New recursive-least-squares algorithms for nonlinear active control of sound and vibration using neural networks.

PubMed

Bouchard, M

2001-01-01

In recent years, a few articles describing the use of neural networks for nonlinear active control of sound and vibration were published. Using a control structure with two multilayer feedforward neural networks (one as a nonlinear controller and one as a nonlinear plant model), steepest descent algorithms based on two distinct gradient approaches were introduced for the training of the controller network. The two gradient approaches were sometimes called the filtered-x approach and the adjoint approach. Some recursive-least-squares algorithms were also introduced, using the adjoint approach. In this paper, an heuristic procedure is introduced for the development of recursive-least-squares algorithms based on the filtered-x and the adjoint gradient approaches. This leads to the development of new recursive-least-squares algorithms for the training of the controller neural network in the two networks structure. These new algorithms produce a better convergence performance than previously published algorithms. Differences in the performance of algorithms using the filtered-x and the adjoint gradient approaches are discussed in the paper. The computational load of the algorithms discussed in the paper is evaluated for multichannel systems of nonlinear active control. Simulation results are presented to compare the convergence performance of the algorithms, showing the convergence gain provided by the new algorithms.

An improved affine projection algorithm for active noise cancellation

NASA Astrophysics Data System (ADS)

Zhang, Congyan; Wang, Mingjiang; Han, Yufei; Sun, Yunzhuo

2017-08-01

Affine projection algorithm is a signal reuse algorithm, and it has a good convergence rate compared to other traditional adaptive filtering algorithm. There are two factors that affect the performance of the algorithm, which are step factor and the projection length. In the paper, we propose a new variable step size affine projection algorithm (VSS-APA). It dynamically changes the step size according to certain rules, so that it can get smaller steady-state error and faster convergence speed. Simulation results can prove that its performance is superior to the traditional affine projection algorithm and in the active noise control (ANC) applications, the new algorithm can get very good results.

Computational Fluid Dynamics. [numerical methods and algorithm development

NASA Technical Reports Server (NTRS)

1992-01-01

This collection of papers was presented at the Computational Fluid Dynamics (CFD) Conference held at Ames Research Center in California on March 12 through 14, 1991. It is an overview of CFD activities at NASA Lewis Research Center. The main thrust of computational work at Lewis is aimed at propulsion systems. Specific issues related to propulsion CFD and associated modeling will also be presented. Examples of results obtained with the most recent algorithm development will also be presented.

Image processing meta-algorithm development via genetic manipulation of existing algorithm graphs

NASA Astrophysics Data System (ADS)

Schalkoff, Robert J.; Shaaban, Khaled M.

1999-07-01

Automatic algorithm generation for image processing applications is not a new idea, however previous work is either restricted to morphological operates or impractical. In this paper, we show recent research result in the development and use of meta-algorithms, i.e. algorithms which lead to new algorithms. Although the concept is generally applicable, the application domain in this work is restricted to image processing. The meta-algorithm concept described in this paper is based upon out work in dynamic algorithm. The paper first present the concept of dynamic algorithms which, on the basis of training and archived algorithmic experience embedded in an algorithm graph (AG), dynamically adjust the sequence of operations applied to the input image data. Each node in the tree-based representation of a dynamic algorithm with out degree greater than 2 is a decision node. At these nodes, the algorithm examines the input data and determines which path will most likely achieve the desired results. This is currently done using nearest-neighbor classification. The details of this implementation are shown. The constrained perturbation of existing algorithm graphs, coupled with a suitable search strategy, is one mechanism to achieve meta-algorithm an doffers rich potential for the discovery of new algorithms. In our work, a meta-algorithm autonomously generates new dynamic algorithm graphs via genetic recombination of existing algorithm graphs. The AG representation is well suited to this genetic-like perturbation, using a commonly- employed technique in artificial neural network synthesis, namely the blueprint representation of graphs. A number of exam. One of the principal limitations of our current approach is the need for significant human input in the learning phase. Efforts to overcome this limitation are discussed. Future research directions are indicated.

An ATR architecture for algorithm development and testing

NASA Astrophysics Data System (ADS)

Breivik, Gøril M.; Løkken, Kristin H.; Brattli, Alvin; Palm, Hans C.; Haavardsholm, Trym

2013-05-01

A research platform with four cameras in the infrared and visible spectral domains is under development at the Norwegian Defence Research Establishment (FFI). The platform will be mounted on a high-speed jet aircraft and will primarily be used for image acquisition and for development and test of automatic target recognition (ATR) algorithms. The sensors on board produce large amounts of data, the algorithms can be computationally intensive and the data processing is complex. This puts great demands on the system architecture; it has to run in real-time and at the same time be suitable for algorithm development. In this paper we present an architecture for ATR systems that is designed to be exible, generic and efficient. The architecture is module based so that certain parts, e.g. specific ATR algorithms, can be exchanged without affecting the rest of the system. The modules are generic and can be used in various ATR system configurations. A software framework in C++ that handles large data ows in non-linear pipelines is used for implementation. The framework exploits several levels of parallelism and lets the hardware processing capacity be fully utilised. The ATR system is under development and has reached a first level that can be used for segmentation algorithm development and testing. The implemented system consists of several modules, and although their content is still limited, the segmentation module includes two different segmentation algorithms that can be easily exchanged. We demonstrate the system by applying the two segmentation algorithms to infrared images from sea trial recordings.

Performance Evaluation of Multichannel Adaptive Algorithms for Local Active Noise Control

NASA Astrophysics Data System (ADS)

DE DIEGO, M.; GONZALEZ, A.

2001-07-01

This paper deals with the development of a multichannel active noise control (ANC) system inside an enclosed space. The purpose is to design a real practical system which works well in local ANC applications. Moreover, the algorithm implemented in the adaptive controller should be robust, of low computational complexity and it should manage to generate a uniform useful-size zone of quite in order to allow the head motion of a person seated on a seat inside a car. Experiments were carried out under semi-anechoic and listening room conditions to verify the successful implementation of the multichannel system. The developed prototype consists of an array of up to four microphones used as error sensors mounted on the headrest of a seat place inside the enclosure. One loudspeaker was used as single primary source and two secondary sources were placed facing the seat. The aim of this multichannel system is to reduce the sound pressure levels in an area around the error sensors, following a local control strategy. When using this technique, the cancellation points are not only the error sensor positions but an area around them, which is measured by using a monitoring microphone. Different multichannel adaptive algorithms for ANC have been analyzed and their performance verified. Multiple error algorithms are used in order to cancel out different types of primary noise (engine noise and random noise) with several configurations (up to four channels system). As an alternative to the multiple error LMS algorithm (multichannel version of the filtered-X LMS algorithm, MELMS), the least maximum mean squares (LMMS) and the scanning error-LMS algorithm have been developed in this work in order to reduce computational complexity and achieve a more uniform residual field. The ANC algorithms were programmed on a digital signal processing board equipped with a TMS320C40 floating point DSP processor. Measurements concerning real-time experiments on local noise reduction in two

Passive microwave algorithm development and evaluation

NASA Technical Reports Server (NTRS)

Petty, Grant W.

1995-01-01

The scientific objectives of this grant are: (1) thoroughly evaluate, both theoretically and empirically, all available Special Sensor Microwave Imager (SSM/I) retrieval algorithms for column water vapor, column liquid water, and surface wind speed; (2) where both appropriate and feasible, develop, validate, and document satellite passive microwave retrieval algorithms that offer significantly improved performance compared with currently available algorithms; and (3) refine and validate a novel physical inversion scheme for retrieving rain rate over the ocean. This report summarizes work accomplished or in progress during the first year of a three year grant. The emphasis during the first year has been on the validation and refinement of the rain rate algorithm published by Petty and on the analysis of independent data sets that can be used to help evaluate the performance of rain rate algorithms over remote areas of the ocean. Two articles in the area of global oceanic precipitation are attached.

Landscape Analysis and Algorithm Development for Plateau Plagued Search Spaces

DTIC Science & Technology

2011-02-28

Final Report for AFOSR #FA9550-08-1-0422 Landscape Analysis and Algorithm Development for Plateau Plagued Search Spaces August 1, 2008 to November 30...focused on developing high level general purpose algorithms , such as Tabu Search and Genetic Algorithms . However, understanding of when and why these... algorithms perform well still lags. Our project extended the theory of certain combi- natorial optimization problems to develop analytical

Development of Quadratic Programming Algorithm Based on Interior Point Method with Estimation Mechanism of Active Constraints

NASA Astrophysics Data System (ADS)

Hashimoto, Hiroyuki; Takaguchi, Yusuke; Nakamura, Shizuka

Instability of calculation process and increase of calculation time caused by increasing size of continuous optimization problem remain the major issues to be solved to apply the technique to practical industrial systems. This paper proposes an enhanced quadratic programming algorithm based on interior point method mainly for improvement of calculation stability. The proposed method has dynamic estimation mechanism of active constraints on variables, which fixes the variables getting closer to the upper/lower limit on them and afterwards releases the fixed ones as needed during the optimization process. It is considered as algorithm-level integration of the solution strategy of active-set method into the interior point method framework. We describe some numerical results on commonly-used bench-mark problems called “CUTEr” to show the effectiveness of the proposed method. Furthermore, the test results on large-sized ELD problem (Economic Load Dispatching problems in electric power supply scheduling) are also described as a practical industrial application.

Experimental evaluation of leaky least-mean-square algorithms for active noise reduction in communication headsets.

PubMed

Cartes, David A; Ray, Laura R; Collier, Robert D

2002-04-01

An adaptive leaky normalized least-mean-square (NLMS) algorithm has been developed to optimize stability and performance of active noise cancellation systems. The research addresses LMS filter performance issues related to insufficient excitation, nonstationary noise fields, and time-varying signal-to-noise ratio. The adaptive leaky NLMS algorithm is based on a Lyapunov tuning approach in which three candidate algorithms, each of which is a function of the instantaneous measured reference input, measurement noise variance, and filter length, are shown to provide varying degrees of tradeoff between stability and noise reduction performance. Each algorithm is evaluated experimentally for reduction of low frequency noise in communication headsets, and stability and noise reduction performance are compared with that of traditional NLMS and fixed-leakage NLMS algorithms. Acoustic measurements are made in a specially designed acoustic test cell which is based on the original work of Ryan et al. ["Enclosure for low frequency assessment of active noise reducing circumaural headsets and hearing protection," Can. Acoust. 21, 19-20 (1993)] and which provides a highly controlled and uniform acoustic environment. The stability and performance of the active noise reduction system, including a prototype communication headset, are investigated for a variety of noise sources ranging from stationary tonal noise to highly nonstationary measured F-16 aircraft noise over a 20 dB dynamic range. Results demonstrate significant improvements in stability of Lyapunov-tuned LMS algorithms over traditional leaky or nonleaky normalized algorithms, while providing noise reduction performance equivalent to that of the NLMS algorithm for idealized noise fields.

Development of Educational Support System for Algorithm using Flowchart

NASA Astrophysics Data System (ADS)

Ohchi, Masashi; Aoki, Noriyuki; Furukawa, Tatsuya; Takayama, Kanta

Recently, an information technology is indispensable for the business and industrial developments. However, it has been a social problem that the number of software developers has been insufficient. To solve the problem, it is necessary to develop and implement the environment for learning the algorithm and programming language. In the paper, we will describe the algorithm study support system for a programmer using the flowchart. Since the proposed system uses Graphical User Interface(GUI), it will become easy for a programmer to understand the algorithm in programs.

Evidence-based algorithm for heparin dosing before cardiopulmonary bypass. Part 1: Development of the algorithm.

PubMed

McKinney, Mark C; Riley, Jeffrey B

2007-12-01

The incidence of heparin resistance during adult cardiac surgery with cardiopulmonary bypass has been reported at 15%-20%. The consistent use of a clinical decision-making algorithm may increase the consistency of patient care and likely reduce the total required heparin dose and other problems associated with heparin dosing. After a directed survey of practicing perfusionists regarding treatment of heparin resistance and a literature search for high-level evidence regarding the diagnosis and treatment of heparin resistance, an evidence-based decision-making algorithm was constructed. The face validity of the algorithm decisive steps and logic was confirmed by a second survey of practicing perfusionists. The algorithm begins with review of the patient history to identify predictors for heparin resistance. The definition for heparin resistance contained in the algorithm is an activated clotting time < 450 seconds with > 450 IU/kg heparin loading dose. Based on the literature, the treatment for heparin resistance used in the algorithm is anti-thrombin III supplement. The algorithm seems to be valid and is supported by high-level evidence and clinician opinion. The next step is a human randomized clinical trial to test the clinical procedure guideline algorithm vs. current standard clinical practice.

Feasibility of the MUSIC Algorithm for the Active Protection System

DTIC Science & Technology

2001-03-01

Feasibility of the MUSIC Algorithm for the Active Protection System ARL-MR-501 March 2001 Canh Ly Approved for public release; distribution... MUSIC Algorithm for the Active Protection System Canh Ly Sensors and Electron Devices Directorate Approved for public release; distribution unlimited...This report compares the accuracy of the doppler frequency of an incoming projectile with the use of the MUSIC (multiple signal classification

Development, Comparisons and Evaluation of Aerosol Retrieval Algorithms

NASA Astrophysics Data System (ADS)

de Leeuw, G.; Holzer-Popp, T.; Aerosol-cci Team

2011-12-01

The Climate Change Initiative (cci) of the European Space Agency (ESA) has brought together a team of European Aerosol retrieval groups working on the development and improvement of aerosol retrieval algorithms. The goal of this cooperation is the development of methods to provide the best possible information on climate and climate change based on satellite observations. To achieve this, algorithms are characterized in detail as regards the retrieval approaches, the aerosol models used in each algorithm, cloud detection and surface treatment. A round-robin intercomparison of results from the various participating algorithms serves to identify the best modules or combinations of modules for each sensor. Annual global datasets including their uncertainties will then be produced and validated. The project builds on 9 existing algorithms to produce spectral aerosol optical depth (AOD and Ångström exponent) as well as other aerosol information; two instruments are included to provide the absorbing aerosol index (AAI) and stratospheric aerosol information. The algorithms included are: - 3 for ATSR (ORAC developed by RAL / Oxford university, ADV developed by FMI and the SU algorithm developed by Swansea University ) - 2 for MERIS (BAER by Bremen university and the ESA standard handled by HYGEOS) - 1 for POLDER over ocean (LOA) - 1 for synergetic retrieval (SYNAER by DLR ) - 1 for OMI retreival of the absorbing aerosol index with averaging kernel information (KNMI) - 1 for GOMOS stratospheric extinction profile retrieval (BIRA) The first seven algorithms aim at the retrieval of the AOD. However, each of the algorithms used differ in their approach, even for algorithms working with the same instrument such as ATSR or MERIS. To analyse the strengths and weaknesses of each algorithm several tests are made. The starting point for comparison and measurement of improvements is a retrieval run for 1 month, September 2008. The data from the same month are subsequently used for

Active control of flexible structures using a fuzzy logic algorithm

NASA Astrophysics Data System (ADS)

Cohen, Kelly; Weller, Tanchum; Ben-Asher, Joseph Z.

2002-08-01

This study deals with the development and application of an active control law for the vibration suppression of beam-like flexible structures experiencing transient disturbances. Collocated pairs of sensors/actuators provide active control of the structure. A design methodology for the closed-loop control algorithm based on fuzzy logic is proposed. First, the behavior of the open-loop system is observed. Then, the number and locations of collocated actuator/sensor pairs are selected. The proposed control law, which is based on the principles of passivity, commands the actuator to emulate the behavior of a dynamic vibration absorber. The absorber is tuned to a targeted frequency, whereas the damping coefficient of the dashpot is varied in a closed loop using a fuzzy logic based algorithm. This approach not only ensures inherent stability associated with passive absorbers, but also circumvents the phenomenon of modal spillover. The developed controller is applied to the AFWAL/FIB 10 bar truss. Simulated results using MATLAB© show that the closed-loop system exhibits fairly quick settling times and desirable performance, as well as robustness characteristics. To demonstrate the robustness of the control system to changes in the temporal dynamics of the flexible structure, the transient response to a considerably perturbed plant is simulated. The modal frequencies of the 10 bar truss were raised as well as lowered substantially, thereby significantly perturbing the natural frequencies of vibration. For these cases, too, the developed control law provides adequate settling times and rates of vibrational energy dissipation.

Developing an Enhanced Lightning Jump Algorithm for Operational Use

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Petersen, Walter A.; Carey, Lawrence D.

2009-01-01

Overall Goals: 1. Build on the lightning jump framework set through previous studies. 2. Understand what typically occurs in nonsevere convection with respect to increases in lightning. 3. Ultimately develop a lightning jump algorithm for use on the Geostationary Lightning Mapper (GLM). 4 Lightning jump algorithm configurations were developed (2(sigma), 3(sigma), Threshold 10 and Threshold 8). 5 algorithms were tested on a population of 47 nonsevere and 38 severe thunderstorms. Results indicate that the 2(sigma) algorithm performed best over the entire thunderstorm sample set with a POD of 87%, a far of 35%, a CSI of 59% and a HSS of 75%.

Development of activity pencil beam algorithm using measured distribution data of positron emitter nuclei generated by proton irradiation of targets containing (12)C, (16)O, and (40)Ca nuclei in preparation of clinical application.

PubMed

Miyatake, Aya; Nishio, Teiji; Ogino, Takashi

2011-10-01

The purpose of this study is to develop a new calculation algorithm that is satisfactory in terms of the requirements for both accuracy and calculation time for a simulation of imaging of the proton-irradiated volume in a patient body in clinical proton therapy. The activity pencil beam algorithm (APB algorithm), which is a new technique to apply the pencil beam algorithm generally used for proton dose calculations in proton therapy to the calculation of activity distributions, was developed as a calculation algorithm of the activity distributions formed by positron emitter nuclei generated from target nuclear fragment reactions. In the APB algorithm, activity distributions are calculated using an activity pencil beam kernel. In addition, the activity pencil beam kernel is constructed using measured activity distributions in the depth direction and calculations in the lateral direction. (12)C, (16)O, and (40)Ca nuclei were determined as the major target nuclei that constitute a human body that are of relevance for calculation of activity distributions. In this study, "virtual positron emitter nuclei" was defined as the integral yield of various positron emitter nuclei generated from each target nucleus by target nuclear fragment reactions with irradiated proton beam. Compounds, namely, polyethylene, water (including some gelatin) and calcium oxide, which contain plenty of the target nuclei, were irradiated using a proton beam. In addition, depth activity distributions of virtual positron emitter nuclei generated in each compound from target nuclear fragment reactions were measured using a beam ON-LINE PET system mounted a rotating gantry port (BOLPs-RGp). The measured activity distributions depend on depth or, in other words, energy. The irradiated proton beam energies were 138, 179, and 223 MeV, and measurement time was about 5 h until the measured activity reached the background level. Furthermore, the activity pencil beam data were made using the activity pencil

Development of a Novel Locomotion Algorithm for Snake Robot

NASA Astrophysics Data System (ADS)

Khan, Raisuddin; Masum Billah, Md; Watanabe, Mitsuru; Shafie, A. A.

2013-12-01

A novel algorithm for snake robot locomotion is developed and analyzed in this paper. Serpentine is one of the renowned locomotion for snake robot in disaster recovery mission to overcome narrow space navigation. Several locomotion for snake navigation, such as concertina or rectilinear may be suitable for narrow spaces, but is highly inefficient if the same type of locomotion is used even in open spaces resulting friction reduction which make difficulties for snake movement. A novel locomotion algorithm has been proposed based on the modification of the multi-link snake robot, the modifications include alterations to the snake segments as well elements that mimic scales on the underside of the snake body. Snake robot can be able to navigate in the narrow space using this developed locomotion algorithm. The developed algorithm surmount the others locomotion limitation in narrow space navigation.

Development of a two wheeled self balancing robot with speech recognition and navigation algorithm

NASA Astrophysics Data System (ADS)

Rahman, Md. Muhaimin; Ashik-E-Rasul, Haq, Nowab. Md. Aminul; Hassan, Mehedi; Hasib, Irfan Mohammad Al; Hassan, K. M. Rafidh

2016-07-01

This paper is aimed to discuss modeling, construction and development of navigation algorithm of a two wheeled self balancing mobile robot in an enclosure. In this paper, we have discussed the design of two of the main controller algorithms, namely PID algorithms, on the robot model. Simulation is performed in the SIMULINK environment. The controller is developed primarily for self-balancing of the robot and also it's positioning. As for the navigation in an enclosure, template matching algorithm is proposed for precise measurement of the robot position. The navigation system needs to be calibrated before navigation process starts. Almost all of the earlier template matching algorithms that can be found in the open literature can only trace the robot. But the proposed algorithm here can also locate the position of other objects in an enclosure, like furniture, tables etc. This will enable the robot to know the exact location of every stationary object in the enclosure. Moreover, some additional features, such as Speech Recognition and Object Detection, are added. For Object Detection, the single board Computer Raspberry Pi is used. The system is programmed to analyze images captured via the camera, which are then processed through background subtraction, followed by active noise reduction.

Global Precipitation Measurement: GPM Microwave Imager (GMI) Algorithm Development Approach

NASA Technical Reports Server (NTRS)

Stocker, Erich Franz

2009-01-01

This slide presentation reviews the approach to the development of the Global Precipitation Measurement algorithm. This presentation includes information about the responsibilities for the development of the algorithm, and the calibration. Also included is information about the orbit, and the sun angle. The test of the algorithm code will be done with synthetic data generated from the Precipitation Processing System (PPS).

Teaching and Learning Activity Sequencing System using Distributed Genetic Algorithms

NASA Astrophysics Data System (ADS)

Matsui, Tatsunori; Ishikawa, Tomotake; Okamoto, Toshio

The purpose of this study is development of a supporting system for teacher's design of lesson plan. Especially design of lesson plan which relates to the new subject "Information Study" is supported. In this study, we developed a system which generates teaching and learning activity sequences by interlinking lesson's activities corresponding to the various conditions according to the user's input. Because user's input is multiple information, there will be caused contradiction which the system should solve. This multiobjective optimization problem is resolved by Distributed Genetic Algorithms, in which some fitness functions are defined with reference models on lesson, thinking and teaching style. From results of various experiments, effectivity and validity of the proposed methods and reference models were verified; on the other hand, some future works on reference models and evaluation functions were also pointed out.

Reliability and validity of bilateral ankle accelerometer algorithms for activity recognition and walking speed after stroke.

PubMed

Dobkin, Bruce H; Xu, Xiaoyu; Batalin, Maxim; Thomas, Seth; Kaiser, William

2011-08-01

Outcome measures of mobility for large stroke trials are limited to timed walks for short distances in a laboratory, step counters and ordinal scales of disability and quality of life. Continuous monitoring and outcome measurements of the type and quantity of activity in the community would provide direct data about daily performance, including compliance with exercise and skills practice during routine care and clinical trials. Twelve adults with impaired ambulation from hemiparetic stroke and 6 healthy controls wore triaxial accelerometers on their ankles. Walking speed for repeated outdoor walks was determined by machine-learning algorithms and compared to a stopwatch calculation of speed for distances not known to the algorithm. The reliability of recognizing walking, exercise, and cycling by the algorithms was compared to activity logs. A high correlation was found between stopwatch-measured outdoor walking speed and algorithm-calculated speed (Pearson coefficient, 0.98; P=0.001) and for repeated measures of algorithm-derived walking speed (P=0.01). Bouts of walking >5 steps, variations in walking speed, cycling, stair climbing, and leg exercises were correctly identified during a day in the community. Compared to healthy subjects, those with stroke were, as expected, more sedentary and slower, and their gait revealed high paretic-to-unaffected leg swing ratios. Test-retest reliability and concurrent and construct validity are high for activity pattern-recognition Bayesian algorithms developed from inertial sensors. This ratio scale data can provide real-world monitoring and outcome measurements of lower extremity activities and walking speed for stroke and rehabilitation studies.

The threshold algorithm: Description of the methodology and new developments

NASA Astrophysics Data System (ADS)

Neelamraju, Sridhar; Oligschleger, Christina; Schön, J. Christian

2017-10-01

Understanding the dynamics of complex systems requires the investigation of their energy landscape. In particular, the flow of probability on such landscapes is a central feature in visualizing the time evolution of complex systems. To obtain such flows, and the concomitant stable states of the systems and the generalized barriers among them, the threshold algorithm has been developed. Here, we describe the methodology of this approach starting from the fundamental concepts in complex energy landscapes and present recent new developments, the threshold-minimization algorithm and the molecular dynamics threshold algorithm. For applications of these new algorithms, we draw on landscape studies of three disaccharide molecules: lactose, maltose, and sucrose.

Human activity recognition based on feature selection in smart home using back-propagation algorithm.

PubMed

Fang, Hongqing; He, Lei; Si, Hao; Liu, Peng; Xie, Xiaolei

2014-09-01

In this paper, Back-propagation(BP) algorithm has been used to train the feed forward neural network for human activity recognition in smart home environments, and inter-class distance method for feature selection of observed motion sensor events is discussed and tested. And then, the human activity recognition performances of neural network using BP algorithm have been evaluated and compared with other probabilistic algorithms: Naïve Bayes(NB) classifier and Hidden Markov Model(HMM). The results show that different feature datasets yield different activity recognition accuracy. The selection of unsuitable feature datasets increases the computational complexity and degrades the activity recognition accuracy. Furthermore, neural network using BP algorithm has relatively better human activity recognition performances than NB classifier and HMM. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Novel particle tracking algorithm based on the Random Sample Consensus Model for the Active Target Time Projection Chamber (AT-TPC)

NASA Astrophysics Data System (ADS)

Ayyad, Yassid; Mittig, Wolfgang; Bazin, Daniel; Beceiro-Novo, Saul; Cortesi, Marco

2018-02-01

The three-dimensional reconstruction of particle tracks in a time projection chamber is a challenging task that requires advanced classification and fitting algorithms. In this work, we have developed and implemented a novel algorithm based on the Random Sample Consensus Model (RANSAC). The RANSAC is used to classify tracks including pile-up, to remove uncorrelated noise hits, as well as to reconstruct the vertex of the reaction. The algorithm, developed within the Active Target Time Projection Chamber (AT-TPC) framework, was tested and validated by analyzing the 4He+4He reaction. Results, performance and quality of the proposed algorithm are presented and discussed in detail.

Development of an inverse distance weighted active infrared stealth scheme using the repulsive particle swarm optimization algorithm.

PubMed

Han, Kuk-Il; Kim, Do-Hwi; Choi, Jun-Hyuk; Kim, Tae-Kuk

2018-04-20

Treatments for detection by infrared (IR) signals are higher than for other signals such as radar or sonar because an object detected by the IR sensor cannot easily recognize its detection status. Recently, research for actively reducing IR signal has been conducted to control the IR signal by adjusting the surface temperature of the object. In this paper, we propose an active IR stealth algorithm to synchronize IR signals from the object and the background around the object. The proposed method includes the repulsive particle swarm optimization statistical optimization algorithm to estimate the IR stealth surface temperature, which will result in a synchronization between the IR signals from the object and the surrounding background by setting the inverse distance weighted contrast radiant intensity (CRI) equal to zero. We tested the IR stealth performance in mid wavelength infrared (MWIR) and long wavelength infrared (LWIR) bands for a test plate located at three different positions on a forest scene to verify the proposed method. Our results show that the inverse distance weighted active IR stealth technique proposed in this study is proved to be an effective method for reducing the contrast radiant intensity between the object and background up to 32% as compared to the previous method using the CRI determined as the simple signal difference between the object and the background.

Development of an algorithm for controlling a multilevel three-phase converter

NASA Astrophysics Data System (ADS)

Taissariyeva, Kyrmyzy; Ilipbaeva, Lyazzat

2017-08-01

This work is devoted to the development of an algorithm for controlling transistors in a three-phase multilevel conversion system. The developed algorithm allows to organize a correct operation and describes the state of transistors at each moment of time when constructing a computer model of a three-phase multilevel converter. The developed algorithm of operation of transistors provides in-phase of a three-phase converter and obtaining a sinusoidal voltage curve at the converter output.

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.

Development of a New De Novo Design Algorithm for Exploring Chemical Space.

PubMed

Mishima, Kazuaki; Kaneko, Hiromasa; Funatsu, Kimito

2014-12-01

In the first stage of development of new drugs, various lead compounds with high activity are required. To design such compounds, we focus on chemical space defined by structural descriptors. New compounds close to areas where highly active compounds exist will show the same degree of activity. We have developed a new de novo design system to search a target area in chemical space. First, highly active compounds are manually selected as initial seeds. Then, the seeds are entered into our system, and structures slightly different from the seeds are generated and pooled. Next, seeds are selected from the new structure pool based on the distance from target coordinates on the map. To test the algorithm, we used two datasets of ligand binding affinity and showed that the proposed generator could produce diverse virtual compounds that had high activity in docking simulations. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of an analytical guidance algorithm for lunar descent

NASA Astrophysics Data System (ADS)

Chomel, Christina Tvrdik

In recent years, NASA has indicated a desire to return humans to the moon. With NASA planning manned missions within the next couple of decades, the concept development for these lunar vehicles has begun. The guidance, navigation, and control (GN&C) computer programs that will perform the function of safely landing a spacecraft on the moon are part of that development. The lunar descent guidance algorithm takes the horizontally oriented spacecraft from orbital speeds hundreds of kilometers from the desired landing point to the landing point at an almost vertical orientation and very low speed. Existing lunar descent GN&C algorithms date back to the Apollo era with little work available for implementation since then. Though these algorithms met the criteria of the 1960's, they are cumbersome today. At the basis of the lunar descent phase are two elements: the targeting, which generates a reference trajectory, and the real-time guidance, which forces the spacecraft to fly that trajectory. The Apollo algorithm utilizes a complex, iterative, numerical optimization scheme for developing the reference trajectory. The real-time guidance utilizes this reference trajectory in the form of a quartic rather than a more general format to force the real-time trajectory errors to converge to zero; however, there exist no guarantees under any conditions for this convergence. The proposed algorithm implements a purely analytical targeting algorithm used to generate two-dimensional trajectories "on-the-fly"' or to retarget the spacecraft to another landing site altogether. It is based on the analytical solutions to the equations for speed, downrange, and altitude as a function of flight path angle and assumes two constant thrust acceleration curves. The proposed real-time guidance algorithm has at its basis the three-dimensional non-linear equations of motion and a control law that is proven to converge under certain conditions through Lyapunov analysis to a reference trajectory

Development and application of unified algorithms for problems in computational science

NASA Technical Reports Server (NTRS)

Shankar, Vijaya; Chakravarthy, Sukumar

1987-01-01

A framework is presented for developing computationally unified numerical algorithms for solving nonlinear equations that arise in modeling various problems in mathematical physics. The concept of computational unification is an attempt to encompass efficient solution procedures for computing various nonlinear phenomena that may occur in a given problem. For example, in Computational Fluid Dynamics (CFD), a unified algorithm will be one that allows for solutions to subsonic (elliptic), transonic (mixed elliptic-hyperbolic), and supersonic (hyperbolic) flows for both steady and unsteady problems. The objectives are: development of superior unified algorithms emphasizing accuracy and efficiency aspects; development of codes based on selected algorithms leading to validation; application of mature codes to realistic problems; and extension/application of CFD-based algorithms to problems in other areas of mathematical physics. The ultimate objective is to achieve integration of multidisciplinary technologies to enhance synergism in the design process through computational simulation. Specific unified algorithms for a hierarchy of gas dynamics equations and their applications to two other areas: electromagnetic scattering, and laser-materials interaction accounting for melting.

Seizures in the elderly: development and validation of a diagnostic algorithm.

PubMed

Dupont, Sophie; Verny, Marc; Harston, Sandrine; Cartz-Piver, Leslie; Schück, Stéphane; Martin, Jennifer; Puisieux, François; Alecu, Cosmin; Vespignani, Hervé; Marchal, Cécile; Derambure, Philippe

2010-05-01

Seizures are frequent in the elderly, but their diagnosis can be challenging. The objective of this work was to develop and validate an expert-based algorithm for the diagnosis of seizures in elderly people. A multidisciplinary group of neurologists and geriatricians developed a diagnostic algorithm using a combination of selected clinical, electroencephalographical and radiological criteria. The algorithm was validated by multicentre retrospective analysis of data of patients referred for specific symptoms and classified by the experts as epileptic patients or not. The algorithm was applied to all the patients, and the diagnosis provided by the algorithm was compared to the clinical diagnosis of the experts. Twenty-nine clinical, electroencephalographical and radiological criteria were selected for the algorithm. According to criteria combination, seizures were classified in four levels of diagnosis: certain, highly probable, possible or improbable. To validate the algorithm, the medical records of 269 elderly patients were analyzed (138 with epileptic seizures, 131 with non-epileptic manifestations). Patients were mainly referred for a transient focal deficit (40%), confusion (38%), unconsciousness (27%). The algorithm best classified certain and probable seizures versus possible and improbable seizures, with 86.2% sensitivity and 67.2% specificity. Using logistical regression, 2 simplified models were developed, the first with 13 criteria (Se 85.5%, Sp 90.1%), and the second with 7 criteria only (Se 84.8%, Sp 88.6%). In conclusion, the present study validated the use of a revised diagnostic algorithm to help diagnosis epileptic seizures in the elderly. A prospective study is planned to further validate this algorithm. Copyright 2010 Elsevier B.V. All rights reserved.

Development and Application of a Portable Health Algorithms Test System

NASA Technical Reports Server (NTRS)

Melcher, Kevin J.; Fulton, Christopher E.; Maul, William A.; Sowers, T. Shane

2007-01-01

This paper describes the development and initial demonstration of a Portable Health Algorithms Test (PHALT) System that is being developed by researchers at the NASA Glenn Research Center (GRC). The PHALT System was conceived as a means of evolving the maturity and credibility of algorithms developed to assess the health of aerospace systems. Comprising an integrated hardware-software environment, the PHALT System allows systems health management algorithms to be developed in a graphical programming environment; to be tested and refined using system simulation or test data playback; and finally, to be evaluated in a real-time hardware-in-the-loop mode with a live test article. In this paper, PHALT System development is described through the presentation of a functional architecture, followed by the selection and integration of hardware and software. Also described is an initial real-time hardware-in-the-loop demonstration that used sensor data qualification algorithms to diagnose and isolate simulated sensor failures in a prototype Power Distribution Unit test-bed. Success of the initial demonstration is highlighted by the correct detection of all sensor failures and the absence of any real-time constraint violations.

Development and Evaluation of Model Algorithms to Account for Chemical Transformation in the Nearroad Environment

EPA Science Inventory

We describe the development and evaluation of two new model algorithms for NOx chemistry in the R-LINE near-road dispersion model for traffic sources. With increased urbanization, there is increased mobility leading to higher amount of traffic related activity on a global scale. ...

Battery algorithm verification and development using hardware-in-the-loop testing

NASA Astrophysics Data System (ADS)

He, Yongsheng; Liu, Wei; Koch, Brain J.

Battery algorithms play a vital role in hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), extended-range electric vehicles (EREVs), and electric vehicles (EVs). The energy management of hybrid and electric propulsion systems needs to rely on accurate information on the state of the battery in order to determine the optimal electric drive without abusing the battery. In this study, a cell-level hardware-in-the-loop (HIL) system is used to verify and develop state of charge (SOC) and power capability predictions of embedded battery algorithms for various vehicle applications. Two different batteries were selected as representative examples to illustrate the battery algorithm verification and development procedure. One is a lithium-ion battery with a conventional metal oxide cathode, which is a power battery for HEV applications. The other is a lithium-ion battery with an iron phosphate (LiFePO 4) cathode, which is an energy battery for applications in PHEVs, EREVs, and EVs. The battery cell HIL testing provided valuable data and critical guidance to evaluate the accuracy of the developed battery algorithms, to accelerate battery algorithm future development and improvement, and to reduce hybrid/electric vehicle system development time and costs.

Status report: Data management program algorithm evaluation activity at Marshall Space Flight Center

NASA Technical Reports Server (NTRS)

Jayroe, R. R., Jr.

1977-01-01

An algorithm evaluation activity was initiated to study the problems associated with image processing by assessing the independent and interdependent effects of registration, compression, and classification techniques on LANDSAT data for several discipline applications. The objective of the activity was to make recommendations on selected applicable image processing algorithms in terms of accuracy, cost, and timeliness or to propose alternative ways of processing the data. As a means of accomplishing this objective, an Image Coding Panel was established. The conduct of the algorithm evaluation is described.

Active control of impulsive noise with symmetric α-stable distribution based on an improved step-size normalized adaptive algorithm

NASA Astrophysics Data System (ADS)

Zhou, Yali; Zhang, Qizhi; Yin, Yixin

2015-05-01

In this paper, active control of impulsive noise with symmetric α-stable (SαS) distribution is studied. A general step-size normalized filtered-x Least Mean Square (FxLMS) algorithm is developed based on the analysis of existing algorithms, and the Gaussian distribution function is used to normalize the step size. Compared with existing algorithms, the proposed algorithm needs neither the parameter selection and thresholds estimation nor the process of cost function selection and complex gradient computation. Computer simulations have been carried out to suggest that the proposed algorithm is effective for attenuating SαS impulsive noise, and then the proposed algorithm has been implemented in an experimental ANC system. Experimental results show that the proposed scheme has good performance for SαS impulsive noise attenuation.

Development and implementation of clinical algorithms in occupational health practice.

PubMed

Ghafur, Imran; Lalloo, Drushca; Macdonald, Ewan B; Menon, Manju

2013-12-01

Occupational health (OH) practice is framed by legal, ethical, and regulatory requirements. Integrating this information into daily practice can be a difficult task. We devised evidence-based framework standards of good practice that would aid clinical management, and assessed their impact. The clinical algorithm was the method deemed most appropriate to our needs. Using "the first OH consultation" as an example, the development, implementation, and evaluation of an algorithm is described. The first OH consultation algorithm was developed. Evaluation demonstrated an overall improvement in recording of information, specifically consent, recreational drug history, function, and review arrangements. Clinical algorithms can be a method for assimilating and succinctly presenting the various facets of OH practice, for use by all OH clinicians as a practical guide and as a way of improving quality in clinical record-keeping.

Development of an Inverse Algorithm for Resonance Inspection

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

Lai, Canhai; Xu, Wei; Sun, Xin

2012-10-01

Resonance inspection (RI), which employs the natural frequency spectra shift between the good and the anomalous part populations to detect defects, is a non-destructive evaluation (NDE) technique with many advantages such as low inspection cost, high testing speed, and broad applicability to structures with complex geometry compared to other contemporary NDE methods. It has already been widely used in the automobile industry for quality inspections of safety critical parts. Unlike some conventionally used NDE methods, the current RI technology is unable to provide details, i.e. location, dimension, or types, of the flaws for the discrepant parts. Such limitation severely hindersmore » its wide spread applications and further development. In this study, an inverse RI algorithm based on maximum correlation function is proposed to quantify the location and size of flaws for a discrepant part. A dog-bone shaped stainless steel sample with and without controlled flaws are used for algorithm development and validation. The results show that multiple flaws can be accurately pinpointed back using the algorithms developed, and the prediction accuracy decreases with increasing flaw numbers and decreasing distance between flaws.« less

Strategic Control Algorithm Development : Volume 3. Strategic Algorithm Report.

DOT National Transportation Integrated Search

1974-08-01

The strategic algorithm report presents a detailed description of the functional basic strategic control arrival algorithm. This description is independent of a particular computer or language. Contained in this discussion are the geometrical and env...

Recognition physical activities with optimal number of wearable sensors using data mining algorithms and deep belief network.

PubMed

Al-Fatlawi, Ali H; Fatlawi, Hayder K; Sai Ho Ling

2017-07-01

Daily physical activities monitoring is benefiting the health care field in several ways, in particular with the development of the wearable sensors. This paper adopts effective ways to calculate the optimal number of the necessary sensors and to build a reliable and a high accuracy monitoring system. Three data mining algorithms, namely Decision Tree, Random Forest and PART Algorithm, have been applied for the sensors selection process. Furthermore, the deep belief network (DBN) has been investigated to recognise 33 physical activities effectively. The results indicated that the proposed method is reliable with an overall accuracy of 96.52% and the number of sensors is minimised from nine to six sensors.

Unified Framework for Development, Deployment and Robust Testing of Neuroimaging Algorithms

PubMed Central

Joshi, Alark; Scheinost, Dustin; Okuda, Hirohito; Belhachemi, Dominique; Murphy, Isabella; Staib, Lawrence H.; Papademetris, Xenophon

2011-01-01

Developing both graphical and command-line user interfaces for neuroimaging algorithms requires considerable effort. Neuroimaging algorithms can meet their potential only if they can be easily and frequently used by their intended users. Deployment of a large suite of such algorithms on multiple platforms requires consistency of user interface controls, consistent results across various platforms and thorough testing. We present the design and implementation of a novel object-oriented framework that allows for rapid development of complex image analysis algorithms with many reusable components and the ability to easily add graphical user interface controls. Our framework also allows for simplified yet robust nightly testing of the algorithms to ensure stability and cross platform interoperability. All of the functionality is encapsulated into a software object requiring no separate source code for user interfaces, testing or deployment. This formulation makes our framework ideal for developing novel, stable and easy-to-use algorithms for medical image analysis and computer assisted interventions. The framework has been both deployed at Yale and released for public use in the open source multi-platform image analysis software—BioImage Suite (bioimagesuite.org). PMID:21249532

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.

AeroADL: applying the integration of the Suomi-NPP science algorithms with the Algorithm Development Library to the calibration and validation task

NASA Astrophysics Data System (ADS)

Houchin, J. S.

2014-09-01

A common problem for the off-line validation of the calibration algorithms and algorithm coefficients is being able to run science data through the exact same software used for on-line calibration of that data. The Joint Polar Satellite System (JPSS) program solved part of this problem by making the Algorithm Development Library (ADL) available, which allows the operational algorithm code to be compiled and run on a desktop Linux workstation using flat file input and output. However, this solved only part of the problem, as the toolkit and methods to initiate the processing of data through the algorithms were geared specifically toward the algorithm developer, not the calibration analyst. In algorithm development mode, a limited number of sets of test data are staged for the algorithm once, and then run through the algorithm over and over as the software is developed and debugged. In calibration analyst mode, we are continually running new data sets through the algorithm, which requires significant effort to stage each of those data sets for the algorithm without additional tools. AeroADL solves this second problem by providing a set of scripts that wrap the ADL tools, providing both efficient means to stage and process an input data set, to override static calibration coefficient look-up-tables (LUT) with experimental versions of those tables, and to manage a library containing multiple versions of each of the static LUT files in such a way that the correct set of LUTs required for each algorithm are automatically provided to the algorithm without analyst effort. Using AeroADL, The Aerospace Corporation's analyst team has demonstrated the ability to quickly and efficiently perform analysis tasks for both the VIIRS and OMPS sensors with minimal training on the software tools.

Acoustic change detection algorithm using an FM radio

NASA Astrophysics Data System (ADS)

Goldman, Geoffrey H.; Wolfe, Owen

2012-06-01

The U.S. Army is interested in developing low-cost, low-power, non-line-of-sight sensors for monitoring human activity. One modality that is often overlooked is active acoustics using sources of opportunity such as speech or music. Active acoustics can be used to detect human activity by generating acoustic images of an area at different times, then testing for changes among the imagery. A change detection algorithm was developed to detect physical changes in a building, such as a door changing positions or a large box being moved using acoustics sources of opportunity. The algorithm is based on cross correlating the acoustic signal measured from two microphones. The performance of the algorithm was shown using data generated with a hand-held FM radio as a sound source and two microphones. The algorithm could detect a door being opened in a hallway.

A Computational Algorithm for Functional Clustering of Proteome Dynamics During Development

PubMed Central

Wang, Yaqun; Wang, Ningtao; Hao, Han; Guo, Yunqian; Zhen, Yan; Shi, Jisen; Wu, Rongling

2014-01-01

Phenotypic traits, such as seed development, are a consequence of complex biochemical interactions among genes, proteins and metabolites, but the underlying mechanisms that operate in a coordinated and sequential manner remain elusive. Here, we address this issue by developing a computational algorithm to monitor proteome changes during the course of trait development. The algorithm is built within the mixture-model framework in which each mixture component is modeled by a specific group of proteins that display a similar temporal pattern of expression in trait development. A nonparametric approach based on Legendre orthogonal polynomials was used to fit dynamic changes of protein expression, increasing the power and flexibility of protein clustering. By analyzing a dataset of proteomic dynamics during early embryogenesis of the Chinese fir, the algorithm has successfully identified several distinct types of proteins that coordinate with each other to determine seed development in this forest tree commercially and environmentally important to China. The algorithm will find its immediate applications for the characterization of mechanistic underpinnings for any other biological processes in which protein abundance plays a key role. PMID:24955031

Development of a measurement approach to assess time children participate in organized sport, active travel, outdoor active play, and curriculum-based physical activity.

PubMed

Borghese, Michael M; Janssen, Ian

2018-03-22

Children participate in four main types of physical activity: organized sport, active travel, outdoor active play, and curriculum-based physical activity. The objective of this study was to develop a valid approach that can be used to concurrently measure time spent in each of these types of physical activity. Two samples (sample 1: n = 50; sample 2: n = 83) of children aged 10-13 wore an accelerometer and a GPS watch continuously over 7 days. They also completed a log where they recorded the start and end times of organized sport sessions. Sample 1 also completed an outdoor time log where they recorded the times they went outdoors and a description of the outdoor activity. Sample 2 also completed a curriculum log where they recorded times they participated in physical activity (e.g., physical education) during class time. We describe the development of a measurement approach that can be used to concurrently assess the time children spend participating in specific types of physical activity. The approach uses a combination of data from accelerometers, GPS, and activity logs and relies on merging and then processing these data using several manual (e.g., data checks and cleaning) and automated (e.g., algorithms) procedures. In the new measurement approach time spent in organized sport is estimated using the activity log. Time spent in active travel is estimated using an existing algorithm that uses GPS data. Time spent in outdoor active play is estimated using an algorithm (with a sensitivity and specificity of 85%) that was developed using data collected in sample 1 and which uses all of the data sources. Time spent in curriculum-based physical activity is estimated using an algorithm (with a sensitivity of 78% and specificity of 92%) that was developed using data collected in sample 2 and which uses accelerometer data collected during class time. There was evidence of excellent intra- and inter-rater reliability of the estimates for all of these types of

Update on Development of Mesh Generation Algorithms in MeshKit

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

Jain, Rajeev; Vanderzee, Evan; Mahadevan, Vijay

2015-09-30

MeshKit uses a graph-based design for coding all its meshing algorithms, which includes the Reactor Geometry (and mesh) Generation (RGG) algorithms. This report highlights the developmental updates of all the algorithms, results and future work. Parallel versions of algorithms, documentation and performance results are reported. RGG GUI design was updated to incorporate new features requested by the users; boundary layer generation and parallel RGG support were added to the GUI. Key contributions to the release, upgrade and maintenance of other SIGMA1 libraries (CGM and MOAB) were made. Several fundamental meshing algorithms for creating a robust parallel meshing pipeline in MeshKitmore » are under development. Results and current status of automated, open-source and high quality nuclear reactor assembly mesh generation algorithms such as trimesher, quadmesher, interval matching and multi-sweeper are reported.« less

An Optimal CDS Construction Algorithm with Activity Scheduling in Ad Hoc Networks

PubMed Central

Penumalli, Chakradhar; Palanichamy, Yogesh

2015-01-01

A new energy efficient optimal Connected Dominating Set (CDS) algorithm with activity scheduling for mobile ad hoc networks (MANETs) is proposed. This algorithm achieves energy efficiency by minimizing the Broadcast Storm Problem [BSP] and at the same time considering the node's remaining energy. The Connected Dominating Set is widely used as a virtual backbone or spine in mobile ad hoc networks [MANETs] or Wireless Sensor Networks [WSN]. The CDS of a graph representing a network has a significant impact on an efficient design of routing protocol in wireless networks. Here the CDS is a distributed algorithm with activity scheduling based on unit disk graph [UDG]. The node's mobility and residual energy (RE) are considered as parameters in the construction of stable optimal energy efficient CDS. The performance is evaluated at various node densities, various transmission ranges, and mobility rates. The theoretical analysis and simulation results of this algorithm are also presented which yield better results. PMID:26221627

Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity

USGS Publications Warehouse

Louis, S.J.; Raines, G.L.

2003-01-01

We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic algorithm searches through a space of transition rule parameters of a two dimensional cellular automata model to find rule parameters that fit observed mining activity data. Previous work by one of the authors in calibrating the cellular automaton took weeks - the genetic algorithm takes a day and produces rules leading to about the same (or better) fit to observed data. These preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application. Experience gained during the calibration of this cellular automata suggests that mineral resource information is a critical factor in the quality of the results. With automated calibration, further refinements of how the mineral-resource information is provided to the cellular automaton will probably improve our model.

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.

Anti-aliasing algorithm development

NASA Astrophysics Data System (ADS)

Bodrucki, F.; Davis, J.; Becker, J.; Cordell, J.

2017-10-01

In this paper, we discuss the testing image processing algorithms for mitigation of aliasing artifacts under pulsed illumination. Previously sensors were tested, one with a fixed frame rate and one with an adjustable frame rate, which results showed different degrees of operability when subjected to a Quantum Cascade Laser (QCL) laser pulsed at the frame rate of the fixe-rate sensor. We implemented algorithms to allow the adjustable frame-rate sensor to detect the presence of aliasing artifacts, and in response, to alter the frame rate of the sensor. The result was that the sensor output showed a varying laser intensity (beat note) as opposed to a fixed signal level. A MIRAGE Infrared Scene Projector (IRSP) was used to explore the efficiency of the new algorithms, introduction secondary elements into the sensor's field of view.

Development of an algorithm for improving quality and information processing capacity of MathSpeak synthetic speech renderings.

PubMed

Isaacson, M D; Srinivasan, S; Lloyd, L L

2010-01-01

MathSpeak is a set of rules for non speaking of mathematical expressions. These rules have been incorporated into a computerised module that translates printed mathematics into the non-ambiguous MathSpeak form for synthetic speech rendering. Differences between individual utterances produced with the translator module are difficult to discern because of insufficient pausing between utterances; hence, the purpose of this study was to develop an algorithm for improving the synthetic speech rendering of MathSpeak. To improve synthetic speech renderings, an algorithm for inserting pauses was developed based upon recordings of middle and high school math teachers speaking mathematic expressions. Efficacy testing of this algorithm was conducted with college students without disabilities and high school/college students with visual impairments. Parameters measured included reception accuracy, short-term memory retention, MathSpeak processing capacity and various rankings concerning the quality of synthetic speech renderings. All parameters measured showed statistically significant improvements when the algorithm was used. The algorithm improves the quality and information processing capacity of synthetic speech renderings of MathSpeak. This increases the capacity of individuals with print disabilities to perform mathematical activities and to successfully fulfill science, technology, engineering and mathematics academic and career objectives.

Time-varying delays compensation algorithm for powertrain active damping of an electrified vehicle equipped with an axle motor during regenerative braking

NASA Astrophysics Data System (ADS)

Zhang, Junzhi; Li, Yutong; Lv, Chen; Gou, Jinfang; Yuan, Ye

2017-03-01

The flexibility of the electrified powertrain system elicits a negative effect upon the cooperative control performance between regenerative and hydraulic braking and the active damping control performance. Meanwhile, the connections among sensors, controllers, and actuators are realized via network communication, i.e., controller area network (CAN), that introduces time-varying delays and deteriorates the control performances of the closed-loop control systems. As such, the goal of this paper is to develop a control algorithm to cope with all these challenges. To this end, the models of the stochastic network induced time-varying delays, based on a real in-vehicle network topology and on a flexible electrified powertrain, were firstly built. In order to further enhance the control performances of active damping and cooperative control of regenerative and hydraulic braking, the time-varying delays compensation algorithm for the electrified powertrain active damping during regenerative braking was developed based on a predictive scheme. The augmented system is constructed and the H∞ performance is analyzed. Based on this analysis, the control gains are derived by solving a nonlinear minimization problem. The simulations and hardware-in-loop (HIL) tests were carried out to validate the effectiveness of the developed algorithm. The test results show that the active damping and cooperative control performances are enhanced significantly.

Performance of thigh-mounted triaxial accelerometer algorithms in objective quantification of sedentary behaviour and physical activity in older adults.

PubMed

Wullems, Jorgen A; Verschueren, Sabine M P; Degens, Hans; Morse, Christopher I; Onambélé, Gladys L

2017-01-01

Accurate monitoring of sedentary behaviour and physical activity is key to investigate their exact role in healthy ageing. To date, accelerometers using cut-off point models are most preferred for this, however, machine learning seems a highly promising future alternative. Hence, the current study compared between cut-off point and machine learning algorithms, for optimal quantification of sedentary behaviour and physical activity intensities in the elderly. Thus, in a heterogeneous sample of forty participants (aged ≥60 years, 50% female) energy expenditure during laboratory-based activities (ranging from sedentary behaviour through to moderate-to-vigorous physical activity) was estimated by indirect calorimetry, whilst wearing triaxial thigh-mounted accelerometers. Three cut-off point algorithms and a Random Forest machine learning model were developed and cross-validated using the collected data. Detailed analyses were performed to check algorithm robustness, and examine and benchmark both overall and participant-specific balanced accuracies. This revealed that the four models can at least be used to confidently monitor sedentary behaviour and moderate-to-vigorous physical activity. Nevertheless, the machine learning algorithm outperformed the cut-off point models by being robust for all individual's physiological and non-physiological characteristics and showing more performance of an acceptable level over the whole range of physical activity intensities. Therefore, we propose that Random Forest machine learning may be optimal for objective assessment of sedentary behaviour and physical activity in older adults using thigh-mounted triaxial accelerometry.

Performance of thigh-mounted triaxial accelerometer algorithms in objective quantification of sedentary behaviour and physical activity in older adults

PubMed Central

Verschueren, Sabine M. P.; Degens, Hans; Morse, Christopher I.; Onambélé, Gladys L.

2017-01-01

Accurate monitoring of sedentary behaviour and physical activity is key to investigate their exact role in healthy ageing. To date, accelerometers using cut-off point models are most preferred for this, however, machine learning seems a highly promising future alternative. Hence, the current study compared between cut-off point and machine learning algorithms, for optimal quantification of sedentary behaviour and physical activity intensities in the elderly. Thus, in a heterogeneous sample of forty participants (aged ≥60 years, 50% female) energy expenditure during laboratory-based activities (ranging from sedentary behaviour through to moderate-to-vigorous physical activity) was estimated by indirect calorimetry, whilst wearing triaxial thigh-mounted accelerometers. Three cut-off point algorithms and a Random Forest machine learning model were developed and cross-validated using the collected data. Detailed analyses were performed to check algorithm robustness, and examine and benchmark both overall and participant-specific balanced accuracies. This revealed that the four models can at least be used to confidently monitor sedentary behaviour and moderate-to-vigorous physical activity. Nevertheless, the machine learning algorithm outperformed the cut-off point models by being robust for all individual’s physiological and non-physiological characteristics and showing more performance of an acceptable level over the whole range of physical activity intensities. Therefore, we propose that Random Forest machine learning may be optimal for objective assessment of sedentary behaviour and physical activity in older adults using thigh-mounted triaxial accelerometry. PMID:29155839

Ocean observations with EOS/MODIS: Algorithm development and post launch studies

NASA Technical Reports Server (NTRS)

Gordon, Howard R.

1995-01-01

An investigation of the influence of stratospheric aerosol on the performance of the atmospheric correction algorithm was carried out. The results indicate how the performance of the algorithm is degraded if the stratospheric aerosol is ignored. Use of the MODIS 1380 nm band to effect a correction for stratospheric aerosols was also studied. The development of a multi-layer Monte Carlo radiative transfer code that includes polarization by molecular and aerosol scattering and wind-induced sea surface roughness has been completed. Comparison tests with an existing two-layer successive order of scattering code suggests that both codes are capable of producing top-of-atmosphere radiances with errors usually less than 0.1 percent. An initial set of simulations to study the effects of ignoring the polarization of the the ocean-atmosphere light field, in both the development of the atmospheric correction algorithm and the generation of the lookup tables used for operation of the algorithm, have been completed. An algorithm was developed that can be used to invert the radiance exiting the top and bottom of the atmosphere to yield the columnar optical properties of the atmospheric aerosol under clear sky conditions over the ocean, for aerosol optical thicknesses as large as 2. The algorithm is capable of retrievals with such large optical thicknesses because all significant orders of multiple scattering are included.

Development and Evaluation of Algorithms for Breath Alcohol Screening.

PubMed

Ljungblad, Jonas; Hök, Bertil; Ekström, Mikael

2016-04-01

Breath alcohol screening is important for traffic safety, access control and other areas of health promotion. A family of sensor devices useful for these purposes is being developed and evaluated. This paper is focusing on algorithms for the determination of breath alcohol concentration in diluted breath samples using carbon dioxide to compensate for the dilution. The examined algorithms make use of signal averaging, weighting and personalization to reduce estimation errors. Evaluation has been performed by using data from a previously conducted human study. It is concluded that these features in combination will significantly reduce the random error compared to the signal averaging algorithm taken alone.

Motion Cueing Algorithm Development: Human-Centered Linear and Nonlinear Approaches

NASA Technical Reports Server (NTRS)

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

2005-01-01

While the performance of flight simulator motion system hardware has advanced substantially, the development of the motion cueing algorithm, the software that transforms simulated aircraft dynamics into realizable motion commands, has not kept pace. Prior research identified viable features from two algorithms: the nonlinear "adaptive algorithm", and the "optimal algorithm" that incorporates human vestibular models. A novel approach to motion cueing, the "nonlinear algorithm" is introduced that combines features from both approaches. This algorithm is formulated by optimal control, and incorporates a new integrated perception model that includes both visual and vestibular sensation and the interaction between the stimuli. Using a time-varying control law, the matrix Riccati equation is updated in real time by a neurocomputing approach. Preliminary pilot testing resulted in the optimal algorithm incorporating a new otolith model, producing improved motion cues. The nonlinear algorithm vertical mode produced a motion cue with a time-varying washout, sustaining small cues for longer durations and washing out large cues more quickly compared to the optimal algorithm. The inclusion of the integrated perception model improved the responses to longitudinal and lateral cues. False cues observed with the NASA adaptive algorithm were absent. The neurocomputing approach was crucial in that the number of presentations of an input vector could be reduced to meet the real time requirement without degrading the quality of the motion cues.

Effects of Varying Epoch Lengths, Wear Time Algorithms, and Activity Cut-Points on Estimates of Child Sedentary Behavior and Physical Activity from Accelerometer Data.

PubMed

Banda, Jorge A; Haydel, K Farish; Davila, Tania; Desai, Manisha; Bryson, Susan; Haskell, William L; Matheson, Donna; Robinson, Thomas N

2016-01-01

To examine the effects of accelerometer epoch lengths, wear time (WT) algorithms, and activity cut-points on estimates of WT, sedentary behavior (SB), and physical activity (PA). 268 7-11 year-olds with BMI ≥ 85th percentile for age and sex wore accelerometers on their right hips for 4-7 days. Data were processed and analyzed at epoch lengths of 1-, 5-, 10-, 15-, 30-, and 60-seconds. For each epoch length, WT minutes/day was determined using three common WT algorithms, and minutes/day and percent time spent in SB, light (LPA), moderate (MPA), and vigorous (VPA) PA were determined using five common activity cut-points. ANOVA tested differences in WT, SB, LPA, MPA, VPA, and MVPA when using the different epoch lengths, WT algorithms, and activity cut-points. WT minutes/day varied significantly by epoch length when using the NHANES WT algorithm (p < .0001), but did not vary significantly by epoch length when using the ≥ 20 minute consecutive zero or Choi WT algorithms. Minutes/day and percent time spent in SB, LPA, MPA, VPA, and MVPA varied significantly by epoch length for all sets of activity cut-points tested with all three WT algorithms (all p < .0001). Across all epoch lengths, minutes/day and percent time spent in SB, LPA, MPA, VPA, and MVPA also varied significantly across all sets of activity cut-points with all three WT algorithms (all p < .0001). The common practice of converting WT algorithms and activity cut-point definitions to match different epoch lengths may introduce significant errors. Estimates of SB and PA from studies that process and analyze data using different epoch lengths, WT algorithms, and/or activity cut-points are not comparable, potentially leading to very different results, interpretations, and conclusions, misleading research and public policy.

Investigation of trunk muscle activities during lifting using a multi-objective optimization-based model and intelligent optimization algorithms.

PubMed

Ghiasi, Mohammad Sadegh; Arjmand, Navid; Boroushaki, Mehrdad; Farahmand, Farzam

2016-03-01

A six-degree-of-freedom musculoskeletal model of the lumbar spine was developed to predict the activity of trunk muscles during light, moderate and heavy lifting tasks in standing posture. The model was formulated into a multi-objective optimization problem, minimizing the sum of the cubed muscle stresses and maximizing the spinal stability index. Two intelligent optimization algorithms, i.e., the vector evaluated particle swarm optimization (VEPSO) and nondominated sorting genetic algorithm (NSGA), were employed to solve the optimization problem. The optimal solution for each task was then found in the way that the corresponding in vivo intradiscal pressure could be reproduced. Results indicated that both algorithms predicted co-activity in the antagonistic abdominal muscles, as well as an increase in the stability index when going from the light to the heavy task. For all of the light, moderate and heavy tasks, the muscles' activities predictions of the VEPSO and the NSGA were generally consistent and in the same order of the in vivo electromyography data. The proposed methodology is thought to provide improved estimations for muscle activities by considering the spinal stability and incorporating the in vivo intradiscal pressure data.

Active module identification in intracellular networks using a memetic algorithm with a new binary decoding scheme.

PubMed

Li, Dong; Pan, Zhisong; Hu, Guyu; Zhu, Zexuan; He, Shan

2017-03-14

Active modules are connected regions in biological network which show significant changes in expression over particular conditions. The identification of such modules is important since it may reveal the regulatory and signaling mechanisms that associate with a given cellular response. In this paper, we propose a novel active module identification algorithm based on a memetic algorithm. We propose a novel encoding/decoding scheme to ensure the connectedness of the identified active modules. Based on the scheme, we also design and incorporate a local search operator into the memetic algorithm to improve its performance. The effectiveness of proposed algorithm is validated on both small and large protein interaction networks.

Computationally efficient algorithm for high sampling-frequency operation of active noise control

NASA Astrophysics Data System (ADS)

Rout, Nirmal Kumar; Das, Debi Prasad; Panda, Ganapati

2015-05-01

In high sampling-frequency operation of active noise control (ANC) system the length of the secondary path estimate and the ANC filter are very long. This increases the computational complexity of the conventional filtered-x least mean square (FXLMS) algorithm. To reduce the computational complexity of long order ANC system using FXLMS algorithm, frequency domain block ANC algorithms have been proposed in past. These full block frequency domain ANC algorithms are associated with some disadvantages such as large block delay, quantization error due to computation of large size transforms and implementation difficulties in existing low-end DSP hardware. To overcome these shortcomings, the partitioned block ANC algorithm is newly proposed where the long length filters in ANC are divided into a number of equal partitions and suitably assembled to perform the FXLMS algorithm in the frequency domain. The complexity of this proposed frequency domain partitioned block FXLMS (FPBFXLMS) algorithm is quite reduced compared to the conventional FXLMS algorithm. It is further reduced by merging one fast Fourier transform (FFT)-inverse fast Fourier transform (IFFT) combination to derive the reduced structure FPBFXLMS (RFPBFXLMS) algorithm. Computational complexity analysis for different orders of filter and partition size are presented. Systematic computer simulations are carried out for both the proposed partitioned block ANC algorithms to show its accuracy compared to the time domain FXLMS algorithm.

Collaboration space division in collaborative product development based on a genetic algorithm

NASA Astrophysics Data System (ADS)

Qian, Xueming; Ma, Yanqiao; Feng, Huan

2018-02-01

The advance in the global environment, rapidly changing markets, and information technology has created a new stage for design. In such an environment, one strategy for success is the Collaborative Product Development (CPD). Organizing people effectively is the goal of Collaborative Product Development, and it solves the problem with certain foreseeability. The development group activities are influenced not only by the methods and decisions available, but also by correlation among personnel. Grouping the personnel according to their correlation intensity is defined as collaboration space division (CSD). Upon establishment of a correlation matrix (CM) of personnel and an analysis of the collaboration space, the genetic algorithm (GA) and minimum description length (MDL) principle may be used as tools in optimizing collaboration space. The MDL principle is used in setting up an object function, and the GA is used as a methodology. The algorithm encodes spatial information as a chromosome in binary. After repetitious crossover, mutation, selection and multiplication, a robust chromosome is found, which can be decoded into an optimal collaboration space. This new method can calculate the members in sub-spaces and individual groupings within the staff. Furthermore, the intersection of sub-spaces and public persons belonging to all sub-spaces can be determined simultaneously.

Development and validation of an algorithm for laser application in wound treatment 1

PubMed Central

da Cunha, Diequison Rite; Salomé, Geraldo Magela; Massahud, Marcelo Renato; Mendes, Bruno; Ferreira, Lydia Masako

2017-01-01

ABSTRACT Objective: To develop and validate an algorithm for laser wound therapy. Method: Methodological study and literature review. For the development of the algorithm, a review was performed in the Health Sciences databases of the past ten years. The algorithm evaluation was performed by 24 participants, nurses, physiotherapists, and physicians. For data analysis, the Cronbach’s alpha coefficient and the chi-square test for independence was used. The level of significance of the statistical test was established at 5% (p<0.05). Results: The professionals’ responses regarding the facility to read the algorithm indicated: 41.70%, great; 41.70%, good; 16.70%, regular. With regard the algorithm being sufficient for supporting decisions related to wound evaluation and wound cleaning, 87.5% said yes to both questions. Regarding the participants’ opinion that the algorithm contained enough information to support their decision regarding the choice of laser parameters, 91.7% said yes. The questionnaire presented reliability using the Cronbach’s alpha coefficient test (α = 0.962). Conclusion: The developed and validated algorithm showed reliability for evaluation, wound cleaning, and use of laser therapy in wounds. PMID:29211197

Automated Development of Accurate Algorithms and Efficient Codes for Computational Aeroacoustics

NASA Technical Reports Server (NTRS)

Goodrich, John W.; Dyson, Rodger W.

1999-01-01

The simulation of sound generation and propagation in three space dimensions with realistic aircraft components is a very large time dependent computation with fine details. Simulations in open domains with embedded objects require accurate and robust algorithms for propagation, for artificial inflow and outflow boundaries, and for the definition of geometrically complex objects. The development, implementation, and validation of methods for solving these demanding problems is being done to support the NASA pillar goals for reducing aircraft noise levels. Our goal is to provide algorithms which are sufficiently accurate and efficient to produce usable results rapidly enough to allow design engineers to study the effects on sound levels of design changes in propulsion systems, and in the integration of propulsion systems with airframes. There is a lack of design tools for these purposes at this time. Our technical approach to this problem combines the development of new, algorithms with the use of Mathematica and Unix utilities to automate the algorithm development, code implementation, and validation. We use explicit methods to ensure effective implementation by domain decomposition for SPMD parallel computing. There are several orders of magnitude difference in the computational efficiencies of the algorithms which we have considered. We currently have new artificial inflow and outflow boundary conditions that are stable, accurate, and unobtrusive, with implementations that match the accuracy and efficiency of the propagation methods. The artificial numerical boundary treatments have been proven to have solutions which converge to the full open domain problems, so that the error from the boundary treatments can be driven as low as is required. The purpose of this paper is to briefly present a method for developing highly accurate algorithms for computational aeroacoustics, the use of computer automation in this process, and a brief survey of the algorithms that

Problem Solving Techniques for the Design of Algorithms.

ERIC Educational Resources Information Center

Kant, Elaine; Newell, Allen

1984-01-01

Presents model of algorithm design (activity in software development) based on analysis of protocols of two subjects designing three convex hull algorithms. Automation methods, methods for studying algorithm design, role of discovery in problem solving, and comparison of different designs of case study according to model are highlighted.…

User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm.

PubMed

Bourobou, Serge Thomas Mickala; Yoo, Younghwan

2015-05-21

This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen's temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home.

User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm

PubMed Central

Bourobou, Serge Thomas Mickala; Yoo, Younghwan

2015-01-01

This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen’s temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home. PMID:26007738

Phase 2 development of Great Lakes algorithms for Nimbus-7 coastal zone color scanner

NASA Technical Reports Server (NTRS)

Tanis, Fred J.

1984-01-01

A series of experiments have been conducted in the Great Lakes designed to evaluate the application of the NIMBUS-7 Coastal Zone Color Scanner (CZCS). Atmospheric and water optical models were used to relate surface and subsurface measurements to satellite measured radiances. Absorption and scattering measurements were reduced to obtain a preliminary optical model for the Great Lakes. Algorithms were developed for geometric correction, correction for Rayleigh and aerosol path radiance, and prediction of chlorophyll-a pigment and suspended mineral concentrations. The atmospheric algorithm developed compared favorably with existing algorithms and was the only algorithm found to adequately predict the radiance variations in the 670 nm band. The atmospheric correction algorithm developed was designed to extract needed algorithm parameters from the CZCS radiance values. The Gordon/NOAA ocean algorithms could not be demonstrated to work for Great Lakes waters. Predicted values of chlorophyll-a concentration compared favorably with expected and measured data for several areas of the Great Lakes.

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.

Active flow separation control by a position-based iterative learning control algorithm with experimental validation

NASA Astrophysics Data System (ADS)

Cai, Zhonglun; Chen, Peng; Angland, David; Zhang, Xin

2014-03-01

A novel iterative learning control (ILC) algorithm was developed and applied to an active flow control problem. The technique uses pulsed air jets to delay flow separation on a two-element high-lift wing. The ILC algorithm uses position-based pressure measurements to update the actuation. The method was experimentally tested on a wing model in a 0.9 m × 0.6 m low-speed wind tunnel at the University of Southampton. Compressed air and fast switching solenoid valves were used as actuators to excite the flow, and the pressure distribution around the chord of the wing was measured as a feedback control signal for the ILC controller. Experimental results showed that the actuation was able to delay the separation and increase the lift by approximately 10%-15%. By using the ILC algorithm, the controller was able to find the optimum control input and maintain the improvement despite sudden changes of the separation position.

Developing and Implementing the Data Mining Algorithms in RAVEN

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

Sen, Ramazan Sonat; Maljovec, Daniel Patrick; Alfonsi, Andrea

The RAVEN code is becoming a comprehensive tool to perform probabilistic risk assessment, uncertainty quantification, and verification and validation. The RAVEN code is being developed to support many programs and to provide a set of methodologies and algorithms for advanced analysis. Scientific computer codes can generate enormous amounts of data. To post-process and analyze such data might, in some cases, take longer than the initial software runtime. Data mining algorithms/methods help in recognizing and understanding patterns in the data, and thus discover knowledge in databases. The methodologies used in the dynamic probabilistic risk assessment or in uncertainty and error quantificationmore » analysis couple system/physics codes with simulation controller codes, such as RAVEN. RAVEN introduces both deterministic and stochastic elements into the simulation while the system/physics code model the dynamics deterministically. A typical analysis is performed by sampling values of a set of parameter values. A major challenge in using dynamic probabilistic risk assessment or uncertainty and error quantification analysis for a complex system is to analyze the large number of scenarios generated. Data mining techniques are typically used to better organize and understand data, i.e. recognizing patterns in the data. This report focuses on development and implementation of Application Programming Interfaces (APIs) for different data mining algorithms, and the application of these algorithms to different databases.« less

The development of a whole-body algorithm

NASA Technical Reports Server (NTRS)

Kay, F. J.

1973-01-01

The whole-body algorithm is envisioned as a mathematical model that utilizes human physiology to simulate the behavior of vital body systems. The objective of this model is to determine the response of selected body parameters within these systems to various input perturbations, or stresses. Perturbations of interest are exercise, chemical unbalances, gravitational changes and other abnormal environmental conditions. This model provides for a study of man's physiological response in various space applications, underwater applications, normal and abnormal workloads and environments, and the functioning of the system with physical impairments or decay of functioning components. Many methods or approaches to the development of a whole-body algorithm are considered. Of foremost concern is the determination of the subsystems to be included, the detail of the subsystems and the interaction between the subsystems.

VIIRS validation and algorithm development efforts in coastal and inland Waters

NASA Astrophysics Data System (ADS)

Stengel, E.; Ondrusek, M.

2016-02-01

Accurate satellite ocean color measurements in coastal and inland waters are more challenging than open-ocean measurements. Complex water and atmospheric conditions can limit the utilization of remote sensing data in coastal waters where it is most needed. The Coastal Optical Characterization Experiment (COCE) is an ongoing project at NOAA/NESDIS/STAR Satellite Oceanography and Climatology Division. The primary goals of COCE are satellite ocean color validation and application development. Currently, this effort concentrates on the initialization and validation of the Joint Polar Satellite System (JPSS) VIIRS sensor using a Satlantic HyperPro II radiometer as a validation tool. A report on VIIRS performance in coastal waters will be given by presenting comparisons between in situ ground truth measurements and VIIRS retrievals made in the Chesapeake Bay, and inland waters of the Gulf of Mexico and Puerto Rico. The COCE application development effort focuses on developing new ocean color satellite remote sensing tools for monitoring relevant coastal ocean parameters. A new VIIRS total suspended matter algorithm will be presented for the Chesapeake Bay. These activities improve the utility of ocean color satellite data in monitoring and analyzing coastal and oceanic processes. Progress on these activities will be reported.

Development of an algorithm to plan and simulate a new interventional procedure.

PubMed

Fujita, Buntaro; Kütting, Maximilian; Scholtz, Smita; Utzenrath, Marc; Hakim-Meibodi, Kavous; Paluszkiewicz, Lech; Schmitz, Christoph; Börgermann, Jochen; Gummert, Jan; Steinseifer, Ulrich; Ensminger, Stephan

2015-07-01

The number of implanted biological valves for treatment of valvular heart disease is growing and a percentage of these patients will eventually undergo a transcatheter valve-in-valve (ViV) procedure. Some of these patients will represent challenging cases. The aim of this study was to develop a feasible algorithm to plan and in vitro simulate a new interventional procedure to improve patient outcome. In addition to standard diagnostic routine, our algorithm includes 3D printing of the annulus, hydrodynamic measurements and high-speed analysis of leaflet kinematics after simulation of the procedure in different prosthesis positions as well as X-ray imaging of the most suitable valve position to create a 'blueprint' for the patient procedure. This algorithm was developed for a patient with a degenerated Perceval aortic sutureless prosthesis requiring a ViV procedure. Different ViV procedures were assessed in the algorithm and based on these results the best option for the patient was chosen. The actual procedure went exactly as planned with help of this algorithm. Here we have developed a new technically feasible algorithm simulating important aspects of a novel interventional procedure prior to the actual procedure. This algorithm can be applied to virtually all patients requiring a novel interventional procedure to help identify risks and find optimal parameters for prosthesis selection and placement in order to maximize safety for the patient. © The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Effects of activity and energy budget balancing algorithm on laboratory performance of a fish bioenergetics model

USGS Publications Warehouse

Madenjian, Charles P.; David, Solomon R.; Pothoven, Steven A.

2012-01-01

We evaluated the performance of the Wisconsin bioenergetics model for lake trout Salvelinus namaycush that were fed ad libitum in laboratory tanks under regimes of low activity and high activity. In addition, we compared model performance under two different model algorithms: (1) balancing the lake trout energy budget on day t based on lake trout energy density on day t and (2) balancing the lake trout energy budget on day t based on lake trout energy density on day t + 1. Results indicated that the model significantly underestimated consumption for both inactive and active lake trout when algorithm 1 was used and that the degree of underestimation was similar for the two activity levels. In contrast, model performance substantially improved when using algorithm 2, as no detectable bias was found in model predictions of consumption for inactive fish and only a slight degree of overestimation was detected for active fish. The energy budget was accurately balanced by using algorithm 2 but not by using algorithm 1. Based on the results of this study, we recommend the use of algorithm 2 to estimate food consumption by fish in the field. Our study results highlight the importance of accurately accounting for changes in fish energy density when balancing the energy budget; furthermore, these results have implications for the science of evaluating fish bioenergetics model performance and for more accurate estimation of food consumption by fish in the field when fish energy density undergoes relatively rapid changes.

Machine Learning Algorithms Outperform Conventional Regression Models in Predicting Development of Hepatocellular Carcinoma

PubMed Central

Singal, Amit G.; Mukherjee, Ashin; Elmunzer, B. Joseph; Higgins, Peter DR; Lok, Anna S.; Zhu, Ji; Marrero, Jorge A; Waljee, Akbar K

2015-01-01

Background Predictive models for hepatocellular carcinoma (HCC) have been limited by modest accuracy and lack of validation. Machine learning algorithms offer a novel methodology, which may improve HCC risk prognostication among patients with cirrhosis. Our study's aim was to develop and compare predictive models for HCC development among cirrhotic patients, using conventional regression analysis and machine learning algorithms. Methods We enrolled 442 patients with Child A or B cirrhosis at the University of Michigan between January 2004 and September 2006 (UM cohort) and prospectively followed them until HCC development, liver transplantation, death, or study termination. Regression analysis and machine learning algorithms were used to construct predictive models for HCC development, which were tested on an independent validation cohort from the Hepatitis C Antiviral Long-term Treatment against Cirrhosis (HALT-C) Trial. Both models were also compared to the previously published HALT-C model. Discrimination was assessed using receiver operating characteristic curve analysis and diagnostic accuracy was assessed with net reclassification improvement and integrated discrimination improvement statistics. Results After a median follow-up of 3.5 years, 41 patients developed HCC. The UM regression model had a c-statistic of 0.61 (95%CI 0.56-0.67), whereas the machine learning algorithm had a c-statistic of 0.64 (95%CI 0.60–0.69) in the validation cohort. The machine learning algorithm had significantly better diagnostic accuracy as assessed by net reclassification improvement (p<0.001) and integrated discrimination improvement (p=0.04). The HALT-C model had a c-statistic of 0.60 (95%CI 0.50-0.70) in the validation cohort and was outperformed by the machine learning algorithm (p=0.047). Conclusion Machine learning algorithms improve the accuracy of risk stratifying patients with cirrhosis and can be used to accurately identify patients at high-risk for developing HCC

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.

An algorithm to detect fire activity using Meteosat: fine tuning and quality assesment

NASA Astrophysics Data System (ADS)

Amraoui, M.; DaCamara, C. C.; Ermida, S. L.

2012-04-01

Hot spot detection by means of sensors on-board geostationary satellites allows studying wildfire activity at hourly and even sub-hourly intervals, an advantage that cannot be met by polar orbiters. Since 1997, the Satellite Application Facility for Land Surface Analysis has been running an operational procedure that allows detecting active fires based on information from Meteosat-8/SEVIRI. This is the so-called Fire Detection and Monitoring (FD&M) product and the procedure takes advantage of the temporal resolution of SEVIRI (one image every 15 min), and relies on information from SEVIRI channels (namely 0.6, 0.8, 3.9, 10.8 and 12.0 μm) together with information on illumination angles. The method is based on heritage from contextual algorithms designed for polar, sun-synchronous instruments, namely NOAA/AVHRR and MODIS/TERRAAQUA. A potential fire pixel is compared with the neighboring ones and the decision is made based on relative thresholds as derived from the pixels in the neighborhood. Generally speaking, the observed fire incidence compares well against hot spots extracted from the global daily active fire product developed by the MODIS Fire Team. However, values of probability of detection (POD) tend to be quite low, a result that may be partially expected by the finer resolution of MODIS. The aim of the present study is to make a systematic assessment of the impacts on POD and False Alarm Ratio (FAR) of the several parameters that are set in the algorithms. Such parameters range from the threshold values of brightness temperature in the IR3.9 and 10.8 channels that are used to select potential fire pixels up to the extent of the background grid and thresholds used to statistically characterize the radiometric departures of a potential pixel from the respective background. The impact of different criteria to identify pixels contaminated by clouds, smoke and sun glint is also evaluated. Finally, the advantages that may be brought to the algorithm by adding

Efficient parallel implementation of active appearance model fitting algorithm on GPU.

PubMed

Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou

2014-01-01

The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures.

Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU

PubMed Central

Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou

2014-01-01

The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures. PMID:24723812

Identifying Active Travel Behaviors in Challenging Environments Using GPS, Accelerometers, and Machine Learning Algorithms.

PubMed

Ellis, Katherine; Godbole, Suneeta; Marshall, Simon; Lanckriet, Gert; Staudenmayer, John; Kerr, Jacqueline

2014-01-01

Active travel is an important area in physical activity research, but objective measurement of active travel is still difficult. Automated methods to measure travel behaviors will improve research in this area. In this paper, we present a supervised machine learning method for transportation mode prediction from global positioning system (GPS) and accelerometer data. We collected a dataset of about 150 h of GPS and accelerometer data from two research assistants following a protocol of prescribed trips consisting of five activities: bicycling, riding in a vehicle, walking, sitting, and standing. We extracted 49 features from 1-min windows of this data. We compared the performance of several machine learning algorithms and chose a random forest algorithm to classify the transportation mode. We used a moving average output filter to smooth the output predictions over time. The random forest algorithm achieved 89.8% cross-validated accuracy on this dataset. Adding the moving average filter to smooth output predictions increased the cross-validated accuracy to 91.9%. Machine learning methods are a viable approach for automating measurement of active travel, particularly for measuring travel activities that traditional accelerometer data processing methods misclassify, such as bicycling and vehicle travel.

Development of a multi-biomarker disease activity test for rheumatoid arthritis.

PubMed

Centola, Michael; Cavet, Guy; Shen, Yijing; Ramanujan, Saroja; Knowlton, Nicholas; Swan, Kathryn A; Turner, Mary; Sutton, Chris; Smith, Dustin R; Haney, Douglas J; Chernoff, David; Hesterberg, Lyndal K; Carulli, John P; Taylor, Peter C; Shadick, Nancy A; Weinblatt, Michael E; Curtis, Jeffrey R

2013-01-01

Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities. We followed a stepwise approach to

Improving the performance of active-optical reflectance sensor algorithms using soil and weather information

USDA-ARS?s Scientific Manuscript database

Active-optical reflectance sensors (AORS) use corn (Zea mays L.) plant tissue as a bioassay of crop N status to determine future N requirements. However, studies have shown AORS algorithms used for making N fertilizer recommendations are not consistently accurate. Thus, AORS algorithm improvements s...

The design and development of signal-processing algorithms for an airborne x-band Doppler weather radar

NASA Technical Reports Server (NTRS)

Nicholson, Shaun R.

1994-01-01

Improved measurements of precipitation will aid our understanding of the role of latent heating on global circulations. Spaceborne meteorological sensors such as the planned precipitation radar and microwave radiometers on the Tropical Rainfall Measurement Mission (TRMM) provide for the first time a comprehensive means of making these global measurements. Pre-TRMM activities include development of precipitation algorithms using existing satellite data, computer simulations, and measurements from limited aircraft campaigns. Since the TRMM radar will be the first spaceborne precipitation radar, there is limited experience with such measurements, and only recently have airborne radars become available that can attempt to address the issue of the limitations of a spaceborne radar. There are many questions regarding how much attenuation occurs in various cloud types and the effect of cloud vertical motions on the estimation of precipitation rates. The EDOP program being developed by NASA GSFC will provide data useful for testing both rain-retrieval algorithms and the importance of vertical motions on the rain measurements. The purpose of this report is to describe the design and development of real-time embedded parallel algorithms used by EDOP to extract reflectivity and Doppler products (velocity, spectrum width, and signal-to-noise ratio) as the first step in the aforementioned goals.

Development of an Algorithm for Satellite Remote Sensing of Sea and Lake Ice

NASA Astrophysics Data System (ADS)

Dorofy, Peter T.

Satellite remote sensing of snow and ice has a long history. The traditional method for many snow and ice detection algorithms has been the use of the Normalized Difference Snow Index (NDSI). This manuscript is composed of two parts. Chapter 1, Development of a Mid-Infrared Sea and Lake Ice Index (MISI) using the GOES Imager, discusses the desirability, development, and implementation of alternative index for an ice detection algorithm, application of the algorithm to the detection of lake ice, and qualitative validation against other ice mapping products; such as, the Ice Mapping System (IMS). Chapter 2, Application of Dynamic Threshold in a Lake Ice Detection Algorithm, continues with a discussion of the development of a method that considers the variable viewing and illumination geometry of observations throughout the day. The method is an alternative to Bidirectional Reflectance Distribution Function (BRDF) models. Evaluation of the performance of the algorithm is introduced by aggregating classified pixels within geometrical boundaries designated by IMS and obtaining sensitivity and specificity statistical measures.

A semi-active suspension control algorithm for vehicle comprehensive vertical dynamics performance

NASA Astrophysics Data System (ADS)

Nie, Shida; Zhuang, Ye; Liu, Weiping; Chen, Fan

2017-08-01

Comprehensive performance of the vehicle, including ride qualities and road-holding, is essentially of great value in practice. Many up-to-date semi-active control algorithms improve vehicle dynamics performance effectively. However, it is hard to improve comprehensive performance for the conflict between ride qualities and road-holding around the second-order resonance. Hence, a new control algorithm is proposed to achieve a good trade-off between ride qualities and road-holding. In this paper, the properties of the invariant points are analysed, which gives an insight into the performance conflicting around the second-order resonance. Based on it, a new control algorithm is proposed. The algorithm employs a novel frequency selector to balance suspension ride and handling performance by adopting a medium damping around the second-order resonance. The results of this study show that the proposed control algorithm could improve the performance of ride qualities and suspension working space up to 18.3% and 8.2%, respectively, with little loss of road-holding compared to the passive suspension. Consequently, the comprehensive performance can be improved by 6.6%. Hence, the proposed algorithm is of great potential to be implemented in practice.

Multi-objective decoupling algorithm for active distance control of intelligent hybrid electric vehicle

NASA Astrophysics Data System (ADS)

Luo, Yugong; Chen, Tao; Li, Keqiang

2015-12-01

The paper presents a novel active distance control strategy for intelligent hybrid electric vehicles (IHEV) with the purpose of guaranteeing an optimal performance in view of the driving functions, optimum safety, fuel economy and ride comfort. Considering the complexity of driving situations, the objects of safety and ride comfort are decoupled from that of fuel economy, and a hierarchical control architecture is adopted to improve the real-time performance and the adaptability. The hierarchical control structure consists of four layers: active distance control object determination, comprehensive driving and braking torque calculation, comprehensive torque distribution and torque coordination. The safety distance control and the emergency stop algorithms are designed to achieve the safety and ride comfort goals. The optimal rule-based energy management algorithm of the hybrid electric system is developed to improve the fuel economy. The torque coordination control strategy is proposed to regulate engine torque, motor torque and hydraulic braking torque to improve the ride comfort. This strategy is verified by simulation and experiment using a forward simulation platform and a prototype vehicle. The results show that the novel control strategy can achieve the integrated and coordinated control of its multiple subsystems, which guarantees top performance of the driving functions and optimum safety, fuel economy and ride comfort.

Development of microwave rainfall retrieval algorithm for climate applications

NASA Astrophysics Data System (ADS)

KIM, J. H.; Shin, D. B.

2014-12-01

With the accumulated satellite datasets for decades, it is possible that satellite-based data could contribute to sustained climate applications. Level-3 products from microwave sensors for climate applications can be obtained from several algorithms. For examples, the Microwave Emission brightness Temperature Histogram (METH) algorithm produces level-3 rainfalls directly, whereas the Goddard profiling (GPROF) algorithm first generates instantaneous rainfalls and then temporal and spatial averaging process leads to level-3 products. The rainfall algorithm developed in this study follows a similar approach to averaging instantaneous rainfalls. However, the algorithm is designed to produce instantaneous rainfalls at an optimal resolution showing reduced non-linearity in brightness temperature (TB)-rain rate(R) relations. It is found that the resolution tends to effectively utilize emission channels whose footprints are relatively larger than those of scattering channels. This algorithm is mainly composed of a-priori databases (DBs) and a Bayesian inversion module. The DB contains massive pairs of simulated microwave TBs and rain rates, obtained by WRF (version 3.4) and RTTOV (version 11.1) simulations. To improve the accuracy and efficiency of retrieval process, data mining technique is additionally considered. The entire DB is classified into eight types based on Köppen climate classification criteria using reanalysis data. Among these sub-DBs, only one sub-DB which presents the most similar physical characteristics is selected by considering the thermodynamics of input data. When the Bayesian inversion is applied to the selected DB, instantaneous rain rate with 6 hours interval is retrieved. The retrieved monthly mean rainfalls are statistically compared with CMAP and GPCP, respectively.

Preliminary Development and Evaluation of Lightning Jump Algorithms for the Real-Time Detection of Severe Weather

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Petersen, Walter A.; Carey, Lawrence D.

2009-01-01

Previous studies have demonstrated that rapid increases in total lightning activity (intracloud + cloud-to-ground) are often observed tens of minutes in advance of the occurrence of severe weather at the ground. These rapid increases in lightning activity have been termed "lightning jumps." Herein, we document a positive correlation between lightning jumps and the manifestation of severe weather in thunderstorms occurring across the Tennessee Valley and Washington D.C. A total of 107 thunderstorms were examined in this study, with 69 of the 107 thunderstorms falling into the category of non-severe, and 38 into the category of severe. From the dataset of 69 isolated non-severe thunderstorms, an average peak 1 minute flash rate of 10 flashes/min was determined. A variety of severe thunderstorm types were examined for this study including an MCS, MCV, tornadic outer rainbands of tropical remnants, supercells, and pulse severe thunderstorms. Of the 107 thunderstorms, 85 thunderstorms (47 non-severe, 38 severe) from the Tennessee Valley and Washington D.C tested 6 lightning jump algorithm configurations (Gatlin, Gatlin 45, 2(sigma), 3(sigma), Threshold 10, and Threshold 8). Performance metrics for each algorithm were then calculated, yielding encouraging results from the limited sample of 85 thunderstorms. The 2(sigma) lightning jump algorithm had a high probability of detection (POD; 87%), a modest false alarm rate (FAR; 33%), and a solid Heidke Skill Score (HSS; 0.75). A second and more simplistic lightning jump algorithm named the Threshold 8 lightning jump algorithm also shows promise, with a POD of 81% and a FAR of 41%. Average lead times to severe weather occurrence for these two algorithms were 23 minutes and 20 minutes, respectively. The overall goal of this study is to advance the development of an operationally-applicable jump algorithm that can be used with either total lightning observations made from the ground, or in the near future from space using the

Texas Medication Algorithm Project: development and feasibility testing of a treatment algorithm for patients with bipolar disorder.

PubMed

Suppes, T; Swann, A C; Dennehy, E B; Habermacher, E D; Mason, M; Crismon, M L; Toprac, M G; Rush, A J; Shon, S P; Altshuler, K Z

2001-06-01

Use of treatment guidelines for treatment of major psychiatric illnesses has increased in recent years. The Texas Medication Algorithm Project (TMAP) was developed to study the feasibility and process of developing and implementing guidelines for bipolar disorder, major depressive disorder, and schizophrenia in the public mental health system of Texas. This article describes the consensus process used to develop the first set of TMAP algorithms for the Bipolar Disorder Module (Phase 1) and the trial testing the feasibility of their implementation in inpatient and outpatient psychiatric settings across Texas (Phase 2). The feasibility trial answered core questions regarding implementation of treatment guidelines for bipolar disorder. A total of 69 patients were treated with the original algorithms for bipolar disorder developed in Phase 1 of TMAP. Results support that physicians accepted the guidelines, followed recommendations to see patients at certain intervals, and utilized sequenced treatment steps differentially over the course of treatment. While improvements in clinical symptoms (24-item Brief Psychiatric Rating Scale) were observed over the course of enrollment in the trial, these conclusions are limited by the fact that physician volunteers were utilized for both treatment and ratings. and there was no control group. Results from Phases 1 and 2 indicate that it is possible to develop and implement a treatment guideline for patients with a history of mania in public mental health clinics in Texas. TMAP Phase 3, a recently completed larger and controlled trial assessing the clinical and economic impact of treatment guidelines and patient and family education in the public mental health system of Texas, improves upon this methodology.

Distilling the Verification Process for Prognostics Algorithms

NASA Technical Reports Server (NTRS)

Roychoudhury, Indranil; Saxena, Abhinav; Celaya, Jose R.; Goebel, Kai

2013-01-01

The goal of prognostics and health management (PHM) systems is to ensure system safety, and reduce downtime and maintenance costs. It is important that a PHM system is verified and validated before it can be successfully deployed. Prognostics algorithms are integral parts of PHM systems. This paper investigates a systematic process of verification of such prognostics algorithms. To this end, first, this paper distinguishes between technology maturation and product development. Then, the paper describes the verification process for a prognostics algorithm as it moves up to higher maturity levels. This process is shown to be an iterative process where verification activities are interleaved with validation activities at each maturation level. In this work, we adopt the concept of technology readiness levels (TRLs) to represent the different maturity levels of a prognostics algorithm. It is shown that at each TRL, the verification of a prognostics algorithm depends on verifying the different components of the algorithm according to the requirements laid out by the PHM system that adopts this prognostics algorithm. Finally, using simplified examples, the systematic process for verifying a prognostics algorithm is demonstrated as the prognostics algorithm moves up TRLs.

Crowdsourcing seizure detection: algorithm development and validation on human implanted device recordings.

PubMed

Baldassano, Steven N; Brinkmann, Benjamin H; Ung, Hoameng; Blevins, Tyler; Conrad, Erin C; Leyde, Kent; Cook, Mark J; Khambhati, Ankit N; Wagenaar, Joost B; Worrell, Gregory A; Litt, Brian

2017-06-01

There exist significant clinical and basic research needs for accurate, automated seizure detection algorithms. These algorithms have translational potential in responsive neurostimulation devices and in automatic parsing of continuous intracranial electroencephalography data. An important barrier to developing accurate, validated algorithms for seizure detection is limited access to high-quality, expertly annotated seizure data from prolonged recordings. To overcome this, we hosted a kaggle.com competition to crowdsource the development of seizure detection algorithms using intracranial electroencephalography from canines and humans with epilepsy. The top three performing algorithms from the contest were then validated on out-of-sample patient data including standard clinical data and continuous ambulatory human data obtained over several years using the implantable NeuroVista seizure advisory system. Two hundred teams of data scientists from all over the world participated in the kaggle.com competition. The top performing teams submitted highly accurate algorithms with consistent performance in the out-of-sample validation study. The performance of these seizure detection algorithms, achieved using freely available code and data, sets a new reproducible benchmark for personalized seizure detection. We have also shared a 'plug and play' pipeline to allow other researchers to easily use these algorithms on their own datasets. The success of this competition demonstrates how sharing code and high quality data results in the creation of powerful translational tools with significant potential to impact patient care. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Identifying Active Travel Behaviors in Challenging Environments Using GPS, Accelerometers, and Machine Learning Algorithms

PubMed Central

Ellis, Katherine; Godbole, Suneeta; Marshall, Simon; Lanckriet, Gert; Staudenmayer, John; Kerr, Jacqueline

2014-01-01

Background: Active travel is an important area in physical activity research, but objective measurement of active travel is still difficult. Automated methods to measure travel behaviors will improve research in this area. In this paper, we present a supervised machine learning method for transportation mode prediction from global positioning system (GPS) and accelerometer data. Methods: We collected a dataset of about 150 h of GPS and accelerometer data from two research assistants following a protocol of prescribed trips consisting of five activities: bicycling, riding in a vehicle, walking, sitting, and standing. We extracted 49 features from 1-min windows of this data. We compared the performance of several machine learning algorithms and chose a random forest algorithm to classify the transportation mode. We used a moving average output filter to smooth the output predictions over time. Results: The random forest algorithm achieved 89.8% cross-validated accuracy on this dataset. Adding the moving average filter to smooth output predictions increased the cross-validated accuracy to 91.9%. Conclusion: Machine learning methods are a viable approach for automating measurement of active travel, particularly for measuring travel activities that traditional accelerometer data processing methods misclassify, such as bicycling and vehicle travel. PMID:24795875

Hypersonic Vehicle Propulsion System Control Model Development Roadmap and Activities

NASA Technical Reports Server (NTRS)

Stueber, Thomas J.; Le, Dzu K.; Vrnak, Daniel R.

2009-01-01

The NASA Fundamental Aeronautics Program Hypersonic project is directed towards fundamental research for two classes of hypersonic vehicles: highly reliable reusable launch systems (HRRLS) and high-mass Mars entry systems (HMMES). The objective of the hypersonic guidance, navigation, and control (GN&C) discipline team is to develop advanced guidance and control algorithms to enable efficient and effective operation of these challenging vehicles. The ongoing work at the NASA Glenn Research Center supports the hypersonic GN&C effort in developing tools to aid the design of advanced control algorithms that specifically address the propulsion system of the HRRLSclass vehicles. These tools are being developed in conjunction with complementary research and development activities in hypersonic propulsion at Glenn and elsewhere. This report is focused on obtaining control-relevant dynamic models of an HRRLS-type hypersonic vehicle propulsion system.

Algorithm integration using ADL (Algorithm Development Library) for improving CrIMSS EDR science product quality

NASA Astrophysics Data System (ADS)

Das, B.; Wilson, M.; Divakarla, M. G.; Chen, W.; Barnet, C.; Wolf, W.

2013-05-01

Algorithm Development Library (ADL) is a framework that mimics the operational system IDPS (Interface Data Processing Segment) that is currently being used to process data from instruments aboard Suomi National Polar-orbiting Partnership (S-NPP) satellite. The satellite was launched successfully in October 2011. The Cross-track Infrared and Microwave Sounder Suite (CrIMSS) consists of the Advanced Technology Microwave Sounder (ATMS) and Cross-track Infrared Sounder (CrIS) instruments that are on-board of S-NPP. These instruments will also be on-board of JPSS (Joint Polar Satellite System) that will be launched in early 2017. The primary products of the CrIMSS Environmental Data Record (EDR) include global atmospheric vertical temperature, moisture, and pressure profiles (AVTP, AVMP and AVPP) and Ozone IP (Intermediate Product from CrIS radiances). Several algorithm updates have recently been proposed by CrIMSS scientists that include fixes to the handling of forward modeling errors, a more conservative identification of clear scenes, indexing corrections for daytime products, and relaxed constraints between surface temperature and air temperature for daytime land scenes. We have integrated these improvements into the ADL framework. This work compares the results from ADL emulation of future IDPS system incorporating all the suggested algorithm updates with the current official processing results by qualitative and quantitative evaluations. The results prove these algorithm updates improve science product quality.

A novel fair active queue management algorithm based on traffic delay jitter

NASA Astrophysics Data System (ADS)

Wang, Xue-Shun; Yu, Shao-Hua; Dai, Jin-You; Luo, Ting

2009-11-01

In order to guarantee the quantity of data traffic delivered in the network, congestion control strategy is adopted. According to the study of many active queue management (AQM) algorithms, this paper proposes a novel active queue management algorithm named JFED. JFED can stabilize queue length at a desirable level by adjusting output traffic rate and adopting a reasonable calculation of packet drop probability based on buffer queue length and traffic jitter; and it support burst packet traffic through the packet delay jitter, so that it can traffic flow medium data. JFED impose effective punishment upon non-responsible flow with a full stateless method. To verify the performance of JFED, it is implemented in NS2 and is compared with RED and CHOKe with respect to different performance metrics. Simulation results show that the proposed JFED algorithm outperforms RED and CHOKe in stabilizing instantaneous queue length and in fairness. It is also shown that JFED enables the link capacity to be fully utilized by stabilizing the queue length at a desirable level, while not incurring excessive packet loss ratio.

Performance improvement of an active vibration absorber subsystem for an aircraft model using a bees algorithm based on multi-objective intelligent optimization

NASA Astrophysics Data System (ADS)

Zarchi, Milad; Attaran, Behrooz

2017-11-01

This study develops a mathematical model to investigate the behaviour of adaptable shock absorber dynamics for the six-degree-of-freedom aircraft model in the taxiing phase. The purpose of this research is to design a proportional-integral-derivative technique for control of an active vibration absorber system using a hydraulic nonlinear actuator based on the bees algorithm. This optimization algorithm is inspired by the natural intelligent foraging behaviour of honey bees. The neighbourhood search strategy is used to find better solutions around the previous one. The parameters of the controller are adjusted by minimizing the aircraft's acceleration and impact force as the multi-objective function. The major advantages of this algorithm over other optimization algorithms are its simplicity, flexibility and robustness. The results of the numerical simulation indicate that the active suspension increases the comfort of the ride for passengers and the fatigue life of the structure. This is achieved by decreasing the impact force, displacement and acceleration significantly.

A new cross-correlation algorithm for the analysis of "in vitro" neuronal network activity aimed at pharmacological studies.

PubMed

Biffi, E; Menegon, A; Regalia, G; Maida, S; Ferrigno, G; Pedrocchi, A

2011-08-15

Modern drug discovery for Central Nervous System pathologies has recently focused its attention to in vitro neuronal networks as models for the study of neuronal activities. Micro Electrode Arrays (MEAs), a widely recognized tool for pharmacological investigations, enable the simultaneous study of the spiking activity of discrete regions of a neuronal culture, providing an insight into the dynamics of networks. Taking advantage of MEAs features and making the most of the cross-correlation analysis to assess internal parameters of a neuronal system, we provide an efficient method for the evaluation of comprehensive neuronal network activity. We developed an intra network burst correlation algorithm, we evaluated its sensitivity and we explored its potential use in pharmacological studies. Our results demonstrate the high sensitivity of this algorithm and the efficacy of this methodology in pharmacological dose-response studies, with the advantage of analyzing the effect of drugs on the comprehensive correlative properties of integrated neuronal networks. Copyright © 2011 Elsevier B.V. All rights reserved.

A novel algorithm for detecting active propulsion in wheelchair users following spinal cord injury.

PubMed

Popp, Werner L; Brogioli, Michael; Leuenberger, Kaspar; Albisser, Urs; Frotzler, Angela; Curt, Armin; Gassert, Roger; Starkey, Michelle L

2016-03-01

Physical activity in wheelchair-bound individuals can be assessed by monitoring their mobility as this is one of the most intense upper extremity activities they perform. Current accelerometer-based approaches for describing wheelchair mobility do not distinguish between self- and attendant-propulsion and hence may overestimate total physical activity. The aim of this study was to develop and validate an inertial measurement unit based algorithm to monitor wheel kinematics and the type of wheelchair propulsion (self- or attendant-) within a "real-world" situation. Different sensor set-ups were investigated, ranging from a high precision set-up including four sensor modules with a relatively short measurement duration of 24 h, to a less precise set-up with only one module attached at the wheel exceeding one week of measurement because the gyroscope of the sensor was turned off. The "high-precision" algorithm distinguished self- and attendant-propulsion with accuracy greater than 93% whilst the long-term measurement set-up showed an accuracy of 82%. The estimation accuracy of kinematic parameters was greater than 97% for both set-ups. The possibility of having different sensor set-ups allows the use of the inertial measurement units as high precision tools for researchers as well as unobtrusive and simple tools for manual wheelchair users. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Off-the-shelf mobile handset environments for deploying accelerometer based gait and activity analysis algorithms.

PubMed

Hynes, Martin; Wang, Han; Kilmartin, Liam

2009-01-01

Over the last decade, there has been substantial research interest in the application of accelerometry data for many forms of automated gait and activity analysis algorithms. This paper introduces a summary of new "of-the-shelf" mobile phone handset platforms containing embedded accelerometers which support the development of custom software to implement real time analysis of the accelerometer data. An overview of the main software programming environments which support the development of such software, including Java ME based JSR 256 API, C++ based Motion Sensor API and the Python based "aXYZ" module, is provided. Finally, a sample application is introduced and its performance evaluated in order to illustrate how a standard mobile phone can be used to detect gait activity using such a non-intrusive and easily accepted sensing platform.

A comparison of two adaptive algorithms for the control of active engine mounts

NASA Astrophysics Data System (ADS)

Hillis, A. J.; Harrison, A. J. L.; Stoten, D. P.

2005-08-01

This paper describes work conducted in order to control automotive active engine mounts, consisting of a conventional passive mount and an internal electromagnetic actuator. Active engine mounts seek to cancel the oscillatory forces generated by the rotation of out-of-balance masses within the engine. The actuator generates a force dependent on a control signal from an algorithm implemented with a real-time DSP. The filtered-x least-mean-square (FXLMS) adaptive filter is used as a benchmark for comparison with a new implementation of the error-driven minimal controller synthesis (Er-MCSI) adaptive controller. Both algorithms are applied to an active mount fitted to a saloon car equipped with a four-cylinder turbo-diesel engine, and have no a priori knowledge of the system dynamics. The steady-state and transient performance of the two algorithms are compared and the relative merits of the two approaches are discussed. The Er-MCSI strategy offers significant computational advantages as it requires no cancellation path modelling. The Er-MCSI controller is found to perform in a fashion similar to the FXLMS filter—typically reducing chassis vibration by 50-90% under normal driving conditions.

Development of sensor-based nitrogen recommendation algorithms for cereal crops

NASA Astrophysics Data System (ADS)

Asebedo, Antonio Ray

Nitrogen (N) management is one of the most recognizable components of farming both within and outside the world of agriculture. Interest over the past decade has greatly increased in improving N management systems in corn (Zea mays) and winter wheat (Triticum aestivum ) to have high NUE, high yield, and be environmentally sustainable. Nine winter wheat experiments were conducted across seven locations from 2011 through 2013. The objectives of this study were to evaluate the impacts of fall-winter, Feekes 4, Feekes 7, and Feekes 9 N applications on winter wheat grain yield, grain protein, and total grain N uptake. Nitrogen treatments were applied as single or split applications in the fall-winter, and top-dressed in the spring at Feekes 4, Feekes 7, and Feekes 9 with applied N rates ranging from 0 to 134 kg ha-1. Results indicate that Feekes 7 and 9 N applications provide more optimal combinations of grain yield, grain protein levels, and fertilizer N recovered in the grain when compared to comparable rates of N applied in the fall-winter or at Feekes 4. Winter wheat N management studies from 2006 through 2013 were utilized to develop sensor-based N recommendation algorithms for winter wheat in Kansas. Algorithm RosieKat v.2.6 was designed for multiple N application strategies and utilized N reference strips for establishing N response potential. Algorithm NRS v1.5 addressed single top-dress N applications and does not require a N reference strip. In 2013, field validations of both algorithms were conducted at eight locations across Kansas. Results show algorithm RK v2.6 consistently provided highly efficient N recommendations for improving NUE, while achieving high grain yield and grain protein. Without the use of the N reference strip, NRS v1.5 performed statistically equal to the KSU soil test N recommendation in regards to grain yield but with lower applied N rates. Six corn N fertigation experiments were conducted at KSU irrigated experiment fields from 2012

Algorithm for evaluating the effectiveness of a high-rise development project based on current yield

NASA Astrophysics Data System (ADS)

Soboleva, Elena

2018-03-01

The article is aimed at the issues of operational evaluation of development project efficiency in high-rise construction under the current economic conditions in Russia. The author touches the following issues: problems of implementing development projects, the influence of the operational evaluation quality of high-rise construction projects on general efficiency, assessing the influence of the project's external environment on the effectiveness of project activities under crisis conditions and the quality of project management. The article proposes the algorithm and the methodological approach to the quality management of the developer project efficiency based on operational evaluation of the current yield efficiency. The methodology for calculating the current efficiency of a development project for high-rise construction has been updated.

Recent Progress in Development of SWOT River Discharge Algorithms

NASA Astrophysics Data System (ADS)

Pavelsky, Tamlin M.; Andreadis, Konstantinos; Biancamaria, Sylvian; Durand, Michael; Moller, Dewlyn; Rodriguez, Enersto; Smith, Laurence C.

2013-09-01

The Surface Water and Ocean Topography (SWOT) Mission is a satellite mission under joint development by NASA and CNES. The mission will use interferometric synthetic aperture radar technology to continuously map, for the first time, water surface elevations and water surface extents in rivers, lakes, and oceans at high spatial resolutions. Among the primary goals of SWOT is the accurate retrieval of river discharge directly from SWOT measurements. Although it is central to the SWOT mission, discharge retrieval represents a substantial challenge due to uncertainties in SWOT measurements and because traditional discharge algorithms are not optimized for SWOT-like measurements. However, recent work suggests that SWOT may also have unique strengths that can be exploited to yield accurate estimates of discharge. A NASA-sponsored workshop convened June 18-20, 2012 at the University of North Carolina focused on progress and challenges in developing SWOT-specific discharge algorithms. Workshop participants agreed that the only viable approach to discharge estimation will be based on a slope-area scaling method such as Manning's equation, but modified slightly to reflect the fact that SWOT will estimate reach-averaged rather than cross- sectional discharge. While SWOT will provide direct measurements of some key parameters such as width and slope, others such as baseflow depth and channel roughness must be estimated. Fortunately, recent progress has suggested several algorithms that may allow the simultaneous estimation of these quantities from SWOT observations by using multitemporal observations over several adjacent reaches. However, these algorithms will require validation, which will require the collection of new field measurements, airborne imagery from AirSWOT (a SWOT analogue), and compilation of global datasets of channel roughness, river width, and other relevant variables.

Optimal Parameter Exploration for Online Change-Point Detection in Activity Monitoring Using Genetic Algorithms

PubMed Central

Khan, Naveed; McClean, Sally; Zhang, Shuai; Nugent, Chris

2016-01-01

In recent years, smart phones with inbuilt sensors have become popular devices to facilitate activity recognition. The sensors capture a large amount of data, containing meaningful events, in a short period of time. The change points in this data are used to specify transitions to distinct events and can be used in various scenarios such as identifying change in a patient’s vital signs in the medical domain or requesting activity labels for generating real-world labeled activity datasets. Our work focuses on change-point detection to identify a transition from one activity to another. Within this paper, we extend our previous work on multivariate exponentially weighted moving average (MEWMA) algorithm by using a genetic algorithm (GA) to identify the optimal set of parameters for online change-point detection. The proposed technique finds the maximum accuracy and F_measure by optimizing the different parameters of the MEWMA, which subsequently identifies the exact location of the change point from an existing activity to a new one. Optimal parameter selection facilitates an algorithm to detect accurate change points and minimize false alarms. Results have been evaluated based on two real datasets of accelerometer data collected from a set of different activities from two users, with a high degree of accuracy from 99.4% to 99.8% and F_measure of up to 66.7%. PMID:27792177

Development of antibiotic regimens using graph based evolutionary algorithms.

PubMed

Corns, Steven M; Ashlock, Daniel A; Bryden, Kenneth M

2013-12-01

This paper examines the use of evolutionary algorithms in the development of antibiotic regimens given to production animals. A model is constructed that combines the lifespan of the animal and the bacteria living in the animal's gastro-intestinal tract from the early finishing stage until the animal reaches market weight. This model is used as the fitness evaluation for a set of graph based evolutionary algorithms to assess the impact of diversity control on the evolving antibiotic regimens. The graph based evolutionary algorithms have two objectives: to find an antibiotic treatment regimen that maintains the weight gain and health benefits of antibiotic use and to reduce the risk of spreading antibiotic resistant bacteria. This study examines different regimens of tylosin phosphate use on bacteria populations divided into Gram positive and Gram negative types, with a focus on Campylobacter spp. Treatment regimens were found that provided decreased antibiotic resistance relative to conventional methods while providing nearly the same benefits as conventional antibiotic regimes. By using a graph to control the information flow in the evolutionary algorithm, a variety of solutions along the Pareto front can be found automatically for this and other multi-objective problems. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Development of a Multi-Biomarker Disease Activity Test for Rheumatoid Arthritis

PubMed Central

Shen, Yijing; Ramanujan, Saroja; Knowlton, Nicholas; Swan, Kathryn A.; Turner, Mary; Sutton, Chris; Smith, Dustin R.; Haney, Douglas J.; Chernoff, David; Hesterberg, Lyndal K.; Carulli, John P.; Taylor, Peter C.; Shadick, Nancy A.; Weinblatt, Michael E.; Curtis, Jeffrey R.

2013-01-01

Background Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. Objectives To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. Methods Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. Results 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities

Soil Moisture Active Passive (SMAP) Project Algorithm Theoretical Basis Document SMAP L1B Radiometer Data Product: L1B_TB

NASA Technical Reports Server (NTRS)

Piepmeier, Jeffrey; Mohammed, Priscilla; De Amici, Giovanni; Kim, Edward; Peng, Jinzheng; Ruf, Christopher; Hanna, Maher; Yueh, Simon; Entekhabi, Dara

2016-01-01

The purpose of the Soil Moisture Active Passive (SMAP) radiometer calibration algorithm is to convert Level 0 (L0) radiometer digital counts data into calibrated estimates of brightness temperatures referenced to the Earth's surface within the main beam. The algorithm theory in most respects is similar to what has been developed and implemented for decades for other satellite radiometers; however, SMAP includes two key features heretofore absent from most satellite borne radiometers: radio frequency interference (RFI) detection and mitigation, and measurement of the third and fourth Stokes parameters using digital correlation. The purpose of this document is to describe the SMAP radiometer and forward model, explain the SMAP calibration algorithm, including approximations, errors, and biases, provide all necessary equations for implementing the calibration algorithm and detail the RFI detection and mitigation process. Section 2 provides a summary of algorithm objectives and driving requirements. Section 3 is a description of the instrument and Section 4 covers the forward models, upon which the algorithm is based. Section 5 gives the retrieval algorithm and theory. Section 6 describes the orbit simulator, which implements the forward model and is the key for deriving antenna pattern correction coefficients and testing the overall algorithm.

The NASA Soil Moisture Active Passive (SMAP) Mission - Algorithm and Cal/Val Activities and Synergies with SMOS and Other L-Band Missions

NASA Technical Reports Server (NTRS)

Njoku, Eni; Entekhabi, Dara; O'Neill, Peggy; Jackson, Tom; Kellogg, Kent; Entin, Jared

2011-01-01

applicable to soil moisture measurement, such as Aquarius, SAO COM, and ALOS-2. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. The algorithms are developed and evaluated in the SDS Testbed using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including SMOS. The SMAP project is developing a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). A key component of the Cal/Val Plan is the identification, characterization, and instrumentation of sites that can be used to calibrate and validate the sensor data (Level I) and derived geophysical products (Level 2 and higher). In this presentation we report on the development status of the SMAP data product algorithms, and the planning and implementation of the SMAP Cal/Val program. Several components of the SMAP algorithm development and Cal/Val plans have commonality with those of SMOS, and for this reason there are shared activities and resources that can be utilized between the missions, including in situ networks, ancillary data sets, and long-term monitoring sites.

Longitudinal wearable tremor measurement system with activity recognition algorithms for upper limb tremor.

PubMed

Jeonghee Kim; Parnell, Claire; Wichmann, Thomas; DeWeerth, Stephen P

2016-08-01

Assessments of tremor characteristics by movement disorder physicians are usually done at single time points in clinic settings, so that the description of the tremor does not take into account the dependence of the tremor on specific behavioral situations. Moreover, treatment-induced changes in tremor or behavior cannot be quantitatively tracked for extended periods of time. We developed a wearable tremor measurement system with tremor and activity recognition algorithms for long-term upper limb behavior tracking, to characterize tremor characteristics and treatment effects in their daily lives. In this pilot study, we collected sensor data of arm movement from three healthy participants using a wrist device that included a 3-axis accelerometer and a 3-axis gyroscope, and classified tremor and activities within scenario tasks which resembled real life situations. Our results show that the system was able to classify the tremor and activities with 89.71% and 74.48% accuracies during the scenario tasks. From this results, we expect to expand our tremor and activity measurement in longer time period.

Ocean Observations with EOS/MODIS: Algorithm Development and Post Launch Studies

NASA Technical Reports Server (NTRS)

Gordon, Howard R.

1997-01-01

Significant accomplishments made during the present reporting period are as follows: (1) We developed a new method for identifying the presence of absorbing aerosols and, simultaneously, performing atmospheric correction. The algorithm consists of optimizing the match between the top-of-atmosphere radiance spectrum and the result of models of both the ocean and aerosol optical properties; (2) We developed an algorithm for providing an accurate computation of the diffuse transmittance of the atmosphere given an aerosol model. A module for inclusion into the MODIS atmospheric-correction algorithm was completed; (3) We acquired reflectance data for oceanic whitecaps during a cruise on the RV Ka'imimoana in the Tropical Pacific (Manzanillo, Mexico to Honolulu, Hawaii). The reflectance spectrum of whitecaps was found to be similar to that for breaking waves in the surf zone measured by Frouin, Schwindling and Deschamps, however, the drop in augmented reflectance from 670 to 860 nm was not as great, and the magnitude of the augmented reflectance was significantly less than expected; and (4) We developed a method for the approximate correction for the effects of the MODIS polarization sensitivity. The correction, however, requires adequate characterization of the polarization sensitivity of MODIS prior to launch.

Model and algorithmic framework for detection and correction of cognitive errors.

PubMed

Feki, Mohamed Ali; Biswas, Jit; Tolstikov, Andrei

2009-01-01

This paper outlines an approach that we are taking for elder-care applications in the smart home, involving cognitive errors and their compensation. Our approach involves high level modeling of daily activities of the elderly by breaking down these activities into smaller units, which can then be automatically recognized at a low level by collections of sensors placed in the homes of the elderly. This separation allows us to employ plan recognition algorithms and systems at a high level, while developing stand-alone activity recognition algorithms and systems at a low level. It also allows the mixing and matching of multi-modality sensors of various kinds that go to support the same high level requirement. Currently our plan recognition algorithms are still at a conceptual stage, whereas a number of low level activity recognition algorithms and systems have been developed. Herein we present our model for plan recognition, providing a brief survey of the background literature. We also present some concrete results that we have achieved for activity recognition, emphasizing how these results are incorporated into the overall plan recognition system.

The Texas Medication Algorithm Project (TMAP) schizophrenia algorithms.

PubMed

Miller, A L; Chiles, J A; Chiles, J K; Crismon, M L; Rush, A J; Shon, S P

1999-10-01

In the Texas Medication Algorithm Project (TMAP), detailed guidelines for medication management of schizophrenia and related disorders, bipolar disorders, and major depressive disorders have been developed and implemented. This article describes the algorithms developed for medication treatment of schizophrenia and related disorders. The guidelines recommend a sequence of medications and discuss dosing, duration, and switch-over tactics. They also specify response criteria at each stage of the algorithm for both positive and negative symptoms. The rationale and evidence for each aspect of the algorithms are presented.

Development of PET projection data correction algorithm

NASA Astrophysics Data System (ADS)

Bazhanov, P. V.; Kotina, E. D.

2017-12-01

Positron emission tomography is modern nuclear medicine method used in metabolism and internals functions examinations. This method allows to diagnosticate treatments on their early stages. Mathematical algorithms are widely used not only for images reconstruction but also for PET data correction. In this paper random coincidences and scatter correction algorithms implementation are considered, as well as algorithm of PET projection data acquisition modeling for corrections verification.

Data inversion algorithm development for the hologen occultation experiment

NASA Technical Reports Server (NTRS)

Gordley, Larry L.; Mlynczak, Martin G.

1986-01-01

The successful retrieval of atmospheric parameters from radiometric measurement requires not only the ability to do ideal radiometric calculations, but also a detailed understanding of instrument characteristics. Therefore a considerable amount of time was spent in instrument characterization in the form of test data analysis and mathematical formulation. Analyses of solar-to-reference interference (electrical cross-talk), detector nonuniformity, instrument balance error, electronic filter time-constants and noise character were conducted. A second area of effort was the development of techniques for the ideal radiometric calculations required for the Halogen Occultation Experiment (HALOE) data reduction. The computer code for these calculations must be extremely complex and fast. A scheme for meeting these requirements was defined and the algorithms needed form implementation are currently under development. A third area of work included consulting on the implementation of the Emissivity Growth Approximation (EGA) method of absorption calculation into a HALOE broadband radiometer channel retrieval algorithm.

Bringing Algorithms to Life: Cooperative Computing Activities Using Students as Processors.

ERIC Educational Resources Information Center

Bachelis, Gregory F.; And Others

1994-01-01

Presents cooperative computing activities in which each student plays the role of a switch or processor and acts out algorithms. Includes binary counting, finding the smallest card in a deck, sorting by selection and merging, adding and multiplying large numbers, and sieving for primes. (16 references) (Author/MKR)

Development and testing of operational incident detection algorithms : executive summary

DOT National Transportation Integrated Search

1997-09-01

This report describes the development of operational surveillance data processing algorithms and software for application to urban freeway systems, conforming to a framework in which data processing is performed in stages: sensor malfunction detectio...

Seismic design of passive tuned mass damper parameters using active control algorithm

NASA Astrophysics Data System (ADS)

Chang, Chia-Ming; Shia, Syuan; Lai, Yong-An

2018-07-01

Tuned mass dampers are a widely-accepted control method to effectively reduce the vibrations of tall buildings. A tuned mass damper employs a damped harmonic oscillator with specific dynamic characteristics, thus the response of structures can be regulated by the additive dynamics. The additive dynamics are, however, similar to the feedback control system in active control. Therefore, the objective of this study is to develop a new tuned mass damper design procedure based on the active control algorithm, i.e., the H2/LQG control. This design facilitates the similarity of feedback control in the active control algorithm to determine the spring and damper in a tuned mass damper. Given a mass ratio between the damper and structure, the stiffness and damping coefficient of the tuned mass damper are derived by minimizing the response objective function of the primary structure, where the structural properties are known. Varying a single weighting in this objective function yields the optimal TMD design when the minimum peak in the displacement transfer function of the structure with the TMD is met. This study examines various objective functions as well as derives the associated equations to compute the stiffness and damping coefficient. The relationship between the primary structure and optimal tuned mass damper is parametrically studied. Performance is evaluated by exploring the h2-and h∞-norms of displacements and accelerations of the primary structure. In time-domain analysis, the damping effectiveness of the tune mass damper controlled structures is investigated under impulse excitation. Structures with the optimal tuned mass dampers are also assessed under seismic excitation. As a result, the proposed design procedure produces an effective tuned mass damper to be employed in a structure against earthquakes.

Development and validation of a risk prediction algorithm for the recurrence of suicidal ideation among general population with low mood.

PubMed

Liu, Y; Sareen, J; Bolton, J M; Wang, J L

2016-03-15

Suicidal ideation is one of the strongest predictors of recent and future suicide attempt. This study aimed to develop and validate a risk prediction algorithm for the recurrence of suicidal ideation among population with low mood 3035 participants from U.S National Epidemiologic Survey on Alcohol and Related Conditions with suicidal ideation at their lowest mood at baseline were included. The Alcohol Use Disorder and Associated Disabilities Interview Schedule, based on the DSM-IV criteria was used. Logistic regression modeling was conducted to derive the algorithm. Discrimination and calibration were assessed in the development and validation cohorts. In the development data, the proportion of recurrent suicidal ideation over 3 years was 19.5 (95% CI: 17.7, 21.5). The developed algorithm consisted of 6 predictors: age, feelings of emptiness, sudden mood changes, self-harm history, depressed mood in the past 4 weeks, interference with social activities in the past 4 weeks because of physical health or emotional problems and emptiness was the most important risk factor. The model had good discriminative power (C statistic=0.8273, 95% CI: 0.8027, 0.8520). The C statistic was 0.8091 (95% CI: 0.7786, 0.8395) in the external validation dataset and was 0.8193 (95% CI: 0.8001, 0.8385) in the combined dataset. This study does not apply to people with suicidal ideation who are not depressed. The developed risk algorithm for predicting the recurrence of suicidal ideation has good discrimination and excellent calibration. Clinicians can use this algorithm to stratify the risk of recurrence in patients and thus improve personalized treatment approaches, make advice and further intensive monitoring. Copyright © 2016 Elsevier B.V. All rights reserved.

Development of a thresholding algorithm for calcium classification at multiple CT energies

NASA Astrophysics Data System (ADS)

Ng, LY.; Alssabbagh, M.; Tajuddin, A. A.; Shuaib, I. L.; Zainon, R.

2017-05-01

The objective of this study was to develop a thresholding method for calcium classification with different concentration using single-energy computed tomography. Five different concentrations of calcium chloride were filled in PMMA tubes and placed inside a water-filled PMMA phantom (diameter 10 cm). The phantom was scanned at 70, 80, 100, 120 and 140 kV using a SECT. CARE DOSE 4D was used and the slice thickness was set to 1 mm for all energies. ImageJ software inspired by the National Institute of Health (NIH) was used to measure the CT numbers for each calcium concentration from the CT images. The results were compared with a developed algorithm for verification. The percentage differences between the measured CT numbers obtained from the developed algorithm and the ImageJ show similar results. The multi-thresholding algorithm was found to be able to distinguish different concentrations of calcium chloride. However, it was unable to detect low concentrations of calcium chloride and iron (III) nitrate with CT numbers between 25 HU and 65 HU. The developed thresholding method used in this study may help to differentiate between calcium plaques and other types of plaques in blood vessels as it is proven to have a good ability to detect the high concentration of the calcium chloride. However, the algorithm needs to be improved to solve the limitations of detecting calcium chloride solution which has a similar CT number with iron (III) nitrate solution.

Correlation signatures of wet soils and snows. [algorithm development and computer programming

NASA Technical Reports Server (NTRS)

Phillips, M. R.

1972-01-01

Interpretation, analysis, and development of algorithms have provided the necessary computational programming tools for soil data processing, data handling and analysis. Algorithms that have been developed thus far, are adequate and have been proven successful for several preliminary and fundamental applications such as software interfacing capabilities, probability distributions, grey level print plotting, contour plotting, isometric data displays, joint probability distributions, boundary mapping, channel registration and ground scene classification. A description of an Earth Resources Flight Data Processor, (ERFDP), which handles and processes earth resources data under a users control is provided.

Integrated Graphics Operations and Analysis Lab Development of Advanced Computer Graphics Algorithms

NASA Technical Reports Server (NTRS)

Wheaton, Ira M.

2011-01-01

The focus of this project is to aid the IGOAL in researching and implementing algorithms for advanced computer graphics. First, this project focused on porting the current International Space Station (ISS) Xbox experience to the web. Previously, the ISS interior fly-around education and outreach experience only ran on an Xbox 360. One of the desires was to take this experience and make it into something that can be put on NASA s educational site for anyone to be able to access. The current code works in the Unity game engine which does have cross platform capability but is not 100% compatible. The tasks for an intern to complete this portion consisted of gaining familiarity with Unity and the current ISS Xbox code, porting the Xbox code to the web as is, and modifying the code to work well as a web application. In addition, a procedurally generated cloud algorithm will be developed. Currently, the clouds used in AGEA animations and the Xbox experiences are a texture map. The desire is to create a procedurally generated cloud algorithm to provide dynamically generated clouds for both AGEA animations and the Xbox experiences. This task consists of gaining familiarity with AGEA and the plug-in interface, developing the algorithm, creating an AGEA plug-in to implement the algorithm inside AGEA, and creating a Unity script to implement the algorithm for the Xbox. This portion of the project was unable to be completed in the time frame of the internship; however, the IGOAL will continue to work on it in the future.

Using qualitative research to inform development of a diagnostic algorithm for UTI in children.

PubMed

de Salis, Isabel; Whiting, Penny; Sterne, Jonathan A C; Hay, Alastair D

2013-06-01

Diagnostic and prognostic algorithms can help reduce clinical uncertainty. The selection of candidate symptoms and signs to be measured in case report forms (CRFs) for potential inclusion in diagnostic algorithms needs to be comprehensive, clearly formulated and relevant for end users. To investigate whether qualitative methods could assist in designing CRFs in research developing diagnostic algorithms. Specifically, the study sought to establish whether qualitative methods could have assisted in designing the CRF for the Health Technology Association funded Diagnosis of Urinary Tract infection in Young children (DUTY) study, which will develop a diagnostic algorithm to improve recognition of urinary tract infection (UTI) in children aged <5 years presenting acutely unwell to primary care. Qualitative methods were applied using semi-structured interviews of 30 UK doctors and nurses working with young children in primary care and a Children's Emergency Department. We elicited features that clinicians believed useful in diagnosing UTI and compared these for presence or absence and terminology with the DUTY CRF. Despite much agreement between clinicians' accounts and the DUTY CRFs, we identified a small number of potentially important symptoms and signs not included in the CRF and some included items that could have been reworded to improve understanding and final data analysis. This study uniquely demonstrates the role of qualitative methods in the design and content of CRFs used for developing diagnostic (and prognostic) algorithms. Research groups developing such algorithms should consider using qualitative methods to inform the selection and wording of candidate symptoms and signs.

Volumetric visualization algorithm development for an FPGA-based custom computing machine

NASA Astrophysics Data System (ADS)

Sallinen, Sami J.; Alakuijala, Jyrki; Helminen, Hannu; Laitinen, Joakim

1998-05-01

Rendering volumetric medical images is a burdensome computational task for contemporary computers due to the large size of the data sets. Custom designed reconfigurable hardware could considerably speed up volume visualization if an algorithm suitable for the platform is used. We present an algorithm and speedup techniques for visualizing volumetric medical CT and MR images with a custom-computing machine based on a Field Programmable Gate Array (FPGA). We also present simulated performance results of the proposed algorithm calculated with a software implementation running on a desktop PC. Our algorithm is capable of generating perspective projection renderings of single and multiple isosurfaces with transparency, simulated X-ray images, and Maximum Intensity Projections (MIP). Although more speedup techniques exist for parallel projection than for perspective projection, we have constrained ourselves to perspective viewing, because of its importance in the field of radiotherapy. The algorithm we have developed is based on ray casting, and the rendering is sped up by three different methods: shading speedup by gradient precalculation, a new generalized version of Ray-Acceleration by Distance Coding (RADC), and background ray elimination by speculative ray selection.

Development of the Landsat Data Continuity Mission Cloud Cover Assessment Algorithms

USGS Publications Warehouse

Scaramuzza, Pat; Bouchard, M.A.; Dwyer, John L.

2012-01-01

The upcoming launch of the Operational Land Imager (OLI) will start the next era of the Landsat program. However, the Automated Cloud-Cover Assessment (CCA) (ACCA) algorithm used on Landsat 7 requires a thermal band and is thus not suited for OLI. There will be a thermal instrument on the Landsat Data Continuity Mission (LDCM)-the Thermal Infrared Sensor-which may not be available during all OLI collections. This illustrates a need for CCA for LDCM in the absence of thermal data. To research possibilities for full-resolution OLI cloud assessment, a global data set of 207 Landsat 7 scenes with manually generated cloud masks was created. It was used to evaluate the ACCA algorithm, showing that the algorithm correctly classified 79.9% of a standard test subset of 3.95 109 pixels. The data set was also used to develop and validate two successor algorithms for use with OLI data-one derived from an off-the-shelf machine learning package and one based on ACCA but enhanced by a simple neural network. These comprehensive CCA algorithms were shown to correctly classify pixels as cloudy or clear 88.5% and 89.7% of the time, respectively.

Development of a Smart Release Algorithm for Mid-Air Separation of Parachute Test Articles

NASA Technical Reports Server (NTRS)

Moore, James W.

2011-01-01

The Crew Exploration Vehicle Parachute Assembly System (CPAS) project is currently developing an autonomous method to separate a capsule-shaped parachute test vehicle from an air-drop platform for use in the test program to develop and validate the parachute system for the Orion spacecraft. The CPAS project seeks to perform air-drop tests of an Orion-like boilerplate capsule. Delivery of the boilerplate capsule to the test condition has proven to be a critical and complicated task. In the current concept, the boilerplate vehicle is extracted from an aircraft on top of a Type V pallet and then separated from the pallet in mid-air. The attitude of the vehicles at separation is critical to avoiding re-contact and successfully deploying the boilerplate into a heatshield-down orientation. Neither the pallet nor the boilerplate has an active control system. However, the attitude of the mated vehicle as a function of time is somewhat predictable. CPAS engineers have designed an avionics system to monitor the attitude of the mated vehicle as it is extracted from the aircraft and command a release when the desired conditions are met. The algorithm includes contingency capabilities designed to release the test vehicle before undesirable orientations occur. The algorithm was verified with simulation and ground testing. The pre-flight development and testing is discussed and limitations of ground testing are noted. The CPAS project performed a series of three drop tests as a proof-of-concept of the release technique. These tests helped to refine the attitude instrumentation and software algorithm to be used on future tests. The drop tests are described in detail and the evolution of the release system with each test is described.

Development and testing of incident detection algorithms. Vol. 2, research methodology and detailed results.

DOT National Transportation Integrated Search

1976-04-01

The development and testing of incident detection algorithms was based on Los Angeles and Minneapolis freeway surveillance data. Algorithms considered were based on times series and pattern recognition techniques. Attention was given to the effects o...

A prediction algorithm for first onset of major depression in the general population: development and validation.

PubMed

Wang, JianLi; Sareen, Jitender; Patten, Scott; Bolton, James; Schmitz, Norbert; Birney, Arden

2014-05-01

Prediction algorithms are useful for making clinical decisions and for population health planning. However, such prediction algorithms for first onset of major depression do not exist. The objective of this study was to develop and validate a prediction algorithm for first onset of major depression in the general population. Longitudinal study design with approximate 3-year follow-up. The study was based on data from a nationally representative sample of the US general population. A total of 28 059 individuals who participated in Waves 1 and 2 of the US National Epidemiologic Survey on Alcohol and Related Conditions and who had not had major depression at Wave 1 were included. The prediction algorithm was developed using logistic regression modelling in 21 813 participants from three census regions. The algorithm was validated in participants from the 4th census region (n=6246). Major depression occurred since Wave 1 of the National Epidemiologic Survey on Alcohol and Related Conditions, assessed by the Alcohol Use Disorder and Associated Disabilities Interview Schedule-diagnostic and statistical manual for mental disorders IV. A prediction algorithm containing 17 unique risk factors was developed. The algorithm had good discriminative power (C statistics=0.7538, 95% CI 0.7378 to 0.7699) and excellent calibration (F-adjusted test=1.00, p=0.448) with the weighted data. In the validation sample, the algorithm had a C statistic of 0.7259 and excellent calibration (Hosmer-Lemeshow χ(2)=3.41, p=0.906). The developed prediction algorithm has good discrimination and calibration capacity. It can be used by clinicians, mental health policy-makers and service planners and the general public to predict future risk of having major depression. The application of the algorithm may lead to increased personalisation of treatment, better clinical decisions and more optimal mental health service planning.

Geologist's Field Assistant: Developing Image and Spectral Analyses Algorithms for Remote Science Exploration

NASA Technical Reports Server (NTRS)

Gulick, V. C.; Morris, R. L.; Bishop, J.; Gazis, P.; Alena, R.; Sierhuis, M.

2002-01-01

We are developing science analyses algorithms to interface with a Geologist's Field Assistant device to allow robotic or human remote explorers to better sense their surroundings during limited surface excursions. Our algorithms will interpret spectral and imaging data obtained by various sensors. Additional information is contained in the original extended abstract.

Leadership development in the age of the algorithm.

PubMed

Buckingham, Marcus

2012-06-01

By now we expect personalized content--it's routinely served up by online retailers and news services, for example. But the typical leadership development program still takes a formulaic, one-size-fits-all approach. And it rarely happens that an excellent technique can be effectively transferred from one leader to all others. Someone trying to adopt a practice from a leader with a different style usually seems stilted and off--a Franken-leader. Breakthrough work at Hilton Hotels and other organizations shows how companies can use an algorithmic model to deliver training tips uniquely suited to each individual's style. It's a five-step process: First, a company must choose a tool with which to identify each person's leadership type. Second, it should assess its best leaders, and third, it should interview them about their techniques. Fourth, it should use its algorithmic model to feed tips drawn from those techniques to developing leaders of the same type. And fifth, it should make the system dynamically intelligent, with user reactions sharpening the content and targeting of tips. The power of this kind of system--highly customized, based on peer-to-peer sharing, and continually evolving--will soon overturn the generic model of leadership development. And such systems will inevitably break through any one organization, until somewhere in the cloud the best leadership tips from all over are gathered, sorted, and distributed according to which ones suit which people best.

Developments in Human Centered Cueing Algorithms for Control of Flight Simulator Motion Systems

NASA Technical Reports Server (NTRS)

Houck, Jacob A.; Telban, Robert J.; Cardullo, Frank M.

1997-01-01

The authors conducted further research with cueing algorithms for control of flight simulator motion systems. A variation of the so-called optimal algorithm was formulated using simulated aircraft angular velocity input as a basis. Models of the human vestibular sensation system, i.e. the semicircular canals and otoliths, are incorporated within the algorithm. Comparisons of angular velocity cueing responses showed a significant improvement over a formulation using angular acceleration input. Results also compared favorably with the coordinated adaptive washout algorithm, yielding similar results for angular velocity cues while eliminating false cues and reducing the tilt rate for longitudinal cues. These results were confirmed in piloted tests on the current motion system at NASA-Langley, the Visual Motion Simulator (VMS). Proposed future developments by the authors in cueing algorithms are revealed. The new motion system, the Cockpit Motion Facility (CMF), where the final evaluation of the cueing algorithms will be conducted, is also described.

Algorithm improvement program nuclide identification algorithm scoring criteria and scoring application.

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

Enghauser, Michael

2016-02-01

The goal of the Domestic Nuclear Detection Office (DNDO) Algorithm Improvement Program (AIP) is to facilitate gamma-radiation detector nuclide identification algorithm development, improvement, and validation. Accordingly, scoring criteria have been developed to objectively assess the performance of nuclide identification algorithms. In addition, a Microsoft Excel spreadsheet application for automated nuclide identification scoring has been developed. This report provides an overview of the equations, nuclide weighting factors, nuclide equivalencies, and configuration weighting factors used by the application for scoring nuclide identification algorithm performance. Furthermore, this report presents a general overview of the nuclide identification algorithm scoring application including illustrative examples.

Developing Information Power Grid Based Algorithms and Software

NASA Technical Reports Server (NTRS)

Dongarra, Jack

1998-01-01

This exploratory study initiated our effort to understand performance modeling on parallel systems. The basic goal of performance modeling is to understand and predict the performance of a computer program or set of programs on a computer system. Performance modeling has numerous applications, including evaluation of algorithms, optimization of code implementations, parallel library development, comparison of system architectures, parallel system design, and procurement of new systems. Our work lays the basis for the construction of parallel libraries that allow for the reconstruction of application codes on several distinct architectures so as to assure performance portability. Following our strategy, once the requirements of applications are well understood, one can then construct a library in a layered fashion. The top level of this library will consist of architecture-independent geometric, numerical, and symbolic algorithms that are needed by the sample of applications. These routines should be written in a language that is portable across the targeted architectures.

A multi-reference filtered-x-Newton narrowband algorithm for active isolation of vibration and experimental investigations

NASA Astrophysics Data System (ADS)

Wang, Chun-yu; He, Lin; Li, Yan; Shuai, Chang-geng

2018-01-01

In engineering applications, ship machinery vibration may be induced by multiple rotational machines sharing a common vibration isolation platform and operating at the same time, and multiple sinusoidal components may be excited. These components may be located at frequencies with large differences or at very close frequencies. A multi-reference filtered-x Newton narrowband (MRFx-Newton) algorithm is proposed to control these multiple sinusoidal components in an MIMO (multiple input and multiple output) system, especially for those located at very close frequencies. The proposed MRFx-Newton algorithm can decouple and suppress multiple sinusoidal components located in the same narrow frequency band even though such components cannot be separated from each other by a narrowband-pass filter. Like the Fx-Newton algorithm, good real-time performance is also achieved by the faster convergence speed brought by the 2nd-order inverse secondary-path filter in the time domain. Experiments are also conducted to verify the feasibility and test the performance of the proposed algorithm installed in an active-passive vibration isolation system in suppressing the vibration excited by an artificial source and air compressor/s. The results show that the proposed algorithm not only has comparable convergence rate as the Fx-Newton algorithm but also has better real-time performance and robustness than the Fx-Newton algorithm in active control of the vibration induced by multiple sound sources/rotational machines working on a shared platform.

Development of an Aircraft Approach and Departure Atmospheric Profile Generation Algorithm

NASA Technical Reports Server (NTRS)

Buck, Bill K.; Velotas, Steven G.; Rutishauser, David K. (Technical Monitor)

2004-01-01

In support of NASA Virtual Airspace Modeling and Simulation (VAMS) project, an effort was initiated to develop and test techniques for extracting meteorological data from landing and departing aircraft, and for building altitude based profiles for key meteorological parameters from these data. The generated atmospheric profiles will be used as inputs to NASA s Aircraft Vortex Spacing System (AVOLSS) Prediction Algorithm (APA) for benefits and trade analysis. A Wake Vortex Advisory System (WakeVAS) is being developed to apply weather and wake prediction and sensing technologies with procedures to reduce current wake separation criteria when safe and appropriate to increase airport operational efficiency. The purpose of this report is to document the initial theory and design of the Aircraft Approach Departure Atmospheric Profile Generation Algorithm.

An improved VSS NLMS algorithm for active noise cancellation

NASA Astrophysics Data System (ADS)

Sun, Yunzhuo; Wang, Mingjiang; Han, Yufei; Zhang, Congyan

2017-08-01

In this paper, an improved variable step size NLMS algorithm is proposed. NLMS has fast convergence rate and low steady state error compared to other traditional adaptive filtering algorithm. But there is a contradiction between the convergence speed and steady state error that affect the performance of the NLMS algorithm. Now, we propose a new variable step size NLMS algorithm. It dynamically changes the step size according to current error and iteration times. The proposed algorithm has simple formulation and easily setting parameters, and effectively solves the contradiction in NLMS. The simulation results show that the proposed algorithm has a good tracking ability, fast convergence rate and low steady state error simultaneously.

3-D CSEM data inversion algorithm based on simultaneously active multiple transmitters concept

NASA Astrophysics Data System (ADS)

Dehiya, Rahul; Singh, Arun; Gupta, Pravin Kumar; Israil, Mohammad

2017-05-01

We present an algorithm for efficient 3-D inversion of marine controlled-source electromagnetic data. The efficiency is achieved by exploiting the redundancy in data. The data redundancy is reduced by compressing the data through stacking of the response of transmitters which are in close proximity. This stacking is equivalent to synthesizing the data as if the multiple transmitters are simultaneously active. The redundancy in data, arising due to close transmitter spacing, has been studied through singular value analysis of the Jacobian formed in 1-D inversion. This study reveals that the transmitter spacing of 100 m, typically used in marine data acquisition, does result in redundancy in the data. In the proposed algorithm, the data are compressed through stacking which leads to both computational advantage and reduction in noise. The performance of the algorithm for noisy data is demonstrated through the studies on two types of noise, viz., uncorrelated additive noise and correlated non-additive noise. It is observed that in case of uncorrelated additive noise, up to a moderately high (10 percent) noise level the algorithm addresses the noise as effectively as the traditional full data inversion. However, when the noise level in the data is high (20 percent), the algorithm outperforms the traditional full data inversion in terms of data misfit. Similar results are obtained in case of correlated non-additive noise and the algorithm performs better if the level of noise is high. The inversion results of a real field data set are also presented to demonstrate the robustness of the algorithm. The significant computational advantage in all cases presented makes this algorithm a better choice.

SPHERES as Formation Flight Algorithm Development and Validation Testbed: Current Progress and Beyond

NASA Technical Reports Server (NTRS)

Kong, Edmund M.; Saenz-Otero, Alvar; Nolet, Simon; Berkovitz, Dustin S.; Miller, David W.; Sell, Steve W.

2004-01-01

The MIT-SSL SPHERES testbed provides a facility for the development of algorithms necessary for the success of Distributed Satellite Systems (DSS). The initial development contemplated formation flight and docking control algorithms; SPHERES now supports the study of metrology, control, autonomy, artificial intelligence, and communications algorithms and their effects on DSS projects. To support this wide range of topics, the SPHERES design contemplated the need to support multiple researchers, as echoed from both the hardware and software designs. The SPHERES operational plan further facilitates the development of algorithms by multiple researchers, while the operational locations incrementally increase the ability of the tests to operate in a representative environment. In this paper, an overview of the SPHERES testbed is first presented. The SPHERES testbed serves as a model of the design philosophies that allow for the various researches being carried out on such a facility. The implementation of these philosophies are further highlighted in the three different programs that are currently scheduled for testing onboard the International Space Station (ISS) and three that are proposed for a re-flight mission: Mass Property Identification, Autonomous Rendezvous and Docking, TPF Multiple Spacecraft Formation Flight in the first flight and Precision Optical Pointing, Tethered Formation Flight and Mars Orbit Sample Retrieval for the re-flight mission.

Aerocapture Guidance Algorithm Comparison Campaign

NASA Technical Reports Server (NTRS)

Rousseau, Stephane; Perot, Etienne; Graves, Claude; Masciarelli, James P.; Queen, Eric

2002-01-01

The aerocapture is a promising technique for the future human interplanetary missions. The Mars Sample Return was initially based on an insertion by aerocapture. A CNES orbiter Mars Premier was developed to demonstrate this concept. Mainly due to budget constraints, the aerocapture was cancelled for the French orbiter. A lot of studies were achieved during the three last years to develop and test different guidance algorithms (APC, EC, TPC, NPC). This work was shared between CNES and NASA, with a fruitful joint working group. To finish this study an evaluation campaign has been performed to test the different algorithms. The objective was to assess the robustness, accuracy, capability to limit the load, and the complexity of each algorithm. A simulation campaign has been specified and performed by CNES, with a similar activity on the NASA side to confirm the CNES results. This evaluation has demonstrated that the numerical guidance principal is not competitive compared to the analytical concepts. All the other algorithms are well adapted to guaranty the success of the aerocapture. The TPC appears to be the more robust, the APC the more accurate, and the EC appears to be a good compromise.

Algorithmic developments of the kinetic activation-relaxation technique: Accessing long-time kinetics of larger and more complex systems

NASA Astrophysics Data System (ADS)

Trochet, Mickaël; Sauvé-Lacoursière, Alecsandre; Mousseau, Normand

2017-10-01

In spite of the considerable computer speed increase of the last decades, long-time atomic simulations remain a challenge and most molecular dynamical simulations are limited to 1 μ s at the very best in condensed matter and materials science. There is a need, therefore, for accelerated methods that can bridge the gap between the full dynamical description of molecular dynamics and experimentally relevant time scales. This is the goal of the kinetic Activation-Relaxation Technique (k-ART), an off-lattice kinetic Monte-Carlo method with on-the-fly catalog building capabilities based on the topological tool NAUTY and the open-ended search method Activation-Relaxation Technique (ART nouveau) that has been applied with success to the study of long-time kinetics of complex materials, including grain boundaries, alloys, and amorphous materials. We present a number of recent algorithmic additions, including the use of local force calculation, two-level parallelization, improved topological description, and biased sampling and show how they perform on two applications linked to defect diffusion and relaxation after ion bombardement in Si.

The development of a scalable parallel 3-D CFD algorithm for turbomachinery. M.S. Thesis Final Report

NASA Technical Reports Server (NTRS)

Luke, Edward Allen

1993-01-01

Two algorithms capable of computing a transonic 3-D inviscid flow field about rotating machines are considered for parallel implementation. During the study of these algorithms, a significant new method of measuring the performance of parallel algorithms is developed. The theory that supports this new method creates an empirical definition of scalable parallel algorithms that is used to produce quantifiable evidence that a scalable parallel application was developed. The implementation of the parallel application and an automated domain decomposition tool are also discussed.

Development of an algorithm for an EEG-based driver fatigue countermeasure.

PubMed

Lal, Saroj K L; Craig, Ashley; Boord, Peter; Kirkup, Les; Nguyen, Hung

2003-01-01

Fatigue affects a driver's ability to proceed safely. Driver-related fatigue and/or sleepiness are a significant cause of traffic accidents, which makes this an area of great socioeconomic concern. Monitoring physiological signals while driving provides the possibility of detecting and warning of fatigue. The aim of this paper is to describe an EEG-based fatigue countermeasure algorithm and to report its reliability. Changes in all major EEG bands during fatigue were used to develop the algorithm for detecting different levels of fatigue. The software was shown to be capable of detecting fatigue accurately in 10 subjects tested. The percentage of time the subjects were detected to be in a fatigue state was significantly different than the alert phase (P<.01). This is the first countermeasure software described that has shown to detect fatigue based on EEG changes in all frequency bands. Field research is required to evaluate the fatigue software in order to produce a robust and reliable fatigue countermeasure system. The development of the fatigue countermeasure algorithm forms the basis of a future fatigue countermeasure device. Implementation of electronic devices for fatigue detection is crucial for reducing fatigue-related road accidents and their associated costs.

Knowing 'something is not right' is beyond intuition: development of a clinical algorithm to enhance surveillance and assist nurses to organise and communicate clinical findings.

PubMed

Brier, Jessica; Carolyn, Moalem; Haverly, Marsha; Januario, Mary Ellen; Padula, Cynthia; Tal, Ahuva; Triosh, Henia

2015-03-01

To develop a clinical algorithm to guide nurses' critical thinking through systematic surveillance, assessment, actions required and communication strategies. To achieve this, an international, multiphase project was initiated. Patients receive hospital care postoperatively because they require the skilled surveillance of nurses. Effective assessment of postoperative patients is essential for early detection of clinical deterioration and optimal care management. Despite the significant amount of time devoted to surveillance activities, there is lack of evidence that nurses use a consistent, systematic approach in surveillance, management and communication, potentially leading to less optimal outcomes. Several explanations for the lack of consistency have been suggested in the literature. Mixed methods approach. Retrospective chart review; semi-structured interviews conducted with expert nurses (n = 10); algorithm development. Themes developed from the semi-structured interviews, including (1) complete, systematic assessment, (2) something is not right (3) validating with others, (4) influencing factors and (5) frustration with lack of response when communicating findings were used as the basis for development of the Surveillance Algorithm for Post-Surgical Patients. The algorithm proved beneficial based on limited use in clinical settings. Further work is needed to fully test it in education and practice. The Surveillance Algorithm for Post-Surgical Patients represents the approach of expert nurses, and serves to guide less expert nurses' observations, critical thinking, actions and communication. Based on this approach, the algorithm assists nurses to develop skills promoting early detection, intervention and communication in cases of patient deterioration. © 2014 John Wiley & Sons Ltd.

Design requirements and development of an airborne descent path definition algorithm for time navigation

NASA Technical Reports Server (NTRS)

Izumi, K. H.; Thompson, J. L.; Groce, J. L.; Schwab, R. W.

1986-01-01

The design requirements for a 4D path definition algorithm are described. These requirements were developed for the NASA ATOPS as an extension of the Local Flow Management/Profile Descent algorithm. They specify the processing flow, functional and data architectures, and system input requirements, and recommended the addition of a broad path revision (reinitialization) function capability. The document also summarizes algorithm design enhancements and the implementation status of the algorithm on an in-house PDP-11/70 computer. Finally, the requirements for the pilot-computer interfaces, the lateral path processor, and guidance and steering function are described.

Triggering Interventions for Influenza: The ALERT Algorithm

PubMed Central

Reich, Nicholas G.; Cummings, Derek A. T.; Lauer, Stephen A.; Zorn, Martha; Robinson, Christine; Nyquist, Ann-Christine; Price, Connie S.; Simberkoff, Michael; Radonovich, Lewis J.; Perl, Trish M.

2015-01-01

Background. Early, accurate predictions of the onset of influenza season enable targeted implementation of control efforts. Our objective was to develop a tool to assist public health practitioners, researchers, and clinicians in defining the community-level onset of seasonal influenza epidemics. Methods. Using recent surveillance data on virologically confirmed infections of influenza, we developed the Above Local Elevated Respiratory Illness Threshold (ALERT) algorithm, a method to identify the period of highest seasonal influenza activity. We used data from 2 large hospitals that serve Baltimore, Maryland and Denver, Colorado, and the surrounding geographic areas. The data used by ALERT are routinely collected surveillance data: weekly case counts of laboratory-confirmed influenza A virus. The main outcome is the percentage of prospective seasonal influenza cases identified by the ALERT algorithm. Results. When ALERT thresholds designed to capture 90% of all cases were applied prospectively to the 2011–2012 and 2012–2013 influenza seasons in both hospitals, 71%–91% of all reported cases fell within the ALERT period. Conclusions. The ALERT algorithm provides a simple, robust, and accurate metric for determining the onset of elevated influenza activity at the community level. This new algorithm provides valuable information that can impact infection prevention recommendations, public health practice, and healthcare delivery. PMID:25414260

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.

Development and validation of a risk-prediction algorithm for the recurrence of panic disorder.

PubMed

Liu, Yan; Sareen, Jitender; Bolton, James; Wang, JianLi

2015-05-01

To develop and validate a risk prediction algorithm for the recurrence of panic disorder. Three-year longitudinal data were taken from the National Epidemiologic Survey on Alcohol and Related Conditions (2001/2002-2004/2005). One thousand six hundred and eighty one participants with a lifetime panic disorder and who had not had panic attacks for at least 2 months at baseline were included. The development cohort included 949 participants; 732 from different census regions were in the validation cohort. Recurrence of panic disorder over the follow-up period was assessed using the Alcohol Use Disorder and Associated Disabilities Interview Schedule, based on the DSM-IV criteria. Logistic regression was used for deriving the algorithm. Discrimination and calibration were assessed in the development and the validation cohorts. The developed algorithm consisted of 11 predictors: age, sex, panic disorder in the past 12 months, nicotine dependence, rapid heartbeat/tachycardia, taking medication for panic attacks, feelings of choking and persistent worry about having another panic attack, two personality traits, and childhood trauma. The algorithm had good discriminative power (C statistic = 0.7863, 95% CI: 0.7487, 0.8240). The C statistic was 0.7283 (95% CI: 0.6889, 0.7764) in the external validation data set. The developed risk algorithm for predicting the recurrence of panic disorder has good discrimination and excellent calibration. Data related to the predictors can be easily attainable in routine clinical practice. It can be used by clinicians to calculate the probability of recurrence of panic disorder in the next 3 years for individual patients, communicate with patients regarding personal risks, and thus improve personalized treatment approaches. © 2015 Wiley Periodicals, Inc.

A Robust Dynamic Heart-Rate Detection Algorithm Framework During Intense Physical Activities Using Photoplethysmographic Signals

PubMed Central

Song, Jiajia; Li, Dan; Ma, Xiaoyuan; Teng, Guowei; Wei, Jianming

2017-01-01

Dynamic accurate heart-rate (HR) estimation using a photoplethysmogram (PPG) during intense physical activities is always challenging due to corruption by motion artifacts (MAs). It is difficult to reconstruct a clean signal and extract HR from contaminated PPG. This paper proposes a robust HR-estimation algorithm framework that uses one-channel PPG and tri-axis acceleration data to reconstruct the PPG and calculate the HR based on features of the PPG and spectral analysis. Firstly, the signal is judged by the presence of MAs. Then, the spectral peaks corresponding to acceleration data are filtered from the periodogram of the PPG when MAs exist. Different signal-processing methods are applied based on the amount of remaining PPG spectral peaks. The main MA-removal algorithm (NFEEMD) includes the repeated single-notch filter and ensemble empirical mode decomposition. Finally, HR calibration is designed to ensure the accuracy of HR tracking. The NFEEMD algorithm was performed on the 23 datasets from the 2015 IEEE Signal Processing Cup Database. The average estimation errors were 1.12 BPM (12 training datasets), 2.63 BPM (10 testing datasets) and 1.87 BPM (all 23 datasets), respectively. The Pearson correlation was 0.992. The experiment results illustrate that the proposed algorithm is not only suitable for HR estimation during continuous activities, like slow running (13 training datasets), but also for intense physical activities with acceleration, like arm exercise (10 testing datasets). PMID:29068403

Stationary-phase optimized selectivity liquid chromatography: development of a linear gradient prediction algorithm.

PubMed

De Beer, Maarten; Lynen, Fréderic; Chen, Kai; Ferguson, Paul; Hanna-Brown, Melissa; Sandra, Pat

2010-03-01

Stationary-phase optimized selectivity liquid chromatography (SOS-LC) is a tool in reversed-phase LC (RP-LC) to optimize the selectivity for a given separation by combining stationary phases in a multisegment column. The presently (commercially) available SOS-LC optimization procedure and algorithm are only applicable to isocratic analyses. Step gradient SOS-LC has been developed, but this is still not very elegant for the analysis of complex mixtures composed of components covering a broad hydrophobicity range. A linear gradient prediction algorithm has been developed allowing one to apply SOS-LC as a generic RP-LC optimization method. The algorithm allows operation in isocratic, stepwise, and linear gradient run modes. The features of SOS-LC in the linear gradient mode are demonstrated by means of a mixture of 13 steroids, whereby baseline separation is predicted and experimentally demonstrated.

Algorithm Improvement Program Nuclide Identification Algorithm Scoring Criteria And Scoring Application - DNDO.

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

Enghauser, Michael

2015-02-01

The goal of the Domestic Nuclear Detection Office (DNDO) Algorithm Improvement Program (AIP) is to facilitate gamma-radiation detector nuclide identification algorithm development, improvement, and validation. Accordingly, scoring criteria have been developed to objectively assess the performance of nuclide identification algorithms. In addition, a Microsoft Excel spreadsheet application for automated nuclide identification scoring has been developed. This report provides an overview of the equations, nuclide weighting factors, nuclide equivalencies, and configuration weighting factors used by the application for scoring nuclide identification algorithm performance. Furthermore, this report presents a general overview of the nuclide identification algorithm scoring application including illustrative examples.

Development of Fast Algorithms Using Recursion, Nesting and Iterations for Computational Electromagnetics

NASA Technical Reports Server (NTRS)

Chew, W. C.; Song, J. M.; Lu, C. C.; Weedon, W. H.

1995-01-01

In the first phase of our work, we have concentrated on laying the foundation to develop fast algorithms, including the use of recursive structure like the recursive aggregate interaction matrix algorithm (RAIMA), the nested equivalence principle algorithm (NEPAL), the ray-propagation fast multipole algorithm (RPFMA), and the multi-level fast multipole algorithm (MLFMA). We have also investigated the use of curvilinear patches to build a basic method of moments code where these acceleration techniques can be used later. In the second phase, which is mainly reported on here, we have concentrated on implementing three-dimensional NEPAL on a massively parallel machine, the Connection Machine CM-5, and have been able to obtain some 3D scattering results. In order to understand the parallelization of codes on the Connection Machine, we have also studied the parallelization of 3D finite-difference time-domain (FDTD) code with PML material absorbing boundary condition (ABC). We found that simple algorithms like the FDTD with material ABC can be parallelized very well allowing us to solve within a minute a problem of over a million nodes. In addition, we have studied the use of the fast multipole method and the ray-propagation fast multipole algorithm to expedite matrix-vector multiplication in a conjugate-gradient solution to integral equations of scattering. We find that these methods are faster than LU decomposition for one incident angle, but are slower than LU decomposition when many incident angles are needed as in the monostatic RCS calculations.

Algorithm for automatic forced spirometry quality assessment: technological developments.

PubMed

Melia, Umberto; Burgos, Felip; Vallverdú, Montserrat; Velickovski, Filip; Lluch-Ariet, Magí; Roca, Josep; Caminal, Pere

2014-01-01

We hypothesized that the implementation of automatic real-time assessment of quality of forced spirometry (FS) may significantly enhance the potential for extensive deployment of a FS program in the community. Recent studies have demonstrated that the application of quality criteria defined by the ATS/ERS (American Thoracic Society/European Respiratory Society) in commercially available equipment with automatic quality assessment can be markedly improved. To this end, an algorithm for assessing quality of FS automatically was reported. The current research describes the mathematical developments of the algorithm. An innovative analysis of the shape of the spirometric curve, adding 23 new metrics to the traditional 4 recommended by ATS/ERS, was done. The algorithm was created through a two-step iterative process including: (1) an initial version using the standard FS curves recommended by the ATS; and, (2) a refined version using curves from patients. In each of these steps the results were assessed against one expert's opinion. Finally, an independent set of FS curves from 291 patients was used for validation purposes. The novel mathematical approach to characterize the FS curves led to appropriate FS classification with high specificity (95%) and sensitivity (96%). The results constitute the basis for a successful transfer of FS testing to non-specialized professionals in the community.

Activity recognition in planetary navigation field tests using classification algorithms applied to accelerometer data.

PubMed

Song, Wen; Ade, Carl; Broxterman, Ryan; Barstow, Thomas; Nelson, Thomas; Warren, Steve

2012-01-01

Accelerometer data provide useful information about subject activity in many different application scenarios. For this study, single-accelerometer data were acquired from subjects participating in field tests that mimic tasks that astronauts might encounter in reduced gravity environments. The primary goal of this effort was to apply classification algorithms that could identify these tasks based on features present in their corresponding accelerometer data, where the end goal is to establish methods to unobtrusively gauge subject well-being based on sensors that reside in their local environment. In this initial analysis, six different activities that involve leg movement are classified. The k-Nearest Neighbors (kNN) algorithm was found to be the most effective, with an overall classification success rate of 90.8%.

A collaborative approach to developing an electronic health record phenotyping algorithm for drug-induced liver injury

PubMed Central

Overby, Casey Lynnette; Pathak, Jyotishman; Gottesman, Omri; Haerian, Krystl; Perotte, Adler; Murphy, Sean; Bruce, Kevin; Johnson, Stephanie; Talwalkar, Jayant; Shen, Yufeng; Ellis, Steve; Kullo, Iftikhar; Chute, Christopher; Friedman, Carol; Bottinger, Erwin; Hripcsak, George; Weng, Chunhua

2013-01-01

Objective To describe a collaborative approach for developing an electronic health record (EHR) phenotyping algorithm for drug-induced liver injury (DILI). Methods We analyzed types and causes of differences in DILI case definitions provided by two institutions—Columbia University and Mayo Clinic; harmonized two EHR phenotyping algorithms; and assessed the performance, measured by sensitivity, specificity, positive predictive value, and negative predictive value, of the resulting algorithm at three institutions except that sensitivity was measured only at Columbia University. Results Although these sites had the same case definition, their phenotyping methods differed by selection of liver injury diagnoses, inclusion of drugs cited in DILI cases, laboratory tests assessed, laboratory thresholds for liver injury, exclusion criteria, and approaches to validating phenotypes. We reached consensus on a DILI phenotyping algorithm and implemented it at three institutions. The algorithm was adapted locally to account for differences in populations and data access. Implementations collectively yielded 117 algorithm-selected cases and 23 confirmed true positive cases. Discussion Phenotyping for rare conditions benefits significantly from pooling data across institutions. Despite the heterogeneity of EHRs and varied algorithm implementations, we demonstrated the portability of this algorithm across three institutions. The performance of this algorithm for identifying DILI was comparable with other computerized approaches to identify adverse drug events. Conclusions Phenotyping algorithms developed for rare and complex conditions are likely to require adaptive implementation at multiple institutions. Better approaches are also needed to share algorithms. Early agreement on goals, data sources, and validation methods may improve the portability of the algorithms. PMID:23837993

Detection of algorithmic trading

NASA Astrophysics Data System (ADS)

Bogoev, Dimitar; Karam, Arzé

2017-10-01

We develop a new approach to reflect the behavior of algorithmic traders. Specifically, we provide an analytical and tractable way to infer patterns of quote volatility and price momentum consistent with different types of strategies employed by algorithmic traders, and we propose two ratios to quantify these patterns. Quote volatility ratio is based on the rate of oscillation of the best ask and best bid quotes over an extremely short period of time; whereas price momentum ratio is based on identifying patterns of rapid upward or downward movement in prices. The two ratios are evaluated across several asset classes. We further run a two-stage Artificial Neural Network experiment on the quote volatility ratio; the first stage is used to detect the quote volatility patterns resulting from algorithmic activity, while the second is used to validate the quality of signal detection provided by our measure.

Prosthetic joint infection development of an evidence-based diagnostic algorithm.

PubMed

Mühlhofer, Heinrich M L; Pohlig, Florian; Kanz, Karl-Georg; Lenze, Ulrich; Lenze, Florian; Toepfer, Andreas; Kelch, Sarah; Harrasser, Norbert; von Eisenhart-Rothe, Rüdiger; Schauwecker, Johannes

2017-03-09

Increasing rates of prosthetic joint infection (PJI) have presented challenges for general practitioners, orthopedic surgeons and the health care system in the recent years. The diagnosis of PJI is complex; multiple diagnostic tools are used in the attempt to correctly diagnose PJI. Evidence-based algorithms can help to identify PJI using standardized diagnostic steps. We reviewed relevant publications between 1990 and 2015 using a systematic literature search in MEDLINE and PUBMED. The selected search results were then classified into levels of evidence. The keywords were prosthetic joint infection, biofilm, diagnosis, sonication, antibiotic treatment, implant-associated infection, Staph. aureus, rifampicin, implant retention, pcr, maldi-tof, serology, synovial fluid, c-reactive protein level, total hip arthroplasty (THA), total knee arthroplasty (TKA) and combinations of these terms. From an initial 768 publications, 156 publications were stringently reviewed. Publications with class I-III recommendations (EAST) were considered. We developed an algorithm for the diagnostic approach to display the complex diagnosis of PJI in a clear and logically structured process according to ISO 5807. The evidence-based standardized algorithm combines modern clinical requirements and evidence-based treatment principles. The algorithm provides a detailed transparent standard operating procedure (SOP) for diagnosing PJI. Thus, consistently high, examiner-independent process quality is assured to meet the demands of modern quality management in PJI diagnosis.

DNA Microarray Data Analysis: A Novel Biclustering Algorithm Approach

NASA Astrophysics Data System (ADS)

Tchagang, Alain B.; Tewfik, Ahmed H.

2006-12-01

Biclustering algorithms refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. Biclustering problems arise in DNA microarray data analysis, collaborative filtering, market research, information retrieval, text mining, electoral trends, exchange analysis, and so forth. When dealing with DNA microarray experimental data for example, the goal of biclustering algorithms is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this study, we develop novel biclustering algorithms using basic linear algebra and arithmetic tools. The proposed biclustering algorithms can be used to search for all biclusters with constant values, biclusters with constant values on rows, biclusters with constant values on columns, and biclusters with coherent values from a set of data in a timely manner and without solving any optimization problem. We also show how one of the proposed biclustering algorithms can be adapted to identify biclusters with coherent evolution. The algorithms developed in this study discover all valid biclusters of each type, while almost all previous biclustering approaches will miss some.

Development of a stereo analysis algorithm for generating topographic maps using interactive techniques of the MPP

NASA Technical Reports Server (NTRS)

Strong, James P.

1987-01-01

A local area matching algorithm was developed on the Massively Parallel Processor (MPP). It is an iterative technique that first matches coarse or low resolution areas and at each iteration performs matches of higher resolution. Results so far show that when good matches are possible in the two images, the MPP algorithm matches corresponding areas as well as a human observer. To aid in developing this algorithm, a control or shell program was developed for the MPP that allows interactive experimentation with various parameters and procedures to be used in the matching process. (This would not be possible without the high speed of the MPP). With the system, optimal techniques can be developed for different types of matching problems.

Development of Algorithms for Control of Humidity in Plant Growth Chambers

NASA Technical Reports Server (NTRS)

Costello, Thomas A.

2003-01-01

Algorithms were developed to control humidity in plant growth chambers used for research on bioregenerative life support at Kennedy Space Center. The algorithms used the computed water vapor pressure (based on measured air temperature and relative humidity) as the process variable, with time-proportioned outputs to operate the humidifier and de-humidifier. Algorithms were based upon proportional-integral-differential (PID) and Fuzzy Logic schemes and were implemented using I/O Control software (OPTO-22) to define and download the control logic to an autonomous programmable logic controller (PLC, ultimate ethernet brain and assorted input-output modules, OPTO-22), which performed the monitoring and control logic processing, as well the physical control of the devices that effected the targeted environment in the chamber. During limited testing, the PLC's successfully implemented the intended control schemes and attained a control resolution for humidity of less than 1%. The algorithms have potential to be used not only with autonomous PLC's but could also be implemented within network-based supervisory control programs. This report documents unique control features that were implemented within the OPTO-22 framework and makes recommendations regarding future uses of the hardware and software for biological research by NASA.

Evaluation of a Didactic Method for the Active Learning of Greedy Algorithms

ERIC Educational Resources Information Center

Esteban-Sánchez, Natalia; Pizarro, Celeste; Velázquez-Iturbide, J. Ángel

2014-01-01

An evaluation of the educational effectiveness of a didactic method for the active learning of greedy algorithms is presented. The didactic method sets students structured-inquiry challenges to be addressed with a specific experimental method, supported by the interactive system GreedEx. This didactic method has been refined over several years of…

Experiences on developing digital down conversion algorithms using Xilinx system generator

NASA Astrophysics Data System (ADS)

Xu, Chengfa; Yuan, Yuan; Zhao, Lizhi

2013-07-01

The Digital Down Conversion (DDC) algorithm is a classical signal processing method which is widely used in radar and communication systems. In this paper, the DDC function is implemented by Xilinx System Generator tool on FPGA. System Generator is an FPGA design tool provided by Xilinx Inc and MathWorks Inc. It is very convenient for programmers to manipulate the design and debug the function, especially for the complex algorithm. Through the developing process of DDC function based on System Generator, the results show that System Generator is a very fast and efficient tool for FPGA design.

Development and comparisons of wind retrieval algorithms for small unmanned aerial systems

NASA Astrophysics Data System (ADS)

Bonin, T. A.; Chilson, P. B.; Zielke, B. S.; Klein, P. M.; Leeman, J. R.

2012-12-01

Recently, there has been an increase in use of Unmanned Aerial Systems (UASs) as platforms for conducting fundamental and applied research in the lower atmosphere due to their relatively low cost and ability to collect samples with high spatial and temporal resolution. Concurrent with this development comes the need for accurate instrumentation and measurement methods suitable for small meteorological UASs. Moreover, the instrumentation to be integrated into such platforms must be small and lightweight. Whereas thermodynamic variables can be easily measured using well aspirated sensors onboard, it is much more challenging to accurately measure the wind with a UAS. Several algorithms have been developed that incorporate GPS observations as a means of estimating the horizontal wind vector, with each algorithm exhibiting its own particular strengths and weaknesses. In the present study, the performance of three such GPS-based wind-retrieval algorithms has been investigated and compared with wind estimates from rawinsonde and sodar observations. Each of the algorithms considered agreed well with the wind measurements from sounding and sodar data. Through the integration of UAS-retrieved profiles of thermodynamic and kinematic parameters, one can investigate the static and dynamic stability of the atmosphere and relate them to the state of the boundary layer across a variety of times and locations, which might be difficult to access using conventional instrumentation.

Review and Analysis of Algorithmic Approaches Developed for Prognostics on CMAPSS Dataset

NASA Technical Reports Server (NTRS)

Ramasso, Emannuel; Saxena, Abhinav

2014-01-01

Benchmarking of prognostic algorithms has been challenging due to limited availability of common datasets suitable for prognostics. In an attempt to alleviate this problem several benchmarking datasets have been collected by NASA's prognostic center of excellence and made available to the Prognostics and Health Management (PHM) community to allow evaluation and comparison of prognostics algorithms. Among those datasets are five C-MAPSS datasets that have been extremely popular due to their unique characteristics making them suitable for prognostics. The C-MAPSS datasets pose several challenges that have been tackled by different methods in the PHM literature. In particular, management of high variability due to sensor noise, effects of operating conditions, and presence of multiple simultaneous fault modes are some factors that have great impact on the generalization capabilities of prognostics algorithms. More than 70 publications have used the C-MAPSS datasets for developing data-driven prognostic algorithms. The C-MAPSS datasets are also shown to be well-suited for development of new machine learning and pattern recognition tools for several key preprocessing steps such as feature extraction and selection, failure mode assessment, operating conditions assessment, health status estimation, uncertainty management, and prognostics performance evaluation. This paper summarizes a comprehensive literature review of publications using C-MAPSS datasets and provides guidelines and references to further usage of these datasets in a manner that allows clear and consistent comparison between different approaches.

A Robust Step Detection Algorithm and Walking Distance Estimation Based on Daily Wrist Activity Recognition Using a Smart Band.

PubMed

Trong Bui, Duong; Nguyen, Nhan Duc; Jeong, Gu-Min

2018-06-25

Human activity recognition and pedestrian dead reckoning are an interesting field because of their importance utilities in daily life healthcare. Currently, these fields are facing many challenges, one of which is the lack of a robust algorithm with high performance. This paper proposes a new method to implement a robust step detection and adaptive distance estimation algorithm based on the classification of five daily wrist activities during walking at various speeds using a smart band. The key idea is that the non-parametric adaptive distance estimator is performed after two activity classifiers and a robust step detector. In this study, two classifiers perform two phases of recognizing five wrist activities during walking. Then, a robust step detection algorithm, which is integrated with an adaptive threshold, peak and valley correction algorithm, is applied to the classified activities to detect the walking steps. In addition, the misclassification activities are fed back to the previous layer. Finally, three adaptive distance estimators, which are based on a non-parametric model of the average walking speed, calculate the length of each strike. The experimental results show that the average classification accuracy is about 99%, and the accuracy of the step detection is 98.7%. The error of the estimated distance is 2.2⁻4.2% depending on the type of wrist activities.

Advanced biologically plausible algorithms for low-level image processing

NASA Astrophysics Data System (ADS)

Gusakova, Valentina I.; Podladchikova, Lubov N.; Shaposhnikov, Dmitry G.; Markin, Sergey N.; Golovan, Alexander V.; Lee, Seong-Whan

1999-08-01

At present, in computer vision, the approach based on modeling the biological vision mechanisms is extensively developed. However, up to now, real world image processing has no effective solution in frameworks of both biologically inspired and conventional approaches. Evidently, new algorithms and system architectures based on advanced biological motivation should be developed for solution of computational problems related to this visual task. Basic problems that should be solved for creation of effective artificial visual system to process real world imags are a search for new algorithms of low-level image processing that, in a great extent, determine system performance. In the present paper, the result of psychophysical experiments and several advanced biologically motivated algorithms for low-level processing are presented. These algorithms are based on local space-variant filter, context encoding visual information presented in the center of input window, and automatic detection of perceptually important image fragments. The core of latter algorithm are using local feature conjunctions such as noncolinear oriented segment and composite feature map formation. Developed algorithms were integrated into foveal active vision model, the MARR. It is supposed that proposed algorithms may significantly improve model performance while real world image processing during memorizing, search, and recognition.

Development and Validation of Various Phenotyping Algorithms for Diabetes Mellitus Using Data from Electronic Health Records.

PubMed

Esteban, Santiago; Rodríguez Tablado, Manuel; Peper, Francisco; Mahumud, Yamila S; Ricci, Ricardo I; Kopitowski, Karin; Terrasa, Sergio

2017-01-01

Precision medicine requires extremely large samples. Electronic health records (EHR) are thought to be a cost-effective source of data for that purpose. Phenotyping algorithms help reduce classification errors, making EHR a more reliable source of information for research. Four algorithm development strategies for classifying patients according to their diabetes status (diabetics; non-diabetics; inconclusive) were tested (one codes-only algorithm; one boolean algorithm, four statistical learning algorithms and six stacked generalization meta-learners). The best performing algorithms within each strategy were tested on the validation set. The stacked generalization algorithm yielded the highest Kappa coefficient value in the validation set (0.95 95% CI 0.91, 0.98). The implementation of these algorithms allows for the exploitation of data from thousands of patients accurately, greatly reducing the costs of constructing retrospective cohorts for research.

CT liver volumetry using geodesic active contour segmentation with a level-set algorithm

NASA Astrophysics Data System (ADS)

Suzuki, Kenji; Epstein, Mark L.; Kohlbrenner, Ryan; Obajuluwa, Ademola; Xu, Jianwu; Hori, Masatoshi; Baron, Richard

2010-03-01

Automatic liver segmentation on CT images is challenging because the liver often abuts other organs of a similar density. Our purpose was to develop an accurate automated liver segmentation scheme for measuring liver volumes. We developed an automated volumetry scheme for the liver in CT based on a 5 step schema. First, an anisotropic smoothing filter was applied to portal-venous phase CT images to remove noise while preserving the liver structure, followed by an edge enhancer to enhance the liver boundary. By using the boundary-enhanced image as a speed function, a fastmarching algorithm generated an initial surface that roughly estimated the liver shape. A geodesic-active-contour segmentation algorithm coupled with level-set contour-evolution refined the initial surface so as to more precisely fit the liver boundary. The liver volume was calculated based on the refined liver surface. Hepatic CT scans of eighteen prospective liver donors were obtained under a liver transplant protocol with a multi-detector CT system. Automated liver volumes obtained were compared with those manually traced by a radiologist, used as "gold standard." The mean liver volume obtained with our scheme was 1,520 cc, whereas the mean manual volume was 1,486 cc, with the mean absolute difference of 104 cc (7.0%). CT liver volumetrics based on an automated scheme agreed excellently with "goldstandard" manual volumetrics (intra-class correlation coefficient was 0.95) with no statistically significant difference (p(F<=f)=0.32), and required substantially less completion time. Our automated scheme provides an efficient and accurate way of measuring liver volumes.

Development of sub-daily erosion and sediment transport algorithms in SWAT

USDA-ARS?s Scientific Manuscript database

New Soil and Water Assessment Tool (SWAT) algorithms for simulation of stormwater best management practices (BMPs) such as detention basins, wet ponds, sedimentation filtration ponds, and retention irrigation systems are under development for modeling small/urban watersheds. Modeling stormwater BMPs...

Superior Generalization Capability of Hardware-Learing Algorithm Developed for Self-Learning Neuron-MOS Neural Networks

NASA Astrophysics Data System (ADS)

Kondo, Shuhei; Shibata, Tadashi; Ohmi, Tadahiro

1995-02-01

We have investigated the learning performance of the hardware backpropagation (HBP) algorithm, a hardware-oriented learning algorithm developed for the self-learning architecture of neural networks constructed using neuron MOS (metal-oxide-semiconductor) transistors. The solution to finding a mirror symmetry axis in a 4×4 binary pixel array was tested by computer simulation based on the HBP algorithm. Despite the inherent restrictions imposed on the hardware-learning algorithm, HBP exhibits equivalent learning performance to that of the original backpropagation (BP) algorithm when all the pertinent parameters are optimized. Very importantly, we have found that HBP has a superior generalization capability over BP; namely, HBP exhibits higher performance in solving problems that the network has not yet learnt.

Development of a fire detection algorithm for the COMS (Communication Ocean and Meteorological Satellite)

NASA Astrophysics Data System (ADS)

Kim, Goo; Kim, Dae Sun; Lee, Yang-Won

2013-10-01

The forest fires do much damage to our life in ecological and economic aspects. South Korea is probably more liable to suffer from the forest fire because mountain area occupies more than half of land in South Korea. They have recently launched the COMS(Communication Ocean and Meteorological Satellite) which is a geostationary satellite. In this paper, we developed forest fire detection algorithm using COMS data. Generally, forest fire detection algorithm uses characteristics of 4 and 11 micrometer brightness temperature. Our algorithm additionally uses LST(Land Surface Temperature). We confirmed the result of our fire detection algorithm using statistical data of Korea Forest Service and ASTER(Advanced Spaceborne Thermal Emission and Reflection Radiometer) images. We used the data in South Korea On April 1 and 2, 2011 because there are small and big forest fires at that time. The detection rate was 80% in terms of the frequency of the forest fires and was 99% in terms of the damaged area. Considering the number of COMS's channels and its low resolution, this result is a remarkable outcome. To provide users with the result of our algorithm, we developed a smartphone application for users JSP(Java Server Page). This application can work regardless of the smartphone's operating system. This study can be unsuitable for other areas and days because we used just two days data. To improve the accuracy of our algorithm, we need analysis using long-term data as future work.

Developments in the Aerosol Layer Height Retrieval Algorithm for the Copernicus Sentinel-4/UVN Instrument

NASA Astrophysics Data System (ADS)

Nanda, Swadhin; Sanders, Abram; Veefkind, Pepijn

2016-04-01

The Sentinel-4 mission is a part of the European Commission's Copernicus programme, the goal of which is to provide geo-information to manage environmental assets, and to observe, understand and mitigate the effects of the changing climate. The Sentinel-4/UVN instrument design is motivated by the need to monitor trace gas concentrations and aerosols in the atmosphere from a geostationary orbit. The on-board instrument is a high resolution UV-VIS-NIR (UVN) spectrometer system that provides hourly radiance measurements over Europe and northern Africa with a spatial sampling of 8 km. The main application area of Sentinel-4/UVN is air quality. One of the data products that is being developed for Sentinel-4/UVN is the Aerosol Layer Height (ALH). The goal is to determine the height of aerosol plumes with a resolution of better than 0.5 - 1 km. The ALH product thus targets aerosol layers in the free troposphere, such as desert dust, volcanic ash and biomass during plumes. KNMI is assigned with the development of the Aerosol Layer Height (ALH) algorithm. Its heritage is the ALH algorithm developed by Sanders and De Haan (ATBD, 2016) for the TROPOMI instrument on board the Sentinel-5 Precursor mission that is to be launched in June or July 2016 (tentative date). The retrieval algorithm designed so far for the aerosol height product is based on the absorption characteristics of the oxygen-A band (759-770 nm). The algorithm has heritage to the ALH algorithm developed for TROPOMI on the Sentinel 5 precursor satellite. New aspects for Sentinel-4/UVN include the higher resolution (0.116 nm compared to 0.4 for TROPOMI) and hourly observation from the geostationary orbit. The algorithm uses optimal estimation to obtain a spectral fit of the reflectance across absorption band, while assuming a single uniform layer with fixed width to represent the aerosol vertical distribution. The state vector includes amongst other elements the height of this layer and its aerosol optical

A time series based sequence prediction algorithm to detect activities of daily living in smart home.

PubMed

Marufuzzaman, M; Reaz, M B I; Ali, M A M; Rahman, L F

2015-01-01

The goal of smart homes is to create an intelligent environment adapting the inhabitants need and assisting the person who needs special care and safety in their daily life. This can be reached by collecting the ADL (activities of daily living) data and further analysis within existing computing elements. In this research, a very recent algorithm named sequence prediction via enhanced episode discovery (SPEED) is modified and in order to improve accuracy time component is included. The modified SPEED or M-SPEED is a sequence prediction algorithm, which modified the previous SPEED algorithm by using time duration of appliance's ON-OFF states to decide the next state. M-SPEED discovered periodic episodes of inhabitant behavior, trained it with learned episodes, and made decisions based on the obtained knowledge. The results showed that M-SPEED achieves 96.8% prediction accuracy, which is better than other time prediction algorithms like PUBS, ALZ with temporal rules and the previous SPEED. Since human behavior shows natural temporal patterns, duration times can be used to predict future events more accurately. This inhabitant activity prediction system will certainly improve the smart homes by ensuring safety and better care for elderly and handicapped people.

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

Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters.

PubMed

Wang, Jiao; Deng, Zhiqiang

2017-06-01

A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.

Ocean Observations with EOS/MODIS: Algorithm Development and Post Launch Studies

NASA Technical Reports Server (NTRS)

Gordon, Howard R.

1997-01-01

The following accomplishments were made during the present reporting period: (1) We expanded our new method, for identifying the presence of absorbing aerosols and simultaneously performing atmospheric correction, to the point where it could be added as a subroutine to the MODIS water-leaving radiance algorithm; (2) We successfully acquired micro pulse lidar (MPL) data at sea during a cruise in February; (3) We developed a water-leaving radiance algorithm module for an approximate correction of the MODIS instrument polarization sensitivity; and (4) We participated in one cruise to the Gulf of Maine, a well known region for mesoscale coccolithophore blooms. We measured coccolithophore abundance, production and optical properties.

Ocean observations with EOS/MODIS: Algorithm Development and Post Launch Studies

NASA Technical Reports Server (NTRS)

Gordon, Howard R.

1998-01-01

Significant accomplishments made during the present reporting period: (1) We expanded our "spectral-matching" algorithm (SMA), for identifying the presence of absorbing aerosols and simultaneously performing atmospheric correction and derivation of the ocean's bio-optical parameters, to the point where it could be added as a subroutine to the MODIS water-leaving radiance algorithm; (2) A modification to the SMA that does not require detailed aerosol models has been developed. This is important as the requirement for realistic aerosol models has been a weakness of the SMA; and (3) We successfully acquired micro pulse lidar data in a Saharan dust outbreak during ACE-2 in the Canary Islands.

Roadmap of Advanced GNC and Image Processing Algorithms for Fully Autonomous MSR-Like Rendezvous Missions

NASA Astrophysics Data System (ADS)

Strippoli, L. S.; Gonzalez-Arjona, D. G.

2018-04-01

GMV extensively worked in many activities aimed at developing, validating, and verifying up to TRL-6 advanced GNC and IP algorithms for Mars Sample Return rendezvous working under different ESA contracts on the development of advanced algorithms for VBN sensor.

Collaborative workbench for cyberinfrastructure to accelerate science algorithm development

NASA Astrophysics Data System (ADS)

Ramachandran, R.; Maskey, M.; Kuo, K.; Lynnes, C.

2013-12-01

There are significant untapped resources for information and knowledge creation within the Earth Science community in the form of data, algorithms, services, analysis workflows or scripts, and the related knowledge about these resources. Despite the huge growth in social networking and collaboration platforms, these resources often reside on an investigator's workstation or laboratory and are rarely shared. A major reason for this is that there are very few scientific collaboration platforms, and those that exist typically require the use of a new set of analysis tools and paradigms to leverage the shared infrastructure. As a result, adoption of these collaborative platforms for science research is inhibited by the high cost to an individual scientist of switching from his or her own familiar environment and set of tools to a new environment and tool set. This presentation will describe an ongoing project developing an Earth Science Collaborative Workbench (CWB). The CWB approach will eliminate this barrier by augmenting a scientist's current research environment and tool set to allow him or her to easily share diverse data and algorithms. The CWB will leverage evolving technologies such as commodity computing and social networking to design an architecture for scalable collaboration that will support the emerging vision of an Earth Science Collaboratory. The CWB is being implemented on the robust and open source Eclipse framework and will be compatible with widely used scientific analysis tools such as IDL. The myScience Catalog built into CWB will capture and track metadata and provenance about data and algorithms for the researchers in a non-intrusive manner with minimal overhead. Seamless interfaces to multiple Cloud services will support sharing algorithms, data, and analysis results, as well as access to storage and computer resources. A Community Catalog will track the use of shared science artifacts and manage collaborations among researchers.

PCTFPeval: a web tool for benchmarking newly developed algorithms for predicting cooperative transcription factor pairs in yeast.

PubMed

Lai, Fu-Jou; Chang, Hong-Tsun; Wu, Wei-Sheng

2015-01-01

Computational identification of cooperative transcription factor (TF) pairs helps understand the combinatorial regulation of gene expression in eukaryotic cells. Many advanced algorithms have been proposed to predict cooperative TF pairs in yeast. However, it is still difficult to conduct a comprehensive and objective performance comparison of different algorithms because of lacking sufficient performance indices and adequate overall performance scores. To solve this problem, in our previous study (published in BMC Systems Biology 2014), we adopted/proposed eight performance indices and designed two overall performance scores to compare the performance of 14 existing algorithms for predicting cooperative TF pairs in yeast. Most importantly, our performance comparison framework can be applied to comprehensively and objectively evaluate the performance of a newly developed algorithm. However, to use our framework, researchers have to put a lot of effort to construct it first. To save researchers time and effort, here we develop a web tool to implement our performance comparison framework, featuring fast data processing, a comprehensive performance comparison and an easy-to-use web interface. The developed tool is called PCTFPeval (Predicted Cooperative TF Pair evaluator), written in PHP and Python programming languages. The friendly web interface allows users to input a list of predicted cooperative TF pairs from their algorithm and select (i) the compared algorithms among the 15 existing algorithms, (ii) the performance indices among the eight existing indices, and (iii) the overall performance scores from two possible choices. The comprehensive performance comparison results are then generated in tens of seconds and shown as both bar charts and tables. The original comparison results of each compared algorithm and each selected performance index can be downloaded as text files for further analyses. Allowing users to select eight existing performance indices and 15

PCTFPeval: a web tool for benchmarking newly developed algorithms for predicting cooperative transcription factor pairs in yeast

PubMed Central

2015-01-01

Background Computational identification of cooperative transcription factor (TF) pairs helps understand the combinatorial regulation of gene expression in eukaryotic cells. Many advanced algorithms have been proposed to predict cooperative TF pairs in yeast. However, it is still difficult to conduct a comprehensive and objective performance comparison of different algorithms because of lacking sufficient performance indices and adequate overall performance scores. To solve this problem, in our previous study (published in BMC Systems Biology 2014), we adopted/proposed eight performance indices and designed two overall performance scores to compare the performance of 14 existing algorithms for predicting cooperative TF pairs in yeast. Most importantly, our performance comparison framework can be applied to comprehensively and objectively evaluate the performance of a newly developed algorithm. However, to use our framework, researchers have to put a lot of effort to construct it first. To save researchers time and effort, here we develop a web tool to implement our performance comparison framework, featuring fast data processing, a comprehensive performance comparison and an easy-to-use web interface. Results The developed tool is called PCTFPeval (Predicted Cooperative TF Pair evaluator), written in PHP and Python programming languages. The friendly web interface allows users to input a list of predicted cooperative TF pairs from their algorithm and select (i) the compared algorithms among the 15 existing algorithms, (ii) the performance indices among the eight existing indices, and (iii) the overall performance scores from two possible choices. The comprehensive performance comparison results are then generated in tens of seconds and shown as both bar charts and tables. The original comparison results of each compared algorithm and each selected performance index can be downloaded as text files for further analyses. Conclusions Allowing users to select eight

Item Selection for the Development of Short Forms of Scales Using an Ant Colony Optimization Algorithm

ERIC Educational Resources Information Center

Leite, Walter L.; Huang, I-Chan; Marcoulides, George A.

2008-01-01

This article presents the use of an ant colony optimization (ACO) algorithm for the development of short forms of scales. An example 22-item short form is developed for the Diabetes-39 scale, a quality-of-life scale for diabetes patients, using a sample of 265 diabetes patients. A simulation study comparing the performance of the ACO algorithm and…

Development of algorithms for building inventory compilation through remote sensing and statistical inferencing

NASA Astrophysics Data System (ADS)

Sarabandi, Pooya

Building inventories are one of the core components of disaster vulnerability and loss estimations models, and as such, play a key role in providing decision support for risk assessment, disaster management and emergency response efforts. In may parts of the world inclusive building inventories, suitable for the use in catastrophe models cannot be found. Furthermore, there are serious shortcomings in the existing building inventories that include incomplete or out-dated information on critical attributes as well as missing or erroneous values for attributes. In this dissertation a set of methodologies for updating spatial and geometric information of buildings from single and multiple high-resolution optical satellite images are presented. Basic concepts, terminologies and fundamentals of 3-D terrain modeling from satellite images are first introduced. Different sensor projection models are then presented and sources of optical noise such as lens distortions are discussed. An algorithm for extracting height and creating 3-D building models from a single high-resolution satellite image is formulated. The proposed algorithm is a semi-automated supervised method capable of extracting attributes such as longitude, latitude, height, square footage, perimeter, irregularity index and etc. The associated errors due to the interactive nature of the algorithm are quantified and solutions for minimizing the human-induced errors are proposed. The height extraction algorithm is validated against independent survey data and results are presented. The validation results show that an average height modeling accuracy of 1.5% can be achieved using this algorithm. Furthermore, concept of cross-sensor data fusion for the purpose of 3-D scene reconstruction using quasi-stereo images is developed in this dissertation. The developed algorithm utilizes two or more single satellite images acquired from different sensors and provides the means to construct 3-D building models in a more

Development and Evaluation of the National Cancer Institute's Dietary Screener Questionnaire Scoring Algorithms.

PubMed

Thompson, Frances E; Midthune, Douglas; Kahle, Lisa; Dodd, Kevin W

2017-06-01

Background: Methods for improving the utility of short dietary assessment instruments are needed. Objective: We sought to describe the development of the NHANES Dietary Screener Questionnaire (DSQ) and its scoring algorithms and performance. Methods: The 19-item DSQ assesses intakes of fruits and vegetables, whole grains, added sugars, dairy, fiber, and calcium. Two nonconsecutive 24-h dietary recalls and the DSQ were administered in NHANES 2009-2010 to respondents aged 2-69 y ( n = 7588). The DSQ frequency responses, coupled with sex- and age-specific portion size information, were regressed on intake from 24-h recalls by using the National Cancer Institute usual intake method to obtain scoring algorithms to estimate mean and prevalences of reaching 2 a priori threshold levels. The resulting scoring algorithms were applied to the DSQ and compared with intakes estimated with the 24-h recall data only. The stability of the derived scoring algorithms was evaluated in repeated sampling. Finally, scoring algorithms were applied to screener data, and these estimates were compared with those from multiple 24-h recalls in 3 external studies. Results: The DSQ and its scoring algorithms produced estimates of mean intake and prevalence that agreed closely with those from multiple 24-h recalls. The scoring algorithms were stable in repeated sampling. Differences in the means were <2%; differences in prevalence were <16%. In other studies, agreement between screener and 24-h recall estimates in fruit and vegetable intake varied. For example, among men in 2 studies, estimates from the screener were significantly lower than the 24-h recall estimates (3.2 compared with 3.8 and 3.2 compared with 4.1). In the third study, agreement between the screener and 24-h recall estimates were close among both men (3.2 compared with 3.1) and women (2.6 compared with 2.5). Conclusions: This approach to developing scoring algorithms is an advance in the use of screeners. However, because these

Development of a job rotation scheduling algorithm for minimizing accumulated work load per body parts.

PubMed

Song, JooBong; Lee, Chaiwoo; Lee, WonJung; Bahn, Sangwoo; Jung, ChanJu; Yun, Myung Hwan

2015-01-01

For the successful implementation of job rotation, jobs should be scheduled systematically so that physical workload is evenly distributed with the use of various body parts. However, while the potential benefits are widely recognized by research and industry, there is still a need for a more effective and efficient algorithm that considers multiple work-related factors in job rotation scheduling. This study suggests a type of job rotation algorithm that aims to minimize musculoskeletal disorders with the approach of decreasing the overall workload. Multiple work characteristics are evaluated as inputs to the proposed algorithm. Important factors, such as physical workload on specific body parts, working height, involvement of heavy lifting, and worker characteristics such as physical disorders, are included in the algorithm. For evaluation of the overall workload in a given workplace, an objective function was defined to aggregate the scores from the individual factors. A case study, where the algorithm was applied at a workplace, is presented with an examination on its applicability and effectiveness. With the application of the suggested algorithm in case study, the value of the final objective function, which is the weighted sum of the workload in various body parts, decreased by 71.7% when compared to a typical sequential assignment and by 84.9% when compared to a single job assignment, which is doing one job all day. An algorithm was developed using the data from the ergonomic evaluation tool used in the plant and from the known factors related to workload. The algorithm was developed so that it can be efficiently applied with a small amount of required inputs, while covering a wide range of work-related factors. A case study showed that the algorithm was beneficial in determining a job rotation schedule aimed at minimizing workload across body parts.

Hip and Wrist Accelerometer Algorithms for Free-Living Behavior Classification.

PubMed

Ellis, Katherine; Kerr, Jacqueline; Godbole, Suneeta; Staudenmayer, John; Lanckriet, Gert

2016-05-01

Accelerometers are a valuable tool for objective measurement of physical activity (PA). Wrist-worn devices may improve compliance over standard hip placement, but more research is needed to evaluate their validity for measuring PA in free-living settings. Traditional cut-point methods for accelerometers can be inaccurate and need testing in free living with wrist-worn devices. In this study, we developed and tested the performance of machine learning (ML) algorithms for classifying PA types from both hip and wrist accelerometer data. Forty overweight or obese women (mean age = 55.2 ± 15.3 yr; BMI = 32.0 ± 3.7) wore two ActiGraph GT3X+ accelerometers (right hip, nondominant wrist; ActiGraph, Pensacola, FL) for seven free-living days. Wearable cameras captured ground truth activity labels. A classifier consisting of a random forest and hidden Markov model classified the accelerometer data into four activities (sitting, standing, walking/running, and riding in a vehicle). Free-living wrist and hip ML classifiers were compared with each other, with traditional accelerometer cut points, and with an algorithm developed in a laboratory setting. The ML classifier obtained average values of 89.4% and 84.6% balanced accuracy over the four activities using the hip and wrist accelerometer, respectively. In our data set with average values of 28.4 min of walking or running per day, the ML classifier predicted average values of 28.5 and 24.5 min of walking or running using the hip and wrist accelerometer, respectively. Intensity-based cut points and the laboratory algorithm significantly underestimated walking minutes. Our results demonstrate the superior performance of our PA-type classification algorithm, particularly in comparison with traditional cut points. Although the hip algorithm performed better, additional compliance achieved with wrist devices might justify using a slightly lower performing algorithm.

Automated isotope identification algorithm using artificial neural networks

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

Kamuda, Mark; Stinnett, Jacob; Sullivan, Clair

There is a need to develop an algorithm that can determine the relative activities of radio-isotopes in a large dataset of low-resolution gamma-ray spectra that contains a mixture of many radio-isotopes. Low-resolution gamma-ray spectra that contain mixtures of radio-isotopes often exhibit feature over-lap, requiring algorithms that can analyze these features when overlap occurs. While machine learning and pattern recognition algorithms have shown promise for the problem of radio-isotope identification, their ability to identify and quantify mixtures of radio-isotopes has not been studied. Because machine learning algorithms use abstract features of the spectrum, such as the shape of overlapping peaks andmore » Compton continuum, they are a natural choice for analyzing radio-isotope mixtures. An artificial neural network (ANN) has be trained to calculate the relative activities of 32 radio-isotopes in a spectrum. Furthermore, the ANN is trained with simulated gamma-ray spectra, allowing easy expansion of the library of target radio-isotopes. In this paper we present our initial algorithms based on an ANN and evaluate them against a series measured and simulated spectra.« less

Automated isotope identification algorithm using artificial neural networks

DOE PAGES

Kamuda, Mark; Stinnett, Jacob; Sullivan, Clair

2017-04-12

There is a need to develop an algorithm that can determine the relative activities of radio-isotopes in a large dataset of low-resolution gamma-ray spectra that contains a mixture of many radio-isotopes. Low-resolution gamma-ray spectra that contain mixtures of radio-isotopes often exhibit feature over-lap, requiring algorithms that can analyze these features when overlap occurs. While machine learning and pattern recognition algorithms have shown promise for the problem of radio-isotope identification, their ability to identify and quantify mixtures of radio-isotopes has not been studied. Because machine learning algorithms use abstract features of the spectrum, such as the shape of overlapping peaks andmore » Compton continuum, they are a natural choice for analyzing radio-isotope mixtures. An artificial neural network (ANN) has be trained to calculate the relative activities of 32 radio-isotopes in a spectrum. Furthermore, the ANN is trained with simulated gamma-ray spectra, allowing easy expansion of the library of target radio-isotopes. In this paper we present our initial algorithms based on an ANN and evaluate them against a series measured and simulated spectra.« less

Algorithm and code development for unsteady three-dimensional Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Obayashi, Shigeru

1994-01-01

Aeroelastic tests require extensive cost and risk. An aeroelastic wind-tunnel experiment is an order of magnitude more expensive than a parallel experiment involving only aerodynamics. By complementing the wind-tunnel experiments with numerical simulations, the overall cost of the development of aircraft can be considerably reduced. In order to accurately compute aeroelastic phenomenon it is necessary to solve the unsteady Euler/Navier-Stokes equations simultaneously with the structural equations of motion. These equations accurately describe the flow phenomena for aeroelastic applications. At ARC a code, ENSAERO, is being developed for computing the unsteady aerodynamics and aeroelasticity of aircraft, and it solves the Euler/Navier-Stokes equations. The purpose of this cooperative agreement was to enhance ENSAERO in both algorithm and geometric capabilities. During the last five years, the algorithms of the code have been enhanced extensively by using high-resolution upwind algorithms and efficient implicit solvers. The zonal capability of the code has been extended from a one-to-one grid interface to a mismatching unsteady zonal interface. The geometric capability of the code has been extended from a single oscillating wing case to a full-span wing-body configuration with oscillating control surfaces. Each time a new capability was added, a proper validation case was simulated, and the capability of the code was demonstrated.

Refinement and evaluation of helicopter real-time self-adaptive active vibration controller algorithms

NASA Technical Reports Server (NTRS)

Davis, M. W.

1984-01-01

A Real-Time Self-Adaptive (RTSA) active vibration controller was used as the framework in developing a computer program for a generic controller that can be used to alleviate helicopter vibration. Based upon on-line identification of system parameters, the generic controller minimizes vibration in the fuselage by closed-loop implementation of higher harmonic control in the main rotor system. The new generic controller incorporates a set of improved algorithms that gives the capability to readily define many different configurations by selecting one of three different controller types (deterministic, cautious, and dual), one of two linear system models (local and global), and one or more of several methods of applying limits on control inputs (external and/or internal limits on higher harmonic pitch amplitude and rate). A helicopter rotor simulation analysis was used to evaluate the algorithms associated with the alternative controller types as applied to the four-bladed H-34 rotor mounted on the NASA Ames Rotor Test Apparatus (RTA) which represents the fuselage. After proper tuning all three controllers provide more effective vibration reduction and converge more quickly and smoothly with smaller control inputs than the initial RTSA controller (deterministic with external pitch-rate limiting). It is demonstrated that internal limiting of the control inputs a significantly improves the overall performance of the deterministic controller.

Optimal coordinated voltage control in active distribution networks using backtracking search algorithm.

PubMed

Tengku Hashim, Tengku Juhana; Mohamed, Azah

2017-01-01

The growing interest in distributed generation (DG) in recent years has led to a number of generators connected to a distribution system. The integration of DGs in a distribution system has resulted in a network known as active distribution network due to the existence of bidirectional power flow in the system. Voltage rise issue is one of the predominantly important technical issues to be addressed when DGs exist in an active distribution network. This paper presents the application of the backtracking search algorithm (BSA), which is relatively new optimisation technique to determine the optimal settings of coordinated voltage control in a distribution system. The coordinated voltage control considers power factor, on-load tap-changer and generation curtailment control to manage voltage rise issue. A multi-objective function is formulated to minimise total losses and voltage deviation in a distribution system. The proposed BSA is compared with that of particle swarm optimisation (PSO) so as to evaluate its effectiveness in determining the optimal settings of power factor, tap-changer and percentage active power generation to be curtailed. The load flow algorithm from MATPOWER is integrated in the MATLAB environment to solve the multi-objective optimisation problem. Both the BSA and PSO optimisation techniques have been tested on a radial 13-bus distribution system and the results show that the BSA performs better than PSO by providing better fitness value and convergence rate.

Implementation on Landsat Data of a Simple Cloud Mask Algorithm Developed for MODIS Land Bands

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Wilson, Michael J.; Varnai, Tamas

2010-01-01

This letter assesses the performance on Landsat-7 images of a modified version of a cloud masking algorithm originally developed for clear-sky compositing of Moderate Resolution Imaging Spectroradiometer (MODIS) images at northern mid-latitudes. While data from recent Landsat missions include measurements at thermal wavelengths, and such measurements are also planned for the next mission, thermal tests are not included in the suggested algorithm in its present form to maintain greater versatility and ease of use. To evaluate the masking algorithm we take advantage of the availability of manual (visual) cloud masks developed at USGS for the collection of Landsat scenes used here. As part of our evaluation we also include the Automated Cloud Cover Assesment (ACCA) algorithm that includes thermal tests and is used operationally by the Landsat-7 mission to provide scene cloud fractions, but no cloud masks. We show that the suggested algorithm can perform about as well as ACCA both in terms of scene cloud fraction and pixel-level cloud identification. Specifically, we find that the algorithm gives an error of 1.3% for the scene cloud fraction of 156 scenes, and a root mean square error of 7.2%, while it agrees with the manual mask for 93% of the pixels, figures very similar to those from ACCA (1.2%, 7.1%, 93.7%).

Brain-Inspired Constructive Learning Algorithms with Evolutionally Additive Nonlinear Neurons

NASA Astrophysics Data System (ADS)

Fang, Le-Heng; Lin, Wei; Luo, Qiang

In this article, inspired partially by the physiological evidence of brain’s growth and development, we developed a new type of constructive learning algorithm with evolutionally additive nonlinear neurons. The new algorithms have remarkable ability in effective regression and accurate classification. In particular, the algorithms are able to sustain a certain reduction of the loss function when the dynamics of the trained network are bogged down in the vicinity of the local minima. The algorithm augments the neural network by adding only a few connections as well as neurons whose activation functions are nonlinear, nonmonotonic, and self-adapted to the dynamics of the loss functions. Indeed, we analytically demonstrate the reduction dynamics of the algorithm for different problems, and further modify the algorithms so as to obtain an improved generalization capability for the augmented neural networks. Finally, through comparing with the classical algorithm and architecture for neural network construction, we show that our constructive learning algorithms as well as their modified versions have better performances, such as faster training speed and smaller network size, on several representative benchmark datasets including the MNIST dataset for handwriting digits.

Development of Online Cognitive and Algorithm Tests as Assessment Tools in Introductory Computer Science Courses

ERIC Educational Resources Information Center

Avancena, Aimee Theresa; Nishihara, Akinori; Vergara, John Paul

2012-01-01

This paper presents the online cognitive and algorithm tests, which were developed in order to determine if certain cognitive factors and fundamental algorithms correlate with the performance of students in their introductory computer science course. The tests were implemented among Management Information Systems majors from the Philippines and…

SMMR Simulator radiative transfer calibration model. 2: Algorithm development

NASA Technical Reports Server (NTRS)

Link, S.; Calhoon, C.; Krupp, B.

1980-01-01

Passive microwave measurements performed from Earth orbit can be used to provide global data on a wide range of geophysical and meteorological phenomena. A Scanning Multichannel Microwave Radiometer (SMMR) is being flown on the Nimbus-G satellite. The SMMR Simulator duplicates the frequency bands utilized in the spacecraft instruments through an amalgamate of radiometer systems. The algorithm developed utilizes data from the fall 1978 NASA CV-990 Nimbus-G underflight test series and subsequent laboratory testing.

Space-based Doppler lidar sampling strategies: Algorithm development and simulated observation experiments

NASA Technical Reports Server (NTRS)

Emmitt, G. D.; Wood, S. A.; Morris, M.

1990-01-01

Lidar Atmospheric Wind Sounder (LAWS) Simulation Models (LSM) were developed to evaluate the potential impact of global wind observations on the basic understanding of the Earth's atmosphere and on the predictive skills of current forecast models (GCM and regional scale). Fully integrated top to bottom LAWS Simulation Models for global and regional scale simulations were developed. The algorithm development incorporated the effects of aerosols, water vapor, clouds, terrain, and atmospheric turbulence into the models. Other additions include a new satellite orbiter, signal processor, line of sight uncertainty model, new Multi-Paired Algorithm and wind error analysis code. An atmospheric wind field library containing control fields, meteorological fields, phenomena fields, and new European Center for Medium Range Weather Forecasting (ECMWF) data was also added. The LSM was used to address some key LAWS issues and trades such as accuracy and interpretation of LAWS information, data density, signal strength, cloud obscuration, and temporal data resolution.

Developing the science product algorithm testbed for Chinese next-generation geostationary meteorological satellites: Fengyun-4 series

NASA Astrophysics Data System (ADS)

Min, Min; Wu, Chunqiang; Li, Chuan; Liu, Hui; Xu, Na; Wu, Xiao; Chen, Lin; Wang, Fu; Sun, Fenglin; Qin, Danyu; Wang, Xi; Li, Bo; Zheng, Zhaojun; Cao, Guangzhen; Dong, Lixin

2017-08-01

Fengyun-4A (FY-4A), the first of the Chinese next-generation geostationary meteorological satellites, launched in 2016, offers several advances over the FY-2: more spectral bands, faster imaging, and infrared hyperspectral measurements. To support the major objective of developing the prototypes of FY-4 science algorithms, two science product algorithm testbeds for imagers and sounders have been developed by the scientists in the FY-4 Algorithm Working Group (AWG). Both testbeds, written in FORTRAN and C programming languages for Linux or UNIX systems, have been tested successfully by using Intel/g compilers. Some important FY-4 science products, including cloud mask, cloud properties, and temperature profiles, have been retrieved successfully through using a proxy imager, Himawari-8/Advanced Himawari Imager (AHI), and sounder data, obtained from the Atmospheric InfraRed Sounder, thus demonstrating their robustness. In addition, in early 2016, the FY-4 AWG was developed based on the imager testbed—a near real-time processing system for Himawari-8/AHI data for use by Chinese weather forecasters. Consequently, robust and flexible science product algorithm testbeds have provided essential and productive tools for popularizing FY-4 data and developing substantial improvements in FY-4 products.

Algorithm Development and Validation for Satellite-Derived Distributions of DOC and CDOM in the US Middle Atlantic Bight

NASA Technical Reports Server (NTRS)

Mannino, Antonio; Russ, Mary E.; Hooker, Stanford B.

2007-01-01

In coastal ocean waters, distributions of dissolved organic carbon (DOC) and chromophoric dissolved organic matter (CDOM) vary seasonally and interannually due to multiple source inputs and removal processes. We conducted several oceanographic cruises within the continental margin of the U.S. Middle Atlantic Bight (MAB) to collect field measurements in order to develop algorithms to retrieve CDOM and DOC from NASA's MODIS-Aqua and SeaWiFS satellite sensors. In order to develop empirical algorithms for CDOM and DOC, we correlated the CDOM absorption coefficient (a(sub cdom)) with in situ radiometry (remote sensing reflectance, Rrs, band ratios) and then correlated DOC to Rrs band ratios through the CDOM to DOC relationships. Our validation analyses demonstrate successful retrieval of DOC and CDOM from coastal ocean waters using the MODIS-Aqua and SeaWiFS satellite sensors with mean absolute percent differences from field measurements of < 9 %for DOC, 20% for a(sub cdom)(355)1,6 % for a(sub cdom)(443), and 12% for the CDOM spectral slope. To our knowledge, the algorithms presented here represent the first validated algorithms for satellite retrieval of a(sub cdom) DOC, and CDOM spectral slope in the coastal ocean. The satellite-derived DOC and a(sub cdom) products demonstrate the seasonal net ecosystem production of DOC and photooxidation of CDOM from spring to fall. With accurate satellite retrievals of CDOM and DOC, we will be able to apply satellite observations to investigate interannual and decadal-scale variability in surface CDOM and DOC within continental margins and monitor impacts of climate change and anthropogenic activities on coastal ecosystems.

Advanced synthetic image generation models and their application to multi/hyperspectral algorithm development

NASA Astrophysics Data System (ADS)

Schott, John R.; Brown, Scott D.; Raqueno, Rolando V.; Gross, Harry N.; Robinson, Gary

1999-01-01

The need for robust image data sets for algorithm development and testing has prompted the consideration of synthetic imagery as a supplement to real imagery. The unique ability of synthetic image generation (SIG) tools to supply per-pixel truth allows algorithm writers to test difficult scenarios that would require expensive collection and instrumentation efforts. In addition, SIG data products can supply the user with `actual' truth measurements of the entire image area that are not subject to measurement error thereby allowing the user to more accurately evaluate the performance of their algorithm. Advanced algorithms place a high demand on synthetic imagery to reproduce both the spectro-radiometric and spatial character observed in real imagery. This paper describes a synthetic image generation model that strives to include the radiometric processes that affect spectral image formation and capture. In particular, it addresses recent advances in SIG modeling that attempt to capture the spatial/spectral correlation inherent in real images. The model is capable of simultaneously generating imagery from a wide range of sensors allowing it to generate daylight, low-light-level and thermal image inputs for broadband, multi- and hyper-spectral exploitation algorithms.

Identifying patients likely to have atopic dermatitis: development of a pilot algorithm.

PubMed

Farage, Miranda A; Bowtell, Philip; Katsarou, Alexandra

2010-01-01

A quick method to distinguish people who are predisposed to skin complaints would be useful in a variety of fields. Certain subgroups, such as people with atopic dermatitis, might be more susceptible to skin irritation than the typical consumer and may be more likely to report product-related complaints. To develop a rapid, questionnaire-based algorithm to predict whether or not individuals who report skin complaints have atopic dermatitis. A 9-item questionnaire on self-perceived skin sensitivity and product categories reportedly associated with skin reactions was administered to two groups of patients from a dermatology clinic: one with clinically diagnosed, active atopic dermatitis (n = 25) and a control group of patients with dermatologic complaints unrelated to atopic dermatitis (n = 25). Questionnaire responses were correlated with the patients' clinical diagnoses in order to derive the minimum number of questions needed to best predict the patients' original diagnoses. We demonstrated that responses to a sequence of three targeted questions related to self-perceived skin sensitivity, preference for hypoallergenic products, and reactions to or avoidance of alpha-hydroxy acids were highly predictive of atopic dermatitis among a population of dermatology clinic patients. The predictive algorithm concept may be useful in postmarketing surveillance programs to rapidly assess the possible status of consumers who report frequent or persistent product-related complaints. Further refinement and validation of this concept is planned with samples drawn from the general population and from consumers who report skin complaints associated with personal products.

Remote Sensing of Ocean Color in the Arctic: Algorithm Development and Comparative Validation. Chapter 9

NASA Technical Reports Server (NTRS)

Cota, Glenn F.

2001-01-01

The overall goal of this effort is to acquire a large bio-optical database, encompassing most environmental variability in the Arctic, to develop algorithms for phytoplankton biomass and production and other optically active constituents. A large suite of bio-optical and biogeochemical observations have been collected in a variety of high latitude ecosystems at different seasons. The Ocean Research Consortium of the Arctic (ORCA) is a collaborative effort between G.F. Cota of Old Dominion University (ODU), W.G. Harrison and T. Platt of the Bedford Institute of Oceanography (BIO), S. Sathyendranath of Dalhousie University and S. Saitoh of Hokkaido University. ORCA has now conducted 12 cruises and collected over 500 in-water optical profiles plus a variety of ancillary data. Observational suites typically include apparent optical properties (AOPs), inherent optical property (IOPs), and a variety of ancillary observations including sun photometry, biogeochemical profiles, and productivity measurements. All quality-assured data have been submitted to NASA's SeaWIFS Bio-Optical Archive and Storage System (SeaBASS) data archive. Our algorithm development efforts address most of the potential bio-optical data products for the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and GLI, and provides validation for a specific areas of concern, i.e., high latitudes and coastal waters.

Development and Implementation of a Hardware In-the-Loop Test Bed for Unmanned Aerial Vehicle Control Algorithms

NASA Technical Reports Server (NTRS)

Nyangweso, Emmanuel; Bole, Brian

2014-01-01

Successful prediction and management of battery life using prognostic algorithms through ground and flight tests is important for performance evaluation of electrical systems. This paper details the design of test beds suitable for replicating loading profiles that would be encountered in deployed electrical systems. The test bed data will be used to develop and validate prognostic algorithms for predicting battery discharge time and battery failure time. Online battery prognostic algorithms will enable health management strategies. The platform used for algorithm demonstration is the EDGE 540T electric unmanned aerial vehicle (UAV). The fully designed test beds developed and detailed in this paper can be used to conduct battery life tests by controlling current and recording voltage and temperature to develop a model that makes a prediction of end-of-charge and end-of-life of the system based on rapid state of health (SOH) assessment.

Development of adaptive noise reduction filter algorithm for pediatric body images in a multi-detector CT

NASA Astrophysics Data System (ADS)

Nishimaru, Eiji; Ichikawa, Katsuhiro; Okita, Izumi; Ninomiya, Yuuji; Tomoshige, Yukihiro; Kurokawa, Takehiro; Ono, Yutaka; Nakamura, Yuko; Suzuki, Masayuki

2008-03-01

Recently, several kinds of post-processing image filters which reduce the noise of computed tomography (CT) images have been proposed. However, these image filters are mostly for adults. Because these are not very effective in small (< 20 cm) display fields of view (FOV), we cannot use them for pediatric body images (e.g., premature babies and infant children). We have developed a new noise reduction filter algorithm for pediatric body CT images. This algorithm is based on a 3D post-processing in which the output pixel values are calculated by nonlinear interpolation in z-directions on original volumetric-data-sets. This algorithm does not need the in-plane (axial plane) processing, so the spatial resolution does not change. From the phantom studies, our algorithm could reduce SD up to 40% without affecting the spatial resolution of x-y plane and z-axis, and improved the CNR up to 30%. This newly developed filter algorithm will be useful for the diagnosis and radiation dose reduction of the pediatric body CT images.

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).

Development and evaluation of a predictive algorithm for telerobotic task complexity

NASA Technical Reports Server (NTRS)

Gernhardt, M. L.; Hunter, R. C.; Hedgecock, J. C.; Stephenson, A. G.

1993-01-01

There is a wide range of complexity in the various telerobotic servicing tasks performed in subsea, space, and hazardous material handling environments. Experience with telerobotic servicing has evolved into a knowledge base used to design tasks to be 'telerobot friendly.' This knowledge base generally resides in a small group of people. Written documentation and requirements are limited in conveying this knowledge base to serviceable equipment designers and are subject to misinterpretation. A mathematical model of task complexity based on measurable task parameters and telerobot performance characteristics would be a valuable tool to designers and operational planners. Oceaneering Space Systems and TRW have performed an independent research and development project to develop such a tool for telerobotic orbital replacement unit (ORU) exchange. This algorithm was developed to predict an ORU exchange degree of difficulty rating (based on the Cooper-Harper rating used to assess piloted operations). It is based on measurable parameters of the ORU, attachment receptacle and quantifiable telerobotic performance characteristics (e.g., link length, joint ranges, positional accuracy, tool lengths, number of cameras, and locations). The resulting algorithm can be used to predict task complexity as the ORU parameters, receptacle parameters, and telerobotic characteristics are varied.

Advancements in the Development of an Operational Lightning Jump Algorithm for GOES-R GLM

NASA Technical Reports Server (NTRS)

Shultz, Chris; Petersen, Walter; Carey, Lawrence

2011-01-01

Rapid increases in total lightning have been shown to precede the manifestation of severe weather at the surface. These rapid increases have been termed lightning jumps, and are the current focus of algorithm development for the GOES-R Geostationary Lightning Mapper (GLM). Recent lightning jump algorithm work has focused on evaluation of algorithms in three additional regions of the country, as well as, markedly increasing the number of thunderstorms in order to evaluate the each algorithm s performance on a larger population of storms. Lightning characteristics of just over 600 thunderstorms have been studied over the past four years. The 2 lightning jump algorithm continues to show the most promise for an operational lightning jump algorithm, with a probability of detection of 82%, a false alarm rate of 35%, a critical success index of 57%, and a Heidke Skill Score of 0.73 on the entire population of thunderstorms. Average lead time for the 2 algorithm on all severe weather is 21.15 minutes, with a standard deviation of +/- 14.68 minutes. Looking at tornadoes alone, the average lead time is 18.71 minutes, with a standard deviation of +/-14.88 minutes. Moreover, removing the 2 lightning jumps that occur after a jump has been detected, and before severe weather is detected at the ground, the 2 lightning jump algorithm s false alarm rate drops from 35% to 21%. Cold season, low topped, and tropical environments cause problems for the 2 lightning jump algorithm, due to their relative dearth in lightning as compared to a supercellular or summertime airmass thunderstorm environment.

Algorithm Development for the Multi-Fluid Plasma Model

DTIC Science & Technology

2011-05-30

392, Sep 1995. [13] L Chacon , DC Barnes, DA Knoll, and GH Miley. An implicit energy- conservative 2D Fokker-Planck algorithm. Journal of Computational...Physics, 157(2):618–653, 2000. [14] L Chacon , DC Barnes, DA Knoll, and GH Miley. An implicit energy- conservative 2D Fokker-Planck algorithm - II

An algorithm to estimate aircraft cruise black carbon emissions for use in developing a cruise emissions inventory.

PubMed

Peck, Jay; Oluwole, Oluwayemisi O; Wong, Hsi-Wu; Miake-Lye, Richard C

2013-03-01

To provide accurate input parameters to the large-scale global climate simulation models, an algorithm was developed to estimate the black carbon (BC) mass emission index for engines in the commercial fleet at cruise. Using a high-dimensional model representation (HDMR) global sensitivity analysis, relevant engine specification/operation parameters were ranked, and the most important parameters were selected. Simple algebraic formulas were then constructed based on those important parameters. The algorithm takes the cruise power (alternatively, fuel flow rate), altitude, and Mach number as inputs, and calculates BC emission index for a given engine/airframe combination using the engine property parameters, such as the smoke number, available in the International Civil Aviation Organization (ICAO) engine certification databank. The algorithm can be interfaced with state-of-the-art aircraft emissions inventory development tools, and will greatly improve the global climate simulations that currently use a single fleet average value for all airplanes. An algorithm to estimate the cruise condition black carbon emission index for commercial aircraft engines was developed. Using the ICAO certification data, the algorithm can evaluate the black carbon emission at given cruise altitude and speed.

GOES-R Geostationary Lightning Mapper Performance Specifications and Algorithms

NASA Technical Reports Server (NTRS)

Mach, Douglas M.; Goodman, Steven J.; Blakeslee, Richard J.; Koshak, William J.; Petersen, William A.; Boldi, Robert A.; Carey, Lawrence D.; Bateman, Monte G.; Buchler, Dennis E.; McCaul, E. William, Jr.

2008-01-01

The Geostationary Lightning Mapper (GLM) is a single channel, near-IR imager/optical transient event detector, used to detect, locate and measure total lightning activity over the full-disk. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series will carry a GLM that will provide continuous day and night observations of lightning. The mission objectives for the GLM are to: (1) Provide continuous, full-disk lightning measurements for storm warning and nowcasting, (2) Provide early warning of tornadic activity, and (2) Accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997- present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 13 year data record of global lightning activity. GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms and applications. The science data will consist of lightning "events", "groups", and "flashes". The algorithm is being designed to be an efficient user of the computational resources. This may include parallelization of the code and the concept of sub-dividing the GLM FOV into regions to be processed in parallel. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds (e.g., Lightning Mapping Arrays in North Alabama, Oklahoma, Central Florida, and the Washington DC Metropolitan area) are being used to develop the prelaunch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution.

Development and clinical application of an evidence-based pharmaceutical care service algorithm in acute coronary syndrome.

PubMed

Kang, J E; Yu, J M; Choi, J H; Chung, I-M; Pyun, W B; Kim, S A; Lee, E K; Han, N Y; Yoon, J-H; Oh, J M; Rhie, S J

2018-06-01

Drug therapies are critical for preventing secondary complications in acute coronary syndrome (ACS). The purpose of this study was to develop and apply a pharmaceutical care service (PCS) algorithm for ACS and confirm that it is applicable through a prospective clinical trial. The ACS-PCS algorithm was developed according to extant evidence-based treatment and pharmaceutical care guidelines. Quality assurance was conducted through two methods: literature comparison and expert panel evaluation. The literature comparison was used to compare the content of the algorithm with the referenced guidelines. Expert evaluations were conducted by nine experts for 75 questionnaire items. A trial was conducted to confirm its effectiveness. Seventy-nine patients were assigned to either the pharmacist-included multidisciplinary team care (MTC) group or the usual care (UC) group. The endpoints of the trial were the prescription rate of two important drugs, readmission, emergency room (ER) visit and mortality. The main frame of the algorithm was structured with three tasks: medication reconciliation, medication optimization and transition of care. The contents and context of the algorithm were compliant with class I recommendations and the main service items from the evidence-based guidelines. Opinions from the expert panel were mostly positive. There were significant differences in beta-blocker prescription rates in the overall period (P = .013) and ER visits (four cases, 9.76%, P = .016) in the MTC group compared to the UC group, respectively. We developed a PCS algorithm for ACS based on the contents of evidence-based drug therapy and the core concept of pharmacist services. © 2018 John Wiley & Sons Ltd.

Developing a Learning Algorithm-Generated Empirical Relaxer

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

Mitchell, Wayne; Kallman, Josh; Toreja, Allen

2016-03-30

One of the main difficulties when running Arbitrary Lagrangian-Eulerian (ALE) simulations is determining how much to relax the mesh during the Eulerian step. This determination is currently made by the user on a simulation-by-simulation basis. We present a Learning Algorithm-Generated Empirical Relaxer (LAGER) which uses a regressive random forest algorithm to automate this decision process. We also demonstrate that LAGER successfully relaxes a variety of test problems, maintains simulation accuracy, and has the potential to significantly decrease both the person-hours and computational hours needed to run a successful ALE simulation.

Optimal coordinated voltage control in active distribution networks using backtracking search algorithm

PubMed Central

Tengku Hashim, Tengku Juhana; Mohamed, Azah

2017-01-01

The growing interest in distributed generation (DG) in recent years has led to a number of generators connected to a distribution system. The integration of DGs in a distribution system has resulted in a network known as active distribution network due to the existence of bidirectional power flow in the system. Voltage rise issue is one of the predominantly important technical issues to be addressed when DGs exist in an active distribution network. This paper presents the application of the backtracking search algorithm (BSA), which is relatively new optimisation technique to determine the optimal settings of coordinated voltage control in a distribution system. The coordinated voltage control considers power factor, on-load tap-changer and generation curtailment control to manage voltage rise issue. A multi-objective function is formulated to minimise total losses and voltage deviation in a distribution system. The proposed BSA is compared with that of particle swarm optimisation (PSO) so as to evaluate its effectiveness in determining the optimal settings of power factor, tap-changer and percentage active power generation to be curtailed. The load flow algorithm from MATPOWER is integrated in the MATLAB environment to solve the multi-objective optimisation problem. Both the BSA and PSO optimisation techniques have been tested on a radial 13-bus distribution system and the results show that the BSA performs better than PSO by providing better fitness value and convergence rate. PMID:28991919

Activity concentration measurements using a conjugate gradient (Siemens xSPECT) reconstruction algorithm in SPECT/CT.

PubMed

Armstrong, Ian S; Hoffmann, Sandra A

2016-11-01

The interest in quantitative single photon emission computer tomography (SPECT) shows potential in a number of clinical applications and now several vendors are providing software and hardware solutions to allow 'SUV-SPECT' to mirror metrics used in PET imaging. This brief technical report assesses the accuracy of activity concentration measurements using a new algorithm 'xSPECT' from Siemens Healthcare. SPECT/CT data were acquired from a uniform cylinder with 5, 10, 15 and 20 s/projection and NEMA image quality phantom with 25 s/projection. The NEMA phantom had hot spheres filled with an 8 : 1 activity concentration relative to the background compartment. Reconstructions were performed using parameters defined by manufacturer presets available with the algorithm. The accuracy of activity concentration measurements was assessed. A dose calibrator-camera cross-calibration factor (CCF) was derived from the uniform phantom data. In uniform phantom images, a positive bias was observed, ranging from ∼6% in the lower count images to ∼4% in the higher-count images. On the basis of the higher-count data, a CCF of 0.96 was derived. As expected, considerable negative bias was measured in the NEMA spheres using region mean values whereas positive bias was measured in the four largest NEMA spheres. Nonmonotonically increasing recovery curves for the hot spheres suggested the presence of Gibbs edge enhancement from resolution modelling. Sufficiently accurate activity concentration measurements can easily be measured on images reconstructed with the xSPECT algorithm without a CCF. However, the use of a CCF is likely to improve accuracy further. A manual conversion of voxel values into SUV should be possible, provided that the patient weight, injected activity and time between injection and imaging are all known accurately.

The development of line-scan image recognition algorithms for the detection of frass on mature tomatoes

USDA-ARS?s Scientific Manuscript database

In this research, a multispectral algorithm derived from hyperspectral line-scan fluorescence imaging under violet LED excitation was developed for the detection of frass contamination on mature tomatoes. The algorithm utilized the fluorescence intensities at two wavebands, 664 nm and 690 nm, for co...

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.

A metal artifact reduction algorithm in CT using multiple prior images by recursive active contour segmentation

PubMed Central

Nam, Haewon

2017-01-01

We propose a novel metal artifact reduction (MAR) algorithm for CT images that completes a corrupted sinogram along the metal trace region. When metal implants are located inside a field of view, they create a barrier to the transmitted X-ray beam due to the high attenuation of metals, which significantly degrades the image quality. To fill in the metal trace region efficiently, the proposed algorithm uses multiple prior images with residual error compensation in sinogram space. Multiple prior images are generated by applying a recursive active contour (RAC) segmentation algorithm to the pre-corrected image acquired by MAR with linear interpolation, where the number of prior image is controlled by RAC depending on the object complexity. A sinogram basis is then acquired by forward projection of the prior images. The metal trace region of the original sinogram is replaced by the linearly combined sinogram of the prior images. Then, the additional correction in the metal trace region is performed to compensate the residual errors occurred by non-ideal data acquisition condition. The performance of the proposed MAR algorithm is compared with MAR with linear interpolation and the normalized MAR algorithm using simulated and experimental data. The results show that the proposed algorithm outperforms other MAR algorithms, especially when the object is complex with multiple bone objects. PMID:28604794

Development of Speckle Interferometry Algorithm and System

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

Shamsir, A. A. M.; Jafri, M. Z. M.; Lim, H. S.

2011-05-25

Electronic speckle pattern interferometry (ESPI) method is a wholefield, non destructive measurement method widely used in the industries such as detection of defects on metal bodies, detection of defects in intergrated circuits in digital electronics components and in the preservation of priceless artwork. In this research field, this method is widely used to develop algorithms and to develop a new laboratory setup for implementing the speckle pattern interferometry. In speckle interferometry, an optically rough test surface is illuminated with an expanded laser beam creating a laser speckle pattern in the space surrounding the illuminated region. The speckle pattern is opticallymore » mixed with a second coherent light field that is either another speckle pattern or a smooth light field. This produces an interferometric speckle pattern that will be detected by sensor to count the change of the speckle pattern due to force given. In this project, an experimental setup of ESPI is proposed to analyze a stainless steel plate using 632.8 nm (red) wavelength of lights.« less

A sonification algorithm for developing the off-roads models for driving simulators

NASA Astrophysics Data System (ADS)

Chiroiu, Veturia; Brişan, Cornel; Dumitriu, Dan; Munteanu, Ligia

2018-01-01

In this paper, a sonification algorithm for developing the off-road models for driving simulators, is proposed. The aim of this algorithm is to overcome difficulties of heuristics identification which are best suited to a particular off-road profile built by measurements. The sonification algorithm is based on the stochastic polynomial chaos analysis suitable in solving equations with random input data. The fluctuations are generated by incomplete measurements leading to inhomogeneities of the cross-sectional curves of off-roads before and after deformation, the unstable contact between the tire and the road and the unreal distribution of contact and friction forces in the unknown contact domains. The approach is exercised on two particular problems and results compare favorably to existing analytical and numerical solutions. The sonification technique represents a useful multiscale analysis able to build a low-cost virtual reality environment with increased degrees of realism for driving simulators and higher user flexibility.

Development of a Crosstalk Suppression Algorithm for KID Readout

NASA Astrophysics Data System (ADS)

Lee, Kyungmin; Ishitsuka, H.; Oguri, S.; Suzuki, J.; Tajima, O.; Tomita, N.; Won, Eunil; Yoshida, M.

2018-06-01

The GroundBIRD telescope aims to detect B-mode polarization of the cosmic microwave background radiation using the kinetic inductance detector array as a polarimeter. For the readout of the signal from detector array, we have developed a frequency division multiplexing readout system based on a digital down converter method. These techniques in general have the leakage problems caused by the crosstalks. The window function was applied in the field programmable gate arrays to mitigate the effect of these problems and tested it in algorithm level.

Physical environment virtualization for human activities recognition

NASA Astrophysics Data System (ADS)

Poshtkar, Azin; Elangovan, Vinayak; Shirkhodaie, Amir; Chan, Alex; Hu, Shuowen

2015-05-01

Human activity recognition research relies heavily on extensive datasets to verify and validate performance of activity recognition algorithms. However, obtaining real datasets are expensive and highly time consuming. A physics-based virtual simulation can accelerate the development of context based human activity recognition algorithms and techniques by generating relevant training and testing videos simulating diverse operational scenarios. In this paper, we discuss in detail the requisite capabilities of a virtual environment to aid as a test bed for evaluating and enhancing activity recognition algorithms. To demonstrate the numerous advantages of virtual environment development, a newly developed virtual environment simulation modeling (VESM) environment is presented here to generate calibrated multisource imagery datasets suitable for development and testing of recognition algorithms for context-based human activities. The VESM environment serves as a versatile test bed to generate a vast amount of realistic data for training and testing of sensor processing algorithms. To demonstrate the effectiveness of VESM environment, we present various simulated scenarios and processed results to infer proper semantic annotations from the high fidelity imagery data for human-vehicle activity recognition under different operational contexts.

Algorithms and Libraries

NASA Technical Reports Server (NTRS)

Dongarra, Jack

1998-01-01

This exploratory study initiated our inquiry into algorithms and applications that would benefit by latency tolerant approach to algorithm building, including the construction of new algorithms where appropriate. In a multithreaded execution, when a processor reaches a point where remote memory access is necessary, the request is sent out on the network and a context--switch occurs to a new thread of computation. This effectively masks a long and unpredictable latency due to remote loads, thereby providing tolerance to remote access latency. We began to develop standards to profile various algorithm and application parameters, such as the degree of parallelism, granularity, precision, instruction set mix, interprocessor communication, latency etc. These tools will continue to develop and evolve as the Information Power Grid environment matures. To provide a richer context for this research, the project also focused on issues of fault-tolerance and computation migration of numerical algorithms and software. During the initial phase we tried to increase our understanding of the bottlenecks in single processor performance. Our work began by developing an approach for the automatic generation and optimization of numerical software for processors with deep memory hierarchies and pipelined functional units. Based on the results we achieved in this study we are planning to study other architectures of interest, including development of cost models, and developing code generators appropriate to these architectures.

A false-alarm aware methodology to develop robust and efficient multi-scale infrared small target detection algorithm

NASA Astrophysics Data System (ADS)

Moradi, Saed; Moallem, Payman; Sabahi, Mohamad Farzan

2018-03-01

False alarm rate and detection rate are still two contradictory metrics for infrared small target detection in an infrared search and track system (IRST), despite the development of new detection algorithms. In certain circumstances, not detecting true targets is more tolerable than detecting false items as true targets. Hence, considering background clutter and detector noise as the sources of the false alarm in an IRST system, in this paper, a false alarm aware methodology is presented to reduce false alarm rate while the detection rate remains undegraded. To this end, advantages and disadvantages of each detection algorithm are investigated and the sources of the false alarms are determined. Two target detection algorithms having independent false alarm sources are chosen in a way that the disadvantages of the one algorithm can be compensated by the advantages of the other one. In this work, multi-scale average absolute gray difference (AAGD) and Laplacian of point spread function (LoPSF) are utilized as the cornerstones of the desired algorithm of the proposed methodology. After presenting a conceptual model for the desired algorithm, it is implemented through the most straightforward mechanism. The desired algorithm effectively suppresses background clutter and eliminates detector noise. Also, since the input images are processed through just four different scales, the desired algorithm has good capability for real-time implementation. Simulation results in term of signal to clutter ratio and background suppression factor on real and simulated images prove the effectiveness and the performance of the proposed methodology. Since the desired algorithm was developed based on independent false alarm sources, our proposed methodology is expandable to any pair of detection algorithms which have different false alarm sources.

Development of independent MU/treatment time verification algorithm for non-IMRT treatment planning: A clinical experience

NASA Astrophysics Data System (ADS)

Tatli, Hamza; Yucel, Derya; Yilmaz, Sercan; Fayda, Merdan

2018-02-01

The aim of this study is to develop an algorithm for independent MU/treatment time (TT) verification for non-IMRT treatment plans, as a part of QA program to ensure treatment delivery accuracy. Two radiotherapy delivery units and their treatment planning systems (TPS) were commissioned in Liv Hospital Radiation Medicine Center, Tbilisi, Georgia. Beam data were collected according to vendors' collection guidelines, and AAPM reports recommendations, and processed by Microsoft Excel during in-house algorithm development. The algorithm is designed and optimized for calculating SSD and SAD treatment plans, based on AAPM TG114 dose calculation recommendations, coded and embedded in MS Excel spreadsheet, as a preliminary verification algorithm (VA). Treatment verification plans were created by TPSs based on IAEA TRS 430 recommendations, also calculated by VA, and point measurements were collected by solid water phantom, and compared. Study showed that, in-house VA can be used for non-IMRT plans MU/TT verifications.

Development of a real time activity monitoring Android application utilizing SmartStep.

PubMed

Hegde, Nagaraj; Melanson, Edward; Sazonov, Edward

2016-08-01

Footwear based activity monitoring systems are becoming popular in academic research as well as consumer industry segments. In our previous work, we had presented developmental aspects of an insole based activity and gait monitoring system-SmartStep, which is a socially acceptable, fully wireless and versatile insole. The present work describes the development of an Android application that captures the SmartStep data wirelessly over Bluetooth Low energy (BLE), computes features on the received data, runs activity classification algorithms and provides real time feedback. The development of activity classification methods was based on the the data from a human study involving 4 participants. Participants were asked to perform activities of sitting, standing, walking, and cycling while they wore SmartStep insole system. Multinomial Logistic Discrimination (MLD) was utilized in the development of machine learning model for activity prediction. The resulting classification model was implemented in an Android Smartphone. The Android application was benchmarked for power consumption and CPU loading. Leave one out cross validation resulted in average accuracy of 96.9% during model training phase. The Android application for real time activity classification was tested on a human subject wearing SmartStep resulting in testing accuracy of 95.4%.

Development and evaluation of an algorithm to facilitate drug prescription for inpatients with feeding tubes.

PubMed

Lohmann, Kristina; Freigofas, Julia; Leichsenring, Julian; Wallenwein, Chantal Marie; Haefeli, Walter Emil; Seidling, Hanna Marita

2015-04-01

We aimed to develop and evaluate an algorithm to facilitate drug switching between primary and tertiary care for patients with feeding tubes. An expert consortium developed an algorithm and applied it manually to 267 preadmission drugs of 46 patients admitted to a surgical ward of a tertiary care university hospital between June 12 and December 2, 2013, and requiring a feeding tube during their inpatient stay. The new algorithm considered the following principles: Drugs should be ideally listed on the hospital drug formulary (HDF). Additionally, drugs should include the same ingredient instead of a therapeutic equivalent. Preferred dosage forms were appropriate liquids, followed by solid drugs with liquid administration form, and solid drugs that could be crushed and/or suspended. Of all evaluated drugs, 83.5% could be switched to suitable drugs listed on the HDF and another 6.0% to drugs available on the German drug market. Additionally, for 4.1% of the drugs, the integration of individual switching rules allowed the switch from enteric-coated to immediate-release drugs. Consequently, 6.4% of the drugs could not be automatically switched and required case-to-case decision by a clinical professional (e.g., from sustained-release to immediate-release). The predefined principles were successfully integrated in the new algorithm. Thus, the algorithm switched more than 90% of the evaluated preadmission drugs to suitable drugs for inpatients with feeding tubes. This finding suggests that the algorithm can readily be transferred to an electronic format and integrated into a clinical decision support system.

Development of a Dynamic Operational Scheduling Algorithm for an Independent Micro-Grid with Renewable Energy

NASA Astrophysics Data System (ADS)

Obara, Shin'ya

A micro-grid with the capacity for sustainable energy is expected to be a distributed energy system that exhibits quite a small environmental impact. In an independent micro-grid, “green energy,” which is typically thought of as unstable, can be utilized effectively by introducing a battery. In the past study, the production-of-electricity prediction algorithm (PAS) of the solar cell was developed. In PAS, a layered neural network is made to learn based on past weather data and the operation plan of the compound system of a solar cell and other energy systems was examined using this prediction algorithm. In this paper, a dynamic operational scheduling algorithm is developed using a neural network (PAS) and a genetic algorithm (GA) to provide predictions for solar cell power output. We also do a case study analysis in which we use this algorithm to plan the operation of a system that connects nine houses in Sapporo to a micro-grid composed of power equipment and a polycrystalline silicon solar cell. In this work, the relationship between the accuracy of output prediction of the solar cell and the operation plan of the micro-grid was clarified. Moreover, we found that operating the micro-grid according to the plan derived with PAS was far superior, in terms of equipment hours of operation, to that using past average weather data.

Development and evaluation of ice phenology algorithm from space-borne active and passive microwave measurements

NASA Astrophysics Data System (ADS)

Kang, K.; Duguay, C. R.

2013-12-01

The presence (or absence) of ice cover plays an important role in lake-atmosphere interactions at high latitudes during the winter months. Knowledge of ice phenology (i.e. freeze-onset/melt-onset, ice-on/ice-off dates, and ice cover duration) is crucial for understanding both the role of lake ice cover in and its response to regional weather and climate. Shortening of the ice cover season in many regions of the Northern Hemisphere over recent decades has been shown to significantly influence the thermal regime as well as the water quality and quantity of lakes. In this respect, satellite remote sensing instruments are providing invaluable measurements for monitoring changes in timing of ice phenological events and the length of the ice cover (or open water) season on large northern lakes, and also for providing more spatially representative limnological information than available from in situ measurements. In this study, we present a new ice phenology retrieval algorithm developed from the synergistic use of Quick Scatterometer (QuikSCAT), Oceansat-2 Scatterometer (OSCAT) and the Advanced Microwave Scanning Radiometer (AMSR-E). Retrieved ice dates are then evaluated against those derived from the NOAA Interactive Multisensor Snow and Ice Mapping System (IMS) 4 km resolution product (2004-2011) during the freeze-up and break-up periods (2002-2012) for 11 lakes (Amadjuak, Nettilling, Great Bear, Great Slave, Manitoba, and Winnipeg in North America as well as Inarijrvi, Ladoga, Onega, Qinghai (Koko Nor), and Baikal in Eurasia). In addition, daily wind speed derived from QuikSCAT/OSCAT is analyzed along with WindSAT surface wind vector products (2002-2012) during the open water season for the large lakes. A detailed evaluation of the new algorithm conducted over Great Slave Lake (GSL) and Great Bear Lake (GBL) reveals that estimated ice-on/ice-off dates are within 4-7 days of those derived from the IMS product. Preliminary analysis of ice dates show that ice-on occurs

Development of a control algorithm for the ultrasound scanning robot (NCCUSR) using ultrasound image and force feedback.

PubMed

Kim, Yeoun Jae; Seo, Jong Hyun; Kim, Hong Rae; Kim, Kwang Gi

2017-06-01

Clinicians who frequently perform ultrasound scanning procedures often suffer from musculoskeletal disorders, arthritis, and myalgias. To minimize their occurrence and to assist clinicians, ultrasound scanning robots have been developed worldwide. Although, to date, there is still no commercially available ultrasound scanning robot, many control methods have been suggested and researched. These control algorithms are either image based or force based. If the ultrasound scanning robot control algorithm was a combination of the two algorithms, it could benefit from the advantage of each one. However, there are no existing control methods for ultrasound scanning robots that combine force control and image analysis. Therefore, in this work, a control algorithm is developed for an ultrasound scanning robot using force feedback and ultrasound image analysis. A manipulator-type ultrasound scanning robot named 'NCCUSR' is developed and a control algorithm for this robot is suggested and verified. First, conventional hybrid position-force control is implemented for the robot and the hybrid position-force control algorithm is combined with ultrasound image analysis to fully control the robot. The control method is verified using a thyroid phantom. It was found that the proposed algorithm can be applied to control the ultrasound scanning robot and experimental outcomes suggest that the images acquired using the proposed control method can yield a rating score that is equivalent to images acquired directly by the clinicians. The proposed control method can be applied to control the ultrasound scanning robot. However, more work must be completed to verify the proposed control method in order to become clinically feasible. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Development of the atmospheric correction algorithm for the next generation geostationary ocean color sensor data

NASA Astrophysics Data System (ADS)

Lee, Kwon-Ho; Kim, Wonkook

2017-04-01

The geostationary ocean color imager-II (GOCI-II), designed to be focused on the ocean environmental monitoring with better spatial (250m for local and 1km for full disk) and spectral resolution (13 bands) then the current operational mission of the GOCI-I. GOCI-II will be launched in 2018. This study presents currently developing algorithm for atmospheric correction and retrieval of surface reflectance over land to be optimized with the sensor's characteristics. We first derived the top-of-atmosphere radiances as the proxy data derived from the parameterized radiative transfer code in the 13 bands of GOCI-II. Based on the proxy data, the algorithm has been made with cloud masking, gas absorption correction, aerosol inversion, computation of aerosol extinction correction. The retrieved surface reflectances are evaluated by the MODIS level 2 surface reflectance products (MOD09). For the initial test period, the algorithm gave error of within 0.05 compared to MOD09. Further work will be progressed to fully implement the GOCI-II Ground Segment system (G2GS) algorithm development environment. These atmospherically corrected surface reflectance product will be the standard GOCI-II product after launch.

Unveiling the development of intracranial injury using dynamic brain EIT: an evaluation of current reconstruction algorithms.

PubMed

Li, Haoting; Chen, Rongqing; Xu, Canhua; Liu, Benyuan; Tang, Mengxing; Yang, Lin; Dong, Xiuzhen; Fu, Feng

2017-08-21

Dynamic brain electrical impedance tomography (EIT) is a promising technique for continuously monitoring the development of cerebral injury. While there are many reconstruction algorithms available for brain EIT, there is still a lack of study to compare their performance in the context of dynamic brain monitoring. To address this problem, we develop a framework for evaluating different current algorithms with their ability to correctly identify small intracranial conductivity changes. Firstly, a simulation 3D head phantom with realistic layered structure and impedance distribution is developed. Next several reconstructing algorithms, such as back projection (BP), damped least-square (DLS), Bayesian, split Bregman (SB) and GREIT are introduced. We investigate their temporal response, noise performance, location and shape error with respect to different noise levels on the simulation phantom. The results show that the SB algorithm demonstrates superior performance in reducing image error. To further improve the location accuracy, we optimize SB by incorporating the brain structure-based conductivity distribution priors, in which differences of the conductivities between different brain tissues and the inhomogeneous conductivity distribution of the skull are considered. We compare this novel algorithm (called SB-IBCD) with SB and DLS using anatomically correct head shaped phantoms with spatial varying skull conductivity. Main results and Significance: The results showed that SB-IBCD is the most effective in unveiling small intracranial conductivity changes, where it can reduce the image error by an average of 30.0% compared to DLS.

Development of novel algorithm and real-time monitoring ambulatory system using Bluetooth module for fall detection in the elderly.

PubMed

Hwang, J Y; Kang, J M; Jang, Y W; Kim, H

2004-01-01

Novel algorithm and real-time ambulatory monitoring system for fall detection in elderly people is described. Our system is comprised of accelerometer, tilt sensor and gyroscope. For real-time monitoring, we used Bluetooth. Accelerometer measures kinetic force, tilt sensor and gyroscope estimates body posture. Also, we suggested algorithm using signals which obtained from the system attached to the chest for fall detection. To evaluate our system and algorithm, we experimented on three people aged over 26 years. The experiment of four cases such as forward fall, backward fall, side fall and sit-stand was repeated ten times and the experiment in daily life activity was performed one time to each subject. These experiments showed that our system and algorithm could distinguish between falling and daily life activity. Moreover, the accuracy of fall detection is 96.7%. Our system is especially adapted for long-time and real-time ambulatory monitoring of elderly people in emergency situation.

The development of a novel knowledge-based weaning algorithm using pulmonary parameters: a simulation study.

PubMed

Guler, Hasan; Kilic, Ugur

2018-03-01

Weaning is important for patients and clinicians who have to determine correct weaning time so that patients do not become addicted to the ventilator. There are already some predictors developed, such as the rapid shallow breathing index (RSBI), the pressure time index (PTI), and Jabour weaning index. Many important dimensions of weaning are sometimes ignored by these predictors. This is an attempt to develop a knowledge-based weaning process via fuzzy logic that eliminates the disadvantages of the present predictors. Sixteen vital parameters listed in published literature have been used to determine the weaning decisions in the developed system. Since there are considered to be too many individual parameters in it, related parameters were grouped together to determine acid-base balance, adequate oxygenation, adequate pulmonary function, hemodynamic stability, and the psychological status of the patients. To test the performance of the developed algorithm, 20 clinical scenarios were generated using Monte Carlo simulations and the Gaussian distribution method. The developed knowledge-based algorithm and RSBI predictor were applied to the generated scenarios. Finally, a clinician evaluated each clinical scenario independently. The Student's t test was used to show the statistical differences between the developed weaning algorithm, RSBI, and the clinician's evaluation. According to the results obtained, there were no statistical differences between the proposed methods and the clinician evaluations.

Development of a new metal artifact reduction algorithm by using an edge preserving method for CBCT imaging

NASA Astrophysics Data System (ADS)

Kim, Juhye; Nam, Haewon; Lee, Rena

2015-07-01

CT (computed tomography) images, metal materials such as tooth supplements or surgical clips can cause metal artifact and degrade image quality. In severe cases, this may lead to misdiagnosis. In this research, we developed a new MAR (metal artifact reduction) algorithm by using an edge preserving filter and the MATLAB program (Mathworks, version R2012a). The proposed algorithm consists of 6 steps: image reconstruction from projection data, metal segmentation, forward projection, interpolation, applied edge preserving smoothing filter, and new image reconstruction. For an evaluation of the proposed algorithm, we obtained both numerical simulation data and data for a Rando phantom. In the numerical simulation data, four metal regions were added into the Shepp Logan phantom for metal artifacts. The projection data of the metal-inserted Rando phantom were obtained by using a prototype CBCT scanner manufactured by medical engineering and medical physics (MEMP) laboratory research group in medical science at Ewha Womans University. After these had been adopted the proposed algorithm was performed, and the result were compared with the original image (with metal artifact without correction) and with a corrected image based on linear interpolation. Both visual and quantitative evaluations were done. Compared with the original image with metal artifacts and with the image corrected by using linear interpolation, both the numerical and the experimental phantom data demonstrated that the proposed algorithm reduced the metal artifact. In conclusion, the evaluation in this research showed that the proposed algorithm outperformed the interpolation based MAR algorithm. If an optimization and a stability evaluation of the proposed algorithm can be performed, the developed algorithm is expected to be an effective tool for eliminating metal artifacts even in commercial CT systems.

Data and software tools for gamma radiation spectral threat detection and nuclide identification algorithm development and evaluation

NASA Astrophysics Data System (ADS)

Portnoy, David; Fisher, Brian; Phifer, Daniel

2015-06-01

The detection of radiological and nuclear threats is extremely important to national security. The federal government is spending significant resources developing new detection systems and attempting to increase the performance of existing ones. The detection of illicit radionuclides that may pose a radiological or nuclear threat is a challenging problem complicated by benign radiation sources (e.g., cat litter and medical treatments), shielding, and large variations in background radiation. Although there is a growing acceptance within the community that concentrating efforts on algorithm development (independent of the specifics of fully assembled systems) has the potential for significant overall system performance gains, there are two major hindrances to advancements in gamma spectral analysis algorithms under the current paradigm: access to data and common performance metrics along with baseline performance measures. Because many of the signatures collected during performance measurement campaigns are classified, dissemination to algorithm developers is extremely limited. This leaves developers no choice but to collect their own data if they are lucky enough to have access to material and sensors. This is often combined with their own definition of metrics for measuring performance. These two conditions make it all but impossible for developers and external reviewers to make meaningful comparisons between algorithms. Without meaningful comparisons, performance advancements become very hard to achieve and (more importantly) recognize. The objective of this work is to overcome these obstacles by developing and freely distributing real and synthetically generated gamma-spectra data sets as well as software tools for performance evaluation with associated performance baselines to national labs, academic institutions, government agencies, and industry. At present, datasets for two tracks, or application domains, have been developed: one that includes temporal

Development and Testing of an Algorithm for Efficient Resource Positioning in Pre-hospital Emergency Care

PubMed Central

Saini, Devashish; Mazza, Giovanni; Shah, Najaf; Mirza, Muzna; Gori, Mandar M; Nandigam, Hari Krishna; Orthner, Helmuth F

2006-01-01

Response times for pre-hospital emergency care may be improved with the use of algorithms that analyzes historical patterns in incident location and suggests optimal places for prepositioning of emergency response units. We will develop such an algorithm based on cluster analysis and test whether it leads to significant improvement in mileage when compared to actual historical data of dispatching based on fixed stations. PMID:17238702

Development and testing of an algorithm for efficient resource positioning in pre-hospital emergency care.

PubMed

Saini, Devashish; Mazza, Giovanni; Shah, Najaf; Mirza, Muzna; Gori, Mandar M; Nandigam, Hari Krishna; Orthner, Helmuth F

2006-01-01

Response times for pre-hospital emergency care may be improved with the use of algorithms that analyzes historical patterns in incident location and suggests optimal places for pre-positioning of emergency response units. We will develop such an algorithm based on cluster analysis and test whether it leads to significant improvement in mileage when compared to actual historical data of dispatching based on fixed stations.

Development of Elevation and Relief Databases for ICESat-2/ATLAS Receiver Algorithms

NASA Astrophysics Data System (ADS)

Leigh, H. W.; Magruder, L. A.; Carabajal, C. C.; Saba, J. L.; Urban, T. J.; Mcgarry, J.; Schutz, B. E.

2013-12-01

The Advanced Topographic Laser Altimeter System (ATLAS) is planned to launch onboard NASA's ICESat-2 spacecraft in 2016. ATLAS operates at a wavelength of 532 nm with a laser repeat rate of 10 kHz and 6 individual laser footprints. The satellite will be in a 500 km, 91-day repeat ground track orbit at an inclination of 92°. A set of onboard Receiver Algorithms has been developed to reduce the data volume and data rate to acceptable levels while still transmitting the relevant ranging data. The onboard algorithms limit the data volume by distinguishing between surface returns and background noise and selecting a small vertical region around the surface return to be included in telemetry. The algorithms make use of signal processing techniques, along with three databases, the Digital Elevation Model (DEM), the Digital Relief Map (DRM), and the Surface Reference Mask (SRM), to find the signal and determine the appropriate dynamic range of vertical data surrounding the surface for downlink. The DEM provides software-based range gating for ATLAS. This approach allows the algorithm to limit the surface signal search to the vertical region between minimum and maximum elevations provided by the DEM (plus some margin to account for uncertainties). The DEM is constructed in a nested, three-tiered grid to account for a hardware constraint limiting the maximum vertical range to 6 km. The DRM is used to select the vertical width of the telemetry band around the surface return. The DRM contains global values of relief calculated along 140 m and 700 m ground track segments consistent with a 92° orbit. The DRM must contain the maximum value of relief seen in any given area, but must be as close to truth as possible as the DRM directly affects data volume. The SRM, which has been developed independently from the DEM and DRM, is used to set parameters within the algorithm and select telemetry bands for downlink. Both the DEM and DRM are constructed from publicly available digital

Developing Electronic Health Record Algorithms That Accurately Identify Patients With Systemic Lupus Erythematosus.

PubMed

Barnado, April; Casey, Carolyn; Carroll, Robert J; Wheless, Lee; Denny, Joshua C; Crofford, Leslie J

2017-05-01

To study systemic lupus erythematosus (SLE) in the electronic health record (EHR), we must accurately identify patients with SLE. Our objective was to develop and validate novel EHR algorithms that use International Classification of Diseases, Ninth Revision (ICD-9), Clinical Modification codes, laboratory testing, and medications to identify SLE patients. We used Vanderbilt's Synthetic Derivative, a de-identified version of the EHR, with 2.5 million subjects. We selected all individuals with at least 1 SLE ICD-9 code (710.0), yielding 5,959 individuals. To create a training set, 200 subjects were randomly selected for chart review. A subject was defined as a case if diagnosed with SLE by a rheumatologist, nephrologist, or dermatologist. Positive predictive values (PPVs) and sensitivity were calculated for combinations of code counts of the SLE ICD-9 code, a positive antinuclear antibody (ANA), ever use of medications, and a keyword of "lupus" in the problem list. The algorithms with the highest PPV were each internally validated using a random set of 100 individuals from the remaining 5,759 subjects. The algorithm with the highest PPV at 95% in the training set and 91% in the validation set was 3 or more counts of the SLE ICD-9 code, ANA positive (≥1:40), and ever use of both disease-modifying antirheumatic drugs and steroids, while excluding individuals with systemic sclerosis and dermatomyositis ICD-9 codes. We developed and validated the first EHR algorithm that incorporates laboratory values and medications with the SLE ICD-9 code to identify patients with SLE accurately. © 2016, American College of Rheumatology.

A novel vehicle tracking algorithm based on mean shift and active contour model in complex environment

NASA Astrophysics Data System (ADS)

Cai, Lei; Wang, Lin; Li, Bo; Zhang, Libao; Lv, Wen

2017-06-01

Vehicle tracking technology is currently one of the most active research topics in machine vision. It is an important part of intelligent transportation system. However, in theory and technology, it still faces many challenges including real-time and robustness. In video surveillance, the targets need to be detected in real-time and to be calculated accurate position for judging the motives. The contents of video sequence images and the target motion are complex, so the objects can't be expressed by a unified mathematical model. Object-tracking is defined as locating the interest moving target in each frame of a piece of video. The current tracking technology can achieve reliable results in simple environment over the target with easy identified characteristics. However, in more complex environment, it is easy to lose the target because of the mismatch between the target appearance and its dynamic model. Moreover, the target usually has a complex shape, but the tradition target tracking algorithm usually represents the tracking results by simple geometric such as rectangle or circle, so it cannot provide accurate information for the subsequent upper application. This paper combines a traditional object-tracking technology, Mean-Shift algorithm, with a kind of image segmentation algorithm, Active-Contour model, to get the outlines of objects while the tracking process and automatically handle topology changes. Meanwhile, the outline information is used to aid tracking algorithm to improve it.

MEMS-based sensing and algorithm development for fall detection and gait analysis

NASA Astrophysics Data System (ADS)

Gupta, Piyush; Ramirez, Gabriel; Lie, Donald Y. C.; Dallas, Tim; Banister, Ron E.; Dentino, Andrew

2010-02-01

Falls by the elderly are highly detrimental to health, frequently resulting in injury, high medical costs, and even death. Using a MEMS-based sensing system, algorithms are being developed for detecting falls and monitoring the gait of elderly and disabled persons. In this study, wireless sensors utilize Zigbee protocols were incorporated into planar shoe insoles and a waist mounted device. The insole contains four sensors to measure pressure applied by the foot. A MEMS based tri-axial accelerometer is embedded in the insert and a second one is utilized by the waist mounted device. The primary fall detection algorithm is derived from the waist accelerometer. The differential acceleration is calculated from samples received in 1.5s time intervals. This differential acceleration provides the quantification via an energy index. From this index one may ascertain different gait and identify fall events. Once a pre-determined index threshold is exceeded, the algorithm will classify an event as a fall or a stumble. The secondary algorithm is derived from frequency analysis techniques. The analysis consists of wavelet transforms conducted on the waist accelerometer data. The insole pressure data is then used to underline discrepancies in the transforms, providing more accurate data for classifying gait and/or detecting falls. The range of the transform amplitude in the fourth iteration of a Daubechies-6 transform was found sufficient to detect and classify fall events.

Developing operation algorithms for vision subsystems in autonomous mobile robots

NASA Astrophysics Data System (ADS)

Shikhman, M. V.; Shidlovskiy, S. V.

2018-05-01

The paper analyzes algorithms for selecting keypoints on the image for the subsequent automatic detection of people and obstacles. The algorithm is based on the histogram of oriented gradients and the support vector method. The combination of these methods allows successful selection of dynamic and static objects. The algorithm can be applied in various autonomous mobile robots.

Development and Validation of a Spike Detection and Classification Algorithm Aimed at Implementation on Hardware Devices

PubMed Central

Biffi, E.; Ghezzi, D.; Pedrocchi, A.; Ferrigno, G.

2010-01-01

Neurons cultured in vitro on MicroElectrode Array (MEA) devices connect to each other, forming a network. To study electrophysiological activity and long term plasticity effects, long period recording and spike sorter methods are needed. Therefore, on-line and real time analysis, optimization of memory use and data transmission rate improvement become necessary. We developed an algorithm for amplitude-threshold spikes detection, whose performances were verified with (a) statistical analysis on both simulated and real signal and (b) Big O Notation. Moreover, we developed a PCA-hierarchical classifier, evaluated on simulated and real signal. Finally we proposed a spike detection hardware design on FPGA, whose feasibility was verified in terms of CLBs number, memory occupation and temporal requirements; once realized, it will be able to execute on-line detection and real time waveform analysis, reducing data storage problems. PMID:20300592

Understanding disordered systems through numerical simulation and algorithm development

NASA Astrophysics Data System (ADS)

Sweeney, Sean Michael

Disordered systems arise in many physical contexts. Not all matter is uniform, and impurities or heterogeneities can be modeled by fixed random disorder. Numerous complex networks also possess fixed disorder, leading to applications in transportation systems, telecommunications, social networks, and epidemic modeling, to name a few. Due to their random nature and power law critical behavior, disordered systems are difficult to study analytically. Numerical simulation can help overcome this hurdle by allowing for the rapid computation of system states. In order to get precise statistics and extrapolate to the thermodynamic limit, large systems must be studied over many realizations. Thus, innovative algorithm development is essential in order reduce memory or running time requirements of simulations. This thesis presents a review of disordered systems, as well as a thorough study of two particular systems through numerical simulation, algorithm development and optimization, and careful statistical analysis of scaling properties. Chapter 1 provides a thorough overview of disordered systems, the history of their study in the physics community, and the development of techniques used to study them. Topics of quenched disorder, phase transitions, the renormalization group, criticality, and scale invariance are discussed. Several prominent models of disordered systems are also explained. Lastly, analysis techniques used in studying disordered systems are covered. In Chapter 2, minimal spanning trees on critical percolation clusters are studied, motivated in part by an analytic perturbation expansion by Jackson and Read that I check against numerical calculations. This system has a direct mapping to the ground state of the strongly disordered spin glass. We compute the path length fractal dimension of these trees in dimensions d = {2, 3, 4, 5} and find our results to be compatible with the analytic results suggested by Jackson and Read. In Chapter 3, the random bond Ising

Development and evaluation of an articulated registration algorithm for human skeleton registration

NASA Astrophysics Data System (ADS)

Yip, Stephen; Perk, Timothy; Jeraj, Robert

2014-03-01

Accurate registration over multiple scans is necessary to assess treatment response of bone diseases (e.g. metastatic bone lesions). This study aimed to develop and evaluate an articulated registration algorithm for the whole-body skeleton registration in human patients. In articulated registration, whole-body skeletons are registered by auto-segmenting into individual bones using atlas-based segmentation, and then rigidly aligning them. Sixteen patients (weight = 80-117 kg, height = 168-191 cm) with advanced prostate cancer underwent the pre- and mid-treatment PET/CT scans over a course of cancer therapy. Skeletons were extracted from the CT images by thresholding (HU>150). Skeletons were registered using the articulated, rigid, and deformable registration algorithms to account for position and postural variability between scans. The inter-observers agreement in the atlas creation, the agreement between the manually and atlas-based segmented bones, and the registration performances of all three registration algorithms were all assessed using the Dice similarity index—DSIobserved, DSIatlas, and DSIregister. Hausdorff distance (dHausdorff) of the registered skeletons was also used for registration evaluation. Nearly negligible inter-observers variability was found in the bone atlases creation as the DSIobserver was 96 ± 2%. Atlas-based and manual segmented bones were in excellent agreement with DSIatlas of 90 ± 3%. Articulated (DSIregsiter = 75 ± 2%, dHausdorff = 0.37 ± 0.08 cm) and deformable registration algorithms (DSIregister = 77 ± 3%, dHausdorff = 0.34 ± 0.08 cm) considerably outperformed the rigid registration algorithm (DSIregsiter = 59 ± 9%, dHausdorff = 0.69 ± 0.20 cm) in the skeleton registration as the rigid registration algorithm failed to capture the skeleton flexibility in the joints. Despite superior skeleton registration performance, deformable registration algorithm failed to preserve the local rigidity of bones as over 60% of the

A fast and accurate online sequential learning algorithm for feedforward networks.

PubMed

Liang, Nan-Ying; Huang, Guang-Bin; Saratchandran, P; Sundararajan, N

2006-11-01

In this paper, we develop an online sequential learning algorithm for single hidden layer feedforward networks (SLFNs) with additive or radial basis function (RBF) hidden nodes in a unified framework. The algorithm is referred to as online sequential extreme learning machine (OS-ELM) and can learn data one-by-one or chunk-by-chunk (a block of data) with fixed or varying chunk size. The activation functions for additive nodes in OS-ELM can be any bounded nonconstant piecewise continuous functions and the activation functions for RBF nodes can be any integrable piecewise continuous functions. In OS-ELM, the parameters of hidden nodes (the input weights and biases of additive nodes or the centers and impact factors of RBF nodes) are randomly selected and the output weights are analytically determined based on the sequentially arriving data. The algorithm uses the ideas of ELM of Huang et al. developed for batch learning which has been shown to be extremely fast with generalization performance better than other batch training methods. Apart from selecting the number of hidden nodes, no other control parameters have to be manually chosen. Detailed performance comparison of OS-ELM is done with other popular sequential learning algorithms on benchmark problems drawn from the regression, classification and time series prediction areas. The results show that the OS-ELM is faster than the other sequential algorithms and produces better generalization performance.

Portable Health Algorithms Test System

NASA Technical Reports Server (NTRS)

Melcher, Kevin J.; Wong, Edmond; Fulton, Christopher E.; Sowers, Thomas S.; Maul, William A.

2010-01-01

A document discusses the Portable Health Algorithms Test (PHALT) System, which has been designed as a means for evolving the maturity and credibility of algorithms developed to assess the health of aerospace systems. Comprising an integrated hardware-software environment, the PHALT system allows systems health management algorithms to be developed in a graphical programming environment, to be tested and refined using system simulation or test data playback, and to be evaluated in a real-time hardware-in-the-loop mode with a live test article. The integrated hardware and software development environment provides a seamless transition from algorithm development to real-time implementation. The portability of the hardware makes it quick and easy to transport between test facilities. This hard ware/software architecture is flexible enough to support a variety of diagnostic applications and test hardware, and the GUI-based rapid prototyping capability is sufficient to support development execution, and testing of custom diagnostic algorithms. The PHALT operating system supports execution of diagnostic algorithms under real-time constraints. PHALT can perform real-time capture and playback of test rig data with the ability to augment/ modify the data stream (e.g. inject simulated faults). It performs algorithm testing using a variety of data input sources, including real-time data acquisition, test data playback, and system simulations, and also provides system feedback to evaluate closed-loop diagnostic response and mitigation control.

GASAKe: forecasting landslide activations by a genetic-algorithms based hydrological model

NASA Astrophysics Data System (ADS)

Terranova, O. G.; Gariano, S. L.; Iaquinta, P.; Iovine, G. G. R.

2015-02-01

GASAKe is a new hydrological model aimed at forecasting the triggering of landslides. The model is based on genetic-algorithms and allows to obtaining thresholds of landslide activation from the set of historical occurrences and from the rainfall series. GASAKe can be applied to either single landslides or set of similar slope movements in a homogeneous environment. Calibration of the model is based on genetic-algorithms, and provides for families of optimal, discretized solutions (kernels) that maximize the fitness function. Starting from these latter, the corresponding mobility functions (i.e. the predictive tools) can be obtained through convolution with the rain series. The base time of the kernel is related to the magnitude of the considered slope movement, as well as to hydro-geological complexity of the site. Generally, smaller values are expected for shallow slope instabilities with respect to large-scale phenomena. Once validated, the model can be applied to estimate the timing of future landslide activations in the same study area, by employing recorded or forecasted rainfall series. Example of application of GASAKe to a medium-scale slope movement (the Uncino landslide at San Fili, in Calabria, Southern Italy) and to a set of shallow landslides (in the Sorrento Peninsula, Campania, Southern Italy) are discussed. In both cases, a successful calibration of the model has been achieved, despite unavoidable uncertainties concerning the dates of landslide occurrence. In particular, for the Sorrento Peninsula case, a fitness of 0.81 has been obtained by calibrating the model against 10 dates of landslide activation; in the Uncino case, a fitness of 1 (i.e. neither missing nor false alarms) has been achieved against 5 activations. As for temporal validation, the experiments performed by considering the extra dates of landslide activation have also proved satisfactory. In view of early-warning applications for civil protection purposes, the capability of the

Applications and development of new algorithms for displacement analysis using InSAR time series

NASA Astrophysics Data System (ADS)

Osmanoglu, Batuhan

-dimensional (3-D) phase unwrapping. Chapter 4 focuses on the unwrapping path. Unwrapping algorithms can be divided into two groups, path-dependent and path-independent algorithms. Path-dependent algorithms use local unwrapping functions applied pixel-by-pixel to the dataset. In contrast, path-independent algorithms use global optimization methods such as least squares, and return a unique solution. However, when aliasing and noise are present, path-independent algorithms can underestimate the signal in some areas due to global fitting criteria. Path-dependent algorithms do not underestimate the signal, but, as the name implies, the unwrapping path can affect the result. Comparison between existing path algorithms and a newly developed algorithm based on Fisher information theory was conducted. Results indicate that Fisher information theory does indeed produce lower misfit results for most tested cases. Chapter 5 presents a new time series analysis method based on 3-D unwrapping of SAR data using extended Kalman filters. Existing methods for time series generation using InSAR data employ special filters to combine two-dimensional (2-D) spatial unwrapping with one-dimensional (1-D) temporal unwrapping results. The new method, however, combines observations in azimuth, range and time for repeat pass interferometry. Due to the pixel-by-pixel characteristic of the filter, the unwrapping path is selected based on a quality map. This unwrapping algorithm is the first application of extended Kalman filters to the 3-D unwrapping problem. Time series analyses of InSAR data are used in a variety of applications with different characteristics. Consequently, it is difficult to develop a single algorithm that can provide optimal results in all cases, given that different algorithms possess a unique set of strengths and weaknesses. Nonetheless, filter-based unwrapping algorithms such as the one presented in this dissertation have the capability of joining multiple observations into a uniform

Forecasting of the development of professional medical equipment engineering based on neuro-fuzzy algorithms

NASA Astrophysics Data System (ADS)

Vaganova, E. V.; Syryamkin, M. V.

2015-11-01

The purpose of the research is the development of evolutionary algorithms for assessments of promising scientific directions. The main attention of the present study is paid to the evaluation of the foresight possibilities for identification of technological peaks and emerging technologies in professional medical equipment engineering in Russia and worldwide on the basis of intellectual property items and neural network modeling. An automated information system consisting of modules implementing various classification methods for accuracy of the forecast improvement and the algorithm of construction of neuro-fuzzy decision tree have been developed. According to the study result, modern trends in this field will focus on personalized smart devices, telemedicine, bio monitoring, «e-Health» and «m-Health» technologies.

Algorithm Visualization: The State of the Field

ERIC Educational Resources Information Center

Shaffer, Clifford A.; Cooper, Matthew L.; Alon, Alexander Joel D.; Akbar, Monika; Stewart, Michael; Ponce, Sean; Edwards, Stephen H.

2010-01-01

We present findings regarding the state of the field of Algorithm Visualization (AV) based on our analysis of a collection of over 500 AVs. We examine how AVs are distributed among topics, who created them and when, their overall quality, and how they are disseminated. There does exist a cadre of good AVs and active developers. Unfortunately, we…

Active Learning Using Hint Information.

PubMed

Li, Chun-Liang; Ferng, Chun-Sung; Lin, Hsuan-Tien

2015-08-01

The abundance of real-world data and limited labeling budget calls for active learning, an important learning paradigm for reducing human labeling efforts. Many recently developed active learning algorithms consider both uncertainty and representativeness when making querying decisions. However, exploiting representativeness with uncertainty concurrently usually requires tackling sophisticated and challenging learning tasks, such as clustering. In this letter, we propose a new active learning framework, called hinted sampling, which takes both uncertainty and representativeness into account in a simpler way. We design a novel active learning algorithm within the hinted sampling framework with an extended support vector machine. Experimental results validate that the novel active learning algorithm can result in a better and more stable performance than that achieved by state-of-the-art algorithms. We also show that the hinted sampling framework allows improving another active learning algorithm designed from the transductive support vector machine.

Learning neural connectivity from firing activity: efficient algorithms with provable guarantees on topology.

PubMed

Karbasi, Amin; Salavati, Amir Hesam; Vetterli, Martin

2018-04-01

The connectivity of a neuronal network has a major effect on its functionality and role. It is generally believed that the complex network structure of the brain provides a physiological basis for information processing. Therefore, identifying the network's topology has received a lot of attentions in neuroscience and has been the center of many research initiatives such as Human Connectome Project. Nevertheless, direct and invasive approaches that slice and observe the neural tissue have proven to be time consuming, complex and costly. As a result, the inverse methods that utilize firing activity of neurons in order to identify the (functional) connections have gained momentum recently, especially in light of rapid advances in recording technologies; It will soon be possible to simultaneously monitor the activities of tens of thousands of neurons in real time. While there are a number of excellent approaches that aim to identify the functional connections from firing activities, the scalability of the proposed techniques plays a major challenge in applying them on large-scale datasets of recorded firing activities. In exceptional cases where scalability has not been an issue, the theoretical performance guarantees are usually limited to a specific family of neurons or the type of firing activities. In this paper, we formulate the neural network reconstruction as an instance of a graph learning problem, where we observe the behavior of nodes/neurons (i.e., firing activities) and aim to find the links/connections. We develop a scalable learning mechanism and derive the conditions under which the estimated graph for a network of Leaky Integrate and Fire (LIf) neurons matches the true underlying synaptic connections. We then validate the performance of the algorithm using artificially generated data (for benchmarking) and real data recorded from multiple hippocampal areas in rats.

Development of a generally applicable morphokinetic algorithm capable of predicting the implantation potential of embryos transferred on Day 3.

PubMed

Petersen, Bjørn Molt; Boel, Mikkel; Montag, Markus; Gardner, David K

2016-10-01

Can a generally applicable morphokinetic algorithm suitable for Day 3 transfers of time-lapse monitored embryos originating from different culture conditions and fertilization methods be developed for the purpose of supporting the embryologist's decision on which embryo to transfer back to the patient in assisted reproduction? The algorithm presented here can be used independently of culture conditions and fertilization method and provides predictive power not surpassed by other published algorithms for ranking embryos according to their blastocyst formation potential. Generally applicable algorithms have so far been developed only for predicting blastocyst formation. A number of clinics have reported validated implantation prediction algorithms, which have been developed based on clinic-specific culture conditions and clinical environment. However, a generally applicable embryo evaluation algorithm based on actual implantation outcome has not yet been reported. Retrospective evaluation of data extracted from a database of known implantation data (KID) originating from 3275 embryos transferred on Day 3 conducted in 24 clinics between 2009 and 2014. The data represented different culture conditions (reduced and ambient oxygen with various culture medium strategies) and fertilization methods (IVF, ICSI). The capability to predict blastocyst formation was evaluated on an independent set of morphokinetic data from 11 218 embryos which had been cultured to Day 5. PARTICIPANTS/MATERIALS, SETTING, The algorithm was developed by applying automated recursive partitioning to a large number of annotation types and derived equations, progressing to a five-fold cross-validation test of the complete data set and a validation test of different incubation conditions and fertilization methods. The results were expressed as receiver operating characteristics curves using the area under the curve (AUC) to establish the predictive strength of the algorithm. By applying the here

Development of a generally applicable morphokinetic algorithm capable of predicting the implantation potential of embryos transferred on Day 3

PubMed Central

Petersen, Bjørn Molt; Boel, Mikkel; Montag, Markus; Gardner, David K.

2016-01-01

STUDY QUESTION Can a generally applicable morphokinetic algorithm suitable for Day 3 transfers of time-lapse monitored embryos originating from different culture conditions and fertilization methods be developed for the purpose of supporting the embryologist's decision on which embryo to transfer back to the patient in assisted reproduction? SUMMARY ANSWER The algorithm presented here can be used independently of culture conditions and fertilization method and provides predictive power not surpassed by other published algorithms for ranking embryos according to their blastocyst formation potential. WHAT IS KNOWN ALREADY Generally applicable algorithms have so far been developed only for predicting blastocyst formation. A number of clinics have reported validated implantation prediction algorithms, which have been developed based on clinic-specific culture conditions and clinical environment. However, a generally applicable embryo evaluation algorithm based on actual implantation outcome has not yet been reported. STUDY DESIGN, SIZE, DURATION Retrospective evaluation of data extracted from a database of known implantation data (KID) originating from 3275 embryos transferred on Day 3 conducted in 24 clinics between 2009 and 2014. The data represented different culture conditions (reduced and ambient oxygen with various culture medium strategies) and fertilization methods (IVF, ICSI). The capability to predict blastocyst formation was evaluated on an independent set of morphokinetic data from 11 218 embryos which had been cultured to Day 5. PARTICIPANTS/MATERIALS, SETTING, METHODS The algorithm was developed by applying automated recursive partitioning to a large number of annotation types and derived equations, progressing to a five-fold cross-validation test of the complete data set and a validation test of different incubation conditions and fertilization methods. The results were expressed as receiver operating characteristics curves using the area under the

Help, I don’t know which sea ice algorithm to use?!: Developing an authoritative sea ice climate data record

NASA Astrophysics Data System (ADS)

Meier, W.; Stroeve, J.; Duerr, R. E.; Fetterer, F. M.

2009-12-01

The declining Arctic sea ice is one of the most dramatic indicators of climate change and is being recognized as a key factor in future climate impacts on biology, human activities, and global climate change. As such, the audience for sea ice data is expanding well beyond the sea ice community. The most comprehensive sea ice data are from a series of satellite-borne passive microwave sensors. They provide a near-complete daily timeseries of sea ice concentration and extent since late-1978. However, there are many complicating issues in using such data, particularly for novice users. First, there is not one single, definitive algorithm, but several. And even for a given algorithm, different processing and quality-control methods may be used, depending on the source. Second, for all algorithms, there are uncertainties in any retrieved value. In general, these limitations are well-known: low spatial-resolution results in an imprecise ice edge determination and lack of small-scale detail (e.g., lead detection) within the ice pack; surface melt depresses concentration values during summer; thin ice is underestimated in some algorithms; some algorithms are sensitive to physical surface temperature; other surface features (e.g., snow) can influence retrieved data. While general error estimates are available for concentration values, currently the products do not carry grid-cell level or even granule level data quality information. Finally, metadata and data provenance information are limited, both of which are essential for future reprocessing. Here we describe the progress to date toward development of sea ice concentration products and outline the future steps needed to complete a sea ice climate data record.

Large-scale image region documentation for fully automated image biomarker algorithm development and evaluation.

PubMed

Reeves, Anthony P; Xie, Yiting; Liu, Shuang

2017-04-01

With the advent of fully automated image analysis and modern machine learning methods, there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. This paper presents a method and implementation for facilitating such datasets that addresses the critical issue of size scaling for algorithm validation and evaluation; current evaluation methods that are usually used in academic studies do not scale to large datasets. This method includes protocols for the documentation of many regions in very large image datasets; the documentation may be incrementally updated by new image data and by improved algorithm outcomes. This method has been used for 5 years in the context of chest health biomarkers from low-dose chest CT images that are now being used with increasing frequency in lung cancer screening practice. The lung scans are segmented into over 100 different anatomical regions, and the method has been applied to a dataset of over 20,000 chest CT images. Using this framework, the computer algorithms have been developed to achieve over 90% acceptable image segmentation on the complete dataset.

Estimating the kinetic parameters of activated sludge storage using weighted non-linear least-squares and accelerating genetic algorithm.

PubMed

Fang, Fang; Ni, Bing-Jie; Yu, Han-Qing

2009-06-01

In this study, weighted non-linear least-squares analysis and accelerating genetic algorithm are integrated to estimate the kinetic parameters of substrate consumption and storage product formation of activated sludge. A storage product formation equation is developed and used to construct the objective function for the determination of its production kinetics. The weighted least-squares analysis is employed to calculate the differences in the storage product concentration between the model predictions and the experimental data as the sum of squared weighted errors. The kinetic parameters for the substrate consumption and the storage product formation are estimated to be the maximum heterotrophic growth rate of 0.121/h, the yield coefficient of 0.44 mg CODX/mg CODS (COD, chemical oxygen demand) and the substrate half saturation constant of 16.9 mg/L, respectively, by minimizing the objective function using a real-coding-based accelerating genetic algorithm. Also, the fraction of substrate electrons diverted to the storage product formation is estimated to be 0.43 mg CODSTO/mg CODS. The validity of our approach is confirmed by the results of independent tests and the kinetic parameter values reported in literature, suggesting that this approach could be useful to evaluate the product formation kinetics of mixed cultures like activated sludge. More importantly, as this integrated approach could estimate the kinetic parameters rapidly and accurately, it could be applied to other biological processes.

The development of algorithms for the deployment of new version of GEM-detector-based acquisition system

NASA Astrophysics Data System (ADS)

Krawczyk, Rafał D.; Czarski, Tomasz; Kolasiński, Piotr; Linczuk, Paweł; Poźniak, Krzysztof T.; Chernyshova, Maryna; Kasprowicz, Grzegorz; Wojeński, Andrzej; Zabolotny, Wojciech; Zienkiewicz, Paweł

2016-09-01

This article is an overview of what has been implemented in the process of development and testing the GEM detector based acquisition system in terms of post-processing algorithms. Information is given on mex functions for extended statistics collection, unified hex topology and optimized S-DAQ algorithm for splitting overlapped signals. Additional discussion on bottlenecks and major factors concerning optimization is presented.

The Rational Hybrid Monte Carlo algorithm

NASA Astrophysics Data System (ADS)

Clark, Michael

2006-12-01

The past few years have seen considerable progress in algorithmic development for the generation of gauge fields including the effects of dynamical fermions. The Rational Hybrid Monte Carlo (RHMC) algorithm, where Hybrid Monte Carlo is performed using a rational approximation in place the usual inverse quark matrix kernel is one of these developments. This algorithm has been found to be extremely beneficial in many areas of lattice QCD (chiral fermions, finite temperature, Wilson fermions etc.). We review the algorithm and some of these benefits, and we compare against other recent algorithm developements. We conclude with an update of the Berlin wall plot comparing costs of all popular fermion formulations.

Utilization of Airborne and in Situ Data Obtained in SGP99, SMEX02, CLASIC and SMAPVEX08 Field Campaigns for SMAP Soil Moisture Algorithm Development and Validation

NASA Technical Reports Server (NTRS)

Colliander, Andreas; Chan, Steven; Yueh, Simon; Cosh, Michael; Bindlish, Rajat; Jackson, Tom; Njoku, Eni

2010-01-01

Field experiment data sets that include coincident remote sensing measurements and in situ sampling will be valuable in the development and validation of the soil moisture algorithms of the NASA's future SMAP (Soil Moisture Active and Passive) mission. This paper presents an overview of the field experiment data collected from SGP99, SMEX02, CLASIC and SMAPVEX08 campaigns. Common in these campaigns were observations of the airborne PALS (Passive and Active L- and S-band) instrument, which was developed to acquire radar and radiometer measurements at low frequencies. The combined set of the PALS measurements and ground truth obtained from all these campaigns was under study. The investigation shows that the data set contains a range of soil moisture values collected under a limited number of conditions. The quality of both PALS and ground truth data meets the needs of the SMAP algorithm development and validation. The data set has already made significant impact on the science behind SMAP mission. The areas where complementing of the data would be most beneficial are also discussed.

Predicting mining activity with parallel genetic algorithms

USGS Publications Warehouse

Talaie, S.; Leigh, R.; Louis, S.J.; Raines, G.L.; Beyer, H.G.; O'Reilly, U.M.; Banzhaf, Arnold D.; Blum, W.; Bonabeau, C.; Cantu-Paz, E.W.; ,; ,

2005-01-01

We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa statistic to measure correlation between ground truth data and data predicted by the model. Within the genetic algorithm, we introduce a new evaluation function sensitive to spatial correctness and we explore the idea of evolving different rule parameters for different subregions of the land. We reduce the time required to run a simulation from 6 hours to 10 minutes by parallelizing the code and employing a 10-node cluster. Our empirical results suggest that using the spatially sensitive evaluation function does indeed improve the performance of the model and our preliminary results also show that evolving different rule parameters for different regions tends to improve overall model performance. Copyright 2005 ACM.

Nonlinear Motion Cueing Algorithm: Filtering at Pilot Station and Development of the Nonlinear Optimal Filters for Pitch and Roll

NASA Technical Reports Server (NTRS)

Zaychik, Kirill B.; Cardullo, Frank M.

2012-01-01

Telban and Cardullo have developed and successfully implemented the non-linear optimal motion cueing algorithm at the Visual Motion Simulator (VMS) at the NASA Langley Research Center in 2005. The latest version of the non-linear algorithm performed filtering of motion cues in all degrees-of-freedom except for pitch and roll. This manuscript describes the development and implementation of the non-linear optimal motion cueing algorithm for the pitch and roll degrees of freedom. Presented results indicate improved cues in the specified channels as compared to the original design. To further advance motion cueing in general, this manuscript describes modifications to the existing algorithm, which allow for filtering at the location of the pilot's head as opposed to the centroid of the motion platform. The rational for such modification to the cueing algorithms is that the location of the pilot's vestibular system must be taken into account as opposed to the off-set of the centroid of the cockpit relative to the center of rotation alone. Results provided in this report suggest improved performance of the motion cueing algorithm.

Development of Serum Marker Models to Increase Diagnostic Accuracy of Advanced Fibrosis in Nonalcoholic Fatty Liver Disease: The New LINKI Algorithm Compared with Established Algorithms.

PubMed

Lykiardopoulos, Byron; Hagström, Hannes; Fredrikson, Mats; Ignatova, Simone; Stål, Per; Hultcrantz, Rolf; Ekstedt, Mattias; Kechagias, Stergios

2016-01-01

Detection of advanced fibrosis (F3-F4) in nonalcoholic fatty liver disease (NAFLD) is important for ascertaining prognosis. Serum markers have been proposed as alternatives to biopsy. We attempted to develop a novel algorithm for detection of advanced fibrosis based on a more efficient combination of serological markers and to compare this with established algorithms. We included 158 patients with biopsy-proven NAFLD. Of these, 38 had advanced fibrosis. The following fibrosis algorithms were calculated: NAFLD fibrosis score, BARD, NIKEI, NASH-CRN regression score, APRI, FIB-4, King´s score, GUCI, Lok index, Forns score, and ELF. Study population was randomly divided in a training and a validation group. A multiple logistic regression analysis using bootstrapping methods was applied to the training group. Among many variables analyzed age, fasting glucose, hyaluronic acid and AST were included, and a model (LINKI-1) for predicting advanced fibrosis was created. Moreover, these variables were combined with platelet count in a mathematical way exaggerating the opposing effects, and alternative models (LINKI-2) were also created. Models were compared using area under the receiver operator characteristic curves (AUROC). Of established algorithms FIB-4 and King´s score had the best diagnostic accuracy with AUROCs 0.84 and 0.83, respectively. Higher accuracy was achieved with the novel LINKI algorithms. AUROCs in the total cohort for LINKI-1 was 0.91 and for LINKI-2 models 0.89. The LINKI algorithms for detection of advanced fibrosis in NAFLD showed better accuracy than established algorithms and should be validated in further studies including larger cohorts.

Research of the multimodal brain-tumor segmentation algorithm

NASA Astrophysics Data System (ADS)

Lu, Yisu; Chen, Wufan

2015-12-01

It is well-known that the number of clusters is one of the most important parameters for automatic segmentation. However, it is difficult to define owing to the high diversity in appearance of tumor tissue among different patients and the ambiguous boundaries of lesions. In this study, a nonparametric mixture of Dirichlet process (MDP) model is applied to segment the tumor images, and the MDP segmentation can be performed without the initialization of the number of clusters. A new nonparametric segmentation algorithm combined with anisotropic diffusion and a Markov random field (MRF) smooth constraint is proposed in this study. Besides the segmentation of single modal brain tumor images, we developed the algorithm to segment multimodal brain tumor images by the magnetic resonance (MR) multimodal features and obtain the active tumor and edema in the same time. The proposed algorithm is evaluated and compared with other approaches. The accuracy and computation time of our algorithm demonstrates very impressive performance.

GLASS daytime all-wave net radiation product: Algorithm development and preliminary validation

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

Jiang, Bo; Liang, Shunlin; Ma, Han

Mapping surface all-wave net radiation (R n) is critically needed for various applications. Several existing R n products from numerical models and satellite observations have coarse spatial resolutions and their accuracies may not meet the requirements of land applications. In this study, we develop the Global LAnd Surface Satellite (GLASS) daytime R n product at a 5 km spatial resolution. Its algorithm for converting shortwave radiation to all-wave net radiation using the Multivariate Adaptive Regression Splines (MARS) model is determined after comparison with three other algorithms. The validation of the GLASS R n product based on high-quality in situ measurementsmore » in the United States shows a coefficient of determination value of 0.879, an average root mean square error value of 31.61 Wm -2, and an average bias of 17.59 Wm -2. Furthermore, we also compare our product/algorithm with another satellite product (CERES-SYN) and two reanalysis products (MERRA and JRA55), and find that the accuracy of the much higher spatial resolution GLASS R n product is satisfactory. The GLASS R n product from 2000 to the present is operational and freely available to the public.« less

GLASS daytime all-wave net radiation product: Algorithm development and preliminary validation

DOE PAGES

Jiang, Bo; Liang, Shunlin; Ma, Han; ...

2016-03-09

Mapping surface all-wave net radiation (R n) is critically needed for various applications. Several existing R n products from numerical models and satellite observations have coarse spatial resolutions and their accuracies may not meet the requirements of land applications. In this study, we develop the Global LAnd Surface Satellite (GLASS) daytime R n product at a 5 km spatial resolution. Its algorithm for converting shortwave radiation to all-wave net radiation using the Multivariate Adaptive Regression Splines (MARS) model is determined after comparison with three other algorithms. The validation of the GLASS R n product based on high-quality in situ measurementsmore » in the United States shows a coefficient of determination value of 0.879, an average root mean square error value of 31.61 Wm -2, and an average bias of 17.59 Wm -2. Furthermore, we also compare our product/algorithm with another satellite product (CERES-SYN) and two reanalysis products (MERRA and JRA55), and find that the accuracy of the much higher spatial resolution GLASS R n product is satisfactory. The GLASS R n product from 2000 to the present is operational and freely available to the public.« less

Development of GK-2A cloud optical and microphysical properties retrieval algorithm

NASA Astrophysics Data System (ADS)

Yang, Y.; Yum, S. S.; Um, J.

2017-12-01

Cloud and aerosol radiative forcing is known to be one of the the largest uncertainties in climate change prediction. To reduce this uncertainty, remote sensing observation of cloud radiative and microphysical properties have been used since 1970s and the corresponding remote sensing techniques and instruments have been developed. As a part of such effort, Geo-KOMPSAT-2A (Geostationary Korea Multi-Purpose Satellite-2A, GK-2A) will be launched in 2018. On the GK-2A, the Advanced Meteorological Imager (AMI) is primary instrument which have 3 visible, 3 near-infrared, and 10 infrared channels. To retrieve optical and microphysical properties of clouds using AMI measurements, the preliminary version of new cloud retrieval algorithm for GK-2A was developed and several validation tests were conducted. This algorithm retrieves cloud optical thickness (COT), cloud effective radius (CER), liquid water path (LWP), and ice water path (IWP), so we named this algorithm as Daytime Cloud Optical thickness, Effective radius and liquid and ice Water path (DCOEW). The DCOEW uses cloud reflectance at visible and near-infrared channels as input data. An optimal estimation (OE) approach that requires appropriate a-priori values and measurement error information is used to retrieve COT and CER. LWP and IWP are calculated using empirical relationships between COT/CER and cloud water path that were determined previously. To validate retrieved cloud properties, we compared DCOEW output data with other operational satellite data. For COT and CER validation, we used two different data sets. To compare algorithms that use cloud reflectance at visible and near-IR channels as input data, MODIS MYD06 cloud product was selected. For the validation with cloud products that are based on microwave measurements, COT(2B-TAU)/CER(2C-ICE) data retrieved from CloudSat cloud profiling radar (W-band, 94 GHz) was used. For cloud water path validation, AMSR-2 Level-3 Cloud liquid water data was used

MACVIA clinical decision algorithm in adolescents and adults with allergic rhinitis.

PubMed

Bousquet, Jean; Schünemann, Holger J; Hellings, Peter W; Arnavielhe, Sylvie; Bachert, Claus; Bedbrook, Anna; Bergmann, Karl-Christian; Bosnic-Anticevich, Sinthia; Brozek, Jan; Calderon, Moises; Canonica, G Walter; Casale, Thomas B; Chavannes, Niels H; Cox, Linda; Chrystyn, Henry; Cruz, Alvaro A; Dahl, Ronald; De Carlo, Giuseppe; Demoly, Pascal; Devillier, Phillipe; Dray, Gérard; Fletcher, Monica; Fokkens, Wytske J; Fonseca, Joao; Gonzalez-Diaz, Sandra N; Grouse, Lawrence; Keil, Thomas; Kuna, Piotr; Larenas-Linnemann, Désirée; Lodrup Carlsen, Karin C; Meltzer, Eli O; Mullol, Jaoquim; Muraro, Antonella; Naclerio, Robert N; Palkonen, Susanna; Papadopoulos, Nikolaos G; Passalacqua, Giovanni; Price, David; Ryan, Dermot; Samolinski, Boleslaw; Scadding, Glenis K; Sheikh, Aziz; Spertini, François; Valiulis, Arunas; Valovirta, Erkka; Walker, Samantha; Wickman, Magnus; Yorgancioglu, Arzu; Haahtela, Tari; Zuberbier, Torsten

2016-08-01

The selection of pharmacotherapy for patients with allergic rhinitis (AR) depends on several factors, including age, prominent symptoms, symptom severity, control of AR, patient preferences, and cost. Allergen exposure and the resulting symptoms vary, and treatment adjustment is required. Clinical decision support systems (CDSSs) might be beneficial for the assessment of disease control. CDSSs should be based on the best evidence and algorithms to aid patients and health care professionals to jointly determine treatment and its step-up or step-down strategy depending on AR control. Contre les MAladies Chroniques pour un VIeillissement Actif en Languedoc-Roussillon (MACVIA-LR [fighting chronic diseases for active and healthy ageing]), one of the reference sites of the European Innovation Partnership on Active and Healthy Ageing, has initiated an allergy sentinel network (the MACVIA-ARIA Sentinel Network). A CDSS is currently being developed to optimize AR control. An algorithm developed by consensus is presented in this article. This algorithm should be confirmed by appropriate trials. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Systems Engineering Approach to Develop Guidance, Navigation and Control Algorithms for Unmanned Ground Vehicle

DTIC Science & Technology

2016-09-01

identification and tracking algorithm. 14. SUBJECT TERMS unmanned ground vehicles , pure pursuit, vector field histogram, feature recognition 15. NUMBER OF...located within the various theaters of war. The pace for the development and deployment of unmanned ground vehicles (UGV) was, however, not keeping...DEVELOPMENT OF UNMANNED GROUND VEHICLES The development and fielding of UGVs in an operational role are not a new concept in the battlefield. In

An Image-Based Algorithm for Precise and Accurate High Throughput Assessment of Drug Activity against the Human Parasite Trypanosoma cruzi

PubMed Central

Moraes, Carolina Borsoi; Yang, Gyongseon; Kang, Myungjoo; Freitas-Junior, Lucio H.; Hansen, Michael A. E.

2014-01-01

We present a customized high content (image-based) and high throughput screening algorithm for the quantification of Trypanosoma cruzi infection in host cells. Based solely on DNA staining and single-channel images, the algorithm precisely segments and identifies the nuclei and cytoplasm of mammalian host cells as well as the intracellular parasites infecting the cells. The algorithm outputs statistical parameters including the total number of cells, number of infected cells and the total number of parasites per image, the average number of parasites per infected cell, and the infection ratio (defined as the number of infected cells divided by the total number of cells). Accurate and precise estimation of these parameters allow for both quantification of compound activity against parasites, as well as the compound cytotoxicity, thus eliminating the need for an additional toxicity-assay, hereby reducing screening costs significantly. We validate the performance of the algorithm using two known drugs against T.cruzi: Benznidazole and Nifurtimox. Also, we have checked the performance of the cell detection with manual inspection of the images. Finally, from the titration of the two compounds, we confirm that the algorithm provides the expected half maximal effective concentration (EC50) of the anti-T. cruzi activity. PMID:24503652

High reliability - low noise radionuclide signature identification algorithms for border security applications

NASA Astrophysics Data System (ADS)

Lee, Sangkyu

Illicit trafficking and smuggling of radioactive materials and special nuclear materials (SNM) are considered as one of the most important recent global nuclear threats. Monitoring the transport and safety of radioisotopes and SNM are challenging due to their weak signals and easy shielding. Great efforts worldwide are focused at developing and improving the detection technologies and algorithms, for accurate and reliable detection of radioisotopes of interest in thus better securing the borders against nuclear threats. In general, radiation portal monitors enable detection of gamma and neutron emitting radioisotopes. Passive or active interrogation techniques, present and/or under the development, are all aimed at increasing accuracy, reliability, and in shortening the time of interrogation as well as the cost of the equipment. Equally important efforts are aimed at advancing algorithms to process the imaging data in an efficient manner providing reliable "readings" of the interiors of the examined volumes of various sizes, ranging from cargos to suitcases. The main objective of this thesis is to develop two synergistic algorithms with the goal to provide highly reliable - low noise identification of radioisotope signatures. These algorithms combine analysis of passive radioactive detection technique with active interrogation imaging techniques such as gamma radiography or muon tomography. One algorithm consists of gamma spectroscopy and cosmic muon tomography, and the other algorithm is based on gamma spectroscopy and gamma radiography. The purpose of fusing two detection methodologies per algorithm is to find both heavy-Z radioisotopes and shielding materials, since radionuclides can be identified with gamma spectroscopy, and shielding materials can be detected using muon tomography or gamma radiography. These combined algorithms are created and analyzed based on numerically generated images of various cargo sizes and materials. In summary, the three detection

Development of a simple algorithm to guide the effective management of traumatic cardiac arrest.

PubMed

Lockey, David J; Lyon, Richard M; Davies, Gareth E

2013-06-01

Major trauma is the leading worldwide cause of death in young adults. The mortality from traumatic cardiac arrest remains high but survival with good neurological outcome from cardiopulmonary arrest following major trauma has been regularly reported. Rapid, effective intervention is required to address potential reversible causes of traumatic cardiac arrest if the victim is to survive. Current ILCOR guidelines do not contain a standard algorithm for management of traumatic cardiac arrest. We present a simple algorithm to manage the major trauma patient in actual or imminent cardiac arrest. We reviewed the published English language literature on traumatic cardiac arrest and major trauma management. A treatment algorithm was developed based on this and the experience of treatment of more than a thousand traumatic cardiac arrests by a physician - paramedic pre-hospital trauma service. The algorithm addresses the need treat potential reversible causes of traumatic cardiac arrest. This includes immediate resuscitative thoracotomy in cases of penetrating chest trauma, airway management, optimising oxygenation, correction of hypovolaemia and chest decompression to exclude tension pneumothorax. The requirement to rapidly address a number of potentially reversible pathologies in a short time period lends the management of traumatic cardiac arrest to a simple treatment algorithm. A standardised approach may prevent delay in diagnosis and treatment and improve current poor survival rates. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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.

Development and Validation of an Algorithm to Identify Patients with Multiple Myeloma Using Administrative Claims Data.

PubMed

Princic, Nicole; Gregory, Chris; Willson, Tina; Mahue, Maya; Felici, Diana; Werther, Winifred; Lenhart, Gregory; Foley, Kathleen A

2016-01-01

The objective was to expand on prior work by developing and validating a new algorithm to identify multiple myeloma (MM) patients in administrative claims. Two files were constructed to select MM cases from MarketScan Oncology Electronic Medical Records (EMR) and controls from the MarketScan Primary Care EMR during January 1, 2000-March 31, 2014. Patients were linked to MarketScan claims databases, and files were merged. Eligible cases were age ≥18, had a diagnosis and visit for MM in the Oncology EMR, and were continuously enrolled in claims for ≥90 days preceding and ≥30 days after diagnosis. Controls were age ≥18, had ≥12 months of overlap in claims enrollment (observation period) in the Primary Care EMR and ≥1 claim with an ICD-9-CM diagnosis code of MM (203.0×) during that time. Controls were excluded if they had chemotherapy; stem cell transplant; or text documentation of MM in the EMR during the observation period. A split sample was used to develop and validate algorithms. A maximum of 180 days prior to and following each MM diagnosis was used to identify events in the diagnostic process. Of 20 algorithms explored, the baseline algorithm of 2 MM diagnoses and the 3 best performing were validated. Values for sensitivity, specificity, and positive predictive value (PPV) were calculated. Three claims-based algorithms were validated with ~10% improvement in PPV (87-94%) over prior work (81%) and the baseline algorithm (76%) and can be considered for future research. Consistent with prior work, it was found that MM diagnoses before and after tests were needed.

Strategic Control Algorithm Development : Volume 4A. Computer Program Report.

DOT National Transportation Integrated Search

1974-08-01

A description of the strategic algorithm evaluation model is presented, both at the user and programmer levels. The model representation of an airport configuration, environmental considerations, the strategic control algorithm logic, and the airplan...

A social activity and physical contact-based routing algorithm in mobile opportunistic networks for emergency response to sudden disasters

NASA Astrophysics Data System (ADS)

Wang, Xiaoming; Lin, Yaguang; Zhang, Shanshan; Cai, Zhipeng

2017-05-01

Sudden disasters such as earthquake, flood and hurricane necessitate the employment of communication networks to carry out emergency response activities. Routing has a significant impact on the functionality, performance and flexibility of communication networks. In this article, the routing problem is studied considering the delivery ratio of messages, the overhead ratio of messages and the average delay of messages in mobile opportunistic networks (MONs) for enterprise-level emergency response communications in sudden disaster scenarios. Unlike the traditional routing methods for MONS, this article presents a new two-stage spreading and forwarding dynamic routing algorithm based on the proposed social activity degree and physical contact factor for mobile customers. A new modelling method for describing a dynamic evolving process of the topology structure of a MON is first proposed. Then a multi-copy spreading strategy based on the social activity degree of nodes and a single-copy forwarding strategy based on the physical contact factor between nodes are designed. Compared with the most relevant routing algorithms such as Epidemic, Prophet, Labelled-sim, Dlife-comm and Distribute-sim, the proposed routing algorithm can significantly increase the delivery ratio of messages, and decrease the overhead ratio and average delay of messages.

NOSS Altimeter Detailed Algorithm specifications

NASA Technical Reports Server (NTRS)

Hancock, D. W.; Mcmillan, J. D.

1982-01-01

The details of the algorithms and data sets required for satellite radar altimeter data processing are documented in a form suitable for (1) development of the benchmark software and (2) coding the operational software. The algorithms reported in detail are those established for altimeter processing. The algorithms which required some additional development before documenting for production were only scoped. The algorithms are divided into two levels of processing. The first level converts the data to engineering units and applies corrections for instrument variations. The second level provides geophysical measurements derived from altimeter parameters for oceanographic users.

Large-scale image region documentation for fully automated image biomarker algorithm development and evaluation

PubMed Central

Reeves, Anthony P.; Xie, Yiting; Liu, Shuang

2017-01-01

Abstract. With the advent of fully automated image analysis and modern machine learning methods, there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. This paper presents a method and implementation for facilitating such datasets that addresses the critical issue of size scaling for algorithm validation and evaluation; current evaluation methods that are usually used in academic studies do not scale to large datasets. This method includes protocols for the documentation of many regions in very large image datasets; the documentation may be incrementally updated by new image data and by improved algorithm outcomes. This method has been used for 5 years in the context of chest health biomarkers from low-dose chest CT images that are now being used with increasing frequency in lung cancer screening practice. The lung scans are segmented into over 100 different anatomical regions, and the method has been applied to a dataset of over 20,000 chest CT images. Using this framework, the computer algorithms have been developed to achieve over 90% acceptable image segmentation on the complete dataset. PMID:28612037

Development of a Real-Time Pulse Processing Algorithm for TES-Based X-Ray Microcalorimeters

NASA Technical Reports Server (NTRS)

Tan, Hui; Hennig, Wolfgang; Warburton, William K.; Doriese, W. Bertrand; Kilbourne, Caroline A.

2011-01-01

We report here a real-time pulse processing algorithm for superconducting transition-edge sensor (TES) based x-ray microcalorimeters. TES-based. microca1orimeters offer ultra-high energy resolutions, but the small volume of each pixel requires that large arrays of identical microcalorimeter pixe1s be built to achieve sufficient detection efficiency. That in turn requires as much pulse processing as possible must be performed at the front end of readout electronics to avoid transferring large amounts of data to a host computer for post-processing. Therefore, a real-time pulse processing algorithm that not only can be implemented in the readout electronics but also achieve satisfactory energy resolutions is desired. We have developed an algorithm that can be easily implemented. in hardware. We then tested the algorithm offline using several data sets acquired with an 8 x 8 Goddard TES x-ray calorimeter array and 2x16 NIST time-division SQUID multiplexer. We obtained an average energy resolution of close to 3.0 eV at 6 keV for the multiplexed pixels while preserving over 99% of the events in the data sets.

Genetic Algorithms and Local Search

NASA Technical Reports Server (NTRS)

Whitley, Darrell

1996-01-01

The first part of this presentation is a tutorial level introduction to the principles of genetic search and models of simple genetic algorithms. The second half covers the combination of genetic algorithms with local search methods to produce hybrid genetic algorithms. Hybrid algorithms can be modeled within the existing theoretical framework developed for simple genetic algorithms. An application of a hybrid to geometric model matching is given. The hybrid algorithm yields results that improve on the current state-of-the-art for this problem.

An algorithm to improve diagnostic accuracy in diabetes in computerised problem orientated medical records (POMR) compared with an established algorithm developed in episode orientated records (EOMR).

PubMed

de Lusignan, Simon; Liaw, Siaw-Teng; Dedman, Daniel; Khunti, Kamlesh; Sadek, Khaled; Jones, Simon

2015-06-05

An algorithm that detects errors in diagnosis, classification or coding of diabetes in primary care computerised medial record (CMR) systems is currently available. However, this was developed on CMR systems that are episode orientated medical records (EOMR); and do not force the user to always code a problem or link data to an existing one. More strictly problem orientated medical record (POMR) systems mandate recording a problem and linking consultation data to them. To compare the rates of detection of diagnostic accuracy using an algorithm developed in EOMR with a new POMR specific algorithm. We used data from The Health Improvement Network (THIN) database (N = 2,466,364) to identify a population of 100,513 (4.08%) patients considered likely to have diabetes. We recalibrated algorithms designed to classify cases of diabetes to take account of that POMR enforced coding consistency in the computerised medical record systems [In Practice Systems (InPS) Vision] that contribute data to THIN. We explored the different proportions of people classified as having type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM) and with diabetes unclassifiable as either T1DM or T2DM. We compared proportions using chi-square tests and used Tukey's test to compare the characteristics of the people in each group. The prevalence of T1DM using the original EOMR algorithm was 0.38% (9,264/2,466,364), and for T2DM 3.22% (79,417/2,466,364). The prevalence using the new POMR algorithm was 0.31% (7,750/2,466,364) T1DM and 3.65% (89,990/2,466,364) T2DM. The EOMR algorithms also left more people unclassified 11,439 (12%), as to their type of diabetes compared with 2,380 (2.4%), for the new algorithm. Those people who were only classified by the EOMR system differed in terms of older age, and apparently better glycaemic control, despite not being prescribed medication for their diabetes (p < 0.005). Increasing the degree of problem orientation of the medical record system can

New human-centered linear and nonlinear motion cueing algorithms for control of simulator motion systems

NASA Astrophysics Data System (ADS)

Telban, Robert J.

While the performance of flight simulator motion system hardware has advanced substantially, the development of the motion cueing algorithm, the software that transforms simulated aircraft dynamics into realizable motion commands, has not kept pace. To address this, new human-centered motion cueing algorithms were developed. A revised "optimal algorithm" uses time-invariant filters developed by optimal control, incorporating human vestibular system models. The "nonlinear algorithm" is a novel approach that is also formulated by optimal control, but can also be updated in real time. It incorporates a new integrated visual-vestibular perception model that includes both visual and vestibular sensation and the interaction between the stimuli. A time-varying control law requires the matrix Riccati equation to be solved in real time by a neurocomputing approach. Preliminary pilot testing resulted in the optimal algorithm incorporating a new otolith model, producing improved motion cues. The nonlinear algorithm vertical mode produced a motion cue with a time-varying washout, sustaining small cues for longer durations and washing out large cues more quickly compared to the optimal algorithm. The inclusion of the integrated perception model improved the responses to longitudinal and lateral cues. False cues observed with the NASA adaptive algorithm were absent. As a result of unsatisfactory sensation, an augmented turbulence cue was added to the vertical mode for both the optimal and nonlinear algorithms. The relative effectiveness of the algorithms, in simulating aircraft maneuvers, was assessed with an eleven-subject piloted performance test conducted on the NASA Langley Visual Motion Simulator (VMS). Two methods, the quasi-objective NASA Task Load Index (TLX), and power spectral density analysis of pilot control, were used to assess pilot workload. TLX analysis reveals, in most cases, less workload and variation among pilots with the nonlinear algorithm. Control input

Developing Subdomain Allocation Algorithms Based on Spatial and Communicational Constraints to Accelerate Dust Storm Simulation

PubMed Central

Gui, Zhipeng; Yu, Manzhu; Yang, Chaowei; Jiang, Yunfeng; Chen, Songqing; Xia, Jizhe; Huang, Qunying; Liu, Kai; Li, Zhenlong; Hassan, Mohammed Anowarul; Jin, Baoxuan

2016-01-01

Dust storm has serious disastrous impacts on environment, human health, and assets. The developments and applications of dust storm models have contributed significantly to better understand and predict the distribution, intensity and structure of dust storms. However, dust storm simulation is a data and computing intensive process. To improve the computing performance, high performance computing has been widely adopted by dividing the entire study area into multiple subdomains and allocating each subdomain on different computing nodes in a parallel fashion. Inappropriate allocation may introduce imbalanced task loads and unnecessary communications among computing nodes. Therefore, allocation is a key factor that may impact the efficiency of parallel process. An allocation algorithm is expected to consider the computing cost and communication cost for each computing node to minimize total execution time and reduce overall communication cost for the entire simulation. This research introduces three algorithms to optimize the allocation by considering the spatial and communicational constraints: 1) an Integer Linear Programming (ILP) based algorithm from combinational optimization perspective; 2) a K-Means and Kernighan-Lin combined heuristic algorithm (K&K) integrating geometric and coordinate-free methods by merging local and global partitioning; 3) an automatic seeded region growing based geometric and local partitioning algorithm (ASRG). The performance and effectiveness of the three algorithms are compared based on different factors. Further, we adopt the K&K algorithm as the demonstrated algorithm for the experiment of dust model simulation with the non-hydrostatic mesoscale model (NMM-dust) and compared the performance with the MPI default sequential allocation. The results demonstrate that K&K method significantly improves the simulation performance with better subdomain allocation. This method can also be adopted for other relevant atmospheric and numerical

Development of ocean color algorithms for estimating chlorophyll-a concentrations and inherent optical properties using gene expression programming (GEP).

PubMed

Chang, Chih-Hua

2015-03-09

This paper proposes new inversion algorithms for the estimation of Chlorophyll-a concentration (Chla) and the ocean's inherent optical properties (IOPs) from the measurement of remote sensing reflectance (Rrs). With in situ data from the NASA bio-optical marine algorithm data set (NOMAD), inversion algorithms were developed by the novel gene expression programming (GEP) approach, which creates, manipulates and selects the most appropriate tree-structured functions based on evolutionary computing. The limitations and validity of the proposed algorithms are evaluated by simulated Rrs spectra with respect to NOMAD, and a closure test for IOPs obtained at a single reference wavelength. The application of GEP-derived algorithms is validated against in situ, synthetic and satellite match-up data sets compiled by NASA and the International Ocean Color Coordinate Group (IOCCG). The new algorithms are able to provide Chla and IOPs retrievals to those derived by other state-of-the-art regression approaches and obtained with the semi- and quasi-analytical algorithms, respectively. In practice, there are no significant differences between GEP, support vector regression, and multilayer perceptron model in terms of the overall performance. The GEP-derived algorithms are successfully applied in processing the images taken by the Sea Wide Field-of-view Sensor (SeaWiFS), generate Chla and IOPs maps which show better details of developing algal blooms, and give more information on the distribution of water constituents between different water bodies.

A Feature Selection Algorithm to Compute Gene Centric Methylation from Probe Level Methylation Data.

PubMed

Baur, Brittany; Bozdag, Serdar

2016-01-01

DNA methylation is an important epigenetic event that effects gene expression during development and various diseases such as cancer. Understanding the mechanism of action of DNA methylation is important for downstream analysis. In the Illumina Infinium HumanMethylation 450K array, there are tens of probes associated with each gene. Given methylation intensities of all these probes, it is necessary to compute which of these probes are most representative of the gene centric methylation level. In this study, we developed a feature selection algorithm based on sequential forward selection that utilized different classification methods to compute gene centric DNA methylation using probe level DNA methylation data. We compared our algorithm to other feature selection algorithms such as support vector machines with recursive feature elimination, genetic algorithms and ReliefF. We evaluated all methods based on the predictive power of selected probes on their mRNA expression levels and found that a K-Nearest Neighbors classification using the sequential forward selection algorithm performed better than other algorithms based on all metrics. We also observed that transcriptional activities of certain genes were more sensitive to DNA methylation changes than transcriptional activities of other genes. Our algorithm was able to predict the expression of those genes with high accuracy using only DNA methylation data. Our results also showed that those DNA methylation-sensitive genes were enriched in Gene Ontology terms related to the regulation of various biological processes.

Measuring river from the cloud - River width algorithm development on Google Earth Engine

NASA Astrophysics Data System (ADS)

Yang, X.; Pavelsky, T.; Allen, G. H.; Donchyts, G.

2017-12-01

Rivers are some of the most dynamic features of the terrestrial land surface. They help distribute freshwater, nutrients, sediment, and they are also responsible for some of the greatest natural hazards. Despite their importance, our understanding of river behavior is limited at the global scale, in part because we do not have a river observational dataset that spans both time and space. Remote sensing data represent a rich, largely untapped resource for observing river dynamics. In particular, publicly accessible archives of satellite optical imagery, which date back to the 1970s, can be used to study the planview morphodynamics of rivers at the global scale. Here we present an image processing algorithm developed using the Google Earth Engine cloud-based platform, that can automatically extracts river centerlines and widths from Landsat 5, 7, and 8 scenes at 30 m resolution. Our algorithm makes use of the latest monthly global surface water history dataset and an existing Global River Width from Landsat (GRWL) dataset to efficiently extract river masks from each Landsat scene. Then a combination of distance transform and skeletonization techniques are used to extract river centerlines. Finally, our algorithm calculates wetted river width at each centerline pixel perpendicular to its local centerline direction. We validated this algorithm using in situ data estimated from 16 USGS gauge stations (N=1781). We find that 92% of the width differences are within 60 m (i.e. the minimum length of 2 Landsat pixels). Leveraging Earth Engine's infrastructure of collocated data and processing power, our goal is to use this algorithm to reconstruct the morphodynamic history of rivers globally by processing over 100,000 Landsat 5 scenes, covering from 1984 to 2013.

GEONEX: algorithm development and validation of Gross Primary Production from geostationary satellites

NASA Astrophysics Data System (ADS)

Hashimoto, H.; Wang, W.; Ganguly, S.; Li, S.; Michaelis, A.; Higuchi, A.; Takenaka, H.; Nemani, R. R.

2017-12-01

New geostationary sensors such as the AHI (Advanced Himawari Imager on Himawari-8) and the ABI (Advanced Baseline Imager on GOES-16) have the potential to advance ecosystem modeling particularly of diurnally varying phenomenon through frequent observations. These sensors have similar channels as in MODIS (MODerate resolution Imaging Spectroradiometer), and allow us to utilize the knowledge and experience in MODIS data processing. Here, we developed sub-hourly Gross Primary Production (GPP) algorithm, leverating the MODIS 17 GPP algorithm. We run the model at 1-km resolution over Japan and Australia using geo-corrected AHI data. Solar radiation was directly calculated from AHI using a neural network technique. The other necessary climate data were derived from weather stations and other satellite data. The sub-hourly estimates of GPP were first compared with ground-measured GPP at various Fluxnet sites. We also compared the AHI GPP with MODIS 17 GPP, and analyzed the differences in spatial patterns and the effect of diurnal changes in climate forcing. The sub-hourly GPP products require massive storage and strong computational power. We use NEX (NASA Earth Exchange) facility to produce the GPP products. This GPP algorithm can be applied to other geostationary satellites including GOES-16 in future.

NOAA AVHRR Land Surface Albedo Algorithm Development

NASA Technical Reports Server (NTRS)

Toll, D. L.; Shirey, D.; Kimes, D. S.

1997-01-01

The primary objective of this research is to develop a surface albedo model for the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR). The primary test site is the Konza prairie, Kansas (U.S.A.), used by the International Satellite Land Surface Climatology Project (ISLSCP) in the First ISLSCP Field Experiment (FIFE). In this research, high spectral resolution field spectrometer data was analyzed to simulate AVHRR wavebands and to derive surface albedos. Development of a surface albedo algorithm was completed by analysing a combination of satellite, field spectrometer, and ancillary data. Estimated albedos from the field spectrometer data were compared to reference albedos derived using pyranometer data. Variations from surface anisotropy of reflected solar radiation were found to be the most significant albedo-related error. Additional error or sensitivity came from estimation of a shortwave mid-IR reflectance (1.3-4.0 micro-m) using the AVHRR red and near-IR bands. Errors caused by the use of AVHRR spectral reflectance to estimate both a total visible (0.4-0.7 micro-m) and near-IR (0.7-1.3 micro-m) reflectance were small. The solar spectral integration, using the derived ultraviolet, visible, near-IR and SW mid-IR reflectivities, was not sensitive to many clear-sky changes in atmospheric properties and illumination conditions.

On the development of efficient algorithms for three dimensional fluid flow

NASA Technical Reports Server (NTRS)

Maccormack, R. W.

1988-01-01

The difficulties of constructing efficient algorithms for three-dimensional flow are discussed. Reasonable candidates are analyzed and tested, and most are found to have obvious shortcomings. Yet, there is promise that an efficient class of algorithms exist between the severely time-step sized-limited explicit or approximately factored algorithms and the computationally intensive direct inversion of large sparse matrices by Gaussian elimination.

Two Meanings of Algorithmic Mathematics.

ERIC Educational Resources Information Center

Maurer, Stephen B.

1984-01-01

Two mathematical topics are interpreted from the viewpoints of traditional (performing algorithms) and contemporary (creating algorithms and thinking in terms of them for solving problems and developing theory) algorithmic mathematics. The two topics are Horner's method for evaluating polynomials and Gauss's method for solving systems of linear…

[An improved algorithm for electrohysterogram envelope extraction].

PubMed

Lu, Yaosheng; Pan, Jie; Chen, Zhaoxia; Chen, Zhaoxia

2017-02-01

Extraction uterine contraction signal from abdominal uterine electromyogram(EMG) signal is considered as the most promising method to replace the traditional tocodynamometer(TOCO) for detecting uterine contractions activity. The traditional root mean square(RMS) algorithm has only some limited values in canceling the impulsive noise. In our study, an improved algorithm for uterine EMG envelope extraction was proposed to overcome the problem. Firstly, in our experiment, zero-crossing detection method was used to separate the burst of uterine electrical activity from the raw uterine EMG signal. After processing the separated signals by employing two filtering windows which have different width, we used the traditional RMS algorithm to extract uterus EMG envelope. To assess the performance of the algorithm, the improved algorithm was compared with two existing intensity of uterine electromyogram(IEMG) extraction algorithms. The results showed that the improved algorithm was better than the traditional ones in eliminating impulsive noise present in the uterine EMG signal. The measurement sensitivity and positive predictive value(PPV) of the improved algorithm were 0.952 and 0.922, respectively, which were not only significantly higher than the corresponding values(0.859 and 0.847) of the first comparison algorithm, but also higher than the values(0.928 and 0.877) of the second comparison algorithm. Thus the new method is reliable and effective.

Small Fire Detection Algorithm Development using VIIRS 375m Imagery: Application to Agricultural Fires in Eastern China

NASA Astrophysics Data System (ADS)

Zhang, Tianran; Wooster, Martin

2016-04-01

Until recently, crop residues have been the second largest industrial waste product produced in China and field-based burning of crop residues is considered to remain extremely widespread, with impacts on air quality and potential negative effects on health, public transportation. However, due to the small size and perhaps short-lived nature of the individual burns, the extent of the activity and its spatial variability remains somewhat unclear. Satellite EO data has been used to gauge the timing and magnitude of Chinese crop burning, but current approaches very likely miss significant amounts of the activity because the individual burned areas are either too small to detect with frequently acquired moderate spatial resolution data such as MODIS. The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board Suomi-NPP (National Polar-orbiting Partnership) satellite launched on October, 2011 has one set of multi-spectral channels providing full global coverage at 375 m nadir spatial resolutions. It is expected that the 375 m spatial resolution "I-band" imagery provided by VIIRS will allow active fires to be detected that are ~ 10× smaller than those that can be detected by MODIS. In this study the new small fire detection algorithm is built based on VIIRS-I band global fire detection algorithm and hot spot detection algorithm for the BIRD satellite mission. VIIRS-I band imagery data will be used to identify agricultural fire activity across Eastern China. A 30 m spatial resolution global land cover data map is used for false alarm masking. The ground-based validation is performed using images taken from UAV. The fire detection result is been compared with active fire product from the long-standing MODIS sensor onboard the TERRA and AQUA satellites, which shows small fires missed from traditional MODIS fire product may count for over 1/3 of total fire energy in Eastern China.

Novel algorithm for a smartphone-based 6-minute walk test application: algorithm, application development, and evaluation.

PubMed

Capela, Nicole A; Lemaire, Edward D; Baddour, Natalie

2015-02-20

The 6-minute walk test (6MWT: the maximum distance walked in 6 minutes) is used by rehabilitation professionals as a measure of exercise capacity. Today's smartphones contain hardware that can be used for wearable sensor applications and mobile data analysis. A smartphone application can run the 6MWT and provide typically unavailable biomechanical information about how the person moves during the test. A new algorithm for a calibration-free 6MWT smartphone application was developed that uses the test's inherent conditions and smartphone accelerometer-gyroscope data to report the total distance walked, step timing, gait symmetry, and walking changes over time. This information is not available with a standard 6MWT and could help with clinical decision-making. The 6MWT application was evaluated with 15 able-bodied participants. A BlackBerry Z10 smartphone was worn on a belt at the mid lower back. Audio from the phone instructed the person to start and stop walking. Digital video was independently recorded during the trial as a gold-standard comparator. The average difference between smartphone and gold standard foot strike timing was 0.014 ± 0.015 s. The total distance calculated by the application was within 1 m of the measured distance for all but one participant, which was more accurate than other smartphone-based studies. These results demonstrated that clinically relevant 6MWT results can be achieved with typical smartphone hardware and a novel algorithm.

Recommending Learning Activities in Social Network Using Data Mining Algorithms

ERIC Educational Resources Information Center

Mahnane, Lamia

2017-01-01

In this paper, we show how data mining algorithms (e.g. Apriori Algorithm (AP) and Collaborative Filtering (CF)) is useful in New Social Network (NSN-AP-CF). "NSN-AP-CF" processes the clusters based on different learning styles. Next, it analyzes the habits and the interests of the users through mining the frequent episodes by the…

Development and validation of a simple algorithm for initiation of CPAP in neonates with respiratory distress in Malawi

PubMed Central

Hundalani, Shilpa G; Richards-Kortum, Rebecca; Oden, Maria; Kawaza, Kondwani; Gest, Alfred; Molyneux, Elizabeth

2015-01-01

Background Low-cost bubble continuous positive airway pressure (bCPAP) systems have been shown to improve survival in neonates with respiratory distress, in developing countries including Malawi. District hospitals in Malawi implementing CPAP requested simple and reliable guidelines to enable healthcare workers with basic skills and minimal training to determine when treatment with CPAP is necessary. We developed and validated TRY (T: Tone is good, R: Respiratory Distress and Y=Yes) CPAP, a simple algorithm to identify neonates with respiratory distress who would benefit from CPAP. Objective To validate the TRY CPAP algorithm for neonates with respiratory distress in a low-resource setting. Methods We constructed an algorithm using a combination of vital signs, tone and birth weight to determine the need for CPAP in neonates with respiratory distress. Neonates admitted to the neonatal ward of Queen Elizabeth Central Hospital, in Blantyre, Malawi, were assessed in a prospective, cross-sectional study. Nurses and paediatricians-in-training assessed neonates to determine whether they required CPAP using the TRY CPAP algorithm. To establish the accuracy of the TRY CPAP algorithm in evaluating the need for CPAP, their assessment was compared with the decision of a neonatologist blinded to the TRY CPAP algorithm findings. Results 325 neonates were evaluated over a 2-month period; 13% were deemed to require CPAP by the neonatologist. The inter-rater reliability with the algorithm was 0.90 for nurses and 0.97 for paediatricians-in-training using the neonatologist's assessment as the reference standard. Conclusions The TRY CPAP algorithm has the potential to be a simple and reliable tool to assist nurses and clinicians in identifying neonates who require treatment with CPAP in low-resource settings. PMID:25877290

Development and validation of a simple algorithm for initiation of CPAP in neonates with respiratory distress in Malawi.

PubMed

Hundalani, Shilpa G; Richards-Kortum, Rebecca; Oden, Maria; Kawaza, Kondwani; Gest, Alfred; Molyneux, Elizabeth

2015-07-01

Low-cost bubble continuous positive airway pressure (bCPAP) systems have been shown to improve survival in neonates with respiratory distress, in developing countries including Malawi. District hospitals in Malawi implementing CPAP requested simple and reliable guidelines to enable healthcare workers with basic skills and minimal training to determine when treatment with CPAP is necessary. We developed and validated TRY (T: Tone is good, R: Respiratory Distress and Y=Yes) CPAP, a simple algorithm to identify neonates with respiratory distress who would benefit from CPAP. To validate the TRY CPAP algorithm for neonates with respiratory distress in a low-resource setting. We constructed an algorithm using a combination of vital signs, tone and birth weight to determine the need for CPAP in neonates with respiratory distress. Neonates admitted to the neonatal ward of Queen Elizabeth Central Hospital, in Blantyre, Malawi, were assessed in a prospective, cross-sectional study. Nurses and paediatricians-in-training assessed neonates to determine whether they required CPAP using the TRY CPAP algorithm. To establish the accuracy of the TRY CPAP algorithm in evaluating the need for CPAP, their assessment was compared with the decision of a neonatologist blinded to the TRY CPAP algorithm findings. 325 neonates were evaluated over a 2-month period; 13% were deemed to require CPAP by the neonatologist. The inter-rater reliability with the algorithm was 0.90 for nurses and 0.97 for paediatricians-in-training using the neonatologist's assessment as the reference standard. The TRY CPAP algorithm has the potential to be a simple and reliable tool to assist nurses and clinicians in identifying neonates who require treatment with CPAP in low-resource settings. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Toward Development of a Fibromyalgia Responder Index and Disease Activity Score: OMERACT Module Update

PubMed Central

Mease, PJ; Clauw, DJ; Christensen, R; Crofford, L; Gendreau, M; Martin, SA; Simon, L; Strand, V; Williams, DA; Arnold, LM

2012-01-01

Following development of the core domain set for fibromyalgia (FM) in OMERACT 7–9, the FM working group has progressed toward the development of an FM responder index and a disease activity score based on these domains, utilizing outcome indices of these domains from archived randomized clinical trials (RCTs) in FM. Possible clinical domains that could be included in a responder index and disease activity score include: pain, fatigue, sleep disturbance, cognitive dysfunction, mood disturbance, tenderness, stiffness, and functional impairment. Outcome measures for these domains demonstrate good to adequate psychometric properties, although measures of cognitive dysfunction need to be further developed. The approach used in the development of responder indices and disease activity scores for rheumatoid arthritis and ankylosing spondylitis represent heuristic models for our work, but FM is challenging in that there is no clear algorithm of treatment that defines disease activity based on treatment decisions, nor are there objective markers that define thresholds of severity or response to treatment. The process of developing candidate dichotomous responder definitions and continuous quantitative disease activity measures is described, as is participant discussion that transpired at OMERACT 10. Final results of this work will be published in a separate manuscript pending completion of analyses. PMID:21724721

Methods to Develop an Electronic Medical Record Phenotype Algorithm to Compare the Risk of Coronary Artery Disease across 3 Chronic Disease Cohorts.

PubMed

Liao, Katherine P; Ananthakrishnan, Ashwin N; Kumar, Vishesh; Xia, Zongqi; Cagan, Andrew; Gainer, Vivian S; Goryachev, Sergey; Chen, Pei; Savova, Guergana K; Agniel, Denis; Churchill, Susanne; Lee, Jaeyoung; Murphy, Shawn N; Plenge, Robert M; Szolovits, Peter; Kohane, Isaac; Shaw, Stanley Y; Karlson, Elizabeth W; Cai, Tianxi

2015-01-01

Typically, algorithms to classify phenotypes using electronic medical record (EMR) data were developed to perform well in a specific patient population. There is increasing interest in analyses which can allow study of a specific outcome across different diseases. Such a study in the EMR would require an algorithm that can be applied across different patient populations. Our objectives were: (1) to develop an algorithm that would enable the study of coronary artery disease (CAD) across diverse patient populations; (2) to study the impact of adding narrative data extracted using natural language processing (NLP) in the algorithm. Additionally, we demonstrate how to implement CAD algorithm to compare risk across 3 chronic diseases in a preliminary study. We studied 3 established EMR based patient cohorts: diabetes mellitus (DM, n = 65,099), inflammatory bowel disease (IBD, n = 10,974), and rheumatoid arthritis (RA, n = 4,453) from two large academic centers. We developed a CAD algorithm using NLP in addition to structured data (e.g. ICD9 codes) in the RA cohort and validated it in the DM and IBD cohorts. The CAD algorithm using NLP in addition to structured data achieved specificity >95% with a positive predictive value (PPV) 90% in the training (RA) and validation sets (IBD and DM). The addition of NLP data improved the sensitivity for all cohorts, classifying an additional 17% of CAD subjects in IBD and 10% in DM while maintaining PPV of 90%. The algorithm classified 16,488 DM (26.1%), 457 IBD (4.2%), and 245 RA (5.0%) with CAD. In a cross-sectional analysis, CAD risk was 63% lower in RA and 68% lower in IBD compared to DM (p<0.0001) after adjusting for traditional cardiovascular risk factors. We developed and validated a CAD algorithm that performed well across diverse patient populations. The addition of NLP into the CAD algorithm improved the sensitivity of the algorithm, particularly in cohorts where the prevalence of CAD was low. Preliminary data suggest that

A semi-learning algorithm for noise rejection: an fNIRS study on ADHD children

NASA Astrophysics Data System (ADS)

Sutoko, Stephanie; Funane, Tsukasa; Katura, Takusige; Sato, Hiroki; Kiguchi, Masashi; Maki, Atsushi; Monden, Yukifumi; Nagashima, Masako; Yamagata, Takanori; Dan, Ippeita

2017-02-01

In pediatrics studies, the quality of functional near infrared spectroscopy (fNIRS) signals is often reduced by motion artifacts. These artifacts likely mislead brain functionality analysis, causing false discoveries. While noise correction methods and their performance have been investigated, these methods require several parameter assumptions that apparently result in noise overfitting. In contrast, the rejection of noisy signals serves as a preferable method because it maintains the originality of the signal waveform. Here, we describe a semi-learning algorithm to detect and eliminate noisy signals. The algorithm dynamically adjusts noise detection according to the predetermined noise criteria, which are spikes, unusual activation values (averaged amplitude signals within the brain activation period), and high activation variances (among trials). Criteria were sequentially organized in the algorithm and orderly assessed signals based on each criterion. By initially setting an acceptable rejection rate, particular criteria causing excessive data rejections are neglected, whereas others with tolerable rejections practically eliminate noises. fNIRS data measured during the attention response paradigm (oddball task) in children with attention deficit/hyperactivity disorder (ADHD) were utilized to evaluate and optimize the algorithm's performance. This algorithm successfully substituted the visual noise identification done in the previous studies and consistently found significantly lower activation of the right prefrontal and parietal cortices in ADHD patients than in typical developing children. Thus, we conclude that the semi-learning algorithm confers more objective and standardized judgment for noise rejection and presents a promising alternative to visual noise rejection

Development of an Evolutionary Algorithm for the ab Initio Discovery of Two-Dimensional Materials

NASA Astrophysics Data System (ADS)

Revard, Benjamin Charles

Crystal structure prediction is an important first step on the path toward computational materials design. Increasingly robust methods have become available in recent years for computing many materials properties, but because properties are largely a function of crystal structure, the structure must be known before these methods can be brought to bear. In addition, structure prediction is particularly useful for identifying low-energy structures of subperiodic materials, such as two-dimensional (2D) materials, which may adopt unexpected structures that differ from those of the corresponding bulk phases. Evolutionary algorithms, which are heuristics for global optimization inspired by biological evolution, have proven to be a fruitful approach for tackling the problem of crystal structure prediction. This thesis describes the development of an improved evolutionary algorithm for structure prediction and several applications of the algorithm to predict the structures of novel low-energy 2D materials. The first part of this thesis contains an overview of evolutionary algorithms for crystal structure prediction and presents our implementation, including details of extending the algorithm to search for clusters, wires, and 2D materials, improvements to efficiency when running in parallel, improved composition space sampling, and the ability to search for partial phase diagrams. We then present several applications of the evolutionary algorithm to 2D systems, including InP, the C-Si and Sn-S phase diagrams, and several group-IV dioxides. This thesis makes use of the Cornell graduate school's "papers" option. Chapters 1 and 3 correspond to the first-author publications of Refs. [131] and [132], respectively, and chapter 2 will soon be submitted as a first-author publication. The material in chapter 4 is taken from Ref. [144], in which I share joint first-authorship. In this case I have included only my own contributions.

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.

Development of optimization model for sputtering process parameter based on gravitational search algorithm

NASA Astrophysics Data System (ADS)

Norlina, M. S.; Diyana, M. S. Nor; Mazidah, P.; Rusop, M.

2016-07-01

In the RF magnetron sputtering process, the desirable layer properties are largely influenced by the process parameters and conditions. If the quality of the thin film has not reached up to its intended level, the experiments have to be repeated until the desirable quality has been met. This research is proposing Gravitational Search Algorithm (GSA) as the optimization model to reduce the time and cost to be spent in the thin film fabrication. The optimization model's engine has been developed using Java. The model is developed based on GSA concept, which is inspired by the Newtonian laws of gravity and motion. In this research, the model is expected to optimize four deposition parameters which are RF power, deposition time, oxygen flow rate and substrate temperature. The results have turned out to be promising and it could be concluded that the performance of the model is satisfying in this parameter optimization problem. Future work could compare GSA with other nature based algorithms and test them with various set of data.

An approach to the development of numerical algorithms for first order linear hyperbolic systems in multiple space dimensions: The constant coefficient case

NASA Technical Reports Server (NTRS)

Goodrich, John W.

1995-01-01

Two methods for developing high order single step explicit algorithms on symmetric stencils with data on only one time level are presented. Examples are given for the convection and linearized Euler equations with up to the eighth order accuracy in both space and time in one space dimension, and up to the sixth in two space dimensions. The method of characteristics is generalized to nondiagonalizable hyperbolic systems by using exact local polynominal solutions of the system, and the resulting exact propagator methods automatically incorporate the correct multidimensional wave propagation dynamics. Multivariate Taylor or Cauchy-Kowaleskaya expansions are also used to develop algorithms. Both of these methods can be applied to obtain algorithms of arbitrarily high order for hyperbolic systems in multiple space dimensions. Cross derivatives are included in the local approximations used to develop the algorithms in this paper in order to obtain high order accuracy, and improved isotropy and stability. Efficiency in meeting global error bounds is an important criterion for evaluating algorithms, and the higher order algorithms are shown to be up to several orders of magnitude more efficient even though they are more complex. Stable high order boundary conditions for the linearized Euler equations are developed in one space dimension, and demonstrated in two space dimensions.

Control algorithm implementation for a redundant degree of freedom manipulator

NASA Technical Reports Server (NTRS)

Cohan, Steve

1991-01-01

This project's purpose is to develop and implement control algorithms for a kinematically redundant robotic manipulator. The manipulator is being developed concurrently by Odetics Inc., under internal research and development funding. This SBIR contract supports algorithm conception, development, and simulation, as well as software implementation and integration with the manipulator hardware. The Odetics Dexterous Manipulator is a lightweight, high strength, modular manipulator being developed for space and commercial applications. It has seven fully active degrees of freedom, is electrically powered, and is fully operational in 1 G. The manipulator consists of five self-contained modules. These modules join via simple quick-disconnect couplings and self-mating connectors which allow rapid assembly/disassembly for reconfiguration, transport, or servicing. Each joint incorporates a unique drive train design which provides zero backlash operation, is insensitive to wear, and is single fault tolerant to motor or servo amplifier failure. The sensing system is also designed to be single fault tolerant. Although the initial prototype is not space qualified, the design is well-suited to meeting space qualification requirements. The control algorithm design approach is to develop a hierarchical system with well defined access and interfaces at each level. The high level endpoint/configuration control algorithm transforms manipulator endpoint position/orientation commands to joint angle commands, providing task space motion. At the same time, the kinematic redundancy is resolved by controlling the configuration (pose) of the manipulator, using several different optimizing criteria. The center level of the hierarchy servos the joints to their commanded trajectories using both linear feedback and model-based nonlinear control techniques. The lowest control level uses sensed joint torque to close torque servo loops, with the goal of improving the manipulator dynamic behavior

Quantitative structure-activity relationship (QSAR) for insecticides: development of predictive in vivo insecticide activity models.

PubMed

Naik, P K; Singh, T; Singh, H

2009-07-01

Quantitative structure-activity relationship (QSAR) analyses were performed independently on data sets belonging to two groups of insecticides, namely the organophosphates and carbamates. Several types of descriptors including topological, spatial, thermodynamic, information content, lead likeness and E-state indices were used to derive quantitative relationships between insecticide activities and structural properties of chemicals. A systematic search approach based on missing value, zero value, simple correlation and multi-collinearity tests as well as the use of a genetic algorithm allowed the optimal selection of the descriptors used to generate the models. The QSAR models developed for both organophosphate and carbamate groups revealed good predictability with r(2) values of 0.949 and 0.838 as well as [image omitted] values of 0.890 and 0.765, respectively. In addition, a linear correlation was observed between the predicted and experimental LD(50) values for the test set data with r(2) of 0.871 and 0.788 for both the organophosphate and carbamate groups, indicating that the prediction accuracy of the QSAR models was acceptable. The models were also tested successfully from external validation criteria. QSAR models developed in this study should help further design of novel potent insecticides.

Ocean observations with EOS/MODIS: Algorithm development and post launch studies

NASA Technical Reports Server (NTRS)

Gordon, Howard R.

1995-01-01

Several significant accomplishments were made during the present reporting period. (1) Initial simulations to understand the applicability of the MODerate Resolution Imaging Spectrometer (MODIS) 1380 nm band for removing the effects of stratospheric aerosols and thin cirrus clouds were completed using a model for an aged volcanic aerosol. The results suggest that very simple procedures requiring no a priori knowledge of the optical properties of the stratospheric aerosol may be as effective as complex procedures requiring full knowledge of the aerosol properties, except the concentration which is estimated from the reflectance at 1380 nm. The limitations of this conclusion will be examined in the next reporting period; (2) The lookup tables employed in the implementation of the atmospheric correction algorithm have been modified in several ways intended to improve the accuracy and/or speed of processing. These have been delivered to R. Evans for implementation into the MODIS prototype processing algorithm for testing; (3) A method was developed for removal of the effects of the O2 'A' absorption band from SeaWiFS band 7 (745-785 nm). This is important in that SeaWiFS imagery will be used as a test data set for the MODIS atmospheric correction algorithm over the oceans; and (4) Construction of a radiometer, and associated deployment boom, for studying the spectral reflectance of oceanic whitecaps at sea was completed. The system was successfully tested on a cruise off Hawaii on which whitecaps were plentiful during October-November. This data set is now under analysis.

A pipelined FPGA implementation of an encryption algorithm based on genetic algorithm

NASA Astrophysics Data System (ADS)

Thirer, Nonel

2013-05-01

With the evolution of digital data storage and exchange, it is essential to protect the confidential information from every unauthorized access. High performance encryption algorithms were developed and implemented by software and hardware. Also many methods to attack the cipher text were developed. In the last years, the genetic algorithm has gained much interest in cryptanalysis of cipher texts and also in encryption ciphers. This paper analyses the possibility to use the genetic algorithm as a multiple key sequence generator for an AES (Advanced Encryption Standard) cryptographic system, and also to use a three stages pipeline (with four main blocks: Input data, AES Core, Key generator, Output data) to provide a fast encryption and storage/transmission of a large amount of data.

Millimeter-wave Imaging Radiometer (MIR) data processing and development of water vapor retrieval algorithms

NASA Technical Reports Server (NTRS)

Chang, L. Aron

1995-01-01

This document describes the progress of the task of the Millimeter-wave Imaging Radiometer (MIR) data processing and the development of water vapor retrieval algorithms, for the second six-month performing period. Aircraft MIR data from two 1995 field experiments were collected and processed with a revised data processing software. Two revised versions of water vapor retrieval algorithm were developed, one for the execution of retrieval on a supercomputer platform, and one for using pressure as the vertical coordinate. Two implementations of incorporating products from other sensors into the water vapor retrieval system, one from the Special Sensor Microwave Imager (SSM/I), the other from the High-resolution Interferometer Sounder (HIS). Water vapor retrievals were performed for both airborne MIR data and spaceborne SSM/T-2 data, during field experiments of TOGA/COARE, CAMEX-1, and CAMEX-2. The climatology of water vapor during TOGA/COARE was examined by SSM/T-2 soundings and conventional rawinsonde.

Development of Cloud and Precipitation Property Retrieval Algorithms and Measurement Simulators from ASR Data

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

Mace, Gerald G.

What has made the ASR program unique is the amount of information that is available. The suite of recently deployed instruments significantly expands the scope of the program (Mather and Voyles, 2013). The breadth of this information allows us to pose sophisticated process-level questions. Our ASR project, now entering its third year, has been about developing algorithms that use this information in ways that fully exploit the new capacity of the ARM data streams. Using optimal estimation (OE) and Markov Chain Monte Carlo (MCMC) inversion techniques, we have developed methodologies that allow us to use multiple radar frequency Doppler spectramore » along with lidar and passive constraints where data streams can be added or subtracted efficiently and algorithms can be reformulated for various combinations of hydrometeors by exchanging sets of empirical coefficients. These methodologies have been applied to boundary layer clouds, mixed phase snow cloud systems, and cirrus.« less

Molecular descriptor subset selection in theoretical peptide quantitative structure-retention relationship model development using nature-inspired optimization algorithms.

PubMed

Žuvela, Petar; Liu, J Jay; Macur, Katarzyna; Bączek, Tomasz

2015-10-06

In this work, performance of five nature-inspired optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), firefly algorithm (FA), and flower pollination algorithm (FPA), was compared in molecular descriptor selection for development of quantitative structure-retention relationship (QSRR) models for 83 peptides that originate from eight model proteins. The matrix with 423 descriptors was used as input, and QSRR models based on selected descriptors were built using partial least squares (PLS), whereas root mean square error of prediction (RMSEP) was used as a fitness function for their selection. Three performance criteria, prediction accuracy, computational cost, and the number of selected descriptors, were used to evaluate the developed QSRR models. The results show that all five variable selection methods outperform interval PLS (iPLS), sparse PLS (sPLS), and the full PLS model, whereas GA is superior because of its lowest computational cost and higher accuracy (RMSEP of 5.534%) with a smaller number of variables (nine descriptors). The GA-QSRR model was validated initially through Y-randomization. In addition, it was successfully validated with an external testing set out of 102 peptides originating from Bacillus subtilis proteomes (RMSEP of 22.030%). Its applicability domain was defined, from which it was evident that the developed GA-QSRR exhibited strong robustness. All the sources of the model's error were identified, thus allowing for further application of the developed methodology in proteomics.

Drowsiness/alertness algorithm development and validation using synchronized EEG and cognitive performance to individualize a generalized model

PubMed Central

Johnson, Robin R.; Popovic, Djordje P.; Olmstead, Richard E.; Stikic, Maja; Levendowski, Daniel J.; Berka, Chris

2011-01-01

A great deal of research over the last century has focused on drowsiness/alertness detection, as fatigue-related physical and cognitive impairments pose a serious risk to public health and safety. Available drowsiness/alertness detection solutions are unsatisfactory for a number of reasons: 1) lack of generalizability, 2) failure to address individual variability in generalized models, and/or 3) they lack a portable, un-tethered application. The current study aimed to address these issues, and determine if an individualized electroencephalography (EEG) based algorithm could be defined to track performance decrements associated with sleep loss, as this is the first step in developing a field deployable drowsiness/alertness detection system. The results indicated that an EEG-based algorithm, individualized using a series of brief "identification" tasks, was able to effectively track performance decrements associated with sleep deprivation. Future development will address the need for the algorithm to predict performance decrements due to sleep loss, and provide field applicability. PMID:21419826

Drowsiness/alertness algorithm development and validation using synchronized EEG and cognitive performance to individualize a generalized model.

PubMed

Johnson, Robin R; Popovic, Djordje P; Olmstead, Richard E; Stikic, Maja; Levendowski, Daniel J; Berka, Chris

2011-05-01

A great deal of research over the last century has focused on drowsiness/alertness detection, as fatigue-related physical and cognitive impairments pose a serious risk to public health and safety. Available drowsiness/alertness detection solutions are unsatisfactory for a number of reasons: (1) lack of generalizability, (2) failure to address individual variability in generalized models, and/or (3) lack of a portable, un-tethered application. The current study aimed to address these issues, and determine if an individualized electroencephalography (EEG) based algorithm could be defined to track performance decrements associated with sleep loss, as this is the first step in developing a field deployable drowsiness/alertness detection system. The results indicated that an EEG-based algorithm, individualized using a series of brief "identification" tasks, was able to effectively track performance decrements associated with sleep deprivation. Future development will address the need for the algorithm to predict performance decrements due to sleep loss, and provide field applicability. Copyright © 2011 Elsevier B.V. All rights reserved.

Toward Developing an Unbiased Scoring Algorithm for "NASA" and Similar Ranking Tasks.

ERIC Educational Resources Information Center

Lane, Irving M.; And Others

1981-01-01

Presents both logical and empirical evidence to illustrate that the conventional scoring algorithm for ranking tasks significantly underestimates the initial level of group ability and that Slevin's alternative scoring algorithm significantly overestimates the initial level of ability. Presents a modification of Slevin's algorithm which authors…

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.

PubMed

Gulshan, Varun; Peng, Lily; Coram, Marc; Stumpe, Martin C; Wu, Derek; Narayanaswamy, Arunachalam; Venugopalan, Subhashini; Widner, Kasumi; Madams, Tom; Cuadros, Jorge; Kim, Ramasamy; Raman, Rajiv; Nelson, Philip C; Mega, Jessica L; Webster, Dale R

2016-12-13

Deep learning is a family of computational methods that allow an algorithm to program itself by learning from a large set of examples that demonstrate the desired behavior, removing the need to specify rules explicitly. Application of these methods to medical imaging requires further assessment and validation. To apply deep learning to create an algorithm for automated detection of diabetic retinopathy and diabetic macular edema in retinal fundus photographs. A specific type of neural network optimized for image classification called a deep convolutional neural network was trained using a retrospective development data set of 128 175 retinal images, which were graded 3 to 7 times for diabetic retinopathy, diabetic macular edema, and image gradability by a panel of 54 US licensed ophthalmologists and ophthalmology senior residents between May and December 2015. The resultant algorithm was validated in January and February 2016 using 2 separate data sets, both graded by at least 7 US board-certified ophthalmologists with high intragrader consistency. Deep learning-trained algorithm. The sensitivity and specificity of the algorithm for detecting referable diabetic retinopathy (RDR), defined as moderate and worse diabetic retinopathy, referable diabetic macular edema, or both, were generated based on the reference standard of the majority decision of the ophthalmologist panel. The algorithm was evaluated at 2 operating points selected from the development set, one selected for high specificity and another for high sensitivity. The EyePACS-1 data set consisted of 9963 images from 4997 patients (mean age, 54.4 years; 62.2% women; prevalence of RDR, 683/8878 fully gradable images [7.8%]); the Messidor-2 data set had 1748 images from 874 patients (mean age, 57.6 years; 42.6% women; prevalence of RDR, 254/1745 fully gradable images [14.6%]). For detecting RDR, the algorithm had an area under the receiver operating curve of 0.991 (95% CI, 0.988-0.993) for EyePACS-1 and 0

Automated algorithms for detecting sleep period time using a multi-sensor pattern-recognition activity monitor from 24 h free-living data in older adults.

PubMed

Cabanas-Sánchez, Verónica; Higueras-Fresnillo, Sara; De la Cámara, Miguel Ángel; Veiga, Oscar L; Martinez-Gomez, David

2018-05-16

The aims of the present study were (i) to develop automated algorithms to identify the sleep period time in 24 h data from the Intelligent Device for Energy Expenditure and Activity (IDEEA) in older adults, and (ii) to analyze the agreement between these algorithms to identify the sleep period time as compared to self-reported data and expert visual analysis of accelerometer raw data. This study comprised 50 participants, aged 65-85 years. Fourteen automated algorithms were developed. Participants reported their bedtime and waking time on the days on which they wore the device. A well-trained expert reviewed each IDEEA file in order to visually identify bedtime and waking time on each day. To explore the agreement between methods, Pearson correlations, mean differences, mean percentage errors, accuracy, sensitivity and specificity, and the Bland-Altman method were calculated. With 87 d of valid data, algorithms 6, 7, 11 and 12 achieved higher levels of agreement in determining sleep period time when compared to self-reported data (mean difference  =  -0.34 to 0.01 h d -1 ; mean absolute error  =  10.66%-11.44%; r  =  0.515-0.686; accuracy  =  95.0%-95.6%; sensitivity  =  93.0%-95.8%; specificity  =  95.7%-96.4%) and expert visual analysis (mean difference  =  -0.04 to 0.31 h d -1 ; mean absolute error  =  5.0%-6.97%; r  =  0.620-0.766; accuracy  =  97.2%-98.0%; sensitivity  =  94.5%-97.6%; specificity  =  98.4%-98.8%). Bland-Altman plots showed no systematic biases in these comparisons (all p  >  0.05). Differences between methods did not vary significantly by gender, age, obesity, self-rated health, or the presence of chronic conditions. These four algorithms can be used to identify easily and with adequate accuracy the sleep period time using the IDEEA activity monitor from 24 h free-living data in older adults.

Development and validation of an electronic phenotyping algorithm for chronic kidney disease

PubMed Central

Nadkarni, Girish N; Gottesman, Omri; Linneman, James G; Chase, Herbert; Berg, Richard L; Farouk, Samira; Nadukuru, Rajiv; Lotay, Vaneet; Ellis, Steve; Hripcsak, George; Peissig, Peggy; Weng, Chunhua; Bottinger, Erwin P

2014-01-01

Twenty-six million Americans are estimated to have chronic kidney disease (CKD) with increased risk for cardiovascular disease and end stage renal disease. CKD is frequently undiagnosed and patients are unaware, hampering intervention. A tool for accurate and timely identification of CKD from electronic medical records (EMR) could improve healthcare quality and identify patients for research. As members of eMERGE (electronic medical records and genomics) Network, we developed an automated phenotyping algorithm that can be deployed to identify rapidly diabetic and/or hypertensive CKD cases and controls in health systems with EMRs It uses diagnostic codes, laboratory results, medication and blood pressure records, and textual information culled from notes. Validation statistics demonstrated positive predictive values of 96% and negative predictive values of 93.3. Similar results were obtained on implementation by two independent eMERGE member institutions. The algorithm dramatically outperformed identification by ICD-9-CM codes with 63% positive and 54% negative predictive values, respectively. PMID:25954398

Development of a pharmacogenetic-guided warfarin dosing algorithm for Puerto Rican patients.

PubMed

Ramos, Alga S; Seip, Richard L; Rivera-Miranda, Giselle; Felici-Giovanini, Marcos E; Garcia-Berdecia, Rafael; Alejandro-Cowan, Yirelia; Kocherla, Mohan; Cruz, Iadelisse; Feliu, Juan F; Cadilla, Carmen L; Renta, Jessica Y; Gorowski, Krystyna; Vergara, Cunegundo; Ruaño, Gualberto; Duconge, Jorge

2012-12-01

This study was aimed at developing a pharmacogenetic-driven warfarin-dosing algorithm in 163 admixed Puerto Rican patients on stable warfarin therapy. A multiple linear-regression analysis was performed using log-transformed effective warfarin dose as the dependent variable, and combining CYP2C9 and VKORC1 genotyping with other relevant nongenetic clinical and demographic factors as independent predictors. The model explained more than two-thirds of the observed variance in the warfarin dose among Puerto Ricans, and also produced significantly better 'ideal dose' estimates than two pharmacogenetic models and clinical algorithms published previously, with the greatest benefit seen in patients ultimately requiring <7 mg/day. We also assessed the clinical validity of the model using an independent validation cohort of 55 Puerto Rican patients from Hartford, CT, USA (R(2) = 51%). Our findings provide the basis for planning prospective pharmacogenetic studies to demonstrate the clinical utility of genotyping warfarin-treated Puerto Rican patients.

Development of a pharmacogenetic-guided warfarin dosing algorithm for Puerto Rican patients

PubMed Central

Ramos, Alga S; Seip, Richard L; Rivera-Miranda, Giselle; Felici-Giovanini, Marcos E; Garcia-Berdecia, Rafael; Alejandro-Cowan, Yirelia; Kocherla, Mohan; Cruz, Iadelisse; Feliu, Juan F; Cadilla, Carmen L; Renta, Jessica Y; Gorowski, Krystyna; Vergara, Cunegundo; Ruaño, Gualberto; Duconge, Jorge

2012-01-01

Aim This study was aimed at developing a pharmacogenetic-driven warfarin-dosing algorithm in 163 admixed Puerto Rican patients on stable warfarin therapy. Patients & methods A multiple linear-regression analysis was performed using log-transformed effective warfarin dose as the dependent variable, and combining CYP2C9 and VKORC1 genotyping with other relevant nongenetic clinical and demographic factors as independent predictors. Results The model explained more than two-thirds of the observed variance in the warfarin dose among Puerto Ricans, and also produced significantly better ‘ideal dose’ estimates than two pharmacogenetic models and clinical algorithms published previously, with the greatest benefit seen in patients ultimately requiring <7 mg/day. We also assessed the clinical validity of the model using an independent validation cohort of 55 Puerto Rican patients from Hartford, CT, USA (R2 = 51%). Conclusion Our findings provide the basis for planning prospective pharmacogenetic studies to demonstrate the clinical utility of genotyping warfarin-treated Puerto Rican patients. PMID:23215886

Development of a 3D muon disappearance algorithm for muon scattering tomography

NASA Astrophysics Data System (ADS)

Blackwell, T. B.; Kudryavtsev, V. A.

2015-05-01

Upon passing through a material, muons lose energy, scatter off nuclei and atomic electrons, and can stop in the material. Muons will more readily lose energy in higher density materials. Therefore multiple muon disappearances within a localized volume may signal the presence of high-density materials. We have developed a new technique that improves the sensitivity of standard muon scattering tomography. This technique exploits these muon disappearances to perform non-destructive assay of an inspected volume. Muons that disappear have their track evaluated using a 3D line extrapolation algorithm, which is in turn used to construct a 3D tomographic image of the inspected volume. Results of Monte Carlo simulations that measure muon disappearance in different types of target materials are presented. The ability to differentiate between different density materials using the 3D line extrapolation algorithm is established. Finally the capability of this new muon disappearance technique to enhance muon scattering tomography techniques in detecting shielded HEU in cargo containers has been demonstrated.

Algorithm and code development for unsteady three-dimensional Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Obayashi, Shigeru

1991-01-01

A streamwise upwind algorithm for solving the unsteady 3-D Navier-Stokes equations was extended to handle the moving grid system. It is noted that the finite volume concept is essential to extend the algorithm. The resulting algorithm is conservative for any motion of the coordinate system. Two extensions to an implicit method were considered and the implicit extension that makes the algorithm computationally efficient is implemented into Ames's aeroelasticity code, ENSAERO. The new flow solver has been validated through the solution of test problems. Test cases include three-dimensional problems with fixed and moving grids. The first test case shown is an unsteady viscous flow over an F-5 wing, while the second test considers the motion of the leading edge vortex as well as the motion of the shock wave for a clipped delta wing. The resulting algorithm has been implemented into ENSAERO. The upwind version leads to higher accuracy in both steady and unsteady computations than the previously used central-difference method does, while the increase in the computational time is small.

Control Algorithms For Liquid-Cooled Garments

NASA Technical Reports Server (NTRS)

Drew, B.; Harner, K.; Hodgson, E.; Homa, J.; Jennings, D.; Yanosy, J.

1988-01-01

Three algorithms developed for control of cooling in protective garments. Metabolic rate inferred from temperatures of cooling liquid outlet and inlet, suitably filtered to account for thermal lag of human body. Temperature at inlet adjusted to value giving maximum comfort at inferred metabolic rate. Applicable to space suits, used for automatic control of cooling in suits worn by workers in radioactive, polluted, or otherwise hazardous environments. More effective than manual control, subject to frequent, overcompensated adjustments as level of activity varies.

Improvements to a five-phase ABS algorithm for experimental validation

NASA Astrophysics Data System (ADS)

Gerard, Mathieu; Pasillas-Lépine, William; de Vries, Edwin; Verhaegen, Michel

2012-10-01

The anti-lock braking system (ABS) is the most important active safety system for passenger cars. Unfortunately, the literature is not really precise about its description, stability and performance. This research improves a five-phase hybrid ABS control algorithm based on wheel deceleration [W. Pasillas-Lépine, Hybrid modeling and limit cycle analysis for a class of five-phase anti-lock brake algorithms, Veh. Syst. Dyn. 44 (2006), pp. 173-188] and validates it on a tyre-in-the-loop laboratory facility. Five relevant effects are modelled so that the simulation matches the reality: oscillations in measurements, wheel acceleration reconstruction, brake pressure dynamics, brake efficiency changes and tyre relaxation. The time delays in measurement and actuation have been identified as the main difficulty for the initial algorithm to work in practice. Three methods are proposed in order to deal with these delays. It is verified that the ABS limit cycles encircle the optimal braking point, without assuming any tyre parameter being a priori known. The ABS algorithm is compared with the commercial algorithm developed by Bosch.

Object-Oriented/Data-Oriented Design of a Direct Simulation Monte Carlo Algorithm

NASA Technical Reports Server (NTRS)

Liechty, Derek S.

2014-01-01

Over the past decade, there has been much progress towards improved phenomenological modeling and algorithmic updates for the direct simulation Monte Carlo (DSMC) method, which provides a probabilistic physical simulation of gas Rows. These improvements have largely been based on the work of the originator of the DSMC method, Graeme Bird. Of primary importance are improved chemistry, internal energy, and physics modeling and a reduction in time to solution. These allow for an expanded range of possible solutions In altitude and velocity space. NASA's current production code, the DSMC Analysis Code (DAC), is well-established and based on Bird's 1994 algorithms written in Fortran 77 and has proven difficult to upgrade. A new DSMC code is being developed in the C++ programming language using object-oriented and data-oriented design paradigms to facilitate the inclusion of the recent improvements and future development activities. The development efforts on the new code, the Multiphysics Algorithm with Particles (MAP), are described, and performance comparisons are made with DAC.

Development of an algorithm for automatic detection and rating of squeak and rattle events

NASA Astrophysics Data System (ADS)

Chandrika, Unnikrishnan Kuttan; Kim, Jay H.

2010-10-01

A new algorithm for automatic detection and rating of squeak and rattle (S&R) events was developed. The algorithm utilizes the perceived transient loudness (PTL) that approximates the human perception of a transient noise. At first, instantaneous specific loudness time histories are calculated over 1-24 bark range by applying the analytic wavelet transform and Zwicker loudness transform to the recorded noise. Transient specific loudness time histories are then obtained by removing estimated contributions of the background noise from instantaneous specific loudness time histories. These transient specific loudness time histories are summed to obtain the transient loudness time history. Finally, the PTL time history is obtained by applying Glasberg and Moore temporal integration to the transient loudness time history. Detection of S&R events utilizes the PTL time history obtained by summing only 18-24 barks components to take advantage of high signal-to-noise ratio in the high frequency range. A S&R event is identified when the value of the PTL time history exceeds the detection threshold pre-determined by a jury test. The maximum value of the PTL time history is used for rating of S&R events. Another jury test showed that the method performs much better if the PTL time history obtained by summing all frequency components is used. Therefore, r ating of S&R events utilizes this modified PTL time history. Two additional jury tests were conducted to validate the developed detection and rating methods. The algorithm developed in this work will enable automatic detection and rating of S&R events with good accuracy and minimum possibility of false alarm.

Synthesis of Greedy Algorithms Using Dominance Relations

NASA Technical Reports Server (NTRS)

Nedunuri, Srinivas; Smith, Douglas R.; Cook, William R.

2010-01-01

Greedy algorithms exploit problem structure and constraints to achieve linear-time performance. Yet there is still no completely satisfactory way of constructing greedy algorithms. For example, the Greedy Algorithm of Edmonds depends upon translating a problem into an algebraic structure called a matroid, but the existence of such a translation can be as hard to determine as the existence of a greedy algorithm itself. An alternative characterization of greedy algorithms is in terms of dominance relations, a well-known algorithmic technique used to prune search spaces. We demonstrate a process by which dominance relations can be methodically derived for a number of greedy algorithms, including activity selection, and prefix-free codes. By incorporating our approach into an existing framework for algorithm synthesis, we demonstrate that it could be the basis for an effective engineering method for greedy algorithms. We also compare our approach with other characterizations of greedy algorithms.

Algorithmic formulation of control problems in manipulation

NASA Technical Reports Server (NTRS)

Bejczy, A. K.

1975-01-01

The basic characteristics of manipulator control algorithms are discussed. The state of the art in the development of manipulator control algorithms is briefly reviewed. Different end-point control techniques are described together with control algorithms which operate on external sensor (imaging, proximity, tactile, and torque/force) signals in realtime. Manipulator control development at JPL is briefly described and illustrated with several figures. The JPL work pays special attention to the front or operator input end of the control algorithms.

Multidisciplinary Design, Analysis, and Optimization Tool Development Using a Genetic Algorithm

NASA Technical Reports Server (NTRS)

Pak, Chan-gi; Li, Wesley

2009-01-01

Multidisciplinary design, analysis, and optimization using a genetic algorithm is being developed at the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) to automate analysis and design process by leveraging existing tools to enable true multidisciplinary optimization in the preliminary design stage of subsonic, transonic, supersonic, and hypersonic aircraft. This is a promising technology, but faces many challenges in large-scale, real-world application. This report describes current approaches, recent results, and challenges for multidisciplinary design, analysis, and optimization as demonstrated by experience with the Ikhana fire pod design.!

Probabilistic models, learning algorithms, and response variability: sampling in cognitive development.

PubMed

Bonawitz, Elizabeth; Denison, Stephanie; Griffiths, Thomas L; Gopnik, Alison

2014-10-01

Although probabilistic models of cognitive development have become increasingly prevalent, one challenge is to account for how children might cope with a potentially vast number of possible hypotheses. We propose that children might address this problem by 'sampling' hypotheses from a probability distribution. We discuss empirical results demonstrating signatures of sampling, which offer an explanation for the variability of children's responses. The sampling hypothesis provides an algorithmic account of how children might address computationally intractable problems and suggests a way to make sense of their 'noisy' behavior. Copyright © 2014 Elsevier Ltd. All rights reserved.

Strategic Control Algorithm Development : Volume 4B. Computer Program Report (Concluded)

DOT National Transportation Integrated Search

1974-08-01

A description of the strategic algorithm evaluation model is presented, both at the user and programmer levels. The model representation of an airport configuration, environmental considerations, the strategic control algorithm logic, and the airplan...

The Chandra Source Catalog: Algorithms

NASA Astrophysics Data System (ADS)

McDowell, Jonathan; Evans, I. N.; Primini, F. A.; Glotfelty, K. J.; McCollough, M. L.; Houck, J. C.; Nowak, M. A.; Karovska, M.; Davis, J. E.; Rots, A. H.; Siemiginowska, A. L.; Hain, R.; Evans, J. D.; Anderson, C. S.; Bonaventura, N. R.; Chen, J. C.; Doe, S. M.; Fabbiano, G.; Galle, E. C.; Gibbs, D. G., II; Grier, J. D.; Hall, D. M.; Harbo, P. N.; He, X.; Lauer, J.; Miller, J. B.; Mitschang, A. W.; Morgan, D. L.; Nichols, J. S.; Plummer, D. A.; Refsdal, B. L.; Sundheim, B. A.; Tibbetts, M. S.; van Stone, D. W.; Winkelman, S. L.; Zografou, P.

2009-09-01

Creation of the Chandra Source Catalog (CSC) required adjustment of existing pipeline processing, adaptation of existing interactive analysis software for automated use, and development of entirely new algorithms. Data calibration was based on the existing pipeline, but more rigorous data cleaning was applied and the latest calibration data products were used. For source detection, a local background map was created including the effects of ACIS source readout streaks. The existing wavelet source detection algorithm was modified and a set of post-processing scripts used to correct the results. To analyse the source properties we ran the SAO Traceray trace code for each source to generate a model point spread function, allowing us to find encircled energy correction factors and estimate source extent. Further algorithms were developed to characterize the spectral, spatial and temporal properties of the sources and to estimate the confidence intervals on count rates and fluxes. Finally, sources detected in multiple observations were matched, and best estimates of their merged properties derived. In this paper we present an overview of the algorithms used, with more detailed treatment of some of the newly developed algorithms presented in companion papers.

The Goes-R Geostationary Lightning Mapper (GLM): Algorithm and Instrument Status

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, Richard J.; Koshak, William J.; Mach, Douglas

2010-01-01

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved capability for the Advanced Baseline Imager (ABI). The Geostationary Lighting Mapper (GLM) will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development (a prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms, cal/val performance monitoring tools, and new applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. A joint field campaign with Brazilian researchers in 2010-2011 will produce concurrent observations from a VHF lightning mapping array, Meteosat multi-band imagery, Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) overpasses, and related ground and in-situ lightning and meteorological measurements in the vicinity of Sao Paulo. These data will provide a new comprehensive proxy data set for algorithm and

Algorithms of walking and stability for an anthropomorphic robot

NASA Astrophysics Data System (ADS)

Sirazetdinov, R. T.; Devaev, V. M.; Nikitina, D. V.; Fadeev, A. Y.; Kamalov, A. R.

2017-09-01

Autonomous movement of an anthropomorphic robot is considered as a superposition of a set of typical elements of movement - so-called patterns, each of which can be considered as an agent of some multi-agent system [ 1 ]. To control the AP-601 robot, an information and communication infrastructure has been created that represents some multi-agent system that allows the development of algorithms for individual patterns of moving and run them in the system as a set of independently executed and interacting agents. The algorithms of lateral movement of the anthropomorphic robot AP-601 series with active stability due to the stability pattern are presented.

Methods to Develop an Electronic Medical Record Phenotype Algorithm to Compare the Risk of Coronary Artery Disease across 3 Chronic Disease Cohorts

PubMed Central

Liao, Katherine P.; Ananthakrishnan, Ashwin N.; Kumar, Vishesh; Xia, Zongqi; Cagan, Andrew; Gainer, Vivian S.; Goryachev, Sergey; Chen, Pei; Savova, Guergana K.; Agniel, Denis; Churchill, Susanne; Lee, Jaeyoung; Murphy, Shawn N.; Plenge, Robert M.; Szolovits, Peter; Kohane, Isaac; Shaw, Stanley Y.; Karlson, Elizabeth W.; Cai, Tianxi

2015-01-01

Background Typically, algorithms to classify phenotypes using electronic medical record (EMR) data were developed to perform well in a specific patient population. There is increasing interest in analyses which can allow study of a specific outcome across different diseases. Such a study in the EMR would require an algorithm that can be applied across different patient populations. Our objectives were: (1) to develop an algorithm that would enable the study of coronary artery disease (CAD) across diverse patient populations; (2) to study the impact of adding narrative data extracted using natural language processing (NLP) in the algorithm. Additionally, we demonstrate how to implement CAD algorithm to compare risk across 3 chronic diseases in a preliminary study. Methods and Results We studied 3 established EMR based patient cohorts: diabetes mellitus (DM, n = 65,099), inflammatory bowel disease (IBD, n = 10,974), and rheumatoid arthritis (RA, n = 4,453) from two large academic centers. We developed a CAD algorithm using NLP in addition to structured data (e.g. ICD9 codes) in the RA cohort and validated it in the DM and IBD cohorts. The CAD algorithm using NLP in addition to structured data achieved specificity >95% with a positive predictive value (PPV) 90% in the training (RA) and validation sets (IBD and DM). The addition of NLP data improved the sensitivity for all cohorts, classifying an additional 17% of CAD subjects in IBD and 10% in DM while maintaining PPV of 90%. The algorithm classified 16,488 DM (26.1%), 457 IBD (4.2%), and 245 RA (5.0%) with CAD. In a cross-sectional analysis, CAD risk was 63% lower in RA and 68% lower in IBD compared to DM (p<0.0001) after adjusting for traditional cardiovascular risk factors. Conclusions We developed and validated a CAD algorithm that performed well across diverse patient populations. The addition of NLP into the CAD algorithm improved the sensitivity of the algorithm, particularly in cohorts where the prevalence of

Identification of mild cognitive impairment in ACTIVE: algorithmic classification and stability.

PubMed

Cook, Sarah E; Marsiske, Michael; Thomas, Kelsey R; Unverzagt, Frederick W; Wadley, Virginia G; Langbaum, Jessica B S; Crowe, Michael

2013-01-01

Rates of mild cognitive impairment (MCI) have varied substantially, depending on the criteria used and the samples surveyed. The present investigation used a psychometric algorithm for identifying MCI and its stability to determine if low cognitive functioning was related to poorer longitudinal outcomes. The Advanced Cognitive Training of Independent and Vital Elders (ACTIVE) study is a multi-site longitudinal investigation of long-term effects of cognitive training with older adults. ACTIVE exclusion criteria eliminated participants at highest risk for dementia (i.e., Mini-Mental State Examination < 23). Using composite normative for sample- and training-corrected psychometric data, 8.07% of the sample had amnestic impairment, while 25.09% had a non-amnestic impairment at baseline. Poorer baseline functional scores were observed in those with impairment at the first visit, including a higher rate of attrition, depressive symptoms, and self-reported physical functioning. Participants were then classified based upon the stability of their classification. Those who were stably impaired over the 5-year interval had the worst functional outcomes (e.g., Instrumental Activities of Daily Living performance), and inconsistency in classification over time also appeared to be associated increased risk. These findings suggest that there is prognostic value in assessing and tracking cognition to assist in identifying the critical baseline features associated with poorer outcomes.

Data-driven approach of CUSUM algorithm in temporal aberrant event detection using interactive web applications.

PubMed

Li, Ye; Whelan, Michael; Hobbs, Leigh; Fan, Wen Qi; Fung, Cecilia; Wong, Kenny; Marchand-Austin, Alex; Badiani, Tina; Johnson, Ian

2016-06-27

In 2014/2015, Public Health Ontario developed disease-specific, cumulative sum (CUSUM)-based statistical algorithms for detecting aberrant increases in reportable infectious disease incidence in Ontario. The objective of this study was to determine whether the prospective application of these CUSUM algorithms, based on historical patterns, have improved specificity and sensitivity compared to the currently used Early Aberration Reporting System (EARS) algorithm, developed by the US Centers for Disease Control and Prevention. A total of seven algorithms were developed for the following diseases: cyclosporiasis, giardiasis, influenza (one each for type A and type B), mumps, pertussis, invasive pneumococcal disease. Historical data were used as baseline to assess known outbreaks. Regression models were used to model seasonality and CUSUM was applied to the difference between observed and expected counts. An interactive web application was developed allowing program staff to directly interact with data and tune the parameters of CUSUM algorithms using their expertise on the epidemiology of each disease. Using these parameters, a CUSUM detection system was applied prospectively and the results were compared to the outputs generated by EARS. The outcome was the detection of outbreaks, or the start of a known seasonal increase and predicting the peak in activity. The CUSUM algorithms detected provincial outbreaks earlier than the EARS algorithm, identified the start of the influenza season in advance of traditional methods, and had fewer false positive alerts. Additionally, having staff involved in the creation of the algorithms improved their understanding of the algorithms and improved use in practice. Using interactive web-based technology to tune CUSUM improved the sensitivity and specificity of detection algorithms.

Mars Entry Atmospheric Data System Modelling and Algorithm Development

NASA Technical Reports Server (NTRS)

Karlgaard, Christopher D.; Beck, Roger E.; OKeefe, Stephen A.; Siemers, Paul; White, Brady; Engelund, Walter C.; Munk, Michelle M.

2009-01-01

The Mars Entry Atmospheric Data System (MEADS) is being developed as part of the Mars Science Laboratory (MSL), Entry, Descent, and Landing Instrumentation (MEDLI) project. The MEADS project involves installing an array of seven pressure transducers linked to ports on the MSL forebody to record the surface pressure distribution during atmospheric entry. These measured surface pressures are used to generate estimates of atmospheric quantities based on modeled surface pressure distributions. In particular, the quantities to be estimated from the MEADS pressure measurements include the total pressure, dynamic pressure, Mach number, angle of attack, and angle of sideslip. Secondary objectives are to estimate atmospheric winds by coupling the pressure measurements with the on-board Inertial Measurement Unit (IMU) data. This paper provides details of the algorithm development, MEADS system performance based on calibration, and uncertainty analysis for the aerodynamic and atmospheric quantities of interest. The work presented here is part of the MEDLI performance pre-flight validation and will culminate with processing flight data after Mars entry in 2012.

Musculoskeletal-see-through mirror: computational modeling and algorithm for whole-body muscle activity visualization in real time.

PubMed

Murai, Akihiko; Kurosaki, Kosuke; Yamane, Katsu; Nakamura, Yoshihiko

2010-12-01

In this paper, we present a system that estimates and visualizes muscle tensions in real time using optical motion capture and electromyography (EMG). The system overlays rendered musculoskeletal human model on top of a live video image of the subject. The subject therefore has an impression that he/she sees the muscles with tension information through the cloth and skin. The main technical challenge lies in real-time estimation of muscle tension. Since existing algorithms using mathematical optimization to distribute joint torques to muscle tensions are too slow for our purpose, we develop a new algorithm that computes a reasonable approximation of muscle tensions based on the internal connections between muscles known as neuronal binding. The algorithm can estimate the tensions of 274 muscles in only 16 ms, and the whole visualization system runs at about 15 fps. The developed system is applied to assisting sport training, and the user case studies show its usefulness. Possible applications include interfaces for assisting rehabilitation. Copyright © 2010 Elsevier Ltd. All rights reserved.

Revisiting negative selection algorithms.

PubMed

Ji, Zhou; Dasgupta, Dipankar

2007-01-01

This paper reviews the progress of negative selection algorithms, an anomaly/change detection approach in Artificial Immune Systems (AIS). Following its initial model, we try to identify the fundamental characteristics of this family of algorithms and summarize their diversities. There exist various elements in this method, including data representation, coverage estimate, affinity measure, and matching rules, which are discussed for different variations. The various negative selection algorithms are categorized by different criteria as well. The relationship and possible combinations with other AIS or other machine learning methods are discussed. Prospective development and applicability of negative selection algorithms and their influence on related areas are then speculated based on the discussion.

Recognition of military-specific physical activities with body-fixed sensors.

PubMed

Wyss, Thomas; Mäder, Urs

2010-11-01

The purpose of this study was to develop and validate an algorithm for recognizing military-specific, physically demanding activities using body-fixed sensors. To develop the algorithm, the first group of study participants (n = 15) wore body-fixed sensors capable of measuring acceleration, step frequency, and heart rate while completing six military-specific activities: walking, marching with backpack, lifting and lowering loads, lifting and carrying loads, digging, and running. The accuracy of the algorithm was tested in these isolated activities in a laboratory setting (n = 18) and in the context of daily military training routine (n = 24). The overall recognition rates during isolated activities and during daily military routine activities were 87.5% and 85.5%, respectively. We conclude that the algorithm adequately recognized six military-specific physical activities based on sensor data alone both in a laboratory setting and in the military training environment. By recognizing type of physical activities this objective method provides additional information on military-job descriptions.

A divide-and-conquer algorithm for large-scale de novo transcriptome assembly through combining small assemblies from existing algorithms.

PubMed

Sze, Sing-Hoi; Parrott, Jonathan J; Tarone, Aaron M

2017-12-06

While the continued development of high-throughput sequencing has facilitated studies of entire transcriptomes in non-model organisms, the incorporation of an increasing amount of RNA-Seq libraries has made de novo transcriptome assembly difficult. Although algorithms that can assemble a large amount of RNA-Seq data are available, they are generally very memory-intensive and can only be used to construct small assemblies. We develop a divide-and-conquer strategy that allows these algorithms to be utilized, by subdividing a large RNA-Seq data set into small libraries. Each individual library is assembled independently by an existing algorithm, and a merging algorithm is developed to combine these assemblies by picking a subset of high quality transcripts to form a large transcriptome. When compared to existing algorithms that return a single assembly directly, this strategy achieves comparable or increased accuracy as memory-efficient algorithms that can be used to process a large amount of RNA-Seq data, and comparable or decreased accuracy as memory-intensive algorithms that can only be used to construct small assemblies. Our divide-and-conquer strategy allows memory-intensive de novo transcriptome assembly algorithms to be utilized to construct large assemblies.

TH-E-BRE-07: Development of Dose Calculation Error Predictors for a Widely Implemented Clinical Algorithm

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

Egan, A; Laub, W

2014-06-15

Purpose: Several shortcomings of the current implementation of the analytic anisotropic algorithm (AAA) may lead to dose calculation errors in highly modulated treatments delivered to highly heterogeneous geometries. Here we introduce a set of dosimetric error predictors that can be applied to a clinical treatment plan and patient geometry in order to identify high risk plans. Once a problematic plan is identified, the treatment can be recalculated with more accurate algorithm in order to better assess its viability. Methods: Here we focus on three distinct sources dosimetric error in the AAA algorithm. First, due to a combination of discrepancies inmore » smallfield beam modeling as well as volume averaging effects, dose calculated through small MLC apertures can be underestimated, while that behind small MLC blocks can overestimated. Second, due the rectilinear scaling of the Monte Carlo generated pencil beam kernel, energy is not properly transported through heterogeneities near, but not impeding, the central axis of the beamlet. And third, AAA overestimates dose in regions very low density (< 0.2 g/cm{sup 3}). We have developed an algorithm to detect the location and magnitude of each scenario within the patient geometry, namely the field-size index (FSI), the heterogeneous scatter index (HSI), and the lowdensity index (LDI) respectively. Results: Error indices successfully identify deviations between AAA and Monte Carlo dose distributions in simple phantom geometries. Algorithms are currently implemented in the MATLAB computing environment and are able to run on a typical RapidArc head and neck geometry in less than an hour. Conclusion: Because these error indices successfully identify each type of error in contrived cases, with sufficient benchmarking, this method can be developed into a clinical tool that may be able to help estimate AAA dose calculation errors and when it might be advisable to use Monte Carlo calculations.« less

Development of fog detection algorithm using Himawari-8/AHI data at daytime

NASA Astrophysics Data System (ADS)

Han, Ji-Hye; Kim, So-Hyeong; suh, Myoung-Seok

2017-04-01

Fog is defined that small cloud water drops or ice particles float in the air and visibility is less than 1 km. In general, fog affects ecological system, radiation budget and human activities such as airplane, ship, and car. In this study, we developed a fog detection algorithm (FDA) consisted of four threshold tests of optical and textual properties of fog using satellite and ground observation data at daytime. For the detection of fog, we used satellite data (Himawari-8/AHI data) and other ancillary data such as air temperature from NWP data (over land), SST from OSTIA (over sea). And for validation, ground observed visibility data from KMA. The optical and textual properties of fog are normalized albedo (NAlb) and normalized local standard deviation (NLSD), respectively. In addition, differences between air temperature (SST) and fog top temperature (FTa(S)) are applied to discriminate the fog from low clouds. And post-processing is performed to detect the fog edge based on spatial continuity of fog. Threshold values for each test are determined by optimization processes based on the ROC analysis for the selected fog cases. Fog detection is performed according to solar zenith angle (SZA) because of the difference of available satellite data. In this study, we defined daytime when SZA is less than 85˚ . Result of FDA is presented by probability (0 ˜ 100 %) of fog through the weighted sum of each test result. The validation results with ground observed visibility data showed that POD and FAR are 0.63 ˜ 0.89 and 0.29 ˜ 0.46 according to the fog intensity and type, respectively. In general, the detection skills are better in the cases of intense and without high clouds than localized and weak fog. We are plan to transfer this algorithm to the National Meteorological Satellite Center of KMA for the operational detection of fog using GK-2A/AMI data which will be launched in 2018.

Developing Information Power Grid Based Algorithms and Software

NASA Technical Reports Server (NTRS)

Dongarra, Jack

1998-01-01

This was an exploratory study to enhance our understanding of problems involved in developing large scale applications in a heterogeneous distributed environment. It is likely that the large scale applications of the future will be built by coupling specialized computational modules together. For example, efforts now exist to couple ocean and atmospheric prediction codes to simulate a more complete climate system. These two applications differ in many respects. They have different grids, the data is in different unit systems and the algorithms for inte,-rating in time are different. In addition the code for each application is likely to have been developed on different architectures and tend to have poor performance when run on an architecture for which the code was not designed, if it runs at all. Architectural differences may also induce differences in data representation which effect precision and convergence criteria as well as data transfer issues. In order to couple such dissimilar codes some form of translation must be present. This translation should be able to handle interpolation from one grid to another as well as construction of the correct data field in the correct units from available data. Even if a code is to be developed from scratch, a modular approach will likely be followed in that standard scientific packages will be used to do the more mundane tasks such as linear algebra or Fourier transform operations. This approach allows the developers to concentrate on their science rather than becoming experts in linear algebra or signal processing. Problems associated with this development approach include difficulties associated with data extraction and translation from one module to another, module performance on different nodal architectures, and others. In addition to these data and software issues there exists operational issues such as platform stability and resource management.

Predicting Activity Energy Expenditure Using the Actical[R] Activity Monitor

ERIC Educational Resources Information Center

Heil, Daniel P.

2006-01-01

This study developed algorithms for predicting activity energy expenditure (AEE) in children (n = 24) and adults (n = 24) from the Actical[R] activity monitor. Each participant performed 10 activities (supine resting, three sitting, three house cleaning, and three locomotion) while wearing monitors on the ankle, hip, and wrist; AEE was computed…

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.

DEVELOPMENT AND TESTING OF FAULT-DIAGNOSIS ALGORITHMS FOR REACTOR PLANT SYSTEMS

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

Grelle, Austin L.; Park, Young S.; Vilim, Richard B.

Argonne National Laboratory is further developing fault diagnosis algorithms for use by the operator of a nuclear plant to aid in improved monitoring of overall plant condition and performance. The objective is better management of plant upsets through more timely, informed decisions on control actions with the ultimate goal of improved plant safety, production, and cost management. Integration of these algorithms with visual aids for operators is taking place through a collaboration under the concept of an operator advisory system. This is a software entity whose purpose is to manage and distill the enormous amount of information an operator mustmore » process to understand the plant state, particularly in off-normal situations, and how the state trajectory will unfold in time. The fault diagnosis algorithms were exhaustively tested using computer simulations of twenty different faults introduced into the chemical and volume control system (CVCS) of a pressurized water reactor (PWR). The algorithms are unique in that each new application to a facility requires providing only the piping and instrumentation diagram (PID) and no other plant-specific information; a subject-matter expert is not needed to install and maintain each instance of an application. The testing approach followed accepted procedures for verifying and validating software. It was shown that the code satisfies its functional requirement which is to accept sensor information, identify process variable trends based on this sensor information, and then to return an accurate diagnosis based on chains of rules related to these trends. The validation and verification exercise made use of GPASS, a one-dimensional systems code, for simulating CVCS operation. Plant components were failed and the code generated the resulting plant response. Parametric studies with respect to the severity of the fault, the richness of the plant sensor set, and the accuracy of sensors were performed as part of the validation

The development of a 3D mesoscopic model of metallic foam based on an improved watershed algorithm

NASA Astrophysics Data System (ADS)

Zhang, Jinhua; Zhang, Yadong; Wang, Guikun; Fang, Qin

2018-06-01

The watershed algorithm has been used widely in the x-ray computed tomography (XCT) image segmentation. It provides a transformation defined on a grayscale image and finds the lines that separate adjacent images. However, distortion occurs in developing a mesoscopic model of metallic foam based on XCT image data. The cells are oversegmented at some events when the traditional watershed algorithm is used. The improved watershed algorithm presented in this paper can avoid oversegmentation and is composed of three steps. Firstly, it finds all of the connected cells and identifies the junctions of the corresponding cell walls. Secondly, the image segmentation is conducted to separate the adjacent cells. It generates the lost cell walls between the adjacent cells. Optimization is then performed on the segmentation image. Thirdly, this improved algorithm is validated when it is compared with the image of the metallic foam, which shows that it can avoid the image segmentation distortion. A mesoscopic model of metallic foam is thus formed based on the improved algorithm, and the mesoscopic characteristics of the metallic foam, such as cell size, volume and shape, are identified and analyzed.

Evaluation of SMAP Level 2 Soil Moisture Algorithms Using SMOS Data

NASA Technical Reports Server (NTRS)

Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann; Shi, J. C.

2011-01-01

The objectives of the SMAP (Soil Moisture Active Passive) mission are global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolution, respectively. SMAP will provide soil moisture with a spatial resolution of 10 km with a 3-day revisit time at an accuracy of 0.04 m3/m3 [1]. In this paper we contribute to the development of the Level 2 soil moisture algorithm that is based on passive microwave observations by exploiting Soil Moisture Ocean Salinity (SMOS) satellite observations and products. SMOS brightness temperatures provide a global real-world, rather than simulated, test input for the SMAP radiometer-only soil moisture algorithm. Output of the potential SMAP algorithms will be compared to both in situ measurements and SMOS soil moisture products. The investigation will result in enhanced SMAP pre-launch algorithms for soil moisture.

Microphysical particle properties derived from inversion algorithms developed in the framework of EARLINET

NASA Astrophysics Data System (ADS)

Müller, Detlef; Böckmann, Christine; Kolgotin, Alexei; Schneidenbach, Lars; Chemyakin, Eduard; Rosemann, Julia; Znak, Pavel; Romanov, Anton

2016-10-01

We present a summary on the current status of two inversion algorithms that are used in EARLINET (European Aerosol Research Lidar Network) for the inversion of data collected with EARLINET multiwavelength Raman lidars. These instruments measure backscatter coefficients at 355, 532, and 1064 nm, and extinction coefficients at 355 and 532 nm. Development of these two algorithms started in 2000 when EARLINET was founded. The algorithms are based on a manually controlled inversion of optical data which allows for detailed sensitivity studies. The algorithms allow us to derive particle effective radius as well as volume and surface area concentration with comparably high confidence. The retrieval of the real and imaginary parts of the complex refractive index still is a challenge in view of the accuracy required for these parameters in climate change studies in which light absorption needs to be known with high accuracy. It is an extreme challenge to retrieve the real part with an accuracy better than 0.05 and the imaginary part with accuracy better than 0.005-0.1 or ±50 %. Single-scattering albedo can be computed from the retrieved microphysical parameters and allows us to categorize aerosols into high- and low-absorbing aerosols. On the basis of a few exemplary simulations with synthetic optical data we discuss the current status of these manually operated algorithms, the potentially achievable accuracy of data products, and the goals for future work. One algorithm was used with the purpose of testing how well microphysical parameters can be derived if the real part of the complex refractive index is known to at least 0.05 or 0.1. The other algorithm was used to find out how well microphysical parameters can be derived if this constraint for the real part is not applied. The optical data used in our study cover a range of Ångström exponents and extinction-to-backscatter (lidar) ratios that are found from lidar measurements of various aerosol types. We also tested

Periodic activation function and a modified learning algorithm for the multivalued neuron.

PubMed

Aizenberg, Igor

2010-12-01

In this paper, we consider a new periodic activation function for the multivalued neuron (MVN). The MVN is a neuron with complex-valued weights and inputs/output, which are located on the unit circle. Although the MVN outperforms many other neurons and MVN-based neural networks have shown their high potential, the MVN still has a limited capability of learning highly nonlinear functions. A periodic activation function, which is introduced in this paper, makes it possible to learn nonlinearly separable problems and non-threshold multiple-valued functions using a single multivalued neuron. We call this neuron a multivalued neuron with a periodic activation function (MVN-P). The MVN-Ps functionality is much higher than that of the regular MVN. The MVN-P is more efficient in solving various classification problems. A learning algorithm based on the error-correction rule for the MVN-P is also presented. It is shown that a single MVN-P can easily learn and solve those benchmark classification problems that were considered unsolvable using a single neuron. It is also shown that a universal binary neuron, which can learn nonlinearly separable Boolean functions, and a regular MVN are particular cases of the MVN-P.

Development and validation of an algorithm to complete colonoscopy using standard endoscopes in patients with prior incomplete colonoscopy

PubMed Central

Rogers, Melinda C.; Gawron, Andrew; Grande, David; Keswani, Rajesh N.

2017-01-01

Background and study aims  Incomplete colonoscopy may occur as a result of colon angulation (adhesions or diverticulosis), endoscope looping, or both. Specialty endoscopes/devices have been shown to successfully complete prior incomplete colonoscopies, but may not be widely available. Radiographic or other image-based evaluations have been shown to be effective but may miss small or flat lesions, and colonoscopy is often still indicated if a large lesion is identified. The purpose of this study was to develop and validate an algorithm to determine the optimum endoscope to ensure completion of the examination in patients with prior incomplete colonoscopy. Patients and methods  This was a prospective cohort study of 175 patients with prior incomplete colonoscopy who were referred to a single endoscopist at a single academic medical center over a 3-year period from 2012 through 2015. Colonoscopy outcomes from the initial 50 patients were used to develop an algorithm to determine the optimal standard endoscope and technique to achieve cecal intubation. The algorithm was validated on the subsequent 125 patients. Results  The overall repeat colonoscopy success rate using a standard endoscope was 94 %. The initial standard endoscope specified by the algorithm was used and completed the colonoscopy in 90 % of patients. Conclusions  This study identifies an effective strategy for completing colonoscopy in patients with prior incomplete examination, using widely available standard endoscopes and an algorithm based on patient characteristics and reasons for prior incomplete colonoscopy. PMID:28924595

Machine learning algorithms for the prediction of hERG and CYP450 binding in drug development.

PubMed

Klon, Anthony E

2010-07-01

The cost of developing new drugs is estimated at approximately $1 billion; the withdrawal of a marketed compound due to toxicity can result in serious financial loss for a pharmaceutical company. There has been a greater interest in the development of in silico tools that can identify compounds with metabolic liabilities before they are brought to market. The two largest classes of machine learning (ML) models, which will be discussed in this review, have been developed to predict binding to the human ether-a-go-go related gene (hERG) ion channel protein and the various CYP isoforms. Being able to identify potentially toxic compounds before they are made would greatly reduce the number of compound failures and the costs associated with drug development. This review summarizes the state of modeling hERG and CYP binding towards this goal since 2003 using ML algorithms. A wide variety of ML algorithms that are comparable in their overall performance are available. These ML methods may be applied regularly in discovery projects to flag compounds with potential metabolic liabilities.

Research On Vehicle-Based Driver Status/Performance Monitoring; Development, Validation, And Refinement Of Algorithms For Detection Of Driver Drowsiness, Final Report

DOT National Transportation Integrated Search

1994-12-01

THIS REPORT SUMMARIZES THE RESULTS OF A 3-YEAR RESEARCH PROJECT TO DEVELOP RELIABLE ALGORITHMS FOR THE DETECTION OF MOTOR VEHICLE DRIVER IMPAIRMENT DUE TO DROWSINESS. THESE ALGORITHMS ARE BASED ON DRIVING PERFORMANCE MEASURES THAT CAN POTENTIALLY BE ...

Implementing a self-structuring data learning algorithm

NASA Astrophysics Data System (ADS)

Graham, James; Carson, Daniel; Ternovskiy, Igor

2016-05-01

In this paper, we elaborate on what we did to implement our self-structuring data learning algorithm. To recap, we are working to develop a data learning algorithm that will eventually be capable of goal driven pattern learning and extrapolation of more complex patterns from less complex ones. At this point we have developed a conceptual framework for the algorithm, but have yet to discuss our actual implementation and the consideration and shortcuts we needed to take to create said implementation. We will elaborate on our initial setup of the algorithm and the scenarios we used to test our early stage algorithm. While we want this to be a general algorithm, it is necessary to start with a simple scenario or two to provide a viable development and testing environment. To that end, our discussion will be geared toward what we include in our initial implementation and why, as well as what concerns we may have. In the future, we expect to be able to apply our algorithm to a more general approach, but to do so within a reasonable time, we needed to pick a place to start.

Multidisciplinary Design, Analysis, and Optimization Tool Development using a Genetic Algorithm

NASA Technical Reports Server (NTRS)

Pak, Chan-gi; Li, Wesley

2008-01-01

Multidisciplinary design, analysis, and optimization using a genetic algorithm is being developed at the National Aeronautics and Space A dministration Dryden Flight Research Center to automate analysis and design process by leveraging existing tools such as NASTRAN, ZAERO a nd CFD codes to enable true multidisciplinary optimization in the pr eliminary design stage of subsonic, transonic, supersonic, and hypers onic aircraft. This is a promising technology, but faces many challe nges in large-scale, real-world application. This paper describes cur rent approaches, recent results, and challenges for MDAO as demonstr ated by our experience with the Ikhana fire pod design.

An End-to-End simulator for the development of atmospheric corrections and temperature - emissivity separation algorithms in the TIR spectral domain

NASA Astrophysics Data System (ADS)

Rock, Gilles; Fischer, Kim; Schlerf, Martin; Gerhards, Max; Udelhoven, Thomas

2017-04-01

The development and optimization of image processing algorithms requires the availability of datasets depicting every step from earth surface to the sensor's detector. The lack of ground truth data obliges to develop algorithms on simulated data. The simulation of hyperspectral remote sensing data is a useful tool for a variety of tasks such as the design of systems, the understanding of the image formation process, and the development and validation of data processing algorithms. An end-to-end simulator has been set up consisting of a forward simulator, a backward simulator and a validation module. The forward simulator derives radiance datasets based on laboratory sample spectra, applies atmospheric contributions using radiative transfer equations, and simulates the instrument response using configurable sensor models. This is followed by the backward simulation branch, consisting of an atmospheric correction (AC), a temperature and emissivity separation (TES) or a hybrid AC and TES algorithm. An independent validation module allows the comparison between input and output dataset and the benchmarking of different processing algorithms. In this study, hyperspectral thermal infrared scenes of a variety of surfaces have been simulated to analyze existing AC and TES algorithms. The ARTEMISS algorithm was optimized and benchmarked against the original implementations. The errors in TES were found to be related to incorrect water vapor retrieval. The atmospheric characterization could be optimized resulting in increasing accuracies in temperature and emissivity retrieval. Airborne datasets of different spectral resolutions were simulated from terrestrial HyperCam-LW measurements. The simulated airborne radiance spectra were subjected to atmospheric correction and TES and further used for a plant species classification study analyzing effects related to noise and mixed pixels.

Development and validation of a prediction algorithm for the onset of common mental disorders in a working population.

PubMed

Fernandez, Ana; Salvador-Carulla, Luis; Choi, Isabella; Calvo, Rafael; Harvey, Samuel B; Glozier, Nicholas

2018-01-01

Common mental disorders are the most common reason for long-term sickness absence in most developed countries. Prediction algorithms for the onset of common mental disorders may help target indicated work-based prevention interventions. We aimed to develop and validate a risk algorithm to predict the onset of common mental disorders at 12 months in a working population. We conducted a secondary analysis of the Household, Income and Labour Dynamics in Australia Survey, a longitudinal, nationally representative household panel in Australia. Data from the 6189 working participants who did not meet the criteria for a common mental disorders at baseline were non-randomly split into training and validation databases, based on state of residence. Common mental disorders were assessed with the mental component score of 36-Item Short Form Health Survey questionnaire (score ⩽45). Risk algorithms were constructed following recommendations made by the Transparent Reporting of a multivariable prediction model for Prevention Or Diagnosis statement. Different risk factors were identified among women and men for the final risk algorithms. In the training data, the model for women had a C-index of 0.73 and effect size (Hedges' g) of 0.91. In men, the C-index was 0.76 and the effect size was 1.06. In the validation data, the C-index was 0.66 for women and 0.73 for men, with positive predictive values of 0.28 and 0.26, respectively Conclusion: It is possible to develop an algorithm with good discrimination for the onset identifying overall and modifiable risks of common mental disorders among working men. Such models have the potential to change the way that prevention of common mental disorders at the workplace is conducted, but different models may be required for women.

Development of an Algorithm for Stroke Prediction: A National Health Insurance Database Study in Korea.

PubMed

Min, Seung Nam; Park, Se Jin; Kim, Dong Joon; Subramaniyam, Murali; Lee, Kyung-Sun

2018-01-01

Stroke is the second leading cause of death worldwide and remains an important health burden both for the individuals and for the national healthcare systems. Potentially modifiable risk factors for stroke include hypertension, cardiac disease, diabetes, and dysregulation of glucose metabolism, atrial fibrillation, and lifestyle factors. We aimed to derive a model equation for developing a stroke pre-diagnosis algorithm with the potentially modifiable risk factors. We used logistic regression for model derivation, together with data from the database of the Korea National Health Insurance Service (NHIS). We reviewed the NHIS records of 500,000 enrollees. For the regression analysis, data regarding 367 stroke patients were selected. The control group consisted of 500 patients followed up for 2 consecutive years and with no history of stroke. We developed a logistic regression model based on information regarding several well-known modifiable risk factors. The developed model could correctly discriminate between normal subjects and stroke patients in 65% of cases. The model developed in the present study can be applied in the clinical setting to estimate the probability of stroke in a year and thus improve the stroke prevention strategies in high-risk patients. The approach used to develop the stroke prevention algorithm can be applied for developing similar models for the pre-diagnosis of other diseases. © 2018 S. Karger AG, Basel.

An Efficient Correction Algorithm for Eliminating Image Misalignment Effects on Co-Phasing Measurement Accuracy for Segmented Active Optics Systems

PubMed Central

Yue, Dan; Xu, Shuyan; Nie, Haitao; Wang, Zongyang

2016-01-01

The misalignment between recorded in-focus and out-of-focus images using the Phase Diversity (PD) algorithm leads to a dramatic decline in wavefront detection accuracy and image recovery quality for segmented active optics systems. This paper demonstrates the theoretical relationship between the image misalignment and tip-tilt terms in Zernike polynomials of the wavefront phase for the first time, and an efficient two-step alignment correction algorithm is proposed to eliminate these misalignment effects. This algorithm processes a spatial 2-D cross-correlation of the misaligned images, revising the offset to 1 or 2 pixels and narrowing the search range for alignment. Then, it eliminates the need for subpixel fine alignment to achieve adaptive correction by adding additional tip-tilt terms to the Optical Transfer Function (OTF) of the out-of-focus channel. The experimental results demonstrate the feasibility and validity of the proposed correction algorithm to improve the measurement accuracy during the co-phasing of segmented mirrors. With this alignment correction, the reconstructed wavefront is more accurate, and the recovered image is of higher quality. PMID:26934045

Firefly algorithm with chaos

NASA Astrophysics Data System (ADS)

Gandomi, A. H.; Yang, X.-S.; Talatahari, S.; Alavi, A. H.

2013-01-01

A recently developed metaheuristic optimization algorithm, firefly algorithm (FA), mimics the social behavior of fireflies based on the flashing and attraction characteristics of fireflies. In the present study, we will introduce chaos into FA so as to increase its global search mobility for robust global optimization. Detailed studies are carried out on benchmark problems with different chaotic maps. Here, 12 different chaotic maps are utilized to tune the attractive movement of the fireflies in the algorithm. The results show that some chaotic FAs can clearly outperform the standard FA.

Tuning of active vibration controllers for ACTEX by genetic algorithm

NASA Astrophysics Data System (ADS)

Kwak, Moon K.; Denoyer, Keith K.

1999-06-01

This paper is concerned with the optimal tuning of digitally programmable analog controllers on the ACTEX-1 smart structures flight experiment. The programmable controllers for each channel include a third order Strain Rate Feedback (SRF) controller, a fifth order SRF controller, a second order Positive Position Feedback (PPF) controller, and a fourth order PPF controller. Optimal manual tuning of several control parameters can be a difficult task even though the closed-loop control characteristics of each controller are well known. Hence, the automatic tuning of individual control parameters using Genetic Algorithms is proposed in this paper. The optimal control parameters of each control law are obtained by imposing a constraint on the closed-loop frequency response functions using the ACTEX mathematical model. The tuned control parameters are then uploaded to the ACTEX electronic control electronics and experiments on the active vibration control are carried out in space. The experimental results on ACTEX will be presented.

Accessing primary care Big Data: the development of a software algorithm to explore the rich content of consultation records.

PubMed

MacRae, J; Darlow, B; McBain, L; Jones, O; Stubbe, M; Turner, N; Dowell, A

2015-08-21

To develop a natural language processing software inference algorithm to classify the content of primary care consultations using electronic health record Big Data and subsequently test the algorithm's ability to estimate the prevalence and burden of childhood respiratory illness in primary care. Algorithm development and validation study. To classify consultations, the algorithm is designed to interrogate clinical narrative entered as free text, diagnostic (Read) codes created and medications prescribed on the day of the consultation. Thirty-six consenting primary care practices from a mixed urban and semirural region of New Zealand. Three independent sets of 1200 child consultation records were randomly extracted from a data set of all general practitioner consultations in participating practices between 1 January 2008-31 December 2013 for children under 18 years of age (n=754,242). Each consultation record within these sets was independently classified by two expert clinicians as respiratory or non-respiratory, and subclassified according to respiratory diagnostic categories to create three 'gold standard' sets of classified records. These three gold standard record sets were used to train, test and validate the algorithm. Sensitivity, specificity, positive predictive value and F-measure were calculated to illustrate the algorithm's ability to replicate judgements of expert clinicians within the 1200 record gold standard validation set. The algorithm was able to identify respiratory consultations in the 1200 record validation set with a sensitivity of 0.72 (95% CI 0.67 to 0.78) and a specificity of 0.95 (95% CI 0.93 to 0.98). The positive predictive value of algorithm respiratory classification was 0.93 (95% CI 0.89 to 0.97). The positive predictive value of the algorithm classifying consultations as being related to specific respiratory diagnostic categories ranged from 0.68 (95% CI 0.40 to 1.00; other respiratory conditions) to 0.91 (95% CI 0.79 to 1

Development and validation of a novel algorithm based on the ECG magnet response for rapid identification of any unknown pacemaker.

PubMed

Squara, Fabien; Chik, William W; Benhayon, Daniel; Maeda, Shingo; Latcu, Decebal Gabriel; Lacaze-Gadonneix, Jonathan; Tibi, Thierry; Thomas, Olivier; Cooper, Joshua M; Duthoit, Guillaume

2014-08-01

Pacemaker (PM) interrogation requires correct manufacturer identification. However, an unidentified PM is a frequent occurrence, requiring time-consuming steps to identify the device. The purpose of this study was to develop and validate a novel algorithm for PM manufacturer identification, using the ECG response to magnet application. Data on the magnet responses of all recent PM models (≤15 years) from the 5 major manufacturers were collected. An algorithm based on the ECG response to magnet application to identify the PM manufacturer was subsequently developed. Patients undergoing ECG during magnet application in various clinical situations were prospectively recruited in 7 centers. The algorithm was applied in the analysis of every ECG by a cardiologist blinded to PM information. A second blinded cardiologist analyzed a sample of randomly selected ECGs in order to assess the reproducibility of the results. A total of 250 ECGs were analyzed during magnet application. The algorithm led to the correct single manufacturer choice in 242 ECGs (96.8%), whereas 7 (2.8%) could only be narrowed to either 1 of 2 manufacturer possibilities. Only 2 (0.4%) incorrect manufacturer identifications occurred. The algorithm identified Medtronic and Sorin Group PMs with 100% sensitivity and specificity, Biotronik PMs with 100% sensitivity and 99.5% specificity, and St. Jude and Boston Scientific PMs with 92% sensitivity and 100% specificity. The results were reproducible between the 2 blinded cardiologists with 92% concordant findings. Unknown PM manufacturers can be accurately identified by analyzing the ECG magnet response using this newly developed algorithm. Copyright © 2014 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Development of a remote sensing algorithm to retrieve atmospheric aerosol properties using multiwavelength and multipixel information

NASA Astrophysics Data System (ADS)

Hashimoto, Makiko; Nakajima, Teruyuki

2017-06-01

We developed a satellite remote sensing algorithm to retrieve the aerosol optical properties using satellite-received radiances for multiple wavelengths and pixels. Our algorithm utilizes spatial inhomogeneity of surface reflectance to retrieve aerosol properties, and the main target is urban aerosols. This algorithm can simultaneously retrieve aerosol optical thicknesses (AOT) for fine- and coarse-mode aerosols, soot volume fraction in fine-mode aerosols (SF), and surface reflectance over heterogeneous surfaces such as urban areas that are difficult to obtain by conventional pixel-by-pixel methods. We applied this algorithm to radiances measured by the Greenhouse Gases Observing Satellite/Thermal and Near Infrared Sensor for Carbon Observations-Cloud and Aerosol Image (GOSAT/TANSO-CAI) at four wavelengths and were able to retrieve the aerosol parameters in several urban regions and other surface types. A comparison of the retrieved AOTs with those from the Aerosol Robotic Network (AERONET) indicated retrieval accuracy within ±0.077 on average. It was also found that the column-averaged SF and the aerosol single scattering albedo (SSA) underwent seasonal changes as consistent with the ground surface measurements of SSA and black carbon at Beijing, China.

Iterative algorithms for large sparse linear systems on parallel computers

NASA Technical Reports Server (NTRS)

Adams, L. M.

1982-01-01

Algorithms for assembling in parallel the sparse system of linear equations that result from finite difference or finite element discretizations of elliptic partial differential equations, such as those that arise in structural engineering are developed. Parallel linear stationary iterative algorithms and parallel preconditioned conjugate gradient algorithms are developed for solving these systems. In addition, a model for comparing parallel algorithms on array architectures is developed and results of this model for the algorithms are given.

Development of GPS Receiver Kalman Filter Algorithms for Stationary, Low-Dynamics, and High-Dynamics Applications

DTIC Science & Technology

2016-06-01

UNCLASSIFIED Development of GPS Receiver Kalman Filter Algorithms for Stationary, Low-Dynamics, and High-Dynamics Applications Peter W. Sarunic 1 1...determine instantaneous estimates of receiver position and then goes on to develop three Kalman filter based estimators, which use stationary receiver...used in actual GPS receivers, and cover a wide range of applications. While the standard form of the Kalman filter , of which the three filters just

HYBRID FAST HANKEL TRANSFORM ALGORITHM FOR ELECTROMAGNETIC MODELING

EPA Science Inventory

A hybrid fast Hankel transform algorithm has been developed that uses several complementary features of two existing algorithms: Anderson's digital filtering or fast Hankel transform (FHT) algorithm and Chave's quadrature and continued fraction algorithm. A hybrid FHT subprogram ...

The Texas Children's Medication Algorithm Project: Revision of the Algorithm for Pharmacotherapy of Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Pliszka, Steven R.; Crismon, M. Lynn; Hughes, Carroll W.; Corners, C. Keith; Emslie, Graham J.; Jensen, Peter S.; McCracken, James T.; Swanson, James M.; Lopez, Molly

2006-01-01

Objective: In 1998, the Texas Department of Mental Health and Mental Retardation developed algorithms for medication treatment of attention-deficit/hyperactivity disorder (ADHD). Advances in the psychopharmacology of ADHD and results of a feasibility study of algorithm use in community mental health centers caused the algorithm to be modified and…

Development and Validation of the Cognitive Behavioral Physical Activity Questionnaire.

PubMed

Schembre, Susan M; Durand, Casey P; Blissmer, Bryan J; Greene, Geoffrey W

2015-01-01

Develop and demonstrate preliminary validation of a brief questionnaire aimed at assessing social cognitive determinants of physical activity (PA) in a college population. Quantitative and observational. A midsized northeastern university. Convenience sample of 827 male and female college students age 18 to 24 years. International Physical Activity Questionnaire and a PA stage-of-change algorithm. A sequential process of survey development, including item generation and data reduction analyses by factor analysis, was followed with the goal of creating a parsimonious questionnaire. Structural equation modeling was used for confirmatory factor analysis and construct validation was confirmed against self-reported PA and stage of change. Validation analyses were replicated in a second, independent sample of 1032 college students. Fifteen items reflecting PA self-regulation, outcome expectations, and personal barriers explained 65% of the questionnaire data and explained 28.6% and 39.5% of the variance in total PA and moderate-to-vigorous-intensity PA, respectively. Scale scores were distinguishable across the stages of change. Findings were similar when the Cognitive Behavioral Physical Activity Questionnaire (CBPAQ) was tested in a similar and independent sample of college students (40%; R (2) moderate-to-vigorous-intensity PA = .40; p < .001). The CBPAQ successfully explains and predicts PA behavior in a college population, warranting its incorporation into future studies aiming at understanding and improving on PA behavior in college students.

Real time algorithms for sharp wave ripple detection.

PubMed

Sethi, Ankit; Kemere, Caleb

2014-01-01

Neural activity during sharp wave ripples (SWR), short bursts of co-ordinated oscillatory activity in the CA1 region of the rodent hippocampus, is implicated in a variety of memory functions from consolidation to recall. Detection of these events in an algorithmic framework, has thus far relied on simple thresholding techniques with heuristically derived parameters. This study is an investigation into testing and improving the current methods for detection of SWR events in neural recordings. We propose and profile methods to reduce latency in ripple detection. Proposed algorithms are tested on simulated ripple data. The findings show that simple realtime algorithms can improve upon existing power thresholding methods and can detect ripple activity with latencies in the range of 10-20 ms.

Comprehensive eye evaluation algorithm

NASA Astrophysics Data System (ADS)

Agurto, C.; Nemeth, S.; Zamora, G.; Vahtel, M.; Soliz, P.; Barriga, S.

2016-03-01

In recent years, several research groups have developed automatic algorithms to detect diabetic retinopathy (DR) in individuals with diabetes (DM), using digital retinal images. Studies have indicated that diabetics have 1.5 times the annual risk of developing primary open angle glaucoma (POAG) as do people without DM. Moreover, DM patients have 1.8 times the risk for age-related macular degeneration (AMD). Although numerous investigators are developing automatic DR detection algorithms, there have been few successful efforts to create an automatic algorithm that can detect other ocular diseases, such as POAG and AMD. Consequently, our aim in the current study was to develop a comprehensive eye evaluation algorithm that not only detects DR in retinal images, but also automatically identifies glaucoma suspects and AMD by integrating other personal medical information with the retinal features. The proposed system is fully automatic and provides the likelihood of each of the three eye disease. The system was evaluated in two datasets of 104 and 88 diabetic cases. For each eye, we used two non-mydriatic digital color fundus photographs (macula and optic disc centered) and, when available, information about age, duration of diabetes, cataracts, hypertension, gender, and laboratory data. Our results show that the combination of multimodal features can increase the AUC by up to 5%, 7%, and 8% in the detection of AMD, DR, and glaucoma respectively. Marked improvement was achieved when laboratory results were combined with retinal image features.

Runtime support for parallelizing data mining algorithms

NASA Astrophysics Data System (ADS)

Jin, Ruoming; Agrawal, Gagan

2002-03-01

With recent technological advances, shared memory parallel machines have become more scalable, and offer large main memories and high bus bandwidths. They are emerging as good platforms for data warehousing and data mining. In this paper, we focus on shared memory parallelization of data mining algorithms. We have developed a series of techniques for parallelization of data mining algorithms, including full replication, full locking, fixed locking, optimized full locking, and cache-sensitive locking. Unlike previous work on shared memory parallelization of specific data mining algorithms, all of our techniques apply to a large number of common data mining algorithms. In addition, we propose a reduction-object based interface for specifying a data mining algorithm. We show how our runtime system can apply any of the technique we have developed starting from a common specification of the algorithm.

Development of TIF based figuring algorithm for deterministic pitch tool polishing

NASA Astrophysics Data System (ADS)

Yi, Hyun-Su; Kim, Sug-Whan; Yang, Ho-Soon; Lee, Yun-Woo

2007-12-01

Pitch is perhaps the oldest material used for optical polishing, leaving superior surface texture, and has been used widely in the optics shop floor. However, for its unpredictable controllability of removal characteristics, the pitch tool polishing has been rarely analysed quantitatively and many optics shops rely heavily on optician's "feel" even today. In order to bring a degree of process controllability to the pitch tool polishing, we added motorized tool motions to the conventional Draper type polishing machine and modelled the tool path in the absolute machine coordinate. We then produced a number of Tool Influence Function (TIF) both from an analytical model and a series of experimental polishing runs using the pitch tool. The theoretical TIFs agreed well with the experimental TIFs to the profile accuracy of 79 % in terms of its shape. The surface figuring algorithm was then developed in-house utilizing both theoretical and experimental TIFs. We are currently undertaking a series of trial figuring experiments to prove the performance of the polishing algorithm, and the early results indicate that the highly deterministic material removal control with the pitch tool can be achieved to a certain level of form error. The machine renovation, TIF theory and experimental confirmation, figuring simulation results are reported together with implications to deterministic polishing.

Estimation and tracking of AP-diameter of the inferior vena cava in ultrasound images using a novel active circle algorithm.

PubMed

Karami, Ebrahim; Shehata, Mohamed S; Smith, Andrew

2018-05-04

Medical research suggests that the anterior-posterior (AP)-diameter of the inferior vena cava (IVC) and its associated temporal variation as imaged by bedside ultrasound is useful in guiding fluid resuscitation of the critically-ill patient. Unfortunately, indistinct edges and gaps in vessel walls are frequently present which impede accurate estimation of the IVC AP-diameter for both human operators and segmentation algorithms. The majority of research involving use of the IVC to guide fluid resuscitation involves manual measurement of the maximum and minimum AP-diameter as it varies over time. This effort proposes using a time-varying circle fitted inside the typically ellipsoid IVC as an efficient, consistent and novel approach to tracking and approximating the AP-diameter even in the context of poor image quality. In this active-circle algorithm, a novel evolution functional is proposed and shown to be a useful tool for ultrasound image processing. The proposed algorithm is compared with an expert manual measurement, and state-of-the-art relevant algorithms. It is shown that the algorithm outperforms other techniques and performs very close to manual measurement. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Robustly Stabilizing Model Predictive Control Algorithm

NASA Technical Reports Server (NTRS)

Ackmece, A. Behcet; Carson, John M., III

2007-01-01

A model predictive control (MPC) algorithm that differs from prior MPC algorithms has been developed for controlling an uncertain nonlinear system. This algorithm guarantees the resolvability of an associated finite-horizon optimal-control problem in a receding-horizon implementation.

A new algorithm for attitude-independent magnetometer calibration

NASA Technical Reports Server (NTRS)

Alonso, Roberto; Shuster, Malcolm D.

1994-01-01

A new algorithm is developed for inflight magnetometer bias determination without knowledge of the attitude. This algorithm combines the fast convergence of a heuristic algorithm currently in use with the correct treatment of the statistics and without discarding data. The algorithm performance is examined using simulated data and compared with previous algorithms.

Development of Analytical Algorithm for the Performance Analysis of Power Train System of an Electric Vehicle

NASA Astrophysics Data System (ADS)

Kim, Chul-Ho; Lee, Kee-Man; Lee, Sang-Heon

Power train system design is one of the key R&D areas on the development process of new automobile because an optimum size of engine with adaptable power transmission which can accomplish the design requirement of new vehicle can be obtained through the system design. Especially, for the electric vehicle design, very reliable design algorithm of a power train system is required for the energy efficiency. In this study, an analytical simulation algorithm is developed to estimate driving performance of a designed power train system of an electric. The principal theory of the simulation algorithm is conservation of energy with several analytical and experimental data such as rolling resistance, aerodynamic drag, mechanical efficiency of power transmission etc. From the analytical calculation results, running resistance of a designed vehicle is obtained with the change of operating condition of the vehicle such as inclined angle of road and vehicle speed. Tractive performance of the model vehicle with a given power train system is also calculated at each gear ratio of transmission. Through analysis of these two calculation results: running resistance and tractive performance, the driving performance of a designed electric vehicle is estimated and it will be used to evaluate the adaptability of the designed power train system on the vehicle.

A recursive algorithm for the three-dimensional imaging of brain electric activity: Shrinking LORETA-FOCUSS.

PubMed

Liu, Hesheng; Gao, Xiaorong; Schimpf, Paul H; Yang, Fusheng; Gao, Shangkai

2004-10-01