm is evaluated with correlative measurements registered by a lidar system and also with all-sky images obtained at the sunset and sunrise of the previous and following days. Promising results are obtained detecting cloud-affected data. Additionally, the cloud screening algorithm has been evaluated under different aerosol conditions including Saharan dust intrusion, biomass burning and pollution events.

Accelerating the reconstruction of magnetic resonance imaging by three-dimensional dual-dictionary learning using CUDA.

PubMed

Jiansen Li; Jianqi Sun; Ying Song; Yanran Xu; Jun Zhao

2014-01-01

An effective way to improve the data acquisition speed of magnetic resonance imaging (MRI) is using under-sampled k-space data, and dictionary learning method can be used to maintain the reconstruction quality. Three-dimensional dictionary trains the atoms in dictionary in the form of blocks, which can utilize the spatial correlation among slices. Dual-dictionary learning method includes a low-resolution dictionary and a high-resolution dictionary, for sparse coding and image updating respectively. However, the amount of data is huge for three-dimensional reconstruction, especially when the number of slices is large. Thus, the procedure is time-consuming. In this paper, we first utilize the NVIDIA Corporation's compute unified device architecture (CUDA) programming model to design the parallel algorithms on graphics processing unit (GPU) to accelerate the reconstruction procedure. The main optimizations operate in the dictionary learning algorithm and the image updating part, such as the orthogonal matching pursuit (OMP) algorithm and the k-singular value decomposition (K-SVD) algorithm. Then we develop another version of CUDA code with algorithmic optimization. Experimental results show that more than 324 times of speedup is achieved compared with the CPU-only codes when the number of MRI slices is 24.

A proposed method to estimate premorbid full scale intelligence quotient (FSIQ) for the Canadian Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) using demographic and combined estimation procedures.

PubMed

Schoenberg, Mike R; Lange, Rael T; Saklofske, Donald H

2007-11-01

Establishing a comparison standard in neuropsychological assessment is crucial to determining change in function. There is no available method to estimate premorbid intellectual functioning for the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). The WISC-IV provided normative data for both American and Canadian children aged 6 to 16 years old. This study developed regression algorithms as a proposed method to estimate full-scale intelligence quotient (FSIQ) for the Canadian WISC-IV. Participants were the Canadian WISC-IV standardization sample (n = 1,100). The sample was randomly divided into two groups (development and validation groups). The development group was used to generate regression algorithms; 1 algorithm only included demographics, and 11 combined demographic variables with WISC-IV subtest raw scores. The algorithms accounted for 18% to 70% of the variance in FSIQ (standard error of estimate, SEE = 8.6 to 14.2). Estimated FSIQ significantly correlated with actual FSIQ (r = .30 to .80), and the majority of individual FSIQ estimates were within +/-10 points of actual FSIQ. The demographic-only algorithm was less accurate than algorithms combining demographic variables with subtest raw scores. The current algorithms yielded accurate estimates of current FSIQ for Canadian individuals aged 6-16 years old. The potential application of the algorithms to estimate premorbid FSIQ is reviewed. While promising, clinical validation of the algorithms in a sample of children and/or adolescents with known neurological dysfunction is needed to establish these algorithms as a premorbid estimation procedure.

A Framework to Debug Diagnostic Matrices

NASA Technical Reports Server (NTRS)

Kodal, Anuradha; Robinson, Peter; Patterson-Hine, Ann

2013-01-01

Diagnostics is an important concept in system health and monitoring of space operations. Many of the existing diagnostic algorithms utilize system knowledge in the form of diagnostic matrix (D-matrix, also popularly known as diagnostic dictionary, fault signature matrix or reachability matrix) gleaned from physical models. But, sometimes, this may not be coherent to obtain high diagnostic performance. In such a case, it is important to modify this D-matrix based on knowledge obtained from other sources such as time-series data stream (simulated or maintenance data) within the context of a framework that includes the diagnostic/inference algorithm. A systematic and sequential update procedure, diagnostic modeling evaluator (DME) is proposed to modify D-matrix and wrapper logic considering least expensive solution first. This iterative procedure includes conditions ranging from modifying 0s and 1s in the matrix, or adding/removing the rows (failure sources) columns (tests). We will experiment this framework on datasets from DX challenge 2009.

Practical advantages of evolutionary computation

NASA Astrophysics Data System (ADS)

Fogel, David B.

1997-10-01

Evolutionary computation is becoming a common technique for solving difficult, real-world problems in industry, medicine, and defense. This paper reviews some of the practical advantages to using evolutionary algorithms as compared with classic methods of optimization or artificial intelligence. Specific advantages include the flexibility of the procedures, as well as their ability to self-adapt the search for optimum solutions on the fly. As desktop computers increase in speed, the application of evolutionary algorithms will become routine.

Development of advanced acreage estimation methods

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr. (Principal Investigator)

1980-01-01

The use of the AMOEBA clustering/classification algorithm was investigated as a basis for both a color display generation technique and maximum likelihood proportion estimation procedure. An approach to analyzing large data reduction systems was formulated and an exploratory empirical study of spatial correlation in LANDSAT data was also carried out. Topics addressed include: (1) development of multiimage color images; (2) spectral spatial classification algorithm development; (3) spatial correlation studies; and (4) evaluation of data systems.

Navigation strategy and filter design for solar electric missions

NASA Technical Reports Server (NTRS)

Tapley, B. D.; Hagar, H., Jr.

1972-01-01

Methods which have been proposed to improve the navigation accuracy for the low-thrust space vehicle include modifications to the standard Sequential- and Batch-type orbit determination procedures and the use of inertial measuring units (IMU) which measures directly the acceleration applied to the vehicle. The navigation accuracy obtained using one of the more promising modifications to the orbit determination procedures is compared with a combined IMU-Standard. The unknown accelerations are approximated as both first-order and second-order Gauss-Markov processes. The comparison is based on numerical results obtained in a study of the navigation requirements of a numerically simulated 152-day low-thrust mission to the asteroid Eros. The results obtained in the simulation indicate that the DMC algorithm will yield a significant improvement over the navigation accuracies achieved with previous estimation algorithms. In addition, the DMC algorithms will yield better navigation accuracies than the IMU-Standard Orbit Determination algorithm, except for extremely precise IMU measurements, i.e., gyroplatform alignment .01 deg and accelerometer signal-to-noise ratio .07. Unless these accuracies are achieved, the IMU navigation accuracies are generally unacceptable.

The Mucciardi-Gose Clustering Algorithm and Its Applications in Automatic Pattern Recognition.

DTIC Science & Technology

A procedure known as the Mucciardi- Gose clustering algorithm, CLUSTR, for determining the geometrical or statistical relationships among groups of N...discussion of clustering algorithms is given; the particular advantages of the Mucciardi- Gose procedure are described. The mathematical basis for, and the

Optimal design of the rotor geometry of line-start permanent magnet synchronous motor using the bat algorithm

NASA Astrophysics Data System (ADS)

Knypiński, Łukasz

2017-12-01

In this paper an algorithm for the optimization of excitation system of line-start permanent magnet synchronous motors will be presented. For the basis of this algorithm, software was developed in the Borland Delphi environment. The software consists of two independent modules: an optimization solver, and a module including the mathematical model of a synchronous motor with a self-start ability. The optimization module contains the bat algorithm procedure. The mathematical model of the motor has been developed in an Ansys Maxwell environment. In order to determine the functional parameters of the motor, additional scripts in Visual Basic language were developed. Selected results of the optimization calculation are presented and compared with results for the particle swarm optimization algorithm.

Replication and Comparison of the Newly Proposed ADOS-2, Module 4 Algorithm in ASD Without ID: A Multi-site Study.

PubMed

Pugliese, Cara E; Kenworthy, Lauren; Bal, Vanessa Hus; Wallace, Gregory L; Yerys, Benjamin E; Maddox, Brenna B; White, Susan W; Popal, Haroon; Armour, Anna Chelsea; Miller, Judith; Herrington, John D; Schultz, Robert T; Martin, Alex; Anthony, Laura Gutermuth

2015-12-01

Recent updates have been proposed to the Autism Diagnostic Observation Schedule-2 Module 4 diagnostic algorithm. This new algorithm, however, has not yet been validated in an independent sample without intellectual disability (ID). This multi-site study compared the original and revised algorithms in individuals with ASD without ID. The revised algorithm demonstrated increased sensitivity, but lower specificity in the overall sample. Estimates were highest for females, individuals with a verbal IQ below 85 or above 115, and ages 16 and older. Best practice diagnostic procedures should include the Module 4 in conjunction with other assessment tools. Balancing needs for sensitivity and specificity depending on the purpose of assessment (e.g., clinical vs. research) and demographic characteristics mentioned above will enhance its utility.

An efficient algorithm for automatic phase correction of NMR spectra based on entropy minimization

NASA Astrophysics Data System (ADS)

Chen, Li; Weng, Zhiqiang; Goh, LaiYoong; Garland, Marc

2002-09-01

A new algorithm for automatic phase correction of NMR spectra based on entropy minimization is proposed. The optimal zero-order and first-order phase corrections for a NMR spectrum are determined by minimizing entropy. The objective function is constructed using a Shannon-type information entropy measure. Entropy is defined as the normalized derivative of the NMR spectral data. The algorithm has been successfully applied to experimental 1H NMR spectra. The results of automatic phase correction are found to be comparable to, or perhaps better than, manual phase correction. The advantages of this automatic phase correction algorithm include its simple mathematical basis and the straightforward, reproducible, and efficient optimization procedure. The algorithm is implemented in the Matlab program ACME—Automated phase Correction based on Minimization of Entropy.

Iterative refinement of structure-based sequence alignments by Seed Extension

PubMed Central

Kim, Changhoon; Tai, Chin-Hsien; Lee, Byungkook

2009-01-01

Background Accurate sequence alignment is required in many bioinformatics applications but, when sequence similarity is low, it is difficult to obtain accurate alignments based on sequence similarity alone. The accuracy improves when the structures are available, but current structure-based sequence alignment procedures still mis-align substantial numbers of residues. In order to correct such errors, we previously explored the possibility of replacing the residue-based dynamic programming algorithm in structure alignment procedures with the Seed Extension algorithm, which does not use a gap penalty. Here, we describe a new procedure called RSE (Refinement with Seed Extension) that iteratively refines a structure-based sequence alignment. Results RSE uses SE (Seed Extension) in its core, which is an algorithm that we reported recently for obtaining a sequence alignment from two superimposed structures. The RSE procedure was evaluated by comparing the correctly aligned fractions of residues before and after the refinement of the structure-based sequence alignments produced by popular programs. CE, DaliLite, FAST, LOCK2, MATRAS, MATT, TM-align, SHEBA and VAST were included in this analysis and the NCBI's CDD root node set was used as the reference alignments. RSE improved the average accuracy of sequence alignments for all programs tested when no shift error was allowed. The amount of improvement varied depending on the program. The average improvements were small for DaliLite and MATRAS but about 5% for CE and VAST. More substantial improvements have been seen in many individual cases. The additional computation times required for the refinements were negligible compared to the times taken by the structure alignment programs. Conclusion RSE is a computationally inexpensive way of improving the accuracy of a structure-based sequence alignment. It can be used as a standalone procedure following a regular structure-based sequence alignment or to replace the traditional iterative refinement procedures based on residue-level dynamic programming algorithm in many structure alignment programs. PMID:19589133

A structure preserving Lanczos algorithm for computing the optical absorption spectrum

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shao, Meiyue; Jornada, Felipe H. da; Lin, Lin

2016-11-16

We present a new structure preserving Lanczos algorithm for approximating the optical absorption spectrum in the context of solving full Bethe-Salpeter equation without Tamm-Dancoff approximation. The new algorithm is based on a structure preserving Lanczos procedure, which exploits the special block structure of Bethe-Salpeter Hamiltonian matrices. A recently developed technique of generalized averaged Gauss quadrature is incorporated to accelerate the convergence. We also establish the connection between our structure preserving Lanczos procedure with several existing Lanczos procedures developed in different contexts. Numerical examples are presented to demonstrate the effectiveness of our Lanczos algorithm.

A stochastic estimation procedure for intermittently-observed semi-Markov multistate models with back transitions.

PubMed

Aralis, Hilary; Brookmeyer, Ron

2017-01-01

Multistate models provide an important method for analyzing a wide range of life history processes including disease progression and patient recovery following medical intervention. Panel data consisting of the states occupied by an individual at a series of discrete time points are often used to estimate transition intensities of the underlying continuous-time process. When transition intensities depend on the time elapsed in the current state and back transitions between states are possible, this intermittent observation process presents difficulties in estimation due to intractability of the likelihood function. In this manuscript, we present an iterative stochastic expectation-maximization algorithm that relies on a simulation-based approximation to the likelihood function and implement this algorithm using rejection sampling. In a simulation study, we demonstrate the feasibility and performance of the proposed procedure. We then demonstrate application of the algorithm to a study of dementia, the Nun Study, consisting of intermittently-observed elderly subjects in one of four possible states corresponding to intact cognition, impaired cognition, dementia, and death. We show that the proposed stochastic expectation-maximization algorithm substantially reduces bias in model parameter estimates compared to an alternative approach used in the literature, minimal path estimation. We conclude that in estimating intermittently observed semi-Markov models, the proposed approach is a computationally feasible and accurate estimation procedure that leads to substantial improvements in back transition estimates.

Progress on the development of automated data analysis algorithms and software for ultrasonic inspection of composites

NASA Astrophysics Data System (ADS)

Aldrin, John C.; Coughlin, Chris; Forsyth, David S.; Welter, John T.

2014-02-01

Progress is presented on the development and implementation of automated data analysis (ADA) software to address the burden in interpreting ultrasonic inspection data for large composite structures. The automated data analysis algorithm is presented in detail, which follows standard procedures for analyzing signals for time-of-flight indications and backwall amplitude dropout. ADA processing results are presented for test specimens that include inserted materials and discontinuities produced under poor manufacturing conditions.

Development and Validation of an Algorithm to Identify Planned Readmissions From Claims Data.

PubMed

Horwitz, Leora I; Grady, Jacqueline N; Cohen, Dorothy B; Lin, Zhenqiu; Volpe, Mark; Ngo, Chi K; Masica, Andrew L; Long, Theodore; Wang, Jessica; Keenan, Megan; Montague, Julia; Suter, Lisa G; Ross, Joseph S; Drye, Elizabeth E; Krumholz, Harlan M; Bernheim, Susannah M

2015-10-01

It is desirable not to include planned readmissions in readmission measures because they represent deliberate, scheduled care. To develop an algorithm to identify planned readmissions, describe its performance characteristics, and identify improvements. Consensus-driven algorithm development and chart review validation study at 7 acute-care hospitals in 2 health systems. For development, all discharges qualifying for the publicly reported hospital-wide readmission measure. For validation, all qualifying same-hospital readmissions that were characterized by the algorithm as planned, and a random sampling of same-hospital readmissions that were characterized as unplanned. We calculated weighted sensitivity and specificity, and positive and negative predictive values of the algorithm (version 2.1), compared to gold standard chart review. In consultation with 27 experts, we developed an algorithm that characterizes 7.8% of readmissions as planned. For validation we reviewed 634 readmissions. The weighted sensitivity of the algorithm was 45.1% overall, 50.9% in large teaching centers and 40.2% in smaller community hospitals. The weighted specificity was 95.9%, positive predictive value was 51.6%, and negative predictive value was 94.7%. We identified 4 minor changes to improve algorithm performance. The revised algorithm had a weighted sensitivity 49.8% (57.1% at large hospitals), weighted specificity 96.5%, positive predictive value 58.7%, and negative predictive value 94.5%. Positive predictive value was poor for the 2 most common potentially planned procedures: diagnostic cardiac catheterization (25%) and procedures involving cardiac devices (33%). An administrative claims-based algorithm to identify planned readmissions is feasible and can facilitate public reporting of primarily unplanned readmissions. © 2015 Society of Hospital Medicine.

SIAM Conference on Parallel Processing for Scientific Computing, 4th, Chicago, IL, Dec. 11-13, 1989, Proceedings

NASA Technical Reports Server (NTRS)

Dongarra, Jack (Editor); Messina, Paul (Editor); Sorensen, Danny C. (Editor); Voigt, Robert G. (Editor)

1990-01-01

Attention is given to such topics as an evaluation of block algorithm variants in LAPACK and presents a large-grain parallel sparse system solver, a multiprocessor method for the solution of the generalized Eigenvalue problem on an interval, and a parallel QR algorithm for iterative subspace methods on the CM2. A discussion of numerical methods includes the topics of asynchronous numerical solutions of PDEs on parallel computers, parallel homotopy curve tracking on a hypercube, and solving Navier-Stokes equations on the Cedar Multi-Cluster system. A section on differential equations includes a discussion of a six-color procedure for the parallel solution of elliptic systems using the finite quadtree structure, data parallel algorithms for the finite element method, and domain decomposition methods in aerodynamics. Topics dealing with massively parallel computing include hypercube vs. 2-dimensional meshes and massively parallel computation of conservation laws. Performance and tools are also discussed.

Non-parametric diffeomorphic image registration with the demons algorithm.

PubMed

Vercauteren, Tom; Pennec, Xavier; Perchant, Aymeric; Ayache, Nicholas

2007-01-01

We propose a non-parametric diffeomorphic image registration algorithm based on Thirion's demons algorithm. The demons algorithm can be seen as an optimization procedure on the entire space of displacement fields. The main idea of our algorithm is to adapt this procedure to a space of diffeomorphic transformations. In contrast to many diffeomorphic registration algorithms, our solution is computationally efficient since in practice it only replaces an addition of free form deformations by a few compositions. Our experiments show that in addition to being diffeomorphic, our algorithm provides results that are similar to the ones from the demons algorithm but with transformations that are much smoother and closer to the true ones in terms of Jacobians.

Algorithm for Identifying Erroneous Rain-Gauge Readings

NASA Technical Reports Server (NTRS)

Rickman, Doug

2005-01-01

An algorithm analyzes rain-gauge data to identify statistical outliers that could be deemed to be erroneous readings. Heretofore, analyses of this type have been performed in burdensome manual procedures that have involved subjective judgements. Sometimes, the analyses have included computational assistance for detecting values falling outside of arbitrary limits. The analyses have been performed without statistically valid knowledge of the spatial and temporal variations of precipitation within rain events. In contrast, the present algorithm makes it possible to automate such an analysis, makes the analysis objective, takes account of the spatial distribution of rain gauges in conjunction with the statistical nature of spatial variations in rainfall readings, and minimizes the use of arbitrary criteria. The algorithm implements an iterative process that involves nonparametric statistics.

Hybridisations of Variable Neighbourhood Search and Modified Simplex Elements to Harmony Search and Shuffled Frog Leaping Algorithms for Process Optimisations

NASA Astrophysics Data System (ADS)

Aungkulanon, P.; Luangpaiboon, P.

2010-10-01

Nowadays, the engineering problem systems are large and complicated. An effective finite sequence of instructions for solving these problems can be categorised into optimisation and meta-heuristic algorithms. Though the best decision variable levels from some sets of available alternatives cannot be done, meta-heuristics is an alternative for experience-based techniques that rapidly help in problem solving, learning and discovery in the hope of obtaining a more efficient or more robust procedure. All meta-heuristics provide auxiliary procedures in terms of their own tooled box functions. It has been shown that the effectiveness of all meta-heuristics depends almost exclusively on these auxiliary functions. In fact, the auxiliary procedure from one can be implemented into other meta-heuristics. Well-known meta-heuristics of harmony search (HSA) and shuffled frog-leaping algorithms (SFLA) are compared with their hybridisations. HSA is used to produce a near optimal solution under a consideration of the perfect state of harmony of the improvisation process of musicians. A meta-heuristic of the SFLA, based on a population, is a cooperative search metaphor inspired by natural memetics. It includes elements of local search and global information exchange. This study presents solution procedures via constrained and unconstrained problems with different natures of single and multi peak surfaces including a curved ridge surface. Both meta-heuristics are modified via variable neighbourhood search method (VNSM) philosophy including a modified simplex method (MSM). The basic idea is the change of neighbourhoods during searching for a better solution. The hybridisations proceed by a descent method to a local minimum exploring then, systematically or at random, increasingly distant neighbourhoods of this local solution. The results show that the variant of HSA with VNSM and MSM seems to be better in terms of the mean and variance of design points and yields.

A hybrid-domain approach for modeling climate data time series

NASA Astrophysics Data System (ADS)

Wen, Qiuzi H.; Wang, Xiaolan L.; Wong, Augustine

2011-09-01

In order to model climate data time series that often contain periodic variations, trends, and sudden changes in mean (mean shifts, mostly artificial), this study proposes a hybrid-domain (HD) algorithm, which incorporates a time domain test and a newly developed frequency domain test through an iterative procedure that is analogue to the well known backfitting algorithm. A two-phase competition procedure is developed to address the confounding issue between modeling periodic variations and mean shifts. A variety of distinctive features of climate data time series, including trends, periodic variations, mean shifts, and a dependent noise structure, can be modeled in tandem using the HD algorithm. This is particularly important for homogenization of climate data from a low density observing network in which reference series are not available to help preserve climatic trends and long-term periodic variations, preventing them from being mistaken as artificial shifts. The HD algorithm is also powerful in estimating trend and periodicity in a homogeneous data time series (i.e., in the absence of any mean shift). The performance of the HD algorithm (in terms of false alarm rate and hit rate in detecting shifts/cycles, and estimation accuracy) is assessed via a simulation study. Its power is further illustrated through its application to a few climate data time series.

Replication and Comparison of the Newly Proposed ADOS-2, Module 4 Algorithm in ASD without ID: A Multi-site Study

PubMed Central

Pugliese, Cara E.; Kenworthy, Lauren; Bal, Vanessa Hus; Wallace, Gregory L; Yerys, Benjamin E; Maddox, Brenna B.; White, Susan W.; Popal, Haroon; Armour, Anna Chelsea; Miller, Judith; Herrington, John D.; Schultz, Robert T.; Martin, Alex; Anthony, Laura Gutermuth

2015-01-01

Recent updates have been proposed to the Autism Diagnostic Observation Schedule-2 Module 4 diagnostic algorithm. This new algorithm, however, has not yet been validated in an independent sample without intellectual disability (ID). This multi-site study compared the original and revised algorithms in individuals with ASD without ID. The revised algorithm demonstrated increased sensitivity, but lower specificity in the overall sample. Estimates were highest for females, individuals with a verbal IQ below 85 or above 115, and ages 16 and older. Best practice diagnostic procedures should include the Module 4 in conjunction with other assessment tools. Balancing needs for sensitivity and specificity depending on the purpose of assessment (e.g., clinical vs. research) and demographic characteristics mentioned above will enhance its utility. PMID:26385796

Data reduction using cubic rational B-splines

NASA Technical Reports Server (NTRS)

Chou, Jin J.; Piegl, Les A.

1992-01-01

A geometric method is proposed for fitting rational cubic B-spline curves to data that represent smooth curves including intersection or silhouette lines. The algorithm is based on the convex hull and the variation diminishing properties of Bezier/B-spline curves. The algorithm has the following structure: it tries to fit one Bezier segment to the entire data set and if it is impossible it subdivides the data set and reconsiders the subset. After accepting the subset the algorithm tries to find the longest run of points within a tolerance and then approximates this set with a Bezier cubic segment. The algorithm uses this procedure repeatedly to the rest of the data points until all points are fitted. It is concluded that the algorithm delivers fitting curves which approximate the data with high accuracy even in cases with large tolerances.

Solar Eclipse Monitoring for Solar Energy Applications Using the Solar and Moon Position Algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reda, I.

2010-03-01

This report includes a procedure for implementing an algorithm (described by Jean Meeus) to calculate the moon's zenith angle with uncertainty of +/-0.001 degrees and azimuth angle with uncertainty of +/-0.003 degrees. The step-by-step format presented here simplifies the complicated steps Meeus describes to calculate the Moon's position, and focuses on the Moon instead of the planets and stars. It also introduces some changes to accommodate for solar radiation applications.

Transition Flight Control Room Automation

NASA Technical Reports Server (NTRS)

Welborn, Curtis Ray

1990-01-01

The Workstation Prototype Laboratory is currently working on a number of projects which we feel can have a direct impact on ground operations automation. These projects include: The Fuel Cell Monitoring System (FCMS), which will monitor and detect problems with the fuel cells on the Shuttle. FCMS will use a combination of rules (forward/backward) and multi-threaded procedures which run concurrently with the rules, to implement the malfunction algorithms of the EGIL flight controllers. The combination of rule based reasoning and procedural reasoning allows us to more easily map the malfunction algorithms into a real-time system implementation. A graphical computation language (AGCOMPL). AGCOMPL is an experimental prototype to determine the benefits and drawbacks of using a graphical language to design computations (algorithms) to work on Shuttle or Space Station telemetry and trajectory data. The design of a system which will allow a model of an electrical system, including telemetry sensors, to be configured on the screen graphically using previously defined electrical icons. This electrical model would then be used to generate rules and procedures for detecting malfunctions in the electrical components of the model. A generic message management (GMM) system. GMM is being designed as a message management system for real-time applications which send advisory messages to a user. The primary purpose of GMM is to reduce the risk of overloading a user with information when multiple failures occurs and in assisting the developer in devising an explanation facility. The emphasis of our work is to develop practical tools and techniques, while determining the feasibility of a given approach, including identification of appropriate software tools to support research, application and tool building activities.

Transition flight control room automation

NASA Technical Reports Server (NTRS)

Welborn, Curtis Ray

1990-01-01

The Workstation Prototype Laboratory is currently working on a number of projects which can have a direct impact on ground operations automation. These projects include: (1) The fuel cell monitoring system (FCMS), which will monitor and detect problems with the fuel cells on the shuttle. FCMS will use a combination of rules (forward/backward) and multithreaded procedures, which run concurrently with the rules, to implement the malfunction algorithms of the EGIL flight controllers. The combination of rule-based reasoning and procedural reasoning allows us to more easily map the malfunction algorithms into a real-time system implementation. (2) A graphical computation language (AGCOMPL) is an experimental prototype to determine the benefits and drawbacks of using a graphical language to design computations (algorithms) to work on shuttle or space station telemetry and trajectory data. (3) The design of a system will allow a model of an electrical system, including telemetry sensors, to be configured on the screen graphically using previously defined electrical icons. This electrical model would then be used to generate rules and procedures for detecting malfunctions in the electrical components of the model. (4) A generic message management (GMM) system is being designed for real-time applications as a message management system which sends advisory messages to a user. The primary purpose of GMM is to reduce the risk of overloading a user with information when multiple failures occur and to assist the developer in the devising an explanation facility. The emphasis of our work is to develop practical tools and techniques, including identification of appropriate software tools to support research, application, and tool building activities, while determining the feasibility of a given approach.

Online selective kernel-based temporal difference learning.

PubMed

Chen, Xingguo; Gao, Yang; Wang, Ruili

2013-12-01

In this paper, an online selective kernel-based temporal difference (OSKTD) learning algorithm is proposed to deal with large scale and/or continuous reinforcement learning problems. OSKTD includes two online procedures: online sparsification and parameter updating for the selective kernel-based value function. A new sparsification method (i.e., a kernel distance-based online sparsification method) is proposed based on selective ensemble learning, which is computationally less complex compared with other sparsification methods. With the proposed sparsification method, the sparsified dictionary of samples is constructed online by checking if a sample needs to be added to the sparsified dictionary. In addition, based on local validity, a selective kernel-based value function is proposed to select the best samples from the sample dictionary for the selective kernel-based value function approximator. The parameters of the selective kernel-based value function are iteratively updated by using the temporal difference (TD) learning algorithm combined with the gradient descent technique. The complexity of the online sparsification procedure in the OSKTD algorithm is O(n). In addition, two typical experiments (Maze and Mountain Car) are used to compare with both traditional and up-to-date O(n) algorithms (GTD, GTD2, and TDC using the kernel-based value function), and the results demonstrate the effectiveness of our proposed algorithm. In the Maze problem, OSKTD converges to an optimal policy and converges faster than both traditional and up-to-date algorithms. In the Mountain Car problem, OSKTD converges, requires less computation time compared with other sparsification methods, gets a better local optima than the traditional algorithms, and converges much faster than the up-to-date algorithms. In addition, OSKTD can reach a competitive ultimate optima compared with the up-to-date algorithms.

A Feature and Algorithm Selection Method for Improving the Prediction of Protein Structural Class.

PubMed

Ni, Qianwu; Chen, Lei

2017-01-01

Correct prediction of protein structural class is beneficial to investigation on protein functions, regulations and interactions. In recent years, several computational methods have been proposed in this regard. However, based on various features, it is still a great challenge to select proper classification algorithm and extract essential features to participate in classification. In this study, a feature and algorithm selection method was presented for improving the accuracy of protein structural class prediction. The amino acid compositions and physiochemical features were adopted to represent features and thirty-eight machine learning algorithms collected in Weka were employed. All features were first analyzed by a feature selection method, minimum redundancy maximum relevance (mRMR), producing a feature list. Then, several feature sets were constructed by adding features in the list one by one. For each feature set, thirtyeight algorithms were executed on a dataset, in which proteins were represented by features in the set. The predicted classes yielded by these algorithms and true class of each protein were collected to construct a dataset, which were analyzed by mRMR method, yielding an algorithm list. From the algorithm list, the algorithm was taken one by one to build an ensemble prediction model. Finally, we selected the ensemble prediction model with the best performance as the optimal ensemble prediction model. Experimental results indicate that the constructed model is much superior to models using single algorithm and other models that only adopt feature selection procedure or algorithm selection procedure. The feature selection procedure or algorithm selection procedure are really helpful for building an ensemble prediction model that can yield a better performance. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Impact of the Parameter Identification of Plastic Potentials on the Finite Element Simulation of Sheet Metal Forming

NASA Astrophysics Data System (ADS)

Rabahallah, M.; Bouvier, S.; Balan, T.; Bacroix, B.; Teodosiu, C.

2007-04-01

In this work, an implicit, backward Euler time integration scheme is developed for an anisotropic, elastic-plastic model based on strain-rate potentials. The constitutive algorithm includes a sub-stepping procedure to deal with the strong nonlinearity of the plastic potentials when applied to FCC materials. The algorithm is implemented in the static implicit version of the Abaqus finite element code. Several recent plastic potentials have been implemented in this framework. The most accurate potentials require the identification of about twenty material parameters. Both mechanical tests and micromechanical simulations have been used for their identification, for a number of BCC and FCC materials. The impact of the identification procedure on the prediction of ears in cup drawing is investigated.

TU-D-209-03: Alignment of the Patient Graphic Model Using Fluoroscopic Images for Skin Dose Mapping

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oines, A; Oines, A; Kilian-Meneghin, J

2016-06-15

Purpose: The Dose Tracking System (DTS) was developed to provide realtime feedback of skin dose and dose rate during interventional fluoroscopic procedures. A color map on a 3D graphic of the patient represents the cumulative dose distribution on the skin. Automated image correlation algorithms are described which use the fluoroscopic procedure images to align and scale the patient graphic for more accurate dose mapping. Methods: Currently, the DTS employs manual patient graphic selection and alignment. To improve the accuracy of dose mapping and automate the software, various methods are explored to extract information about the beam location and patient morphologymore » from the procedure images. To match patient anatomy with a reference projection image, preprocessing is first used, including edge enhancement, edge detection, and contour detection. Template matching algorithms from OpenCV are then employed to find the location of the beam. Once a match is found, the reference graphic is scaled and rotated to fit the patient, using image registration correlation functions in Matlab. The algorithm runs correlation functions for all points and maps all correlation confidences to a surface map. The highest point of correlation is used for alignment and scaling. The transformation data is saved for later model scaling. Results: Anatomic recognition is used to find matching features between model and image and image registration correlation provides for alignment and scaling at any rotation angle with less than onesecond runtime, and at noise levels in excess of 150% of those found in normal procedures. Conclusion: The algorithm provides the necessary scaling and alignment tools to improve the accuracy of dose distribution mapping on the patient graphic with the DTS. Partial support from NIH Grant R01-EB002873 and Toshiba Medical Systems Corp.« less

WE-AB-209-06: Dynamic Collimator Trajectory Algorithm for Use in VMAT Treatment Deliveries

DOE Office of Scientific and Technical Information (OSTI.GOV)

MacDonald, L; Thomas, C; Syme, A

2016-06-15

Purpose: To develop advanced dynamic collimator positioning algorithms for optimal beam’s-eye-view (BEV) fitting of targets in VMAT procedures, including multiple metastases stereotactic radiosurgery procedures. Methods: A trajectory algorithm was developed, which can dynamically modify the angle of the collimator as a function of VMAT control point to provide optimized collimation of target volume(s). Central to this algorithm is a concept denoted “whitespace”, defined as area within the jaw-defined BEV field, outside of the PTV, and not shielded by the MLC when fit to the PTV. Calculating whitespace at all collimator angles and every control point, a two-dimensional topographical map depictingmore » the tightness-of-fit of the MLC was generated. A variety of novel searching algorithms identified a number of candidate trajectories of continuous collimator motion. Ranking these candidate trajectories according to their accrued whitespace value produced an optimal solution for navigation of this map. Results: All trajectories were normalized to minimum possible (i.e. calculated without consideration of collimator motion constraints) accrued whitespace. On an acoustic neuroma case, a random walk algorithm generated a trajectory with 151% whitespace; random walk including a mandatory anchor point improved this to 148%; gradient search produced a trajectory with 137%; and bi-directional gradient search generated a trajectory with 130% whitespace. For comparison, a fixed collimator angle of 30° and 330° accumulated 272% and 228% of whitespace, respectively. The algorithm was tested on a clinical case with two metastases (single isocentre) and identified collimator angles that allow for simultaneous irradiation of the PTVs while minimizing normal tissue irradiation. Conclusion: Dynamic collimator trajectories have the potential to improve VMAT deliveries through increased efficiency and reduced normal tissue dose, especially in treatment of multiple cranial metastases, without significant safety concerns that hinder immediate clinical implementation.« less

Performance of a cavity-method-based algorithm for the prize-collecting Steiner tree problem on graphs

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.

Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

NASA Technical Reports Server (NTRS)

Key, Jeff; Maslanik, James; Steffen, Konrad

1995-01-01

During the second phase project year we have made progress in the development and refinement of surface temperature retrieval algorithms and in product generation. More specifically, we have accomplished the following: (1) acquired a new advanced very high resolution radiometer (AVHRR) data set for the Beaufort Sea area spanning an entire year; (2) acquired additional along-track scanning radiometer(ATSR) data for the Arctic and Antarctic now totalling over eight months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) developed cloud masking procedures for both AVHRR and ATSR; (6) generated a two-week bi-polar global area coverage (GAC) set of composite images from which IST is being estimated; (7) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; and (8) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and special sensor microwave imager (SSM/I).

Hierarchical image segmentation via recursive superpixel with adaptive regularity

NASA Astrophysics Data System (ADS)

Nakamura, Kensuke; Hong, Byung-Woo

2017-11-01

A fast and accurate segmentation algorithm in a hierarchical way based on a recursive superpixel technique is presented. We propose a superpixel energy formulation in which the trade-off between data fidelity and regularization is dynamically determined based on the local residual in the energy optimization procedure. We also present an energy optimization algorithm that allows a pixel to be shared by multiple regions to improve the accuracy and appropriate the number of segments. The qualitative and quantitative evaluations demonstrate that our algorithm, combining the proposed energy and optimization, outperforms the conventional k-means algorithm by up to 29.10% in F-measure. We also perform comparative analysis with state-of-the-art algorithms in the hierarchical segmentation. Our algorithm yields smooth regions throughout the hierarchy as opposed to the others that include insignificant details. Our algorithm overtakes the other algorithms in terms of balance between accuracy and computational time. Specifically, our method runs 36.48% faster than the region-merging approach, which is the fastest of the comparing algorithms, while achieving a comparable accuracy.

Clustering analysis of moving target signatures

NASA Astrophysics Data System (ADS)

Martone, Anthony; Ranney, Kenneth; Innocenti, Roberto

2010-04-01

Previously, we developed a moving target indication (MTI) processing approach to detect and track slow-moving targets inside buildings, which successfully detected moving targets (MTs) from data collected by a low-frequency, ultra-wideband radar. Our MTI algorithms include change detection, automatic target detection (ATD), clustering, and tracking. The MTI algorithms can be implemented in a real-time or near-real-time system; however, a person-in-the-loop is needed to select input parameters for the clustering algorithm. Specifically, the number of clusters to input into the cluster algorithm is unknown and requires manual selection. A critical need exists to automate all aspects of the MTI processing formulation. In this paper, we investigate two techniques that automatically determine the number of clusters: the adaptive knee-point (KP) algorithm and the recursive pixel finding (RPF) algorithm. The KP algorithm is based on a well-known heuristic approach for determining the number of clusters. The RPF algorithm is analogous to the image processing, pixel labeling procedure. Both algorithms are used to analyze the false alarm and detection rates of three operational scenarios of personnel walking inside wood and cinderblock buildings.

Cryptography: Cracking Codes.

ERIC Educational Resources Information Center

Myerscough, Don; And Others

1996-01-01

Describes an activity whose objectives are to encode and decode messages using linear functions and their inverses; to use modular arithmetic, including use of the reciprocal for simple equation solving; to analyze patterns and make and test conjectures; to communicate procedures and algorithms; and to use problem-solving strategies. (ASK)

Target-type probability combining algorithms for multisensor tracking

NASA Astrophysics Data System (ADS)

Wigren, Torbjorn

2001-08-01

Algorithms for the handing of target type information in an operational multi-sensor tracking system are presented. The paper discusses recursive target type estimation, computation of crosses from passive data (strobe track triangulation), as well as the computation of the quality of the crosses for deghosting purposes. The focus is on Bayesian algorithms that operate in the discrete target type probability space, and on the approximations introduced for computational complexity reduction. The centralized algorithms are able to fuse discrete data from a variety of sensors and information sources, including IFF equipment, ESM's, IRST's as well as flight envelopes estimated from track data. All algorithms are asynchronous and can be tuned to handle clutter, erroneous associations as well as missed and erroneous detections. A key to obtain this ability is the inclusion of data forgetting by a procedure for propagation of target type probability states between measurement time instances. Other important properties of the algorithms are their abilities to handle ambiguous data and scenarios. The above aspects are illustrated in a simulations study. The simulation setup includes 46 air targets of 6 different types that are tracked by 5 airborne sensor platforms using ESM's and IRST's as data sources.

Constraint treatment techniques and parallel algorithms for multibody dynamic analysis. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Chiou, Jin-Chern

1990-01-01

Computational procedures for kinematic and dynamic analysis of three-dimensional multibody dynamic (MBD) systems are developed from the differential-algebraic equations (DAE's) viewpoint. Constraint violations during the time integration process are minimized and penalty constraint stabilization techniques and partitioning schemes are developed. The governing equations of motion, a two-stage staggered explicit-implicit numerical algorithm, are treated which takes advantage of a partitioned solution procedure. A robust and parallelizable integration algorithm is developed. This algorithm uses a two-stage staggered central difference algorithm to integrate the translational coordinates and the angular velocities. The angular orientations of bodies in MBD systems are then obtained by using an implicit algorithm via the kinematic relationship between Euler parameters and angular velocities. It is shown that the combination of the present solution procedures yields a computationally more accurate solution. To speed up the computational procedures, parallel implementation of the present constraint treatment techniques, the two-stage staggered explicit-implicit numerical algorithm was efficiently carried out. The DAE's and the constraint treatment techniques were transformed into arrowhead matrices to which Schur complement form was derived. By fully exploiting the sparse matrix structural analysis techniques, a parallel preconditioned conjugate gradient numerical algorithm is used to solve the systems equations written in Schur complement form. A software testbed was designed and implemented in both sequential and parallel computers. This testbed was used to demonstrate the robustness and efficiency of the constraint treatment techniques, the accuracy of the two-stage staggered explicit-implicit numerical algorithm, and the speed up of the Schur-complement-based parallel preconditioned conjugate gradient algorithm on a parallel computer.

The MHOST finite element program: 3-D inelastic analysis methods for hot section components. Volume 1: Theoretical manual

NASA Technical Reports Server (NTRS)

Nakazawa, Shohei

1991-01-01

Formulations and algorithms implemented in the MHOST finite element program are discussed. The code uses a novel concept of the mixed iterative solution technique for the efficient 3-D computations of turbine engine hot section components. The general framework of variational formulation and solution algorithms are discussed which were derived from the mixed three field Hu-Washizu principle. This formulation enables the use of nodal interpolation for coordinates, displacements, strains, and stresses. Algorithmic description of the mixed iterative method includes variations for the quasi static, transient dynamic and buckling analyses. The global-local analysis procedure referred to as the subelement refinement is developed in the framework of the mixed iterative solution, of which the detail is presented. The numerically integrated isoparametric elements implemented in the framework is discussed. Methods to filter certain parts of strain and project the element discontinuous quantities to the nodes are developed for a family of linear elements. Integration algorithms are described for linear and nonlinear equations included in MHOST program.

GSFC Technology Development Center Report

NASA Technical Reports Server (NTRS)

Himwich, Ed; Gipson, John

2013-01-01

This report summarizes the activities of the GSFC Technology Development Center (TDC) for 2012 and forecasts planned activities for 2013. The GSFC TDC develops station software including the Field System (FS), scheduling software (SKED), hardware including tools for station timing and meteorology, scheduling algorithms, and operational procedures. It provides a pool of individuals to assist with station implementation, check-out, upgrades, and training.

Shape-driven 3D segmentation using spherical wavelets.

PubMed

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

2006-01-01

This paper presents a novel active surface segmentation algorithm using a multiscale shape representation and prior. We define a parametric model of a surface using spherical wavelet functions and learn a prior probability distribution over the wavelet coefficients to model shape variations at different scales and spatial locations in a training set. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior in the segmentation framework. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to the segmentation of brain caudate nucleus, of interest in the study of schizophrenia. Our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm by capturing finer shape details.

Genetic algorithms and MCML program for recovery of optical properties of homogeneous turbid media

PubMed Central

Morales Cruzado, Beatriz; y Montiel, Sergio Vázquez; Atencio, José Alberto Delgado

2013-01-01

In this paper, we present and validate a new method for optical properties recovery of turbid media with slab geometry. This method is an iterative method that compares diffuse reflectance and transmittance, measured using integrating spheres, with those obtained using the known algorithm MCML. The search procedure is based in the evolution of a population due to selection of the best individual, i.e., using a genetic algorithm. This new method includes several corrections such as non-linear effects in integrating spheres measurements and loss of light due to the finite size of the sample. As a potential application and proof-of-principle experiment of this new method, we use this new algorithm in the recovery of optical properties of blood samples at different degrees of coagulation. PMID:23504404

Validation of administrative data used for the diagnosis of upper gastrointestinal events following nonsteroidal anti-inflammatory drug prescription.

PubMed

Abraham, N S; Cohen, D C; Rivers, B; Richardson, P

2006-07-15

To validate veterans affairs (VA) administrative data for the diagnosis of nonsteroidal anti-inflammatory drug (NSAID)-related upper gastrointestinal events (UGIE) and to develop a diagnostic algorithm. A retrospective study of veterans prescribed an NSAID as identified from the national pharmacy database merged with in-patient and out-patient data, followed by primary chart abstraction. Contingency tables were constructed to allow comparison with a random sample of patients prescribed an NSAID, but without UGIE. Multivariable logistic regression analysis was used to derive a predictive algorithm. Once derived, the algorithm was validated in a separate cohort of veterans. Of 906 patients, 606 had a diagnostic code for UGIE; 300 were a random subsample of 11 744 patients (control). Only 161 had a confirmed UGIE. The positive predictive value (PPV) of diagnostic codes was poor, but improved from 27% to 51% with the addition of endoscopic procedural codes. The strongest predictors of UGIE were an in-patient ICD-9 code for gastric ulcer, duodenal ulcer and haemorrhage combined with upper endoscopy. This algorithm had a PPV of 73% when limited to patients >or=65 years (c-statistic 0.79). Validation of the algorithm revealed a PPV of 80% among patients with an overlapping NSAID prescription. NSAID-related UGIE can be assessed using VA administrative data. The optimal algorithm includes an in-patient ICD-9 code for gastric or duodenal ulcer and gastrointestinal bleeding combined with a procedural code for upper endoscopy.

Self-adaptive predictor-corrector algorithm for static nonlinear structural analysis

NASA Technical Reports Server (NTRS)

Padovan, J.

1981-01-01

A multiphase selfadaptive predictor corrector type algorithm was developed. This algorithm enables the solution of highly nonlinear structural responses including kinematic, kinetic and material effects as well as pro/post buckling behavior. The strategy involves three main phases: (1) the use of a warpable hyperelliptic constraint surface which serves to upperbound dependent iterate excursions during successive incremental Newton Ramphson (INR) type iterations; (20 uses an energy constraint to scale the generation of successive iterates so as to maintain the appropriate form of local convergence behavior; (3) the use of quality of convergence checks which enable various self adaptive modifications of the algorithmic structure when necessary. The restructuring is achieved by tightening various conditioning parameters as well as switch to different algorithmic levels to improve the convergence process. The capabilities of the procedure to handle various types of static nonlinear structural behavior are illustrated.

Semi-supervised learning via regularized boosting working on multiple semi-supervised assumptions.

PubMed

Chen, Ke; Wang, Shihai

2011-01-01

Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learning with various strategies. To our knowledge, however, none of them takes all three semi-supervised assumptions, i.e., smoothness, cluster, and manifold assumptions, together into account during boosting learning. In this paper, we propose a novel cost functional consisting of the margin cost on labeled data and the regularization penalty on unlabeled data based on three fundamental semi-supervised assumptions. Thus, minimizing our proposed cost functional with a greedy yet stagewise functional optimization procedure leads to a generic boosting framework for semi-supervised learning. Extensive experiments demonstrate that our algorithm yields favorite results for benchmark and real-world classification tasks in comparison to state-of-the-art semi-supervised learning algorithms, including newly developed boosting algorithms. Finally, we discuss relevant issues and relate our algorithm to the previous work.

Time series modeling and forecasting using memetic algorithms for regime-switching models.

PubMed

Bergmeir, Christoph; Triguero, Isaac; Molina, Daniel; Aznarte, José Luis; Benitez, José Manuel

2012-11-01

In this brief, we present a novel model fitting procedure for the neuro-coefficient smooth transition autoregressive model (NCSTAR), as presented by Medeiros and Veiga. The model is endowed with a statistically founded iterative building procedure and can be interpreted in terms of fuzzy rule-based systems. The interpretability of the generated models and a mathematically sound building procedure are two very important properties of forecasting models. The model fitting procedure employed by the original NCSTAR is a combination of initial parameter estimation by a grid search procedure with a traditional local search algorithm. We propose a different fitting procedure, using a memetic algorithm, in order to obtain more accurate models. An empirical evaluation of the method is performed, applying it to various real-world time series originating from three forecasting competitions. The results indicate that we can significantly enhance the accuracy of the models, making them competitive to models commonly used in the field.

Evaluation of mathematical algorithms for automatic patient alignment in radiosurgery.

PubMed

Williams, Kenneth M; Schulte, Reinhard W; Schubert, Keith E; Wroe, Andrew J

2015-06-01

Image registration techniques based on anatomical features can serve to automate patient alignment for intracranial radiosurgery procedures in an effort to improve the accuracy and efficiency of the alignment process as well as potentially eliminate the need for implanted fiducial markers. To explore this option, four two-dimensional (2D) image registration algorithms were analyzed: the phase correlation technique, mutual information (MI) maximization, enhanced correlation coefficient (ECC) maximization, and the iterative closest point (ICP) algorithm. Digitally reconstructed radiographs from the treatment planning computed tomography scan of a human skull were used as the reference images, while orthogonal digital x-ray images taken in the treatment room were used as the captured images to be aligned. The accuracy of aligning the skull with each algorithm was compared to the alignment of the currently practiced procedure, which is based on a manual process of selecting common landmarks, including implanted fiducials and anatomical skull features. Of the four algorithms, three (phase correlation, MI maximization, and ECC maximization) demonstrated clinically adequate (ie, comparable to the standard alignment technique) translational accuracy and improvements in speed compared to the interactive, user-guided technique; however, the ICP algorithm failed to give clinically acceptable results. The results of this work suggest that a combination of different algorithms may provide the best registration results. This research serves as the initial groundwork for the translation of automated, anatomy-based 2D algorithms into a real-world system for 2D-to-2D image registration and alignment for intracranial radiosurgery. This may obviate the need for invasive implantation of fiducial markers into the skull and may improve treatment room efficiency and accuracy. © The Author(s) 2014.

A cloud masking algorithm for EARLINET lidar systems

NASA Astrophysics Data System (ADS)

Binietoglou, Ioannis; Baars, Holger; D'Amico, Giuseppe; Nicolae, Doina

2015-04-01

Cloud masking is an important first step in any aerosol lidar processing chain as most data processing algorithms can only be applied on cloud free observations. Up to now, the selection of a cloud-free time interval for data processing is typically performed manually, and this is one of the outstanding problems for automatic processing of lidar data in networks such as EARLINET. In this contribution we present initial developments of a cloud masking algorithm that permits the selection of the appropriate time intervals for lidar data processing based on uncalibrated lidar signals. The algorithm is based on a signal normalization procedure using the range of observed values of lidar returns, designed to work with different lidar systems with minimal user input. This normalization procedure can be applied to measurement periods of only few hours, even if no suitable cloud-free interval exists, and thus can be used even when only a short period of lidar measurements is available. Clouds are detected based on a combination of criteria including the magnitude of the normalized lidar signal and time-space edge detection performed using the Sobel operator. In this way the algorithm avoids misclassification of strong aerosol layers as clouds. Cloud detection is performed using the highest available time and vertical resolution of the lidar signals, allowing the effective detection of low-level clouds (e.g. cumulus humilis). Special attention is given to suppress false cloud detection due to signal noise that can affect the algorithm's performance, especially during day-time. In this contribution we present the details of algorithm, the effect of lidar characteristics (space-time resolution, available wavelengths, signal-to-noise ratio) to detection performance, and highlight the current strengths and limitations of the algorithm using lidar scenes from different lidar systems in different locations across Europe.

Clustering algorithm evaluation and the development of a replacement for procedure 1. [for crop inventories

NASA Technical Reports Server (NTRS)

Lennington, R. K.; Johnson, J. K.

1979-01-01

An efficient procedure which clusters data using a completely unsupervised clustering algorithm and then uses labeled pixels to label the resulting clusters or perform a stratified estimate using the clusters as strata is developed. Three clustering algorithms, CLASSY, AMOEBA, and ISOCLS, are compared for efficiency. Three stratified estimation schemes and three labeling schemes are also considered and compared.

Statistical Signal Models and Algorithms for Image Analysis

DTIC Science & Technology

1984-10-25

In this report, two-dimensional stochastic linear models are used in developing algorithms for image analysis such as classification, segmentation, and object detection in images characterized by textured backgrounds. These models generate two-dimensional random processes as outputs to which statistical inference procedures can naturally be applied. A common thread throughout our algorithms is the interpretation of the inference procedures in terms of linear prediction

GPU implementation of prior image constrained compressed sensing (PICCS)

NASA Astrophysics Data System (ADS)

Nett, Brian E.; Tang, Jie; Chen, Guang-Hong

2010-04-01

The Prior Image Constrained Compressed Sensing (PICCS) algorithm (Med. Phys. 35, pg. 660, 2008) has been applied to several computed tomography applications with both standard CT systems and flat-panel based systems designed for guiding interventional procedures and radiation therapy treatment delivery. The PICCS algorithm typically utilizes a prior image which is reconstructed via the standard Filtered Backprojection (FBP) reconstruction algorithm. The algorithm then iteratively solves for the image volume that matches the measured data, while simultaneously assuring the image is similar to the prior image. The PICCS algorithm has demonstrated utility in several applications including: improved temporal resolution reconstruction, 4D respiratory phase specific reconstructions for radiation therapy, and cardiac reconstruction from data acquired on an interventional C-arm. One disadvantage of the PICCS algorithm, just as other iterative algorithms, is the long computation times typically associated with reconstruction. In order for an algorithm to gain clinical acceptance reconstruction must be achievable in minutes rather than hours. In this work the PICCS algorithm has been implemented on the GPU in order to significantly reduce the reconstruction time of the PICCS algorithm. The Compute Unified Device Architecture (CUDA) was used in this implementation.

Turbomachinery Airfoil Design Optimization Using Differential Evolution

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.; Biegel, Bryan A. (Technical Monitor)

2002-01-01

An aerodynamic design optimization procedure that is based on a evolutionary algorithm known at Differential Evolution is described. Differential Evolution is a simple, fast, and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems, including highly nonlinear systems with discontinuities and multiple local optima. The method is combined with a Navier-Stokes solver that evaluates the various intermediate designs and provides inputs to the optimization procedure. An efficient constraint handling mechanism is also incorporated. Results are presented for the inverse design of a turbine airfoil from a modern jet engine. The capability of the method to search large design spaces and obtain the optimal airfoils in an automatic fashion is demonstrated. Substantial reductions in the overall computing time requirements are achieved by using the algorithm in conjunction with neural networks.

Investigation of new techniques for aircraft navigation using the omega navigation

NASA Technical Reports Server (NTRS)

Baxa, E. G., Jr.

1978-01-01

An OMEGA navigation receiver with a microprocessor as the computational component was investigated. A version of the INTEL 4004 microprocessor macroassembler suitable for use on the CDC-6600 system and development of a FORTRAN IV simulator program for the microprocessor was developed. Supporting studies included development and evaluation of navigation algorithms to generate relative position information from OMEGA VLF phase measurements. Simulation studies were used to evaluate assumptions made in developing a navigation equation in OMEGA Line of Position (LOP) coordinates. Included in the navigation algorithms was a procedure for calculating a position in latitude/longitude given an OMEGA LOP fix. Implementation of a digital phase locked loop (DPLL) was evaluated on the basic of phase response characteristics over a range of input phase variations. Included also is an analytical evaluation on the basis of error probability of an algorithm for automatic time synchronization of the receiver to the OMEGA broadcast format. The use of actual OMEGA phase data and published propagation prediction corrections to determine phase velocity estimates was discussed.

Modeling and analysis of pinhole occulter experiment: Initial study phase

NASA Technical Reports Server (NTRS)

Vandervoort, R. J.

1985-01-01

The feasibility of using a generic simulation, TREETOPS, to simulate the Pinhole/Occulter Facility (P/OF) to be tested on the space shuttle was demonstrated. The baseline control system was used to determine the pointing performance of the P/OF. The task included modeling the structure as a three body problem (shuttle-instrument pointing system- P/OP) including the flexibility of the 32 meter P/OF boom. Modeling of sensors, actuators, and control algorithms was also required. Detailed mathematical models for the structure, sensors, and actuators are presented, as well as the control algorithm and corresponding design procedure. Closed loop performance using this controller and computer listings for the simulator are also given.

Ad hoc cost analysis of the new gastrointestinal bleeding algorithm in patients with ventricular assist device.

PubMed

Hirose, Hitoshi; Sarosiek, Konrad; Cavarocchi, Nicholas C

2014-01-01

Gastrointestinal bleed (GIB) is a known complication in patients receiving nonpulsatile ventricular assist devices (VAD). Previously, we reported a new algorithm for the workup of GIB in VAD patients using deep bowel enteroscopy. In this new algorithm, patients underwent fewer procedures, received less transfusions, and took less time to make the diagnosis than the traditional GIB algorithm group. Concurrently, we reviewed the cost-effectiveness of this new algorithm compared with the traditional workup. The procedure charges for the diagnosis and treatment of each episode of GIB was ~ $2,902 in the new algorithm group versus ~ $9,013 in the traditional algorithm group (p < 0.0001). Following the new algorithm in VAD patients with GIB resulted in fewer transfusions and diagnostic tests while attaining a substantial cost savings per episode of bleeding.

Screen and clean: a tool for identifying interactions in genome-wide association studies.

PubMed

Wu, Jing; Devlin, Bernie; Ringquist, Steven; Trucco, Massimo; Roeder, Kathryn

2010-04-01

Epistasis could be an important source of risk for disease. How interacting loci might be discovered is an open question for genome-wide association studies (GWAS). Most researchers limit their statistical analyses to testing individual pairwise interactions (i.e., marginal tests for association). A more effective means of identifying important predictors is to fit models that include many predictors simultaneously (i.e., higher-dimensional models). We explore a procedure called screen and clean (SC) for identifying liability loci, including interactions, by using the lasso procedure, which is a model selection tool for high-dimensional regression. We approach the problem by using a varying dictionary consisting of terms to include in the model. In the first step the lasso dictionary includes only main effects. The most promising single-nucleotide polymorphisms (SNPs) are identified using a screening procedure. Next the lasso dictionary is adjusted to include these main effects and the corresponding interaction terms. Again, promising terms are identified using lasso screening. Then significant terms are identified through the cleaning process. Implementation of SC for GWAS requires algorithms to explore the complex model space induced by the many SNPs genotyped and their interactions. We propose and explore a set of algorithms and find that SC successfully controls Type I error while yielding good power to identify risk loci and their interactions. When the method is applied to data obtained from the Wellcome Trust Case Control Consortium study of Type 1 Diabetes it uncovers evidence supporting interaction within the HLA class II region as well as within Chromosome 12q24.

Performance Analysis of Different Backoff Algorithms for WBAN-Based Emerging Sensor Networks

PubMed Central

Khan, Pervez; Ullah, Niamat; Ali, Farman; Ullah, Sana; Hong, Youn-Sik; Lee, Ki-Young; Kim, Hoon

2017-01-01

The Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) procedure of IEEE 802.15.6 Medium Access Control (MAC) protocols for the Wireless Body Area Network (WBAN) use an Alternative Binary Exponential Backoff (ABEB) procedure. The backoff algorithm plays an important role to avoid collision in wireless networks. The Binary Exponential Backoff (BEB) algorithm used in different standards does not obtain the optimum performance due to enormous Contention Window (CW) gaps induced from packet collisions. Therefore, The IEEE 802.15.6 CSMA/CA has developed the ABEB procedure to avoid the large CW gaps upon each collision. However, the ABEB algorithm may lead to a high collision rate (as the CW size is incremented on every alternative collision) and poor utilization of the channel due to the gap between the subsequent CW. To minimize the gap between subsequent CW sizes, we adopted the Prioritized Fibonacci Backoff (PFB) procedure. This procedure leads to a smooth and gradual increase in the CW size, after each collision, which eventually decreases the waiting time, and the contending node can access the channel promptly with little delay; while ABEB leads to irregular and fluctuated CW values, which eventually increase collision and waiting time before a re-transmission attempt. We analytically approach this problem by employing a Markov chain to design the PFB scheme for the CSMA/CA procedure of the IEEE 80.15.6 standard. The performance of the PFB algorithm is compared against the ABEB function of WBAN CSMA/CA. The results show that the PFB procedure adopted for IEEE 802.15.6 CSMA/CA outperforms the ABEB procedure. PMID:28257112

Arthroscopic treatment options for irreparable rotator cuff tears of the shoulder

PubMed Central

Anley, Cameron M; Chan, Samuel KL; Snow, Martyn

2014-01-01

The management of patients with irreparable rotator cuff tears remains a challenge for orthopaedic surgeons with the final treatment option in many algorithms being either a reverse shoulder arthroplasty or a tendon transfer. The long term results of these procedures are however still widely debated, especially in younger patients. A variety of arthroscopic treatment options have been proposed for patients with an irreparable rotator cuff tear without the presence of arthritis of the glenohumeral joint. These include a simple debridement with or without a biceps tenotomy, partial rotator cuff repair with or without an interval slide, tuberplasty, graft interposition of the rotator cuff, suprascapular nerve ablation, superior capsule reconstruction and insertion of a biodegradable spacer (Inspace) to depress the humeral head. These options should be considered as part of the treatment algorithm in patients with an irreparable rotator cuff and could be used as either as an interim procedure, delaying the need for more invasive surgery in the physiologically young and active, or as potential definitive procedures in the medically unfit. The aim of this review is to highlight and summarise arthroscopic procedures and the results thereof currently utilised in the management of these challenging patients. PMID:25405083

One-year results of an algorithmic approach to managing failed back surgery syndrome

PubMed Central

Avellanal, Martín; Diaz-Reganon, Gonzalo; Orts, Alejandro; Soto, Silvia

2014-01-01

BACKGROUND: Failed back surgery syndrome (FBSS) is a major clinical problem. Different etiologies with different incidence rates have been proposed. There are currently no standards regarding the management of these patients. Epiduroscopy is an endoscopic technique that may play a role in the management of FBSS. OBJECTIVE: To evaluate an algorithm for management of severe FBSS including epiduroscopy as a diagnostic and therapeutic tool. METHODS: A total of 133 patients with severe symptoms of FBSS (visual analogue scale score ≥7) and no response to pharmacological treatment and physical therapy were included. A six-step management algorithm was applied. Data, including patient demographics, pain and surgical procedure, were analyzed. In all cases, one or more objective causes of pain were established. Treatment success was defined as ≥50% long-term pain relief maintained during the first year of follow-up. Final allocation of patients was registered: good outcome with conservative treatment, surgical reintervention and palliative treatment with implantable devices. RESULTS: Of 122 patients enrolled, 59.84% underwent instrumented surgery and 40.16% a noninstrumented procedure. Most (64.75%) experienced significant pain relief with conventional pain clinic treatments; 15.57% required surgical treatment. Palliative spinal cord stimulation and spinal analgesia were applied in 9.84% and 2.46% of the cases, respectively. The most common diagnosis was epidural fibrosis, followed by disc herniation, global or lateral stenosis, and foraminal stenosis. CONCLUSIONS: A new six-step ladder approach to severe FBSS management that includes epiduroscopy was analyzed. Etiologies are accurately described and a useful role of epiduroscopy was confirmed. PMID:25222573

Decomposing the electromagnetic response of magnetic dipoles to determine the geometric parameters of a dipole conductor

NASA Astrophysics Data System (ADS)

Desmarais, Jacques K.; Smith, Richard S.

2016-03-01

A novel automatic data interpretation algorithm is presented for modelling airborne electromagnetic (AEM) data acquired over resistive environments, using a single-component (vertical) transmitter, where the position and orientation of a dipole conductor is allowed to vary in three dimensions. The algorithm assumes that the magnetic fields produced from compact vortex currents are expressed as a linear combinations of the fields arising from dipoles in the subsurface oriented parallel to the [1, 0, 0], [0, 1, 0], and [0, 0, 1], unit vectors. In this manner, AEM responses can be represented as 12 terms. The relative size of each term in the decomposition can be used to determine geometrical information about the orientation of the subsurface conductivity structure. The geometrical parameters of the dipole (location, depth, dip, strike) are estimated using a combination of a look-up table and a matrix inverted in a least-squares sense. Tests on 703 synthetic models show that the algorithm is capable of extracting most of the correct geometrical parameters of a dipole conductor when three-component receiver data is included in the interpretation procedure. The algorithm is unstable when the target is perfectly horizontal, as the strike is undefined. Ambiguities may occur in predicting the orientation of the dipole conductor if y-component data is excluded from the analysis. Application of our approach to an anomaly on line 15 of the Reid Mahaffy test site yields geometrical parameters in reasonable agreement with previous authors. However, our algorithm provides additional information on the strike and offset from the traverse line of the conductor. Disparities in the values of predicted dip and depth are within the range of numerical precision. The index of fit was better when strike and offset were included in the interpretation procedure. Tests on the data from line 15701 of the Chibougamau MEGATEM survey shows that the algorithm is applicable to situations where three-component AEM data is available.

Evidence-based algorithm for diagnosis and assessment in psoriatic arthritis: results by Italian DElphi in psoriatic Arthritis (IDEA).

PubMed

Lapadula, G; Marchesoni, A; Salaffi, F; Ramonda, R; Salvarani, C; Punzi, L; Costa, L; Caso, F; Simone, D; Baiocchi, G; Scioscia, C; Di Carlo, M; Scarpa, R; Ferraccioli, G

2016-12-16

Psoriatic arthritis (PsA) is a chronic inflammatory disease involving skin, peripheral joints, entheses, and axial skeleton. The disease is frequently associated with extrarticular manifestations (EAMs) and comorbidities. In order to create a protocol for PsA diagnosis and global assessment of patients with an algorithm based on anamnestic, clinical, laboratory and imaging procedures, we established a DElphi study on a national scale, named Italian DElphi in psoriatic Arthritis (IDEA). After a literature search, a Delphi poll, involving 52 rheumatologists, was performed. On the basis of the literature search, 202 potential items were identified. The steering committee planned at least two Delphi rounds. In the first Delphi round, the experts judged each of the 202 items using a score ranging from 1 to 9 based on its increasing clinical relevance. The questions posed to experts were How relevant is this procedure/observation/sign/symptom for assessment of a psoriatic arthritis patient? Proposals of additional items, not included in the questionnaire, were also encouraged. The results of the poll were discussed by the Steering Committee, which evaluated the necessity for removing selected procedures or adding additional ones, according to criteria of clinical appropriateness and sustainability. A total of 43 recommended diagnosis and assessment procedures, recognized as items, were derived by combination of the Delphi survey and two National Expert Meetings, and grouped in different areas. Favourable opinion was reached in 100% of cases for several aspects covering the following areas: medical (familial and personal) history, physical evaluation, imaging tool, second level laboratory tests, disease activity measurement and extrarticular manifestations. After performing PsA diagnosis, identification of specific disease activity scores and clinimetric approaches were suggested for assessing the different clinical subsets. Further, results showed the need for investigation on the presence of several EAMs and risk factors. In the context of any area, a rank was assigned for each item by Expert Committee members, in order to create the logical sequence of the algorithm. The final list of recommended diagnosis and assessment procedures, by the Delphi survey and the two National Expert Meetings, was also reported as an algorithm. This study shows results obtained by the combination of a DElphi survey of a group of Italian rheumatologists and two National Expert Meetings, created with the aim of establishing a clinical procedure and algorithm for the diagnosis and the assessment of PsA patients. In order to find accurate and practical diagnostic and assessment items in clinical practice, we have focused our attention on evaluating the different PsA domains. Hence, we conceived the IDEA algorithm in order to address PsA diagnosis and assessment in the context of daily clinical practice. The IDEA algorithm might eventually lead to a multidimensional approach and could represent a useful and practical tool for addressing diagnosis and for assessing the disease appropriately. However, the elaborated algorithm needs to be further investigated in daily practice, for evidencing and proving its eventual efficacy in detecting and staging PsA and its heterogeneous spectrum appropriately.

Shape-Driven 3D Segmentation Using Spherical Wavelets

PubMed Central

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

2013-01-01

This paper presents a novel active surface segmentation algorithm using a multiscale shape representation and prior. We define a parametric model of a surface using spherical wavelet functions and learn a prior probability distribution over the wavelet coefficients to model shape variations at different scales and spatial locations in a training set. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior in the segmentation framework. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to the segmentation of brain caudate nucleus, of interest in the study of schizophrenia. Our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm by capturing finer shape details. PMID:17354875

How anaesthesiologists understand difficult airway guidelines-an interview study.

PubMed

Knudsen, Kati; Pöder, Ulrika; Nilsson, Ulrica; Högman, Marieann; Larsson, Anders; Larsson, Jan

2017-11-01

In the practice of anaesthesia, clinical guidelines that aim to improve the safety of airway procedures have been developed. The aim of this study was to explore how anaesthesiologists understand or conceive of difficult airway management algorithms. A qualitative phenomenographic design was chosen to explore anaesthesiologists' views on airway algorithms. Anaesthesiologists working in three hospitals were included. Individual face-to-face interviews were conducted. Four different ways of understanding were identified, describing airway algorithms as: (A) a law-like rule for how to act in difficult airway situations; (B) a cognitive aid, an action plan for difficult airway situations; (C) a basis for developing flexible, personal action plans for the difficult airway; and (D) the experts' consensus, a set of scientifically based guidelines for handling the difficult airway. The interviewed anaesthesiologists understood difficult airway management guidelines/algorithms very differently.

The Simplified Aircraft-Based Paired Approach With the ALAS Alerting Algorithm

NASA Technical Reports Server (NTRS)

Perry, Raleigh B.; Madden, Michael M.; Torres-Pomales, Wilfredo; Butler, Ricky W.

2013-01-01

This paper presents the results of an investigation of a proposed concept for closely spaced parallel runways called the Simplified Aircraft-based Paired Approach (SAPA). This procedure depends upon a new alerting algorithm called the Adjacent Landing Alerting System (ALAS). This study used both low fidelity and high fidelity simulations to validate the SAPA procedure and test the performance of the new alerting algorithm. The low fidelity simulation enabled a determination of minimum approach distance for the worst case over millions of scenarios. The high fidelity simulation enabled an accurate determination of timings and minimum approach distance in the presence of realistic trajectories, communication latencies, and total system error for 108 test cases. The SAPA procedure and the ALAS alerting algorithm were applied to the 750-ft parallel spacing (e.g., SFO 28L/28R) approach problem. With the SAPA procedure as defined in this paper, this study concludes that a 750-ft application does not appear to be feasible, but preliminary results for 1000-ft parallel runways look promising.

A computational procedure for multibody systems including flexible beam dynamics

NASA Technical Reports Server (NTRS)

Downer, J. D.; Park, K. C.; Chiou, J. C.

1990-01-01

A computational procedure suitable for the solution of equations of motions for flexible multibody systems has been developed. The flexible beams are modeled using a fully nonlinear theory which accounts for both finite rotations and large deformations. The present formulation incorporates physical measures of conjugate Cauchy stress and covariant strain increments. As a consequence, the beam model can easily be interfaced with real-time strain measurements and feedback control systems. A distinct feature of the present work is the computational preservation of total energy for undamped systems; this is obtained via an objective strain increment/stress update procedure combined with an energy-conserving time integration algorithm which contains an accurate update of angular orientations. The procedure is demonstrated via several example problems.

Model Specification Searches Using Ant Colony Optimization Algorithms

ERIC Educational Resources Information Center

Marcoulides, George A.; Drezner, Zvi

2003-01-01

Ant colony optimization is a recently proposed heuristic procedure inspired by the behavior of real ants. This article applies the procedure to model specification searches in structural equation modeling and reports the results. The results demonstrate the capabilities of ant colony optimization algorithms for conducting automated searches.

Implementation and impact of a consensus diagnostic and management algorithm for complicated pneumonia in children.

PubMed

Pillai, Dinesh; Song, Xiaoyan; Pastor, William; Ottolini, Mary; Powell, David; Wiedermann, Bernhard L; DeBiasi, Roberta L

2011-12-01

Variable treatment exists for children with bacterial pneumonia complications such as pleural effusion and empyema. Subspecialists at an urban academic tertiary children's hospital created a literature-based diagnosis and management algorithm for complicated pneumonia in children. We proposed that algorithm implementation would reduce use of computed tomography (CT) for diagnosis of pleural infection, thereby decreasing radiation exposure, without increased adverse outcomes. A cross-sectional study was undertaken in children (3 months to 20 years old) with principal or secondary diagnosis codes for empyema and/or pleural effusion in conjunction with bacterial pneumonia. Study cohorts consisted of subjects admitted 15 months before (cohort 1, n = 83) and after (cohort 2, n = 87) algorithm implementation. Data were collected using clinical and financial data systems. Imaging studies and procedures were identified using Current Procedural Terminology codes. Statistical analysis included χ test, linear and ordinal regression, and analysis of variance. Age (P = 0.56), sex (P = 0.30), diagnoses (P = 0.12), and severity level (P = 0.84) were similar between cohorts. There was a significant decrease in CT use in cohort 2 (cohort 1, 60% vs cohort 2, 17.2%; P = 0.001) and reduction in readmission rate (7.7% vs 0%; P = 0.01) and video-assisted thoracoscopic surgery procedures (44.6% vs 28.7; P = 0.03), without concomitant increases in vancomycin use (34.9% vs 34.5%; P = 0.95) or hospital length of stay (6.4 vs 7.6 days; P = 0.4). Among patients who received video-assisted thoracoscopic surgery drainage (n = 57), there were no significant differences between cohorts in median time from admission to video-assisted thoracoscopic surgery (2 days; P = 0.29) or median duration of chest tube drainage (3 vs 4 days; P = 0.10). There was a statistically nonsignificant trend for higher rate of pathogen identification in cohort 2 (cohort 1, 33% vs cohort 2, 54.1%; P = 0.12); Streptococcus pneumonia was the most commonly identified pathogen in both cohorts (37.5% vs 27%; P = 0.23). Implementation of an institutional complicated pneumonia management algorithm reduced CT scan use/radiation exposure, VATS procedures, and readmission rate in children with a diagnosis of pleural infection, without associated increases in length of stay or vancomycin use. This algorithm provides the framework for future prospective quality improvement studies in pediatric patients with complicated pneumonia.

Colony image acquisition and segmentation

NASA Astrophysics Data System (ADS)

Wang, W. X.

2007-12-01

For counting of both colonies and plaques, there is a large number of applications including food, dairy, beverages, hygiene, environmental monitoring, water, toxicology, sterility testing, AMES testing, pharmaceuticals, paints, sterile fluids and fungal contamination. Recently, many researchers and developers have made efforts for this kind of systems. By investigation, some existing systems have some problems. The main problems are image acquisition and image segmentation. In order to acquire colony images with good quality, an illumination box was constructed as: the box includes front lightning and back lightning, which can be selected by users based on properties of colony dishes. With the illumination box, lightning can be uniform; colony dish can be put in the same place every time, which make image processing easy. The developed colony image segmentation algorithm consists of the sub-algorithms: (1) image classification; (2) image processing; and (3) colony delineation. The colony delineation algorithm main contain: the procedures based on grey level similarity, on boundary tracing, on shape information and colony excluding. In addition, a number of algorithms are developed for colony analysis. The system has been tested and satisfactory.

A Spatio-Temporal Algorithmic Procedure for Environmental Policymaking in the Municipality of Arkalochori in the Greek Island of Crete

NASA Astrophysics Data System (ADS)

Batzias, F. A.; Sidiras, D. K.; Giannopoulos, Ch.; Spetsidis, I.

2009-08-01

This work deals with a methodological framework designed/developed under the form of a spatio-temporal algorithmic procedure for environmental policymaking at local level. The procedure includes 25 activity stages and 9 decision nodes, putting emphasis on (i) mapping on GIS layers water supply/demand and modeling of aquatic pollution coming from point and non-point sources, (ii) environmental monitoring by periodically measuring the main pollutants in situ and in the laboratory, (iii) design of environmental projects, decomposition of them into sub-projects and combination of the latter to form attainable alternatives, (iv) multicriteria ranking of alternatives, according to a modified Delphi method, by using as criteria the expected environmental benefit, the attitude of inhabitants, the priority within the programme of regional development, the capital required for the investment and the operating cost, and (v) knowledge Base (KB) operation/enrichment, functioning in combination with a data mining mechanism to extract knowledge/information/data from external Bases. An implementation is presented referring to the Municipality of Arkalochori in the Greek island of Crete.

Progress on a generalized coordinates tensor product finite element 3DPNS algorithm for subsonic

NASA Technical Reports Server (NTRS)

Baker, A. J.; Orzechowski, J. A.

1983-01-01

A generalized coordinates form of the penalty finite element algorithm for the 3-dimensional parabolic Navier-Stokes equations for turbulent subsonic flows was derived. This algorithm formulation requires only three distinct hypermatrices and is applicable using any boundary fitted coordinate transformation procedure. The tensor matrix product approximation to the Jacobian of the Newton linear algebra matrix statement was also derived. Tne Newton algorithm was restructured to replace large sparse matrix solution procedures with grid sweeping using alpha-block tridiagonal matrices, where alpha equals the number of dependent variables. Numerical experiments were conducted and the resultant data gives guidance on potentially preferred tensor product constructions for the penalty finite element 3DPNS algorithm.

Modeling and characterization of the Earth Radiation Budget Experiment (ERBE) nonscanner and scanner sensors

NASA Technical Reports Server (NTRS)

Halyo, Nesim; Pandey, Dhirendra K.; Taylor, Deborah B.

1989-01-01

The Earth Radiation Budget Experiment (ERBE) is making high-absolute-accuracy measurements of the reflected solar and Earth-emitted radiation as well as the incoming solar radiation from three satellites: ERBS, NOAA-9, and NOAA-10. Each satellite has four Earth-looking nonscanning radiometers and three scanning radiometers. A fifth nonscanner, the solar monitor, measures the incoming solar radiation. The development of the ERBE sensor characterization procedures are described using the calibration data for each of the Earth-looking nonscanners and scanners. Sensor models for the ERBE radiometers are developed including the radiative exchange, conductive heat flow, and electronics processing for transient and steady state conditions. The steady state models are used to interpret the sensor outputs, resulting in the data reduction algorithms for the ERBE instruments. Both ground calibration and flight calibration procedures are treated and analyzed. The ground and flight calibration coefficients for the data reduction algorithms are presented.

Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System

PubMed Central

Kim, Sungkon; Lee, Jungwhee; Park, Min-Seok; Jo, Byung-Wan

2009-01-01

This paper describes the procedures for development of signal analysis algorithms using artificial neural networks for Bridge Weigh-in-Motion (B-WIM) systems. Through the analysis procedure, the extraction of information concerning heavy traffic vehicles such as weight, speed, and number of axles from the time domain strain data of the B-WIM system was attempted. As one of the several possible pattern recognition techniques, an Artificial Neural Network (ANN) was employed since it could effectively include dynamic effects and bridge-vehicle interactions. A number of vehicle traveling experiments with sufficient load cases were executed on two different types of bridges, a simply supported pre-stressed concrete girder bridge and a cable-stayed bridge. Different types of WIM systems such as high-speed WIM or low-speed WIM were also utilized during the experiments for cross-checking and to validate the performance of the developed algorithms. PMID:22408487

Aerodynamics of Engine-Airframe Interaction

NASA Technical Reports Server (NTRS)

Caughey, D. A.

1986-01-01

The report describes progress in research directed towards the efficient solution of the inviscid Euler and Reynolds-averaged Navier-Stokes equations for transonic flows through engine inlets, and past complete aircraft configurations, with emphasis on the flowfields in the vicinity of engine inlets. The research focusses upon the development of solution-adaptive grid procedures for these problems, and the development of multi-grid algorithms in conjunction with both, implicit and explicit time-stepping schemes for the solution of three-dimensional problems. The work includes further development of mesh systems suitable for inlet and wing-fuselage-inlet geometries using a variational approach. Work during this reporting period concentrated upon two-dimensional problems, and has been in two general areas: (1) the development of solution-adaptive procedures to cluster the grid cells in regions of high (truncation) error;and (2) the development of a multigrid scheme for solution of the two-dimensional Euler equations using a diagonalized alternating direction implicit (ADI) smoothing algorithm.

Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System.

PubMed

Kim, Sungkon; Lee, Jungwhee; Park, Min-Seok; Jo, Byung-Wan

2009-01-01

This paper describes the procedures for development of signal analysis algorithms using artificial neural networks for Bridge Weigh-in-Motion (B-WIM) systems. Through the analysis procedure, the extraction of information concerning heavy traffic vehicles such as weight, speed, and number of axles from the time domain strain data of the B-WIM system was attempted. As one of the several possible pattern recognition techniques, an Artificial Neural Network (ANN) was employed since it could effectively include dynamic effects and bridge-vehicle interactions. A number of vehicle traveling experiments with sufficient load cases were executed on two different types of bridges, a simply supported pre-stressed concrete girder bridge and a cable-stayed bridge. Different types of WIM systems such as high-speed WIM or low-speed WIM were also utilized during the experiments for cross-checking and to validate the performance of the developed algorithms.

Systems and methods for predicting materials properties

DOEpatents

Ceder, Gerbrand; Fischer, Chris; Tibbetts, Kevin; Morgan, Dane; Curtarolo, Stefano

2007-11-06

Systems and methods for predicting features of materials of interest. Reference data are analyzed to deduce relationships between the input data sets and output data sets. Reference data includes measured values and/or computed values. The deduced relationships can be specified as equations, correspondences, and/or algorithmic processes that produce appropriate output data when suitable input data is used. In some instances, the output data set is a subset of the input data set, and computational results may be refined by optionally iterating the computational procedure. To deduce features of a new material of interest, a computed or measured input property of the material is provided to an equation, correspondence, or algorithmic procedure previously deduced, and an output is obtained. In some instances, the output is iteratively refined. In some instances, new features deduced for the material of interest are added to a database of input and output data for known materials.

Efficient fractal-based mutation in evolutionary algorithms from iterated function systems

NASA Astrophysics Data System (ADS)

Salcedo-Sanz, S.; Aybar-Ruíz, A.; Camacho-Gómez, C.; Pereira, E.

2018-03-01

In this paper we present a new mutation procedure for Evolutionary Programming (EP) approaches, based on Iterated Function Systems (IFSs). The new mutation procedure proposed consists of considering a set of IFS which are able to generate fractal structures in a two-dimensional phase space, and use them to modify a current individual of the EP algorithm, instead of using random numbers from different probability density functions. We test this new proposal in a set of benchmark functions for continuous optimization problems. In this case, we compare the proposed mutation against classical Evolutionary Programming approaches, with mutations based on Gaussian, Cauchy and chaotic maps. We also include a discussion on the IFS-based mutation in a real application of Tuned Mass Dumper (TMD) location and optimization for vibration cancellation in buildings. In both practical cases, the proposed EP with the IFS-based mutation obtained extremely competitive results compared to alternative classical mutation operators.

Construction of hydrodynamic bead models from high-resolution X-ray crystallographic or nuclear magnetic resonance data.

PubMed Central

Byron, O

1997-01-01

Computer software such as HYDRO, based upon a comprehensive body of theoretical work, permits the hydrodynamic modeling of macromolecules in solution, which are represented to the computer interface as an assembly of spheres. The uniqueness of any satisfactory resultant model is optimized by incorporating into the modeling procedure the maximal possible number of criteria to which the bead model must conform. An algorithm (AtoB, for atoms to beads) that permits the direct construction of bead models from high resolution x-ray crystallographic or nuclear magnetic resonance data has now been formulated and tested. Models so generated then act as informed starting estimates for the subsequent iterative modeling procedure, thereby hastening the convergence to reasonable representations of solution conformation. Successful application of this algorithm to several proteins shows that predictions of hydrodynamic parameters, including those concerning solvation, can be confirmed. PMID:8994627

Two Topics in Data Analysis: Sample-based Optimal Transport and Analysis of Turbulent Spectra from Ship Track Data

NASA Astrophysics Data System (ADS)

Kuang, Simeng Max

This thesis contains two topics in data analysis. The first topic consists of the introduction of algorithms for sample-based optimal transport and barycenter problems. In chapter 1, a family of algorithms is introduced to solve both the L2 optimal transport problem and the Wasserstein barycenter problem. Starting from a theoretical perspective, the new algorithms are motivated from a key characterization of the barycenter measure, which suggests an update that reduces the total transportation cost and stops only when the barycenter is reached. A series of general theorems is given to prove the convergence of all the algorithms. We then extend the algorithms to solve sample-based optimal transport and barycenter problems, in which only finite sample sets are available instead of underlying probability distributions. A unique feature of the new approach is that it compares sample sets in terms of the expected values of a set of feature functions, which at the same time induce the function space of optimal maps and can be chosen by users to incorporate their prior knowledge of the data. All the algorithms are implemented and applied to various synthetic example and practical applications. On synthetic examples it is found that both the SOT algorithm and the SCB algorithm are able to find the true solution and often converge in a handful of iterations. On more challenging applications including Gaussian mixture models, color transfer and shape transform problems, the algorithms give very good results throughout despite the very different nature of the corresponding datasets. In chapter 2, a preconditioning procedure is developed for the L2 and more general optimal transport problems. The procedure is based on a family of affine map pairs, which transforms the original measures into two new measures that are closer to each other, while preserving the optimality of solutions. It is proved that the preconditioning procedure minimizes the remaining transportation cost among all admissible affine maps. The procedure can be used on both continuous measures and finite sample sets from distributions. In numerical examples, the procedure is applied to multivariate normal distributions, to a two-dimensional shape transform problem and to color transfer problems. For the second topic, we present an extension to anisotropic flows of the recently developed Helmholtz and wave-vortex decomposition method for one-dimensional spectra measured along ship or aircraft tracks in Buhler et al. (J. Fluid Mech., vol. 756, 2014, pp. 1007-1026). While in the original method the flow was assumed to be homogeneous and isotropic in the horizontal plane, we allow the flow to have a simple kind of horizontal anisotropy that is chosen in a self-consistent manner and can be deduced from the one-dimensional power spectra of the horizontal velocity fields and their cross-correlation. The key result is that an exact and robust Helmholtz decomposition of the horizontal kinetic energy spectrum can be achieved in this anisotropic flow setting, which then also allows the subsequent wave-vortex decomposition step. The new method is developed theoretically and tested with encouraging results on challenging synthetic data as well as on ocean data from the Gulf Stream.

Multi-Objective Community Detection Based on Memetic Algorithm

PubMed Central

2015-01-01

Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels. PMID:25932646

Multi-objective community detection based on memetic algorithm.

PubMed

Wu, Peng; Pan, Li

2015-01-01

Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels.

HEURISTIC OPTIMIZATION AND ALGORITHM TUNING APPLIED TO SORPTIVE BARRIER DESIGN

EPA Science Inventory

While heuristic optimization is applied in environmental applications, ad-hoc algorithm configuration is typical. We use a multi-layer sorptive barrier design problem as a benchmark for an algorithm-tuning procedure, as applied to three heuristics (genetic algorithms, simulated ...

Optimal control of CPR procedure using hemodynamic circulation model

DOEpatents

Lenhart, Suzanne M.; Protopopescu, Vladimir A.; Jung, Eunok

2007-12-25

A method for determining a chest pressure profile for cardiopulmonary resuscitation (CPR) includes the steps of representing a hemodynamic circulation model based on a plurality of difference equations for a patient, applying an optimal control (OC) algorithm to the circulation model, and determining a chest pressure profile. The chest pressure profile defines a timing pattern of externally applied pressure to a chest of the patient to maximize blood flow through the patient. A CPR device includes a chest compressor, a controller communicably connected to the chest compressor, and a computer communicably connected to the controller. The computer determines the chest pressure profile by applying an OC algorithm to a hemodynamic circulation model based on the plurality of difference equations.

Progress on automated data analysis algorithms for ultrasonic inspection of composites

NASA Astrophysics Data System (ADS)

Aldrin, John C.; Forsyth, David S.; Welter, John T.

2015-03-01

Progress is presented on the development and demonstration of automated data analysis (ADA) software to address the burden in interpreting ultrasonic inspection data for large composite structures. The automated data analysis algorithm is presented in detail, which follows standard procedures for analyzing signals for time-of-flight indications and backwall amplitude dropout. New algorithms have been implemented to reliably identify indications in time-of-flight images near the front and back walls of composite panels. Adaptive call criteria have also been applied to address sensitivity to variation in backwall signal level, panel thickness variation, and internal signal noise. ADA processing results are presented for a variety of test specimens that include inserted materials and discontinuities produced under poor manufacturing conditions. Software tools have been developed to support both ADA algorithm design and certification, producing a statistical evaluation of indication results and false calls using a matching process with predefined truth tables. Parametric studies were performed to evaluate detection and false call results with respect to varying algorithm settings.

An unconditionally stable staggered algorithm for transient finite element analysis of coupled thermoelastic problems

NASA Technical Reports Server (NTRS)

Farhat, C.; Park, K. C.; Dubois-Pelerin, Y.

1991-01-01

An unconditionally stable second order accurate implicit-implicit staggered procedure for the finite element solution of fully coupled thermoelasticity transient problems is proposed. The procedure is stabilized with a semi-algebraic augmentation technique. A comparative cost analysis reveals the superiority of the proposed computational strategy to other conventional staggered procedures. Numerical examples of one and two-dimensional thermomechanical coupled problems demonstrate the accuracy of the proposed numerical solution algorithm.

Detecting non-orthology in the COGs database and other approaches grouping orthologs using genome-specific best hits.

PubMed

Dessimoz, Christophe; Boeckmann, Brigitte; Roth, Alexander C J; Gonnet, Gaston H

2006-01-01

Correct orthology assignment is a critical prerequisite of numerous comparative genomics procedures, such as function prediction, construction of phylogenetic species trees and genome rearrangement analysis. We present an algorithm for the detection of non-orthologs that arise by mistake in current orthology classification methods based on genome-specific best hits, such as the COGs database. The algorithm works with pairwise distance estimates, rather than computationally expensive and error-prone tree-building methods. The accuracy of the algorithm is evaluated through verification of the distribution of predicted cases, case-by-case phylogenetic analysis and comparisons with predictions from other projects using independent methods. Our results show that a very significant fraction of the COG groups include non-orthologs: using conservative parameters, the algorithm detects non-orthology in a third of all COG groups. Consequently, sequence analysis sensitive to correct orthology assignments will greatly benefit from these findings.

How anaesthesiologists understand difficult airway guidelines—an interview study

PubMed Central

Knudsen, Kati; Nilsson, Ulrica; Larsson, Anders; Larsson, Jan

2017-01-01

Background In the practice of anaesthesia, clinical guidelines that aim to improve the safety of airway procedures have been developed. The aim of this study was to explore how anaesthesiologists understand or conceive of difficult airway management algorithms. Methods A qualitative phenomenographic design was chosen to explore anaesthesiologists’ views on airway algorithms. Anaesthesiologists working in three hospitals were included. Individual face-to-face interviews were conducted. Results Four different ways of understanding were identified, describing airway algorithms as: (A) a law-like rule for how to act in difficult airway situations; (B) a cognitive aid, an action plan for difficult airway situations; (C) a basis for developing flexible, personal action plans for the difficult airway; and (D) the experts’ consensus, a set of scientifically based guidelines for handling the difficult airway. Conclusions The interviewed anaesthesiologists understood difficult airway management guidelines/algorithms very differently. PMID:29299973

Identification of Genes Involved in Breast Cancer Metastasis by Integrating Protein-Protein Interaction Information with Expression Data.

PubMed

Tian, Xin; Xin, Mingyuan; Luo, Jian; Liu, Mingyao; Jiang, Zhenran

2017-02-01

The selection of relevant genes for breast cancer metastasis is critical for the treatment and prognosis of cancer patients. Although much effort has been devoted to the gene selection procedures by use of different statistical analysis methods or computational techniques, the interpretation of the variables in the resulting survival models has been limited so far. This article proposes a new Random Forest (RF)-based algorithm to identify important variables highly related with breast cancer metastasis, which is based on the important scores of two variable selection algorithms, including the mean decrease Gini (MDG) criteria of Random Forest and the GeneRank algorithm with protein-protein interaction (PPI) information. The new gene selection algorithm can be called PPIRF. The improved prediction accuracy fully illustrated the reliability and high interpretability of gene list selected by the PPIRF approach.

Quality assessment of two- and three-dimensional unstructured meshes and validation of an upwind Euler flow solver

NASA Technical Reports Server (NTRS)

Woodard, Paul R.; Batina, John T.; Yang, Henry T. Y.

1992-01-01

Quality assessment procedures are described for two-dimensional unstructured meshes. The procedures include measurement of minimum angles, element aspect ratios, stretching, and element skewness. Meshes about the ONERA M6 wing and the Boeing 747 transport configuration are generated using an advancing front method grid generation package of programs. Solutions of Euler's equations for these meshes are obtained at low angle-of-attack, transonic conditions. Results for these cases, obtained as part of a validation study demonstrate accuracy of an implicit upwind Euler solution algorithm.

Treating convection in sequential solvers

NASA Technical Reports Server (NTRS)

Shyy, Wei; Thakur, Siddharth

1992-01-01

The treatment of the convection terms in the sequential solver, a standard procedure found in virtually all pressure based algorithms, to compute the flow problems with sharp gradients and source terms is investigated. Both scalar model problems and one-dimensional gas dynamics equations have been used to study the various issues involved. Different approaches including the use of nonlinear filtering techniques and adoption of TVD type schemes have been investigated. Special treatments of the source terms such as pressure gradients and heat release have also been devised, yielding insight and improved accuracy of the numerical procedure adopted.

A diagonal implicit scheme for computing flows with finite-rate chemistry

NASA Technical Reports Server (NTRS)

Eberhardt, Scott; Imlay, Scott

1990-01-01

A new algorithm for solving steady, finite-rate chemistry, flow problems is presented. The new scheme eliminates the expense of inverting large block matrices that arise when species conservation equations are introduced. The source Jacobian matrix is replaced by a diagonal matrix which is tailored to account for the fastest reactions in the chemical system. A point-implicit procedure is discussed and then the algorithm is included into the LU-SGS scheme. Solutions are presented for hypervelocity reentry and Hydrogen-Oxygen combustion. For the LU-SGS scheme a CFL number in excess of 10,000 has been achieved.

Moving base Gravity Gradiometer Survey System (GGSS) program

NASA Astrophysics Data System (ADS)

Pfohl, Louis; Rusnak, Walter; Jircitano, Albert; Grierson, Andrew

1988-04-01

The GGSS program began in early 1983 with the objective of delivering a landmobile and airborne system capable of fast, accurate, and economical gravity gradient surveys of large areas anywhere in the world. The objective included the development and use of post-mission data reduction software to process the survey data into solutions for the gravity disturbance vector components (north, east and vertical). This document describes the GGSS equipment hardware and software, integration and lab test procedures and results, and airborne and land survey procedures and results. Included are discussions on test strategies, post-mission data reduction algorithms, and the data reduction processing experience. Perspectives and conclusions are drawn from the results.

Genetic algorithms

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.

Nonparametric relevance-shifted multiple testing procedures for the analysis of high-dimensional multivariate data with small sample sizes.

PubMed

Frömke, Cornelia; Hothorn, Ludwig A; Kropf, Siegfried

2008-01-27

In many research areas it is necessary to find differences between treatment groups with several variables. For example, studies of microarray data seek to find a significant difference in location parameters from zero or one for ratios thereof for each variable. However, in some studies a significant deviation of the difference in locations from zero (or 1 in terms of the ratio) is biologically meaningless. A relevant difference or ratio is sought in such cases. This article addresses the use of relevance-shifted tests on ratios for a multivariate parallel two-sample group design. Two empirical procedures are proposed which embed the relevance-shifted test on ratios. As both procedures test a hypothesis for each variable, the resulting multiple testing problem has to be considered. Hence, the procedures include a multiplicity correction. Both procedures are extensions of available procedures for point null hypotheses achieving exact control of the familywise error rate. Whereas the shift of the null hypothesis alone would give straight-forward solutions, the problems that are the reason for the empirical considerations discussed here arise by the fact that the shift is considered in both directions and the whole parameter space in between these two limits has to be accepted as null hypothesis. The first algorithm to be discussed uses a permutation algorithm, and is appropriate for designs with a moderately large number of observations. However, many experiments have limited sample sizes. Then the second procedure might be more appropriate, where multiplicity is corrected according to a concept of data-driven order of hypotheses.

Group implicit concurrent algorithms in nonlinear structural dynamics

NASA Technical Reports Server (NTRS)

Ortiz, M.; Sotelino, E. D.

1989-01-01

During the 70's and 80's, considerable effort was devoted to developing efficient and reliable time stepping procedures for transient structural analysis. Mathematically, the equations governing this type of problems are generally stiff, i.e., they exhibit a wide spectrum in the linear range. The algorithms best suited to this type of applications are those which accurately integrate the low frequency content of the response without necessitating the resolution of the high frequency modes. This means that the algorithms must be unconditionally stable, which in turn rules out explicit integration. The most exciting possibility in the algorithms development area in recent years has been the advent of parallel computers with multiprocessing capabilities. So, this work is mainly concerned with the development of parallel algorithms in the area of structural dynamics. A primary objective is to devise unconditionally stable and accurate time stepping procedures which lend themselves to an efficient implementation in concurrent machines. Some features of the new computer architecture are summarized. A brief survey of current efforts in the area is presented. A new class of concurrent procedures, or Group Implicit algorithms is introduced and analyzed. The numerical simulation shows that GI algorithms hold considerable promise for application in coarse grain as well as medium grain parallel computers.

Minimum Sample Size Requirements for Mokken Scale Analysis

ERIC Educational Resources Information Center

Straat, J. Hendrik; van der Ark, L. Andries; Sijtsma, Klaas

2014-01-01

An automated item selection procedure in Mokken scale analysis partitions a set of items into one or more Mokken scales, if the data allow. Two algorithms are available that pursue the same goal of selecting Mokken scales of maximum length: Mokken's original automated item selection procedure (AISP) and a genetic algorithm (GA). Minimum…

BOPACE 3-D (the Boeing Plastic Analysis Capability for 3-dimensional Solids Using Isoparametric Finite Elements)

NASA Technical Reports Server (NTRS)

Vos, R. G.; Straayer, J. W.

1975-01-01

The BOPACE 3-D is a finite element computer program, which provides a general family of three-dimensional isoparametric solid elements, and includes a new algorithm for improving the efficiency of the elastic-plastic-creep solution procedure. Theoretical, user, and programmer oriented sections are presented to describe the program.

Rotary transformer design with fixed magnetizing and/or leakage inductances

NASA Technical Reports Server (NTRS)

Stuart, T. A.; King, R. J.; Shamseddin, H.

1985-01-01

A design algorithm is considered for transformers that must transfer electric power across a rotating interface. Among other features, this procedure allows the designer to minimize either weight or losses for either a fixed magnetizing inductance or a fixed leakage inductance. Numerical results are included to indicate the design trade-offs between various parameters.

An adaptive tensor voting algorithm combined with texture spectrum

NASA Astrophysics Data System (ADS)

Wang, Gang; Su, Qing-tang; Lü, Gao-huan; Zhang, Xiao-feng; Liu, Yu-huan; He, An-zhi

2015-01-01

An adaptive tensor voting algorithm combined with texture spectrum is proposed. The image texture spectrum is used to get the adaptive scale parameter of voting field. Then the texture information modifies both the attenuation coefficient and the attenuation field so that we can use this algorithm to create more significant and correct structures in the original image according to the human visual perception. At the same time, the proposed method can improve the edge extraction quality, which includes decreasing the flocculent region efficiently and making image clear. In the experiment for extracting pavement cracks, the original pavement image is processed by the proposed method which is combined with the significant curve feature threshold procedure, and the resulted image displays the faint crack signals submerged in the complicated background efficiently and clearly.

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Key, J.

1989-01-01

The objectives are to develop a suitable validation data set for evaluating the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) algorithm for cloud retrieval in polar regions, to identify limitations of current procedures and to explore potential means to remedy them using textural classifiers, and to compare synoptic cloud data from model runs with observations. Toward the first goal, a polar data set consisting of visible, thermal, and passive microwave data was developed. The AVHRR and SMMR data were digitally merged to a polar stereographic projection with an effective pixel size of 5 sq km. With this data set, two unconventional methods of classifying the imagery for the analysis of polar clouds and surfaces were examined: one based on fuzzy sets theory and another based on a trained neural network. An algorithm for cloud detection was developed from an early test version of the ISCCP algorithm. This algorithm includes the identification of surface types with passive microwave, then temporal tests at each pixel location in the cloud detection phase. Cloud maps and clear sky radiance composites for 5 day periods are produced. Algorithm testing and validation was done with both actural AVHRR/SMMR data, and simulated imagery. From this point in the algorithm, groups of cloud pixels are examined for their spectral and textural characteristics, and a procedure is developed for the analysis of cloud patterns utilizing albedo, IR temperature, and texture. In a completion of earlier work, empirical analyses of arctic cloud cover were explored through manual interpretations of DMSP imagery and compared to U.S. Air Force 3D-nephanalysis. Comparisons of observed cloudiness from existing climatologies to patterns computed by the GISS climate model were also made.

17 CFR Appendix A to Part 38 - Guidance on Compliance With Designation Criteria

Code of Federal Regulations, 2011 CFR

2011-04-01

...-matching algorithm and order entry procedures. An application involving a trade-matching algorithm that is... algorithm. (b) A designated contract market's specifications on initial and periodic objective testing and...

17 CFR Appendix A to Part 38 - Guidance on Compliance With Designation Criteria

Code of Federal Regulations, 2012 CFR

2012-04-01

...-matching algorithm and order entry procedures. An application involving a trade-matching algorithm that is... algorithm. (b) A designated contract market's specifications on initial and periodic objective testing and...

Two-year clinical follow-up after pulmonary vein isolation using high-intensity focused ultrasound (HIFU) and an esophageal temperature-guided safety algorithm.

PubMed

Neven, Kars; Metzner, Andreas; Schmidt, Boris; Ouyang, Feifan; Kuck, Karl-Heinz

2012-03-01

High-intensity frequency ultrasound (HIFU) can achieve pulmonary vein isolation (PVI), but severe complications have happened. An esophageal temperature (ET)-guided safety algorithm was implemented. We investigated medium-term outcome. After left atrial access, HIFU was applied until complete PVI. The safety algorithm was as follows: ≤3 complete ablations per pulmonary vein, early abortion when ET ≥40.0°C, use of Power Modulation at ET >39.0°C or when after 20 to 30 seconds no change in PV electrograms: to reduce the ablation temperature in the surrounding tissue, acoustic power is switched on and off with a frequency of 1 Hz; in all first ablations, use of Power Modulation after 50% of programmed time. Touch-up radiofrequency ablation when PVI failed. Follow-up included interviews and Holter electrocardiograms. Recurrence was defined as atrial fibrillation (AF) >30 seconds without a blanking period. A total of 28 symptomatic patients (18 males, age 63 years), with paroxysmal AF (n = 19) and persistent AF (n = 9) were included. After a median follow-up of 738 days, 22 of the 28 patients (79%) were free of AF without antiarrhythmic drugs. After 1 repeat procedure with radiofrequency ablation, 5 patients remained free of AF. The complications were as follows: 1 lethal atrial-to-esophageal fistula at day 31, 1 pericardial effusion at day 48, 1 unexplained death at day 49, and 2 persistent phrenic nerve palsies with full recovery within 12 months. Two-year follow-up after PVI using HIFU and an ET-guided safety algorithm shows success rates similar to those of radiofrequency-based procedures but with higher complication rates. Importantly, the ET-guided safety algorithm failed to prevent severe complications. HIFU does not meet safety standards required for the treatment of AF, and this led to a halt of its clinical use. Copyright © 2012 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Diffeomorphic demons: efficient non-parametric image registration.

PubMed

Vercauteren, Tom; Pennec, Xavier; Perchant, Aymeric; Ayache, Nicholas

2009-03-01

We propose an efficient non-parametric diffeomorphic image registration algorithm based on Thirion's demons algorithm. In the first part of this paper, we show that Thirion's demons algorithm can be seen as an optimization procedure on the entire space of displacement fields. We provide strong theoretical roots to the different variants of Thirion's demons algorithm. This analysis predicts a theoretical advantage for the symmetric forces variant of the demons algorithm. We show on controlled experiments that this advantage is confirmed in practice and yields a faster convergence. In the second part of this paper, we adapt the optimization procedure underlying the demons algorithm to a space of diffeomorphic transformations. In contrast to many diffeomorphic registration algorithms, our solution is computationally efficient since in practice it only replaces an addition of displacement fields by a few compositions. Our experiments show that in addition to being diffeomorphic, our algorithm provides results that are similar to the ones from the demons algorithm but with transformations that are much smoother and closer to the gold standard, available in controlled experiments, in terms of Jacobians.

MARKOV: A methodology for the solution of infinite time horizon MARKOV decision processes

USGS Publications Warehouse

Williams, B.K.

1988-01-01

Algorithms are described for determining optimal policies for finite state, finite action, infinite discrete time horizon Markov decision processes. Both value-improvement and policy-improvement techniques are used in the algorithms. Computing procedures are also described. The algorithms are appropriate for processes that are either finite or infinite, deterministic or stochastic, discounted or undiscounted, in any meaningful combination of these features. Computing procedures are described in terms of initial data processing, bound improvements, process reduction, and testing and solution. Application of the methodology is illustrated with an example involving natural resource management. Management implications of certain hypothesized relationships between mallard survival and harvest rates are addressed by applying the optimality procedures to mallard population models.

The minimal residual QR-factorization algorithm for reliably solving subset regression problems

NASA Technical Reports Server (NTRS)

Verhaegen, M. H.

1987-01-01

A new algorithm to solve test subset regression problems is described, called the minimal residual QR factorization algorithm (MRQR). This scheme performs a QR factorization with a new column pivoting strategy. Basically, this strategy is based on the change in the residual of the least squares problem. Furthermore, it is demonstrated that this basic scheme might be extended in a numerically efficient way to combine the advantages of existing numerical procedures, such as the singular value decomposition, with those of more classical statistical procedures, such as stepwise regression. This extension is presented as an advisory expert system that guides the user in solving the subset regression problem. The advantages of the new procedure are highlighted by a numerical example.

Compiler Optimization Pass Visualization: The Procedural Abstraction Case

ERIC Educational Resources Information Center

Schaeckeler, Stefan; Shang, Weijia; Davis, Ruth

2009-01-01

There is an active research community concentrating on visualizations of algorithms taught in CS1 and CS2 courses. These visualizations can help students to create concrete visual images of the algorithms and their underlying concepts. Not only "fundamental algorithms" can be visualized, but also algorithms used in compilers. Visualizations that…

An interactive adaptive remeshing algorithm for the two-dimensional Euler equations

NASA Technical Reports Server (NTRS)

Slack, David C.; Walters, Robert W.; Lohner, R.

1990-01-01

An interactive adaptive remeshing algorithm utilizing a frontal grid generator and a variety of time integration schemes for the two-dimensional Euler equations on unstructured meshes is presented. Several device dependent interactive graphics interfaces have been developed along with a device independent DI-3000 interface which can be employed on any computer that has the supporting software including the Cray-2 supercomputers Voyager and Navier. The time integration methods available include: an explicit four stage Runge-Kutta and a fully implicit LU decomposition. A cell-centered finite volume upwind scheme utilizing Roe's approximate Riemann solver is developed. To obtain higher order accurate results a monotone linear reconstruction procedure proposed by Barth is utilized. Results for flow over a transonic circular arc and flow through a supersonic nozzle are examined.

On recursive least-squares filtering algorithms and implementations. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Hsieh, Shih-Fu

1990-01-01

In many real-time signal processing applications, fast and numerically stable algorithms for solving least-squares problems are necessary and important. In particular, under non-stationary conditions, these algorithms must be able to adapt themselves to reflect the changes in the system and take appropriate adjustments to achieve optimum performances. Among existing algorithms, the QR-decomposition (QRD)-based recursive least-squares (RLS) methods have been shown to be useful and effective for adaptive signal processing. In order to increase the speed of processing and achieve high throughput rate, many algorithms are being vectorized and/or pipelined to facilitate high degrees of parallelism. A time-recursive formulation of RLS filtering employing block QRD will be considered first. Several methods, including a new non-continuous windowing scheme based on selectively rejecting contaminated data, were investigated for adaptive processing. Based on systolic triarrays, many other forms of systolic arrays are shown to be capable of implementing different algorithms. Various updating and downdating systolic algorithms and architectures for RLS filtering are examined and compared in details, which include Householder reflector, Gram-Schmidt procedure, and Givens rotation. A unified approach encompassing existing square-root-free algorithms is also proposed. For the sinusoidal spectrum estimation problem, a judicious method of separating the noise from the signal is of great interest. Various truncated QR methods are proposed for this purpose and compared to the truncated SVD method. Computer simulations provided for detailed comparisons show the effectiveness of these methods. This thesis deals with fundamental issues of numerical stability, computational efficiency, adaptivity, and VLSI implementation for the RLS filtering problems. In all, various new and modified algorithms and architectures are proposed and analyzed; the significance of any of the new method depends crucially on specific application.

A fast optimization algorithm for multicriteria intensity modulated proton therapy planning.

PubMed

Chen, Wei; Craft, David; Madden, Thomas M; Zhang, Kewu; Kooy, Hanne M; Herman, Gabor T

2010-09-01

To describe a fast projection algorithm for optimizing intensity modulated proton therapy (IMPT) plans and to describe and demonstrate the use of this algorithm in multicriteria IMPT planning. The authors develop a projection-based solver for a class of convex optimization problems and apply it to IMPT treatment planning. The speed of the solver permits its use in multicriteria optimization, where several optimizations are performed which span the space of possible treatment plans. The authors describe a plan database generation procedure which is customized to the requirements of the solver. The optimality precision of the solver can be specified by the user. The authors apply the algorithm to three clinical cases: A pancreas case, an esophagus case, and a tumor along the rib cage case. Detailed analysis of the pancreas case shows that the algorithm is orders of magnitude faster than industry-standard general purpose algorithms (MOSEK'S interior point optimizer, primal simplex optimizer, and dual simplex optimizer). Additionally, the projection solver has almost no memory overhead. The speed and guaranteed accuracy of the algorithm make it suitable for use in multicriteria treatment planning, which requires the computation of several diverse treatment plans. Additionally, given the low memory overhead of the algorithm, the method can be extended to include multiple geometric instances and proton range possibilities, for robust optimization.

6.7 radio sky mapping from satellites at very low frequencies

NASA Technical Reports Server (NTRS)

Storey, L. R. O.

1991-01-01

Wave Distribution Function (WDF) analysis is a procedure for making sky maps of the sources of natural electromagnetic waves in space plasmas, given local measurements of some or all of the three magnetic and three electric field components. The work that still needs to be done on this subject includes solving basic methodological problems, translating the solution into efficient algorithms, and embodying the algorithms in computer software. One important scientific use of WDF analysis is to identify the mode of origin of plasmaspheric hiss. Some of the data from the Japanese satellite Akebono (EXOS D) are likely to be suitable for this purpose.

Radio sky mapping from satellites at very low frequencies

NASA Technical Reports Server (NTRS)

Storey, L. R. O.

1991-01-01

Wave Distribution Function (WDF) analysis is a procedure for making sky maps of the sources of natural electromagnetic waves in space plasmas, given local measurements of some or all of the three magnetic and three electric field components. The work that still needs to be done on this subject includes solving basic methodological problems, translating the solution into efficient algorithms, and embodying the algorithms in computer software. One important scientific use of WDF analysis is to identify the mode of origin of plasmaspheric hiss. Some of the data from the Japanese satellite Akebono (EXOS D) are likely to be suitable for this purpose.

High resolution astrophysical observations using speckle imaging

NASA Astrophysics Data System (ADS)

Noyes, R. W.; Nisenson, P.; Papaliolios, C.; Stachnik, R. V.

1986-04-01

This report describes progress under a contract to develop a complete astronomical speckle image reconstruction facility and to apply that facility to the solution of astronomical problems. During the course of the contract we have developed the procedures, algorithms, theory and hardware required to perform that function and have made and interpreted astronomical observations of substantial significance. A principal result of the program was development of a photon-counting camera of innovative design, the PAPA detector. Development of this device was, in our view, essential to making the speckle process into a useful astronomical tool, since the principal impediment to that circumstance in the past was the necessity for application of photon noise compensation procedures which were difficult if not impossible to calibrate. The photon camera made this procedure unnecessary and permitted precision image recovery. The result of this effort and the associated algorithm development was an active program of astronomical observation which included investigations into young stellar objects, supergiant structure and measurements of the helium abundance of the early universe. We have also continued research on recovery of high angular resolution images of the solar surface working with scientists at the Sacramento Peak Observatory in this area.

Fully-coupled analysis of jet mixing problems. Three-dimensional PNS model, SCIP3D

NASA Technical Reports Server (NTRS)

Wolf, D. E.; Sinha, N.; Dash, S. M.

1988-01-01

Numerical procedures formulated for the analysis of 3D jet mixing problems, as incorporated in the computer model, SCIP3D, are described. The overall methodology closely parallels that developed in the earlier 2D axisymmetric jet mixing model, SCIPVIS. SCIP3D integrates the 3D parabolized Navier-Stokes (PNS) jet mixing equations, cast in mapped cartesian or cylindrical coordinates, employing the explicit MacCormack Algorithm. A pressure split variant of this algorithm is employed in subsonic regions with a sublayer approximation utilized for treating the streamwise pressure component. SCIP3D contains both the ks and kW turbulence models, and employs a two component mixture approach to treat jet exhausts of arbitrary composition. Specialized grid procedures are used to adjust the grid growth in accordance with the growth of the jet, including a hybrid cartesian/cylindrical grid procedure for rectangular jets which moves the hybrid coordinate origin towards the flow origin as the jet transitions from a rectangular to circular shape. Numerous calculations are presented for rectangular mixing problems, as well as for a variety of basic unit problems exhibiting overall capabilities of SCIP3D.

An NCME Instructional Module on Estimating Item Response Theory Models Using Markov Chain Monte Carlo Methods

ERIC Educational Resources Information Center

Kim, Jee-Seon; Bolt, Daniel M.

2007-01-01

The purpose of this ITEMS module is to provide an introduction to Markov chain Monte Carlo (MCMC) estimation for item response models. A brief description of Bayesian inference is followed by an overview of the various facets of MCMC algorithms, including discussion of prior specification, sampling procedures, and methods for evaluating chain…

Precision instrument placement using a 4-DOF robot with integrated fiducials for minimally invasive interventions

NASA Astrophysics Data System (ADS)

Stenzel, Roland; Lin, Ralph; Cheng, Peng; Kronreif, Gernot; Kornfeld, Martin; Lindisch, David; Wood, Bradford J.; Viswanathan, Anand; Cleary, Kevin

2007-03-01

Minimally invasive procedures are increasingly attractive to patients and medical personnel because they can reduce operative trauma, recovery times, and overall costs. However, during these procedures, the physician has a very limited view of the interventional field and the exact position of surgical instruments. We present an image-guided platform for precision placement of surgical instruments based upon a small four degree-of-freedom robot (B-RobII; ARC Seibersdorf Research GmbH, Vienna, Austria). This platform includes a custom instrument guide with an integrated spiral fiducial pattern as the robot's end-effector, and it uses intra-operative computed tomography (CT) to register the robot to the patient directly before the intervention. The physician can then use a graphical user interface (GUI) to select a path for percutaneous access, and the robot will automatically align the instrument guide along this path. Potential anatomical targets include the liver, kidney, prostate, and spine. This paper describes the robotic platform, workflow, software, and algorithms used by the system. To demonstrate the algorithmic accuracy and suitability of the custom instrument guide, we also present results from experiments as well as estimates of the maximum error between target and instrument tip.

Quality assessment of two- and three-dimensional unstructured meshes and validation of an upwind Euler flow solver

NASA Technical Reports Server (NTRS)

Woodard, Paul R.; Yang, Henry T. Y.; Batina, John T.

1992-01-01

Quality assessment procedures are described for two-dimensional and three-dimensional unstructured meshes. The procedures include measurement of minimum angles, element aspect ratios, stretching, and element skewness. Meshes about the ONERA M6 wing and the Boeing 747 transport configuration are generated using an advancing front method grid generation package of programs. Solutions of Euler's equations for these meshes are obtained at low angle-of-attack, transonic conditions. Results for these cases, obtained as part of a validation study demonstrate the accuracy of an implicit upwind Euler solution algorithm.

Algorithm design, user interface, and optimization procedure for a fuzzy logic ramp metering algorithm : a training manual for freeway operations engineers

DOT National Transportation Integrated Search

2000-02-01

This training manual describes the fuzzy logic ramp metering algorithm in detail, as implemented system-wide in the greater Seattle area. The method of defining the inputs to the controller and optimizing the performance of the algorithm is explained...

[Algorithms for the identification of hospital stays due to osteoporotic femoral neck fractures in European medical administrative databases using ICD-10 codes: A non-systematic review of the literature].

PubMed

Caillet, P; Oberlin, P; Monnet, E; Guillon-Grammatico, L; Métral, P; Belhassen, M; Denier, P; Banaei-Bouchareb, L; Viprey, M; Biau, D; Schott, A-M

2017-10-01

Osteoporotic hip fractures (OHF) are associated with significant morbidity and mortality. The French medico-administrative database (SNIIRAM) offers an interesting opportunity to improve the management of OHF. However, the validity of studies conducted with this database relies heavily on the quality of the algorithm used to detect OHF. The aim of the REDSIAM network is to facilitate the use of the SNIIRAM database. The main objective of this study was to present and discuss several OHF-detection algorithms that could be used with this database. A non-systematic literature search was performed. The Medline database was explored during the period January 2005-August 2016. Furthermore, a snowball search was then carried out from the articles included and field experts were contacted. The extraction was conducted using the chart developed by the REDSIAM network's "Methodology" task force. The ICD-10 codes used to detect OHF are mainly S72.0, S72.1, and S72.2. The performance of these algorithms is at best partially validated. Complementary use of medical and surgical procedure codes would affect their performance. Finally, few studies described how they dealt with fractures of non-osteoporotic origin, re-hospitalization, and potential contralateral fracture cases. Authors in the literature encourage the use of ICD-10 codes S72.0 to S72.2 to develop algorithms for OHF detection. These are the codes most frequently used for OHF in France. Depending on the study objectives, other ICD10 codes and medical and surgical procedures could be usefully discussed for inclusion in the algorithm. Detection and management of duplicates and non-osteoporotic fractures should be considered in the process. Finally, when a study is based on such an algorithm, all these points should be precisely described in the publication. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Step wise, multiple objective calibration of a hydrologic model for a snowmelt dominated basin

USGS Publications Warehouse

Hay, L.E.; Leavesley, G.H.; Clark, M.P.; Markstrom, S.L.; Viger, R.J.; Umemoto, M.

2006-01-01

The ability to apply a hydrologic model to large numbers of basins for forecasting purposes requires a quick and effective calibration strategy. This paper presents a step wise, multiple objective, automated procedure for hydrologic model calibration. This procedure includes the sequential calibration of a model's simulation of solar radiation (SR), potential evapotranspiration (PET), water balance, and daily runoff. The procedure uses the Shuffled Complex Evolution global search algorithm to calibrate the U.S. Geological Survey's Precipitation Runoff Modeling System in the Yampa River basin of Colorado. This process assures that intermediate states of the model (SR and PET on a monthly mean basis), as well as the water balance and components of the daily hydrograph are simulated, consistently with measured values.

A simplified procedure for correcting both errors and erasures of a Reed-Solomon code using the Euclidean algorithm

NASA Technical Reports Server (NTRS)

Truong, T. K.; Hsu, I. S.; Eastman, W. L.; Reed, I. S.

1987-01-01

It is well known that the Euclidean algorithm or its equivalent, continued fractions, can be used to find the error locator polynomial and the error evaluator polynomial in Berlekamp's key equation needed to decode a Reed-Solomon (RS) code. A simplified procedure is developed and proved to correct erasures as well as errors by replacing the initial condition of the Euclidean algorithm by the erasure locator polynomial and the Forney syndrome polynomial. By this means, the errata locator polynomial and the errata evaluator polynomial can be obtained, simultaneously and simply, by the Euclidean algorithm only. With this improved technique the complexity of time domain RS decoders for correcting both errors and erasures is reduced substantially from previous approaches. As a consequence, decoders for correcting both errors and erasures of RS codes can be made more modular, regular, simple, and naturally suitable for both VLSI and software implementation. An example illustrating this modified decoding procedure is given for a (15, 9) RS code.

Robust automatic line scratch detection in films.

PubMed

Newson, Alasdair; Almansa, Andrés; Gousseau, Yann; Pérez, Patrick

2014-03-01

Line scratch detection in old films is a particularly challenging problem due to the variable spatiotemporal characteristics of this defect. Some of the main problems include sensitivity to noise and texture, and false detections due to thin vertical structures belonging to the scene. We propose a robust and automatic algorithm for frame-by-frame line scratch detection in old films, as well as a temporal algorithm for the filtering of false detections. In the frame-by-frame algorithm, we relax some of the hypotheses used in previous algorithms in order to detect a wider variety of scratches. This step's robustness and lack of external parameters is ensured by the combined use of an a contrario methodology and local statistical estimation. In this manner, over-detection in textured or cluttered areas is greatly reduced. The temporal filtering algorithm eliminates false detections due to thin vertical structures by exploiting the coherence of their motion with that of the underlying scene. Experiments demonstrate the ability of the resulting detection procedure to deal with difficult situations, in particular in the presence of noise, texture, and slanted or partial scratches. Comparisons show significant advantages over previous work.

Automatic Texture Mapping of Architectural and Archaeological 3d Models

NASA Astrophysics Data System (ADS)

Kersten, T. P.; Stallmann, D.

2012-07-01

Today, detailed, complete and exact 3D models with photo-realistic textures are increasingly demanded for numerous applications in architecture and archaeology. Manual texture mapping of 3D models by digital photographs with software packages, such as Maxon Cinema 4D, Autodesk 3Ds Max or Maya, still requires a complex and time-consuming workflow. So, procedures for automatic texture mapping of 3D models are in demand. In this paper two automatic procedures are presented. The first procedure generates 3D surface models with textures by web services, while the second procedure textures already existing 3D models with the software tmapper. The program tmapper is based on the Multi Layer 3D image (ML3DImage) algorithm and developed in the programming language C++. The studies showing that the visibility analysis using the ML3DImage algorithm is not sufficient to obtain acceptable results of automatic texture mapping. To overcome the visibility problem the Point Cloud Painter algorithm in combination with the Z-buffer-procedure will be applied in the future.

Adaptive striping watershed segmentation method for processing microscopic images of overlapping irregular-shaped and multicentre particles.

PubMed

Xiao, X; Bai, B; Xu, N; Wu, K

2015-04-01

Oversegmentation is a major drawback of the morphological watershed algorithm. Here, we study and reveal that the oversegmentation is not only because of the irregular shapes of the particle images, which people are familiar with, but also because of some particles, such as ellipses, with more than one centre. A new parameter, the striping level, is introduced and the criterion for striping parameter is built to help find the right markers prior to segmentation. An adaptive striping watershed algorithm is established by applying a procedure, called the marker searching algorithm, to find the markers, which can effectively suppress the oversegmentation. The effectiveness of the proposed method is validated by analysing some typical particle images including the images of gold nanorod ensembles. © 2014 The Authors Journal of Microscopy © 2014 Royal Microscopical Society.

Quantum red-green-blue image steganography

NASA Astrophysics Data System (ADS)

Heidari, Shahrokh; Pourarian, Mohammad Rasoul; Gheibi, Reza; Naseri, Mosayeb; Houshmand, Monireh

One of the most considering matters in the field of quantum information processing is quantum data hiding including quantum steganography and quantum watermarking. This field is an efficient tool for protecting any kind of digital data. In this paper, three quantum color images steganography algorithms are investigated based on Least Significant Bit (LSB). The first algorithm employs only one of the image’s channels to cover secret data. The second procedure is based on LSB XORing technique, and the last algorithm utilizes two channels to cover the color image for hiding secret quantum data. The performances of the proposed schemes are analyzed by using software simulations in MATLAB environment. The analysis of PSNR, BER and Histogram graphs indicate that the presented schemes exhibit acceptable performances and also theoretical analysis demonstrates that the networks complexity of the approaches scales squarely.

A Bayesian Approach for Sensor Optimisation in Impact Identification

PubMed Central

Mallardo, Vincenzo; Sharif Khodaei, Zahra; Aliabadi, Ferri M. H.

2016-01-01

This paper presents a Bayesian approach for optimizing the position of sensors aimed at impact identification in composite structures under operational conditions. The uncertainty in the sensor data has been represented by statistical distributions of the recorded signals. An optimisation strategy based on the genetic algorithm is proposed to find the best sensor combination aimed at locating impacts on composite structures. A Bayesian-based objective function is adopted in the optimisation procedure as an indicator of the performance of meta-models developed for different sensor combinations to locate various impact events. To represent a real structure under operational load and to increase the reliability of the Structural Health Monitoring (SHM) system, the probability of malfunctioning sensors is included in the optimisation. The reliability and the robustness of the procedure is tested with experimental and numerical examples. Finally, the proposed optimisation algorithm is applied to a composite stiffened panel for both the uniform and non-uniform probability of impact occurrence. PMID:28774064

User's manual for a TEACH computer program for the analysis of turbulent, swirling reacting flow in a research combustor

NASA Technical Reports Server (NTRS)

Chiappetta, L. M.

1983-01-01

Described is a computer program for the analysis of the subsonic, swirling, reacting turbulent flow in an axisymmetric, bluff-body research combustor. The program features an improved finite-difference procedure designed to reduce the effects of numerical diffusion and a new algorithm for predicting the pressure distribution within the combustor. A research version of the computer program described in the report was supplied to United Technologies Research Center by Professor A. D. Gosman and his students, R. Benodeker and R. I. Issa, of Imperial College, London. The Imperial College staff also supplied much of the program documentation. Presented are a description of the mathematical model for flow within an axisymmetric bluff-body combustor, the development of the finite-difference procedure used to represent the system of equations, an outline of the algorithm for determining the static pressure distribution within the combustor, a description of the computer program including its input format, and the results for representative test cases.

Optimization of the double dosimetry algorithm for interventional cardiologists

NASA Astrophysics Data System (ADS)

Chumak, Vadim; Morgun, Artem; Bakhanova, Elena; Voloskiy, Vitalii; Borodynchik, Elena

2014-11-01

A double dosimetry method is recommended in interventional cardiology (IC) to assess occupational exposure; yet currently there is no common and universal algorithm for effective dose estimation. In this work, flexible and adaptive algorithm building methodology was developed and some specific algorithm applicable for typical irradiation conditions of IC procedures was obtained. It was shown that the obtained algorithm agrees well with experimental measurements and is less conservative compared to other known algorithms.

Algorithms in Learning, Teaching, and Instructional Design. Studies in Systematic Instruction and Training Technical Report 51201.

ERIC Educational Resources Information Center

Gerlach, Vernon S.; And Others

An algorithm is defined here as an unambiguous procedure which will always produce the correct result when applied to any problem of a given class of problems. This paper gives an extended discussion of the definition of an algorithm. It also explores in detail the elements of an algorithm, the representation of algorithms in standard prose, flow…

Bayesian Analysis for Exponential Random Graph Models Using the Adaptive Exchange Sampler.

PubMed

Jin, Ick Hoon; Yuan, Ying; Liang, Faming

2013-10-01

Exponential random graph models have been widely used in social network analysis. However, these models are extremely difficult to handle from a statistical viewpoint, because of the intractable normalizing constant and model degeneracy. In this paper, we consider a fully Bayesian analysis for exponential random graph models using the adaptive exchange sampler, which solves the intractable normalizing constant and model degeneracy issues encountered in Markov chain Monte Carlo (MCMC) simulations. The adaptive exchange sampler can be viewed as a MCMC extension of the exchange algorithm, and it generates auxiliary networks via an importance sampling procedure from an auxiliary Markov chain running in parallel. The convergence of this algorithm is established under mild conditions. The adaptive exchange sampler is illustrated using a few social networks, including the Florentine business network, molecule synthetic network, and dolphins network. The results indicate that the adaptive exchange algorithm can produce more accurate estimates than approximate exchange algorithms, while maintaining the same computational efficiency.

Experimental validation of clock synchronization algorithms

NASA Technical Reports Server (NTRS)

Palumbo, Daniel L.; Graham, R. Lynn

1992-01-01

The objective of this work is to validate mathematically derived clock synchronization theories and their associated algorithms through experiment. Two theories are considered, the Interactive Convergence Clock Synchronization Algorithm and the Midpoint Algorithm. Special clock circuitry was designed and built so that several operating conditions and failure modes (including malicious failures) could be tested. Both theories are shown to predict conservative upper bounds (i.e., measured values of clock skew were always less than the theory prediction). Insight gained during experimentation led to alternative derivations of the theories. These new theories accurately predict the behavior of the clock system. It is found that a 100 percent penalty is paid to tolerate worst-case failures. It is also shown that under optimal conditions (with minimum error and no failures) the clock skew can be as much as three clock ticks. Clock skew grows to six clock ticks when failures are present. Finally, it is concluded that one cannot rely solely on test procedures or theoretical analysis to predict worst-case conditions.

An Approach to a Comprehensive Test Framework for Analysis and Evaluation of Text Line Segmentation Algorithms

PubMed Central

Brodic, Darko; Milivojevic, Dragan R.; Milivojevic, Zoran N.

2011-01-01

The paper introduces a testing framework for the evaluation and validation of text line segmentation algorithms. Text line segmentation represents the key action for correct optical character recognition. Many of the tests for the evaluation of text line segmentation algorithms deal with text databases as reference templates. Because of the mismatch, the reliable testing framework is required. Hence, a new approach to a comprehensive experimental framework for the evaluation of text line segmentation algorithms is proposed. It consists of synthetic multi-like text samples and real handwritten text as well. Although the tests are mutually independent, the results are cross-linked. The proposed method can be used for different types of scripts and languages. Furthermore, two different procedures for the evaluation of algorithm efficiency based on the obtained error type classification are proposed. The first is based on the segmentation line error description, while the second one incorporates well-known signal detection theory. Each of them has different capabilities and convenience, but they can be used as supplements to make the evaluation process efficient. Overall the proposed procedure based on the segmentation line error description has some advantages, characterized by five measures that describe measurement procedures. PMID:22164106

New approaches for measuring changes in the cortical surface using an automatic reconstruction algorithm

NASA Astrophysics Data System (ADS)

Pham, Dzung L.; Han, Xiao; Rettmann, Maryam E.; Xu, Chenyang; Tosun, Duygu; Resnick, Susan; Prince, Jerry L.

2002-05-01

In previous work, the authors presented a multi-stage procedure for the semi-automatic reconstruction of the cerebral cortex from magnetic resonance images. This method suffered from several disadvantages. First, the tissue classification algorithm used can be sensitive to noise within the image. Second, manual interaction was required for masking out undesired regions of the brain image, such as the ventricles and putamen. Third, iterated median filters were used to perform a topology correction on the initial cortical surface, resulting in an overly smoothed initial surface. Finally, the deformable surface used to converge to the cortex had difficulty capturing narrow gyri. In this work, all four disadvantages of the procedure have been addressed. A more robust tissue classification algorithm is employed and the manual masking step is replaced by an automatic method involving level set deformable models. Instead of iterated median filters, an algorithm developed specifically for topology correction is used. The last disadvantage is addressed using an algorithm that artificially separates adjacent sulcal banks. The new procedure is more automated but also more accurate than the previous one. Its utility is demonstrated by performing a preliminary study on data from the Baltimore Longitudinal Study of Aging.

An approach to a comprehensive test framework for analysis and evaluation of text line segmentation algorithms.

PubMed

Brodic, Darko; Milivojevic, Dragan R; Milivojevic, Zoran N

2011-01-01

The paper introduces a testing framework for the evaluation and validation of text line segmentation algorithms. Text line segmentation represents the key action for correct optical character recognition. Many of the tests for the evaluation of text line segmentation algorithms deal with text databases as reference templates. Because of the mismatch, the reliable testing framework is required. Hence, a new approach to a comprehensive experimental framework for the evaluation of text line segmentation algorithms is proposed. It consists of synthetic multi-like text samples and real handwritten text as well. Although the tests are mutually independent, the results are cross-linked. The proposed method can be used for different types of scripts and languages. Furthermore, two different procedures for the evaluation of algorithm efficiency based on the obtained error type classification are proposed. The first is based on the segmentation line error description, while the second one incorporates well-known signal detection theory. Each of them has different capabilities and convenience, but they can be used as supplements to make the evaluation process efficient. Overall the proposed procedure based on the segmentation line error description has some advantages, characterized by five measures that describe measurement procedures.

Direct evaluation of fault trees using object-oriented programming techniques

NASA Technical Reports Server (NTRS)

Patterson-Hine, F. A.; Koen, B. V.

1989-01-01

Object-oriented programming techniques are used in an algorithm for the direct evaluation of fault trees. The algorithm combines a simple bottom-up procedure for trees without repeated events with a top-down recursive procedure for trees with repeated events. The object-oriented approach results in a dynamic modularization of the tree at each step in the reduction process. The algorithm reduces the number of recursive calls required to solve trees with repeated events and calculates intermediate results as well as the solution of the top event. The intermediate results can be reused if part of the tree is modified. An example is presented in which the results of the algorithm implemented with conventional techniques are compared to those of the object-oriented approach.

A critical analysis of the surgical outcomes for the treatment of Peyronie’s disease

PubMed Central

Mandava, Sree H.; Trost, Landon W.; Hellstrom, Wayne J.G.

2013-01-01

Peyronie’s disease (PD) is a relatively common condition, which can impair sexual function and result in emotional and psychological distress. Despite an abundance of minimally invasive treatments, few have confirmed efficacy for improving penile curvature and function. Surgical therapies include many different techniques and are reserved for patients with stable disease of ⩾12 months’ duration. We searched PubMed for all articles from 1990 to the present relating to the surgical management of PD. Preference was given to recent articles, larger series, and those comparing various techniques and/or materials. Outcomes were subsequently analysed and organised by surgical technique and the graft material used. Available surgical techniques include plication/corporoplasty procedures, incision and grafting (I&G), and placing a penile prosthesis with or without adjunctive procedures. Although several surgical algorithms have been reported, in general, plication/corporoplasty procedures are reserved for patients with adequate erectile function, simple curvatures of <60°, and with no deformities (hour-glass, hinge). I&G are reserved for complex curvatures of >60° and those with deformities. Penile prostheses are indicated for combined erectile dysfunction and PD. Overall outcomes show high rates of improved curvature and patient satisfaction, with mildly decreased erectile function with both plication and the I&G procedure (I&G >plication) and decreases in penile length (plication >I&G). Surgical management of PD remains an excellent treatment option for patients with penile curvature precluding or impairing sexual activity. Surgical algorithms are available to assist treating clinicians in appropriately stratifying surgical candidates. Additional research is needed to identify optimal surgical techniques and materials based on patient and disease characteristics. PMID:26558094

New Results in Astrodynamics Using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Coverstone-Carroll, V.; Hartmann, J. W.; Williams, S. N.; Mason, W. J.

1998-01-01

Generic algorithms have gained popularity as an effective procedure for obtaining solutions to traditionally difficult space mission optimization problems. In this paper, a brief survey of the use of genetic algorithms to solve astrodynamics problems is presented and is followed by new results obtained from applying a Pareto genetic algorithm to the optimization of low-thrust interplanetary spacecraft missions.

Golay Complementary Waveforms in Reed–Müller Sequences for Radar Detection of Nonzero Doppler Targets

PubMed Central

Wang, Xuezhi; Huang, Xiaotao; Suvorova, Sofia; Moran, Bill

2018-01-01

Golay complementary waveforms can, in theory, yield radar returns of high range resolution with essentially zero sidelobes. In practice, when deployed conventionally, while high signal-to-noise ratios can be achieved for static target detection, significant range sidelobes are generated by target returns of nonzero Doppler causing unreliable detection. We consider signal processing techniques using Golay complementary waveforms to improve radar detection performance in scenarios involving multiple nonzero Doppler targets. A signal processing procedure based on an existing, so called, Binomial Design algorithm that alters the transmission order of Golay complementary waveforms and weights the returns is proposed in an attempt to achieve an enhanced illumination performance. The procedure applies one of three proposed waveform transmission ordering algorithms, followed by a pointwise nonlinear processor combining the outputs of the Binomial Design algorithm and one of the ordering algorithms. The computational complexity of the Binomial Design algorithm and the three ordering algorithms are compared, and a statistical analysis of the performance of the pointwise nonlinear processing is given. Estimation of the areas in the Delay–Doppler map occupied by significant range sidelobes for given targets are also discussed. Numerical simulations for the comparison of the performances of the Binomial Design algorithm and the three ordering algorithms are presented for both fixed and randomized target locations. The simulation results demonstrate that the proposed signal processing procedure has a better detection performance in terms of lower sidelobes and higher Doppler resolution in the presence of multiple nonzero Doppler targets compared to existing methods. PMID:29324708

Image processing of underwater multispectral imagery

USGS Publications Warehouse

Zawada, D. G.

2003-01-01

Capturing in situ fluorescence images of marine organisms presents many technical challenges. The effects of the medium, as well as the particles and organisms within it, are intermixed with the desired signal. Methods for extracting and preparing the imagery for analysis are discussed in reference to a novel underwater imaging system called the low-light-level underwater multispectral imaging system (LUMIS). The instrument supports both uni- and multispectral collections, each of which is discussed in the context of an experimental application. In unispectral mode, LUMIS was used to investigate the spatial distribution of phytoplankton. A thin sheet of laser light (532 nm) induced chlorophyll fluorescence in the phytoplankton, which was recorded by LUMIS. Inhomogeneities in the light sheet led to the development of a beam-pattern-correction algorithm. Separating individual phytoplankton cells from a weak background fluorescence field required a two-step procedure consisting of edge detection followed by a series of binary morphological operations. In multispectral mode, LUMIS was used to investigate the bio-assay potential of fluorescent pigments in corals. Problems with the commercial optical-splitting device produced nonlinear distortions in the imagery. A tessellation algorithm, including an automated tie-point-selection procedure, was developed to correct the distortions. Only pixels corresponding to coral polyps were of interest for further analysis. Extraction of these pixels was performed by a dynamic global-thresholding algorithm.

Flight Crew Survey Responses from the Interval Management (IM) Avionics Phase 2 Flight Test

NASA Technical Reports Server (NTRS)

Baxley, Brian T.; Swieringa, Kurt A.; Wilson, Sara R.; Roper, Roy D.; Hubbs, Clay E.; Goess, Paul A.; Shay, Richard F.

2017-01-01

The Interval Management (IM) Avionics Phase 2 flight test used three aircraft over a nineteen day period to operationally evaluate a prototype IM avionics. Quantitative data were collected on aircraft state data and IM spacing algorithm performance, and qualitative data were collected through end-of-scenario and end-of-day flight crew surveys. The majority of the IM operations met the performance goals established for spacing accuracy at the Achieve-by Point and the Planned Termination Point, however there were operations that did not meet goals for a variety of reasons. While the positive spacing accuracy results demonstrate the prototype IM avionics can contribute to the overall air traffic goal, critical issues were also identified that need to be addressed to enhance IM performance. The first category was those issues that impacted the conduct and results of the flight test, but are not part of the IM concept or procedures. These included the design of arrival and approach procedures was not ideal to support speed as the primary control mechanism, the ground-side of the Air Traffic Management Technology Demonstration (ATD-1) integrated concept of operations was not part of the flight test, and the high workload to manually enter the information required to conduct an IM operation. The second category was issues associated with the IM spacing algorithm or flight crew procedures. These issues include the high frequency of IM speed changes and reversals (accelerations), a mismatch between the deceleration rate used by the spacing algorithm and the actual aircraft performance, and some spacing error calculations were sensitive to normal operational variations in aircraft airspeed or altitude which triggered additional IM speed changes. Once the issues in these two categories are addressed, the future IM avionics should have considerable promise supporting the goals of improving system throughput and aircraft efficiency.

Design considerations for remotely piloted, high-altitude airplanes powered by microwave energy

NASA Technical Reports Server (NTRS)

Morris, C. E. K., Jr.

1984-01-01

Several types of systems have been considered in a design study of unmanned, microwave-powered, long-endurance, high-altitude airplanes. The study includes vehicles that use power from a continuously transmitted beam and other aircraft that receive intermittent power during cycles of boost-glide flight. Simple design algorithms are presented. Examples of sizing and performance analyses are used to suggest design-procedure guidelines.

THRESHOLD LOGIC.

DTIC Science & Technology

synthesis procedures; a ’best’ method is definitely established. (2) ’Symmetry Types for Threshold Logic’ is a tutorial expositon including a careful...development of the Goto-Takahasi self-dual type ideas. (3) ’Best Threshold Gate Decisions’ reports a comparison, on the 2470 7-argument threshold ...interpretation is shown best. (4) ’ Threshold Gate Networks’ reviews the previously discussed 2-algorithm in geometric terms, describes our FORTRAN

Modal characterization of the ASCIE segmented optics testbed: New algorithms and experimental results

NASA Technical Reports Server (NTRS)

Carrier, Alain C.; Aubrun, Jean-Noel

1993-01-01

New frequency response measurement procedures, on-line modal tuning techniques, and off-line modal identification algorithms are developed and applied to the modal identification of the Advanced Structures/Controls Integrated Experiment (ASCIE), a generic segmented optics telescope test-bed representative of future complex space structures. The frequency response measurement procedure uses all the actuators simultaneously to excite the structure and all the sensors to measure the structural response so that all the transfer functions are measured simultaneously. Structural responses to sinusoidal excitations are measured and analyzed to calculate spectral responses. The spectral responses in turn are analyzed as the spectral data become available and, which is new, the results are used to maintain high quality measurements. Data acquisition, processing, and checking procedures are fully automated. As the acquisition of the frequency response progresses, an on-line algorithm keeps track of the actuator force distribution that maximizes the structural response to automatically tune to a structural mode when approaching a resonant frequency. This tuning is insensitive to delays, ill-conditioning, and nonproportional damping. Experimental results show that is useful for modal surveys even in high modal density regions. For thorough modeling, a constructive procedure is proposed to identify the dynamics of a complex system from its frequency response with the minimization of a least-squares cost function as a desirable objective. This procedure relies on off-line modal separation algorithms to extract modal information and on least-squares parameter subset optimization to combine the modal results and globally fit the modal parameters to the measured data. The modal separation algorithms resolved modal density of 5 modes/Hz in the ASCIE experiment. They promise to be useful in many challenging applications.

A Novel Artificial Bee Colony Based Clustering Algorithm for Categorical Data

PubMed Central

2015-01-01

Data with categorical attributes are ubiquitous in the real world. However, existing partitional clustering algorithms for categorical data are prone to fall into local optima. To address this issue, in this paper we propose a novel clustering algorithm, ABC-K-Modes (Artificial Bee Colony clustering based on K-Modes), based on the traditional k-modes clustering algorithm and the artificial bee colony approach. In our approach, we first introduce a one-step k-modes procedure, and then integrate this procedure with the artificial bee colony approach to deal with categorical data. In the search process performed by scout bees, we adopt the multi-source search inspired by the idea of batch processing to accelerate the convergence of ABC-K-Modes. The performance of ABC-K-Modes is evaluated by a series of experiments in comparison with that of the other popular algorithms for categorical data. PMID:25993469

An Integrated Method Based on PSO and EDA for the Max-Cut Problem.

PubMed

Lin, Geng; Guan, Jian

2016-01-01

The max-cut problem is NP-hard combinatorial optimization problem with many real world applications. In this paper, we propose an integrated method based on particle swarm optimization and estimation of distribution algorithm (PSO-EDA) for solving the max-cut problem. The integrated algorithm overcomes the shortcomings of particle swarm optimization and estimation of distribution algorithm. To enhance the performance of the PSO-EDA, a fast local search procedure is applied. In addition, a path relinking procedure is developed to intensify the search. To evaluate the performance of PSO-EDA, extensive experiments were carried out on two sets of benchmark instances with 800 to 20,000 vertices from the literature. Computational results and comparisons show that PSO-EDA significantly outperforms the existing PSO-based and EDA-based algorithms for the max-cut problem. Compared with other best performing algorithms, PSO-EDA is able to find very competitive results in terms of solution quality.

Scalable software-defined optical networking with high-performance routing and wavelength assignment algorithms.

PubMed

Lee, Chankyun; Cao, Xiaoyuan; Yoshikane, Noboru; Tsuritani, Takehiro; Rhee, June-Koo Kevin

2015-10-19

The feasibility of software-defined optical networking (SDON) for a practical application critically depends on scalability of centralized control performance. The paper, highly scalable routing and wavelength assignment (RWA) algorithms are investigated on an OpenFlow-based SDON testbed for proof-of-concept demonstration. Efficient RWA algorithms are proposed to achieve high performance in achieving network capacity with reduced computation cost, which is a significant attribute in a scalable centralized-control SDON. The proposed heuristic RWA algorithms differ in the orders of request processes and in the procedures of routing table updates. Combined in a shortest-path-based routing algorithm, a hottest-request-first processing policy that considers demand intensity and end-to-end distance information offers both the highest throughput of networks and acceptable computation scalability. We further investigate trade-off relationship between network throughput and computation complexity in routing table update procedure by a simulation study.

A novel artificial bee colony based clustering algorithm for categorical data.

PubMed

Ji, Jinchao; Pang, Wei; Zheng, Yanlin; Wang, Zhe; Ma, Zhiqiang

2015-01-01

Data with categorical attributes are ubiquitous in the real world. However, existing partitional clustering algorithms for categorical data are prone to fall into local optima. To address this issue, in this paper we propose a novel clustering algorithm, ABC-K-Modes (Artificial Bee Colony clustering based on K-Modes), based on the traditional k-modes clustering algorithm and the artificial bee colony approach. In our approach, we first introduce a one-step k-modes procedure, and then integrate this procedure with the artificial bee colony approach to deal with categorical data. In the search process performed by scout bees, we adopt the multi-source search inspired by the idea of batch processing to accelerate the convergence of ABC-K-Modes. The performance of ABC-K-Modes is evaluated by a series of experiments in comparison with that of the other popular algorithms for categorical data.

Vectorized Rebinning Algorithm for Fast Data Down-Sampling

NASA Technical Reports Server (NTRS)

Dean, Bruce; Aronstein, David; Smith, Jeffrey

2013-01-01

A vectorized rebinning (down-sampling) algorithm, applicable to N-dimensional data sets, has been developed that offers a significant reduction in computer run time when compared to conventional rebinning algorithms. For clarity, a two-dimensional version of the algorithm is discussed to illustrate some specific details of the algorithm content, and using the language of image processing, 2D data will be referred to as "images," and each value in an image as a "pixel." The new approach is fully vectorized, i.e., the down-sampling procedure is done as a single step over all image rows, and then as a single step over all image columns. Data rebinning (or down-sampling) is a procedure that uses a discretely sampled N-dimensional data set to create a representation of the same data, but with fewer discrete samples. Such data down-sampling is fundamental to digital signal processing, e.g., for data compression applications.

Improving the Spatial Prediction of Soil Organic Carbon Stocks in a Complex Tropical Mountain Landscape by Methodological Specifications in Machine Learning Approaches.

PubMed

Ließ, Mareike; Schmidt, Johannes; Glaser, Bruno

2016-01-01

Tropical forests are significant carbon sinks and their soils' carbon storage potential is immense. However, little is known about the soil organic carbon (SOC) stocks of tropical mountain areas whose complex soil-landscape and difficult accessibility pose a challenge to spatial analysis. The choice of methodology for spatial prediction is of high importance to improve the expected poor model results in case of low predictor-response correlations. Four aspects were considered to improve model performance in predicting SOC stocks of the organic layer of a tropical mountain forest landscape: Different spatial predictor settings, predictor selection strategies, various machine learning algorithms and model tuning. Five machine learning algorithms: random forests, artificial neural networks, multivariate adaptive regression splines, boosted regression trees and support vector machines were trained and tuned to predict SOC stocks from predictors derived from a digital elevation model and satellite image. Topographical predictors were calculated with a GIS search radius of 45 to 615 m. Finally, three predictor selection strategies were applied to the total set of 236 predictors. All machine learning algorithms-including the model tuning and predictor selection-were compared via five repetitions of a tenfold cross-validation. The boosted regression tree algorithm resulted in the overall best model. SOC stocks ranged between 0.2 to 17.7 kg m-2, displaying a huge variability with diffuse insolation and curvatures of different scale guiding the spatial pattern. Predictor selection and model tuning improved the models' predictive performance in all five machine learning algorithms. The rather low number of selected predictors favours forward compared to backward selection procedures. Choosing predictors due to their indiviual performance was vanquished by the two procedures which accounted for predictor interaction.

Training radial basis function networks for wind speed prediction using PSO enhanced differential search optimizer

PubMed Central

2018-01-01

This paper presents an integrated hybrid optimization algorithm for training the radial basis function neural network (RBF NN). Training of neural networks is still a challenging exercise in machine learning domain. Traditional training algorithms in general suffer and trap in local optima and lead to premature convergence, which makes them ineffective when applied for datasets with diverse features. Training algorithms based on evolutionary computations are becoming popular due to their robust nature in overcoming the drawbacks of the traditional algorithms. Accordingly, this paper proposes a hybrid training procedure with differential search (DS) algorithm functionally integrated with the particle swarm optimization (PSO). To surmount the local trapping of the search procedure, a new population initialization scheme is proposed using Logistic chaotic sequence, which enhances the population diversity and aid the search capability. To demonstrate the effectiveness of the proposed RBF hybrid training algorithm, experimental analysis on publicly available 7 benchmark datasets are performed. Subsequently, experiments were conducted on a practical application case for wind speed prediction to expound the superiority of the proposed RBF training algorithm in terms of prediction accuracy. PMID:29768463

Training radial basis function networks for wind speed prediction using PSO enhanced differential search optimizer.

PubMed

Rani R, Hannah Jessie; Victoire T, Aruldoss Albert

2018-01-01

This paper presents an integrated hybrid optimization algorithm for training the radial basis function neural network (RBF NN). Training of neural networks is still a challenging exercise in machine learning domain. Traditional training algorithms in general suffer and trap in local optima and lead to premature convergence, which makes them ineffective when applied for datasets with diverse features. Training algorithms based on evolutionary computations are becoming popular due to their robust nature in overcoming the drawbacks of the traditional algorithms. Accordingly, this paper proposes a hybrid training procedure with differential search (DS) algorithm functionally integrated with the particle swarm optimization (PSO). To surmount the local trapping of the search procedure, a new population initialization scheme is proposed using Logistic chaotic sequence, which enhances the population diversity and aid the search capability. To demonstrate the effectiveness of the proposed RBF hybrid training algorithm, experimental analysis on publicly available 7 benchmark datasets are performed. Subsequently, experiments were conducted on a practical application case for wind speed prediction to expound the superiority of the proposed RBF training algorithm in terms of prediction accuracy.

Method for hyperspectral imagery exploitation and pixel spectral unmixing

NASA Technical Reports Server (NTRS)

Lin, Ching-Fang (Inventor)

2003-01-01

An efficiently hybrid approach to exploit hyperspectral imagery and unmix spectral pixels. This hybrid approach uses a genetic algorithm to solve the abundance vector for the first pixel of a hyperspectral image cube. This abundance vector is used as initial state in a robust filter to derive the abundance estimate for the next pixel. By using Kalman filter, the abundance estimate for a pixel can be obtained in one iteration procedure which is much fast than genetic algorithm. The output of the robust filter is fed to genetic algorithm again to derive accurate abundance estimate for the current pixel. The using of robust filter solution as starting point of the genetic algorithm speeds up the evolution of the genetic algorithm. After obtaining the accurate abundance estimate, the procedure goes to next pixel, and uses the output of genetic algorithm as the previous state estimate to derive abundance estimate for this pixel using robust filter. And again use the genetic algorithm to derive accurate abundance estimate efficiently based on the robust filter solution. This iteration continues until pixels in a hyperspectral image cube end.

An Algorithm-Based Approach for Behavior and Disease Management in Children.

PubMed

Meyer, Beau D; Lee, Jessica Y; Thikkurissy, S; Casamassimo, Paul S; Vann, William F

2018-03-15

Pharmacologic behavior management for dental treatment is an approach to provide invasive yet compassionate care for young children; it can facilitate the treatment of children who otherwise may not cooperate for traditional in-office care. Some recent highly publicized procedural sedation-related tragedies have drawn attention to risks associated with pharmacologic management. However, it remains widely accepted that, by adhering to proper guidelines, procedural sedation can assist in the provision of high-quality dental care while minimizing morbidity and mortality from the procedure. The purpose of this paper was to propose an algorithm for clinicians to consider when selecting a behavior and disease management strategy for early childhood caries. This algorithm will not ensure a positive outcome but can assist clinicians when counseling caregivers about risks, benefits, and alternatives. It also emphasizes and underscores best-safety practices.

Long-term surface EMG monitoring using K-means clustering and compressive sensing

NASA Astrophysics Data System (ADS)

Balouchestani, Mohammadreza; Krishnan, Sridhar

2015-05-01

In this work, we present an advanced K-means clustering algorithm based on Compressed Sensing theory (CS) in combination with the K-Singular Value Decomposition (K-SVD) method for Clustering of long-term recording of surface Electromyography (sEMG) signals. The long-term monitoring of sEMG signals aims at recording of the electrical activity produced by muscles which are very useful procedure for treatment and diagnostic purposes as well as for detection of various pathologies. The proposed algorithm is examined for three scenarios of sEMG signals including healthy person (sEMG-Healthy), a patient with myopathy (sEMG-Myopathy), and a patient with neuropathy (sEMG-Neuropathr), respectively. The proposed algorithm can easily scan large sEMG datasets of long-term sEMG recording. We test the proposed algorithm with Principal Component Analysis (PCA) and Linear Correlation Coefficient (LCC) dimensionality reduction methods. Then, the output of the proposed algorithm is fed to K-Nearest Neighbours (K-NN) and Probabilistic Neural Network (PNN) classifiers in order to calclute the clustering performance. The proposed algorithm achieves a classification accuracy of 99.22%. This ability allows reducing 17% of Average Classification Error (ACE), 9% of Training Error (TE), and 18% of Root Mean Square Error (RMSE). The proposed algorithm also reduces 14% clustering energy consumption compared to the existing K-Means clustering algorithm.

Multiscale computations with a wavelet-adaptive algorithm

NASA Astrophysics Data System (ADS)

Rastigejev, Yevgenii Anatolyevich

A wavelet-based adaptive multiresolution algorithm for the numerical solution of multiscale problems governed by partial differential equations is introduced. The main features of the method include fast algorithms for the calculation of wavelet coefficients and approximation of derivatives on nonuniform stencils. The connection between the wavelet order and the size of the stencil is established. The algorithm is based on the mathematically well established wavelet theory. This allows us to provide error estimates of the solution which are used in conjunction with an appropriate threshold criteria to adapt the collocation grid. The efficient data structures for grid representation as well as related computational algorithms to support grid rearrangement procedure are developed. The algorithm is applied to the simulation of phenomena described by Navier-Stokes equations. First, we undertake the study of the ignition and subsequent viscous detonation of a H2 : O2 : Ar mixture in a one-dimensional shock tube. Subsequently, we apply the algorithm to solve the two- and three-dimensional benchmark problem of incompressible flow in a lid-driven cavity at large Reynolds numbers. For these cases we show that solutions of comparable accuracy as the benchmarks are obtained with more than an order of magnitude reduction in degrees of freedom. The simulations show the striking ability of the algorithm to adapt to a solution having different scales at different spatial locations so as to produce accurate results at a relatively low computational cost.

A baseline-free procedure for transformation models under interval censorship.

PubMed

Gu, Ming Gao; Sun, Liuquan; Zuo, Guoxin

2005-12-01

An important property of Cox regression model is that the estimation of regression parameters using the partial likelihood procedure does not depend on its baseline survival function. We call such a procedure baseline-free. Using marginal likelihood, we show that an baseline-free procedure can be derived for a class of general transformation models under interval censoring framework. The baseline-free procedure results a simplified and stable computation algorithm for some complicated and important semiparametric models, such as frailty models and heteroscedastic hazard/rank regression models, where the estimation procedures so far available involve estimation of the infinite dimensional baseline function. A detailed computational algorithm using Markov Chain Monte Carlo stochastic approximation is presented. The proposed procedure is demonstrated through extensive simulation studies, showing the validity of asymptotic consistency and normality. We also illustrate the procedure with a real data set from a study of breast cancer. A heuristic argument showing that the score function is a mean zero martingale is provided.

Development of a meta-algorithm for guiding primary care encounters for patients with multimorbidity using evidence-based and case-based guideline development methodology.

PubMed

Muche-Borowski, Cathleen; Lühmann, Dagmar; Schäfer, Ingmar; Mundt, Rebekka; Wagner, Hans-Otto; Scherer, Martin

2017-06-22

The study aimed to develop a comprehensive algorithm (meta-algorithm) for primary care encounters of patients with multimorbidity. We used a novel, case-based and evidence-based procedure to overcome methodological difficulties in guideline development for patients with complex care needs. Systematic guideline development methodology including systematic evidence retrieval (guideline synopses), expert opinions and informal and formal consensus procedures. Primary care. The meta-algorithm was developed in six steps:1. Designing 10 case vignettes of patients with multimorbidity (common, epidemiologically confirmed disease patterns and/or particularly challenging health care needs) in a multidisciplinary workshop.2. Based on the main diagnoses, a systematic guideline synopsis of evidence-based and consensus-based clinical practice guidelines was prepared. The recommendations were prioritised according to the clinical and psychosocial characteristics of the case vignettes.3. Case vignettes along with the respective guideline recommendations were validated and specifically commented on by an external panel of practicing general practitioners (GPs).4. Guideline recommendations and experts' opinions were summarised as case specific management recommendations (N-of-one guidelines).5. Healthcare preferences of patients with multimorbidity were elicited from a systematic literature review and supplemented with information from qualitative interviews.6. All N-of-one guidelines were analysed using pattern recognition to identify common decision nodes and care elements. These elements were put together to form a generic meta-algorithm. The resulting meta-algorithm reflects the logic of a GP's encounter of a patient with multimorbidity regarding decision-making situations, communication needs and priorities. It can be filled with the complex problems of individual patients and hereby offer guidance to the practitioner. Contrary to simple, symptom-oriented algorithms, the meta-algorithm illustrates a superordinate process that permanently keeps the entire patient in view. The meta-algorithm represents the back bone of the multimorbidity guideline of the German College of General Practitioners and Family Physicians. This article presents solely the development phase; the meta-algorithm needs to be piloted before it can be implemented. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Description of the GMAO OSSE for Weather Analysis Software Package: Version 3

NASA Technical Reports Server (NTRS)

Koster, Randal D. (Editor); Errico, Ronald M.; Prive, Nikki C.; Carvalho, David; Sienkiewicz, Meta; El Akkraoui, Amal; Guo, Jing; Todling, Ricardo; McCarty, Will; Putman, William M.;

A time-accurate algorithm for chemical non-equilibrium viscous flows at all speeds

NASA Technical Reports Server (NTRS)

Shuen, J.-S.; Chen, K.-H.; Choi, Y.

1992-01-01

A time-accurate, coupled solution procedure is described for the chemical nonequilibrium Navier-Stokes equations over a wide range of Mach numbers. This method employs the strong conservation form of the governing equations, but uses primitive variables as unknowns. Real gas properties and equilibrium chemistry are considered. Numerical tests include steady convergent-divergent nozzle flows with air dissociation/recombination chemistry, dump combustor flows with n-pentane-air chemistry, nonreacting flow in a model double annular combustor, and nonreacting unsteady driven cavity flows. Numerical results for both the steady and unsteady flows demonstrate the efficiency and robustness of the present algorithm for Mach numbers ranging from the incompressible limit to supersonic speeds.

Improving Pediatric Basic Life Support Performance Through Blended Learning With Web-Based Virtual Patients: Randomized Controlled Trial.

PubMed

Lehmann, Ronny; Thiessen, Christiane; Frick, Barbara; Bosse, Hans Martin; Nikendei, Christoph; Hoffmann, Georg Friedrich; Tönshoff, Burkhard; Huwendiek, Sören

2015-07-02

E-learning and blended learning approaches gain more and more popularity in emergency medicine curricula. So far, little data is available on the impact of such approaches on procedural learning and skill acquisition and their comparison with traditional approaches. This study investigated the impact of a blended learning approach, including Web-based virtual patients (VPs) and standard pediatric basic life support (PBLS) training, on procedural knowledge, objective performance, and self-assessment. A total of 57 medical students were randomly assigned to an intervention group (n=30) and a control group (n=27). Both groups received paper handouts in preparation of simulation-based PBLS training. The intervention group additionally completed two Web-based VPs with embedded video clips. Measurements were taken at randomization (t0), after the preparation period (t1), and after hands-on training (t2). Clinical decision-making skills and procedural knowledge were assessed at t0 and t1. PBLS performance was scored regarding adherence to the correct algorithm, conformance to temporal demands, and the quality of procedural steps at t1 and t2. Participants' self-assessments were recorded in all three measurements. Procedural knowledge of the intervention group was significantly superior to that of the control group at t1. At t2, the intervention group showed significantly better adherence to the algorithm and temporal demands, and better procedural quality of PBLS in objective measures than did the control group. These aspects differed between the groups even at t1 (after VPs, prior to practical training). Self-assessments differed significantly only at t1 in favor of the intervention group. Training with VPs combined with hands-on training improves PBLS performance as judged by objective measures.

Vibration based algorithm for crack detection in cantilever beam containing two different types of cracks

NASA Astrophysics Data System (ADS)

Behzad, Mehdi; Ghadami, Amin; Maghsoodi, Ameneh; Michael Hale, Jack

2013-11-01

In this paper, a simple method for detection of multiple edge cracks in Euler-Bernoulli beams having two different types of cracks is presented based on energy equations. Each crack is modeled as a massless rotational spring using Linear Elastic Fracture Mechanics (LEFM) theory, and a relationship among natural frequencies, crack locations and stiffness of equivalent springs is demonstrated. In the procedure, for detection of m cracks in a beam, 3m equations and natural frequencies of healthy and cracked beam in two different directions are needed as input to the algorithm. The main accomplishment of the presented algorithm is the capability to detect the location, severity and type of each crack in a multi-cracked beam. Concise and simple calculations along with accuracy are other advantages of this method. A number of numerical examples for cantilever beams including one and two cracks are presented to validate the method.

Using ACIS on the Chandra X-ray Observatory as a Particle Radiation Monitor II

NASA Technical Reports Server (NTRS)

Grant, C. E.; Ford, P. G.; Bautz, M. W.; ODell, S. L.

2012-01-01

The Advanced CCD Imaging Spectrometer is an instrument on the Chandra X-ray Observatory. CCDs are vulnerable to radiation damage, particularly by soft protons in the radiation belts and solar storms. The Chandra team has implemented procedures to protect ACIS during high-radiation events including autonomous protection triggered by an on-board radiation monitor. Elevated temperatures have reduced the effectiveness of the on-board monitor. The ACIS team has developed an algorithm which uses data from the CCDs themselves to detect periods of high radiation and a flight software patch to apply this algorithm is currently active on-board the instrument. In this paper, we explore the ACIS response to particle radiation through comparisons to a number of external measures of the radiation environment. We hope to better understand the efficiency of the algorithm as a function of the flux and spectrum of the particles and the time-profile of the radiation event.

A computational study of the flowfield surrounding the Aeroassist Flight Experiment vehicle

NASA Technical Reports Server (NTRS)

Gnoffo, Peter A.; Greene, Francis A.

1987-01-01

A symmetric total variation diminishing (STVD) algorithm has been applied to the solution of the three-dimensional hypersonic flowfield surrounding the Aeroassist Flight Experiment (AFE) vehicle. Both perfect-gas and chemical nonequilibrium models have been used. The perfect-gas flows were computed at two different Reynolds numbers, including a flight trajectory point at maximum dynamic pressure, and on two different grids. Procedures for coupling the solution of the species continuity equations with the Navier-Stokes equations in the presence of chemical nonequilibrium are reviewed and tested on the forebody of the AFE and on the complete flowfield assuming noncatalytic wall and no species diffusion. Problems with the STVD algorithm unique to flows with variable thermodynamic properties (real gas) are identified and algorithm modifications are suggested. A potential heating problem caused by strong flow impingement on the nozzle lip in the near wake at 0-deg angle of attack has been identified.

Galileo Attitude Determination: Experiences with a Rotating Star Scanner

NASA Technical Reports Server (NTRS)

Merken, L.; Singh, G.

1991-01-01

The Galileo experience with a rotating star scanner is discussed in terms of problems encountered in flight, solutions implemented, and lessons learned. An overview of the Galileo project and the attitude and articulation control subsystem is given and the star scanner hardware and relevant software algorithms are detailed. The star scanner is the sole source of inertial attitude reference for this spacecraft. Problem symptoms observed in flight are discussed in terms of effects on spacecraft performance and safety. Sources of thse problems include contributions from flight software idiosyncrasies and inadequate validation of the ground procedures used to identify target stars for use by the autonomous on-board star identification algorithm. Problem fixes (some already implemented and some only proposed) are discussed. A general conclusion is drawn regarding the inherent difficulty of performing simulation tests to validate algorithms which are highly sensitive to external inputs of statistically 'rare' events.

Multistage classification of multispectral Earth observational data: The design approach

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator); Muasher, M. J.; Landgrebe, D. A.

1981-01-01

An algorithm is proposed which predicts the optimal features at every node in a binary tree procedure. The algorithm estimates the probability of error by approximating the area under the likelihood ratio function for two classes and taking into account the number of training samples used in estimating each of these two classes. Some results on feature selection techniques, particularly in the presence of a very limited set of training samples, are presented. Results comparing probabilities of error predicted by the proposed algorithm as a function of dimensionality as compared to experimental observations are shown for aircraft and LANDSAT data. Results are obtained for both real and simulated data. Finally, two binary tree examples which use the algorithm are presented to illustrate the usefulness of the procedure.

Implementation of a partitioned algorithm for simulation of large CSI problems

NASA Technical Reports Server (NTRS)

Alvin, Kenneth F.; Park, K. C.

1991-01-01

The implementation of a partitioned numerical algorithm for determining the dynamic response of coupled structure/controller/estimator finite-dimensional systems is reviewed. The partitioned approach leads to a set of coupled first and second-order linear differential equations which are numerically integrated with extrapolation and implicit step methods. The present software implementation, ACSIS, utilizes parallel processing techniques at various levels to optimize performance on a shared-memory concurrent/vector processing system. A general procedure for the design of controller and filter gains is also implemented, which utilizes the vibration characteristics of the structure to be solved. Also presented are: example problems; a user's guide to the software; the procedures and algorithm scripts; a stability analysis for the algorithm; and the source code for the parallel implementation.

Hyperspectral data analysis procedures with reduced sensitivity to noise

NASA Technical Reports Server (NTRS)

Landgrebe, David A.

1993-01-01

Multispectral sensor systems have become steadily improved over the years in their ability to deliver increased spectral detail. With the advent of hyperspectral sensors, including imaging spectrometers, this technology is in the process of taking a large leap forward, thus providing the possibility of enabling delivery of much more detailed information. However, this direction of development has drawn even more attention to the matter of noise and other deleterious effects in the data, because reducing the fundamental limitations of spectral detail on information collection raises the limitations presented by noise to even greater importance. Much current effort in remote sensing research is thus being devoted to adjusting the data to mitigate the effects of noise and other deleterious effects. A parallel approach to the problem is to look for analysis approaches and procedures which have reduced sensitivity to such effects. We discuss some of the fundamental principles which define analysis algorithm characteristics providing such reduced sensitivity. One such analysis procedure including an example analysis of a data set is described, illustrating this effect.

Measuring the self-similarity exponent in Lévy stable processes of financial time series

NASA Astrophysics Data System (ADS)

Fernández-Martínez, M.; Sánchez-Granero, M. A.; Trinidad Segovia, J. E.

2013-11-01

Geometric method-based procedures, which will be called GM algorithms herein, were introduced in [M.A. Sánchez Granero, J.E. Trinidad Segovia, J. García Pérez, Some comments on Hurst exponent and the long memory processes on capital markets, Phys. A 387 (2008) 5543-5551], to efficiently calculate the self-similarity exponent of a time series. In that paper, the authors showed empirically that these algorithms, based on a geometrical approach, are more accurate than the classical algorithms, especially with short length time series. The authors checked that GM algorithms are good when working with (fractional) Brownian motions. Moreover, in [J.E. Trinidad Segovia, M. Fernández-Martínez, M.A. Sánchez-Granero, A note on geometric method-based procedures to calculate the Hurst exponent, Phys. A 391 (2012) 2209-2214], a mathematical background for the validity of such procedures to estimate the self-similarity index of any random process with stationary and self-affine increments was provided. In particular, they proved theoretically that GM algorithms are also valid to explore long-memory in (fractional) Lévy stable motions. In this paper, we prove empirically by Monte Carlo simulation that GM algorithms are able to calculate accurately the self-similarity index in Lévy stable motions and find empirical evidence that they are more precise than the absolute value exponent (denoted by AVE onwards) and the multifractal detrended fluctuation analysis (MF-DFA) algorithms, especially with a short length time series. We also compare them with the generalized Hurst exponent (GHE) algorithm and conclude that both GM2 and GHE algorithms are the most accurate to study financial series. In addition to that, we provide empirical evidence, based on the accuracy of GM algorithms to estimate the self-similarity index in Lévy motions, that the evolution of the stocks of some international market indices, such as U.S. Small Cap and Nasdaq100, cannot be modelized by means of a Brownian motion.

Validation of an International Classification of Diseases, Ninth Revision Code Algorithm for Identifying Chiari Malformation Type 1 Surgery in Adults.

PubMed

Greenberg, Jacob K; Ladner, Travis R; Olsen, Margaret A; Shannon, Chevis N; Liu, Jingxia; Yarbrough, Chester K; Piccirillo, Jay F; Wellons, John C; Smyth, Matthew D; Park, Tae Sung; Limbrick, David D

2015-08-01

The use of administrative billing data may enable large-scale assessments of treatment outcomes for Chiari Malformation type I (CM-1). However, to utilize such data sets, validated International Classification of Diseases, Ninth Revision (ICD-9-CM) code algorithms for identifying CM-1 surgery are needed. To validate 2 ICD-9-CM code algorithms identifying patients undergoing CM-1 decompression surgery. We retrospectively analyzed the validity of 2 ICD-9-CM code algorithms for identifying adult CM-1 decompression surgery performed at 2 academic medical centers between 2001 and 2013. Algorithm 1 included any discharge diagnosis code of 348.4 (CM-1), as well as a procedure code of 01.24 (cranial decompression) or 03.09 (spinal decompression, or laminectomy). Algorithm 2 restricted this group to patients with a primary diagnosis of 348.4. The positive predictive value (PPV) and sensitivity of each algorithm were calculated. Among 340 first-time admissions identified by Algorithm 1, the overall PPV for CM-1 decompression was 65%. Among the 214 admissions identified by Algorithm 2, the overall PPV was 99.5%. The PPV for Algorithm 1 was lower in the Vanderbilt (59%) cohort, males (40%), and patients treated between 2009 and 2013 (57%), whereas the PPV of Algorithm 2 remained high (≥99%) across subgroups. The sensitivity of Algorithms 1 (86%) and 2 (83%) were above 75% in all subgroups. ICD-9-CM code Algorithm 2 has excellent PPV and good sensitivity to identify adult CM-1 decompression surgery. These results lay the foundation for studying CM-1 treatment outcomes by using large administrative databases.

TORC3: Token-ring clearing heuristic for currency circulation

NASA Astrophysics Data System (ADS)

Humes, Carlos, Jr.; Lauretto, Marcelo S.; Nakano, Fábio; Pereira, Carlos A. B.; Rafare, Guilherme F. G.; Stern, Julio Michael

2012-10-01

Clearing algorithms are at the core of modern payment systems, facilitating the settling of multilateral credit messages with (near) minimum transfers of currency. Traditional clearing procedures use batch processing based on MILP - mixed-integer linear programming algorithms. The MILP approach demands intensive computational resources; moreover, it is also vulnerable to operational risks generated by possible defaults during the inter-batch period. This paper presents TORC3 - the Token-Ring Clearing Algorithm for Currency Circulation. In contrast to the MILP approach, TORC3 is a real time heuristic procedure, demanding modest computational resources, and able to completely shield the clearing operation against the participating agents' risk of default.

The PX-EM algorithm for fast stable fitting of Henderson's mixed model

PubMed Central

Foulley, Jean-Louis; Van Dyk, David A

2000-01-01

This paper presents procedures for implementing the PX-EM algorithm of Liu, Rubin and Wu to compute REML estimates of variance covariance components in Henderson's linear mixed models. The class of models considered encompasses several correlated random factors having the same vector length e.g., as in random regression models for longitudinal data analysis and in sire-maternal grandsire models for genetic evaluation. Numerical examples are presented to illustrate the procedures. Much better results in terms of convergence characteristics (number of iterations and time required for convergence) are obtained for PX-EM relative to the basic EM algorithm in the random regression. PMID:14736399

Surgical options for lumbosacral fusion: biomechanical stability, advantage, disadvantage and affecting factors in selecting options.

PubMed

Yoshihara, Hiroyuki

2014-07-01

Numerous surgical procedures and instrumentation techniques for lumbosacral fusion (LSF) have been developed. This is probably because of its high mechanical demand and unique anatomy. Surgical options include anterior column support (ACS) and posterior stabilization procedures. Biomechanical studies have been performed to verify the stability of those options. The options have their own advantage but also disadvantage aspects. This review article reports the surgical options for lumbosacral fusion, their biomechanical stability, advantages/disadvantages, and affecting factors in option selection. Review of literature. LSF has lots of options both for ACS and posterior stabilization procedures. Combination of posterior stabilization procedures is an option. Furthermore, combinations of ACS and posterior stabilization procedures are other options. It is difficult to make a recommendation or treatment algorithm of LSF from the current literature. However, it is important to know all aspects of the options and decision-making of surgical options for LSF needs to be tailored for each patient, considering factors such as biomechanical stress and osteoporosis.

The Multiple-Minima Problem in Protein Folding

NASA Astrophysics Data System (ADS)

Scheraga, Harold A.

1991-10-01

The conformational energy surface of a polypeptide or protein has many local minima, and conventional energy minimization procedures reach only a local minimum (near the starting point of the optimization algorithm) instead of the global minimum (the multiple-minima problem). Several procedures have been developed to surmount this problem, the most promising of which are: (a) build up procedure, (b) optimization of electrostatics, (c) Monte Carlo-plus-energy minimization, (d) electrostatically-driven Monte Carlo, (e) inclusion of distance restraints, (f) adaptive importance-sampling Monte Carlo, (g) relaxation of dimensionality, (h) pattern-recognition, and (i) diffusion equation method. These procedures have been applied to a variety of polypeptide structural problems, and the results of such computations are presented. These include the computation of the structures of open-chain and cyclic peptides, fibrous proteins and globular proteins. Present efforts are being devoted to scaling up these procedures from small polypeptides to proteins, to try to compute the three-dimensional structure of a protein from its amino sequence.

Dynamic vehicle routing with time windows in theory and practice.

PubMed

Yang, Zhiwei; van Osta, Jan-Paul; van Veen, Barry; van Krevelen, Rick; van Klaveren, Richard; Stam, Andries; Kok, Joost; Bäck, Thomas; Emmerich, Michael

2017-01-01

The vehicle routing problem is a classical combinatorial optimization problem. This work is about a variant of the vehicle routing problem with dynamically changing orders and time windows. In real-world applications often the demands change during operation time. New orders occur and others are canceled. In this case new schedules need to be generated on-the-fly. Online optimization algorithms for dynamical vehicle routing address this problem but so far they do not consider time windows. Moreover, to match the scenarios found in real-world problems adaptations of benchmarks are required. In this paper, a practical problem is modeled based on the procedure of daily routing of a delivery company. New orders by customers are introduced dynamically during the working day and need to be integrated into the schedule. A multiple ant colony algorithm combined with powerful local search procedures is proposed to solve the dynamic vehicle routing problem with time windows. The performance is tested on a new benchmark based on simulations of a working day. The problems are taken from Solomon's benchmarks but a certain percentage of the orders are only revealed to the algorithm during operation time. Different versions of the MACS algorithm are tested and a high performing variant is identified. Finally, the algorithm is tested in situ: In a field study, the algorithm schedules a fleet of cars for a surveillance company. We compare the performance of the algorithm to that of the procedure used by the company and we summarize insights gained from the implementation of the real-world study. The results show that the multiple ant colony algorithm can get a much better solution on the academic benchmark problem and also can be integrated in a real-world environment.

Improved Variable Selection Algorithm Using a LASSO-Type Penalty, with an Application to Assessing Hepatitis B Infection Relevant Factors in Community Residents

PubMed Central

Guo, Pi; Zeng, Fangfang; Hu, Xiaomin; Zhang, Dingmei; Zhu, Shuming; Deng, Yu; Hao, Yuantao

2015-01-01

Objectives In epidemiological studies, it is important to identify independent associations between collective exposures and a health outcome. The current stepwise selection technique ignores stochastic errors and suffers from a lack of stability. The alternative LASSO-penalized regression model can be applied to detect significant predictors from a pool of candidate variables. However, this technique is prone to false positives and tends to create excessive biases. It remains challenging to develop robust variable selection methods and enhance predictability. Material and methods Two improved algorithms denoted the two-stage hybrid and bootstrap ranking procedures, both using a LASSO-type penalty, were developed for epidemiological association analysis. The performance of the proposed procedures and other methods including conventional LASSO, Bolasso, stepwise and stability selection models were evaluated using intensive simulation. In addition, methods were compared by using an empirical analysis based on large-scale survey data of hepatitis B infection-relevant factors among Guangdong residents. Results The proposed procedures produced comparable or less biased selection results when compared to conventional variable selection models. In total, the two newly proposed procedures were stable with respect to various scenarios of simulation, demonstrating a higher power and a lower false positive rate during variable selection than the compared methods. In empirical analysis, the proposed procedures yielding a sparse set of hepatitis B infection-relevant factors gave the best predictive performance and showed that the procedures were able to select a more stringent set of factors. The individual history of hepatitis B vaccination, family and individual history of hepatitis B infection were associated with hepatitis B infection in the studied residents according to the proposed procedures. Conclusions The newly proposed procedures improve the identification of significant variables and enable us to derive a new insight into epidemiological association analysis. PMID:26214802

[Digital breast tomosynthesis : technical principles, current clinical relevance and future perspectives].

PubMed

Hellerhoff, K

2010-11-01

In recent years digital full field mammography has increasingly replaced conventional film mammography. High quality imaging is guaranteed by high quantum efficiency and very good contrast resolution with optimized dosing even for women with dense glandular tissue. However, digital mammography remains a projection procedure by which overlapping tissue limits the detectability of subtle alterations. Tomosynthesis is a procedure developed from digital mammography for slice examination of breasts which eliminates the effects of overlapping tissue and allows 3D imaging of breasts. A curved movement of the X-ray tube during scanning allows the acquisition of many 2D images from different angles. Subseqently, reconstruction algorithms employing a shift and add method improve the recognition of details at a defined level and at the same time eliminate smear artefacts due to overlapping structures. The total dose corresponds to that of conventional mammography imaging. The technical procedure, including the number of levels, suitable anodes/filter combinations, angle regions of images and selection of reconstruction algorithms, is presently undergoing optimization. Previous studies on the clinical value of tomosynthesis have examined screening parameters, such as recall rate and detection rate as well as information on tumor extent for histologically proven breast tumors. More advanced techniques, such as contrast medium-enhanced tomosynthesis, are presently under development and dual-energy imaging is of particular importance.

Technology transfer by means of fault tree synthesis

NASA Astrophysics Data System (ADS)

Batzias, Dimitris F.

2012-12-01

Since Fault Tree Analysis (FTA) attempts to model and analyze failure processes of engineering, it forms a common technique for good industrial practice. On the contrary, fault tree synthesis (FTS) refers to the methodology of constructing complex trees either from dentritic modules built ad hoc or from fault tress already used and stored in a Knowledge Base. In both cases, technology transfer takes place in a quasi-inductive mode, from partial to holistic knowledge. In this work, an algorithmic procedure, including 9 activity steps and 3 decision nodes is developed for performing effectively this transfer when the fault under investigation occurs within one of the latter stages of an industrial procedure with several stages in series. The main parts of the algorithmic procedure are: (i) the construction of a local fault tree within the corresponding production stage, where the fault has been detected, (ii) the formation of an interface made of input faults that might occur upstream, (iii) the fuzzy (to count for uncertainty) multicriteria ranking of these faults according to their significance, and (iv) the synthesis of an extended fault tree based on the construction of part (i) and on the local fault tree of the first-ranked fault in part (iii). An implementation is presented, referring to 'uneven sealing of Al anodic film', thus proving the functionality of the developed methodology.

Geometrical Characterisation of a 2D Laser System and Calibration of a Cross-Grid Encoder by Means of a Self-Calibration Methodology

PubMed Central

Torralba, Marta; Díaz-Pérez, Lucía C.

2017-01-01

This article presents a self-calibration procedure and the experimental results for the geometrical characterisation of a 2D laser system operating along a large working range (50 mm × 50 mm) with submicrometre uncertainty. Its purpose is to correct the geometric errors of the 2D laser system setup generated when positioning the two laser heads and the plane mirrors used as reflectors. The non-calibrated artefact used in this procedure is a commercial grid encoder that is also a measuring instrument. Therefore, the self-calibration procedure also allows the determination of the geometrical errors of the grid encoder, including its squareness error. The precision of the proposed algorithm is tested using virtual data. Actual measurements are subsequently registered, and the algorithm is applied. Once the laser system is characterised, the error of the grid encoder is calculated along the working range, resulting in an expanded submicrometre calibration uncertainty (k = 2) for the X and Y axes. The results of the grid encoder calibration are comparable to the errors provided by the calibration certificate for its main central axes. It is, therefore, possible to confirm the suitability of the self-calibration methodology proposed in this article. PMID:28858239

Behavior of optical properties of coagulated blood sample at 633 nm wavelength

NASA Astrophysics Data System (ADS)

Morales Cruzado, Beatriz; Vázquez y Montiel, Sergio; Delgado Atencio, José Alberto

2011-03-01

Determination of tissue optical parameters is fundamental for application of light in either diagnostics or therapeutical procedures. However, in samples of biological tissue in vitro, the optical properties are modified by cellular death or cellular agglomeration that can not be avoided. This phenomena change the propagation of light within the biological sample. Optical properties of human blood tissue were investigated in vitro at 633 nm using an optical setup that includes a double integrating sphere system. We measure the diffuse transmittance and diffuse reflectance of the blood sample and compare these physical properties with those obtained by Monte Carlo Multi-Layered (MCML). The extraction of the optical parameters: absorption coefficient μa, scattering coefficient μs and anisotropic factor g from the measurements were carried out using a Genetic Algorithm, in which the search procedure is based in the evolution of a population due to selection of the best individual, evaluated by a function that compares the diffuse transmittance and diffuse reflectance of those individuals with the experimental ones. The algorithm converges rapidly to the best individual, extracting the optical parameters of the sample. We compare our results with those obtained by using other retrieve procedures. We found that the scattering coefficient and the anisotropic factor change dramatically due to the formation of clusters.

Assessing the Performance of Sensor Fusion Methods: Application to Magnetic-Inertial-Based Human Body Tracking

PubMed Central

Ligorio, Gabriele; Bergamini, Elena; Pasciuto, Ilaria; Vannozzi, Giuseppe; Cappozzo, Aurelio; Sabatini, Angelo Maria

2016-01-01

Information from complementary and redundant sensors are often combined within sensor fusion algorithms to obtain a single accurate observation of the system at hand. However, measurements from each sensor are characterized by uncertainties. When multiple data are fused, it is often unclear how all these uncertainties interact and influence the overall performance of the sensor fusion algorithm. To address this issue, a benchmarking procedure is presented, where simulated and real data are combined in different scenarios in order to quantify how each sensor’s uncertainties influence the accuracy of the final result. The proposed procedure was applied to the estimation of the pelvis orientation using a waist-worn magnetic-inertial measurement unit. Ground-truth data were obtained from a stereophotogrammetric system and used to obtain simulated data. Two Kalman-based sensor fusion algorithms were submitted to the proposed benchmarking procedure. For the considered application, gyroscope uncertainties proved to be the main error source in orientation estimation accuracy for both tested algorithms. Moreover, although different performances were obtained using simulated data, these differences became negligible when real data were considered. The outcome of this evaluation may be useful both to improve the design of new sensor fusion methods and to drive the algorithm tuning process. PMID:26821027

Assessing the Performance of Sensor Fusion Methods: Application to Magnetic-Inertial-Based Human Body Tracking.

PubMed

Ligorio, Gabriele; Bergamini, Elena; Pasciuto, Ilaria; Vannozzi, Giuseppe; Cappozzo, Aurelio; Sabatini, Angelo Maria

2016-01-26

Information from complementary and redundant sensors are often combined within sensor fusion algorithms to obtain a single accurate observation of the system at hand. However, measurements from each sensor are characterized by uncertainties. When multiple data are fused, it is often unclear how all these uncertainties interact and influence the overall performance of the sensor fusion algorithm. To address this issue, a benchmarking procedure is presented, where simulated and real data are combined in different scenarios in order to quantify how each sensor's uncertainties influence the accuracy of the final result. The proposed procedure was applied to the estimation of the pelvis orientation using a waist-worn magnetic-inertial measurement unit. Ground-truth data were obtained from a stereophotogrammetric system and used to obtain simulated data. Two Kalman-based sensor fusion algorithms were submitted to the proposed benchmarking procedure. For the considered application, gyroscope uncertainties proved to be the main error source in orientation estimation accuracy for both tested algorithms. Moreover, although different performances were obtained using simulated data, these differences became negligible when real data were considered. The outcome of this evaluation may be useful both to improve the design of new sensor fusion methods and to drive the algorithm tuning process.

Supercomputer implementation of finite element algorithms for high speed compressible flows

NASA Technical Reports Server (NTRS)

Thornton, E. A.; Ramakrishnan, R.

1986-01-01

Prediction of compressible flow phenomena using the finite element method is of recent origin and considerable interest. Two shock capturing finite element formulations for high speed compressible flows are described. A Taylor-Galerkin formulation uses a Taylor series expansion in time coupled with a Galerkin weighted residual statement. The Taylor-Galerkin algorithms use explicit artificial dissipation, and the performance of three dissipation models are compared. A Petrov-Galerkin algorithm has as its basis the concepts of streamline upwinding. Vectorization strategies are developed to implement the finite element formulations on the NASA Langley VPS-32. The vectorization scheme results in finite element programs that use vectors of length of the order of the number of nodes or elements. The use of the vectorization procedure speeds up processing rates by over two orders of magnitude. The Taylor-Galerkin and Petrov-Galerkin algorithms are evaluated for 2D inviscid flows on criteria such as solution accuracy, shock resolution, computational speed and storage requirements. The convergence rates for both algorithms are enhanced by local time-stepping schemes. Extension of the vectorization procedure for predicting 2D viscous and 3D inviscid flows are demonstrated. Conclusions are drawn regarding the applicability of the finite element procedures for realistic problems that require hundreds of thousands of nodes.

Tools for computer graphics applications

NASA Technical Reports Server (NTRS)

Phillips, R. L.

1976-01-01

Extensive research in computer graphics has produced a collection of basic algorithms and procedures whose utility spans many disciplines. These tools are described in terms of their fundamental aspects, implementations, applications, and availability. Programs which are discussed include basic data plotting, curve smoothing, and depiction of three dimensional surfaces. As an aid to potential users of these tools, particular attention is given to discussing their availability and, where applicable, their cost.

High speed inviscid compressible flow by the finite element method

NASA Technical Reports Server (NTRS)

Zienkiewicz, O. C.; Loehner, R.; Morgan, K.

1984-01-01

The finite element method and an explicit time stepping algorithm which is based on Taylor-Galerkin schemes with an appropriate artificial viscosity is combined with an automatic mesh refinement process which is designed to produce accurate steady state solutions to problems of inviscid compressible flow in two dimensions. The results of two test problems are included which demonstrate the excellent performance characteristics of the proposed procedures.

Mesh quality control for multiply-refined tetrahedral grids

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Strawn, Roger

1994-01-01

A new algorithm for controlling the quality of multiply-refined tetrahedral meshes is presented in this paper. The basic dynamic mesh adaption procedure allows localized grid refinement and coarsening to efficiently capture aerodynamic flow features in computational fluid dynamics problems; however, repeated application of the procedure may significantly deteriorate the quality of the mesh. Results presented show the effectiveness of this mesh quality algorithm and its potential in the area of helicopter aerodynamics and acoustics.

MCSCF wave functions for excited states of polar molecules - Application to BeO. [Multi-Configuration Self-Consistent Field

NASA Technical Reports Server (NTRS)

Bauschlicher, C. W., Jr.; Yarkony, D. R.

1980-01-01

A previously reported multi-configuration self-consistent field (MCSCF) algorithm based on the generalized Brillouin theorem is extended in order to treat the excited states of polar molecules. In particular, the algorithm takes into account the proper treatment of nonorthogonality in the space of single excitations and invokes, when necessary, a constrained optimization procedure to prevent the variational collapse of excited states. In addition, a configuration selection scheme (suitable for use in conjunction with extended configuration interaction methods) is proposed for the MCSCF procedure. The algorithm is used to study the low-lying singlet states of BeO, a system which has not previously been studied using an MCSCF procedure. MCSCF wave functions are obtained for three 1 Sigma + and two 1 Pi states. The 1 Sigma + results are juxtaposed with comparable results for MgO in order to assess the generality of the description presented here.

A new procedure for dynamic adaption of three-dimensional unstructured grids

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Strawn, Roger

1993-01-01

A new procedure is presented for the simultaneous coarsening and refinement of three-dimensional unstructured tetrahedral meshes. This algorithm allows for localized grid adaption that is used to capture aerodynamic flow features such as vortices and shock waves in helicopter flowfield simulations. The mesh-adaption algorithm is implemented in the C programming language and uses a data structure consisting of a series of dynamically-allocated linked lists. These lists allow the mesh connectivity to be rapidly reconstructed when individual mesh points are added and/or deleted. The algorithm allows the mesh to change in an anisotropic manner in order to efficiently resolve directional flow features. The procedure has been successfully implemented on a single processor of a Cray Y-MP computer. Two sample cases are presented involving three-dimensional transonic flow. Computed results show good agreement with conventional structured-grid solutions for the Euler equations.

A comparison of various algorithms to extract Magic Formula tyre model coefficients for vehicle dynamics simulations

NASA Astrophysics Data System (ADS)

Vijay Alagappan, A.; Narasimha Rao, K. V.; Krishna Kumar, R.

2015-02-01

Tyre models are a prerequisite for any vehicle dynamics simulation. Tyre models range from the simplest mathematical models that consider only the cornering stiffness to a complex set of formulae. Among all the steady-state tyre models that are in use today, the Magic Formula tyre model is unique and most popular. Though the Magic Formula tyre model is widely used, obtaining the model coefficients from either the experimental or the simulation data is not straightforward due to its nonlinear nature and the presence of a large number of coefficients. A common procedure used for this extraction is the least-squares minimisation that requires considerable experience for initial guesses. Various researchers have tried different algorithms, namely, gradient and Newton-based methods, differential evolution, artificial neural networks, etc. The issues involved in all these algorithms are setting bounds or constraints, sensitivity of the parameters, the features of the input data such as the number of points, noisy data, experimental procedure used such as slip angle sweep or tyre measurement (TIME) procedure, etc. The extracted Magic Formula coefficients are affected by these variants. This paper highlights the issues that are commonly encountered in obtaining these coefficients with different algorithms, namely, least-squares minimisation using trust region algorithms, Nelder-Mead simplex, pattern search, differential evolution, particle swarm optimisation, cuckoo search, etc. A key observation is that not all the algorithms give the same Magic Formula coefficients for a given data. The nature of the input data and the type of the algorithm decide the set of the Magic Formula tyre model coefficients.

An implicit higher-order spatially accurate scheme for solving time dependent flows on unstructured meshes

NASA Astrophysics Data System (ADS)

Tomaro, Robert F.

1998-07-01

The present research is aimed at developing a higher-order, spatially accurate scheme for both steady and unsteady flow simulations using unstructured meshes. The resulting scheme must work on a variety of general problems to ensure the creation of a flexible, reliable and accurate aerodynamic analysis tool. To calculate the flow around complex configurations, unstructured grids and the associated flow solvers have been developed. Efficient simulations require the minimum use of computer memory and computational times. Unstructured flow solvers typically require more computer memory than a structured flow solver due to the indirect addressing of the cells. The approach taken in the present research was to modify an existing three-dimensional unstructured flow solver to first decrease the computational time required for a solution and then to increase the spatial accuracy. The terms required to simulate flow involving non-stationary grids were also implemented. First, an implicit solution algorithm was implemented to replace the existing explicit procedure. Several test cases, including internal and external, inviscid and viscous, two-dimensional, three-dimensional and axi-symmetric problems, were simulated for comparison between the explicit and implicit solution procedures. The increased efficiency and robustness of modified code due to the implicit algorithm was demonstrated. Two unsteady test cases, a plunging airfoil and a wing undergoing bending and torsion, were simulated using the implicit algorithm modified to include the terms required for a moving and/or deforming grid. Secondly, a higher than second-order spatially accurate scheme was developed and implemented into the baseline code. Third- and fourth-order spatially accurate schemes were implemented and tested. The original dissipation was modified to include higher-order terms and modified near shock waves to limit pre- and post-shock oscillations. The unsteady cases were repeated using the higher-order spatially accurate code. The new solutions were compared with those obtained using the second-order spatially accurate scheme. Finally, the increased efficiency of using an implicit solution algorithm in a production Computational Fluid Dynamics flow solver was demonstrated for steady and unsteady flows. A third- and fourth-order spatially accurate scheme has been implemented creating a basis for a state-of-the-art aerodynamic analysis tool.

Optimization of a chemical identification algorithm

NASA Astrophysics Data System (ADS)

Chyba, Thomas H.; Fisk, Brian; Gunning, Christin; Farley, Kevin; Polizzi, Amber; Baughman, David; Simpson, Steven; Slamani, Mohamed-Adel; Almassy, Robert; Da Re, Ryan; Li, Eunice; MacDonald, Steve; Slamani, Ahmed; Mitchell, Scott A.; Pendell-Jones, Jay; Reed, Timothy L.; Emge, Darren

2010-04-01

A procedure to evaluate and optimize the performance of a chemical identification algorithm is presented. The Joint Contaminated Surface Detector (JCSD) employs Raman spectroscopy to detect and identify surface chemical contamination. JCSD measurements of chemical warfare agents, simulants, toxic industrial chemicals, interferents and bare surface backgrounds were made in the laboratory and under realistic field conditions. A test data suite, developed from these measurements, is used to benchmark algorithm performance throughout the improvement process. In any one measurement, one of many possible targets can be present along with interferents and surfaces. The detection results are expressed as a 2-category classification problem so that Receiver Operating Characteristic (ROC) techniques can be applied. The limitations of applying this framework to chemical detection problems are discussed along with means to mitigate them. Algorithmic performance is optimized globally using robust Design of Experiments and Taguchi techniques. These methods require figures of merit to trade off between false alarms and detection probability. Several figures of merit, including the Matthews Correlation Coefficient and the Taguchi Signal-to-Noise Ratio are compared. Following the optimization of global parameters which govern the algorithm behavior across all target chemicals, ROC techniques are employed to optimize chemical-specific parameters to further improve performance.

Comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry peak sorting algorithm.

PubMed

Oh, Cheolhwan; Huang, Xiaodong; Regnier, Fred E; Buck, Charles; Zhang, Xiang

2008-02-01

We report a novel peak sorting method for the two-dimensional gas chromatography/time-of-flight mass spectrometry (GC x GC/TOF-MS) system. The objective of peak sorting is to recognize peaks from the same metabolite occurring in different samples from thousands of peaks detected in the analytical procedure. The developed algorithm is based on the fact that the chromatographic peaks for a given analyte have similar retention times in all of the chromatograms. Raw instrument data are first processed by ChromaTOF (Leco) software to provide the peak tables. Our algorithm achieves peak sorting by utilizing the first- and second-dimension retention times in the peak tables and the mass spectra generated during the process of electron impact ionization. The algorithm searches the peak tables for the peaks generated by the same type of metabolite using several search criteria. Our software also includes options to eliminate non-target peaks from the sorting results, e.g., peaks of contaminants. The developed software package has been tested using a mixture of standard metabolites and another mixture of standard metabolites spiked into human serum. Manual validation demonstrates high accuracy of peak sorting with this algorithm.

The Optimization of Automatically Generated Compilers.

DTIC Science & Technology

1987-01-01

than their procedural counterparts, and are also easier to analyze for storage optimizations; (2) AGs can be algorithmically checked to be non-circular...Providing algorithms to move the storage for many attributes from the For structure tree into global stacks and variables. -Dd(2) Creating AEs which build and...54 3.5.2. Partitioning algorithm

College Chemistry Students' Use of Memorized Algorithms in Chemical Reactions

ERIC Educational Resources Information Center

Nyachwaya, James M.; Warfa, Abdi-Rizak M; Roehrig, Gillian H.; Schneider, Jamie L.

2014-01-01

This study sought to uncover memorized algorithms and procedures that students relied on in responding to questions based on the particulate nature of matter (PNM). We describe various memorized algorithms or processes used by students. In the study, students were asked to balance three equations of chemical reaction and then draw particulate…

77 FR 50191 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Order Instituting Proceedings To...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-20

... compete with the algorithms that member firms and other market participants currently use to achieve VWAP... orders generated by market participants that may choose to use a competing algorithm. IV. Procedure... offer trading algorithms that would compete with other market participants would impose an undue burden...

Improved Savitzky-Golay-method-based fluorescence subtraction algorithm for rapid recovery of Raman spectra.

PubMed

Chen, Kun; Zhang, Hongyuan; Wei, Haoyun; Li, Yan

2014-08-20

In this paper, we propose an improved subtraction algorithm for rapid recovery of Raman spectra that can substantially reduce the computation time. This algorithm is based on an improved Savitzky-Golay (SG) iterative smoothing method, which involves two key novel approaches: (a) the use of the Gauss-Seidel method and (b) the introduction of a relaxation factor into the iterative procedure. By applying a novel successive relaxation (SG-SR) iterative method to the relaxation factor, additional improvement in the convergence speed over the standard Savitzky-Golay procedure is realized. The proposed improved algorithm (the RIA-SG-SR algorithm), which uses SG-SR-based iteration instead of Savitzky-Golay iteration, has been optimized and validated with a mathematically simulated Raman spectrum, as well as experimentally measured Raman spectra from non-biological and biological samples. The method results in a significant reduction in computing cost while yielding consistent rejection of fluorescence and noise for spectra with low signal-to-fluorescence ratios and varied baselines. In the simulation, RIA-SG-SR achieved 1 order of magnitude improvement in iteration number and 2 orders of magnitude improvement in computation time compared with the range-independent background-subtraction algorithm (RIA). Furthermore the computation time of the experimentally measured raw Raman spectrum processing from skin tissue decreased from 6.72 to 0.094 s. In general, the processing of the SG-SR method can be conducted within dozens of milliseconds, which can provide a real-time procedure in practical situations.

Modeling of polychromatic attenuation using computed tomography reconstructed images

NASA Technical Reports Server (NTRS)

Yan, C. H.; Whalen, R. T.; Beaupre, G. S.; Yen, S. Y.; Napel, S.

1999-01-01

This paper presents a procedure for estimating an accurate model of the CT imaging process including spectral effects. As raw projection data are typically unavailable to the end-user, we adopt a post-processing approach that utilizes the reconstructed images themselves. This approach includes errors from x-ray scatter and the nonidealities of the built-in soft tissue correction into the beam characteristics, which is crucial to beam hardening correction algorithms that are designed to be applied directly to CT reconstructed images. We formulate this approach as a quadratic programming problem and propose two different methods, dimension reduction and regularization, to overcome ill conditioning in the model. For the regularization method we use a statistical procedure, Cross Validation, to select the regularization parameter. We have constructed step-wedge phantoms to estimate the effective beam spectrum of a GE CT-I scanner. Using the derived spectrum, we computed the attenuation ratios for the wedge phantoms and found that the worst case modeling error is less than 3% of the corresponding attenuation ratio. We have also built two test (hybrid) phantoms to evaluate the effective spectrum. Based on these test phantoms, we have shown that the effective beam spectrum provides an accurate model for the CT imaging process. Last, we used a simple beam hardening correction experiment to demonstrate the effectiveness of the estimated beam profile for removing beam hardening artifacts. We hope that this estimation procedure will encourage more independent research on beam hardening corrections and will lead to the development of application-specific beam hardening correction algorithms.

Towards a robust framework for catchment classification

NASA Astrophysics Data System (ADS)

Deshmukh, A.; Samal, A.; Singh, R.

2017-12-01

Classification of catchments based on various measures of similarity has emerged as an important technique to understand regional scale hydrologic behavior. Classification of catchment characteristics and/or streamflow response has been used reveal which characteristics are more likely to explain the observed variability of hydrologic response. However, numerous algorithms for supervised or unsupervised classification are available, making it hard to identify the algorithm most suitable for the dataset at hand. Consequently, existing catchment classification studies vary significantly in the classification algorithms employed with no previous attempt at understanding the degree of uncertainty in classification due to this algorithmic choice. This hinders the generalizability of interpretations related to hydrologic behavior. Our goal is to develop a protocol that can be followed while classifying hydrologic datasets. We focus on a classification framework for unsupervised classification and provide a step-by-step classification procedure. The steps include testing the clusterabiltiy of original dataset prior to classification, feature selection, validation of clustered data, and quantification of similarity of two clusterings. We test several commonly available methods within this framework to understand the level of similarity of classification results across algorithms. We apply the proposed framework on recently developed datasets for India to analyze to what extent catchment properties can explain observed catchment response. Our testing dataset includes watershed characteristics for over 200 watersheds which comprise of both natural (physio-climatic) characteristics and socio-economic characteristics. This framework allows us to understand the controls on observed hydrologic variability across India.

A real-time ECG data compression and transmission algorithm for an e-health device.

PubMed

Lee, SangJoon; Kim, Jungkuk; Lee, Myoungho

2011-09-01

This paper introduces a real-time data compression and transmission algorithm between e-health terminals for a periodic ECGsignal. The proposed algorithm consists of five compression procedures and four reconstruction procedures. In order to evaluate the performance of the proposed algorithm, the algorithm was applied to all 48 recordings of MIT-BIH arrhythmia database, and the compress ratio (CR), percent root mean square difference (PRD), percent root mean square difference normalized (PRDN), rms, SNR, and quality score (QS) values were obtained. The result showed that the CR was 27.9:1 and the PRD was 2.93 on average for all 48 data instances with a 15% window size. In addition, the performance of the algorithm was compared to those of similar algorithms introduced recently by others. It was found that the proposed algorithm showed clearly superior performance in all 48 data instances at a compression ratio lower than 15:1, whereas it showed similar or slightly inferior PRD performance for a data compression ratio higher than 20:1. In light of the fact that the similarity with the original data becomes meaningless when the PRD is higher than 2, the proposed algorithm shows significantly better performance compared to the performance levels of other algorithms. Moreover, because the algorithm can compress and transmit data in real time, it can be served as an optimal biosignal data transmission method for limited bandwidth communication between e-health devices.

Variable neighborhood search to solve the vehicle routing problem for hazardous materials transportation.

PubMed

Bula, Gustavo Alfredo; Prodhon, Caroline; Gonzalez, Fabio Augusto; Afsar, H Murat; Velasco, Nubia

2017-02-15

This work focuses on the Heterogeneous Fleet Vehicle Routing problem (HFVRP) in the context of hazardous materials (HazMat) transportation. The objective is to determine a set of routes that minimizes the total expected routing risk. This is a nonlinear function, and it depends on the vehicle load and the population exposed when an incident occurs. Thus, a piecewise linear approximation is used to estimate it. For solving the problem, a variant of the Variable Neighborhood Search (VNS) algorithm is employed. To improve its performance, a post-optimization procedure is implemented via a Set Partitioning (SP) problem. The SP is solved on a pool of routes obtained from executions of the local search procedure embedded on the VNS. The algorithm is tested on two sets of HFVRP instances based on literature with up to 100 nodes, these instances are modified to include vehicle and arc risk parameters. The results are competitive in terms of computational efficiency and quality attested by a comparison with Mixed Integer Linear Programming (MILP) previously proposed. Copyright © 2016 Elsevier B.V. All rights reserved.

Real-time dynamics and control strategies for space operations of flexible structures

NASA Technical Reports Server (NTRS)

Park, K. C.; Alvin, K. F.; Alexander, S.

1993-01-01

This project (NAG9-574) was meant to be a three-year research project. However, due to NASA's reorganizations during 1992, the project was funded only for one year. Accordingly, every effort was made to make the present final report as if the project was meant to be for one-year duration. Originally, during the first year we were planning to accomplish the following: we were to start with a three dimensional flexible manipulator beam with articulated joints and with a linear control-based controller applied at the joints; using this simple example, we were to design the software systems requirements for real-time processing, introduce the streamlining of various computational algorithms, perform the necessary reorganization of the partitioned simulation procedures, and assess the potential speed-up realization of the solution process by parallel computations. The three reports included as part of the final report address: the streamlining of various computational algorithms; the necessary reorganization of the partitioned simulation procedures, in particular the observer models; and an initial attempt of reconfiguring the flexible space structures.

A comprehensive study on urban true orthorectification

USGS Publications Warehouse

Zhou, G.; Chen, W.; Kelmelis, J.A.; Zhang, Dongxiao

2005-01-01

To provide some advanced technical bases (algorithms and procedures) and experience needed for national large-scale digital orthophoto generation and revision of the Standards for National Large-Scale City Digital Orthophoto in the National Digital Orthophoto Program (NDOP), this paper presents a comprehensive study on theories, algorithms, and methods of large-scale urban orthoimage generation. The procedures of orthorectification for digital terrain model (DTM)-based and digital building model (DBM)-based orthoimage generation and their mergence for true orthoimage generation are discussed in detail. A method of compensating for building occlusions using photogrammetric geometry is developed. The data structure needed to model urban buildings for accurately generating urban orthoimages is presented. Shadow detection and removal, the optimization of seamline for automatic mosaic, and the radiometric balance of neighbor images are discussed. Street visibility analysis, including the relationship between flight height, building height, street width, and relative location of the street to the imaging center, is analyzed for complete true orthoimage generation. The experimental results demonstrated that our method can effectively and correctly orthorectify the displacements caused by terrain and buildings in urban large-scale aerial images. ?? 2005 IEEE.

Scene-based nonuniformity correction with video sequences and registration.

PubMed

Hardie, R C; Hayat, M M; Armstrong, E; Yasuda, B

2000-03-10

We describe a new, to our knowledge, scene-based nonuniformity correction algorithm for array detectors. The algorithm relies on the ability to register a sequence of observed frames in the presence of the fixed-pattern noise caused by pixel-to-pixel nonuniformity. In low-to-moderate levels of nonuniformity, sufficiently accurate registration may be possible with standard scene-based registration techniques. If the registration is accurate, and motion exists between the frames, then groups of independent detectors can be identified that observe the same irradiance (or true scene value). These detector outputs are averaged to generate estimates of the true scene values. With these scene estimates, and the corresponding observed values through a given detector, a curve-fitting procedure is used to estimate the individual detector response parameters. These can then be used to correct for detector nonuniformity. The strength of the algorithm lies in its simplicity and low computational complexity. Experimental results, to illustrate the performance of the algorithm, include the use of visible-range imagery with simulated nonuniformity and infrared imagery with real nonuniformity.

Spectral areas and ratios classifier algorithm for pancreatic tissue classification using optical spectroscopy

NASA Astrophysics Data System (ADS)

Chandra, Malavika; Scheiman, James; Simeone, Diane; McKenna, Barbara; Purdy, Julianne; Mycek, Mary-Ann

2010-01-01

Pancreatic adenocarcinoma is one of the leading causes of cancer death, in part because of the inability of current diagnostic methods to reliably detect early-stage disease. We present the first assessment of the diagnostic accuracy of algorithms developed for pancreatic tissue classification using data from fiber optic probe-based bimodal optical spectroscopy, a real-time approach that would be compatible with minimally invasive diagnostic procedures for early cancer detection in the pancreas. A total of 96 fluorescence and 96 reflectance spectra are considered from 50 freshly excised tissue sites-including human pancreatic adenocarcinoma, chronic pancreatitis (inflammation), and normal tissues-on nine patients. Classification algorithms using linear discriminant analysis are developed to distinguish among tissues, and leave-one-out cross-validation is employed to assess the classifiers' performance. The spectral areas and ratios classifier (SpARC) algorithm employs a combination of reflectance and fluorescence data and has the best performance, with sensitivity, specificity, negative predictive value, and positive predictive value for correctly identifying adenocarcinoma being 85, 89, 92, and 80%, respectively.

Segmentation of bone and soft tissue regions in digital radiographic images of extremities

NASA Astrophysics Data System (ADS)

Pakin, S. Kubilay; Gaborski, Roger S.; Barski, Lori L.; Foos, David H.; Parker, Kevin J.

2001-07-01

This paper presents an algorithm for segmentation of computed radiography (CR) images of extremities into bone and soft tissue regions. The algorithm is a region-based one in which the regions are constructed using a growing procedure with two different statistical tests. Following the growing process, tissue classification procedure is employed. The purpose of the classification is to label each region as either bone or soft tissue. This binary classification goal is achieved by using a voting procedure that consists of clustering of regions in each neighborhood system into two classes. The voting procedure provides a crucial compromise between local and global analysis of the image, which is necessary due to strong exposure variations seen on the imaging plate. Also, the existence of regions whose size is large enough such that exposure variations can be observed through them makes it necessary to use overlapping blocks during the classification. After the classification step, resulting bone and soft tissue regions are refined by fitting a 2nd order surface to each tissue, and reevaluating the label of each region according to the distance between the region and surfaces. The performance of the algorithm is tested on a variety of extremity images using manually segmented images as gold standard. The experiments showed that our algorithm provided a bone boundary with an average area overlap of 90% compared to the gold standard.

New Method of Calibrating IRT Models.

ERIC Educational Resources Information Center

Jiang, Hai; Tang, K. Linda

This discussion of new methods for calibrating item response theory (IRT) models looks into new optimization procedures, such as the Genetic Algorithm (GA) to improve on the use of the Newton-Raphson procedure. The advantages of using a global optimization procedure like GA is that this kind of procedure is not easily affected by local optima and…

A Constrained Genetic Algorithm with Adaptively Defined Fitness Function in MRS Quantification

NASA Astrophysics Data System (ADS)

Papakostas, G. A.; Karras, D. A.; Mertzios, B. G.; Graveron-Demilly, D.; van Ormondt, D.

MRS Signal quantification is a rather involved procedure and has attracted the interest of the medical engineering community, regarding the development of computationally efficient methodologies. Significant contributions based on Computational Intelligence tools, such as Neural Networks (NNs), demonstrated a good performance but not without drawbacks already discussed by the authors. On the other hand preliminary application of Genetic Algorithms (GA) has already been reported in the literature by the authors regarding the peak detection problem encountered in MRS quantification using the Voigt line shape model. This paper investigates a novel constrained genetic algorithm involving a generic and adaptively defined fitness function which extends the simple genetic algorithm methodology in case of noisy signals. The applicability of this new algorithm is scrutinized through experimentation in artificial MRS signals interleaved with noise, regarding its signal fitting capabilities. Although extensive experiments with real world MRS signals are necessary, the herein shown performance illustrates the method's potential to be established as a generic MRS metabolites quantification procedure.

Eosinophilic pustular folliculitis: A proposal of diagnostic and therapeutic algorithms.

PubMed

Nomura, Takashi; Katoh, Mayumi; Yamamoto, Yosuke; Miyachi, Yoshiki; Kabashima, Kenji

2016-11-01

Eosinophilic pustular folliculitis (EPF) is a sterile inflammatory dermatosis of unknown etiology. In addition to classic EPF, which affects otherwise healthy individuals, an immunocompromised state can cause immunosuppression-associated EPF (IS-EPF), which may be referred to dermatologists in inpatient services for assessments. Infancy-associated EPF (I-EPF) is the least characterized subtype, being observed mainly in non-Japanese infants. Diagnosis of EPF is challenging because its lesions mimic those of other common diseases, such as acne and dermatomycosis. Furthermore, there is no consensus regarding the treatment for each subtype of EPF. Here, we created procedure algorithms that facilitate the diagnosis and selection of therapeutic options on the basis of published work available in the public domain. Our diagnostic algorithm comprised a simple flowchart to direct physicians toward proper diagnosis. Recommended regimens were summarized in an easy-to-comprehend therapeutic algorithm for each subtype of EPF. These algorithms would facilitate the diagnostic and therapeutic procedure of EPF. © 2016 Japanese Dermatological Association.

An efficient parallel-processing method for transposing large matrices in place.

PubMed

Portnoff, M R

1999-01-01

We have developed an efficient algorithm for transposing large matrices in place. The algorithm is efficient because data are accessed either sequentially in blocks or randomly within blocks small enough to fit in cache, and because the same indexing calculations are shared among identical procedures operating on independent subsets of the data. This inherent parallelism makes the method well suited for a multiprocessor computing environment. The algorithm is easy to implement because the same two procedures are applied to the data in various groupings to carry out the complete transpose operation. Using only a single processor, we have demonstrated nearly an order of magnitude increase in speed over the previously published algorithm by Gate and Twigg for transposing a large rectangular matrix in place. With multiple processors operating in parallel, the processing speed increases almost linearly with the number of processors. A simplified version of the algorithm for square matrices is presented as well as an extension for matrices large enough to require virtual memory.

Heuristic algorithms for the minmax regret flow-shop problem with interval processing times.

PubMed

Ćwik, Michał; Józefczyk, Jerzy

2018-01-01

An uncertain version of the permutation flow-shop with unlimited buffers and the makespan as a criterion is considered. The investigated parametric uncertainty is represented by given interval-valued processing times. The maximum regret is used for the evaluation of uncertainty. Consequently, the minmax regret discrete optimization problem is solved. Due to its high complexity, two relaxations are applied to simplify the optimization procedure. First of all, a greedy procedure is used for calculating the criterion's value, as such calculation is NP-hard problem itself. Moreover, the lower bound is used instead of solving the internal deterministic flow-shop. The constructive heuristic algorithm is applied for the relaxed optimization problem. The algorithm is compared with previously elaborated other heuristic algorithms basing on the evolutionary and the middle interval approaches. The conducted computational experiments showed the advantage of the constructive heuristic algorithm with regards to both the criterion and the time of computations. The Wilcoxon paired-rank statistical test confirmed this conclusion.

Post-processing procedure for industrial quantum key distribution systems

NASA Astrophysics Data System (ADS)

Kiktenko, Evgeny; Trushechkin, Anton; Kurochkin, Yury; Fedorov, Aleksey

2016-08-01

We present algorithmic solutions aimed on post-processing procedure for industrial quantum key distribution systems with hardware sifting. The main steps of the procedure are error correction, parameter estimation, and privacy amplification. Authentication of classical public communication channel is also considered.

The chemical information ontology: provenance and disambiguation for chemical data on the biological semantic web.

PubMed

Hastings, Janna; Chepelev, Leonid; Willighagen, Egon; Adams, Nico; Steinbeck, Christoph; Dumontier, Michel

2011-01-01

Cheminformatics is the application of informatics techniques to solve chemical problems in silico. There are many areas in biology where cheminformatics plays an important role in computational research, including metabolism, proteomics, and systems biology. One critical aspect in the application of cheminformatics in these fields is the accurate exchange of data, which is increasingly accomplished through the use of ontologies. Ontologies are formal representations of objects and their properties using a logic-based ontology language. Many such ontologies are currently being developed to represent objects across all the domains of science. Ontologies enable the definition, classification, and support for querying objects in a particular domain, enabling intelligent computer applications to be built which support the work of scientists both within the domain of interest and across interrelated neighbouring domains. Modern chemical research relies on computational techniques to filter and organise data to maximise research productivity. The objects which are manipulated in these algorithms and procedures, as well as the algorithms and procedures themselves, enjoy a kind of virtual life within computers. We will call these information entities. Here, we describe our work in developing an ontology of chemical information entities, with a primary focus on data-driven research and the integration of calculated properties (descriptors) of chemical entities within a semantic web context. Our ontology distinguishes algorithmic, or procedural information from declarative, or factual information, and renders of particular importance the annotation of provenance to calculated data. The Chemical Information Ontology is being developed as an open collaborative project. More details, together with a downloadable OWL file, are available at http://code.google.com/p/semanticchemistry/ (license: CC-BY-SA).

The Chemical Information Ontology: Provenance and Disambiguation for Chemical Data on the Biological Semantic Web

PubMed Central

Hastings, Janna; Chepelev, Leonid; Willighagen, Egon; Adams, Nico; Steinbeck, Christoph; Dumontier, Michel

2011-01-01

Cheminformatics is the application of informatics techniques to solve chemical problems in silico. There are many areas in biology where cheminformatics plays an important role in computational research, including metabolism, proteomics, and systems biology. One critical aspect in the application of cheminformatics in these fields is the accurate exchange of data, which is increasingly accomplished through the use of ontologies. Ontologies are formal representations of objects and their properties using a logic-based ontology language. Many such ontologies are currently being developed to represent objects across all the domains of science. Ontologies enable the definition, classification, and support for querying objects in a particular domain, enabling intelligent computer applications to be built which support the work of scientists both within the domain of interest and across interrelated neighbouring domains. Modern chemical research relies on computational techniques to filter and organise data to maximise research productivity. The objects which are manipulated in these algorithms and procedures, as well as the algorithms and procedures themselves, enjoy a kind of virtual life within computers. We will call these information entities. Here, we describe our work in developing an ontology of chemical information entities, with a primary focus on data-driven research and the integration of calculated properties (descriptors) of chemical entities within a semantic web context. Our ontology distinguishes algorithmic, or procedural information from declarative, or factual information, and renders of particular importance the annotation of provenance to calculated data. The Chemical Information Ontology is being developed as an open collaborative project. More details, together with a downloadable OWL file, are available at http://code.google.com/p/semanticchemistry/ (license: CC-BY-SA). PMID:21991315

Optimizing research in symptomatic uterine fibroids with development of a computable phenotype for use with electronic health records.

PubMed

Hoffman, Sarah R; Vines, Anissa I; Halladay, Jacqueline R; Pfaff, Emily; Schiff, Lauren; Westreich, Daniel; Sundaresan, Aditi; Johnson, La-Shell; Nicholson, Wanda K

2018-06-01

Women with symptomatic uterine fibroids can report a myriad of symptoms, including pain, bleeding, infertility, and psychosocial sequelae. Optimizing fibroid research requires the ability to enroll populations of women with image-confirmed symptomatic uterine fibroids. Our objective was to develop an electronic health record-based algorithm to identify women with symptomatic uterine fibroids for a comparative effectiveness study of medical or surgical treatments on quality-of-life measures. Using an iterative process and text-mining techniques, an effective computable phenotype algorithm, composed of demographics, and clinical and laboratory characteristics, was developed with reasonable performance. Such algorithms provide a feasible, efficient way to identify populations of women with symptomatic uterine fibroids for the conduct of large traditional or pragmatic trials and observational comparative effectiveness studies. Symptomatic uterine fibroids, due to menorrhagia, pelvic pain, bulk symptoms, or infertility, are a source of substantial morbidity for reproductive-age women. Comparing Treatment Options for Uterine Fibroids is a multisite registry study to compare the effectiveness of hormonal or surgical fibroid treatments on women's perceptions of their quality of life. Electronic health record-based algorithms are able to identify large numbers of women with fibroids, but additional work is needed to develop electronic health record algorithms that can identify women with symptomatic fibroids to optimize fibroid research. We sought to develop an efficient electronic health record-based algorithm that can identify women with symptomatic uterine fibroids in a large health care system for recruitment into large-scale observational and interventional research in fibroid management. We developed and assessed the accuracy of 3 algorithms to identify patients with symptomatic fibroids using an iterative approach. The data source was the Carolina Data Warehouse for Health, a repository for the health system's electronic health record data. In addition to International Classification of Diseases, Ninth Revision diagnosis and procedure codes and clinical characteristics, text data-mining software was used to derive information from imaging reports to confirm the presence of uterine fibroids. Results of each algorithm were compared with expert manual review to calculate the positive predictive values for each algorithm. Algorithm 1 was composed of the following criteria: (1) age 18-54 years; (2) either ≥1 International Classification of Diseases, Ninth Revision diagnosis codes for uterine fibroids or mention of fibroids using text-mined key words in imaging records or documents; and (3) no International Classification of Diseases, Ninth Revision or Current Procedural Terminology codes for hysterectomy and no reported history of hysterectomy. The positive predictive value was 47% (95% confidence interval 39-56%). Algorithm 2 required ≥2 International Classification of Diseases, Ninth Revision diagnosis codes for fibroids and positive text-mined key words and had a positive predictive value of 65% (95% confidence interval 50-79%). In algorithm 3, further refinements included ≥2 International Classification of Diseases, Ninth Revision diagnosis codes for fibroids on separate outpatient visit dates, the exclusion of women who had a positive pregnancy test within 3 months of their fibroid-related visit, and exclusion of incidentally detected fibroids during prenatal or emergency department visits. Algorithm 3 achieved a positive predictive value of 76% (95% confidence interval 71-81%). An electronic health record-based algorithm is capable of identifying cases of symptomatic uterine fibroids with moderate positive predictive value and may be an efficient approach for large-scale study recruitment. Copyright © 2018 Elsevier Inc. All rights reserved.

Time-aware service-classified spectrum defragmentation algorithm for flex-grid optical networks

NASA Astrophysics Data System (ADS)

Qiu, Yang; Xu, Jing

2018-01-01

By employing sophisticated routing and spectrum assignment (RSA) algorithms together with a finer spectrum granularity (namely frequency slot) in resource allocation procedures, flex-grid optical networks can accommodate diverse kinds of services with high spectrum-allocation flexibility and resource-utilization efficiency. However, the continuity and the contiguity constraints in spectrum allocation procedures may always induce some isolated, small-sized, and unoccupied spectral blocks (known as spectrum fragments) in flex-grid optical networks. Although these spectrum fragments are left unoccupied, they can hardly be utilized by the subsequent service requests directly because of their spectral characteristics and the constraints in spectrum allocation. In this way, the existence of spectrum fragments may exhaust the available spectrum resources for a coming service request and thus worsens the networking performance. Therefore, many reactive defragmentation algorithms have been proposed to handle the fragmented spectrum resources via re-optimizing the routing paths and the spectrum resources for the existing services. But the routing-path and the spectrum-resource re-optimization in reactive defragmentation algorithms may possibly disrupt the traffic of the existing services and require extra components. By comparison, some proactive defragmentation algorithms (e.g. fragmentation-aware algorithms) were proposed to suppress spectrum fragments from their generation instead of handling the fragmented spectrum resources. Although these proactive defragmentation algorithms induced no traffic disruption and required no extra components, they always left the generated spectrum fragments unhandled, which greatly affected their efficiency in spectrum defragmentation. In this paper, by comprehensively considering the characteristics of both the reactive and the proactive defragmentation algorithms, we proposed a time-aware service-classified (TASC) spectrum defragmentation algorithm, which simultaneously employed proactive and reactive mechanisms in suppressing spectrum fragments with the awareness of services' types and their duration times. By dividing the spectrum resources into several flexible groups according to services' types and limiting both the spectrum allocation and the spectrum re-tuning for a certain service inside one specific spectrum group according to its type, the proposed TASC defragmentation algorithm cannot only suppress spectrum fragments from generation inside each spectrum group, but also handle the fragments generated between two adjacent groups. In this way, the proposed TASC algorithm gains higher efficiency in suppressing spectrum fragments than both the reactive and the proactive defragmentation algorithms. Additionally, as the generation of spectrum fragments is retrained between spectrum groups and the defragmentation procedure is limited inside each spectrum group, the induced traffic disruption for the existing services can be possibly reduced. Besides, the proposed TASC defragmentation algorithm always re-tunes the spectrum resources of the service with the maximum duration time first in spectrum defragmentation procedure, which can further reduce spectrum fragments because of the fact that the services with longer duration times always have higher possibility in inducing spectrum fragments than the services with shorter duration times. The simulation results show that the proposed TASC defragmentation algorithm can significantly reduce the number of the generated spectrum fragments while improving the service blocking performance.

Further investigation on "A multiplicative regularization for force reconstruction"

NASA Astrophysics Data System (ADS)

Aucejo, M.; De Smet, O.

2018-05-01

We have recently proposed a multiplicative regularization to reconstruct mechanical forces acting on a structure from vibration measurements. This method does not require any selection procedure for choosing the regularization parameter, since the amount of regularization is automatically adjusted throughout an iterative resolution process. The proposed iterative algorithm has been developed with performance and efficiency in mind, but it is actually a simplified version of a full iterative procedure not described in the original paper. The present paper aims at introducing the full resolution algorithm and comparing it with its simplified version in terms of computational efficiency and solution accuracy. In particular, it is shown that both algorithms lead to very similar identified solutions.

Finite element concepts in computational aerodynamics

NASA Technical Reports Server (NTRS)

Baker, A. J.

1978-01-01

Finite element theory was employed to establish an implicit numerical solution algorithm for the time averaged unsteady Navier-Stokes equations. Both the multidimensional and a time-split form of the algorithm were considered, the latter of particular interest for problem specification on a regular mesh. A Newton matrix iteration procedure is outlined for solving the resultant nonlinear algebraic equation systems. Multidimensional discretization procedures are discussed with emphasis on automated generation of specific nonuniform solution grids and accounting of curved surfaces. The time-split algorithm was evaluated with regards to accuracy and convergence properties for hyperbolic equations on rectangular coordinates. An overall assessment of the viability of the finite element concept for computational aerodynamics is made.

Standardized Radiation Shield Design Methods: 2005 HZETRN

NASA Technical Reports Server (NTRS)

Wilson, John W.; Tripathi, Ram K.; Badavi, Francis F.; Cucinotta, Francis A.

2006-01-01

Research committed by the Langley Research Center through 1995 resulting in the HZETRN code provides the current basis for shield design methods according to NASA STD-3000 (2005). With this new prominence, the database, basic numerical procedures, and algorithms are being re-examined with new methods of verification and validation being implemented to capture a well defined algorithm for engineering design processes to be used in this early development phase of the Bush initiative. This process provides the methodology to transform the 1995 HZETRN research code into the 2005 HZETRN engineering code to be available for these early design processes. In this paper, we will review the basic derivations including new corrections to the codes to insure improved numerical stability and provide benchmarks for code verification.

Parallel Clustering Algorithm for Large-Scale Biological Data Sets

PubMed Central

Wang, Minchao; Zhang, Wu; Ding, Wang; Dai, Dongbo; Zhang, Huiran; Xie, Hao; Chen, Luonan; Guo, Yike; Xie, Jiang

2014-01-01

Backgrounds Recent explosion of biological data brings a great challenge for the traditional clustering algorithms. With increasing scale of data sets, much larger memory and longer runtime are required for the cluster identification problems. The affinity propagation algorithm outperforms many other classical clustering algorithms and is widely applied into the biological researches. However, the time and space complexity become a great bottleneck when handling the large-scale data sets. Moreover, the similarity matrix, whose constructing procedure takes long runtime, is required before running the affinity propagation algorithm, since the algorithm clusters data sets based on the similarities between data pairs. Methods Two types of parallel architectures are proposed in this paper to accelerate the similarity matrix constructing procedure and the affinity propagation algorithm. The memory-shared architecture is used to construct the similarity matrix, and the distributed system is taken for the affinity propagation algorithm, because of its large memory size and great computing capacity. An appropriate way of data partition and reduction is designed in our method, in order to minimize the global communication cost among processes. Result A speedup of 100 is gained with 128 cores. The runtime is reduced from serval hours to a few seconds, which indicates that parallel algorithm is capable of handling large-scale data sets effectively. The parallel affinity propagation also achieves a good performance when clustering large-scale gene data (microarray) and detecting families in large protein superfamilies. PMID:24705246

Proceedings of the Conference of the International Group for the Psychology of Mathematics Education (PME 20) (20th, Valencia, Spain, July 8-12, 1996). Volume 2.

ERIC Educational Resources Information Center

Puig, Luis, Ed.; Gutierrez, Angel, Ed.

The second volume of this proceedings contains full research articles. Papers include: (1) "Lave and Wenger's social practice theory and teaching and learning school mathematics" (J. Adler); (2) "Being a researcher and being a teacher" (J. Ainley); (3) "Procedural and conceptual aspects of standard algorithms in calculus" (M.B. Ali and D. Tall);…

Hypersonic, nonequilibrium flow over the FIRE 2 forebody at 1634 sec

NASA Technical Reports Server (NTRS)

Chambers, Lin Hartung

1994-01-01

The numerical simulation of hypersonic flow in thermochemical nonequilibrium over the forebody of the FIRE 2 vehicle at 1634 sec in its trajectory is described. The simulation was executed on a Cray C90 with the program Langley Aerodynamic Upwind Relaxation Algorithm (LAURA) 4.0.2. Code setup procedures and sample results, including grid refinement studies, are discussed. This simulation relates to a study of radiative heating predictions on aerobrake type vehicles.

Comparing 15D Valuation Studies in Norway and Finland-Challenges When Combining Information from Several Valuation Tasks.

PubMed

Michel, Yvonne Anne; Augestad, Liv Ariane; Rand, Kim

2018-04-01

The 15D is a generic preference-based health-related quality-of-life instrument developed in Finland. Values for the 15D instrument are estimated by combining responses to three distinct valuation tasks. The impact of how these tasks are combined is relatively unexplored. To compare 15D valuation studies conducted in Norway and Finland in terms of scores assigned in the valuation tasks and resulting value algorithms, and to discuss the contributions of each task and the algorithm estimation procedure to observed differences. Norwegian and Finnish scores from the three valuation tasks were compared using independent samples t tests and Lin concordance correlation coefficients. Covariance between tasks was assessed using Pearson product-moment correlations. Norwegian and Finnish value algorithms were compared using concordance correlation coefficients, total ranges, and ranges for individual dimensions. Observed differences were assessed using minimal important difference. Mean scores in the main valuation task were strikingly similar between the two countries, whereas the final value algorithms were less similar. The largest differences between Norway and Finland were observed for depression, vision, and mental function. 15D algorithms are a product of combining scores from three valuation tasks by use of methods involving multiplication. This procedure used to combine scores from the three tasks by multiplication serves to amplify variance from each task. From relatively similar responses in Norway and Finland, diverging value algorithms are created. We propose to simplify the 15D algorithm estimation procedure by using only one of the valuation tasks. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

The Local Minima Problem in Hierarchical Classes Analysis: An Evaluation of a Simulated Annealing Algorithm and Various Multistart Procedures

ERIC Educational Resources Information Center

Ceulemans, Eva; Van Mechelen, Iven; Leenen, Iwin

2007-01-01

Hierarchical classes models are quasi-order retaining Boolean decomposition models for N-way N-mode binary data. To fit these models to data, rationally started alternating least squares (or, equivalently, alternating least absolute deviations) algorithms have been proposed. Extensive simulation studies showed that these algorithms succeed quite…

Teaching Computation in Primary School without Traditional Written Algorithms

ERIC Educational Resources Information Center

Hartnett, Judy

2015-01-01

Concerns regarding the dominance of the traditional written algorithms in schools have been raised by many mathematics educators, yet the teaching of these procedures remains a dominant focus in in primary schools. This paper reports on a project in one school where the staff agreed to put the teaching of the traditional written algorithm aside,…

A novel washing algorithm for underarm stain removal

NASA Astrophysics Data System (ADS)

Acikgoz Tufan, H.; Gocek, I.; Sahin, U. K.; Erdem, I.

2017-10-01

After contacting with human sweat which comprise around 27% sebum, anti-perspirants comprising aluminium chloride or its compounds form a jel-like structure whose solubility in water is very poor. In daily use, this jel-like structure closes sweat pores and hinders wetting of skin by sweat. However, when in contact with garments, they form yellowish stains at the underarm of the garments. These stains are very hard to remove with regular machine washing. In this study, first of all, we focused on understanding and simulating such stain formation on the garments. Two alternative procedures are offered to form jel-like structures. On both procedures, commercially available spray or deo-stick type anti-perspirants, standard acidic and basic sweat solutions and artificial sebum are used to form jel-like structures, and they are applied on fabric in order to get hard stains. Secondly, after simulation of the stain on the fabric, we put our efforts on developing a washing algorithm specifically designed for removal of underarm stains. Eight alternative washing algorithms are offered with varying washing temperature, amounts of detergent, and pre-stain removal procedures. Better algorithm is selected by comparison of Tristimulus Y values after washing.

Onboard Determination of Vehicle Glide Capability for Shuttle Abort Flight Managment (SAFM)

NASA Technical Reports Server (NTRS)

Straube, Timothy; Jackson, Mark; Fill, Thomas; Nemeth, Scott

2002-01-01

When one or more main engines fail during ascent, the flight crew of the Space Shuttle must make several critical decisions and accurately perform a series of abort procedures. One of the most important decisions for many aborts is the selection ofa landing site. Several factors influence the ability to reach a landing site, including the spacecraft point of atmospheric entry, the energy state at atmospheric entry, the vehicle glide capability from that energy state, and whether one or more suitable landing sites are within the glide capability. Energy assessment is further complicated by the fact that phugoid oscillations in total energy influence glide capability. Once the glide capability is known, the crew must select the "best" site option based upon glide capability and landing site conditions and facilities. Since most of these factors cannot currently be assessed by the crew in flight, extensive planning is required prior to each mission to script a variety of procedures based upon spacecraft velocity at the point of engine failure (or failures). The results of this preflight planning are expressed in tables and diagrams on mission-specific cockpit checklists. Crew checklist procedures involve leafing through several pages of instructions and navigating a decision tree for site selection and flight procedures - all during a time critical abort situation. With the advent of the Cockpit Avionics Upgrade (CAU), the Shuttle will have increased on-board computational power to help alleviate crew workload during aborts and provide valuable situational awareness during nominal operations. One application baselined for the CAU computers is Shuttle Abort Flight Management (SAFM), whose requirements have been designed and prototyped. The SAFM application includes powered and glided flight algorithms. This paper describes the glided flight algorithm which is dispatched by SAFM to determine the vehicle glide capability and make recommendations to the crew for site selection as well as to monitor glide capability while in route to the selected site. Background is provided on Shuttle entry guidance as well as the various types of Shuttle aborts. SAFM entry requirements and cockpit disp lays are discussed briefly to provide background for Glided Flight algorithm design considerations. The central principal of the Glided Flight algorithm is the use of energy-over-weight (EOW) curves to determine range and crossrange boundaries. The major challenges of this technique are exo-atmospheric flight, and phugoid oscillations in energy. During exo-atmospheric flight, energy is constant, so vehicle EOW is not sufficient to determine glide capability. The paper describes how the exo-atmospheric problem is solved by propagating the vehicle state to an "atmospheric pullout" state defined by Shuttle guidance parameters.

Improved epileptic seizure detection combining dynamic feature normalization with EEG novelty detection.

PubMed

Bogaarts, J G; Hilkman, D M W; Gommer, E D; van Kranen-Mastenbroek, V H J M; Reulen, J P H

2016-12-01

Continuous electroencephalographic monitoring of critically ill patients is an established procedure in intensive care units. Seizure detection algorithms, such as support vector machines (SVM), play a prominent role in this procedure. To correct for inter-human differences in EEG characteristics, as well as for intra-human EEG variability over time, dynamic EEG feature normalization is essential. Recently, the median decaying memory (MDM) approach was determined to be the best method of normalization. MDM uses a sliding baseline buffer of EEG epochs to calculate feature normalization constants. However, while this method does include non-seizure EEG epochs, it also includes EEG activity that can have a detrimental effect on the normalization and subsequent seizure detection performance. In this study, EEG data that is to be incorporated into the baseline buffer are automatically selected based on a novelty detection algorithm (Novelty-MDM). Performance of an SVM-based seizure detection framework is evaluated in 17 long-term ICU registrations using the area under the sensitivity-specificity ROC curve. This evaluation compares three different EEG normalization methods, namely a fixed baseline buffer (FB), the median decaying memory (MDM) approach, and our novelty median decaying memory (Novelty-MDM) method. It is demonstrated that MDM did not improve overall performance compared to FB (p < 0.27), partly because seizure like episodes were included in the baseline. More importantly, Novelty-MDM significantly outperforms both FB (p = 0.015) and MDM (p = 0.0065).

Toward dynamic lumbar punctures guidance based on single element synthetic tracked aperture ultrasound imaging

NASA Astrophysics Data System (ADS)

Zhang, Haichong K.; Lin, Melissa; Kim, Younsu; Paredes, Mateo; Kannan, Karun; Patel, Nisu; Moghekar, Abhay; Durr, Nicholas J.; Boctor, Emad M.

2017-03-01

Lumbar punctures (LPs) are interventional procedures used to collect cerebrospinal fluid (CSF), a bodily fluid needed to diagnose central nervous system disorders. Most lumbar punctures are performed blindly without imaging guidance. Because the target window is small, physicians can only accurately palpate the appropriate space about 30% of the time and perform a successful procedure after an average of three attempts. Although various forms of imaging based guidance systems have been developed to aid in this procedure, these systems complicate the procedure by including independent image modalities and requiring image-to-needle registration to guide the needle insertion. Here, we propose a simple and direct needle insertion platform utilizing a single ultrasound element within the needle through dynamic sensing and imaging. The needle-shaped ultrasound transducer can not only sense the distance between the tip and a potential obstacle such as bone, but also visually locate structures by combining transducer location tracking and back projection based tracked synthetic aperture beam-forming algorithm. The concept of the system was validated through simulation first, which revealed the tolerance to realistic error. Then, the initial prototype of the single element transducer was built into a 14G needle, and was mounted on a holster equipped with a rotation tracking encoder. We experimentally evaluated the system using a metal wire phantom mimicking high reflection bone structures and an actual spine bone phantom with both the controlled motion and freehand scanning. An ultrasound image corresponding to the model phantom structure was reconstructed using the beam-forming algorithm, and the resolution was improved compared to without beam-forming. These results demonstrated the proposed system has the potential to be used as an ultrasound imaging system for lumbar puncture procedures.

Detection of Unknown LEO Satellite Using Radar Measurements

NASA Astrophysics Data System (ADS)

Kamensky, S.; Samotokhin, A.; Khutorovsky, Z.; Alfriend, T.

While processing of the radar information aimed at satellite catalog maintenance some measurements do not correlate with cataloged and tracked satellites. These non-correlated measurements participate in the detection (primary orbit determination) of new (not cataloged) satellites. The satellite is considered newly detected when it is missing in the catalog and the primary orbit determination on the basis of the non-correlated measurements provides the accuracy sufficient for reliable correlation of future measurements. We will call this the detection condition. One non-correlated measurement in real conditions does not have enough accuracy and thus does not satisfy the detection condition. Two measurements separated by a revolution or more normally provides orbit determination with accuracy sufficient for selection of other measurements. However, it is not always possible to say with high probability (close to 1) that two measurements belong to one satellite. Three measurements for different revolutions, which are included into one orbit, have significantly higher chances to belong to one satellite. Thus the suggested detection (primary orbit determination) algorithm looks for three uncorrelated measurements in different revolutions for which we can determine the orbit inscribing them. The detection procedure based on search for the triplets is rather laborious. Thus only relatively high efficiency can be the reason for its practical implementation. The work presents the detailed description of the suggested detection procedure based on the search for triplets of uncorrelated measurements (for radar measurements). The break-ups of the tracked satellites provide the most difficult conditions for the operation of the detection algorithm and reveal explicitly its characteristics. The characteristics of time efficiency and reliability of the detected orbits are of maximum interest. Within this work we suggest to determine these characteristics using simulation of break-ups with further acquisition of measurements generated by the fragments. In particular, using simulation we can not only evaluate the characteristics of the algorithm but adjust its parameters for certain conditions: the orbit of the fragmented satellite, the features of the break-up, capabilities of detection radars etc. We describe the algorithm performing the simulation of radar measurements produced by the fragments of the parent satellite. This algorithm accounts of the basic factors affecting the characteristics of time efficiency and reliability of the detection. The catalog maintenance algorithm includes two major components detection and tracking. These are two processes permanently interacting with each other. This is actually in place for the processing of real radar data. The simulation must take this into account since one cannot obtain reliable characteristics of detection procedure simulating only this process. Thus we simulated both processes in their interaction. The work presents the results of simulation for the simplest case of a break-up in near-circular orbit with insignificant atmospheric drag. The simulations show rather high efficiency. We demonstrate as well that the characteristics of time efficiency and reliability of determined orbits essentially depend on the density of the observed break-up fragments.

Development of traffic control and queue management procedures for oversaturated arterials

DOT National Transportation Integrated Search

1997-01-01

The formulation and solution of a new algorithm for queue management and coordination of traffic signals along oversaturated arterials are presented. Existing traffic-control and signal-coordination algorithms deal only with undersaturated steady-sta...

An Efficient and Accurate Genetic Algorithm for Backcalculation of Flexible Pavement Layer Moduli

DOT National Transportation Integrated Search

2012-12-01

The importance of a backcalculation method in the analysis of elastic modulus in pavement engineering has been : known for decades. Despite many backcalculation programs employing different backcalculation procedures and : algorithms, accurate invers...

Uncovering the community structure in signed social networks based on greedy optimization

NASA Astrophysics Data System (ADS)

Chen, Yan; Yan, Jiaqi; Yang, Yu; Chen, Junhua

2017-05-01

The formality of signed relationships has been recently adopted in a lot of complicated systems. The relations among these entities are complicated and multifarious. We cannot indicate these relationships only by positive links, and signed networks have been becoming more and more universal in the study of social networks when community is being significant. In this paper, to identify communities in signed networks, we exploit a new greedy algorithm, taking signs and the density of these links into account. The main idea of the algorithm is the initial procedure of signed modularity and the corresponding update rules. Specially, we employ the “Asymmetric and Constrained Belief Evolution” procedure to evaluate the optimal number of communities. According to the experimental results, the algorithm is proved to be able to run well. More specifically, the proposed algorithm is very efficient for these networks with medium size, both dense and sparse.

Representing Operations Procedures Using Temporal Dependency Algorithms

NASA Technical Reports Server (NTRS)

Fayyad, K.; Cooper, L.

1992-01-01

The research presented in this paper is investigating new ways of specifying operations procedures that incorporate the insight of operations, engineering, and science personnel to improve mission operations. The paper describes the rationale for using Temporal Dependency Networks to represent the procedures, a description of how the data is acquired, and the knowledge engineering effort required to represent operations procedures.

Algorithm for Automatic Segmentation of Nuclear Boundaries in Cancer Cells in Three-Channel Luminescent Images

NASA Astrophysics Data System (ADS)

Lisitsa, Y. V.; Yatskou, M. M.; Apanasovich, V. V.; Apanasovich, T. V.

2015-09-01

We have developed an algorithm for segmentation of cancer cell nuclei in three-channel luminescent images of microbiological specimens. The algorithm is based on using a correlation between fluorescence signals in the detection channels for object segmentation, which permits complete automation of the data analysis procedure. We have carried out a comparative analysis of the proposed method and conventional algorithms implemented in the CellProfiler and ImageJ software packages. Our algorithm has an object localization uncertainty which is 2-3 times smaller than for the conventional algorithms, with comparable segmentation accuracy.

Output-only modal dynamic identification of frames by a refined FDD algorithm at seismic input and high damping

NASA Astrophysics Data System (ADS)

Pioldi, Fabio; Ferrari, Rosalba; Rizzi, Egidio

2016-02-01

The present paper deals with the seismic modal dynamic identification of frame structures by a refined Frequency Domain Decomposition (rFDD) algorithm, autonomously formulated and implemented within MATLAB. First, the output-only identification technique is outlined analytically and then employed to characterize all modal properties. Synthetic response signals generated prior to the dynamic identification are adopted as input channels, in view of assessing a necessary condition for the procedure's efficiency. Initially, the algorithm is verified on canonical input from random excitation. Then, modal identification has been attempted successfully at given seismic input, taken as base excitation, including both strong motion data and single and multiple input ground motions. Rather than different attempts investigating the role of seismic response signals in the Time Domain, this paper considers the identification analysis in the Frequency Domain. Results turn-out very much consistent with the target values, with quite limited errors in the modal estimates, including for the damping ratios, ranging from values in the order of 1% to 10%. Either seismic excitation and high values of damping, resulting critical also in case of well-spaced modes, shall not fulfill traditional FFD assumptions: this shows the consistency of the developed algorithm. Through original strategies and arrangements, the paper shows that a comprehensive rFDD modal dynamic identification of frames at seismic input is feasible, also at concomitant high damping.

Programming Deep Brain Stimulation for Tremor and Dystonia: The Toronto Western Hospital Algorithms.

PubMed

Picillo, Marina; Lozano, Andres M; Kou, Nancy; Munhoz, Renato Puppi; Fasano, Alfonso

2016-01-01

Deep brain stimulation (DBS) is an effective treatment for essential tremor (ET) and dystonia. After surgery, a number of extensive programming sessions are performed, mainly relying on neurologist's personal experience as no programming guidelines have been provided so far, with the exception of recommendations provided by groups of experts. Finally, fewer information is available for the management of DBS in ET and dystonia compared with Parkinson's disease. Our aim is to review the literature on initial and follow-up DBS programming procedures for ET and dystonia and integrate the results with our current practice at Toronto Western Hospital (TWH) to develop standardized DBS programming protocols. We conducted a literature search of PubMed from inception to July 2014 with the keywords "balance", "bradykinesia", "deep brain stimulation", "dysarthria", "dystonia", "gait disturbances", "initial programming", "loss of benefit", "micrographia", "speech", "speech difficulties" and "tremor". Seventy-six papers were considered for this review. Based on the literature review and our experience at TWH, we refined three algorithms for management of ET, including: (1) initial programming, (2) management of balance and speech issues and (3) loss of stimulation benefit. We also depicted algorithms for the management of dystonia, including: (1) initial programming and (2) management of stimulation-induced hypokinesia (shuffling gait, micrographia and speech impairment). We propose five algorithms tailored to an individualized approach to managing ET and dystonia patients with DBS. We encourage the application of these algorithms to supplement current standards of care in established as well as new DBS centers to test the clinical usefulness of these algorithms in supplementing the current standards of care. Copyright © 2016 Elsevier Inc. All rights reserved.

Solution of quadratic matrix equations for free vibration analysis of structures.

NASA Technical Reports Server (NTRS)

Gupta, K. K.

1973-01-01

An efficient digital computer procedure and the related numerical algorithm are presented herein for the solution of quadratic matrix equations associated with free vibration analysis of structures. Such a procedure enables accurate and economical analysis of natural frequencies and associated modes of discretized structures. The numerically stable algorithm is based on the Sturm sequence method, which fully exploits the banded form of associated stiffness and mass matrices. The related computer program written in FORTRAN V for the JPL UNIVAC 1108 computer proves to be substantially more accurate and economical than other existing procedures of such analysis. Numerical examples are presented for two structures - a cantilever beam and a semicircular arch.

CDRD and PNPR passive microwave precipitation retrieval algorithms: verification study over Africa and Southern Atlantic

NASA Astrophysics Data System (ADS)

Panegrossi, Giulia; Casella, Daniele; Cinzia Marra, Anna; Petracca, Marco; Sanò, Paolo; Dietrich, Stefano

2015-04-01

The ongoing NASA/JAXA Global Precipitation Measurement mission (GPM) requires the full exploitation of the complete constellation of passive microwave (PMW) radiometers orbiting around the globe for global precipitation monitoring. In this context the coherence of the estimates of precipitation using different passive microwave radiometers is a crucial need. We have developed two different passive microwave precipitation retrieval algorithms: one is the Cloud Dynamics Radiation Database algorithm (CDRD), a physically ¬based Bayesian algorithm for conically scanning radiometers (i.e., DMSP SSMIS); the other one is the Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for cross¬-track scanning radiometers (i.e., NOAA and MetOp¬A/B AMSU-¬A/MHS, and NPP Suomi ATMS). The algorithms, originally created for application over Europe and the Mediterranean basin, and used operationally within the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF, http://hsaf.meteoam.it), have been recently modified and extended to Africa and Southern Atlantic for application to the MSG full disk area. The two algorithms are based on the same physical foundation, i.e., the same cloud-radiation model simulations as a priori information in the Bayesian solver and as training dataset in the neural network approach, and they also use similar procedures for identification of frozen background surface, detection of snowfall, and determination of a pixel based quality index of the surface precipitation retrievals. In addition, similar procedures for the screening of not ¬precipitating pixels are used. A novel algorithm for the detection of precipitation in tropical/sub-tropical areas has been developed. The precipitation detection algorithm shows a small rate of false alarms (also over arid/desert regions), a superior detection capability in comparison with other widely used screening algorithms, and it is applicable to all available PMW radiometers in the GPM constellation of satellites (including NPP Suomi ATMS, and GMI). Three years of SSMIS and AMSU/MHS data have been considered to carry out a verification study over Africa of the retrievals from the CDRD and PNPR algorithms. The precipitation products from the TRMM ¬Precipitation radar (PR) (TRMM product 2A25 and 2A23) have been used as ground truth. The results of this study aimed at assessing the accuracy of the precipitation retrievals in different climatic regions and precipitation regimes will be presented. Particular emphasis will be given to the analysis of the level of coherence of the precipitation estimates and patterns between the two algorithms exploiting different radiometers. Recent developments aimed at the full exploitation of the GPM constellation of satellites for optimal precipitation/drought monitoring will be also presented.

Insights on correlation dimension from dynamics mapping of three experimental nonlinear laser systems.

PubMed

McMahon, Christopher J; Toomey, Joshua P; Kane, Deb M

2017-01-01

We have analysed large data sets consisting of tens of thousands of time series from three Type B laser systems: a semiconductor laser in a photonic integrated chip, a semiconductor laser subject to optical feedback from a long free-space-external-cavity, and a solid-state laser subject to optical injection from a master laser. The lasers can deliver either constant, periodic, pulsed, or chaotic outputs when parameters such as the injection current and the level of external perturbation are varied. The systems represent examples of experimental nonlinear systems more generally and cover a broad range of complexity including systematically varying complexity in some regions. In this work we have introduced a new procedure for semi-automatically interrogating experimental laser system output power time series to calculate the correlation dimension (CD) using the commonly adopted Grassberger-Proccacia algorithm. The new CD procedure is called the 'minimum gradient detection algorithm'. A value of minimum gradient is returned for all time series in a data set. In some cases this can be identified as a CD, with uncertainty. Applying the new 'minimum gradient detection algorithm' CD procedure, we obtained robust measurements of the correlation dimension for many of the time series measured from each laser system. By mapping the results across an extended parameter space for operation of each laser system, we were able to confidently identify regions of low CD (CD < 3) and assign these robust values for the correlation dimension. However, in all three laser systems, we were not able to measure the correlation dimension at all parts of the parameter space. Nevertheless, by mapping the staged progress of the algorithm, we were able to broadly classify the dynamical output of the lasers at all parts of their respective parameter spaces. For two of the laser systems this included displaying regions of high-complexity chaos and dynamic noise. These high-complexity regions are differentiated from regions where the time series are dominated by technical noise. This is the first time such differentiation has been achieved using a CD analysis approach. More can be known of the CD for a system when it is interrogated in a mapping context, than from calculations using isolated time series. This has been shown for three laser systems and the approach is expected to be useful in other areas of nonlinear science where large data sets are available and need to be semi-automatically analysed to provide real dimensional information about the complex dynamics. The CD/minimum gradient algorithm measure provides additional information that complements other measures of complexity and relative complexity, such as the permutation entropy; and conventional physical measurements.

Robustness of methods for blinded sample size re-estimation with overdispersed count data.

PubMed

Schneider, Simon; Schmidli, Heinz; Friede, Tim

2013-09-20

Counts of events are increasingly common as primary endpoints in randomized clinical trials. With between-patient heterogeneity leading to variances in excess of the mean (referred to as overdispersion), statistical models reflecting this heterogeneity by mixtures of Poisson distributions are frequently employed. Sample size calculation in the planning of such trials requires knowledge on the nuisance parameters, that is, the control (or overall) event rate and the overdispersion parameter. Usually, there is only little prior knowledge regarding these parameters in the design phase resulting in considerable uncertainty regarding the sample size. In this situation internal pilot studies have been found very useful and very recently several blinded procedures for sample size re-estimation have been proposed for overdispersed count data, one of which is based on an EM-algorithm. In this paper we investigate the EM-algorithm based procedure with respect to aspects of their implementation by studying the algorithm's dependence on the choice of convergence criterion and find that the procedure is sensitive to the choice of the stopping criterion in scenarios relevant to clinical practice. We also compare the EM-based procedure to other competing procedures regarding their operating characteristics such as sample size distribution and power. Furthermore, the robustness of these procedures to deviations from the model assumptions is explored. We find that some of the procedures are robust to at least moderate deviations. The results are illustrated using data from the US National Heart, Lung and Blood Institute sponsored Asymptomatic Cardiac Ischemia Pilot study. Copyright © 2013 John Wiley & Sons, Ltd.

A Polyhedral Outer-approximation, Dynamic-discretization optimization solver, 1.x

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bent, Rusell; Nagarajan, Harsha; Sundar, Kaarthik

2017-09-25

In this software, we implement an adaptive, multivariate partitioning algorithm for solving mixed-integer nonlinear programs (MINLP) to global optimality. The algorithm combines ideas that exploit the structure of convex relaxations to MINLPs and bound tightening procedures

The automatic extraction of pitch perturbation using microcomputers: some methodological considerations.

PubMed

Deem, J F; Manning, W H; Knack, J V; Matesich, J S

1989-09-01

A program for the automatic extraction of jitter (PAEJ) was developed for the clinical measurement of pitch perturbations using a microcomputer. The program currently includes 12 implementations of an algorithm for marking the boundary criteria for a fundamental period of vocal fold vibration. The relative sensitivity of these extraction procedures for identifying the pitch period was compared using sine waves. Data obtained to date provide information for each procedure concerning the effects of waveform peakedness and slope, sample duration in cycles, noise level of the analysis system with both direct and tape recorded input, and the influence of interpolation. Zero crossing extraction procedures provided lower jitter values regardless of sine wave frequency or sample duration. The procedures making use of positive- or negative-going zero crossings with interpolation provided the lowest measures of jitter with the sine wave stimuli. Pilot data obtained with normal-speaking adults indicated that jitter measures varied as a function of the speaker, vowel, and sample duration.

Simulation of time-control procedures for terminal area flow management

NASA Technical Reports Server (NTRS)

Alcabin, M.; Erzberger, H.; Tobias, L.; Obrien, P. J.

1985-01-01

Simulations of a terminal area traffic-management system incorporating automated scheduling and time-control (four-dimensional) techniques conducted at NASA Ames Research Center jointly with the Federal Aviation Administration, have shown that efficient procedures can be developed for handling a mix of 4D-equipped and conventionally equipped aircraft. A crucial role in this system is played by an ATC host computer algorithm, referred to as a speed advisory, that allows controllers to maintain accurate time schedules of the conventionally equipped aircraft in the traffic mix. Results are of the most recent simulations in which two important special cases were investigated. First, the effects of a speed advisory on touchdown time scheduling are examined, when unequipped aircraft are constrained to follow fuel-optimized profiles in the near-terminal area, and rescheduling procedures are developed to handle missed approaches of 4D-equipped aircraft. Various performance measures, including controller opinion, are used to evaluate the effectiveness of the procedures.

Air Traffic Management Technology Demostration: 1 Research and Procedural Testing of Routes

NASA Technical Reports Server (NTRS)

Wilson, Sara R.; Kibler, Jennifer L.; Hubbs, Clay E.; Smail, James W.

2015-01-01

NASA's Air Traffic Management Technology Demonstration-1 (ATD-1) will operationally demonstrate the feasibility of efficient arrival operations combining ground-based and airborne NASA technologies. The ATD-1 integrated system consists of the Traffic Management Advisor with Terminal Metering which generates precise time-based schedules to the runway and merge points; Controller Managed Spacing decision support tools which provide controllers with speed advisories and other information needed to meet the schedule; and Flight deck-based Interval Management avionics and procedures which allow flight crews to adjust their speed to achieve precise relative spacing. Initial studies identified air-ground challenges related to the integration of these three scheduling and spacing technologies, and NASA's airborne spacing algorithm was modified to address some of these challenges. The Research and Procedural Testing of Routes human-in-the-loop experiment was then conducted to assess the performance of the new spacing algorithm. The results of this experiment indicate that the algorithm performed as designed, and the pilot participants found the airborne spacing concept, air-ground procedures, and crew interface to be acceptable. However, the researchers concluded that the data revealed issues with the frequency of speed changes and speed reversals.

Noniterative accurate algorithm for the exact exchange potential of density-functional theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cinal, M.; Holas, A.

2007-10-15

An algorithm for determination of the exchange potential is constructed and tested. It represents a one-step procedure based on the equations derived by Krieger, Li, and Iafrate (KLI) [Phys. Rev. A 46, 5453 (1992)], implemented already as an iterative procedure by Kuemmel and Perdew [Phys. Rev. Lett. 90, 043004 (2003)]. Due to suitable transformation of the KLI equations, we can solve them avoiding iterations. Our algorithm is applied to the closed-shell atoms, from Be up to Kr, within the DFT exchange-only approximation. Using pseudospectral techniques for representing orbitals, we obtain extremely accurate values of total and orbital energies with errorsmore » at least four orders of magnitude smaller than known in the literature.« less

A fast bottom-up algorithm for computing the cut sets of noncoherent fault trees

DOE Office of Scientific and Technical Information (OSTI.GOV)

Corynen, G.C.

1987-11-01

An efficient procedure for finding the cut sets of large fault trees has been developed. Designed to address coherent or noncoherent systems, dependent events, shared or common-cause events, the method - called SHORTCUT - is based on a fast algorithm for transforming a noncoherent tree into a quasi-coherent tree (COHERE), and on a new algorithm for reducing cut sets (SUBSET). To assure sufficient clarity and precision, the procedure is discussed in the language of simple sets, which is also developed in this report. Although the new method has not yet been fully implemented on the computer, we report theoretical worst-casemore » estimates of its computational complexity. 12 refs., 10 figs.« less

Genetic algorithms in conceptual design of a light-weight, low-noise, tilt-rotor aircraft

NASA Technical Reports Server (NTRS)

Wells, Valana L.

1996-01-01

This report outlines research accomplishments in the area of using genetic algorithms (GA) for the design and optimization of rotorcraft. It discusses the genetic algorithm as a search and optimization tool, outlines a procedure for using the GA in the conceptual design of helicopters, and applies the GA method to the acoustic design of rotors.

Halftoning Algorithms and Systems.

DTIC Science & Technology

1996-08-01

TERMS 15. NUMBER IF PAGESi. Halftoning algorithms; error diffusions ; color printing; topographic maps 16. PRICE CODE 17. SECURITY CLASSIFICATION 18...graylevels for each screen level. In the case of error diffusion algorithms, the calibration procedure using the new centering concept manifests itself as a...Novel Centering Concept for Overlapping Correction Paper / Transparency (Patent Applied 5/94)I * Applications To Error Diffusion * To Dithering (IS&T

75 FR 81704 - Self-Regulatory Organizations; Chicago Board Options Exchange, Incorporated; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-28

... algorithm \\5\\ for HOSS and to make related changes to Interpretation and Policy .03. Currently, there are... applicable allocation algorithm for the HOSS and modified HOSS rotation procedures. Paragraph (c)(iv) of the... allocation algorithm in effect for the option class pursuant to Rule 6.45A or 6.45B), then to limit orders...

Improving the Interpretability of Classification Rules Discovered by an Ant Colony Algorithm: Extended Results.

PubMed

Otero, Fernando E B; Freitas, Alex A

2016-01-01

Most ant colony optimization (ACO) algorithms for inducing classification rules use a ACO-based procedure to create a rule in a one-at-a-time fashion. An improved search strategy has been proposed in the cAnt-Miner[Formula: see text] algorithm, where an ACO-based procedure is used to create a complete list of rules (ordered rules), i.e., the ACO search is guided by the quality of a list of rules instead of an individual rule. In this paper we propose an extension of the cAnt-Miner[Formula: see text] algorithm to discover a set of rules (unordered rules). The main motivations for this work are to improve the interpretation of individual rules by discovering a set of rules and to evaluate the impact on the predictive accuracy of the algorithm. We also propose a new measure to evaluate the interpretability of the discovered rules to mitigate the fact that the commonly used model size measure ignores how the rules are used to make a class prediction. Comparisons with state-of-the-art rule induction algorithms, support vector machines, and the cAnt-Miner[Formula: see text] producing ordered rules are also presented.

Validation of Living Donor Nephrectomy Codes

PubMed Central

Lam, Ngan N.; Lentine, Krista L.; Klarenbach, Scott; Sood, Manish M.; Kuwornu, Paul J.; Naylor, Kyla L.; Knoll, Gregory A.; Kim, S. Joseph; Young, Ann; Garg, Amit X.

2018-01-01

Background: Use of administrative data for outcomes assessment in living kidney donors is increasing given the rarity of complications and challenges with loss to follow-up. Objective: To assess the validity of living donor nephrectomy in health care administrative databases compared with the reference standard of manual chart review. Design: Retrospective cohort study. Setting: 5 major transplant centers in Ontario, Canada. Patients: Living kidney donors between 2003 and 2010. Measurements: Sensitivity and positive predictive value (PPV). Methods: Using administrative databases, we conducted a retrospective study to determine the validity of diagnostic and procedural codes for living donor nephrectomies. The reference standard was living donor nephrectomies identified through the province’s tissue and organ procurement agency, with verification by manual chart review. Operating characteristics (sensitivity and PPV) of various algorithms using diagnostic, procedural, and physician billing codes were calculated. Results: During the study period, there were a total of 1199 living donor nephrectomies. Overall, the best algorithm for identifying living kidney donors was the presence of 1 diagnostic code for kidney donor (ICD-10 Z52.4) and 1 procedural code for kidney procurement/excision (1PC58, 1PC89, 1PC91). Compared with the reference standard, this algorithm had a sensitivity of 97% and a PPV of 90%. The diagnostic and procedural codes performed better than the physician billing codes (sensitivity 60%, PPV 78%). Limitations: The donor chart review and validation study was performed in Ontario and may not be generalizable to other regions. Conclusions: An algorithm consisting of 1 diagnostic and 1 procedural code can be reliably used to conduct health services research that requires the accurate determination of living kidney donors at the population level. PMID:29662679

Efficient Prediction of Low-Visibility Events at Airports Using Machine-Learning Regression

NASA Astrophysics Data System (ADS)

Cornejo-Bueno, L.; Casanova-Mateo, C.; Sanz-Justo, J.; Cerro-Prada, E.; Salcedo-Sanz, S.

2017-11-01

We address the prediction of low-visibility events at airports using machine-learning regression. The proposed model successfully forecasts low-visibility events in terms of the runway visual range at the airport, with the use of support-vector regression, neural networks (multi-layer perceptrons and extreme-learning machines) and Gaussian-process algorithms. We assess the performance of these algorithms based on real data collected at the Valladolid airport, Spain. We also propose a study of the atmospheric variables measured at a nearby tower related to low-visibility atmospheric conditions, since they are considered as the inputs of the different regressors. A pre-processing procedure of these input variables with wavelet transforms is also described. The results show that the proposed machine-learning algorithms are able to predict low-visibility events well. The Gaussian process is the best algorithm among those analyzed, obtaining over 98% of the correct classification rate in low-visibility events when the runway visual range is {>}1000 m, and about 80% under this threshold. The performance of all the machine-learning algorithms tested is clearly affected in extreme low-visibility conditions ({<}500 m). However, we show improved results of all the methods when data from a neighbouring meteorological tower are included, and also with a pre-processing scheme using a wavelet transform. Also presented are results of the algorithm performance in daytime and nighttime conditions, and for different prediction time horizons.

Deep sulcal landmarks: algorithmic and conceptual improvements in the definition and extraction of sulcal pits.

PubMed

Auzias, G; Brun, L; Deruelle, C; Coulon, O

2015-05-01

Recent interest has been growing concerning points of maximum depth within folds, the sulcal pits, that can be used as reliable cortical landmarks. These remarkable points on the cortical surface are defined algorithmically as the outcome of an automatic extraction procedure. The influence of several crucial parameters of the reference technique (Im et al., 2010) has not been evaluated extensively, and no optimization procedure has been proposed so far. Designing an appropriate optimization framework for these parameters is mandatory to guarantee the reproducibility of results across studies and to ensure the feasibility of sulcal pit extraction and analysis on large cohorts. In this work, we propose a framework specifically dedicated to the optimization of the parameters of the method. This optimization framework relies on new measures for better quantifying the reproducibility of the number of sulcal pits per region across individuals, in line with the assumptions of one-to-one correspondence of sulcal roots across individuals which is an explicit aspect of the sulcal roots model (Régis et al., 2005). Our procedure benefits from a combination of improvements, including the use of a convenient sulcal depth estimation and is methodologically sound. Our experiments on two different groups of individuals, with a total of 137 subjects, show an increased reliability across subjects in deeper sulcal pits, as compared to the previous approach, and cover the entire cortical surface, including shallower and more variable folds that were not considered before. The effectiveness of our method ensures the feasibility of a systematic study of sulcal pits on large cohorts. On top of these methodological advances, we quantify the relationship between the reproducibility of the number of sulcal pits per region across individuals and their respective depth and demonstrate the relatively high reproducibility of several pits corresponding to shallower folds. Finally, we report new results regarding the local pit asymmetry, providing evidence that the algorithmic and conceptual approach defended here may contribute to better understanding of the key role of sulcal pits in neuroanatomy. Copyright © 2015 Elsevier Inc. All rights reserved.

Improvements in estimating proportions of objects from multispectral data

NASA Technical Reports Server (NTRS)

Horwitz, H. M.; Hyde, P. D.; Richardson, W.

1974-01-01

Methods for estimating proportions of objects and materials imaged within the instantaneous field of view of a multispectral sensor were developed further. Improvements in the basic proportion estimation algorithm were devised as well as improved alien object detection procedures. Also, a simplified signature set analysis scheme was introduced for determining the adequacy of signature set geometry for satisfactory proportion estimation. Averaging procedures used in conjunction with the mixtures algorithm were examined theoretically and applied to artificially generated multispectral data. A computationally simpler estimator was considered and found unsatisfactory. Experiments conducted to find a suitable procedure for setting the alien object threshold yielded little definitive result. Mixtures procedures were used on a limited amount of ERTS data to estimate wheat proportion in selected areas. Results were unsatisfactory, partly because of the ill-conditioned nature of the pure signature set.

Regression Models for Identifying Noise Sources in Magnetic Resonance Images

PubMed Central

Zhu, Hongtu; Li, Yimei; Ibrahim, Joseph G.; Shi, Xiaoyan; An, Hongyu; Chen, Yashen; Gao, Wei; Lin, Weili; Rowe, Daniel B.; Peterson, Bradley S.

2009-01-01

Stochastic noise, susceptibility artifacts, magnetic field and radiofrequency inhomogeneities, and other noise components in magnetic resonance images (MRIs) can introduce serious bias into any measurements made with those images. We formally introduce three regression models including a Rician regression model and two associated normal models to characterize stochastic noise in various magnetic resonance imaging modalities, including diffusion-weighted imaging (DWI) and functional MRI (fMRI). Estimation algorithms are introduced to maximize the likelihood function of the three regression models. We also develop a diagnostic procedure for systematically exploring MR images to identify noise components other than simple stochastic noise, and to detect discrepancies between the fitted regression models and MRI data. The diagnostic procedure includes goodness-of-fit statistics, measures of influence, and tools for graphical display. The goodness-of-fit statistics can assess the key assumptions of the three regression models, whereas measures of influence can isolate outliers caused by certain noise components, including motion artifacts. The tools for graphical display permit graphical visualization of the values for the goodness-of-fit statistic and influence measures. Finally, we conduct simulation studies to evaluate performance of these methods, and we analyze a real dataset to illustrate how our diagnostic procedure localizes subtle image artifacts by detecting intravoxel variability that is not captured by the regression models. PMID:19890478

Proactive Alleviation Procedure to Handle Black Hole Attack and Its Version

PubMed Central

Babu, M. Rajesh; Dian, S. Moses; Chelladurai, Siva; Palaniappan, Mathiyalagan

2015-01-01

The world is moving towards a new realm of computing such as Internet of Things. The Internet of Things, however, envisions connecting almost all objects within the world to the Internet by recognizing them as smart objects. In doing so, the existing networks which include wired, wireless, and ad hoc networks should be utilized. Moreover, apart from other networks, the ad hoc network is full of security challenges. For instance, the MANET (mobile ad hoc network) is susceptible to various attacks in which the black hole attacks and its versions do serious damage to the entire MANET infrastructure. The severity of this attack increases, when the compromised MANET nodes work in cooperation with each other to make a cooperative black hole attack. Therefore this paper proposes an alleviation procedure which consists of timely mandate procedure, hole detection algorithm, and sensitive guard procedure to detect the maliciously behaving nodes. It has been observed that the proposed procedure is cost-effective and ensures QoS guarantee by assuring resource availability thus making the MANET appropriate for Internet of Things. PMID:26495430

Proactive Alleviation Procedure to Handle Black Hole Attack and Its Version.

PubMed

Babu, M Rajesh; Dian, S Moses; Chelladurai, Siva; Palaniappan, Mathiyalagan

2015-01-01

The world is moving towards a new realm of computing such as Internet of Things. The Internet of Things, however, envisions connecting almost all objects within the world to the Internet by recognizing them as smart objects. In doing so, the existing networks which include wired, wireless, and ad hoc networks should be utilized. Moreover, apart from other networks, the ad hoc network is full of security challenges. For instance, the MANET (mobile ad hoc network) is susceptible to various attacks in which the black hole attacks and its versions do serious damage to the entire MANET infrastructure. The severity of this attack increases, when the compromised MANET nodes work in cooperation with each other to make a cooperative black hole attack. Therefore this paper proposes an alleviation procedure which consists of timely mandate procedure, hole detection algorithm, and sensitive guard procedure to detect the maliciously behaving nodes. It has been observed that the proposed procedure is cost-effective and ensures QoS guarantee by assuring resource availability thus making the MANET appropriate for Internet of Things.

An integrated portfolio optimisation procedure based on data envelopment analysis, artificial bee colony algorithm and genetic programming

NASA Astrophysics Data System (ADS)

Hsu, Chih-Ming

2014-12-01

Portfolio optimisation is an important issue in the field of investment/financial decision-making and has received considerable attention from both researchers and practitioners. However, besides portfolio optimisation, a complete investment procedure should also include the selection of profitable investment targets and determine the optimal timing for buying/selling the investment targets. In this study, an integrated procedure using data envelopment analysis (DEA), artificial bee colony (ABC) and genetic programming (GP) is proposed to resolve a portfolio optimisation problem. The proposed procedure is evaluated through a case study on investing in stocks in the semiconductor sub-section of the Taiwan stock market for 4 years. The potential average 6-month return on investment of 9.31% from 1 November 2007 to 31 October 2011 indicates that the proposed procedure can be considered a feasible and effective tool for making outstanding investment plans, and thus making profits in the Taiwan stock market. Moreover, it is a strategy that can help investors to make profits even when the overall stock market suffers a loss.

Derivation and experimental verification of clock synchronization theory

NASA Technical Reports Server (NTRS)

Palumbo, Daniel L.

1994-01-01

The objective of this work is to validate mathematically derived clock synchronization theories and their associated algorithms through experiment. Two theories are considered, the Interactive Convergence Clock Synchronization Algorithm and the Mid-Point Algorithm. Special clock circuitry was designed and built so that several operating conditions and failure modes (including malicious failures) could be tested. Both theories are shown to predict conservative upper bounds (i.e., measured values of clock skew were always less than the theory prediction). Insight gained during experimentation led to alternative derivations of the theories. These new theories accurately predict the clock system's behavior. It is found that a 100% penalty is paid to tolerate worst case failures. It is also shown that under optimal conditions (with minimum error and no failures) the clock skew can be as much as 3 clock ticks. Clock skew grows to 6 clock ticks when failures are present. Finally, it is concluded that one cannot rely solely on test procedures or theoretical analysis to predict worst case conditions. conditions.

ICCD: interactive continuous collision detection between deformable models using connectivity-based culling.

PubMed

Tang, Min; Curtis, Sean; Yoon, Sung-Eui; Manocha, Dinesh

2009-01-01

We present an interactive algorithm for continuous collision detection between deformable models. We introduce multiple techniques to improve the culling efficiency and the overall performance of continuous collision detection. First, we present a novel formulation for continuous normal cones and use these normal cones to efficiently cull large regions of the mesh as part of self-collision tests. Second, we introduce the concept of "procedural representative triangles" to remove all redundant elementary tests between nonadjacent triangles. Finally, we exploit the mesh connectivity and introduce the concept of "orphan sets" to eliminate redundant elementary tests between adjacent triangle primitives. In practice, we can reduce the number of elementary tests by two orders of magnitude. These culling techniques have been combined with bounding volume hierarchies and can result in one order of magnitude performance improvement as compared to prior collision detection algorithms for deformable models. We highlight the performance of our algorithm on several benchmarks, including cloth simulations, N-body simulations, and breaking objects.

Improving single molecule force spectroscopy through automated real-time data collection and quantification of experimental conditions

PubMed Central

Scholl, Zackary N.; Marszalek, Piotr E.

2013-01-01

The benefits of single molecule force spectroscopy (SMFS) clearly outweigh the challenges which include small sample sizes, tedious data collection and introduction of human bias during the subjective data selection. These difficulties can be partially eliminated through automation of the experimental data collection process for atomic force microscopy (AFM). Automation can be accomplished using an algorithm that triages usable force-extension recordings quickly with positive and negative selection. We implemented an algorithm based on the windowed fast Fourier transform of force-extension traces that identifies peaks using force-extension regimes to correctly identify usable recordings from proteins composed of repeated domains. This algorithm excels as a real-time diagnostic because it involves <30 ms computational time, has high sensitivity and specificity, and efficiently detects weak unfolding events. We used the statistics provided by the automated procedure to clearly demonstrate the properties of molecular adhesion and how these properties change with differences in the cantilever tip and protein functional groups and protein age. PMID:24001740

Reliability-based design optimization of reinforced concrete structures including soil-structure interaction using a discrete gravitational search algorithm and a proposed metamodel

NASA Astrophysics Data System (ADS)

Khatibinia, M.; Salajegheh, E.; Salajegheh, J.; Fadaee, M. J.

2013-10-01

A new discrete gravitational search algorithm (DGSA) and a metamodelling framework are introduced for reliability-based design optimization (RBDO) of reinforced concrete structures. The RBDO of structures with soil-structure interaction (SSI) effects is investigated in accordance with performance-based design. The proposed DGSA is based on the standard gravitational search algorithm (GSA) to optimize the structural cost under deterministic and probabilistic constraints. The Monte-Carlo simulation (MCS) method is considered as the most reliable method for estimating the probabilities of reliability. In order to reduce the computational time of MCS, the proposed metamodelling framework is employed to predict the responses of the SSI system in the RBDO procedure. The metamodel consists of a weighted least squares support vector machine (WLS-SVM) and a wavelet kernel function, which is called WWLS-SVM. Numerical results demonstrate the efficiency and computational advantages of DGSA and the proposed metamodel for RBDO of reinforced concrete structures.

Palladium-based Mass-Tag Cell Barcoding with a Doublet-Filtering Scheme and Single Cell Deconvolution Algorithm

PubMed Central

Zunder, Eli R.; Finck, Rachel; Behbehani, Gregory K.; Amir, El-ad D.; Krishnaswamy, Smita; Gonzalez, Veronica D.; Lorang, Cynthia G.; Bjornson, Zach; Spitzer, Matthew H.; Bodenmiller, Bernd; Fantl, Wendy J.; Pe’er, Dana; Nolan, Garry P.

2015-01-01

SUMMARY Mass-tag cell barcoding (MCB) labels individual cell samples with unique combinatorial barcodes, after which they are pooled for processing and measurement as a single multiplexed sample. The MCB method eliminates variability between samples in antibody staining and instrument sensitivity, reduces antibody consumption, and shortens instrument measurement time. Here, we present an optimized MCB protocol with several improvements over previously described methods. The use of palladium-based labeling reagents expands the number of measurement channels available for mass cytometry and reduces interference with lanthanide-based antibody measurement. An error-detecting combinatorial barcoding scheme allows cell doublets to be identified and removed from the analysis. A debarcoding algorithm that is single cell-based rather than population-based improves the accuracy and efficiency of sample deconvolution. This debarcoding algorithm has been packaged into software that allows rapid and unbiased sample deconvolution. The MCB procedure takes 3–4 h, not including sample acquisition time of ~1 h per million cells. PMID:25612231

Improving the Spatial Prediction of Soil Organic Carbon Stocks in a Complex Tropical Mountain Landscape by Methodological Specifications in Machine Learning Approaches

PubMed Central

Schmidt, Johannes; Glaser, Bruno

2016-01-01

Tropical forests are significant carbon sinks and their soils’ carbon storage potential is immense. However, little is known about the soil organic carbon (SOC) stocks of tropical mountain areas whose complex soil-landscape and difficult accessibility pose a challenge to spatial analysis. The choice of methodology for spatial prediction is of high importance to improve the expected poor model results in case of low predictor-response correlations. Four aspects were considered to improve model performance in predicting SOC stocks of the organic layer of a tropical mountain forest landscape: Different spatial predictor settings, predictor selection strategies, various machine learning algorithms and model tuning. Five machine learning algorithms: random forests, artificial neural networks, multivariate adaptive regression splines, boosted regression trees and support vector machines were trained and tuned to predict SOC stocks from predictors derived from a digital elevation model and satellite image. Topographical predictors were calculated with a GIS search radius of 45 to 615 m. Finally, three predictor selection strategies were applied to the total set of 236 predictors. All machine learning algorithms—including the model tuning and predictor selection—were compared via five repetitions of a tenfold cross-validation. The boosted regression tree algorithm resulted in the overall best model. SOC stocks ranged between 0.2 to 17.7 kg m-2, displaying a huge variability with diffuse insolation and curvatures of different scale guiding the spatial pattern. Predictor selection and model tuning improved the models’ predictive performance in all five machine learning algorithms. The rather low number of selected predictors favours forward compared to backward selection procedures. Choosing predictors due to their indiviual performance was vanquished by the two procedures which accounted for predictor interaction. PMID:27128736

Development of a clinical algorithm for treating urethral strictures based on a large retrospective single-center cohort

PubMed Central

Tolkach, Yuri; Herrmann, Thomas; Merseburger, Axel; Burchardt, Martin; Wolters, Mathias; Huusmann, Stefan; Kramer, Mario; Kuczyk, Markus; Imkamp, Florian

2017-01-01

Aim: To analyze clinical data from male patients treated with urethrotomy and to develop a clinical decision algorithm. Materials and methods: Two large cohorts of male patients with urethral strictures were included in this retrospective study, historical (1985-1995, n=491) and modern cohorts (1996-2006, n=470). All patients were treated with repeated internal urethrotomies (up to 9 sessions). Clinical outcomes were analyzed and systemized as a clinical decision algorithm. Results: The overall recurrence rates after the first urethrotomy were 32.4% and 23% in the historical and modern cohorts, respectively. In many patients, the second procedure was also effective with the third procedure also feasible in selected patients. The strictures with a length ≤ 2 cm should be treated according to the initial length. In patients with strictures ≤ 1 cm, the second session could be recommended in all patients, but not with penile strictures, strictures related to transurethral operations or for patients who were 31-50 years of age. The third session could be effective in selected cases of idiopathic bulbar strictures. For strictures with a length of 1-2 cm, a second operation is possible for the solitary low-grade bulbar strictures, given that the age is > 50 years and the etiology is not post-transurethral resection of the prostate. For penile strictures that are 1-2 cm, urethrotomy could be attempted in solitary but not in high-grade strictures. Conclusions: We present data on the treatment of urethral strictures with urethrotomy from a single center. Based on the analysis, a clinical decision algorithm was suggested, which could be a reliable basis for everyday clinical practice. PMID:28529689

Joint estimation of motion and illumination change in a sequence of images

NASA Astrophysics Data System (ADS)

Koo, Ja-Keoung; Kim, Hyo-Hun; Hong, Byung-Woo

2015-09-01

We present an algorithm that simultaneously computes optical flow and estimates illumination change from an image sequence in a unified framework. We propose an energy functional consisting of conventional optical flow energy based on Horn-Schunck method and an additional constraint that is designed to compensate for illumination changes. Any undesirable illumination change that occurs in the imaging procedure in a sequence while the optical flow is being computed is considered a nuisance factor. In contrast to the conventional optical flow algorithm based on Horn-Schunck functional, which assumes the brightness constancy constraint, our algorithm is shown to be robust with respect to temporal illumination changes in the computation of optical flows. An efficient conjugate gradient descent technique is used in the optimization procedure as a numerical scheme. The experimental results obtained from the Middlebury benchmark dataset demonstrate the robustness and the effectiveness of our algorithm. In addition, comparative analysis of our algorithm and Horn-Schunck algorithm is performed on the additional test dataset that is constructed by applying a variety of synthetic bias fields to the original image sequences in the Middlebury benchmark dataset in order to demonstrate that our algorithm outperforms the Horn-Schunck algorithm. The superior performance of the proposed method is observed in terms of both qualitative visualizations and quantitative accuracy errors when compared to Horn-Schunck optical flow algorithm that easily yields poor results in the presence of small illumination changes leading to violation of the brightness constancy constraint.

A passive microwave technique for estimating rainfall and vertical structure information from space. Part 1: Algorithm description

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Giglio, Louis

1994-01-01

This paper describes a multichannel physical approach for retrieving rainfall and vertical structure information from satellite-based passive microwave observations. The algorithm makes use of statistical inversion techniques based upon theoretically calculated relations between rainfall rates and brightness temperatures. Potential errors introduced into the theoretical calculations by the unknown vertical distribution of hydrometeors are overcome by explicity accounting for diverse hydrometeor profiles. This is accomplished by allowing for a number of different vertical distributions in the theoretical brightness temperature calculations and requiring consistency between the observed and calculated brightness temperatures. This paper will focus primarily on the theoretical aspects of the retrieval algorithm, which includes a procedure used to account for inhomogeneities of the rainfall within the satellite field of view as well as a detailed description of the algorithm as it is applied over both ocean and land surfaces. The residual error between observed and calculated brightness temperatures is found to be an important quantity in assessing the uniqueness of the solution. It is further found that the residual error is a meaningful quantity that can be used to derive expected accuracies from this retrieval technique. Examples comparing the retrieved results as well as the detailed analysis of the algorithm performance under various circumstances are the subject of a companion paper.

Rational approximations to rational models: alternative algorithms for category learning.

PubMed

Sanborn, Adam N; Griffiths, Thomas L; Navarro, Daniel J

2010-10-01

Rational models of cognition typically consider the abstract computational problems posed by the environment, assuming that people are capable of optimally solving those problems. This differs from more traditional formal models of cognition, which focus on the psychological processes responsible for behavior. A basic challenge for rational models is thus explaining how optimal solutions can be approximated by psychological processes. We outline a general strategy for answering this question, namely to explore the psychological plausibility of approximation algorithms developed in computer science and statistics. In particular, we argue that Monte Carlo methods provide a source of rational process models that connect optimal solutions to psychological processes. We support this argument through a detailed example, applying this approach to Anderson's (1990, 1991) rational model of categorization (RMC), which involves a particularly challenging computational problem. Drawing on a connection between the RMC and ideas from nonparametric Bayesian statistics, we propose 2 alternative algorithms for approximate inference in this model. The algorithms we consider include Gibbs sampling, a procedure appropriate when all stimuli are presented simultaneously, and particle filters, which sequentially approximate the posterior distribution with a small number of samples that are updated as new data become available. Applying these algorithms to several existing datasets shows that a particle filter with a single particle provides a good description of human inferences.

A new automated quantification algorithm for the detection and evaluation of focal liver lesions with contrast-enhanced ultrasound.

PubMed

Gatos, Ilias; Tsantis, Stavros; Spiliopoulos, Stavros; Skouroliakou, Aikaterini; Theotokas, Ioannis; Zoumpoulis, Pavlos; Hazle, John D; Kagadis, George C

2015-07-01

Detect and classify focal liver lesions (FLLs) from contrast-enhanced ultrasound (CEUS) imaging by means of an automated quantification algorithm. The proposed algorithm employs a sophisticated segmentation method to detect and contour focal lesions from 52 CEUS video sequences (30 benign and 22 malignant). Lesion detection involves wavelet transform zero crossings utilization as an initialization step to the Markov random field model toward the lesion contour extraction. After FLL detection across frames, time intensity curve (TIC) is computed which provides the contrast agents' behavior at all vascular phases with respect to adjacent parenchyma for each patient. From each TIC, eight features were automatically calculated and employed into the support vector machines (SVMs) classification algorithm in the design of the image analysis model. With regard to FLLs detection accuracy, all lesions detected had an average overlap value of 0.89 ± 0.16 with manual segmentations for all CEUS frame-subsets included in the study. Highest classification accuracy from the SVM model was 90.3%, misdiagnosing three benign and two malignant FLLs with sensitivity and specificity values of 93.1% and 86.9%, respectively. The proposed quantification system that employs FLLs detection and classification algorithms may be of value to physicians as a second opinion tool for avoiding unnecessary invasive procedures.

Development and validation of an automated operational modal analysis algorithm for vibration-based monitoring and tensile load estimation

NASA Astrophysics Data System (ADS)

Rainieri, Carlo; Fabbrocino, Giovanni

2015-08-01

In the last few decades large research efforts have been devoted to the development of methods for automated detection of damage and degradation phenomena at an early stage. Modal-based damage detection techniques are well-established methods, whose effectiveness for Level 1 (existence) and Level 2 (location) damage detection is demonstrated by several studies. The indirect estimation of tensile loads in cables and tie-rods is another attractive application of vibration measurements. It provides interesting opportunities for cheap and fast quality checks in the construction phase, as well as for safety evaluations and structural maintenance over the structure lifespan. However, the lack of automated modal identification and tracking procedures has been for long a relevant drawback to the extensive application of the above-mentioned techniques in the engineering practice. An increasing number of field applications of modal-based structural health and performance assessment are appearing after the development of several automated output-only modal identification procedures in the last few years. Nevertheless, additional efforts are still needed to enhance the robustness of automated modal identification algorithms, control the computational efforts and improve the reliability of modal parameter estimates (in particular, damping). This paper deals with an original algorithm for automated output-only modal parameter estimation. Particular emphasis is given to the extensive validation of the algorithm based on simulated and real datasets in view of continuous monitoring applications. The results point out that the algorithm is fairly robust and demonstrate its ability to provide accurate and precise estimates of the modal parameters, including damping ratios. As a result, it has been used to develop systems for vibration-based estimation of tensile loads in cables and tie-rods. Promising results have been achieved for non-destructive testing as well as continuous monitoring purposes. They are documented in the last sections of the paper.

[Crohn's disease surgery].

PubMed

Kala, Zdeněk; Marek, Filip; Válek, Vlastimil A; Bartušek, Daniel

2014-01-01

Surgery of Crohns disease is an important part of the general treatment algorithm. The role of surgery is changing with the development of conservative procedures. The recent years have seen the return to early treatment of patients with Crohns disease. Given the character of the disease and its intestinal symptoms, a specific approach to these patients is necessary, especially regarding the correct choice of surgery. The paper focuses on the luminal damage of the small and large intestine including complications of the disease. We describe the individual indications for a surgical solution, including the choice of anastomosis or multiple / repeated surgeries.

Consideration of computer limitations in implementing on-line controls. M.S. Thesis

NASA Technical Reports Server (NTRS)

Roberts, G. K.

1976-01-01

A formal statement of the optimal control problem which includes the interval of dicretization as an optimization parameter, and extend this to include selection of a control algorithm as part of the optimization procedure, is formulated. The performance of the scalar linear system depends on the discretization interval. Discrete-time versions of the output feedback regulator and an optimal compensator, and the use of these results in presenting an example of a system for which fast partial-state-feedback control better minimizes a quadratic cost than either a full-state feedback control or a compensator, are developed.

AIAA/USAF/NASA/OAI Symposium on Multidisciplinary Analysis and Optimization, 4th, Cleveland, OH, Sept. 21-23, 1992, Technical Papers. Pts. 1 & 2

NASA Technical Reports Server (NTRS)

1992-01-01

The papers presented at the symposium cover aerodynamics, design applications, propulsion systems, high-speed flight, structures, controls, sensitivity analysis, optimization algorithms, and space structures applications. Other topics include helicopter rotor design, artificial intelligence/neural nets, and computational aspects of optimization. Papers are included on flutter calculations for a system with interacting nonlinearities, optimization in solid rocket booster application, improving the efficiency of aerodynamic shape optimization procedures, nonlinear control theory, and probabilistic structural analysis of space truss structures for nonuniform thermal environmental effects.

Robotic space construction

NASA Technical Reports Server (NTRS)

Mixon, Randolph W.; Hankins, Walter W., III; Wise, Marion A.

1988-01-01

Research at Langley AFB concerning automated space assembly is reviewed, including a Space Shuttle experiment to test astronaut ability to assemble a repetitive truss structure, testing the use of teleoperated manipulators to construct the Assembly Concept for Construction of Erectable Space Structures I truss, and assessment of the basic characteristics of manipulator assembly operations. Other research topics include the simultaneous coordinated control of dual-arm manipulators and the automated assembly of candidate Space Station trusses. Consideration is given to the construction of an Automated Space Assembly Laboratory to study and develop the algorithms, procedures, special purpose hardware, and processes needed for automated truss assembly.

Chiari malformation Type I surgery in pediatric patients. Part 1: validation of an ICD-9-CM code search algorithm.

PubMed

Ladner, Travis R; Greenberg, Jacob K; Guerrero, Nicole; Olsen, Margaret A; Shannon, Chevis N; Yarbrough, Chester K; Piccirillo, Jay F; Anderson, Richard C E; Feldstein, Neil A; Wellons, John C; Smyth, Matthew D; Park, Tae Sung; Limbrick, David D

2016-05-01

OBJECTIVE Administrative billing data may facilitate large-scale assessments of treatment outcomes for pediatric Chiari malformation Type I (CM-I). Validated International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code algorithms for identifying CM-I surgery are critical prerequisites for such studies but are currently only available for adults. The objective of this study was to validate two ICD-9-CM code algorithms using hospital billing data to identify pediatric patients undergoing CM-I decompression surgery. METHODS The authors retrospectively analyzed the validity of two ICD-9-CM code algorithms for identifying pediatric CM-I decompression surgery performed at 3 academic medical centers between 2001 and 2013. Algorithm 1 included any discharge diagnosis code of 348.4 (CM-I), as well as a procedure code of 01.24 (cranial decompression) or 03.09 (spinal decompression or laminectomy). Algorithm 2 restricted this group to the subset of patients with a primary discharge diagnosis of 348.4. The positive predictive value (PPV) and sensitivity of each algorithm were calculated. RESULTS Among 625 first-time admissions identified by Algorithm 1, the overall PPV for CM-I decompression was 92%. Among the 581 admissions identified by Algorithm 2, the PPV was 97%. The PPV for Algorithm 1 was lower in one center (84%) compared with the other centers (93%-94%), whereas the PPV of Algorithm 2 remained high (96%-98%) across all subgroups. The sensitivity of Algorithms 1 (91%) and 2 (89%) was very good and remained so across subgroups (82%-97%). CONCLUSIONS An ICD-9-CM algorithm requiring a primary diagnosis of CM-I has excellent PPV and very good sensitivity for identifying CM-I decompression surgery in pediatric patients. These results establish a basis for utilizing administrative billing data to assess pediatric CM-I treatment outcomes.

An Efficient and Accurate Genetic Algorithm for Backcalculation of Flexible Pavement Layer Moduli : Executive Summary Report

DOT National Transportation Integrated Search

2012-12-01

Backcalculation of pavement moduli has been an intensively researched subject for more than four decades. Despite the existence of many backcalculation programs employing different backcalculation procedures and algorithms, accurate inverse of the la...

Non-intrusive parameter identification procedure user's guide

NASA Technical Reports Server (NTRS)

Hanson, G. D.; Jewell, W. F.

1983-01-01

Written in standard FORTRAN, NAS is capable of identifying linear as well as nonlinear relations between input and output parameters; the only restriction is that the input/output relation be linear with respect to the unknown coefficients of the estimation equations. The output of the identification algorithm can be specified to be in either the time domain (i.e., the estimation equation coefficients) or in the frequency domain (i.e., a frequency response of the estimation equation). The frame length ("window") over which the identification procedure is to take place can be specified to be any portion of the input time history, thereby allowing the freedom to start and stop the identification procedure within a time history. There also is an option which allows a sliding window, which gives a moving average over the time history. The NAS software also includes the ability to identify several assumed solutions simultaneously for the same or different input data.

Parallel Domain Decomposition Formulation and Software for Large-Scale Sparse Symmetrical/Unsymmetrical Aeroacoustic Applications

NASA Technical Reports Server (NTRS)

Nguyen, D. T.; Watson, Willie R. (Technical Monitor)

2005-01-01

The overall objectives of this research work are to formulate and validate efficient parallel algorithms, and to efficiently design/implement computer software for solving large-scale acoustic problems, arised from the unified frameworks of the finite element procedures. The adopted parallel Finite Element (FE) Domain Decomposition (DD) procedures should fully take advantages of multiple processing capabilities offered by most modern high performance computing platforms for efficient parallel computation. To achieve this objective. the formulation needs to integrate efficient sparse (and dense) assembly techniques, hybrid (or mixed) direct and iterative equation solvers, proper pre-conditioned strategies, unrolling strategies, and effective processors' communicating schemes. Finally, the numerical performance of the developed parallel finite element procedures will be evaluated by solving series of structural, and acoustic (symmetrical and un-symmetrical) problems (in different computing platforms). Comparisons with existing "commercialized" and/or "public domain" software are also included, whenever possible.

Assistive technology for ultrasound-guided central venous catheter placement.

PubMed

Ikhsan, Mohammad; Tan, Kok Kiong; Putra, Andi Sudjana

2018-01-01

This study evaluated the existing technology used to improve the safety and ease of ultrasound-guided central venous catheterization. Electronic database searches were conducted in Scopus, IEEE, Google Patents, and relevant conference databases (SPIE, MICCAI, and IEEE conferences) for related articles on assistive technology for ultrasound-guided central venous catheterization. A total of 89 articles were examined and pointed to several fields that are currently the focus of improvements to ultrasound-guided procedures. These include improving needle visualization, needle guides and localization technology, image processing algorithms to enhance and segment important features within the ultrasound image, robotic assistance using probe-mounted manipulators, and improving procedure ergonomics through in situ projections of important information. Probe-mounted robotic manipulators provide a promising avenue for assistive technology developed for freehand ultrasound-guided percutaneous procedures. However, there is currently a lack of clinical trials to validate the effectiveness of these devices.

Development and Testing of Data Mining Algorithms for Earth Observation

NASA Technical Reports Server (NTRS)

Glymour, Clark

2005-01-01

The new algorithms developed under this project included a principled procedure for classification of objects, events or circumstances according to a target variable when a very large number of potential predictor variables is available but the number of cases that can be used for training a classifier is relatively small. These "high dimensional" problems require finding a minimal set of variables -called the Markov Blanket-- sufficient for predicting the value of the target variable. An algorithm, the Markov Blanket Fan Search, was developed, implemented and tested on both simulated and real data in conjunction with a graphical model classifier, which was also implemented. Another algorithm developed and implemented in TETRAD IV for time series elaborated on work by C. Granger and N. Swanson, which in turn exploited some of our earlier work. The algorithms in question learn a linear time series model from data. Given such a time series, the simultaneous residual covariances, after factoring out time dependencies, may provide information about causal processes that occur more rapidly than the time series representation allow, so called simultaneous or contemporaneous causal processes. Working with A. Monetta, a graduate student from Italy, we produced the correct statistics for estimating the contemporaneous causal structure from time series data using the TETRAD IV suite of algorithms. Two economists, David Bessler and Kevin Hoover, have independently published applications using TETRAD style algorithms to the same purpose. These implementations and algorithmic developments were separately used in two kinds of studies of climate data: Short time series of geographically proximate climate variables predicting agricultural effects in California, and longer duration climate measurements of temperature teleconnections.

Mining Peripheral Arterial Disease Cases from Narrative Clinical Notes Using Natural Language Processing

PubMed Central

Afzal, Naveed; Sohn, Sunghwan; Abram, Sara; Scott, Christopher G.; Chaudhry, Rajeev; Liu, Hongfang; Kullo, Iftikhar J.; Arruda-Olson, Adelaide M.

2016-01-01

Objective Lower extremity peripheral arterial disease (PAD) is highly prevalent and affects millions of individuals worldwide. We developed a natural language processing (NLP) system for automated ascertainment of PAD cases from clinical narrative notes and compared the performance of the NLP algorithm to billing code algorithms, using ankle-brachial index (ABI) test results as the gold standard. Methods We compared the performance of the NLP algorithm to 1) results of gold standard ABI; 2) previously validated algorithms based on relevant ICD-9 diagnostic codes (simple model) and 3) a combination of ICD-9 codes with procedural codes (full model). A dataset of 1,569 PAD patients and controls was randomly divided into training (n= 935) and testing (n= 634) subsets. Results We iteratively refined the NLP algorithm in the training set including narrative note sections, note types and service types, to maximize its accuracy. In the testing dataset, when compared with both simple and full models, the NLP algorithm had better accuracy (NLP: 91.8%, full model: 81.8%, simple model: 83%, P<.001), PPV (NLP: 92.9%, full model: 74.3%, simple model: 79.9%, P<.001), and specificity (NLP: 92.5%, full model: 64.2%, simple model: 75.9%, P<.001). Conclusions A knowledge-driven NLP algorithm for automatic ascertainment of PAD cases from clinical notes had greater accuracy than billing code algorithms. Our findings highlight the potential of NLP tools for rapid and efficient ascertainment of PAD cases from electronic health records to facilitate clinical investigation and eventually improve care by clinical decision support. PMID:28189359

Attention Recognition in EEG-Based Affective Learning Research Using CFS+KNN Algorithm.

PubMed

Hu, Bin; Li, Xiaowei; Sun, Shuting; Ratcliffe, Martyn

2018-01-01

The research detailed in this paper focuses on the processing of Electroencephalography (EEG) data to identify attention during the learning process. The identification of affect using our procedures is integrated into a simulated distance learning system that provides feedback to the user with respect to attention and concentration. The authors propose a classification procedure that combines correlation-based feature selection (CFS) and a k-nearest-neighbor (KNN) data mining algorithm. To evaluate the CFS+KNN algorithm, it was test against CFS+C4.5 algorithm and other classification algorithms. The classification performance was measured 10 times with different 3-fold cross validation data. The data was derived from 10 subjects while they were attempting to learn material in a simulated distance learning environment. A self-assessment model of self-report was used with a single valence to evaluate attention on 3 levels (high, neutral, low). It was found that CFS+KNN had a much better performance, giving the highest correct classification rate (CCR) of % for the valence dimension divided into three classes.

Performance of biometric quality measures.

PubMed

Grother, Patrick; Tabassi, Elham

2007-04-01

We document methods for the quantitative evaluation of systems that produce a scalar summary of a biometric sample's quality. We are motivated by a need to test claims that quality measures are predictive of matching performance. We regard a quality measurement algorithm as a black box that converts an input sample to an output scalar. We evaluate it by quantifying the association between those values and observed matching results. We advance detection error trade-off and error versus reject characteristics as metrics for the comparative evaluation of sample quality measurement algorithms. We proceed this with a definition of sample quality, a description of the operational use of quality measures. We emphasize the performance goal by including a procedure for annotating the samples of a reference corpus with quality values derived from empirical recognition scores.

Adiabatic quantum simulation of quantum chemistry.

PubMed

Babbush, Ryan; Love, Peter J; Aspuru-Guzik, Alán

2014-10-13

We show how to apply the quantum adiabatic algorithm directly to the quantum computation of molecular properties. We describe a procedure to map electronic structure Hamiltonians to 2-body qubit Hamiltonians with a small set of physically realizable couplings. By combining the Bravyi-Kitaev construction to map fermions to qubits with perturbative gadgets to reduce the Hamiltonian to 2-body, we obtain precision requirements on the coupling strengths and a number of ancilla qubits that scale polynomially in the problem size. Hence our mapping is efficient. The required set of controllable interactions includes only two types of interaction beyond the Ising interactions required to apply the quantum adiabatic algorithm to combinatorial optimization problems. Our mapping may also be of interest to chemists directly as it defines a dictionary from electronic structure to spin Hamiltonians with physical interactions.

The Papers Printing Quality Complex Assessment Algorithm Development Taking into Account the Composition and Production Technological Features

NASA Astrophysics Data System (ADS)

Babakhanova, Kh A.; Varepo, L. G.; Nagornova, I. V.; Babluyk, E. B.; Kondratov, A. P.

2018-04-01

Paper is one of the printing system key components causing the high-quality printed products output. Providing the printing companies with the specified printing properties paper, while simultaneously increasing the paper products range and volume by means of the forecasting methods application and evaluation during the production process, is certainly a relevant problem. The paper presents the printing quality control algorithm taking into consideration the paper printing properties quality assessment depending on the manufacture technological features and composition variation. The information system including raw material and paper properties data and making possible pulp and paper enterprises to select paper composition optimal formulation is proposed taking into account the printing process procedure peculiarities of the paper manufacturing with specified printing properties.

A computational approach for hypersonic nonequilibrium radiation utilizing space partition algorithm and Gauss quadrature

NASA Astrophysics Data System (ADS)

Shang, J. S.; Andrienko, D. A.; Huang, P. G.; Surzhikov, S. T.

2014-06-01

An efficient computational capability for nonequilibrium radiation simulation via the ray tracing technique has been accomplished. The radiative rate equation is iteratively coupled with the aerodynamic conservation laws including nonequilibrium chemical and chemical-physical kinetic models. The spectral properties along tracing rays are determined by a space partition algorithm of the nearest neighbor search process, and the numerical accuracy is further enhanced by a local resolution refinement using the Gauss-Lobatto polynomial. The interdisciplinary governing equations are solved by an implicit delta formulation through the diminishing residual approach. The axisymmetric radiating flow fields over the reentry RAM-CII probe have been simulated and verified with flight data and previous solutions by traditional methods. A computational efficiency gain nearly forty times is realized over that of the existing simulation procedures.

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

NASA Technical Reports Server (NTRS)

2004-01-01

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

Problem solving with genetic algorithms and Splicer

NASA Technical Reports Server (NTRS)

Bayer, Steven E.; Wang, Lui

1991-01-01

Genetic algorithms are highly parallel, adaptive search procedures (i.e., problem-solving methods) loosely based on the processes of population genetics and Darwinian survival of the fittest. Genetic algorithms have proven useful in domains where other optimization techniques perform poorly. The main purpose of the paper is to discuss a NASA-sponsored software development project to develop a general-purpose tool for using genetic algorithms. The tool, called Splicer, can be used to solve a wide variety of optimization problems and is currently available from NASA and COSMIC. This discussion is preceded by an introduction to basic genetic algorithm concepts and a discussion of genetic algorithm applications.

A Spectral Algorithm for Solving the Relativistic Vlasov-Maxwell Equations

NASA Technical Reports Server (NTRS)

Shebalin, John V.

2001-01-01

A spectral method algorithm is developed for the numerical solution of the full six-dimensional Vlasov-Maxwell system of equations. Here, the focus is on the electron distribution function, with positive ions providing a constant background. The algorithm consists of a Jacobi polynomial-spherical harmonic formulation in velocity space and a trigonometric formulation in position space. A transform procedure is used to evaluate nonlinear terms. The algorithm is suitable for performing moderate resolution simulations on currently available supercomputers for both scientific and engineering applications.

Routing Algorithm based on Minimum Spanning Tree and Minimum Cost Flow for Hybrid Wireless-optical Broadband Access Network

NASA Astrophysics Data System (ADS)

Le, Zichun; Suo, Kaihua; Fu, Minglei; Jiang, Ling; Dong, Wen

2012-03-01

In order to minimize the average end to end delay for data transporting in hybrid wireless optical broadband access network, a novel routing algorithm named MSTMCF (minimum spanning tree and minimum cost flow) is devised. The routing problem is described as a minimum spanning tree and minimum cost flow model and corresponding algorithm procedures are given. To verify the effectiveness of MSTMCF algorithm, extensively simulations based on OWNS have been done under different types of traffic source.

Research on numerical algorithms for large space structures

NASA Technical Reports Server (NTRS)

Denman, E. D.

1981-01-01

Numerical algorithms for analysis and design of large space structures are investigated. The sign algorithm and its application to decoupling of differential equations are presented. The generalized sign algorithm is given and its application to several problems discussed. The Laplace transforms of matrix functions and the diagonalization procedure for a finite element equation are discussed. The diagonalization of matrix polynomials is considered. The quadrature method and Laplace transforms is discussed and the identification of linear systems by the quadrature method investigated.

Development of a Compound Optimization Approach Based on Imperialist Competitive Algorithm

NASA Astrophysics Data System (ADS)

Wang, Qimei; Yang, Zhihong; Wang, Yong

In this paper, an improved novel approach is developed for the imperialist competitive algorithm to achieve a greater performance. The Nelder-Meand simplex method is applied to execute alternately with the original procedures of the algorithm. The approach is tested on twelve widely-used benchmark functions and is also compared with other relative studies. It is shown that the proposed approach has a faster convergence rate, better search ability, and higher stability than the original algorithm and other relative methods.

Parameter Trending, Geolocation Quality Control and the Procedures to Support Preparation of Next Versions of the TRMM Reprocessing Algorithm

NASA Technical Reports Server (NTRS)

Stocker, Erich Franz

2004-01-01

TRMM has been an imminently successful mission from an engineering standpoint but even more from a science standpoint. An important part of this science success has been the careful quality control of the TRMM standard products. This paper will present the quality monitoring efforts that the TRMM Science Data and Information System (TSDIS) conducts on a routine basis. The paper will detail parameter trending, geolocation quality control and the procedures to support the preparation of next versions of the algorithm used for reprocessing.

23 CFR Appendix B to Part 1240 - Procedures for Missing or Inadequate State-Submitted Information (Calendar Years 1996 and 1997)

Code of Federal Regulations, 2011 CFR

2011-04-01

... (FARS) will be translated into estimated observed seat belt use rates using an algorithm that relates... 133, June, 1994. B. The algorithm is as follows: u = (−.221794 + √.049193 + .410769F) / .456410 Where... change in the FARS-based observed seat belt use rate (derived from the above algorithm) between the two...

23 CFR Appendix B to Part 1240 - Procedures for Missing or Inadequate State-Submitted Information (Calendar Years 1996 and 1997)

Code of Federal Regulations, 2013 CFR

2013-04-01

... (FARS) will be translated into estimated observed seat belt use rates using an algorithm that relates... 133, June, 1994. B. The algorithm is as follows: u = (−.221794 + √.049193 + .410769F) / .456410 Where... change in the FARS-based observed seat belt use rate (derived from the above algorithm) between the two...

23 CFR Appendix B to Part 1240 - Procedures for Missing or Inadequate State-Submitted Information (Calendar Years 1996 and 1997)

Code of Federal Regulations, 2014 CFR

2014-04-01

... (FARS) will be translated into estimated observed seat belt use rates using an algorithm that relates... 133, June, 1994. B. The algorithm is as follows: u = (−.221794 + √.049193 + .410769F) / .456410 Where... change in the FARS-based observed seat belt use rate (derived from the above algorithm) between the two...

23 CFR Appendix B to Part 1240 - Procedures for Missing or Inadequate State-Submitted Information (Calendar Years 1996 and 1997)

Code of Federal Regulations, 2012 CFR

2012-04-01

... (FARS) will be translated into estimated observed seat belt use rates using an algorithm that relates... 133, June, 1994. B. The algorithm is as follows: u = (−.221794 + √.049193 + .410769F) / .456410 Where... change in the FARS-based observed seat belt use rate (derived from the above algorithm) between the two...

23 CFR Appendix B to Part 1240 - Procedures for Missing or Inadequate State-Submitted Information (Calendar Years 1996 and 1997)

Code of Federal Regulations, 2010 CFR

2010-04-01

... (FARS) will be translated into estimated observed seat belt use rates using an algorithm that relates... 133, June, 1994. B. The algorithm is as follows: u = (−.221794 + √.049193 + .410769F) / .456410 Where... change in the FARS-based observed seat belt use rate (derived from the above algorithm) between the two...

Real-Time flare detection using guided filter

NASA Astrophysics Data System (ADS)

Lin, Jiaben; Deng, Yuanyong; Yuan, Fei; Guo, Juan

2017-04-01

A procedure is introduced for the automatic detection of solar flare using full-disk solar images from Huairou Solar Observing Station (HSOS), National Astronomical Observatories of China. In image preprocessing, median filter is applied to remove the noises. And then we adopt guided filter, which is first introduced into the astronomical image detection, to enhance the edges of flares and restrain the solar limb darkening. Flares are then detected by modified Otsu algorithm and further threshold processing technique. Compared with other automatic detection procedure, the new procedure has some advantages such as real time and reliability as well as no need of image division and local threshold. Also, it reduces the amount of computation largely, which is benefited from the efficient guided filter algorithm. The procedure has been tested on one month sequences (December 2013) of HSOS full-disk solar images and the result of flares detection shows that the number of flares detected by our procedure is well consistent with the manual one.

Automatic detection of solar features in HSOS full-disk solar images using guided filter

NASA Astrophysics Data System (ADS)

Yuan, Fei; Lin, Jiaben; Guo, Jingjing; Wang, Gang; Tong, Liyue; Zhang, Xinwei; Wang, Bingxiang

2018-02-01

A procedure is introduced for the automatic detection of solar features using full-disk solar images from Huairou Solar Observing Station (HSOS), National Astronomical Observatories of China. In image preprocessing, median filter is applied to remove the noises. Guided filter is adopted to enhance the edges of solar features and restrain the solar limb darkening, which is first introduced into the astronomical target detection. Then specific features are detected by Otsu algorithm and further threshold processing technique. Compared with other automatic detection procedures, our procedure has some advantages such as real time and reliability as well as no need of local threshold. Also, it reduces the amount of computation largely, which is benefited from the efficient guided filter algorithm. The procedure has been tested on one month sequences (December 2013) of HSOS full-disk solar images and the result shows that the number of features detected by our procedure is well consistent with the manual one.

A general Bayesian image reconstruction algorithm with entropy prior: Preliminary application to HST data

NASA Astrophysics Data System (ADS)

Nunez, Jorge; Llacer, Jorge

1993-10-01

This paper describes a general Bayesian iterative algorithm with entropy prior for image reconstruction. It solves the cases of both pure Poisson data and Poisson data with Gaussian readout noise. The algorithm maintains positivity of the solution; it includes case-specific prior information (default map) and flatfield corrections; it removes background and can be accelerated to be faster than the Richardson-Lucy algorithm. In order to determine the hyperparameter that balances the entropy and liklihood terms in the Bayesian approach, we have used a liklihood cross-validation technique. Cross-validation is more robust than other methods because it is less demanding in terms of the knowledge of exact data characteristics and of the point-spread function. We have used the algorithm to reconstruct successfully images obtained in different space-and ground-based imaging situations. It has been possible to recover most of the original intended capabilities of the Hubble Space Telescope (HST) wide field and planetary camera (WFPC) and faint object camera (FOC) from images obtained in their present state. Semireal simulations for the future wide field planetary camera 2 show that even after the repair of the spherical abberration problem, image reconstruction can play a key role in improving the resolution of the cameras, well beyond the design of the Hubble instruments. We also show that ground-based images can be reconstructed successfully with the algorithm. A technique which consists of dividing the CCD observations into two frames, with one-half the exposure time each, emerges as a recommended procedure for the utilization of the described algorithms. We have compared our technique with two commonly used reconstruction algorithms: the Richardson-Lucy and the Cambridge maximum entropy algorithms.

Inferring pregnancy episodes and outcomes within a network of observational databases

PubMed Central

Ryan, Patrick; Fife, Daniel; Gifkins, Dina; Knoll, Chris; Friedman, Andrew

2018-01-01

Administrative claims and electronic health records are valuable resources for evaluating pharmaceutical effects during pregnancy. However, direct measures of gestational age are generally not available. Establishing a reliable approach to infer the duration and outcome of a pregnancy could improve pharmacovigilance activities. We developed and applied an algorithm to define pregnancy episodes in four observational databases: three US-based claims databases: Truven MarketScan® Commercial Claims and Encounters (CCAE), Truven MarketScan® Multi-state Medicaid (MDCD), and the Optum ClinFormatics® (Optum) database and one non-US database, the United Kingdom (UK) based Clinical Practice Research Datalink (CPRD). Pregnancy outcomes were classified as live births, stillbirths, abortions and ectopic pregnancies. Start dates were estimated using a derived hierarchy of available pregnancy markers, including records such as last menstrual period and nuchal ultrasound dates. Validation included clinical adjudication of 700 electronic Optum and CPRD pregnancy episode profiles to assess the operating characteristics of the algorithm, and a comparison of the algorithm’s Optum pregnancy start estimates to starts based on dates of assisted conception procedures. Distributions of pregnancy outcome types were similar across all four data sources and pregnancy episode lengths found were as expected for all outcomes, excepting term lengths in episodes that used amenorrhea and urine pregnancy tests for start estimation. Validation survey results found highest agreement between reviewer chosen and algorithm operating characteristics for questions assessing pregnancy status and accuracy of outcome category with 99–100% agreement for Optum and CPRD. Outcome date agreement within seven days in either direction ranged from 95–100%, while start date agreement within seven days in either direction ranged from 90–97%. In Optum validation sensitivity analysis, a total of 73% of algorithm estimated starts for live births were in agreement with fertility procedure estimated starts within two weeks in either direction; ectopic pregnancy 77%, stillbirth 47%, and abortion 36%. An algorithm to infer live birth and ectopic pregnancy episodes and outcomes can be applied to multiple observational databases with acceptable accuracy for further epidemiologic research. Less accuracy was found for start date estimations in stillbirth and abortion outcomes in our sensitivity analysis, which may be expected given the nature of the outcomes. PMID:29389968

Evaluation of Various Radar Data Quality Control Algorithms Based on Accumulated Radar Rainfall Statistics

NASA Technical Reports Server (NTRS)

Robinson, Michael; Steiner, Matthias; Wolff, David B.; Ferrier, Brad S.; Kessinger, Cathy; Einaudi, Franco (Technical Monitor)

2000-01-01

The primary function of the TRMM Ground Validation (GV) Program is to create GV rainfall products that provide basic validation of satellite-derived precipitation measurements for select primary sites. A fundamental and extremely important step in creating high-quality GV products is radar data quality control. Quality control (QC) processing of TRMM GV radar data is based on some automated procedures, but the current QC algorithm is not fully operational and requires significant human interaction to assure satisfactory results. Moreover, the TRMM GV QC algorithm, even with continuous manual tuning, still can not completely remove all types of spurious echoes. In an attempt to improve the current operational radar data QC procedures of the TRMM GV effort, an intercomparison of several QC algorithms has been conducted. This presentation will demonstrate how various radar data QC algorithms affect accumulated radar rainfall products. In all, six different QC algorithms will be applied to two months of WSR-88D radar data from Melbourne, Florida. Daily, five-day, and monthly accumulated radar rainfall maps will be produced for each quality-controlled data set. The QC algorithms will be evaluated and compared based on their ability to remove spurious echoes without removing significant precipitation. Strengths and weaknesses of each algorithm will be assessed based on, their abilit to mitigate both erroneous additions and reductions in rainfall accumulation from spurious echo contamination and true precipitation removal, respectively. Contamination from individual spurious echo categories will be quantified to further diagnose the abilities of each radar QC algorithm. Finally, a cost-benefit analysis will be conducted to determine if a more automated QC algorithm is a viable alternative to the current, labor-intensive QC algorithm employed by TRMM GV.

Analysis of Two Advanced Smoothing Algorithms.

DTIC Science & Technology

1985-09-01

59 B. METHODOLOGY . ......... ........... 60 6 C. TESTING AND RESULTS ---- LINEAR UNDERLYING FUNCTION...SMOOTHING ALGORITHMS ...... .................... 94 A. GENERAL ......... ....................... .. 94 B. METHODOLOGY ............................ .95 C...to define succinctly. 59 B. METHODOLOGY There is no established procedure to follow in testing the efficiency and effectiveness of a smoothing

Simulation of ultra-high energy photon propagation with PRESHOWER 2.0

NASA Astrophysics Data System (ADS)

Homola, P.; Engel, R.; Pysz, A.; Wilczyński, H.

2013-05-01

In this paper we describe a new release of the PRESHOWER program, a tool for Monte Carlo simulation of propagation of ultra-high energy photons in the magnetic field of the Earth. The PRESHOWER program is designed to calculate magnetic pair production and bremsstrahlung and should be used together with other programs to simulate extensive air showers induced by photons. The main new features of the PRESHOWER code include a much faster algorithm applied in the procedures of simulating the processes of gamma conversion and bremsstrahlung, update of the geomagnetic field model, and a minor correction. The new simulation procedure increases the flexibility of the code so that it can also be applied to other magnetic field configurations such as, for example, encountered in the vicinity of the sun or neutron stars. Program summaryProgram title: PRESHOWER 2.0 Catalog identifier: ADWG_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADWG_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 3968 No. of bytes in distributed program, including test data, etc.: 37198 Distribution format: tar.gz Programming language: C, FORTRAN 77. Computer: Intel-Pentium based PC. Operating system: Linux or Unix. RAM:< 100 kB Classification: 1.1. Does the new version supercede the previous version?: Yes Catalog identifier of previous version: ADWG_v1_0 Journal reference of previous version: Comput. Phys. Comm. 173 (2005) 71 Nature of problem: Simulation of a cascade of particles initiated by UHE photon in magnetic field. Solution method: The primary photon is tracked until its conversion into an e+ e- pair. If conversion occurs each individual particle in the resultant preshower is checked for either bremsstrahlung radiation (electrons) or secondary gamma conversion (photons). Reasons for new version: Slow and outdated algorithm in the old version (a significant speed up is possible); Extension of the program to allow simulations also for extraterrestrial magnetic field configurations (e.g. neutron stars) and very long path lengths. Summary of revisions: A veto algorithm was introduced in the gamma conversion and bremsstrahlung tracking procedures. The length of the tracking step is now variable along the track and depends on the probability of the process expected to occur. The new algorithm reduces significantly the number of tracking steps and speeds up the execution of the program. The geomagnetic field model has been updated to IGRF-11, allowing for interpolations up to the year 2015. Numerical Recipes procedures to calculate modified Bessel functions have been replaced with an open source CERN routine DBSKA. One minor bug has been fixed. Restrictions: Gamma conversion into particles other than an electron pair is not considered. Spatial structure of the cascade is neglected. Additional comments: The following routines are supplied in the package, IGRF [1, 2], DBSKA [3], ran2 [4] Running time: 100 preshower events with primary energy 1020 eV require a 2.66 GHz CPU time of about 200 sec.; at the energy of 1021 eV, 600 sec.

Computational procedures for mixed equations with shock waves

NASA Technical Reports Server (NTRS)

Yu, N. J.; Seebass, R.

1974-01-01

This paper discusses the procedures we have developed to treat a canonical problem involving a mixed nonlinear equation with boundary data that imply a discontinuous solution. This equation arises in various physical contexts and is basic to the description of the nonlinear acoustic behavior of a shock wave near a caustic. The numerical scheme developed is of second order, treats discontinuities as such by applying the appropriate jump conditions across them, and eliminates the numerical dissipation and dispersion associated with large gradients. Our results are compared with the results of a first-order scheme and with those of a second-order scheme we have developed. The algorithm used here can easily be generalized to more complicated problems, including transonic flows with imbedded shocks.

Facial skin color measurement based on camera colorimetric characterization

NASA Astrophysics Data System (ADS)

Yang, Boquan; Zhou, Changhe; Wang, Shaoqing; Fan, Xin; Li, Chao

2016-10-01

The objective measurement of facial skin color and its variance is of great significance as much information can be obtained from it. In this paper, we developed a new skin color measurement procedure which includes following parts: first, a new skin tone color checker made of pantone Skin Tone Color Checker was designed for camera colorimetric characterization; second, the chromaticity of light source was estimated via a new scene illumination estimation method considering several previous algorithms; third, chromatic adaption was used to convert the input facial image into output facial image which appears taken under canonical light; finally the validity and accuracy of our method was verified by comparing the results obtained by our procedure with these by spectrophotometer.

A Standard Platform for Testing and Comparison of MDAO Architectures

NASA Technical Reports Server (NTRS)

Gray, Justin S.; Moore, Kenneth T.; Hearn, Tristan A.; Naylor, Bret A.

2012-01-01

The Multidisciplinary Design Analysis and Optimization (MDAO) community has developed a multitude of algorithms and techniques, called architectures, for performing optimizations on complex engineering systems which involve coupling between multiple discipline analyses. These architectures seek to efficiently handle optimizations with computationally expensive analyses including multiple disciplines. We propose a new testing procedure that can provide a quantitative and qualitative means of comparison among architectures. The proposed test procedure is implemented within the open source framework, OpenMDAO, and comparative results are presented for five well-known architectures: MDF, IDF, CO, BLISS, and BLISS-2000. We also demonstrate how using open source soft- ware development methods can allow the MDAO community to submit new problems and architectures to keep the test suite relevant.

Algorithm Updates for the Fourth SeaWiFS Data Reprocessing

NASA Technical Reports Server (NTRS)

Hooker, Stanford, B. (Editor); Firestone, Elaine R. (Editor); Patt, Frederick S.; Barnes, Robert A.; Eplee, Robert E., Jr.; Franz, Bryan A.; Robinson, Wayne D.; Feldman, Gene Carl; Bailey, Sean W.

2003-01-01

The efforts to improve the data quality for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data products have continued, following the third reprocessing of the global data set in May 2000. Analyses have been ongoing to address all aspects of the processing algorithms, particularly the calibration methodologies, atmospheric correction, and data flagging and masking. All proposed changes were subjected to rigorous testing, evaluation and validation. The results of these activities culminated in the fourth reprocessing, which was completed in July 2002. The algorithm changes, which were implemented for this reprocessing, are described in the chapters of this volume. Chapter 1 presents an overview of the activities leading up to the fourth reprocessing, and summarizes the effects of the changes. Chapter 2 describes the modifications to the on-orbit calibration, specifically the focal plane temperature correction and the temporal dependence. Chapter 3 describes the changes to the vicarious calibration, including the stray light correction to the Marine Optical Buoy (MOBY) data and improved data screening procedures. Chapter 4 describes improvements to the near-infrared (NIR) band correction algorithm. Chapter 5 describes changes to the atmospheric correction and the oceanic property retrieval algorithms, including out-of-band corrections, NIR noise reduction, and handling of unusual conditions. Chapter 6 describes various changes to the flags and masks, to increase the number of valid retrievals, improve the detection of the flag conditions, and add new flags. Chapter 7 describes modifications to the level-la and level-3 algorithms, to improve the navigation accuracy, correct certain types of spacecraft time anomalies, and correct a binning logic error. Chapter 8 describes the algorithm used to generate the SeaWiFS photosynthetically available radiation (PAR) product. Chapter 9 describes a coupled ocean-atmosphere model, which is used in one of the changes described in Chapter 4. Finally, Chapter 10 describes a comparison of results from the third and fourth reprocessings along the US. Northeast coast.

A procedure for testing the quality of LANDSAT atmospheric correction algorithms

NASA Technical Reports Server (NTRS)

Dias, L. A. V. (Principal Investigator); Vijaykumar, N. L.; Neto, G. C.

1982-01-01

There are two basic methods for testing the quality of an algorithm to minimize atmospheric effects on LANDSAT imagery: (1) test the results a posteriori, using ground truth or control points; (2) use a method based on image data plus estimation of additional ground and/or atmospheric parameters. A procedure based on the second method is described. In order to select the parameters, initially the image contrast is examined for a series of parameter combinations. The contrast improves for better corrections. In addition the correlation coefficient between two subimages, taken at different times, of the same scene is used for parameter's selection. The regions to be correlated should not have changed considerably in time. A few examples using this proposed procedure are presented.

A numerical similarity approach for using retired Current Procedural Terminology (CPT) codes for electronic phenotyping in the Scalable Collaborative Infrastructure for a Learning Health System (SCILHS).

PubMed

Klann, Jeffrey G; Phillips, Lori C; Turchin, Alexander; Weiler, Sarah; Mandl, Kenneth D; Murphy, Shawn N

2015-12-11

Interoperable phenotyping algorithms, needed to identify patient cohorts meeting eligibility criteria for observational studies or clinical trials, require medical data in a consistent structured, coded format. Data heterogeneity limits such algorithms' applicability. Existing approaches are often: not widely interoperable; or, have low sensitivity due to reliance on the lowest common denominator (ICD-9 diagnoses). In the Scalable Collaborative Infrastructure for a Learning Healthcare System (SCILHS) we endeavor to use the widely-available Current Procedural Terminology (CPT) procedure codes with ICD-9. Unfortunately, CPT changes drastically year-to-year - codes are retired/replaced. Longitudinal analysis requires grouping retired and current codes. BioPortal provides a navigable CPT hierarchy, which we imported into the Informatics for Integrating Biology and the Bedside (i2b2) data warehouse and analytics platform. However, this hierarchy does not include retired codes. We compared BioPortal's 2014AA CPT hierarchy with Partners Healthcare's SCILHS datamart, comprising three-million patients' data over 15 years. 573 CPT codes were not present in 2014AA (6.5 million occurrences). No existing terminology provided hierarchical linkages for these missing codes, so we developed a method that automatically places missing codes in the most specific "grouper" category, using the numerical similarity of CPT codes. Two informaticians reviewed the results. We incorporated the final table into our i2b2 SCILHS/PCORnet ontology, deployed it at seven sites, and performed a gap analysis and an evaluation against several phenotyping algorithms. The reviewers found the method placed the code correctly with 97 % precision when considering only miscategorizations ("correctness precision") and 52 % precision using a gold-standard of optimal placement ("optimality precision"). High correctness precision meant that codes were placed in a reasonable hierarchal position that a reviewer can quickly validate. Lower optimality precision meant that codes were not often placed in the optimal hierarchical subfolder. The seven sites encountered few occurrences of codes outside our ontology, 93 % of which comprised just four codes. Our hierarchical approach correctly grouped retired and non-retired codes in most cases and extended the temporal reach of several important phenotyping algorithms. We developed a simple, easily-validated, automated method to place retired CPT codes into the BioPortal CPT hierarchy. This complements existing hierarchical terminologies, which do not include retired codes. The approach's utility is confirmed by the high correctness precision and successful grouping of retired with non-retired codes.

Fast clustering using adaptive density peak detection.

PubMed

Wang, Xiao-Feng; Xu, Yifan

2017-12-01

Common limitations of clustering methods include the slow algorithm convergence, the instability of the pre-specification on a number of intrinsic parameters, and the lack of robustness to outliers. A recent clustering approach proposed a fast search algorithm of cluster centers based on their local densities. However, the selection of the key intrinsic parameters in the algorithm was not systematically investigated. It is relatively difficult to estimate the "optimal" parameters since the original definition of the local density in the algorithm is based on a truncated counting measure. In this paper, we propose a clustering procedure with adaptive density peak detection, where the local density is estimated through the nonparametric multivariate kernel estimation. The model parameter is then able to be calculated from the equations with statistical theoretical justification. We also develop an automatic cluster centroid selection method through maximizing an average silhouette index. The advantage and flexibility of the proposed method are demonstrated through simulation studies and the analysis of a few benchmark gene expression data sets. The method only needs to perform in one single step without any iteration and thus is fast and has a great potential to apply on big data analysis. A user-friendly R package ADPclust is developed for public use.

Crystal Identification in Dual-Layer-Offset DOI-PET Detectors Using Stratified Peak Tracking Based on SVD and Mean-Shift Algorithm

NASA Astrophysics Data System (ADS)

Wei, Qingyang; Dai, Tiantian; Ma, Tianyu; Liu, Yaqiang; Gu, Yu

2016-10-01

An Anger-logic based pixelated PET detector block requires a crystal position map (CPM) to assign the position of each detected event to a most probable crystal index. Accurate assignments are crucial to PET imaging performance. In this paper, we present a novel automatic approach to generate the CPMs for dual-layer offset (DLO) PET detectors using a stratified peak tracking method. In which, the top and bottom layers are distinguished by their intensity difference and the peaks of the top and bottom layers are tracked based on a singular value decomposition (SVD) and mean-shift algorithm in succession. The CPM is created by classifying each pixel to its nearest peak and assigning the pixel with the crystal index of that peak. A Matlab-based graphical user interface program was developed including the automatic algorithm and a manual interaction procedure. The algorithm was tested for three DLO PET detector blocks. Results show that the proposed method exhibits good performance as well as robustness for all the three blocks. Compared to the existing methods, our approach can directly distinguish the layer and crystal indices using the information of intensity and offset grid pattern.

Quantum computation and analysis of Wigner and Husimi functions: toward a quantum image treatment.

PubMed

Terraneo, M; Georgeot, B; Shepelyansky, D L

2005-06-01

We study the efficiency of quantum algorithms which aim at obtaining phase-space distribution functions of quantum systems. Wigner and Husimi functions are considered. Different quantum algorithms are envisioned to build these functions, and compared with the classical computation. Different procedures to extract more efficiently information from the final wave function of these algorithms are studied, including coarse-grained measurements, amplitude amplification, and measure of wavelet-transformed wave function. The algorithms are analyzed and numerically tested on a complex quantum system showing different behavior depending on parameters: namely, the kicked rotator. The results for the Wigner function show in particular that the use of the quantum wavelet transform gives a polynomial gain over classical computation. For the Husimi distribution, the gain is much larger than for the Wigner function and is larger with the help of amplitude amplification and wavelet transforms. We discuss the generalization of these results to the simulation of other quantum systems. We also apply the same set of techniques to the analysis of real images. The results show that the use of the quantum wavelet transform allows one to lower dramatically the number of measurements needed, but at the cost of a large loss of information.

Accelerated Training for Large Feedforward Neural Networks

NASA Technical Reports Server (NTRS)

Stepniewski, Slawomir W.; Jorgensen, Charles C.

1998-01-01

In this paper we introduce a new training algorithm, the scaled variable metric (SVM) method. Our approach attempts to increase the convergence rate of the modified variable metric method. It is also combined with the RBackprop algorithm, which computes the product of the matrix of second derivatives (Hessian) with an arbitrary vector. The RBackprop method allows us to avoid computationally expensive, direct line searches. In addition, it can be utilized in the new, 'predictive' updating technique of the inverse Hessian approximation. We have used directional slope testing to adjust the step size and found that this strategy works exceptionally well in conjunction with the Rbackprop algorithm. Some supplementary, but nevertheless important enhancements to the basic training scheme such as improved setting of a scaling factor for the variable metric update and computationally more efficient procedure for updating the inverse Hessian approximation are presented as well. We summarize by comparing the SVM method with four first- and second- order optimization algorithms including a very effective implementation of the Levenberg-Marquardt method. Our tests indicate promising computational speed gains of the new training technique, particularly for large feedforward networks, i.e., for problems where the training process may be the most laborious.

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters. Part 1; Equivalent Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, Galina; DaSilva, Arlindo M.; Norris, Peter M.; Platnick, Steven E.

2013-01-01

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters . Pt. 1; Synthetic Sensor Radiance Formulation; [Synthetic Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, G.; DaSilva, A. M.; Norris, P. M.; Platnick, S.

2013-01-01

In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

Time series segmentation: a new approach based on Genetic Algorithm and Hidden Markov Model

NASA Astrophysics Data System (ADS)

Toreti, A.; Kuglitsch, F. G.; Xoplaki, E.; Luterbacher, J.

2009-04-01

The subdivision of a time series into homogeneous segments has been performed using various methods applied to different disciplines. In climatology, for example, it is accompanied by the well-known homogenization problem and the detection of artificial change points. In this context, we present a new method (GAMM) based on Hidden Markov Model (HMM) and Genetic Algorithm (GA), applicable to series of independent observations (and easily adaptable to autoregressive processes). A left-to-right hidden Markov model, estimating the parameters and the best-state sequence, respectively, with the Baum-Welch and Viterbi algorithms, was applied. In order to avoid the well-known dependence of the Baum-Welch algorithm on the initial condition, a Genetic Algorithm was developed. This algorithm is characterized by mutation, elitism and a crossover procedure implemented with some restrictive rules. Moreover the function to be minimized was derived following the approach of Kehagias (2004), i.e. it is the so-called complete log-likelihood. The number of states was determined applying a two-fold cross-validation procedure (Celeux and Durand, 2008). Being aware that the last issue is complex, and it influences all the analysis, a Multi Response Permutation Procedure (MRPP; Mielke et al., 1981) was inserted. It tests the model with K+1 states (where K is the state number of the best model) if its likelihood is close to K-state model. Finally, an evaluation of the GAMM performances, applied as a break detection method in the field of climate time series homogenization, is shown. 1. G. Celeux and J.B. Durand, Comput Stat 2008. 2. A. Kehagias, Stoch Envir Res 2004. 3. P.W. Mielke, K.J. Berry, G.W. Brier, Monthly Wea Rev 1981.

a Hadoop-Based Algorithm of Generating dem Grid from Point Cloud Data

NASA Astrophysics Data System (ADS)

Jian, X.; Xiao, X.; Chengfang, H.; Zhizhong, Z.; Zhaohui, W.; Dengzhong, Z.

2015-04-01

Airborne LiDAR technology has proven to be the most powerful tools to obtain high-density, high-accuracy and significantly detailed surface information of terrain and surface objects within a short time, and from which the Digital Elevation Model of high quality can be extracted. Point cloud data generated from the pre-processed data should be classified by segmentation algorithms, so as to differ the terrain points from disorganized points, then followed by a procedure of interpolating the selected points to turn points into DEM data. The whole procedure takes a long time and huge computing resource due to high-density, that is concentrated on by a number of researches. Hadoop is a distributed system infrastructure developed by the Apache Foundation, which contains a highly fault-tolerant distributed file system (HDFS) with high transmission rate and a parallel programming model (Map/Reduce). Such a framework is appropriate for DEM generation algorithms to improve efficiency. Point cloud data of Dongting Lake acquired by Riegl LMS-Q680i laser scanner was utilized as the original data to generate DEM by a Hadoop-based algorithms implemented in Linux, then followed by another traditional procedure programmed by C++ as the comparative experiment. Then the algorithm's efficiency, coding complexity, and performance-cost ratio were discussed for the comparison. The results demonstrate that the algorithm's speed depends on size of point set and density of DEM grid, and the non-Hadoop implementation can achieve a high performance when memory is big enough, but the multiple Hadoop implementation can achieve a higher performance-cost ratio, while point set is of vast quantities on the other hand.

Conformally Invariant Powers of the Laplacian, Q-Curvature, and Tractor Calculus

NASA Astrophysics Data System (ADS)

Gover, A. Rod; Peterson, Lawrence J.

We describe an elementary algorithm for expressing, as explicit formulae in tractor calculus, the conformally invariant GJMS operators due to C.R. Graham et alia. These differential operators have leading part a power of the Laplacian. Conformal tractor calculus is the natural induced bundle calculus associated to the conformal Cartan connection. Applications discussed include standard formulae for these operators in terms of the Levi-Civita connection and its curvature and a direct definition and formula for T. Branson's so-called Q-curvature (which integrates to a global conformal invariant) as well as generalisations of the operators and the Q-curvature. Among examples, the operators of order 4, 6 and 8 and the related Q-curvatures are treated explicitly. The algorithm exploits the ambient metric construction of Fefferman and Graham and includes a procedure for converting the ambient curvature and its covariant derivatives into tractor calculus expressions. This is partly based on [12], where the relationship of the normal standard tractor bundle to the ambient construction is described.

PyVCI: A flexible open-source code for calculating accurate molecular infrared spectra

NASA Astrophysics Data System (ADS)

Sibaev, Marat; Crittenden, Deborah L.

2016-06-01

The PyVCI program package is a general purpose open-source code for simulating accurate molecular spectra, based upon force field expansions of the potential energy surface in normal mode coordinates. It includes harmonic normal coordinate analysis and vibrational configuration interaction (VCI) algorithms, implemented primarily in Python for accessibility but with time-consuming routines written in C. Coriolis coupling terms may be optionally included in the vibrational Hamiltonian. Non-negligible VCI matrix elements are stored in sparse matrix format to alleviate the diagonalization problem. CPU and memory requirements may be further controlled by algorithmic choices and/or numerical screening procedures, and recommended values are established by benchmarking using a test set of 44 molecules for which accurate analytical potential energy surfaces are available. Force fields in normal mode coordinates are obtained from the PyPES library of high quality analytical potential energy surfaces (to 6th order) or by numerical differentiation of analytic second derivatives generated using the GAMESS quantum chemical program package (to 4th order).

An algorithm for converting a virtual-bond chain into a complete polypeptide backbone chain

NASA Technical Reports Server (NTRS)

Luo, N.; Shibata, M.; Rein, R.

1991-01-01

A systematic analysis is presented of the algorithm for converting a virtual-bond chain, defined by the coordinates of the alpha-carbons of a given protein, into a complete polypeptide backbone. An alternative algorithm, based upon the same set of geometric parameters used in the Purisima-Scheraga algorithm but with a different "linkage map" of the algorithmic procedures, is proposed. The global virtual-bond chain geometric constraints are more easily separable from the loal peptide geometric and energetic constraints derived from, for example, the Ramachandran criterion, within the framework of this approach.

One-dimensional swarm algorithm packaging

NASA Astrophysics Data System (ADS)

Lebedev, Boris K.; Lebedev, Oleg B.; Lebedeva, Ekaterina O.

2018-05-01

The paper considers an algorithm for solving the problem of onedimensional packaging based on the adaptive behavior model of an ant colony. The key role in the development of the ant algorithm is the choice of representation (interpretation) of the solution. The structure of the solution search graph, the procedure for finding solutions on the graph, the methods of deposition and evaporation of pheromone are described. Unlike the canonical paradigm of an ant algorithm, an ant on the solution search graph generates sets of elements distributed across blocks. Experimental studies were conducted on IBM PC. Compared with the existing algorithms, the results are improved.

Learning algorithm in restricted Boltzmann machines using Kullback-Leibler importance estimation procedure

NASA Astrophysics Data System (ADS)

Yasuda, Muneki; Sakurai, Tetsuharu; Tanaka, Kazuyuki

Restricted Boltzmann machines (RBMs) are bipartite structured statistical neural networks and consist of two layers. One of them is a layer of visible units and the other one is a layer of hidden units. In each layer, any units do not connect to each other. RBMs have high flexibility and rich structure and have been expected to applied to various applications, for example, image and pattern recognitions, face detections and so on. However, most of computational models in RBMs are intractable and often belong to the class of NP-hard problem. In this paper, in order to construct a practical learning algorithm for them, we employ the Kullback-Leibler Importance Estimation Procedure (KLIEP) to RBMs, and give a new scheme of practical approximate learning algorithm for RBMs based on the KLIEP.

Development of Advanced Verification and Validation Procedures and Tools for the Certification of Learning Systems in Aerospace Applications

NASA Technical Reports Server (NTRS)

Jacklin, Stephen; Schumann, Johann; Gupta, Pramod; Richard, Michael; Guenther, Kurt; Soares, Fola

2005-01-01

Adaptive control technologies that incorporate learning algorithms have been proposed to enable automatic flight control and vehicle recovery, autonomous flight, and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments. In order for adaptive control systems to be used in safety-critical aerospace applications, they must be proven to be highly safe and reliable. Rigorous methods for adaptive software verification and validation must be developed to ensure that control system software failures will not occur. Of central importance in this regard is the need to establish reliable methods that guarantee convergent learning, rapid convergence (learning) rate, and algorithm stability. This paper presents the major problems of adaptive control systems that use learning to improve performance. The paper then presents the major procedures and tools presently developed or currently being developed to enable the verification, validation, and ultimate certification of these adaptive control systems. These technologies include the application of automated program analysis methods, techniques to improve the learning process, analytical methods to verify stability, methods to automatically synthesize code, simulation and test methods, and tools to provide on-line software assurance.

Implementation of the multi-channel monolith reactor in an optimisation procedure for heterogeneous oxidation catalysts based on genetic algorithms.

PubMed

Breuer, Christian; Lucas, Martin; Schütze, Frank-Walter; Claus, Peter

2007-01-01

A multi-criteria optimisation procedure based on genetic algorithms is carried out in search of advanced heterogeneous catalysts for total oxidation. Simple but flexible software routines have been created to be applied within a search space of more then 150,000 individuals. The general catalyst design includes mono-, bi- and trimetallic compositions assembled out of 49 different metals and depleted on an Al2O3 support in up to nine amount levels. As an efficient tool for high-throughput screening and perfectly matched to the requirements of heterogeneous gas phase catalysis - especially for applications technically run in honeycomb structures - the multi-channel monolith reactor is implemented to evaluate the catalyst performances. Out of a multi-component feed-gas, the conversion rates of carbon monoxide (CO) and a model hydrocarbon (HC) are monitored in parallel. In combination with further restrictions to preparation and pre-treatment a primary screening can be conducted, promising to provide results close to technically applied catalysts. Presented are the resulting performances of the optimisation process for the first catalyst generations and the prospect of its auto-adaptation to specified optimisation goals.

Kinematic modelling of disc galaxies using graphics processing units

NASA Astrophysics Data System (ADS)

Bekiaris, G.; Glazebrook, K.; Fluke, C. J.; Abraham, R.

2016-01-01

With large-scale integral field spectroscopy (IFS) surveys of thousands of galaxies currently under-way or planned, the astronomical community is in need of methods, techniques and tools that will allow the analysis of huge amounts of data. We focus on the kinematic modelling of disc galaxies and investigate the potential use of massively parallel architectures, such as the graphics processing unit (GPU), as an accelerator for the computationally expensive model-fitting procedure. We review the algorithms involved in model-fitting and evaluate their suitability for GPU implementation. We employ different optimization techniques, including the Levenberg-Marquardt and nested sampling algorithms, but also a naive brute-force approach based on nested grids. We find that the GPU can accelerate the model-fitting procedure up to a factor of ˜100 when compared to a single-threaded CPU, and up to a factor of ˜10 when compared to a multithreaded dual CPU configuration. Our method's accuracy, precision and robustness are assessed by successfully recovering the kinematic properties of simulated data, and also by verifying the kinematic modelling results of galaxies from the GHASP and DYNAMO surveys as found in the literature. The resulting GBKFIT code is available for download from: http://supercomputing.swin.edu.au/gbkfit.

Application of different spectrophotometric methods for simultaneous determination of elbasvir and grazoprevir in pharmaceutical preparation

NASA Astrophysics Data System (ADS)

Attia, Khalid A. M.; El-Abasawi, Nasr M.; El-Olemy, Ahmed; Abdelazim, Ahmed H.

2018-01-01

The first three UV spectrophotometric methods have been developed of simultaneous determination of two new FDA approved drugs namely; elbasvir and grazoprevir in their combined pharmaceutical dosage form. These methods include simultaneous equation, partial least squares with and without variable selection procedure (genetic algorithm). For simultaneous equation method, the absorbance values at 369 (λmax of elbasvir) and 253 nm (λmax of grazoprevir) have been selected for the formation of two simultaneous equations required for the mathematical processing and quantitative analysis of the studied drugs. Alternatively, the partial least squares with and without variable selection procedure (genetic algorithm) have been applied in the spectra analysis because the synchronous inclusion of many unreal wavelengths rather than by using a single or dual wavelength which greatly increases the precision and predictive ability of the methods. Successfully assay of the drugs in their pharmaceutical formulation has been done by the proposed methods. Statistically comparative analysis for the obtained results with the manufacturing methods has been performed. It is noteworthy to mention that there was no significant difference between the proposed methods and the manufacturing one with respect to the validation parameters.

Confidence intervals for expected moments algorithm flood quantile estimates

USGS Publications Warehouse

Cohn, Timothy A.; Lane, William L.; Stedinger, Jery R.

2001-01-01

Historical and paleoflood information can substantially improve flood frequency estimates if appropriate statistical procedures are properly applied. However, the Federal guidelines for flood frequency analysis, set forth in Bulletin 17B, rely on an inefficient “weighting” procedure that fails to take advantage of historical and paleoflood information. This has led researchers to propose several more efficient alternatives including the Expected Moments Algorithm (EMA), which is attractive because it retains Bulletin 17B's statistical structure (method of moments with the Log Pearson Type 3 distribution) and thus can be easily integrated into flood analyses employing the rest of the Bulletin 17B approach. The practical utility of EMA, however, has been limited because no closed‐form method has been available for quantifying the uncertainty of EMA‐based flood quantile estimates. This paper addresses that concern by providing analytical expressions for the asymptotic variance of EMA flood‐quantile estimators and confidence intervals for flood quantile estimates. Monte Carlo simulations demonstrate the properties of such confidence intervals for sites where a 25‐ to 100‐year streamgage record is augmented by 50 to 150 years of historical information. The experiments show that the confidence intervals, though not exact, should be acceptable for most purposes.

Universal test fixture for monolithic mm-wave integrated circuits calibrated with an augmented TRD algorithm

NASA Technical Reports Server (NTRS)

Romanofsky, Robert R.; Shalkhauser, Kurt A.

1989-01-01

The design and evaluation of a novel fixturing technique for characterizing millimeter wave solid state devices is presented. The technique utilizes a cosine-tapered ridge guide fixture and a one-tier de-embedding procedure to produce accurate and repeatable device level data. Advanced features of this technique include nondestructive testing, full waveguide bandwidth operation, universality of application, and rapid, yet repeatable, chip-level characterization. In addition, only one set of calibration standards is required regardless of the device geometry.

Preliminary Evaluation of the Radiometric Calibration of LANDSAT-4 Thematic Mapper Data by the Canada Centre for Remote Sensing

NASA Technical Reports Server (NTRS)

Murphy, J.; Park, W.; Fitzgerald, A.

1985-01-01

The radiometric characteristics of the LANDSAT-4 TM sensor are being studied with a view to developing absolute and relative radiometric calibration procedures. Preliminary results from several different approaches to the relative correction of all detectors within each band are reported. Topics covered include: the radiometric correction method; absolute calibration; the relative radiometric calibration algorithm; relative gain and offset calibration; relative gain and offset observations; and residual radiometric stripping.

Characterization and Performance of the Suomi-NPP VIIRS Solar Diffuser Stability Monitor

NASA Technical Reports Server (NTRS)

Fulbright, Jon P.; Ning, Lei; Kwofu, Chiang; Xiaoxiong, Xiong

2012-01-01

We describe the on-orbit characterization and performance of the Solar Diffuser Stability Monitor (SDSM) on-board Suomi-NPP/VIIRS. This description includes the observing procedure of each SDSM event, the algorithms used to generate the Solar Diffuser degradation corrective factors, and the results for the mission to date. We will also compare the performance of the VIIRS SDSM and SD to the similar components operating on the MODIS instrument on the EOS Terra and Aqua satellites

Systems Design and Pilot Operation of a Regional Center for Technical Processing for the Libraries of the New England State Universities. NELINET, New England Library Information Network. Progress Report, July 1, 1967 - March 30, 1968, Volume II, Appendices.

ERIC Educational Resources Information Center

Agenbroad, James E.; And Others

Included in this volume of appendices to LI 000 979 are acquisitions flow charts; a current operations questionnaire; an algorithm for splitting the Library of Congress call number; analysis of the Machine-Readable Cataloging (MARC II) format; production problems and decisions; operating procedures for information transmittal in the New England…

RECEPTOR MODELING OF AMBIENT PARTICULATE MATTER DATA USING POSITIVE MATRIX FACTORIZATION REVIEW OF EXISTING METHODS

EPA Science Inventory

Methods for apportioning sources of ambient particulate matter (PM) using the positive matrix factorization (PMF) algorithm are reviewed. Numerous procedural decisions must be made and algorithmic parameters selected when analyzing PM data with PMF. However, few publications docu...

A Novel Artificial Bee Colony Algorithm Based on Internal-Feedback Strategy for Image Template Matching

PubMed Central

Gong, Li-Gang

2014-01-01

Image template matching refers to the technique of locating a given reference image over a source image such that they are the most similar. It is a fundamental mission in the field of visual target recognition. In general, there are two critical aspects of a template matching scheme. One is similarity measurement and the other is best-match location search. In this work, we choose the well-known normalized cross correlation model as a similarity criterion. The searching procedure for the best-match location is carried out through an internal-feedback artificial bee colony (IF-ABC) algorithm. IF-ABC algorithm is highlighted by its effort to fight against premature convergence. This purpose is achieved through discarding the conventional roulette selection procedure in the ABC algorithm so as to provide each employed bee an equal chance to be followed by the onlooker bees in the local search phase. Besides that, we also suggest efficiently utilizing the internal convergence states as feedback guidance for searching intensity in the subsequent cycles of iteration. We have investigated four ideal template matching cases as well as four actual cases using different searching algorithms. Our simulation results show that the IF-ABC algorithm is more effective and robust for this template matching mission than the conventional ABC and two state-of-the-art modified ABC algorithms do. PMID:24892107

Estimation of radiative and conductive properties of a semitransparent medium using genetic algorithms

NASA Astrophysics Data System (ADS)

Braiek, A.; Adili, A.; Albouchi, F.; Karkri, M.; Ben Nasrallah, S.

2016-06-01

The aim of this work is to simultaneously identify the conductive and radiative parameters of a semitransparent sample using a photothermal method associated with an inverse problem. The identification of the conductive and radiative proprieties is performed by the minimization of an objective function that represents the errors between calculated temperature and measured signal. The calculated temperature is obtained from a theoretical model built with the thermal quadrupole formalism. Measurement is obtained in the rear face of the sample whose front face is excited by a crenel of heat flux. For identification procedure, a genetic algorithm is developed and used. The genetic algorithm is a useful tool in the simultaneous estimation of correlated or nearly correlated parameters, which can be a limiting factor for the gradient-based methods. The results of the identification procedure show the efficiency and the stability of the genetic algorithm to simultaneously estimate the conductive and radiative properties of clear glass.

A direct-gradient multivariate index of biotic condition

USGS Publications Warehouse

Miranda, Leandro E.; Aycock, J.N.; Killgore, K. J.

2012-01-01

Multimetric indexes constructed by summing metric scores have been criticized despite many of their merits. A leading criticism is the potential for investigator bias involved in metric selection and scoring. Often there is a large number of competing metrics equally well correlated with environmental stressors, requiring a judgment call by the investigator to select the most suitable metrics to include in the index and how to score them. Data-driven procedures for multimetric index formulation published during the last decade have reduced this limitation, yet apprehension remains. Multivariate approaches that select metrics with statistical algorithms may reduce the level of investigator bias and alleviate a weakness of multimetric indexes. We investigated the suitability of a direct-gradient multivariate procedure to derive an index of biotic condition for fish assemblages in oxbow lakes in the Lower Mississippi Alluvial Valley. Although this multivariate procedure also requires that the investigator identify a set of suitable metrics potentially associated with a set of environmental stressors, it is different from multimetric procedures because it limits investigator judgment in selecting a subset of biotic metrics to include in the index and because it produces metric weights suitable for computation of index scores. The procedure, applied to a sample of 35 competing biotic metrics measured at 50 oxbow lakes distributed over a wide geographical region in the Lower Mississippi Alluvial Valley, selected 11 metrics that adequately indexed the biotic condition of five test lakes. Because the multivariate index includes only metrics that explain the maximum variability in the stressor variables rather than a balanced set of metrics chosen to reflect various fish assemblage attributes, it is fundamentally different from multimetric indexes of biotic integrity with advantages and disadvantages. As such, it provides an alternative to multimetric procedures.

AMLSA Algorithm for Hybrid Precoding in Millimeter Wave MIMO Systems

NASA Astrophysics Data System (ADS)

Liu, Fulai; Sun, Zhenxing; Du, Ruiyan; Bai, Xiaoyu

2017-10-01

In this paper, an effective algorithm will be proposed for hybrid precoding in mmWave MIMO systems, referred to as alternating minimization algorithm with the least squares amendment (AMLSA algorithm). To be specific, for the fully-connected structure, the presented algorithm is exploited to minimize the classical objective function and obtain the hybrid precoding matrix. It introduces an orthogonal constraint to the digital precoding matrix which is amended subsequently by the least squares after obtaining its alternating minimization iterative result. Simulation results confirm that the achievable spectral efficiency of our proposed algorithm is better to some extent than that of the existing algorithm without the least squares amendment. Furthermore, the number of iterations is reduced slightly via improving the initialization procedure.

Automatic extraction of numeric strings in unconstrained handwritten document images

NASA Astrophysics Data System (ADS)

Haji, M. Mehdi; Bui, Tien D.; Suen, Ching Y.

2011-01-01

Numeric strings such as identification numbers carry vital pieces of information in documents. In this paper, we present a novel algorithm for automatic extraction of numeric strings in unconstrained handwritten document images. The algorithm has two main phases: pruning and verification. In the pruning phase, the algorithm first performs a new segment-merge procedure on each text line, and then using a new regularity measure, it prunes all sequences of characters that are unlikely to be numeric strings. The segment-merge procedure is composed of two modules: a new explicit character segmentation algorithm which is based on analysis of skeletal graphs and a merging algorithm which is based on graph partitioning. All the candidate sequences that pass the pruning phase are sent to a recognition-based verification phase for the final decision. The recognition is based on a coarse-to-fine approach using probabilistic RBF networks. We developed our algorithm for the processing of real-world documents where letters and digits may be connected or broken in a document. The effectiveness of the proposed approach is shown by extensive experiments done on a real-world database of 607 documents which contains handwritten, machine-printed and mixed documents with different types of layouts and levels of noise.

Towards automated visual flexible endoscope navigation.

PubMed

van der Stap, Nanda; van der Heijden, Ferdinand; Broeders, Ivo A M J

2013-10-01

The design of flexible endoscopes has not changed significantly in the past 50 years. A trend is observed towards a wider application of flexible endoscopes with an increasing role in complex intraluminal therapeutic procedures. The nonintuitive and nonergonomical steering mechanism now forms a barrier in the extension of flexible endoscope applications. Automating the navigation of endoscopes could be a solution for this problem. This paper summarizes the current state of the art in image-based navigation algorithms. The objectives are to find the most promising navigation system(s) to date and to indicate fields for further research. A systematic literature search was performed using three general search terms in two medical-technological literature databases. Papers were included according to the inclusion criteria. A total of 135 papers were analyzed. Ultimately, 26 were included. Navigation often is based on visual information, which means steering the endoscope using the images that the endoscope produces. Two main techniques are described: lumen centralization and visual odometry. Although the research results are promising, no successful, commercially available automated flexible endoscopy system exists to date. Automated systems that employ conventional flexible endoscopes show the most promising prospects in terms of cost and applicability. To produce such a system, the research focus should lie on finding low-cost mechatronics and technologically robust steering algorithms. Additional functionality and increased efficiency can be obtained through software development. The first priority is to find real-time, robust steering algorithms. These algorithms need to handle bubbles, motion blur, and other image artifacts without disrupting the steering process.

A systematic review of validated methods to capture acute bronchospasm using administrative or claims data.

PubMed

Sharifi, Mona; Krishanswami, Shanthi; McPheeters, Melissa L

2013-12-30

To identify and assess billing, procedural, or diagnosis code, or pharmacy claim-based algorithms used to identify acute bronchospasm in administrative and claims databases. We searched the MEDLINE database from 1991 to September 2012 using controlled vocabulary and key terms related to bronchospasm, wheeze and acute asthma. We also searched the reference lists of included studies. Two investigators independently assessed the full text of studies against pre-determined inclusion criteria. Two reviewers independently extracted data regarding participant and algorithm characteristics. Our searches identified 677 citations of which 38 met our inclusion criteria. In these 38 studies, the most commonly used ICD-9 code was 493.x. Only 3 studies reported any validation methods for the identification of bronchospasm, wheeze or acute asthma in administrative and claims databases; all were among pediatric populations and only 2 offered any validation statistics. Some of the outcome definitions utilized were heterogeneous and included other disease based diagnoses, such as bronchiolitis and pneumonia, which are typically of an infectious etiology. One study offered the validation of algorithms utilizing Emergency Department triage chief complaint codes to diagnose acute asthma exacerbations with ICD-9 786.07 (wheezing) revealing the highest sensitivity (56%), specificity (97%), PPV (93.5%) and NPV (76%). There is a paucity of studies reporting rigorous methods to validate algorithms for the identification of bronchospasm in administrative data. The scant validated data available are limited in their generalizability to broad-based populations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Fuzzy Classification of Ocean Color Satellite Data for Bio-optical Algorithm Constituent Retrievals

NASA Technical Reports Server (NTRS)

Campbell, Janet W.

1998-01-01

The ocean has been traditionally viewed as a 2 class system. Morel and Prieur (1977) classified ocean water according to the dominant absorbent particle suspended in the water column. Case 1 is described as having a high concentration of phytoplankton (and detritus) relative to other particles. Conversely, case 2 is described as having inorganic particles such as suspended sediments in high concentrations. Little work has gone into the problem of mixing bio-optical models for these different water types. An approach is put forth here to blend bio-optical algorithms based on a fuzzy classification scheme. This scheme involves two procedures. First, a clustering procedure identifies classes and builds class statistics from in-situ optical measurements. Next, a classification procedure assigns satellite pixels partial memberships to these classes based on their ocean color reflectance signature. These membership assignments can be used as the basis for a weighting retrievals from class-specific bio-optical algorithms. This technique is demonstrated with in-situ optical measurements and an image from the SeaWiFS ocean color satellite.

Exact BPF and FBP algorithms for nonstandard saddle curves.

PubMed

Yu, Hengyong; Zhao, Shiying; Ye, Yangbo; Wang, Ge

2005-11-01

A hot topic in cone-beam CT research is exact cone-beam reconstruction from a general scanning trajectory. Particularly, a nonstandard saddle curve attracts attention, as this construct allows the continuous periodic scanning of a volume-of-interest (VOI). Here we evaluate two algorithms for reconstruction from data collected along a nonstandard saddle curve, which are in the filtered backprojection (FBP) and backprojection filtration (BPF) formats, respectively. Both the algorithms are implemented in a chord-based coordinate system. Then, a rebinning procedure is utilized to transform the reconstructed results into the natural coordinate system. The simulation results demonstrate that the FBP algorithm produces better image quality than the BPF algorithm, while both the algorithms exhibit similar noise characteristics.

Greedy Algorithms for Nonnegativity-Constrained Simultaneous Sparse Recovery

PubMed Central

Kim, Daeun; Haldar, Justin P.

2016-01-01

This work proposes a family of greedy algorithms to jointly reconstruct a set of vectors that are (i) nonnegative and (ii) simultaneously sparse with a shared support set. The proposed algorithms generalize previous approaches that were designed to impose these constraints individually. Similar to previous greedy algorithms for sparse recovery, the proposed algorithms iteratively identify promising support indices. In contrast to previous approaches, the support index selection procedure has been adapted to prioritize indices that are consistent with both the nonnegativity and shared support constraints. Empirical results demonstrate for the first time that the combined use of simultaneous sparsity and nonnegativity constraints can substantially improve recovery performance relative to existing greedy algorithms that impose less signal structure. PMID:26973368

Constructing Aligned Assessments Using Automated Test Construction

ERIC Educational Resources Information Center

Porter, Andrew; Polikoff, Morgan S.; Barghaus, Katherine M.; Yang, Rui

2013-01-01

We describe an innovative automated test construction algorithm for building aligned achievement tests. By incorporating the algorithm into the test construction process, along with other test construction procedures for building reliable and unbiased assessments, the result is much more valid tests than result from current test construction…

A novel material detection algorithm based on 2D GMM-based power density function and image detail addition scheme in dual energy X-ray images.

PubMed

Pourghassem, Hossein

2012-01-01

Material detection is a vital need in dual energy X-ray luggage inspection systems at security of airport and strategic places. In this paper, a novel material detection algorithm based on statistical trainable models using 2-Dimensional power density function (PDF) of three material categories in dual energy X-ray images is proposed. In this algorithm, the PDF of each material category as a statistical model is estimated from transmission measurement values of low and high energy X-ray images by Gaussian Mixture Models (GMM). Material label of each pixel of object is determined based on dependency probability of its transmission measurement values in the low and high energy to PDF of three material categories (metallic, organic and mixed materials). The performance of material detection algorithm is improved by a maximum voting scheme in a neighborhood of image as a post-processing stage. Using two background removing and denoising stages, high and low energy X-ray images are enhanced as a pre-processing procedure. For improving the discrimination capability of the proposed material detection algorithm, the details of the low and high energy X-ray images are added to constructed color image which includes three colors (orange, blue and green) for representing the organic, metallic and mixed materials. The proposed algorithm is evaluated on real images that had been captured from a commercial dual energy X-ray luggage inspection system. The obtained results show that the proposed algorithm is effective and operative in detection of the metallic, organic and mixed materials with acceptable accuracy.

The Cardiac Safety Research Consortium ECG database.

PubMed

Kligfield, Paul; Green, Cynthia L

2012-01-01

The Cardiac Safety Research Consortium (CSRC) ECG database was initiated to foster research using anonymized, XML-formatted, digitized ECGs with corresponding descriptive variables from placebo- and positive-control arms of thorough QT studies submitted to the US Food and Drug Administration (FDA) by pharmaceutical sponsors. The database can be expanded to other data that are submitted directly to CSRC from other sources, and currently includes digitized ECGs from patients with genotyped varieties of congenital long-QT syndrome; this congenital long-QT database is also linked to ambulatory electrocardiograms stored in the Telemetric and Holter ECG Warehouse (THEW). Thorough QT data sets are available from CSRC for unblinded development of algorithms for analysis of repolarization and for blinded comparative testing of algorithms developed for the identification of moxifloxacin, as used as a positive control in thorough QT studies. Policies and procedures for access to these data sets are available from CSRC, which has developed tools for statistical analysis of blinded new algorithm performance. A recently approved CSRC project will create a data set for blinded analysis of automated ECG interval measurements, whose initial focus will include comparison of four of the major manufacturers of automated electrocardiographs in the United States. CSRC welcomes application for use of the ECG database for clinical investigation. Copyright © 2012 Elsevier Inc. All rights reserved.

Automatic red eye correction and its quality metric

NASA Astrophysics Data System (ADS)

Safonov, Ilia V.; Rychagov, Michael N.; Kang, KiMin; Kim, Sang Ho

2008-01-01

The red eye artifacts are troublesome defect of amateur photos. Correction of red eyes during printing without user intervention and making photos more pleasant for an observer are important tasks. The novel efficient technique of automatic correction of red eyes aimed for photo printers is proposed. This algorithm is independent from face orientation and capable to detect paired red eyes as well as single red eyes. The approach is based on application of 3D tables with typicalness levels for red eyes and human skin tones and directional edge detection filters for processing of redness image. Machine learning is applied for feature selection. For classification of red eye regions a cascade of classifiers including Gentle AdaBoost committee from Classification and Regression Trees (CART) is applied. Retouching stage includes desaturation, darkening and blending with initial image. Several versions of approach implementation using trade-off between detection and correction quality, processing time, memory volume are possible. The numeric quality criterion of automatic red eye correction is proposed. This quality metric is constructed by applying Analytic Hierarchy Process (AHP) for consumer opinions about correction outcomes. Proposed numeric metric helped to choose algorithm parameters via optimization procedure. Experimental results demonstrate high accuracy and efficiency of the proposed algorithm in comparison with existing solutions.

Surface registration technique for close-range mapping applications

NASA Astrophysics Data System (ADS)

Habib, Ayman F.; Cheng, Rita W. T.

2006-08-01

Close-range mapping applications such as cultural heritage restoration, virtual reality modeling for the entertainment industry, and anatomical feature recognition for medical activities require 3D data that is usually acquired by high resolution close-range laser scanners. Since these datasets are typically captured from different viewpoints and/or at different times, accurate registration is a crucial procedure for 3D modeling of mapped objects. Several registration techniques are available that work directly with the raw laser points or with extracted features from the point cloud. Some examples include the commonly known Iterative Closest Point (ICP) algorithm and a recently proposed technique based on matching spin-images. This research focuses on developing a surface matching algorithm that is based on the Modified Iterated Hough Transform (MIHT) and ICP to register 3D data. The proposed algorithm works directly with the raw 3D laser points and does not assume point-to-point correspondence between two laser scans. The algorithm can simultaneously establish correspondence between two surfaces and estimates the transformation parameters relating them. Experiment with two partially overlapping laser scans of a small object is performed with the proposed algorithm and shows successful registration. A high quality of fit between the two scans is achieved and improvement is found when compared to the results obtained using the spin-image technique. The results demonstrate the feasibility of the proposed algorithm for registering 3D laser scanning data in close-range mapping applications to help with the generation of complete 3D models.

Programming Deep Brain Stimulation for Parkinson's Disease: The Toronto Western Hospital Algorithms.

PubMed

Picillo, Marina; Lozano, Andres M; Kou, Nancy; Puppi Munhoz, Renato; Fasano, Alfonso

2016-01-01

Deep brain stimulation (DBS) is an established and effective treatment for Parkinson's disease (PD). After surgery, a number of extensive programming sessions are performed to define the most optimal stimulation parameters. Programming sessions mainly rely only on neurologist's experience. As a result, patients often undergo inconsistent and inefficient stimulation changes, as well as unnecessary visits. We reviewed the literature on initial and follow-up DBS programming procedures and integrated our current practice at Toronto Western Hospital (TWH) to develop standardized DBS programming protocols. We propose four algorithms including the initial programming and specific algorithms tailored to symptoms experienced by patients following DBS: speech disturbances, stimulation-induced dyskinesia and gait impairment. We conducted a literature search of PubMed from inception to July 2014 with the keywords "deep brain stimulation", "festination", "freezing", "initial programming", "Parkinson's disease", "postural instability", "speech disturbances", and "stimulation induced dyskinesia". Seventy papers were considered for this review. Based on the literature review and our experience at TWH, we refined four algorithms for: (1) the initial programming stage, and management of symptoms following DBS, particularly addressing (2) speech disturbances, (3) stimulation-induced dyskinesia, and (4) gait impairment. We propose four algorithms tailored to an individualized approach to managing symptoms associated with DBS and disease progression in patients with PD. We encourage established as well as new DBS centers to test the clinical usefulness of these algorithms in supplementing the current standards of care. Copyright © 2016 Elsevier Inc. All rights reserved.

Efficient stabilization and acceleration of numerical simulation of fluid flows by residual recombination

NASA Astrophysics Data System (ADS)

Citro, V.; Luchini, P.; Giannetti, F.; Auteri, F.

2017-09-01

The study of the stability of a dynamical system described by a set of partial differential equations (PDEs) requires the computation of unstable states as the control parameter exceeds its critical threshold. Unfortunately, the discretization of the governing equations, especially for fluid dynamic applications, often leads to very large discrete systems. As a consequence, matrix based methods, like for example the Newton-Raphson algorithm coupled with a direct inversion of the Jacobian matrix, lead to computational costs too large in terms of both memory and execution time. We present a novel iterative algorithm, inspired by Krylov-subspace methods, which is able to compute unstable steady states and/or accelerate the convergence to stable configurations. Our new algorithm is based on the minimization of the residual norm at each iteration step with a projection basis updated at each iteration rather than at periodic restarts like in the classical GMRES method. The algorithm is able to stabilize any dynamical system without increasing the computational time of the original numerical procedure used to solve the governing equations. Moreover, it can be easily inserted into a pre-existing relaxation (integration) procedure with a call to a single black-box subroutine. The procedure is discussed for problems of different sizes, ranging from a small two-dimensional system to a large three-dimensional problem involving the Navier-Stokes equations. We show that the proposed algorithm is able to improve the convergence of existing iterative schemes. In particular, the procedure is applied to the subcritical flow inside a lid-driven cavity. We also discuss the application of Boostconv to compute the unstable steady flow past a fixed circular cylinder (2D) and boundary-layer flow over a hemispherical roughness element (3D) for supercritical values of the Reynolds number. We show that Boostconv can be used effectively with any spatial discretization, be it a finite-difference, finite-volume, finite-element or spectral method.

Mining peripheral arterial disease cases from narrative clinical notes using natural language processing.

PubMed

Afzal, Naveed; Sohn, Sunghwan; Abram, Sara; Scott, Christopher G; Chaudhry, Rajeev; Liu, Hongfang; Kullo, Iftikhar J; Arruda-Olson, Adelaide M

2017-06-01

Lower extremity peripheral arterial disease (PAD) is highly prevalent and affects millions of individuals worldwide. We developed a natural language processing (NLP) system for automated ascertainment of PAD cases from clinical narrative notes and compared the performance of the NLP algorithm with billing code algorithms, using ankle-brachial index test results as the gold standard. We compared the performance of the NLP algorithm to (1) results of gold standard ankle-brachial index; (2) previously validated algorithms based on relevant International Classification of Diseases, Ninth Revision diagnostic codes (simple model); and (3) a combination of International Classification of Diseases, Ninth Revision codes with procedural codes (full model). A dataset of 1569 patients with PAD and controls was randomly divided into training (n = 935) and testing (n = 634) subsets. We iteratively refined the NLP algorithm in the training set including narrative note sections, note types, and service types, to maximize its accuracy. In the testing dataset, when compared with both simple and full models, the NLP algorithm had better accuracy (NLP, 91.8%; full model, 81.8%; simple model, 83%; P < .001), positive predictive value (NLP, 92.9%; full model, 74.3%; simple model, 79.9%; P < .001), and specificity (NLP, 92.5%; full model, 64.2%; simple model, 75.9%; P < .001). A knowledge-driven NLP algorithm for automatic ascertainment of PAD cases from clinical notes had greater accuracy than billing code algorithms. Our findings highlight the potential of NLP tools for rapid and efficient ascertainment of PAD cases from electronic health records to facilitate clinical investigation and eventually improve care by clinical decision support. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Procedures for Geometric Data Reduction in Solid Log Modelling

Treesearch

Luis G. Occeña; Wenzhen Chen; Daniel L. Schmoldt

1995-01-01

One of the difficulties in solid log modelling is working with huge data sets, such as those that come from computed axial tomographic imaging. Algorithmic procedures are described in this paper that have successfully reduced data without sacrificing modelling integrity.

Computer based interpretation of infrared spectra-structure of the knowledge-base, automatic rule generation and interpretation

NASA Astrophysics Data System (ADS)

Ehrentreich, F.; Dietze, U.; Meyer, U.; Abbas, S.; Schulz, H.

1995-04-01

It is a main task within the SpecInfo-Project to develop interpretation tools that can handle a great deal more of the complicated, more specific spectrum-structure-correlations. In the first step the empirical knowledge about the assignment of structural groups and their characteristic IR-bands has been collected from literature and represented in a computer readable well-structured form. Vague, verbal rules are managed by introduction of linguistic variables. The next step was the development of automatic rule generating procedures. We had combined and enlarged the IDIOTS algorithm with the algorithm by Blaffert relying on set theory. The procedures were successfully applied to the SpecInfo database. The realization of the preceding items is a prerequisite for the improvement of the computerized structure elucidation procedure.

Approach for counting vehicles in congested traffic flow

NASA Astrophysics Data System (ADS)

Tan, Xiaojun; Li, Jun; Liu, Wei

2005-02-01

More and more image sensors are used in intelligent transportation systems. In practice, occlusion is always a problem when counting vehicles in congested traffic. This paper tries to present an approach to solve the problem. The proposed approach consists of three main procedures. Firstly, a new algorithm of background subtraction is performed. The aim is to segment moving objects from an illumination-variant background. Secondly, object tracking is performed, where the CONDENSATION algorithm is used. This can avoid the problem of matching vehicles in successive frames. Thirdly, an inspecting procedure is executed to count the vehicles. When a bus firstly occludes a car and then the bus moves away a few frames later, the car will appear in the scene. The inspecting procedure should find the "new" car and add it as a tracking object.

Procedural Quantum Programming

NASA Astrophysics Data System (ADS)

Ömer, Bernhard

2002-09-01

While classical computing science has developed a variety of methods and programming languages around the concept of the universal computer, the typical description of quantum algorithms still uses a purely mathematical, non-constructive formalism which makes no difference between a hydrogen atom and a quantum computer. This paper investigates, how the concept of procedural programming languages, the most widely used classical formalism for describing and implementing algorithms, can be adopted to the field of quantum computing, and how non-classical features like the reversibility of unitary transformations, the non-observability of quantum states or the lack of copy and erase operations can be reflected semantically. It introduces the key concepts of procedural quantum programming (hybrid target architecture, operator hierarchy, quantum data types, memory management, etc.) and presents the experimental language QCL, which implements these principles.

Quality controls for wind measurement of a 1290-MHz boundary layer profiler under strong wind conditions.

PubMed

Liu, Zhao; Zheng, Chaorong; Wu, Yue

2017-09-01

Wind profilers have been widely adopted to observe the wind field information in the atmosphere for different purposes. But accuracy of its observation has limitations due to various noises or disturbances and hence need to be further improved. In this paper, the data measured under strong wind conditions, using a 1290-MHz boundary layer profiler (BLP), are quality controlled via a composite quality control (QC) procedure proposed by the authors. Then, through the comparison with the data measured by radiosonde flights (balloon observations), the critical thresholds in the composite QC procedure, including consensus average threshold T 1 and vertical shear threshold T 3 , are systematically discussed. And the performance of the BLP operated under precipitation is also evaluated. It is found that to ensure the high accuracy and high data collectable rate, the optimal range of subsets is determined to be 4 m/s. Although the number of data rejected by the combined algorithm of vertical shear examination and small median test is quite limited, it is proved that the algorithm is quite useful to recognize the outlier with a large discrepancy. And the optimal wind shear threshold T 3 can be recommended as 5 ms -1 /100m. During patchy precipitation, the quality of data measured by the four oblique beams (using the DBS measuring technique) can still be ensured. After the BLP data are quality controlled by the composite QC procedure, the output can show good agreement with the balloon observation.

An algorithm to diagnose ball bearing faults in servomotors running arbitrary motion profiles

NASA Astrophysics Data System (ADS)

Cocconcelli, Marco; Bassi, Luca; Secchi, Cristian; Fantuzzi, Cesare; Rubini, Riccardo

2012-02-01

This paper describes a procedure to extend the scope of classical methods to detect ball bearing faults (based on envelope analysis and fault frequencies identification) beyond their usual area of application. The objective of this procedure is to allow condition-based monitoring of such bearings in servomotor applications, where typically the motor in its normal mode of operation has to follow a non-constant angular velocity profile that may contain motion inversions. After describing and analyzing the algorithm from a theoretical point of view, experimental results obtained on a real industrial application are presented and commented.

Pseudo-updated constrained solution algorithm for nonlinear heat conduction

NASA Technical Reports Server (NTRS)

Tovichakchaikul, S.; Padovan, J.

1983-01-01

This paper develops efficiency and stability improvements in the incremental successive substitution (ISS) procedure commonly used to generate the solution to nonlinear heat conduction problems. This is achieved by employing the pseudo-update scheme of Broyden, Fletcher, Goldfarb and Shanno in conjunction with the constrained version of the ISS. The resulting algorithm retains the formulational simplicity associated with ISS schemes while incorporating the enhanced convergence properties of slope driven procedures as well as the stability of constrained approaches. To illustrate the enhanced operating characteristics of the new scheme, the results of several benchmark comparisons are presented.

SeaWiFS Technical Report Series. Volume 38; SeaWiFS Calibration and Validation Quality Control Procedures

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); McClain, Charles R.; Darzi, Michael; Barnes, Robert A.; Eplee, Robert E.; Firestone, James K.; Patt, Frederick S.; Robinson, Wayne D.; Schieber, Brian D.;

Applications of modern statistical methods to analysis of data in physical science

NASA Astrophysics Data System (ADS)

Wicker, James Eric

Modern methods of statistical and computational analysis offer solutions to dilemmas confronting researchers in physical science. Although the ideas behind modern statistical and computational analysis methods were originally introduced in the 1970's, most scientists still rely on methods written during the early era of computing. These researchers, who analyze increasingly voluminous and multivariate data sets, need modern analysis methods to extract the best results from their studies. The first section of this work showcases applications of modern linear regression. Since the 1960's, many researchers in spectroscopy have used classical stepwise regression techniques to derive molecular constants. However, problems with thresholds of entry and exit for model variables plagues this analysis method. Other criticisms of this kind of stepwise procedure include its inefficient searching method, the order in which variables enter or leave the model and problems with overfitting data. We implement an information scoring technique that overcomes the assumptions inherent in the stepwise regression process to calculate molecular model parameters. We believe that this kind of information based model evaluation can be applied to more general analysis situations in physical science. The second section proposes new methods of multivariate cluster analysis. The K-means algorithm and the EM algorithm, introduced in the 1960's and 1970's respectively, formed the basis of multivariate cluster analysis methodology for many years. However, several shortcomings of these methods include strong dependence on initial seed values and inaccurate results when the data seriously depart from hypersphericity. We propose new cluster analysis methods based on genetic algorithms that overcomes the strong dependence on initial seed values. In addition, we propose a generalization of the Genetic K-means algorithm which can accurately identify clusters with complex hyperellipsoidal covariance structures. We then use this new algorithm in a genetic algorithm based Expectation-Maximization process that can accurately calculate parameters describing complex clusters in a mixture model routine. Using the accuracy of this GEM algorithm, we assign information scores to cluster calculations in order to best identify the number of mixture components in a multivariate data set. We will showcase how these algorithms can be used to process multivariate data from astronomical observations.

Adiabatic Quantum Simulation of Quantum Chemistry

PubMed Central

Babbush, Ryan; Love, Peter J.; Aspuru-Guzik, Alán

2014-01-01

We show how to apply the quantum adiabatic algorithm directly to the quantum computation of molecular properties. We describe a procedure to map electronic structure Hamiltonians to 2-body qubit Hamiltonians with a small set of physically realizable couplings. By combining the Bravyi-Kitaev construction to map fermions to qubits with perturbative gadgets to reduce the Hamiltonian to 2-body, we obtain precision requirements on the coupling strengths and a number of ancilla qubits that scale polynomially in the problem size. Hence our mapping is efficient. The required set of controllable interactions includes only two types of interaction beyond the Ising interactions required to apply the quantum adiabatic algorithm to combinatorial optimization problems. Our mapping may also be of interest to chemists directly as it defines a dictionary from electronic structure to spin Hamiltonians with physical interactions. PMID:25308187

Contraceptive efficacy of the personal hormone monitoring system Persona.

PubMed

Trussell, J

1999-07-01

This is a commentary on the contraceptive effectiveness of the personal hormone-monitoring system Persona; it points out the various errors committed in computing method pregnancy rates. The modifications presented by Bonnar et al. on the incorrect procedure for computing method pregnancy rates are criticized as erroneous because the denominator includes cycles in which there is no risk of a method pregnancy according to the authors' algorithm for classifying pregnancy in an imperfect-use cycle. It is also claimed that the new exercise is a more complicated and less accurate way of computing for pregnancy rates by comparison with the simpler alternative. Since this new algorithm, used in the Persona system, is based on flawed logic, the annual risk of pregnancy is actually higher than the estimated 6% among women using Persona and having intercourse in each cycle except on red days.

Applications of genetic algorithms on the structure-activity relationship analysis of some cinnamamides.

PubMed

Hou, T J; Wang, J M; Liao, N; Xu, X J

1999-01-01

Quantitative structure-activity relationships (QSARs) for 35 cinnamamides were studied. By using a genetic algorithm (GA), a group of multiple regression models with high fitness scores was generated. From the statistical analyses of the descriptors used in the evolution procedure, the principal features affecting the anticonvulsant activity were found. The significant descriptors include the partition coefficient, the molar refraction, the Hammet sigma constant of the substituents on the benzene ring, and the formation energy of the molecules. It could be found that the steric complementarity and the hydrophobic interaction between the inhibitors and the receptor were very important to the biological activity, while the contribution of the electronic effect was not so obvious. Moreover, by construction of the spline models for these four principal descriptors, the effective range for each descriptor was identified.

The global Minmax k-means algorithm.

PubMed

Wang, Xiaoyan; Bai, Yanping

2016-01-01

The global k -means algorithm is an incremental approach to clustering that dynamically adds one cluster center at a time through a deterministic global search procedure from suitable initial positions, and employs k -means to minimize the sum of the intra-cluster variances. However the global k -means algorithm sometimes results singleton clusters and the initial positions sometimes are bad, after a bad initialization, poor local optimal can be easily obtained by k -means algorithm. In this paper, we modified the global k -means algorithm to eliminate the singleton clusters at first, and then we apply MinMax k -means clustering error method to global k -means algorithm to overcome the effect of bad initialization, proposed the global Minmax k -means algorithm. The proposed clustering method is tested on some popular data sets and compared to the k -means algorithm, the global k -means algorithm and the MinMax k -means algorithm. The experiment results show our proposed algorithm outperforms other algorithms mentioned in the paper.

Development of the L-1011 four-dimensional flight management system

NASA Technical Reports Server (NTRS)

Lee, H. P.; Leffler, M. F.

1984-01-01

The development of 4-D guidance and control algorithms for the L-1011 Flight Management System is described. Four-D Flight Management is a concept by which an aircraft's flight is optimized along the 3-D path within the constraints of today's ATC environment, while its arrival time is controlled to fit into the air traffic flow without incurring or causing delays. The methods developed herein were designed to be compatible with the time-based en route metering techniques that were recently developed by the Dallas/Fort Worth and Denver Air Route Traffic Control Centers. The ensuing development of the 4-D guidance algorithms, the necessary control laws and the operational procedures are discussed. Results of computer simulation evaluation of the guidance algorithms and control laws are presented, along with a description of the software development procedures utilized.

Efficient Levenberg-Marquardt minimization of the maximum likelihood estimator for Poisson deviates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Laurence, T; Chromy, B

2009-11-10

Histograms of counted events are Poisson distributed, but are typically fitted without justification using nonlinear least squares fitting. The more appropriate maximum likelihood estimator (MLE) for Poisson distributed data is seldom used. We extend the use of the Levenberg-Marquardt algorithm commonly used for nonlinear least squares minimization for use with the MLE for Poisson distributed data. In so doing, we remove any excuse for not using this more appropriate MLE. We demonstrate the use of the algorithm and the superior performance of the MLE using simulations and experiments in the context of fluorescence lifetime imaging. Scientists commonly form histograms ofmore » counted events from their data, and extract parameters by fitting to a specified model. Assuming that the probability of occurrence for each bin is small, event counts in the histogram bins will be distributed according to the Poisson distribution. We develop here an efficient algorithm for fitting event counting histograms using the maximum likelihood estimator (MLE) for Poisson distributed data, rather than the non-linear least squares measure. This algorithm is a simple extension of the common Levenberg-Marquardt (L-M) algorithm, is simple to implement, quick and robust. Fitting using a least squares measure is most common, but it is the maximum likelihood estimator only for Gaussian-distributed data. Non-linear least squares methods may be applied to event counting histograms in cases where the number of events is very large, so that the Poisson distribution is well approximated by a Gaussian. However, it is not easy to satisfy this criterion in practice - which requires a large number of events. It has been well-known for years that least squares procedures lead to biased results when applied to Poisson-distributed data; a recent paper providing extensive characterization of these biases in exponential fitting is given. The more appropriate measure based on the maximum likelihood estimator (MLE) for the Poisson distribution is also well known, but has not become generally used. This is primarily because, in contrast to non-linear least squares fitting, there has been no quick, robust, and general fitting method. In the field of fluorescence lifetime spectroscopy and imaging, there have been some efforts to use this estimator through minimization routines such as Nelder-Mead optimization, exhaustive line searches, and Gauss-Newton minimization. Minimization based on specific one- or multi-exponential models has been used to obtain quick results, but this procedure does not allow the incorporation of the instrument response, and is not generally applicable to models found in other fields. Methods for using the MLE for Poisson-distributed data have been published by the wider spectroscopic community, including iterative minimization schemes based on Gauss-Newton minimization. The slow acceptance of these procedures for fitting event counting histograms may also be explained by the use of the ubiquitous, fast Levenberg-Marquardt (L-M) fitting procedure for fitting non-linear models using least squares fitting (simple searches obtain {approx}10000 references - this doesn't include those who use it, but don't know they are using it). The benefits of L-M include a seamless transition between Gauss-Newton minimization and downward gradient minimization through the use of a regularization parameter. This transition is desirable because Gauss-Newton methods converge quickly, but only within a limited domain of convergence; on the other hand the downward gradient methods have a much wider domain of convergence, but converge extremely slowly nearer the minimum. L-M has the advantages of both procedures: relative insensitivity to initial parameters and rapid convergence. Scientists, when wanting an answer quickly, will fit data using L-M, get an answer, and move on. Only those that are aware of the bias issues will bother to fit using the more appropriate MLE for Poisson deviates. However, since there is a simple, analytical formula for the appropriate MLE measure for Poisson deviates, it is inexcusable that least squares estimators are used almost exclusively when fitting event counting histograms. There have been ways found to use successive non-linear least squares fitting to obtain similarly unbiased results, but this procedure is justified by simulation, must be re-tested when conditions change significantly, and requires two successive fits. There is a great need for a fitting routine for the MLE estimator for Poisson deviates that has convergence domains and rates comparable to the non-linear least squares L-M fitting. We show in this report that a simple way to achieve that goal is to use the L-M fitting procedure not to minimize the least squares measure, but the MLE for Poisson deviates.« less

ARYANA: Aligning Reads by Yet Another Approach

PubMed Central

2014-01-01

Motivation Although there are many different algorithms and software tools for aligning sequencing reads, fast gapped sequence search is far from solved. Strong interest in fast alignment is best reflected in the $106 prize for the Innocentive competition on aligning a collection of reads to a given database of reference genomes. In addition, de novo assembly of next-generation sequencing long reads requires fast overlap-layout-concensus algorithms which depend on fast and accurate alignment. Contribution We introduce ARYANA, a fast gapped read aligner, developed on the base of BWA indexing infrastructure with a completely new alignment engine that makes it significantly faster than three other aligners: Bowtie2, BWA and SeqAlto, with comparable generality and accuracy. Instead of the time-consuming backtracking procedures for handling mismatches, ARYANA comes with the seed-and-extend algorithmic framework and a significantly improved efficiency by integrating novel algorithmic techniques including dynamic seed selection, bidirectional seed extension, reset-free hash tables, and gap-filling dynamic programming. As the read length increases ARYANA's superiority in terms of speed and alignment rate becomes more evident. This is in perfect harmony with the read length trend as the sequencing technologies evolve. The algorithmic platform of ARYANA makes it easy to develop mission-specific aligners for other applications using ARYANA engine. Availability ARYANA with complete source code can be obtained from http://github.com/aryana-aligner PMID:25252881

A Frequency-Domain Substructure System Identification Algorithm

NASA Technical Reports Server (NTRS)

Blades, Eric L.; Craig, Roy R., Jr.

1996-01-01

A new frequency-domain system identification algorithm is presented for system identification of substructures, such as payloads to be flown aboard the Space Shuttle. In the vibration test, all interface degrees of freedom where the substructure is connected to the carrier structure are either subjected to active excitation or are supported by a test stand with the reaction forces measured. The measured frequency-response data is used to obtain a linear, viscous-damped model with all interface-degree of freedom entries included. This model can then be used to validate analytical substructure models. This procedure makes it possible to obtain not only the fixed-interface modal data associated with a Craig-Bampton substructure model, but also the data associated with constraint modes. With this proposed algorithm, multiple-boundary-condition tests are not required, and test-stand dynamics is accounted for without requiring a separate modal test or finite element modeling of the test stand. Numerical simulations are used in examining the algorithm's ability to estimate valid reduced-order structural models. The algorithm's performance when frequency-response data covering narrow and broad frequency bandwidths is used as input is explored. Its performance when noise is added to the frequency-response data and the use of different least squares solution techniques are also examined. The identified reduced-order models are also compared for accuracy with other test-analysis models and a formulation for a Craig-Bampton test-analysis model is also presented.

ARYANA: Aligning Reads by Yet Another Approach.

PubMed

Gholami, Milad; Arbabi, Aryan; Sharifi-Zarchi, Ali; Chitsaz, Hamidreza; Sadeghi, Mehdi

2014-01-01

Although there are many different algorithms and software tools for aligning sequencing reads, fast gapped sequence search is far from solved. Strong interest in fast alignment is best reflected in the $10(6) prize for the Innocentive competition on aligning a collection of reads to a given database of reference genomes. In addition, de novo assembly of next-generation sequencing long reads requires fast overlap-layout-concensus algorithms which depend on fast and accurate alignment. We introduce ARYANA, a fast gapped read aligner, developed on the base of BWA indexing infrastructure with a completely new alignment engine that makes it significantly faster than three other aligners: Bowtie2, BWA and SeqAlto, with comparable generality and accuracy. Instead of the time-consuming backtracking procedures for handling mismatches, ARYANA comes with the seed-and-extend algorithmic framework and a significantly improved efficiency by integrating novel algorithmic techniques including dynamic seed selection, bidirectional seed extension, reset-free hash tables, and gap-filling dynamic programming. As the read length increases ARYANA's superiority in terms of speed and alignment rate becomes more evident. This is in perfect harmony with the read length trend as the sequencing technologies evolve. The algorithmic platform of ARYANA makes it easy to develop mission-specific aligners for other applications using ARYANA engine. ARYANA with complete source code can be obtained from http://github.com/aryana-aligner.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

PubMed

Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

2017-07-19

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

Optimization of the Inverse Algorithm for Estimating the Optical Properties of Biological Materials Using Spatially-resolved Diffuse Reflectance Technique

USDA-ARS?s Scientific Manuscript database

Determination of the optical properties from intact biological materials based on diffusion approximation theory is a complicated inverse problem, and it requires proper implementation of inverse algorithm, instrumentation, and experiment. This work was aimed at optimizing the procedure of estimatin...

Using an Algorithm When Solving Hardy-Weinberg Problems in Biology.

ERIC Educational Resources Information Center

Stencel, John E.

1991-01-01

A real world sample of actual data that students can use to see the application of the Hardy-Weinberg law to a real population is provided. The directions for using a six-step algorithmic procedure to determine Hardy-Weinberg percentages on the data given are described. (KR)

How is WFPC flat field made

NASA Technical Reports Server (NTRS)

Hsu, J.-C.; Ritchie, C. E.

1992-01-01

An algorithm developed by the WFPC IDT to generate flat fields from Earth streak exposures is now implemented in STSDAS. We explain in detail how this algorithm works and possible deficiencies. We also present two associated tools which can be used to modify the flat field obtained from the standard procedure.

Application of Network and Decision Theory to Routing Problems.

DTIC Science & Technology

1982-03-01

special thanks to Major Hal Carter, faculty member, for his help in getting the authors to understand one of the underlying algorithms in the methodology...61 26. General Methodology Flowchart .......... .. 64 27. Least Cost/Time Path Algorithm Flowchart . . 65 28. Possible Redundant Arc of Time...minimum time to travel. This was neces- sary because: 1. The DTN designers did not have a procedure to do so. 2. The various network algorithms to

Evaluation of atomic pressure in the multiple time-step integration algorithm.

PubMed

Andoh, Yoshimichi; Yoshii, Noriyuki; Yamada, Atsushi; Okazaki, Susumu

2017-04-15

In molecular dynamics (MD) calculations, reduction in calculation time per MD loop is essential. A multiple time-step (MTS) integration algorithm, the RESPA (Tuckerman and Berne, J. Chem. Phys. 1992, 97, 1990-2001), enables reductions in calculation time by decreasing the frequency of time-consuming long-range interaction calculations. However, the RESPA MTS algorithm involves uncertainties in evaluating the atomic interaction-based pressure (i.e., atomic pressure) of systems with and without holonomic constraints. It is not clear which intermediate forces and constraint forces in the MTS integration procedure should be used to calculate the atomic pressure. In this article, we propose a series of equations to evaluate the atomic pressure in the RESPA MTS integration procedure on the basis of its equivalence to the Velocity-Verlet integration procedure with a single time step (STS). The equations guarantee time-reversibility even for the system with holonomic constrants. Furthermore, we generalize the equations to both (i) arbitrary number of inner time steps and (ii) arbitrary number of force components (RESPA levels). The atomic pressure calculated by our equations with the MTS integration shows excellent agreement with the reference value with the STS, whereas pressures calculated using the conventional ad hoc equations deviated from it. Our equations can be extended straightforwardly to the MTS integration algorithm for the isothermal NVT and isothermal-isobaric NPT ensembles. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Fast inference of interactions in assemblies of stochastic integrate-and-fire neurons from spike recordings.

PubMed

Monasson, Remi; Cocco, Simona

2011-10-01

We present two Bayesian procedures to infer the interactions and external currents in an assembly of stochastic integrate-and-fire neurons from the recording of their spiking activity. The first procedure is based on the exact calculation of the most likely time courses of the neuron membrane potentials conditioned by the recorded spikes, and is exact for a vanishing noise variance and for an instantaneous synaptic integration. The second procedure takes into account the presence of fluctuations around the most likely time courses of the potentials, and can deal with moderate noise levels. The running time of both procedures is proportional to the number S of spikes multiplied by the squared number N of neurons. The algorithms are validated on synthetic data generated by networks with known couplings and currents. We also reanalyze previously published recordings of the activity of the salamander retina (including from 32 to 40 neurons, and from 65,000 to 170,000 spikes). We study the dependence of the inferred interactions on the membrane leaking time; the differences and similarities with the classical cross-correlation analysis are discussed.

An automatic agricultural zone classification procedure for crop inventory satellite images

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Kux, H. J.; Velasco, F. R. D.; Deoliveira, M. O. B.

1982-01-01

A classification procedure for assessing crop areal proportion in multispectral scanner image is discussed. The procedure is into four parts: labeling; classification; proportion estimation; and evaluation. The procedure also has the following characteristics: multitemporal classification; the need for a minimum field information; and verification capability between automatic classification and analyst labeling. The processing steps and the main algorithms involved are discussed. An outlook on the future of this technology is also presented.

Development of OCR system for portable passport and visa reader

NASA Astrophysics Data System (ADS)

Visilter, Yury V.; Zheltov, Sergey Y.; Lukin, Anton A.

1999-01-01

The modern passport and visa documents include special machine-readable zones satisfied the ICAO standards. This allows to develop the special passport and visa automatic readers. However, there are some special problems in such OCR systems: low resolution of character images captured by CCD-camera (down to 150 dpi), essential shifts and slopes (up to 10 degrees), rich paper texture under the character symbols, non-homogeneous illumination. This paper presents the structure and some special aspects of OCR system for portable passport and visa reader. In our approach the binarization procedure is performed after the segmentation step, and it is applied to the each character site separately. Character recognition procedure uses the structural information of machine-readable zone. Special algorithms are developed for machine-readable zone extraction and character segmentation.

Particle swarm optimization-based automatic parameter selection for deep neural networks and its applications in large-scale and high-dimensional data

PubMed Central

2017-01-01

In this paper, we propose a new automatic hyperparameter selection approach for determining the optimal network configuration (network structure and hyperparameters) for deep neural networks using particle swarm optimization (PSO) in combination with a steepest gradient descent algorithm. In the proposed approach, network configurations were coded as a set of real-number m-dimensional vectors as the individuals of the PSO algorithm in the search procedure. During the search procedure, the PSO algorithm is employed to search for optimal network configurations via the particles moving in a finite search space, and the steepest gradient descent algorithm is used to train the DNN classifier with a few training epochs (to find a local optimal solution) during the population evaluation of PSO. After the optimization scheme, the steepest gradient descent algorithm is performed with more epochs and the final solutions (pbest and gbest) of the PSO algorithm to train a final ensemble model and individual DNN classifiers, respectively. The local search ability of the steepest gradient descent algorithm and the global search capabilities of the PSO algorithm are exploited to determine an optimal solution that is close to the global optimum. We constructed several experiments on hand-written characters and biological activity prediction datasets to show that the DNN classifiers trained by the network configurations expressed by the final solutions of the PSO algorithm, employed to construct an ensemble model and individual classifier, outperform the random approach in terms of the generalization performance. Therefore, the proposed approach can be regarded an alternative tool for automatic network structure and parameter selection for deep neural networks. PMID:29236718

Does videothoracoscopy improve clinical outcomes when implemented as part of a pleural empyema treatment algorithm?

PubMed Central

Terra, Ricardo Mingarini; Waisberg, Daniel Reis; de Almeida, José Luiz Jesus; Devido, Marcela Santana; Pêgo-Fernandes, Paulo Manuel; Jatene, Fabio Biscegli

2012-01-01

OBJECTIVE: We aimed to evaluate whether the inclusion of videothoracoscopy in a pleural empyema treatment algorithm would change the clinical outcome of such patients. METHODS: This study performed quality-improvement research. We conducted a retrospective review of patients who underwent pleural decortication for pleural empyema at our institution from 2002 to 2008. With the old algorithm (January 2002 to September 2005), open decortication was the procedure of choice, and videothoracoscopy was only performed in certain sporadic mid-stage cases. With the new algorithm (October 2005 to December 2008), videothoracoscopy became the first-line treatment option, whereas open decortication was only performed in patients with a thick pleural peel (>2 cm) observed by chest scan. The patients were divided into an old algorithm (n = 93) and new algorithm (n = 113) group and compared. The main outcome variables assessed included treatment failure (pleural space reintervention or death up to 60 days after medical discharge) and the occurrence of complications. RESULTS: Videothoracoscopy and open decortication were performed in 13 and 80 patients from the old algorithm group and in 81 and 32 patients from the new algorithm group, respectively (p<0.01). The patients in the new algorithm group were older (41±1 vs. 46.3±16.7 years, p = 0.014) and had higher Charlson Comorbidity Index scores [0(0-3) vs. 2(0-4), p = 0.032]. The occurrence of treatment failure was similar in both groups (19.35% vs. 24.77%, p = 0.35), although the complication rate was lower in the new algorithm group (48.3% vs. 33.6%, p = 0.04). CONCLUSIONS: The wider use of videothoracoscopy in pleural empyema treatment was associated with fewer complications and unaltered rates of mortality and reoperation even though more severely ill patients were subjected to videothoracoscopic surgery. PMID:22760892

Benchmarking Procedures for High-Throughput Context Specific Reconstruction Algorithms

PubMed Central

Pacheco, Maria P.; Pfau, Thomas; Sauter, Thomas

2016-01-01

Recent progress in high-throughput data acquisition has shifted the focus from data generation to processing and understanding of how to integrate collected information. Context specific reconstruction based on generic genome scale models like ReconX or HMR has the potential to become a diagnostic and treatment tool tailored to the analysis of specific individuals. The respective computational algorithms require a high level of predictive power, robustness and sensitivity. Although multiple context specific reconstruction algorithms were published in the last 10 years, only a fraction of them is suitable for model building based on human high-throughput data. Beside other reasons, this might be due to problems arising from the limitation to only one metabolic target function or arbitrary thresholding. This review describes and analyses common validation methods used for testing model building algorithms. Two major methods can be distinguished: consistency testing and comparison based testing. The first is concerned with robustness against noise, e.g., missing data due to the impossibility to distinguish between the signal and the background of non-specific binding of probes in a microarray experiment, and whether distinct sets of input expressed genes corresponding to i.e., different tissues yield distinct models. The latter covers methods comparing sets of functionalities, comparison with existing networks or additional databases. We test those methods on several available algorithms and deduce properties of these algorithms that can be compared with future developments. The set of tests performed, can therefore serve as a benchmarking procedure for future algorithms. PMID:26834640

A decentralized training algorithm for Echo State Networks in distributed big data applications.

PubMed

Scardapane, Simone; Wang, Dianhui; Panella, Massimo

2016-06-01

The current big data deluge requires innovative solutions for performing efficient inference on large, heterogeneous amounts of information. Apart from the known challenges deriving from high volume and velocity, real-world big data applications may impose additional technological constraints, including the need for a fully decentralized training architecture. While several alternatives exist for training feed-forward neural networks in such a distributed setting, less attention has been devoted to the case of decentralized training of recurrent neural networks (RNNs). In this paper, we propose such an algorithm for a class of RNNs known as Echo State Networks. The algorithm is based on the well-known Alternating Direction Method of Multipliers optimization procedure. It is formulated only in terms of local exchanges between neighboring agents, without reliance on a coordinating node. Additionally, it does not require the communication of training patterns, which is a crucial component in realistic big data implementations. Experimental results on large scale artificial datasets show that it compares favorably with a fully centralized implementation, in terms of speed, efficiency and generalization accuracy. Copyright © 2015 Elsevier Ltd. All rights reserved.

A new design approach based on differential evolution algorithm for geometric optimization of magnetorheological brakes

NASA Astrophysics Data System (ADS)

Le-Duc, Thang; Ho-Huu, Vinh; Nguyen-Thoi, Trung; Nguyen-Quoc, Hung

2016-12-01

In recent years, various types of magnetorheological brakes (MRBs) have been proposed and optimized by different optimization algorithms that are integrated in commercial software such as ANSYS and Comsol Multiphysics. However, many of these optimization algorithms often possess some noteworthy shortcomings such as the trap of solutions at local extremes, or the limited number of design variables or the difficulty of dealing with discrete design variables. Thus, to overcome these limitations and develop an efficient computation tool for optimal design of the MRBs, an optimization procedure that combines differential evolution (DE), a gradient-free global optimization method with finite element analysis (FEA) is proposed in this paper. The proposed approach is then applied to the optimal design of MRBs with different configurations including conventional MRBs and MRBs with coils placed on the side housings. Moreover, to approach a real-life design, some necessary design variables of MRBs are considered as discrete variables in the optimization process. The obtained optimal design results are compared with those of available optimal designs in the literature. The results reveal that the proposed method outperforms some traditional approaches.

An evolutionary firefly algorithm for the estimation of nonlinear biological model parameters.

PubMed

Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N V

2013-01-01

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.

An Evolutionary Firefly Algorithm for the Estimation of Nonlinear Biological Model Parameters

PubMed Central

Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N. V.

2013-01-01

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test. PMID:23469172

Towards a phase diagram for spin foams

NASA Astrophysics Data System (ADS)

Delcamp, Clement; Dittrich, Bianca

2017-11-01

One of the most pressing issues for loop quantum gravity and spin foams is the construction of the continuum limit. In this paper, we propose a systematic coarse-graining scheme for three-dimensional lattice gauge models including spin foams. This scheme is based on the concept of decorated tensor networks, which have been introduced recently. Here we develop an algorithm applicable to gauge theories with non-Abelian groups, which for the first time allows for the application of tensor network coarse-graining techniques to proper spin foams. The procedure deals efficiently with the large redundancy of degrees of freedom resulting from gauge invariance. The algorithm is applied to 3D spin foams defined on a cubical lattice which, in contrast to a proper triangulation, allows for non-trivial simplicity constraints. This mimics the construction of spin foams for 4D gravity. For lattice gauge models based on a finite group we use the algorithm to obtain phase diagrams, encoding the continuum limit of a wide range of these models. We find phase transitions for various families of models carrying non-trivial simplicity constraints.

Deep greedy learning under thermal variability in full diurnal cycles

NASA Astrophysics Data System (ADS)

Rauss, Patrick; Rosario, Dalton

2017-08-01

We study the generalization and scalability behavior of a deep belief network (DBN) applied to a challenging long-wave infrared hyperspectral dataset, consisting of radiance from several manmade and natural materials within a fixed site located 500 m from an observation tower. The collections cover multiple full diurnal cycles and include different atmospheric conditions. Using complementary priors, a DBN uses a greedy algorithm that can learn deep, directed belief networks one layer at a time and has two layers form to provide undirected associative memory. The greedy algorithm initializes a slower learning procedure, which fine-tunes the weights, using a contrastive version of the wake-sleep algorithm. After fine-tuning, a network with three hidden layers forms a very good generative model of the joint distribution of spectral data and their labels, despite significant data variability between and within classes due to environmental and temperature variation occurring within and between full diurnal cycles. We argue, however, that more questions than answers are raised regarding the generalization capacity of these deep nets through experiments aimed at investigating their training and augmented learning behavior.

The localization of focal heart activity via body surface potential measurements: tests in a heterogeneous torso phantom

NASA Astrophysics Data System (ADS)

Wetterling, F.; Liehr, M.; Schimpf, P.; Liu, H.; Haueisen, J.

2009-09-01

The non-invasive localization of focal heart activity via body surface potential measurements (BSPM) could greatly benefit the understanding and treatment of arrhythmic heart diseases. However, the in vivo validation of source localization algorithms is rather difficult with currently available measurement techniques. In this study, we used a physical torso phantom composed of different conductive compartments and seven dipoles, which were placed in the anatomical position of the human heart in order to assess the performance of the Recursively Applied and Projected Multiple Signal Classification (RAP-MUSIC) algorithm. Electric potentials were measured on the torso surface for single dipoles with and without further uncorrelated or correlated dipole activity. The localization error averaged 11 ± 5 mm over 22 dipoles, which shows the ability of RAP-MUSIC to distinguish an uncorrelated dipole from surrounding sources activity. For the first time, real computational modelling errors could be included within the validation procedure due to the physically modelled heterogeneities. In conclusion, the introduced heterogeneous torso phantom can be used to validate state-of-the-art algorithms under nearly realistic measurement conditions.

Exact BPF and FBP algorithms for nonstandard saddle curves

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu Hengyong; Zhao Shiying; Ye Yangbo

2005-11-15

A hot topic in cone-beam CT research is exact cone-beam reconstruction from a general scanning trajectory. Particularly, a nonstandard saddle curve attracts attention, as this construct allows the continuous periodic scanning of a volume-of-interest (VOI). Here we evaluate two algorithms for reconstruction from data collected along a nonstandard saddle curve, which are in the filtered backprojection (FBP) and backprojection filtration (BPF) formats, respectively. Both the algorithms are implemented in a chord-based coordinate system. Then, a rebinning procedure is utilized to transform the reconstructed results into the natural coordinate system. The simulation results demonstrate that the FBP algorithm produces better imagemore » quality than the BPF algorithm, while both the algorithms exhibit similar noise characteristics.« less

New image-processing and noise-reduction software reduces radiation dose during complex endovascular procedures.

PubMed

Kirkwood, Melissa L; Guild, Jeffrey B; Arbique, Gary M; Tsai, Shirling; Modrall, J Gregory; Anderson, Jon A; Rectenwald, John; Timaran, Carlos

2016-11-01

A new proprietary image-processing system known as AlluraClarity, developed by Philips Healthcare (Best, The Netherlands) for radiation-based interventional procedures, claims to lower radiation dose while preserving image quality using noise-reduction algorithms. This study determined whether the surgeon and patient radiation dose during complex endovascular procedures (CEPs) is decreased after the implementation of this new operating system. Radiation dose to operators, procedure type, reference air kerma, kerma area product, and patient body mass index were recorded during CEPs on two Philips Allura FD 20 fluoroscopy systems with and without Clarity. Operator dose during CEPs was measured using optically stimulable, luminescent nanoDot (Landauer Inc, Glenwood, Ill) detectors placed outside the lead apron at the left upper chest position. nanoDots were read using a microStar ii (Landauer Inc) medical dosimetry system. For the CEPs in the Clarity group, the radiation dose to surgeons was also measured by the DoseAware (Philips Healthcare) personal dosimetry system. Side-by-side measurements of DoseAware and nanoDots allowed for cross-calibration between systems. Operator effective dose was determined using a modified Niklason algorithm. To control for patient size and case complexity, the average fluoroscopy dose rate and the dose per radiographic frame were adjusted for body mass index differences and then compared between the groups with and without Clarity by procedure. Additional factors, for example, physician practice patterns, that may have affected operator dose were inferred by comparing the ratio of the operator dose to procedural kerma area product with and without Clarity. A one-sided Wilcoxon rank sum test was used to compare groups for radiation doses, reference air kermas, and operating practices for each procedure type. The analysis included 234 CEPs; 95 performed without Clarity and 139 with Clarity. Practice patterns of operators during procedures with and without Clarity were not significantly different. For all cases, procedure radiation dose to the patient and the primary and assistant operators were significantly decreased in the Clarity group by 60% compared with the non-Clarity group. By procedure type, fluorography dose rates decreased from 44% for fenestrated endovascular repair and up to 70% with lower extremity interventions. Fluoroscopy dose rates also significantly decreased, from about 37% to 47%, depending on procedure type. The AlluraClarity system reduces the patient and primary operator's radiation dose by more than half during CEPs. This feature appears to be an effective tool in lowering the radiation dose while maintaining image quality. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

A Practical and Automated Approach to Large Area Forest Disturbance Mapping with Remote Sensing

PubMed Central

Ozdogan, Mutlu

2014-01-01

In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover change analysis over very large regions. PMID:24717283

A practical and automated approach to large area forest disturbance mapping with remote sensing.

PubMed

Ozdogan, Mutlu

2014-01-01

In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover change analysis over very large regions.

An efficient and accurate solution methodology for bilevel multi-objective programming problems using a hybrid evolutionary-local-search algorithm.

PubMed

Deb, Kalyanmoy; Sinha, Ankur

2010-01-01

Bilevel optimization problems involve two optimization tasks (upper and lower level), in which every feasible upper level solution must correspond to an optimal solution to a lower level optimization problem. These problems commonly appear in many practical problem solving tasks including optimal control, process optimization, game-playing strategy developments, transportation problems, and others. However, they are commonly converted into a single level optimization problem by using an approximate solution procedure to replace the lower level optimization task. Although there exist a number of theoretical, numerical, and evolutionary optimization studies involving single-objective bilevel programming problems, not many studies look at the context of multiple conflicting objectives in each level of a bilevel programming problem. In this paper, we address certain intricate issues related to solving multi-objective bilevel programming problems, present challenging test problems, and propose a viable and hybrid evolutionary-cum-local-search based algorithm as a solution methodology. The hybrid approach performs better than a number of existing methodologies and scales well up to 40-variable difficult test problems used in this study. The population sizing and termination criteria are made self-adaptive, so that no additional parameters need to be supplied by the user. The study indicates a clear niche of evolutionary algorithms in solving such difficult problems of practical importance compared to their usual solution by a computationally expensive nested procedure. The study opens up many issues related to multi-objective bilevel programming and hopefully this study will motivate EMO and other researchers to pay more attention to this important and difficult problem solving activity.

Algorithm development for Maxwell's equations for computational electromagnetism

NASA Technical Reports Server (NTRS)

Goorjian, Peter M.

1990-01-01

A new algorithm has been developed for solving Maxwell's equations for the electromagnetic field. It solves the equations in the time domain with central, finite differences. The time advancement is performed implicitly, using an alternating direction implicit procedure. The space discretization is performed with finite volumes, using curvilinear coordinates with electromagnetic components along those directions. Sample calculations are presented of scattering from a metal pin, a square and a circle to demonstrate the capabilities of the new algorithm.

Algorithms for Zonal Methods and Development of Three Dimensional Mesh Generation Procedures.

DTIC Science & Technology

1984-02-01

a r-re complete set of equations is used, but their effect is imposed by means of a right hand side forcing function, not by means of a zonal boundary...modifications of flow-simulation algorithms The explicit finite-difference code of Magnus and are discussed. Computational tests in two dimensions...used to simplify the task of grid generation without an adverse achieve computational efficiency. More recently, effect on flow-field algorithms and

Solution algorithms for the two-dimensional Euler equations on unstructured meshes

NASA Technical Reports Server (NTRS)

Whitaker, D. L.; Slack, David C.; Walters, Robert W.

1990-01-01

The objective of the study was to analyze implicit techniques employed in structured grid algorithms for solving two-dimensional Euler equations and extend them to unstructured solvers in order to accelerate convergence rates. A comparison is made between nine different algorithms for both first-order and second-order accurate solutions. Higher-order accuracy is achieved by using multidimensional monotone linear reconstruction procedures. The discussion is illustrated by results for flow over a transonic circular arc.

On the Solution of the Three-Dimensional Flowfield About a Flow-Through Nacelle. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Compton, William Bernard

1985-01-01

The solution of the three dimensional flow field for a flow through nacelle was studied. Both inviscid and viscous inviscid interacting solutions were examined. Inviscid solutions were obtained with two different computational procedures for solving the three dimensional Euler equations. The first procedure employs an alternating direction implicit numerical algorithm, and required the development of a complete computational model for the nacelle problem. The second computational technique employs a fourth order Runge-Kutta numerical algorithm which was modified to fit the nacelle problem. Viscous effects on the flow field were evaluated with a viscous inviscid interacting computational model. This model was constructed by coupling the explicit Euler solution procedure with a flag entrainment boundary layer solution procedure in a global iteration scheme. The computational techniques were used to compute the flow field for a long duct turbofan engine nacelle at free stream Mach numbers of 0.80 and 0.94 and angles of attack of 0 and 4 deg.

Algorithms for selecting informative marker panels for population assignment.

PubMed

Rosenberg, Noah A

2005-11-01

Given a set of potential source populations, genotypes of an individual of unknown origin at a collection of markers can be used to predict the correct source population of the individual. For improved efficiency, informative markers can be chosen from a larger set of markers to maximize the accuracy of this prediction. However, selecting the loci that are individually most informative does not necessarily produce the optimal panel. Here, using genotypes from eight species--carp, cat, chicken, dog, fly, grayling, human, and maize--this univariate accumulation procedure is compared to new multivariate "greedy" and "maximin" algorithms for choosing marker panels. The procedures generally suggest similar panels, although the greedy method often recommends inclusion of loci that are not chosen by the other algorithms. In seven of the eight species, when applied to five or more markers, all methods achieve at least 94% assignment accuracy on simulated individuals, with one species--dog--producing this level of accuracy with only three markers, and the eighth species--human--requiring approximately 13-16 markers. The new algorithms produce substantial improvements over use of randomly selected markers; where differences among the methods are noticeable, the greedy algorithm leads to slightly higher probabilities of correct assignment. Although none of the approaches necessarily chooses the panel with optimal performance, the algorithms all likely select panels with performance near enough to the maximum that they all are suitable for practical use.

Algorithm-Based Motion Magnification for Video Processing in Urological Laparoscopy.

PubMed

Adams, Fabian; Schoelly, Reto; Schlager, Daniel; Schoenthaler, Martin; Schoeb, Dominik S; Wilhelm, Konrad; Hein, Simon; Wetterauer, Ulrich; Miernik, Arkadiusz

2017-06-01

Minimally invasive surgery is in constant further development and has replaced many conventional operative procedures. If vascular structure movement could be detected during these procedures, it could reduce the risk of vascular injury and conversion to open surgery. The recently proposed motion-amplifying algorithm, Eulerian Video Magnification (EVM), has been shown to substantially enhance minimal object changes in digitally recorded video that is barely perceptible to the human eye. We adapted and examined this technology for use in urological laparoscopy. Video sequences of routine urological laparoscopic interventions were recorded and further processed using spatial decomposition and filtering algorithms. The freely available EVM algorithm was investigated for its usability in real-time processing. In addition, a new image processing technology, the CRS iimotion Motion Magnification (CRSMM) algorithm, was specifically adjusted for endoscopic requirements, applied, and validated by our working group. Using EVM, no significant motion enhancement could be detected without severe impairment of the image resolution, motion, and color presentation. The CRSMM algorithm significantly improved image quality in terms of motion enhancement. In particular, the pulsation of vascular structures could be displayed more accurately than in EVM. Motion magnification image processing technology has the potential for clinical importance as a video optimizing modality in endoscopic and laparoscopic surgery. Barely detectable (micro)movements can be visualized using this noninvasive marker-free method. Despite these optimistic results, the technology requires considerable further technical development and clinical tests.

Computational benefits using artificial intelligent methodologies for the solution of an environmental design problem: saltwater intrusion.

PubMed

Papadopoulou, Maria P; Nikolos, Ioannis K; Karatzas, George P

2010-01-01

Artificial Neural Networks (ANNs) comprise a powerful tool to approximate the complicated behavior and response of physical systems allowing considerable reduction in computation time during time-consuming optimization runs. In this work, a Radial Basis Function Artificial Neural Network (RBFN) is combined with a Differential Evolution (DE) algorithm to solve a water resources management problem, using an optimization procedure. The objective of the optimization scheme is to cover the daily water demand on the coastal aquifer east of the city of Heraklion, Crete, without reducing the subsurface water quality due to seawater intrusion. The RBFN is utilized as an on-line surrogate model to approximate the behavior of the aquifer and to replace some of the costly evaluations of an accurate numerical simulation model which solves the subsurface water flow differential equations. The RBFN is used as a local approximation model in such a way as to maintain the robustness of the DE algorithm. The results of this procedure are compared to the corresponding results obtained by using the Simplex method and by using the DE procedure without the surrogate model. As it is demonstrated, the use of the surrogate model accelerates the convergence of the DE optimization procedure and additionally provides a better solution at the same number of exact evaluations, compared to the original DE algorithm.

Determination of Optimal Subsidy for Materials Saving Investment through Recycle/Recovery at Industrial Level

NASA Astrophysics Data System (ADS)

Batzias, Dimitris F.

2009-08-01

This work deals with a methodological framework under the form of a simple/short algorithmic procedure (including 11 activity steps and 3 decision nodes) designed/developed for the determination of optimal subsidy for materials saving investment through recycle/recovery (RR) at industrial level. Two case examples are presented, covering both aspects, without and with recycling. The expected Relative Cost Decrease (RCD) because of recycling, which forms a critical index for decision making on subsidizing, is estimated. The developed procedure can be extended outside the industrial unit to include collection/transportation/processing of recyclable wasted products. Since, in such a case, transportation cost and processing cost are conflict depended variables (when the quantity collected/processed Q is the independent/explanatory variable), the determination of Qopt is examined under energy crises conditions, when corresponding subsidies might be granted to re-set the original equilibrium and avoid putting the recycling enterprise in jeopardize due to dangerous lowering of the first break-even point.

Pressure ulcer prevention algorithm content validation: a mixed-methods, quantitative study.

PubMed

van Rijswijk, Lia; Beitz, Janice M

2015-04-01

Translating pressure ulcer prevention (PUP) evidence-based recommendations into practice remains challenging for a variety of reasons, including the perceived quality, validity, and usability of the research or the guideline itself. Following the development and face validation testing of an evidence-based PUP algorithm, additional stakeholder input and testing were needed. Using convenience sampling methods, wound care experts attending a national wound care conference and a regional wound ostomy continence nursing (WOCN) conference and/or graduates of a WOCN program were invited to participate in an Internal Review Board-approved, mixed-methods quantitative survey with qualitative components to examine algorithm content validity. After participants provided written informed consent, demographic variables were collected and participants were asked to comment on and rate the relevance and appropriateness of each of the 26 algorithm decision points/steps using standard content validation study procedures. All responses were anonymous. Descriptive summary statistics, mean relevance/appropriateness scores, and the content validity index (CVI) were calculated. Qualitative comments were transcribed and thematically analyzed. Of the 553 wound care experts invited, 79 (average age 52.9 years, SD 10.1; range 23-73) consented to participate and completed the study (a response rate of 14%). Most (67, 85%) were female, registered (49, 62%) or advanced practice (12, 15%) nurses, and had > 10 years of health care experience (88, 92%). Other health disciplines included medical doctors, physical therapists, nurse practitioners, and certified nurse specialists. Almost all had received formal wound care education (75, 95%). On a Likert-type scale of 1 (not relevant/appropriate) to 4 (very relevant and appropriate), the average score for the entire algorithm/all decision points (N = 1,912) was 3.72 with an overall CVI of 0.94 (out of 1). The only decision point/step recommendation with a CVI of ≤ 0.70 was the recommendation to provide medical-grade sheepskin for patients at high risk for friction/shear. Many positive and substantive suggestions for minor modifications including color, flow, and algorithm orientation were received. The high overall and individual item rating scores and CVI further support the validity and appropriateness of the PUP algorithm with the addition of the minor modifications. The generic recommendations facilitate individualization, and future research should focus on construct validation testing.

The Krigifier: A Procedure for Generating Pseudorandom Nonlinear Objective Functions for Computational Experimentation

NASA Technical Reports Server (NTRS)

Trosset, Michael W.

1999-01-01

Comprehensive computational experiments to assess the performance of algorithms for numerical optimization require (among other things) a practical procedure for generating pseudorandom nonlinear objective functions. We propose a procedure that is based on the convenient fiction that objective functions are realizations of stochastic processes. This report details the calculations necessary to implement our procedure for the case of certain stationary Gaussian processes and presents a specific implementation in the statistical programming language S-PLUS.

Modelling Systems of Classical/Quantum Identical Particles by Focusing on Algorithms

ERIC Educational Resources Information Center

Guastella, Ivan; Fazio, Claudio; Sperandeo-Mineo, Rosa Maria

2012-01-01

A procedure modelling ideal classical and quantum gases is discussed. The proposed approach is mainly based on the idea that modelling and algorithm analysis can provide a deeper understanding of particularly complex physical systems. Appropriate representations and physical models able to mimic possible pseudo-mechanisms of functioning and having…

Penalized regression procedures for variable selection in the potential outcomes framework

PubMed Central

Ghosh, Debashis; Zhu, Yeying; Coffman, Donna L.

2015-01-01

A recent topic of much interest in causal inference is model selection. In this article, we describe a framework in which to consider penalized regression approaches to variable selection for causal effects. The framework leads to a simple ‘impute, then select’ class of procedures that is agnostic to the type of imputation algorithm as well as penalized regression used. It also clarifies how model selection involves a multivariate regression model for causal inference problems, and that these methods can be applied for identifying subgroups in which treatment effects are homogeneous. Analogies and links with the literature on machine learning methods, missing data and imputation are drawn. A difference LASSO algorithm is defined, along with its multiple imputation analogues. The procedures are illustrated using a well-known right heart catheterization dataset. PMID:25628185

Physical and cognitive task analysis in interventional radiology.

PubMed

Johnson, S; Healey, A; Evans, J; Murphy, M; Crawshaw, M; Gould, D

2006-01-01

To identify, describe and detail the cognitive thought processes, decision-making, and physical actions involved in the preparation and successful performance of core interventional radiology procedures. Five commonly performed core interventional radiology procedures were selected for cognitive task analysis. Several examples of each procedure being performed by consultant interventional radiologists were videoed. The videos of those procedures, and the steps required for successful outcome, were analysed by a psychologist and an interventional radiologist. Once a skeleton algorithm of the procedures was defined, further refinement was achieved using individual interview techniques with consultant interventional radiologists. Additionally a critique of each iteration of the established algorithm was sought from non-participating independent consultant interventional radiologists. Detailed task descriptions and decision protocols were developed for five interventional radiology procedures (arterial puncture, nephrostomy, venous access, biopsy-using both ultrasound and computed tomography, and percutaneous transhepatic cholangiogram). Identical tasks performed within these procedures were identified and standardized within the protocols. Complex procedures were broken down and their constituent processes identified. This might be suitable for use as a training protocol to provide a universally acceptable safe practice at the most fundamental level. It is envisaged that data collected in this way can be used as an educational resource for trainees and could provide the basis for a training curriculum in interventional radiology. It will direct trainees towards safe practice of the highest standard. It will also provide performance objectives of a simulator model.

Feature detection on 3D images of dental imprints

NASA Astrophysics Data System (ADS)

Mokhtari, Marielle; Laurendeau, Denis

1994-09-01

A computer vision approach for the extraction of feature points on 3D images of dental imprints is presented. The position of feature points are needed for the measurement of a set of parameters for automatic diagnosis of malocclusion problems in orthodontics. The system for the acquisition of the 3D profile of the imprint, the procedure for the detection of the interstices between teeth, and the approach for the identification of the type of tooth are described, as well as the algorithm for the reconstruction of the surface of each type of tooth. A new approach for the detection of feature points, called the watershed algorithm, is described in detail. The algorithm is a two-stage procedure which tracks the position of local minima at four different scales and produces a final map of the position of the minima. Experimental results of the application of the watershed algorithm on actual 3D images of dental imprints are presented for molars, premolars and canines. The segmentation approach for the analysis of the shape of incisors is also described in detail.

End-point detection in potentiometric titration by continuous wavelet transform.

PubMed

Jakubowska, Małgorzata; Baś, Bogusław; Kubiak, Władysław W

2009-10-15

The aim of this work was construction of the new wavelet function and verification that a continuous wavelet transform with a specially defined dedicated mother wavelet is a useful tool for precise detection of end-point in a potentiometric titration. The proposed algorithm does not require any initial information about the nature or the type of analyte and/or the shape of the titration curve. The signal imperfection, as well as random noise or spikes has no influence on the operation of the procedure. The optimization of the new algorithm was done using simulated curves and next experimental data were considered. In the case of well-shaped and noise-free titration data, the proposed method gives the same accuracy and precision as commonly used algorithms. But, in the case of noisy or badly shaped curves, the presented approach works good (relative error mainly below 2% and coefficients of variability below 5%) while traditional procedures fail. Therefore, the proposed algorithm may be useful in interpretation of the experimental data and also in automation of the typical titration analysis, specially in the case when random noise interfere with analytical signal.

Application of modern control theory to the design of optimum aircraft controllers

NASA Technical Reports Server (NTRS)

Power, L. J.

1973-01-01

The synthesis procedure presented is based on the solution of the output regulator problem of linear optimal control theory for time-invariant systems. By this technique, solution of the matrix Riccati equation leads to a constant linear feedback control law for an output regulator which will maintain a plant in a particular equilibrium condition in the presence of impulse disturbances. Two simple algorithms are presented that can be used in an automatic synthesis procedure for the design of maneuverable output regulators requiring only selected state variables for feedback. The first algorithm is for the construction of optimal feedforward control laws that can be superimposed upon a Kalman output regulator and that will drive the output of a plant to a desired constant value on command. The second algorithm is for the construction of optimal Luenberger observers that can be used to obtain feedback control laws for the output regulator requiring measurement of only part of the state vector. This algorithm constructs observers which have minimum response time under the constraint that the magnitude of the gains in the observer filter be less than some arbitrary limit.

A targeted change-detection procedure by combining change vector analysis and post-classification approach

NASA Astrophysics Data System (ADS)

Ye, Su; Chen, Dongmei; Yu, Jie

2016-04-01

In remote sensing, conventional supervised change-detection methods usually require effective training data for multiple change types. This paper introduces a more flexible and efficient procedure that seeks to identify only the changes that users are interested in, here after referred to as "targeted change detection". Based on a one-class classifier "Support Vector Domain Description (SVDD)", a novel algorithm named "Three-layer SVDD Fusion (TLSF)" is developed specially for targeted change detection. The proposed algorithm combines one-class classification generated from change vector maps, as well as before- and after-change images in order to get a more reliable detecting result. In addition, this paper introduces a detailed workflow for implementing this algorithm. This workflow has been applied to two case studies with different practical monitoring objectives: urban expansion and forest fire assessment. The experiment results of these two case studies show that the overall accuracy of our proposed algorithm is superior (Kappa statistics are 86.3% and 87.8% for Case 1 and 2, respectively), compared to applying SVDD to change vector analysis and post-classification comparison.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stoiber, Marcus H.; Brown, James B.

This software implements the first base caller for nanopore data that calls bases directly from raw data. The basecRAWller algorithm has two major advantages over current nanopore base calling software: (1) streaming base calling and (2) base calling from information rich raw signal. The ability to perform truly streaming base calling as signal is received from the sequencer can be very powerful as this is one of the major advantages of this technology as compared to other sequencing technologies. As such enabling as much streaming potential as possible will be incredibly important as this technology continues to become more widelymore » applied in biosciences. All other base callers currently employ the Viterbi algorithm which requires the whole sequence to employ the complete base calling procedure and thus precludes a natural streaming base calling procedure. The other major advantage of the basecRAWller algorithm is the prediction of bases from raw signal which contains much richer information than the segmented chunks that current algorithms employ. This leads to the potential for much more accurate base calls which would make this technology much more valuable to all of the growing user base for this technology.« less

Improving the Held and Karp Approach with Constraint Programming

NASA Astrophysics Data System (ADS)

Benchimol, Pascal; Régin, Jean-Charles; Rousseau, Louis-Martin; Rueher, Michel; van Hoeve, Willem-Jan

Held and Karp have proposed, in the early 1970s, a relaxation for the Traveling Salesman Problem (TSP) as well as a branch-and-bound procedure that can solve small to modest-size instances to optimality [4, 5]. It has been shown that the Held-Karp relaxation produces very tight bounds in practice, and this relaxation is therefore applied in TSP solvers such as Concorde [1]. In this short paper we show that the Held-Karp approach can benefit from well-known techniques in Constraint Programming (CP) such as domain filtering and constraint propagation. Namely, we show that filtering algorithms developed for the weighted spanning tree constraint [3, 8] can be adapted to the context of the Held and Karp procedure. In addition to the adaptation of existing algorithms, we introduce a special-purpose filtering algorithm based on the underlying mechanisms used in Prim's algorithm [7]. Finally, we explored two different branching schemes to close the integrality gap. Our initial experimental results indicate that the addition of the CP techniques to the Held-Karp method can be very effective.

Using video-oriented instructions to speed up sequence comparison.

PubMed

Wozniak, A

1997-04-01

This document presents an implementation of the well-known Smith-Waterman algorithm for comparison of proteic and nucleic sequences, using specialized video instructions. These instructions, SIMD-like in their design, make possible parallelization of the algorithm at the instruction level. Benchmarks on an ULTRA SPARC running at 167 MHz show a speed-up factor of two compared to the same algorithm implemented with integer instructions on the same machine. Performance reaches over 18 million matrix cells per second on a single processor, giving to our knowledge the fastest implementation of the Smith-Waterman algorithm on a workstation. The accelerated procedure was introduced in LASSAP--a LArge Scale Sequence compArison Package software developed at INRIA--which handles parallelism at higher level. On a SUN Enterprise 6000 server with 12 processors, a speed of nearly 200 million matrix cells per second has been obtained. A sequence of length 300 amino acids is scanned against SWISSPROT R33 (1,8531,385 residues) in 29 s. This procedure is not restricted to databank scanning. It applies to all cases handled by LASSAP (intra- and inter-bank comparisons, Z-score computation, etc.

Combinatorial approximation algorithms for MAXCUT using random walks.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seshadhri, Comandur; Kale, Satyen

We give the first combinatorial approximation algorithm for MaxCut that beats the trivial 0.5 factor by a constant. The main partitioning procedure is very intuitive, natural, and easily described. It essentially performs a number of random walks and aggregates the information to provide the partition. We can control the running time to get an approximation factor-running time tradeoff. We show that for any constant b > 1.5, there is an {tilde O}(n{sup b}) algorithm that outputs a (0.5 + {delta})-approximation for MaxCut, where {delta} = {delta}(b) is some positive constant. One of the components of our algorithm is a weakmore » local graph partitioning procedure that may be of independent interest. Given a starting vertex i and a conductance parameter {phi}, unless a random walk of length {ell} = O(log n) starting from i mixes rapidly (in terms of {phi} and {ell}), we can find a cut of conductance at most {phi} close to the vertex. The work done per vertex found in the cut is sublinear in n.« less

Improved genetic algorithm for the protein folding problem by use of a Cartesian combination operator.

PubMed Central

Rabow, A. A.; Scheraga, H. A.

1996-01-01

We have devised a Cartesian combination operator and coding scheme for improving the performance of genetic algorithms applied to the protein folding problem. The genetic coding consists of the C alpha Cartesian coordinates of the protein chain. The recombination of the genes of the parents is accomplished by: (1) a rigid superposition of one parent chain on the other, to make the relation of Cartesian coordinates meaningful, then, (2) the chains of the children are formed through a linear combination of the coordinates of their parents. The children produced with this Cartesian combination operator scheme have similar topology and retain the long-range contacts of their parents. The new scheme is significantly more efficient than the standard genetic algorithm methods for locating low-energy conformations of proteins. The considerable superiority of genetic algorithms over Monte Carlo optimization methods is also demonstrated. We have also devised a new dynamic programming lattice fitting procedure for use with the Cartesian combination operator method. The procedure finds excellent fits of real-space chains to the lattice while satisfying bond-length, bond-angle, and overlap constraints. PMID:8880904

Development of simulation techniques suitable for the analysis of air traffic control situations and instrumentation

NASA Technical Reports Server (NTRS)

1972-01-01

A terminal area simulation is described which permits analysis and synthesis of current and advanced air traffic management system configurations including ground and airborne instrumentation and new and modified aircraft characteristics. Ground elements in the simulation include navigation aids, surveillance radars, communication links, air-route structuring, ATC procedures, airport geometries and runway handling constraints. Airborne elements include traffic samples with individual aircraft performance and operating characteristics and aircraft navigation equipment. The simulation also contains algorithms for conflict detection, conflict resolution, sequencing and pilot-controller data links. The simulation model is used to determine the sensitivities of terminal area traffic flow, safety and congestion to aircraft performance characteristics, avionics systems, and other ATC elements.

Exploring the Energy Landscapes of Protein Folding Simulations with Bayesian Computation

PubMed Central

Burkoff, Nikolas S.; Várnai, Csilla; Wells, Stephen A.; Wild, David L.

2012-01-01

Nested sampling is a Bayesian sampling technique developed to explore probability distributions localized in an exponentially small area of the parameter space. The algorithm provides both posterior samples and an estimate of the evidence (marginal likelihood) of the model. The nested sampling algorithm also provides an efficient way to calculate free energies and the expectation value of thermodynamic observables at any temperature, through a simple post processing of the output. Previous applications of the algorithm have yielded large efficiency gains over other sampling techniques, including parallel tempering. In this article, we describe a parallel implementation of the nested sampling algorithm and its application to the problem of protein folding in a Gō-like force field of empirical potentials that were designed to stabilize secondary structure elements in room-temperature simulations. We demonstrate the method by conducting folding simulations on a number of small proteins that are commonly used for testing protein-folding procedures. A topological analysis of the posterior samples is performed to produce energy landscape charts, which give a high-level description of the potential energy surface for the protein folding simulations. These charts provide qualitative insights into both the folding process and the nature of the model and force field used. PMID:22385859

Topology design and performance analysis of an integrated communication network

NASA Technical Reports Server (NTRS)

Li, V. O. K.; Lam, Y. F.; Hou, T. C.; Yuen, J. H.

1985-01-01

A research study on the topology design and performance analysis for the Space Station Information System (SSIS) network is conducted. It is begun with a survey of existing research efforts in network topology design. Then a new approach for topology design is presented. It uses an efficient algorithm to generate candidate network designs (consisting of subsets of the set of all network components) in increasing order of their total costs, and checks each design to see if it forms an acceptable network. This technique gives the true cost-optimal network, and is particularly useful when the network has many constraints and not too many components. The algorithm for generating subsets is described in detail, and various aspects of the overall design procedure are discussed. Two more efficient versions of this algorithm (applicable in specific situations) are also given. Next, two important aspects of network performance analysis: network reliability and message delays are discussed. A new model is introduced to study the reliability of a network with dependent failures. For message delays, a collection of formulas from existing research results is given to compute or estimate the delays of messages in a communication network without making the independence assumption. The design algorithm coded in PASCAL is included as an appendix.

Exploring the energy landscapes of protein folding simulations with Bayesian computation.

PubMed

Burkoff, Nikolas S; Várnai, Csilla; Wells, Stephen A; Wild, David L

2012-02-22

Nested sampling is a Bayesian sampling technique developed to explore probability distributions localized in an exponentially small area of the parameter space. The algorithm provides both posterior samples and an estimate of the evidence (marginal likelihood) of the model. The nested sampling algorithm also provides an efficient way to calculate free energies and the expectation value of thermodynamic observables at any temperature, through a simple post processing of the output. Previous applications of the algorithm have yielded large efficiency gains over other sampling techniques, including parallel tempering. In this article, we describe a parallel implementation of the nested sampling algorithm and its application to the problem of protein folding in a Gō-like force field of empirical potentials that were designed to stabilize secondary structure elements in room-temperature simulations. We demonstrate the method by conducting folding simulations on a number of small proteins that are commonly used for testing protein-folding procedures. A topological analysis of the posterior samples is performed to produce energy landscape charts, which give a high-level description of the potential energy surface for the protein folding simulations. These charts provide qualitative insights into both the folding process and the nature of the model and force field used. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Procedure of Partitioning Data Into Number of Data Sets or Data Group - A Review

NASA Astrophysics Data System (ADS)

Kim, Tai-Hoon

The goal of clustering is to decompose a dataset into similar groups based on a objective function. Some already well established clustering algorithms are there for data clustering. Objective of these data clustering algorithms are to divide the data points of the feature space into a number of groups (or classes) so that a predefined set of criteria are satisfied. The article considers the comparative study about the effectiveness and efficiency of traditional data clustering algorithms. For evaluating the performance of the clustering algorithms, Minkowski score is used here for different data sets.

Algorithm implementation on the Navier-Stokes computer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krist, S.E.; Zang, T.A.

1987-03-01

The Navier-Stokes Computer is a multi-purpose parallel-processing supercomputer which is currently under development at Princeton University. It consists of multiple local memory parallel processors, called Nodes, which are interconnected in a hypercube network. Details of the procedures involved in implementing an algorithm on the Navier-Stokes computer are presented. The particular finite difference algorithm considered in this analysis was developed for simulation of laminar-turbulent transition in wall bounded shear flows. Projected timing results for implementing this algorithm indicate that operation rates in excess of 42 GFLOPS are feasible on a 128 Node machine.

Algorithm implementation on the Navier-Stokes computer

NASA Technical Reports Server (NTRS)

Krist, Steven E.; Zang, Thomas A.

1987-01-01

The Navier-Stokes Computer is a multi-purpose parallel-processing supercomputer which is currently under development at Princeton University. It consists of multiple local memory parallel processors, called Nodes, which are interconnected in a hypercube network. Details of the procedures involved in implementing an algorithm on the Navier-Stokes computer are presented. The particular finite difference algorithm considered in this analysis was developed for simulation of laminar-turbulent transition in wall bounded shear flows. Projected timing results for implementing this algorithm indicate that operation rates in excess of 42 GFLOPS are feasible on a 128 Node machine.

An ILP based memetic algorithm for finding minimum positive influence dominating sets in social networks

NASA Astrophysics Data System (ADS)

Lin, Geng; Guan, Jian; Feng, Huibin

2018-06-01

The positive influence dominating set problem is a variant of the minimum dominating set problem, and has lots of applications in social networks. It is NP-hard, and receives more and more attention. Various methods have been proposed to solve the positive influence dominating set problem. However, most of the existing work focused on greedy algorithms, and the solution quality needs to be improved. In this paper, we formulate the minimum positive influence dominating set problem as an integer linear programming (ILP), and propose an ILP based memetic algorithm (ILPMA) for solving the problem. The ILPMA integrates a greedy randomized adaptive construction procedure, a crossover operator, a repair operator, and a tabu search procedure. The performance of ILPMA is validated on nine real-world social networks with nodes up to 36,692. The results show that ILPMA significantly improves the solution quality, and is robust.

Solution procedure of dynamical contact problems with friction

NASA Astrophysics Data System (ADS)

Abdelhakim, Lotfi

2017-07-01

Dynamical contact is one of the common research topics because of its wide applications in the engineering field. The main goal of this work is to develop a time-stepping algorithm for dynamic contact problems. We propose a finite element approach for elastodynamics contact problems [1]. Sticking, sliding and frictional contact can be taken into account. Lagrange multipliers are used to enforce non-penetration condition. For the time discretization, we propose a scheme equivalent to the explicit Newmark scheme. Each time step requires solving a nonlinear problem similar to a static friction problem. The nonlinearity of the system of equation needs an iterative solution procedure based on Uzawa's algorithm [2][3]. The applicability of the algorithm is illustrated by selected sample numerical solutions to static and dynamic contact problems. Results obtained with the model have been compared and verified with results from an independent numerical method.

Feedback control for unsteady flow and its application to the stochastic Burgers equation

NASA Technical Reports Server (NTRS)

Choi, Haecheon; Temam, Roger; Moin, Parviz; Kim, John

1993-01-01

The study applies mathematical methods of control theory to the problem of control of fluid flow with the long-range objective of developing effective methods for the control of turbulent flows. Model problems are employed through the formalism and language of control theory to present the procedure of how to cast the problem of controlling turbulence into a problem in optimal control theory. Methods of calculus of variations through the adjoint state and gradient algorithms are used to present a suboptimal control and feedback procedure for stationary and time-dependent problems. Two types of controls are investigated: distributed and boundary controls. Several cases of both controls are numerically simulated to investigate the performances of the control algorithm. Most cases considered show significant reductions of the costs to be minimized. The dependence of the control algorithm on the time-descretization method is discussed.

Validation of Community Models: Identifying Events in Space Weather Model Timelines

NASA Technical Reports Server (NTRS)

MacNeice, Peter

2009-01-01

I develop and document a set of procedures which test the quality of predictions of solar wind speed and polarity of the interplanetary magnetic field (IMF) made by coupled models of the ambient solar corona and heliosphere. The Wang-Sheeley-Arge (WSA) model is used to illustrate the application of these validation procedures. I present an algorithm which detects transitions of the solar wind from slow to high speed. I also present an algorithm which processes the measured polarity of the outward directed component of the IMF. This removes high-frequency variations to expose the longer-scale changes that reflect IMF sector changes. I apply these algorithms to WSA model predictions made using a small set of photospheric synoptic magnetograms obtained by the Global Oscillation Network Group as input to the model. The results of this preliminary validation of the WSA model (version 1.6) are summarized.

An Online Dictionary Learning-Based Compressive Data Gathering Algorithm in Wireless Sensor Networks

PubMed Central

Wang, Donghao; Wan, Jiangwen; Chen, Junying; Zhang, Qiang

2016-01-01

To adapt to sense signals of enormous diversities and dynamics, and to decrease the reconstruction errors caused by ambient noise, a novel online dictionary learning method-based compressive data gathering (ODL-CDG) algorithm is proposed. The proposed dictionary is learned from a two-stage iterative procedure, alternately changing between a sparse coding step and a dictionary update step. The self-coherence of the learned dictionary is introduced as a penalty term during the dictionary update procedure. The dictionary is also constrained with sparse structure. It’s theoretically demonstrated that the sensing matrix satisfies the restricted isometry property (RIP) with high probability. In addition, the lower bound of necessary number of measurements for compressive sensing (CS) reconstruction is given. Simulation results show that the proposed ODL-CDG algorithm can enhance the recovery accuracy in the presence of noise, and reduce the energy consumption in comparison with other dictionary based data gathering methods. PMID:27669250

An Online Dictionary Learning-Based Compressive Data Gathering Algorithm in Wireless Sensor Networks.

PubMed

Wang, Donghao; Wan, Jiangwen; Chen, Junying; Zhang, Qiang

2016-09-22

To adapt to sense signals of enormous diversities and dynamics, and to decrease the reconstruction errors caused by ambient noise, a novel online dictionary learning method-based compressive data gathering (ODL-CDG) algorithm is proposed. The proposed dictionary is learned from a two-stage iterative procedure, alternately changing between a sparse coding step and a dictionary update step. The self-coherence of the learned dictionary is introduced as a penalty term during the dictionary update procedure. The dictionary is also constrained with sparse structure. It's theoretically demonstrated that the sensing matrix satisfies the restricted isometry property (RIP) with high probability. In addition, the lower bound of necessary number of measurements for compressive sensing (CS) reconstruction is given. Simulation results show that the proposed ODL-CDG algorithm can enhance the recovery accuracy in the presence of noise, and reduce the energy consumption in comparison with other dictionary based data gathering methods.

Wavelet compression of multichannel ECG data by enhanced set partitioning in hierarchical trees algorithm.

PubMed

Sharifahmadian, Ershad

2006-01-01

The set partitioning in hierarchical trees (SPIHT) algorithm is very effective and computationally simple technique for image and signal compression. Here the author modified the algorithm which provides even better performance than the SPIHT algorithm. The enhanced set partitioning in hierarchical trees (ESPIHT) algorithm has performance faster than the SPIHT algorithm. In addition, the proposed algorithm reduces the number of bits in a bit stream which is stored or transmitted. I applied it to compression of multichannel ECG data. Also, I presented a specific procedure based on the modified algorithm for more efficient compression of multichannel ECG data. This method employed on selected records from the MIT-BIH arrhythmia database. According to experiments, the proposed method attained the significant results regarding compression of multichannel ECG data. Furthermore, in order to compress one signal which is stored for a long time, the proposed multichannel compression method can be utilized efficiently.

Real-time minimal-bit-error probability decoding of convolutional codes

NASA Technical Reports Server (NTRS)

Lee, L.-N.

1974-01-01

A recursive procedure is derived for decoding of rate R = 1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit, subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e., fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications, such as in the inner coding system for concatenated coding.

Real-time minimal bit error probability decoding of convolutional codes

NASA Technical Reports Server (NTRS)

Lee, L. N.

1973-01-01

A recursive procedure is derived for decoding of rate R=1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e. fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications such as in the inner coding system for concatenated coding.

Algorithm That Synthesizes Other Algorithms for Hashing

NASA Technical Reports Server (NTRS)

James, Mark

2010-01-01

An algorithm that includes a collection of several subalgorithms has been devised as a means of synthesizing still other algorithms (which could include computer code) that utilize hashing to determine whether an element (typically, a number or other datum) is a member of a set (typically, a list of numbers). Each subalgorithm synthesizes an algorithm (e.g., a block of code) that maps a static set of key hashes to a somewhat linear monotonically increasing sequence of integers. The goal in formulating this mapping is to cause the length of the sequence thus generated to be as close as practicable to the original length of the set and thus to minimize gaps between the elements. The advantage of the approach embodied in this algorithm is that it completely avoids the traditional approach of hash-key look-ups that involve either secondary hash generation and look-up or further searching of a hash table for a desired key in the event of collisions. This algorithm guarantees that it will never be necessary to perform a search or to generate a secondary key in order to determine whether an element is a member of a set. This algorithm further guarantees that any algorithm that it synthesizes can be executed in constant time. To enforce these guarantees, the subalgorithms are formulated to employ a set of techniques, each of which works very effectively covering a certain class of hash-key values. These subalgorithms are of two types, summarized as follows: Given a list of numbers, try to find one or more solutions in which, if each number is shifted to the right by a constant number of bits and then masked with a rotating mask that isolates a set of bits, a unique number is thereby generated. In a variant of the foregoing procedure, omit the masking. Try various combinations of shifting, masking, and/or offsets until the solutions are found. From the set of solutions, select the one that provides the greatest compression for the representation and is executable in the minimum amount of time. Given a list of numbers, try to find one or more solutions in which, if each number is compressed by use of the modulo function by some value, then a unique value is generated.

On the inter-instrument and the inter-laboratory transferability of a tandem mass spectral reference library: 2. Optimization and characterization of the search algorithm.

PubMed

Oberacher, Herbert; Pavlic, Marion; Libiseller, Kathrin; Schubert, Birthe; Sulyok, Michael; Schuhmacher, Rainer; Csaszar, Edina; Köfeler, Harald C

2009-04-01

A sophisticated matching algorithm developed for highly efficient identity search within tandem mass spectral libraries is presented. For the optimization of the search procedure a collection of 410 tandem mass spectra corresponding to 22 compounds was used. The spectra were acquired in three different laboratories on four different instruments. The following types of tandem mass spectrometric instruments were used: quadrupole-quadrupole-time-of-flight (QqTOF), quadrupole-quadrupole-linear ion trap (QqLIT), quadrupole-quadrupole-quadrupole (QqQ), and linear ion trap-Fourier transform ion cyclotron resonance mass spectrometer (LIT-FTICR). The obtained spectra were matched to an established MS/MS-spectral library that contained 3759 MS/MS-spectra corresponding to 402 different reference compounds. All 22 test compounds were part of the library. A dynamic intensity cut-off, the search for neutral losses, and optimization of the formula used to calculate the match probability were shown to significantly enhance the performance of the presented library search approach. With the aid of these features the average number of correct assignments was increased to 98%. For statistical evaluation of the match reliability the set of fragment ion spectra was extended with 300 spectra corresponding to 100 compounds not included in the reference library. Performance was checked with the aid of receiver operating characteristic (ROC) curves. Using the magnitude of the match probability as well as the precursor ion mass as benchmarks to rate the obtained top hit, overall correct classification of a compound being included or not included in the mass spectrometric library, was obtained in more than 95% of cases clearly indicating a high predictive accuracy of the established matching procedure. Copyright (c) 2009 John Wiley & Sons, Ltd.

Prevalidation in pharmaceutical analysis. Part I. Fundamentals and critical discussion.

PubMed

Grdinić, Vladimir; Vuković, Jadranka

2004-05-28

A complete prevalidation, as a basic prevalidation strategy for quality control and standardization of analytical procedure was inaugurated. Fast and simple, the prevalidation methodology based on mathematical/statistical evaluation of a reduced number of experiments (N < or = 24) was elaborated and guidelines as well as algorithms were given in detail. This strategy has been produced for the pharmaceutical applications and dedicated to the preliminary evaluation of analytical methods where linear calibration model, which is very often occurred in practice, could be the most appropriate to fit experimental data. The requirements presented in this paper should therefore help the analyst to design and perform the minimum number of prevalidation experiments needed to obtain all the required information to evaluate and demonstrate the reliability of its analytical procedure. In complete prevalidation process, characterization of analytical groups, checking of two limiting groups, testing of data homogeneity, establishment of analytical functions, recognition of outliers, evaluation of limiting values and extraction of prevalidation parameters were included. Moreover, system of diagnosis for particular prevalidation step was suggested. As an illustrative example for demonstration of feasibility of prevalidation methodology, among great number of analytical procedures, Vis-spectrophotometric procedure for determination of tannins with Folin-Ciocalteu's phenol reagent was selected. Favourable metrological characteristics of this analytical procedure, as prevalidation figures of merit, recognized the metrological procedure as a valuable concept in preliminary evaluation of quality of analytical procedures.

Precession-nutation procedures consistent with IAU 2006 resolutions

NASA Astrophysics Data System (ADS)

Wallace, P. T.; Capitaine, N.

2006-12-01

Context: .The 2006 IAU General Assembly has adopted the P03 model of Capitaine et al. (2003a) recommended by the WG on precession and the ecliptic (Hilton et al. 2006) to replace the IAU 2000 model, which comprised the Lieske et al. (1977) model with adjusted rates. Practical implementations of this new "IAU 2006" model are therefore required, involving choices of procedures and algorithms. Aims: .The purpose of this paper is to recommend IAU 2006 based precession-nutation computing procedures, suitable for different classes of application and achieving high standards of consistency. Methods: .We discuss IAU 2006 based procedures and algorithms for generating the rotation matrices that transform celestial to terrestrial coordinates, taking into account frame bias (B), P03 precession (P), P03-adjusted IAU 2000A nutation (N) and Earth rotation. The NPB portion can refer either to the equinox or to the celestial intermediate origin (CIO), requiring either the Greenwich sidereal time (GST) or the Earth rotation angle (ERA) as the measure of Earth rotation. Where GST is used, it is derived from ERA and the equation of the origins (EO) rather than through an explicit formula as in the past, and the EO itself is derived from the CIO locator. Results: .We provide precession-nutation procedures for two different classes of full-accuracy application, namely (i) the construction of algorithm collections such as the Standards Of Fundamental Astronomy (SOFA) library and (ii) IERS Conventions, and in addition some concise procedures for applications where the highest accuracy is not a requirement. The appendix contains a fully worked numerical example, to aid implementors and to illustrate the consistency of the two full-accuracy procedures which, for the test date, agree to better than 1 μas. Conclusions: .The paper recommends, for case (i), procedures based on angles to represent the PB and N components and, for case (ii), procedures based on series for the CIP X,Y. The two methods are of similar efficiency, and both support equinox based as well as CIO based applications.

An improved harmony search algorithm for emergency inspection scheduling

NASA Astrophysics Data System (ADS)

Kallioras, Nikos A.; Lagaros, Nikos D.; Karlaftis, Matthew G.

2014-11-01

The ability of nature-inspired search algorithms to efficiently handle combinatorial problems, and their successful implementation in many fields of engineering and applied sciences, have led to the development of new, improved algorithms. In this work, an improved harmony search (IHS) algorithm is presented, while a holistic approach for solving the problem of post-disaster infrastructure management is also proposed. The efficiency of IHS is compared with that of the algorithms of particle swarm optimization, differential evolution, basic harmony search and the pure random search procedure, when solving the districting problem that is the first part of post-disaster infrastructure management. The ant colony optimization algorithm is employed for solving the associated routing problem that constitutes the second part. The comparison is based on the quality of the results obtained, the computational demands and the sensitivity on the algorithmic parameters.

Updating QR factorization procedure for solution of linear least squares problem with equality constraints.

PubMed

Zeb, Salman; Yousaf, Muhammad

2017-01-01

In this article, we present a QR updating procedure as a solution approach for linear least squares problem with equality constraints. We reduce the constrained problem to unconstrained linear least squares and partition it into a small subproblem. The QR factorization of the subproblem is calculated and then we apply updating techniques to its upper triangular factor R to obtain its solution. We carry out the error analysis of the proposed algorithm to show that it is backward stable. We also illustrate the implementation and accuracy of the proposed algorithm by providing some numerical experiments with particular emphasis on dense problems.

Iterative procedures for space shuttle main engine performance models

NASA Technical Reports Server (NTRS)

Santi, L. Michael

1989-01-01

Performance models of the Space Shuttle Main Engine (SSME) contain iterative strategies for determining approximate solutions to nonlinear equations reflecting fundamental mass, energy, and pressure balances within engine flow systems. Both univariate and multivariate Newton-Raphson algorithms are employed in the current version of the engine Test Information Program (TIP). Computational efficiency and reliability of these procedures is examined. A modified trust region form of the multivariate Newton-Raphson method is implemented and shown to be superior for off nominal engine performance predictions. A heuristic form of Broyden's Rank One method is also tested and favorable results based on this algorithm are presented.

Constrained Self-adaptive Solutions Procedures for Structure Subject to High Temperature Elastic-plastic Creep Effects

NASA Technical Reports Server (NTRS)

Padovan, J.; Tovichakchaikul, S.

1983-01-01

This paper will develop a new solution strategy which can handle elastic-plastic-creep problems in an inherently stable manner. This is achieved by introducing a new constrained time stepping algorithm which will enable the solution of creep initiated pre/postbuckling behavior where indefinite tangent stiffnesses are encountered. Due to the generality of the scheme, both monotone and cyclic loading histories can be handled. The presentation will give a thorough overview of current solution schemes and their short comings, the development of constrained time stepping algorithms as well as illustrate the results of several numerical experiments which benchmark the new procedure.

An efficient dynamic load balancing algorithm

NASA Astrophysics Data System (ADS)

Lagaros, Nikos D.

2014-01-01

In engineering problems, randomness and uncertainties are inherent. Robust design procedures, formulated in the framework of multi-objective optimization, have been proposed in order to take into account sources of randomness and uncertainty. These design procedures require orders of magnitude more computational effort than conventional analysis or optimum design processes since a very large number of finite element analyses is required to be dealt. It is therefore an imperative need to exploit the capabilities of computing resources in order to deal with this kind of problems. In particular, parallel computing can be implemented at the level of metaheuristic optimization, by exploiting the physical parallelization feature of the nondominated sorting evolution strategies method, as well as at the level of repeated structural analyses required for assessing the behavioural constraints and for calculating the objective functions. In this study an efficient dynamic load balancing algorithm for optimum exploitation of available computing resources is proposed and, without loss of generality, is applied for computing the desired Pareto front. In such problems the computation of the complete Pareto front with feasible designs only, constitutes a very challenging task. The proposed algorithm achieves linear speedup factors and almost 100% speedup factor values with reference to the sequential procedure.

Phase-Based Adaptive Estimation of Magnitude-Squared Coherence Between Turbofan Internal Sensors and Far-Field Microphone Signals

NASA Technical Reports Server (NTRS)

Miles, Jeffrey Hilton

2015-01-01

A cross-power spectrum phase based adaptive technique is discussed which iteratively determines the time delay between two digitized signals that are coherent. The adaptive delay algorithm belongs to a class of algorithms that identifies a minimum of a pattern matching function. The algorithm uses a gradient technique to find the value of the adaptive delay that minimizes a cost function based in part on the slope of a linear function that fits the measured cross power spectrum phase and in part on the standard error of the curve fit. This procedure is applied to data from a Honeywell TECH977 static-engine test. Data was obtained using a combustor probe, two turbine exit probes, and far-field microphones. Signals from this instrumentation are used estimate the post-combustion residence time in the combustor. Comparison with previous studies of the post-combustion residence time validates this approach. In addition, the procedure removes the bias due to misalignment of signals in the calculation of coherence which is a first step in applying array processing methods to the magnitude squared coherence data. The procedure also provides an estimate of the cross-spectrum phase-offset.

An Automated Procedure for Evaluating Song Imitation

PubMed Central

Mandelblat-Cerf, Yael; Fee, Michale S.

2014-01-01

Songbirds have emerged as an excellent model system to understand the neural basis of vocal and motor learning. Like humans, songbirds learn to imitate the vocalizations of their parents or other conspecific “tutors.” Young songbirds learn by comparing their own vocalizations to the memory of their tutor song, slowly improving until over the course of several weeks they can achieve an excellent imitation of the tutor. Because of the slow progression of vocal learning, and the large amounts of singing generated, automated algorithms for quantifying vocal imitation have become increasingly important for studying the mechanisms underlying this process. However, methodologies for quantifying song imitation are complicated by the highly variable songs of either juvenile birds or those that learn poorly because of experimental manipulations. Here we present a method for the evaluation of song imitation that incorporates two innovations: First, an automated procedure for selecting pupil song segments, and, second, a new algorithm, implemented in Matlab, for computing both song acoustic and sequence similarity. We tested our procedure using zebra finch song and determined a set of acoustic features for which the algorithm optimally differentiates between similar and non-similar songs. PMID:24809510

Development of an algorithm to identify fall-related injuries and costs in Medicare data.

PubMed

Kim, Sung-Bou; Zingmond, David S; Keeler, Emmett B; Jennings, Lee A; Wenger, Neil S; Reuben, David B; Ganz, David A

2016-12-01

Identifying fall-related injuries and costs using healthcare claims data is cost-effective and easier to implement than using medical records or patient self-report to track falls. We developed a comprehensive four-step algorithm for identifying episodes of care for fall-related injuries and associated costs, using fee-for-service Medicare and Medicare Advantage health plan claims data for 2,011 patients from 5 medical groups between 2005 and 2009. First, as a preparatory step, we identified care received in acute inpatient and skilled nursing facility settings, in addition to emergency department visits. Second, based on diagnosis and procedure codes, we identified all fall-related claim records. Third, with these records, we identified six types of encounters for fall-related injuries, with different levels of injury and care. In the final step, we used these encounters to identify episodes of care for fall-related injuries. To illustrate the algorithm, we present a representative example of a fall episode and examine descriptive statistics of injuries and costs for such episodes. Altogether, we found that the results support the use of our algorithm for identifying episodes of care for fall-related injuries. When we decomposed an episode, we found that the details present a realistic and coherent story of fall-related injuries and healthcare services. Variation of episode characteristics across medical groups supported the use of a complex algorithm approach, and descriptive statistics on the proportion, duration, and cost of episodes by healthcare services and injuries verified that our results are consistent with other studies. This algorithm can be used to identify and analyze various types of fall-related outcomes including episodes of care, injuries, and associated costs. Furthermore, the algorithm can be applied and adopted in other fall-related studies with relative ease.

A general tool for the evaluation of spiral CT interpolation algorithms: revisiting the effect of pitch in multislice CT.

PubMed

Bricault, Ivan; Ferretti, Gilbert

2005-01-01

While multislice spiral computed tomography (CT) scanners are provided by all major manufacturers, their specific interpolation algorithms have been rarely evaluated. Because the results published so far relate to distinct particular cases and differ significantly, there are contradictory recommendations about the choice of pitch in clinical practice. In this paper, we present a new tool for the evaluation of multislice spiral CT z-interpolation algorithms, and apply it to the four-slice case. Our software is based on the computation of a "Weighted Radiation Profile" (WRP), and compares WRP to an expected ideal profile in terms of widening and heterogeneity. It provides a unique scheme for analyzing a large variety of spiral CT acquisition procedures. Freely chosen parameters include: number of detector rows, detector collimation, nominal slice width, helical pitch, and interpolation algorithm with any filter shape and width. Moreover, it is possible to study any longitudinal and off-isocenter positions. Theoretical and experimental results show that WRP, more than Slice Sensitivity Profile (SSP), provides a comprehensive characterization of interpolation algorithms. WRP analysis demonstrates that commonly "preferred helical pitches" are actually nonoptimal regarding the formerly distinguished z-sampling gap reduction criterion. It is also shown that "narrow filter" interpolation algorithms do not enable a general preferred pitch discussion, since they present poor properties with large longitudinal and off-center variations. In the more stable case of "wide filter" interpolation algorithms, SSP width or WRP widening are shown to be almost constant. Therefore, optimal properties should no longer be sought in terms of these criteria. On the contrary, WRP heterogeneity is related to variable artifact phenomena and can pertinently characterize optimal pitches. In particular, the exemplary interpolation properties of pitch = 1 "wide filter" mode are demonstrated.

A projection method for low speed flows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Colella, P.; Pao, K.

The authors propose a decomposition applicable to low speed, inviscid flows of all Mach numbers less than 1. By using the Hodge decomposition, they may write the velocity field as the sum of a divergence-free vector field and a gradient of a scalar function. Evolution equations for these parts are presented. A numerical procedure based on this decomposition is designed, using projection methods for solving the incompressible variables and a backward-Euler method for solving the potential variables. Numerical experiments are included to illustrate various aspects of the algorithm.

Technology Focus: Enhancing Conceptual Knowledge of Linear Programming with a Flash Tool

ERIC Educational Resources Information Center

Garofalo, Joe; Cory, Beth

2007-01-01

Mathematical knowledge can be categorized in different ways. One commonly used way is to distinguish between procedural mathematical knowledge and conceptual mathematical knowledge. Procedural knowledge of mathematics refers to formal language, symbols, algorithms, and rules. Conceptual knowledge is essential for meaningful understanding of…

A computational procedure for large rotational motions in multibody dynamics

NASA Technical Reports Server (NTRS)

Park, K. C.; Chiou, J. C.

1987-01-01

A computational procedure suitable for the solution of equations of motion for multibody systems is presented. The present procedure adopts a differential partitioning of the translational motions and the rotational motions. The translational equations of motion are then treated by either a conventional explicit or an implicit direct integration method. A principle feature of this procedure is a nonlinearly implicit algorithm for updating rotations via the Euler four-parameter representation. This procedure is applied to the rolling of a sphere through a specific trajectory, which shows that it yields robust solutions.

Optimal routing of hazardous substances in time-varying, stochastic transportation networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woods, A.L.; Miller-Hooks, E.; Mahmassani, H.S.

This report is concerned with the selection of routes in a network along which to transport hazardous substances, taking into consideration several key factors pertaining to the cost of transport and the risk of population exposure in the event of an accident. Furthermore, the fact that travel time and the risk measures are not constant over time is explicitly recognized in the routing decisions. Existing approaches typically assume static conditions, possibly resulting in inefficient route selection and unnecessary risk exposure. The report described the application of recent advances in network analysis methodologies to the problem of routing hazardous substances. Severalmore » specific problem formulations are presented, reflecting different degrees of risk aversion on the part of the decision-maker, as well as different possible operational scenarios. All procedures explicitly consider travel times and travel costs (including risk measures) to be stochastic time-varying quantities. The procedures include both exact algorithms, which may require extensive computational effort in some situations, as well as more efficient heuristics that may not guarantee a Pareto-optimal solution. All procedures are systematically illustrated for an example application using the Texas highway network, for both normal and incident condition scenarios. The application illustrates the trade-offs between the information obtained in the solution and computational efficiency, and highlights the benefits of incorporating these procedures in a decision-support system for hazardous substance shipment routing decisions.« less

Automatic vehicle counting system for traffic monitoring

NASA Astrophysics Data System (ADS)

Crouzil, Alain; Khoudour, Louahdi; Valiere, Paul; Truong Cong, Dung Nghy

2016-09-01

The article is dedicated to the presentation of a vision-based system for road vehicle counting and classification. The system is able to achieve counting with a very good accuracy even in difficult scenarios linked to occlusions and/or presence of shadows. The principle of the system is to use already installed cameras in road networks without any additional calibration procedure. We propose a robust segmentation algorithm that detects foreground pixels corresponding to moving vehicles. First, the approach models each pixel of the background with an adaptive Gaussian distribution. This model is coupled with a motion detection procedure, which allows correctly location of moving vehicles in space and time. The nature of trials carried out, including peak periods and various vehicle types, leads to an increase of occlusions between cars and between cars and trucks. A specific method for severe occlusion detection, based on the notion of solidity, has been carried out and tested. Furthermore, the method developed in this work is capable of managing shadows with high resolution. The related algorithm has been tested and compared to a classical method. Experimental results based on four large datasets show that our method can count and classify vehicles in real time with a high level of performance (>98%) under different environmental situations, thus performing better than the conventional inductive loop detectors.

Trajectory prediction for ballistic missiles based on boost-phase LOS measurements

NASA Astrophysics Data System (ADS)

Yeddanapudi, Murali; Bar-Shalom, Yaakov

1997-10-01

This paper addresses the problem of the estimation of the trajectory of a tactical ballistic missile using line of sight (LOS) measurements from one or more passive sensors (typically satellites). The major difficulties of this problem include: the estimation of the unknown time of launch, incorporation of (inaccurate) target thrust profiles to model the target dynamics during the boost phase and an overall ill-conditioning of the estimation problem due to poor observability of the target motion via the LOS measurements. We present a robust estimation procedure based on the Levenberg-Marquardt algorithm that provides both the target state estimate and error covariance taking into consideration the complications mentioned above. An important consideration in the defense against tactical ballistic missiles is the determination of the target position and error covariance at the acquisition range of a surveillance radar in the vicinity of the impact point. We present a systematic procedure to propagate the target state and covariance to a nominal time, when it is within the detection range of a surveillance radar to obtain a cueing volume. Mont Carlo simulation studies on typical single and two sensor scenarios indicate that the proposed algorithms are accurate in terms of the estimates and the estimator calculated covariances are consistent with the errors.

An activity recognition model using inertial sensor nodes in a wireless sensor network for frozen shoulder rehabilitation exercises.

PubMed

Lin, Hsueh-Chun; Chiang, Shu-Yin; Lee, Kai; Kan, Yao-Chiang

2015-01-19

This paper proposes a model for recognizing motions performed during rehabilitation exercises for frozen shoulder conditions. The model consists of wearable wireless sensor network (WSN) inertial sensor nodes, which were developed for this study, and enables the ubiquitous measurement of bodily motions. The model employs the back propagation neural network (BPNN) algorithm to compute motion data that are formed in the WSN packets; herein, six types of rehabilitation exercises were recognized. The packets sent by each node are converted into six components of acceleration and angular velocity according to three axes. Motor features such as basic acceleration, angular velocity, and derivative tilt angle were input into the training procedure of the BPNN algorithm. In measurements of thirteen volunteers, the accelerations and included angles of nodes were adopted from possible features to demonstrate the procedure. Five exercises involving simple swinging and stretching movements were recognized with an accuracy of 85%-95%; however, the accuracy with which exercises entailing spiral rotations were recognized approximately 60%. Thus, a characteristic space and enveloped spectrum improving derivative features were suggested to enable identifying customized parameters. Finally, a real-time monitoring interface was developed for practical implementation. The proposed model can be applied in ubiquitous healthcare self-management to recognize rehabilitation exercises.

A systematic review of validated methods to capture stillbirth and spontaneous abortion using administrative or claims data.

PubMed

Likis, Frances E; Sathe, Nila A; Carnahan, Ryan; McPheeters, Melissa L

2013-12-30

To identify and assess diagnosis, procedure and pharmacy dispensing codes used to identify stillbirths and spontaneous abortion in administrative and claims databases from the United States or Canada. We searched the MEDLINE database from 1991 to September 2012 using controlled vocabulary and key terms related to stillbirth or spontaneous abortion. We also searched the reference lists of included studies. Two investigators independently assessed the full text of studies against pre-determined inclusion criteria. Two reviewers independently extracted data regarding participant and algorithm characteristics and assessed each study's methodological rigor using a pre-defined approach. Ten publications addressing stillbirth and four addressing spontaneous abortion met our inclusion criteria. The International Classification of Diseases, Ninth Revision (ICD-9) codes most commonly used in algorithms for stillbirth were those for intrauterine death (656.4) and stillborn outcomes of delivery (V27.1, V27.3-V27.4, and V27.6-V27.7). Papers identifying spontaneous abortion used codes for missed abortion and spontaneous abortion: 632, 634.x, as well as V27.0-V27.7. Only two studies identifying stillbirth reported validation of algorithms. The overall positive predictive value of the algorithms was high (99%-100%), and one study reported an algorithm with 86% sensitivity. However, the predictive value of individual codes was not assessed and study populations were limited to specific geographic areas. Additional validation studies with a nationally representative sample are needed to confirm the optimal algorithm to identify stillbirths or spontaneous abortion in administrative and claims databases.' Copyright © 2013 Elsevier Ltd. All rights reserved.

Detection and Tracking of Dynamic Objects by Using a Multirobot System: Application to Critical Infrastructures Surveillance

PubMed Central

Rodríguez-Canosa, Gonzalo; Giner, Jaime del Cerro; Barrientos, Antonio

2014-01-01

The detection and tracking of mobile objects (DATMO) is progressively gaining importance for security and surveillance applications. This article proposes a set of new algorithms and procedures for detecting and tracking mobile objects by robots that work collaboratively as part of a multirobot system. These surveillance algorithms are conceived of to work with data provided by long distance range sensors and are intended for highly reliable object detection in wide outdoor environments. Contrary to most common approaches, in which detection and tracking are done by an integrated procedure, the approach proposed here relies on a modular structure, in which detection and tracking are carried out independently, and the latter might accept input data from different detection algorithms. Two movement detection algorithms have been developed for the detection of dynamic objects by using both static and/or mobile robots. The solution to the overall problem is based on the use of a Kalman filter to predict the next state of each tracked object. Additionally, new tracking algorithms capable of combining dynamic objects lists coming from either one or various sources complete the solution. The complementary performance of the separated modular structure for detection and identification is evaluated and, finally, a selection of test examples discussed. PMID:24526305

Phase extraction based on iterative algorithm using five-frame crossed fringes in phase measuring deflectometry

NASA Astrophysics Data System (ADS)

Jin, Chengying; Li, Dahai; Kewei, E.; Li, Mengyang; Chen, Pengyu; Wang, Ruiyang; Xiong, Zhao

2018-06-01

In phase measuring deflectometry, two orthogonal sinusoidal fringe patterns are separately projected on the test surface and the distorted fringes reflected by the surface are recorded, each with a sequential phase shift. Then the two components of the local surface gradients are obtained by triangulation. It usually involves some complicated and time-consuming procedures (fringe projection in the orthogonal directions). In addition, the digital light devices (e.g. LCD screen and CCD camera) are not error free. There are quantization errors for each pixel of both LCD and CCD. Therefore, to avoid the complex process and improve the reliability of the phase distribution, a phase extraction algorithm with five-frame crossed fringes is presented in this paper. It is based on a least-squares iterative process. Using the proposed algorithm, phase distributions and phase shift amounts in two orthogonal directions can be simultaneously and successfully determined through an iterative procedure. Both a numerical simulation and a preliminary experiment are conducted to verify the validity and performance of this algorithm. Experimental results obtained by our method are shown, and comparisons between our experimental results and those obtained by the traditional 16-step phase-shifting algorithm and between our experimental results and those measured by the Fizeau interferometer are made.

A globally convergent LCL method for nonlinear optimization.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Friedlander, M. P.; Saunders, M. A.; Mathematics and Computer Science

2005-01-01

For optimization problems with nonlinear constraints, linearly constrained Lagrangian (LCL) methods solve a sequence of subproblems of the form 'minimize an augmented Lagrangian function subject to linearized constraints.' Such methods converge rapidly near a solution but may not be reliable from arbitrary starting points. Nevertheless, the well-known software package MINOS has proved effective on many large problems. Its success motivates us to derive a related LCL algorithm that possesses three important properties: it is globally convergent, the subproblem constraints are always feasible, and the subproblems may be solved inexactly. The new algorithm has been implemented in Matlab, with an optionmore » to use either MINOS or SNOPT (Fortran codes) to solve the linearly constrained subproblems. Only first derivatives are required. We present numerical results on a subset of the COPS, HS, and CUTE test problems, which include many large examples. The results demonstrate the robustness and efficiency of the stabilized LCL procedure.« less

A programmable and portable NMES device for drop foot correction and blood flow assist applications.

PubMed

Breen, Paul P; Corley, Gavin J; O'Keeffe, Derek T; Conway, Richard; Olaighin, Gearóid

2009-04-01

The Duo-STIM, a new, programmable and portable neuromuscular stimulation system for drop foot correction and blood flow assist applications is presented. The system consists of a programmer unit and a portable, programmable stimulator unit. The portable stimulator features fully programmable, sensor-controlled, constant-voltage, dual-channel stimulation and accommodates a range of customized stimulation profiles. Trapezoidal and free-form adaptive stimulation intensity envelope algorithms are provided for drop foot correction applications, while time dependent and activity dependent algorithms are provided for blood flow assist applications. A variety of sensor types can be used with the portable unit, including force sensitive resistor-based foot switches and MEMS-based accelerometer and gyroscope devices. The paper provides a detailed description of the hardware and block-level system design for both units. The programming and operating procedures for the system are also presented. Finally, functional bench test results for the system are presented.

A programmable and portable NMES device for drop foot correction and blood flow assist applications.

PubMed

Breen, Paul P; Corley, Gavin J; O'Keeffe, Derek T; Conway, Richard; OLaighin, Gearoid

2007-01-01

The Duo-STIM, a new, programmable and portable neuromuscular stimulation system for drop foot correction and blood flow assist applications is presented. The system consists of a programmer unit and a portable, programmable stimulator unit. The portable stimulator features fully programmable, sensor-controlled, constant-voltage, dual-channel stimulation and accommodates a range of customized stimulation profiles. Trapezoidal and free-form adaptive stimulation intensity envelope algorithms are provided for drop foot correction applications, while time dependent and activity dependent algorithms are provided for blood flow assist applications. A variety of sensor types can be used with the portable unit, including force sensitive resistor based foot switches and NMES based accelerometer and gyroscope devices. The paper provides a detailed description of the hardware and block-level system design for both units. The programming and operating procedures for the system are also presented. Finally, functional bench test results for the system are presented.