Machine Learning for Biological Trajectory Classification Applications
NASA Technical Reports Server (NTRS)
Sbalzarini, Ivo F.; Theriot, Julie; Koumoutsakos, Petros
2002-01-01
Machine-learning techniques, including clustering algorithms, support vector machines and hidden Markov models, are applied to the task of classifying trajectories of moving keratocyte cells. The different algorithms axe compared to each other as well as to expert and non-expert test persons, using concepts from signal-detection theory. The algorithms performed very well as compared to humans, suggesting a robust tool for trajectory classification in biological applications.
Supervised Learning Applied to Air Traffic Trajectory Classification
NASA Technical Reports Server (NTRS)
Bosson, Christabelle S.; Nikoleris, Tasos
2018-01-01
Given the recent increase of interest in introducing new vehicle types and missions into the National Airspace System, a transition towards a more autonomous air traffic control system is required in order to enable and handle increased density and complexity. This paper presents an exploratory effort of the needed autonomous capabilities by exploring supervised learning techniques in the context of aircraft trajectories. In particular, it focuses on the application of machine learning algorithms and neural network models to a runway recognition trajectory-classification study. It investigates the applicability and effectiveness of various classifiers using datasets containing trajectory records for a month of air traffic. A feature importance and sensitivity analysis are conducted to challenge the chosen time-based datasets and the ten selected features. The study demonstrates that classification accuracy levels of 90% and above can be reached in less than 40 seconds of training for most machine learning classifiers when one track data point, described by the ten selected features at a particular time step, per trajectory is used as input. It also shows that neural network models can achieve similar accuracy levels but at higher training time costs.
Classification of Dynamical Diffusion States in Single Molecule Tracking Microscopy
Bosch, Peter J.; Kanger, Johannes S.; Subramaniam, Vinod
2014-01-01
Single molecule tracking of membrane proteins by fluorescence microscopy is a promising method to investigate dynamic processes in live cells. Translating the trajectories of proteins to biological implications, such as protein interactions, requires the classification of protein motion within the trajectories. Spatial information of protein motion may reveal where the protein interacts with cellular structures, because binding of proteins to such structures often alters their diffusion speed. For dynamic diffusion systems, we provide an analytical framework to determine in which diffusion state a molecule is residing during the course of its trajectory. We compare different methods for the quantification of motion to utilize this framework for the classification of two diffusion states (two populations with different diffusion speed). We found that a gyration quantification method and a Bayesian statistics-based method are the most accurate in diffusion-state classification for realistic experimentally obtained datasets, of which the gyration method is much less computationally demanding. After classification of the diffusion, the lifetime of the states can be determined, and images of the diffusion states can be reconstructed at high resolution. Simulations validate these applications. We apply the classification and its applications to experimental data to demonstrate the potential of this approach to obtain further insights into the dynamics of cell membrane proteins. PMID:25099798
Mazumder, Oishee; Kundu, Ananda Sankar; Lenka, Prasanna Kumar; Bhaumik, Subhasis
2016-10-01
Ambulatory activity classification is an active area of research for controlling and monitoring state initiation, termination, and transition in mobility assistive devices such as lower-limb exoskeletons. State transition of lower-limb exoskeletons reported thus far are achieved mostly through the use of manual switches or state machine-based logic. In this paper, we propose a postural activity classifier using a 'dendogram-based support vector machine' (DSVM) which can be used to control a lower-limb exoskeleton. A pressure sensor-based wearable insole and two six-axis inertial measurement units (IMU) have been used for recognising two static and seven dynamic postural activities: sit, stand, and sit-to-stand, stand-to-sit, level walk, fast walk, slope walk, stair ascent and stair descent. Most of the ambulatory activities are periodic in nature and have unique patterns of response. The proposed classification algorithm involves the recognition of activity patterns on the basis of the periodic shape of trajectories. Polynomial coefficients extracted from the hip angle trajectory and the centre-of-pressure (CoP) trajectory during an activity cycle are used as features to classify dynamic activities. The novelty of this paper lies in finding suitable instrumentation, developing post-processing techniques, and selecting shape-based features for ambulatory activity classification. The proposed activity classifier is used to identify the activity states of a lower-limb exoskeleton. The DSVM classifier algorithm achieved an overall classification accuracy of 95.2%. Copyright © 2016 Elsevier B.V. All rights reserved.
NASA Technical Reports Server (NTRS)
Cotton, William B.; Hilb, Robert; Koczo, Stefan, Jr.; Wing, David J.
2016-01-01
A set of five developmental steps building from the NASA TASAR (Traffic Aware Strategic Aircrew Requests) concept are described, each providing incrementally more efficiency and capacity benefits to airspace system users and service providers, culminating in a Full Airborne Trajectory Management capability. For each of these steps, the incremental Operational Hazards and Safety Requirements are identified for later use in future formal safety assessments intended to lead to certification and operational approval of the equipment and the associated procedures. Two established safety assessment methodologies that are compliant with the FAA's Safety Management System were used leading to Failure Effects Classifications (FEC) for each of the steps. The most likely FEC for the first three steps, Basic TASAR, Digital TASAR, and 4D TASAR, is "No effect". For step four, Strategic Airborne Trajectory Management, the likely FEC is "Minor". For Full Airborne Trajectory Management (Step 5), the most likely FEC is "Major".
NASA Astrophysics Data System (ADS)
Casasent, David P.; Shenoy, Rajesh
1997-10-01
Classification and pose estimation of distorted input objects are considered. The feature space trajectory representation of distorted views of an object is used with a new eigenfeature space. For a distorted input object, the closest trajectory denotes the class of the input and the closest line segment on it denotes its pose. If an input point is too far from a trajectory, it is rejected as clutter. New methods for selecting Fukunaga-Koontz discriminant vectors, the number of dominant eigenvectors per class and for determining training, and test set compatibility are presented.
Miller, Vonda H; Jansen, Ben H
2008-12-01
Computer algorithms that match human performance in recognizing written text or spoken conversation remain elusive. The reasons why the human brain far exceeds any existing recognition scheme to date in the ability to generalize and to extract invariant characteristics relevant to category matching are not clear. However, it has been postulated that the dynamic distribution of brain activity (spatiotemporal activation patterns) is the mechanism by which stimuli are encoded and matched to categories. This research focuses on supervised learning using a trajectory based distance metric for category discrimination in an oscillatory neural network model. Classification is accomplished using a trajectory based distance metric. Since the distance metric is differentiable, a supervised learning algorithm based on gradient descent is demonstrated. Classification of spatiotemporal frequency transitions and their relation to a priori assessed categories is shown along with the improved classification results after supervised training. The results indicate that this spatiotemporal representation of stimuli and the associated distance metric is useful for simple pattern recognition tasks and that supervised learning improves classification results.
Using Smart Phone Sensors to Detect Transportation Modes
Xia, Hao; Qiao, Yanyou; Jian, Jun; Chang, Yuanfei
2014-01-01
The proliferation of mobile smart devices has led to a rapid increase of location-based services, many of which are amassing large datasets of user trajectory information. Unfortunately, current trajectory information is not yet sufficiently rich to support classification of user transportation modes. In this paper, we propose a method that employs both the Global Positioning System and accelerometer data from smart devices to classify user outdoor transportation modes. The classified modes include walking, bicycling, and motorized transport, in addition to the motionless (stationary) state, for which we provide new depth analysis. In our classification, stationary mode has two sub-modes: stay (remaining in the same place for a prolonged time period; e.g., in a parked vehicle) and wait (remaining at a location for a short period; e.g., waiting at a red traffic light). These two sub-modes present different semantics for data mining applications. We use support vector machines with parameters that are optimized for pattern recognition. In addition, we employ ant colony optimization to reduce the dimension of features and analyze their relative importance. The resulting classification system achieves an accuracy rate of 96.31% when applied to a dataset obtained from 18 mobile users. PMID:25375756
Using smart phone sensors to detect transportation modes.
Xia, Hao; Qiao, Yanyou; Jian, Jun; Chang, Yuanfei
2014-11-04
The proliferation of mobile smart devices has led to a rapid increase of location-based services, many of which are amassing large datasets of user trajectory information. Unfortunately, current trajectory information is not yet sufficiently rich to support classification of user transportation modes. In this paper, we propose a method that employs both the Global Positioning System and accelerometer data from smart devices to classify user outdoor transportation modes. The classified modes include walking, bicycling, and motorized transport, in addition to the motionless (stationary) state, for which we provide new depth analysis. In our classification, stationary mode has two sub-modes: stay (remaining in the same place for a prolonged time period; e.g., in a parked vehicle) and wait (remaining at a location for a short period; e.g., waiting at a red traffic light). These two sub-modes present different semantics for data mining applications. We use support vector machines with parameters that are optimized for pattern recognition. In addition, we employ ant colony optimization to reduce the dimension of features and analyze their relative importance. The resulting classification system achieves an accuracy rate of 96.31% when applied to a dataset obtained from 18 mobile users.
Mars Exploration Rovers Entry, Descent, and Landing Trajectory Analysis
NASA Technical Reports Server (NTRS)
Desai, Prasun N.; Knocke, Philip C.
2007-01-01
In this study we present a novel method of land surface classification using surface-reflected GPS signals in combination with digital imagery. Two GPS-derived classification features are merged with visible image data to create terrain-moisture (TM) classes, defined here as visibly identifiable terrain or landcover classes containing a surface/soil moisture component. As compared to using surface imagery alone, classification accuracy is significantly improved for a number of visible classes when adding the GPS-based signal features. Since the strength of the reflected GPS signal is proportional to the amount of moisture in the surface, use of these GPS features provides information about the surface that is not obtainable using visible wavelengths alone. Application areas include hydrology, precision agriculture, and wetlands mapping.
Wang, Qian; Liu, Zhen; Ziegler, Sibylle I; Shi, Kuangyu
2015-07-07
Position-sensitive positron cameras using silicon pixel detectors have been applied for some preclinical and intraoperative clinical applications. However, the spatial resolution of a positron camera is limited by positron multiple scattering in the detector. An incident positron may fire a number of successive pixels on the imaging plane. It is still impossible to capture the primary fired pixel along a particle trajectory by hardware or to perceive the pixel firing sequence by direct observation. Here, we propose a novel data-driven method to improve the spatial resolution by classifying the primary pixels within the detector using support vector machine. A classification model is constructed by learning the features of positron trajectories based on Monte-Carlo simulations using Geant4. Topological and energy features of pixels fired by (18)F positrons were considered for the training and classification. After applying the classification model on measurements, the primary fired pixels of the positron tracks in the silicon detector were estimated. The method was tested and assessed for [(18)F]FDG imaging of an absorbing edge protocol and a leaf sample. The proposed method improved the spatial resolution from 154.6 ± 4.2 µm (energy weighted centroid approximation) to 132.3 ± 3.5 µm in the absorbing edge measurements. For the positron imaging of a leaf sample, the proposed method achieved lower root mean square error relative to phosphor plate imaging, and higher similarity with the reference optical image. The improvements of the preliminary results support further investigation of the proposed algorithm for the enhancement of positron imaging in clinical and preclinical applications.
NASA Astrophysics Data System (ADS)
Wang, Qian; Liu, Zhen; Ziegler, Sibylle I.; Shi, Kuangyu
2015-07-01
Position-sensitive positron cameras using silicon pixel detectors have been applied for some preclinical and intraoperative clinical applications. However, the spatial resolution of a positron camera is limited by positron multiple scattering in the detector. An incident positron may fire a number of successive pixels on the imaging plane. It is still impossible to capture the primary fired pixel along a particle trajectory by hardware or to perceive the pixel firing sequence by direct observation. Here, we propose a novel data-driven method to improve the spatial resolution by classifying the primary pixels within the detector using support vector machine. A classification model is constructed by learning the features of positron trajectories based on Monte-Carlo simulations using Geant4. Topological and energy features of pixels fired by 18F positrons were considered for the training and classification. After applying the classification model on measurements, the primary fired pixels of the positron tracks in the silicon detector were estimated. The method was tested and assessed for [18F]FDG imaging of an absorbing edge protocol and a leaf sample. The proposed method improved the spatial resolution from 154.6 ± 4.2 µm (energy weighted centroid approximation) to 132.3 ± 3.5 µm in the absorbing edge measurements. For the positron imaging of a leaf sample, the proposed method achieved lower root mean square error relative to phosphor plate imaging, and higher similarity with the reference optical image. The improvements of the preliminary results support further investigation of the proposed algorithm for the enhancement of positron imaging in clinical and preclinical applications.
Applying deep bidirectional LSTM and mixture density network for basketball trajectory prediction
NASA Astrophysics Data System (ADS)
Zhao, Yu; Yang, Rennong; Chevalier, Guillaume; Shah, Rajiv C.; Romijnders, Rob
2018-04-01
Data analytics helps basketball teams to create tactics. However, manual data collection and analytics are costly and ineffective. Therefore, we applied a deep bidirectional long short-term memory (BLSTM) and mixture density network (MDN) approach. This model is not only capable of predicting a basketball trajectory based on real data, but it also can generate new trajectory samples. It is an excellent application to help coaches and players decide when and where to shoot. Its structure is particularly suitable for dealing with time series problems. BLSTM receives forward and backward information at the same time, while stacking multiple BLSTMs further increases the learning ability of the model. Combined with BLSTMs, MDN is used to generate a multi-modal distribution of outputs. Thus, the proposed model can, in principle, represent arbitrary conditional probability distributions of output variables. We tested our model with two experiments on three-pointer datasets from NBA SportVu data. In the hit-or-miss classification experiment, the proposed model outperformed other models in terms of the convergence speed and accuracy. In the trajectory generation experiment, eight model-generated trajectories at a given time closely matched real trajectories.
Chandramouli, Balasubramanian; Mancini, Giordano
2016-01-01
Classical Molecular Dynamics (MD) simulations can provide insights at the nanoscopic scale into protein dynamics. Currently, simulations of large proteins and complexes can be routinely carried out in the ns-μs time regime. Clustering of MD trajectories is often performed to identify selective conformations and to compare simulation and experimental data coming from different sources on closely related systems. However, clustering techniques are usually applied without a careful validation of results and benchmark studies involving the application of different algorithms to MD data often deal with relatively small peptides instead of average or large proteins; finally clustering is often applied as a means to analyze refined data and also as a way to simplify further analysis of trajectories. Herein, we propose a strategy to classify MD data while carefully benchmarking the performance of clustering algorithms and internal validation criteria for such methods. We demonstrate the method on two showcase systems with different features, and compare the classification of trajectories in real and PCA space. We posit that the prototype procedure adopted here could be highly fruitful in clustering large trajectories of multiple systems or that resulting especially from enhanced sampling techniques like replica exchange simulations. Copyright: © 2016 by Fabrizio Serra editore, Pisa · Roma.
Automated tracking, segmentation and trajectory classification of pelvic organs on dynamic MRI.
Nekooeimehr, Iman; Lai-Yuen, Susana; Bao, Paul; Weitzenfeld, Alfredo; Hart, Stuart
2016-08-01
Pelvic organ prolapse is a major health problem in women where pelvic floor organs (bladder, uterus, small bowel, and rectum) fall from their normal position and bulge into the vagina. Dynamic Magnetic Resonance Imaging (DMRI) is presently used to analyze the organs' movements from rest to maximum strain providing complementary support for diagnosis. However, there is currently no automated or quantitative approach to measure the movement of the pelvic organs and their correlation with the severity of prolapse. In this paper, a two-stage method is presented to automatically track and segment pelvic organs on DMRI followed by a multiple-object trajectory classification method to improve the diagnosis of pelvic organ prolapse. Organs are first tracked using particle filters and K-means clustering with prior information. Then, they are segmented using the convex hull of the cluster of particles. Finally, the trajectories of the pelvic organs are modeled using a new Coupled Switched Hidden Markov Model (CSHMM) to classify the severity of pelvic organ prolapse. The tracking and segmentation results are validated using Dice Similarity Index (DSI) whereas the classification results are compared with two manual clinical measurements. Results demonstrate that the presented method is able to automatically track and segment pelvic organs with a DSI above 82% for 26 out of 46 cases and DSI above 75% for all 46 tested cases. The accuracy of the trajectory classification model is also better than current manual measurements.
NASA Astrophysics Data System (ADS)
Wagner, Thorsten; Kroll, Alexandra; Wiemann, Martin; Lipinski, Hans-Gerd
2016-04-01
Darkfield and confocal laser scanning microscopy both allow for a simultaneous observation of live cells and single nanoparticles. Accordingly, a characterization of nanoparticle uptake and intracellular mobility appears possible within living cells. Single particle tracking makes it possible to characterize the particle and the surrounding cell. In case of free diffusion, the mean squared displacement for each trajectory of a nanoparticle can be measured which allows computing the corresponding diffusion coefficient and, if desired, converting it into the hydrodynamic diameter using the Stokes-Einstein equation and the viscosity of the fluid. However, within the more complex system of a cell's cytoplasm unrestrained diffusion is scarce and several other types of movements may occur. Thus, confined or anomalous diffusion (e.g. diffusion in porous media), active transport, and combinations thereof were described by several authors. To distinguish between these types of particle movement we developed an appropriate classification method, and simulated three types of particle motion in a 2D plane using a Monte Carlo approach: (1) normal diffusion, using random direction and step-length, (2) subdiffusion, using confinements like a reflective boundary with defined radius or reflective objects in the closer vicinity, and (3) superdiffusion, using a directed flow added to the normal diffusion. To simulate subdiffusion we devised a new method based on tracks of different length combined with equally probable obstacle interaction. Next we estimated the fractal dimension, elongation and the ratio of long-time / short-time diffusion coefficients. These features were used to train a random forests classification algorithm. The accuracy for simulated trajectories with 180 steps was 97% (95%-CI: 0.9481-0.9884). The balanced accuracy was 94%, 99% and 98% for normal-, sub- and superdiffusion, respectively. Nanoparticle tracking analysis was used with 100 nm polystyrene particles to get trajectories for normal diffusion. As a next step we identified diffusion types of nanoparticles in vital cells and incubated V79 fibroblasts with 50 nm gold nanoparticles, which appeared as intensely bright objects due to their surface plasmon resonance. The movement of particles in both the extracellular and intracellular space was observed by dark field and confocal laser scanning microscopy. After reducing background noise from the video it became possible to identify individual particle spots by a maximum detection algorithm and trace them using the robust single-particle tracking algorithm proposed by Jaqaman, which is able to handle motion heterogeneity and particle disappearance. The particle trajectories inside cells indicated active transport (superdiffusion) as well as subdiffusion. Eventually, the random forest classification algorithm, after being trained by the above simulations, successfully classified the trajectories observed in live cells.
ANALYTiC: An Active Learning System for Trajectory Classification.
Soares Junior, Amilcar; Renso, Chiara; Matwin, Stan
2017-01-01
The increasing availability and use of positioning devices has resulted in large volumes of trajectory data. However, semantic annotations for such data are typically added by domain experts, which is a time-consuming task. Machine-learning algorithms can help infer semantic annotations from trajectory data by learning from sets of labeled data. Specifically, active learning approaches can minimize the set of trajectories to be annotated while preserving good performance measures. The ANALYTiC web-based interactive tool visually guides users through this annotation process.
NASA Astrophysics Data System (ADS)
Vitali, Lina; Righini, Gaia; Piersanti, Antonio; Cremona, Giuseppe; Pace, Giandomenico; Ciancarella, Luisella
2017-12-01
Air backward trajectory calculations are commonly used in a variety of atmospheric analyses, in particular for source attribution evaluation. The accuracy of backward trajectory analysis is mainly determined by the quality and the spatial and temporal resolution of the underlying meteorological data set, especially in the cases of complex terrain. This work describes a new tool for the calculation and the statistical elaboration of backward trajectories. To take advantage of the high-resolution meteorological database of the Italian national air quality model MINNI, a dedicated set of procedures was implemented under the name of M-TraCE (MINNI module for Trajectories Calculation and statistical Elaboration) to calculate and process the backward trajectories of air masses reaching a site of interest. Some outcomes from the application of the developed methodology to the Italian Network of Special Purpose Monitoring Stations are shown to assess its strengths for the meteorological characterization of air quality monitoring stations. M-TraCE has demonstrated its capabilities to provide a detailed statistical assessment of transport patterns and region of influence of the site under investigation, which is fundamental for correctly interpreting pollutants measurements and ascertaining the official classification of the monitoring site based on meta-data information. Moreover, M-TraCE has shown its usefulness in supporting other assessments, i.e., spatial representativeness of a monitoring site, focussing specifically on the analysis of the effects due to meteorological variables.
Bullet trajectory predicts the need for damage control: an artificial neural network model.
Hirshberg, Asher; Wall, Matthew J; Mattox, Kenneth L
2002-05-01
Effective use of damage control in trauma hinges on an early decision to use it. Bullet trajectory has never been studied as a marker for damage control. We hypothesize that this decision can be predicted by an artificial neural network (ANN) model based on the bullet trajectory and the patient's blood pressure. A multilayer perceptron ANN predictive model was developed from a data set of 312 patients with single abdominal gunshot injuries. Input variables were the bullet path, trajectory patterns, and admission systolic pressure. The output variable was either a damage control laparotomy or intraoperative death. The best performing ANN was implemented on prospectively collected data from 34 patients. The model achieved a correct classification rate of 0.96 and area under the receiver operating characteristic curve of 0.94. External validation showed the model to have a sensitivity of 88% and specificity of 96%. Model implementation on the prospectively collected data had a correct classification rate of 0.91. Sensitivity analysis showed that systolic pressure, bullet path across the midline, and trajectory involving the right upper quadrant were the three most important input variables. Bullet trajectory is an important, hitherto unrecognized, factor that should be incorporated into the decision to use damage control.
A Review on Human Activity Recognition Using Vision-Based Method.
Zhang, Shugang; Wei, Zhiqiang; Nie, Jie; Huang, Lei; Wang, Shuang; Li, Zhen
2017-01-01
Human activity recognition (HAR) aims to recognize activities from a series of observations on the actions of subjects and the environmental conditions. The vision-based HAR research is the basis of many applications including video surveillance, health care, and human-computer interaction (HCI). This review highlights the advances of state-of-the-art activity recognition approaches, especially for the activity representation and classification methods. For the representation methods, we sort out a chronological research trajectory from global representations to local representations, and recent depth-based representations. For the classification methods, we conform to the categorization of template-based methods, discriminative models, and generative models and review several prevalent methods. Next, representative and available datasets are introduced. Aiming to provide an overview of those methods and a convenient way of comparing them, we classify existing literatures with a detailed taxonomy including representation and classification methods, as well as the datasets they used. Finally, we investigate the directions for future research.
A Review on Human Activity Recognition Using Vision-Based Method
Nie, Jie
2017-01-01
Human activity recognition (HAR) aims to recognize activities from a series of observations on the actions of subjects and the environmental conditions. The vision-based HAR research is the basis of many applications including video surveillance, health care, and human-computer interaction (HCI). This review highlights the advances of state-of-the-art activity recognition approaches, especially for the activity representation and classification methods. For the representation methods, we sort out a chronological research trajectory from global representations to local representations, and recent depth-based representations. For the classification methods, we conform to the categorization of template-based methods, discriminative models, and generative models and review several prevalent methods. Next, representative and available datasets are introduced. Aiming to provide an overview of those methods and a convenient way of comparing them, we classify existing literatures with a detailed taxonomy including representation and classification methods, as well as the datasets they used. Finally, we investigate the directions for future research. PMID:29065585
NASA Astrophysics Data System (ADS)
Nguyen, Hoang Hai; Tran, Hien; Sunwoo, Wooyeon; Yi, Jong-hyuk; Kim, Dongkyun; Choi, Minha
2017-04-01
A series of multispectral high-resolution Korean Multi-Purpose Satellite (KOMPSAT) images was used to detect the geographical changes in four different tidal flats between the Yellow Sea and the west coast of South Korea. The method of unsupervised classification was used to generate a series of land use/land cover (LULC) maps from satellite images, which were then used as input for temporal trajectory analysis to detect the temporal change of coastal wetlands and its association with natural and anthropogenic activities. The accurately classified LULC maps of KOMPSAT images, with overall accuracy ranging from 83.34% to 95.43%, indicate that these multispectral high-resolution satellite data are highly applicable to the generation of high-quality thematic maps for extracting wetlands. The result of the trajectory analysis showed that, while the variation of the tidal flats in the Gyeonggi and Jeollabuk provinces was well correlated with the regular tidal regimes, the reductive trajectory of the wetland areas belonging to the Saemangeum province was caused by a high degree of human-induced activities including large reclamation and urbanization. The conservation of the Jeungdo Wetland Protected Area in the Jeollanam province revealed that effective social and environmental policies could help in protecting coastal wetlands from degradation.
Intrapartum fetal heart rate classification from trajectory in Sparse SVM feature space.
Spilka, J; Frecon, J; Leonarduzzi, R; Pustelnik, N; Abry, P; Doret, M
2015-01-01
Intrapartum fetal heart rate (FHR) constitutes a prominent source of information for the assessment of fetal reactions to stress events during delivery. Yet, early detection of fetal acidosis remains a challenging signal processing task. The originality of the present contribution are three-fold: multiscale representations and wavelet leader based multifractal analysis are used to quantify FHR variability ; Supervised classification is achieved by means of Sparse-SVM that aim jointly to achieve optimal detection performance and to select relevant features in a multivariate setting ; Trajectories in the feature space accounting for the evolution along time of features while labor progresses are involved in the construction of indices quantifying fetal health. The classification performance permitted by this combination of tools are quantified on a intrapartum FHR large database (≃ 1250 subjects) collected at a French academic public hospital.
Latent Class Analysis of Early Developmental Trajectory in Baby Siblings of Children with Autism
ERIC Educational Resources Information Center
Landa, Rebecca J.; Gross, Alden L.; Stuart, Elizabeth A.; Bauman, Margaret
2012-01-01
Background: Siblings of children with autism (sibs-A) are at increased genetic risk for autism spectrum disorders (ASD) and milder impairments. To elucidate diversity and contour of early developmental trajectories exhibited by sibs-A, regardless of diagnostic classification, latent class modeling was used. Methods: Sibs-A (N = 204) were assessed…
Salvador-Carulla, Luis; Bertelli, Marco; Martinez-Leal, Rafael
2018-03-01
To increase the expert knowledge-base on intellectual developmental disorders (IDDs) by investigating the typology trajectories of consensus formation in the classification systems up to the 11th edition of the International Classification of Diseases (ICD-11). This expert review combines an analysis of key recent literature and the revision of the consensus formation and contestation in the expert committees contributing to the classification systems since the 1950s. Historically two main approaches have contributed to the development of this knowledge-base: a neurodevelopmental-clinical approach and a psychoeducational-social approach. These approaches show a complex interaction throughout the history of IDD and have had a diverse influence on its classification. Although in theory Diagnostic and Statistical Manual (DSM)-5 and ICD adhere to the neurodevelopmental-clinical model, the new definition in the ICD-11 follows a restrictive normality approach to intellectual quotient and to the measurement of adaptive behaviour. On the contrary DSM-5 is closer to the recommendations made by the WHO 'Working Group on Mental Retardation' for ICD-11 for an integrative approach. A cyclical pattern of consensus formation has been identified in IDD. The revision of the three major classification systems in the last decade has increased the terminological and conceptual variability and the overall scientific contestation on IDD.
Fractal measures of video-recorded trajectories can classify motor subtypes in Parkinson's Disease
NASA Astrophysics Data System (ADS)
Figueiredo, Thiago C.; Vivas, Jamile; Peña, Norberto; Miranda, José G. V.
2016-11-01
Parkinson's Disease is one of the most prevalent neurodegenerative diseases in the world and affects millions of individuals worldwide. The clinical criteria for classification of motor subtypes in Parkinson's Disease are subjective and may be misleading when symptoms are not clearly identifiable. A video recording protocol was used to measure hand tremor of 14 individuals with Parkinson's Disease and 7 healthy subjects. A method for motor subtype classification was proposed based on the spectral distribution of the movement and compared with the existing clinical criteria. Box-counting dimension and Hurst Exponent calculated from the trajectories were used as the relevant measures for the statistical tests. The classification based on the power-spectrum is shown to be well suited to separate patients with and without tremor from healthy subjects and could provide clinicians with a tool to aid in the diagnosis of patients in an early stage of the disease.
BOREAS TE-18 Landsat TM Physical Classification Image of the NSA
NASA Technical Reports Server (NTRS)
Hall, Forrest G. (Editor); Knapp, David
2000-01-01
The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the NSA. A Landsat-5 TM image from 21-Jun-1995 was used to derive the classification. A technique was implemented that uses reflectances of various land cover types along with a geometric optical canopy model to produce spectral trajectories. These trajectories are used in a way that is similar to training data to classify the image into the different land cover classes. The data are provided in a binary, image file format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).
BOREAS TE-18 Landsat TM Physical Classification Image of the SSA
NASA Technical Reports Server (NTRS)
Hall, Forrest G. (Editor); Knapp, David
2000-01-01
The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the SSA. A Landsat-5 TM image from 02-Sep-1994 was used to derive the classification. A technique was implemented that uses reflectances of various land cover types along with a geometric optical canopy model to produce spectral trajectories. These trajectories are used as training data to classify the image into the different land cover classes. These data are provided in a binary image file format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).
BOREAS TE-18 Landsat TM Maximum Likelihood Classification Image of the SSA
NASA Technical Reports Server (NTRS)
Hall, Forrest G. (Editor); Knapp, David
2000-01-01
The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the SSA. A Landsat-5 TM image from 02-Sep- 1994 was used to derive the classification. A technique was implemented that uses reflectances of various land cover types along with a geometric optical canopy model to produce spectral trajectories. These trajectories are used as training data to classify the image into the different land cover classes. These data are provided in a binary image file format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Center (DAAC).
Shot trajectory parameters in gold medal stationary shot-putters during world-class competition.
Frossard, Laurent; Smeathers, James; O'Riordan, Alison; Goodman, Scott
2007-10-01
The parameters of the shot's trajectory were reported for male and female gold medalists (classes F52, F53, F54, and F55) who competed at the 2000 Paralympic Games and the 2002 International Paralympic Committee (IPC) World Championships. The specific objective was to determine the magnitude of differences in these parameters across classes and genders. The release velocity of the shot increased with the performance and the classification for both males (8.30 m/s - 9.96 m/s) and females (4.58 m/s - 8.50 m/s). The measured angle of the shot's trajectory at release also increased with the performance and the classification for both males (27.54 degrees - 32.47 degrees) and females (9.02 degrees - 34.52 degrees). The position of the shot from a fixed reference point at release revealed a similar trend for both males (2.01 m - 2.68 m) and females (1.16 m - 1.98 m), although it was weaker.
Gehring, Tiago V.; Luksys, Gediminas; Sandi, Carmen; Vasilaki, Eleni
2015-01-01
The Morris Water Maze is a widely used task in studies of spatial learning with rodents. Classical performance measures of animals in the Morris Water Maze include the escape latency, and the cumulative distance to the platform. Other methods focus on classifying trajectory patterns to stereotypical classes representing different animal strategies. However, these approaches typically consider trajectories as a whole, and as a consequence they assign one full trajectory to one class, whereas animals often switch between these strategies, and their corresponding classes, within a single trial. To this end, we take a different approach: we look for segments of diverse animal behaviour within one trial and employ a semi-automated classification method for identifying the various strategies exhibited by the animals within a trial. Our method allows us to reveal significant and systematic differences in the exploration strategies of two animal groups (stressed, non-stressed), that would be unobserved by earlier methods. PMID:26423140
Trajectories of Mexican American and Mainstream Cultural Values Among Mexican American Adolescents
Knight, George P.; Basilio, Camille D.; Cham, Heining; Gonzales, Nancy A.; Liu, Yu; Umaña-Taylor, Adriana J.
2013-01-01
Mexican Americans are one of the largest and fastest growing ethnic groups in the United States, yet we have limited knowledge regarding changes (i.e., developmental trajectories) in cultural orientation based upon their exposure to the Mexican American and mainstream cultures. We examined the parallel trajectories of Mexican American and mainstream cultural values in a sample of 749 Mexican American adolescents (49% female) across assessments during the fifth grade (approximately 11 years of age), the seventh grade (approximately 13 years of age) and the tenth grade (approximately 16 years of age). We expected that these values would change over this developmental period and this longitudinal approach is more appropriate than the often used median split classification to identify distinct types of acculturation. We found four distinct acculturation trajectory groups: two trajectory groups that were increasing slightly with age in the endorsement of mainstream cultural values, one of which was relatively stable in Mexican American cultural values while the other was declining in their endorsement of these values; and two trajectory groups that were declining substantially with age in their endorsement of mainstream cultural values, one of which was also declining in Mexican American cultural values and the other which was stable in these values. These four trajectory groups differed in expected ways on a number of theoretically related cultural variables, but were not highly consistent with the median split classifications. The findings highlight the need to utilize longitudinal data to examine the developmental changes of Mexican American individual’s adaptation to the ethnic and mainstream culture in order to understand more fully the processes of acculturation and enculturation. PMID:23877194
Trajectories of Mexican American and mainstream cultural values among Mexican American adolescents.
Knight, George P; Basilio, Camille D; Cham, Heining; Gonzales, Nancy A; Liu, Yu; Umaña-Taylor, Adriana J
2014-12-01
Mexican Americans are one of the largest and fastest growing ethnic groups in the United States, yet we have limited knowledge regarding changes (i.e., developmental trajectories) in cultural orientation based upon their exposure to the Mexican American and mainstream cultures. We examined the parallel trajectories of Mexican American and mainstream cultural values in a sample of 749 Mexican American adolescents (49 % female) across assessments during the fifth grade (approximately 11 years of age), the seventh grade (approximately 13 years of age) and the tenth grade (approximately 16 years of age). We expected that these values would change over this developmental period and this longitudinal approach is more appropriate than the often used median split classification to identify distinct types of acculturation. We found four distinct acculturation trajectory groups: two trajectory groups that were increasing slightly with age in the endorsement of mainstream cultural values, one of which was relatively stable in Mexican American cultural values while the other was declining in their endorsement of these values; and two trajectory groups that were declining substantially with age in their endorsement of mainstream cultural values, one of which was also declining in Mexican American cultural values and the other which was stable in these values. These four trajectory groups differed in expected ways on a number of theoretically related cultural variables, but were not highly consistent with the median split classifications. The findings highlight the need to utilize longitudinal data to examine the developmental changes of Mexican American individual's adaptation to the ethnic and mainstream culture in order to understand more fully the processes of acculturation and enculturation.
On Integral Invariants for Effective 3-D Motion Trajectory Matching and Recognition.
Shao, Zhanpeng; Li, Youfu
2016-02-01
Motion trajectories tracked from the motions of human, robots, and moving objects can provide an important clue for motion analysis, classification, and recognition. This paper defines some new integral invariants for a 3-D motion trajectory. Based on two typical kernel functions, we design two integral invariants, the distance and area integral invariants. The area integral invariants are estimated based on the blurred segment of noisy discrete curve to avoid the computation of high-order derivatives. Such integral invariants for a motion trajectory enjoy some desirable properties, such as computational locality, uniqueness of representation, and noise insensitivity. Moreover, our formulation allows the analysis of motion trajectories at a range of scales by varying the scale of kernel function. The features of motion trajectories can thus be perceived at multiscale levels in a coarse-to-fine manner. Finally, we define a distance function to measure the trajectory similarity to find similar trajectories. Through the experiments, we examine the robustness and effectiveness of the proposed integral invariants and find that they can capture the motion cues in trajectory matching and sign recognition satisfactorily.
NASA Astrophysics Data System (ADS)
Piras, Paolo; Torromeo, Concetta; Re, Federica; Evangelista, Antonietta; Gabriele, Stefano; Esposito, Giuseppe; Nardinocchi, Paola; Teresi, Luciano; Madeo, Andrea; Chialastri, Claudia; Schiariti, Michele; Varano, Valerio; Uguccioni, Massimo; Puddu, Paolo E.
2016-10-01
The analysis of full Left Atrium (LA) deformation and whole LA deformational trajectory in time has been poorly investigated and, to the best of our knowledge, seldom discussed in patients with Hypertrophic Cardiomyopathy. Therefore, we considered 22 patients with Hypertrophic Cardiomyopathy (HCM) and 46 healthy subjects, investigated them by three-dimensional Speckle Tracking Echocardiography, and studied the derived landmark clouds via Geometric Morphometrics with Parallel Transport. Trajectory shape and trajectory size were different in Controls versus HCM and their classification powers had high AUC (Area Under the Receiving Operator Characteristic Curve) and accuracy. The two trajectories were much different at the transition between LA conduit and booster pump functions. Full shape and deformation analyses with trajectory analysis enabled a straightforward perception of pathophysiological consequences of HCM condition on LA functioning. It might be worthwhile to apply these techniques to look for novel pathophysiological approaches that may better define atrio-ventricular interaction.
Space Object Classification Using Fused Features of Time Series Data
NASA Astrophysics Data System (ADS)
Jia, B.; Pham, K. D.; Blasch, E.; Shen, D.; Wang, Z.; Chen, G.
In this paper, a fused feature vector consisting of raw time series and texture feature information is proposed for space object classification. The time series data includes historical orbit trajectories and asteroid light curves. The texture feature is derived from recurrence plots using Gabor filters for both unsupervised learning and supervised learning algorithms. The simulation results show that the classification algorithms using the fused feature vector achieve better performance than those using raw time series or texture features only.
Zipf exponent of trajectory distribution in the hidden Markov model
NASA Astrophysics Data System (ADS)
Bochkarev, V. V.; Lerner, E. Yu
2014-03-01
This paper is the first step of generalization of the previously obtained full classification of the asymptotic behavior of the probability for Markov chain trajectories for the case of hidden Markov models. The main goal is to study the power (Zipf) and nonpower asymptotics of the frequency list of trajectories of hidden Markov frequencys and to obtain explicit formulae for the exponent of the power asymptotics. We consider several simple classes of hidden Markov models. We prove that the asymptotics for a hidden Markov model and for the corresponding Markov chain can be essentially different.
Stop! border ahead: Automatic detection of subthalamic exit during deep brain stimulation surgery.
Valsky, Dan; Marmor-Levin, Odeya; Deffains, Marc; Eitan, Renana; Blackwell, Kim T; Bergman, Hagai; Israel, Zvi
2017-01-01
Microelectrode recordings along preplanned trajectories are often used for accurate definition of the subthalamic nucleus (STN) borders during deep brain stimulation (DBS) surgery for Parkinson's disease. Usually, the demarcation of the STN borders is performed manually by a neurophysiologist. The exact detection of the borders is difficult, especially detecting the transition between the STN and the substantia nigra pars reticulata. Consequently, demarcation may be inaccurate, leading to suboptimal location of the DBS lead and inadequate clinical outcomes. We present machine-learning classification procedures that use microelectrode recording power spectra and allow for real-time, high-accuracy discrimination between the STN and substantia nigra pars reticulata. A support vector machine procedure was tested on microelectrode recordings from 58 trajectories that included both STN and substantia nigra pars reticulata that achieved a 97.6% consistency with human expert classification (evaluated by 10-fold cross-validation). We used the same data set as a training set to find the optimal parameters for a hidden Markov model using both microelectrode recording features and trajectory history to enable real-time classification of the ventral STN border (STN exit). Seventy-three additional trajectories were used to test the reliability of the learned statistical model in identifying the exit from the STN. The hidden Markov model procedure identified the STN exit with an error of 0.04 ± 0.18 mm and detection reliability (error < 1 mm) of 94%. The results indicate that robust, accurate, and automatic real-time electrophysiological detection of the ventral STN border is feasible. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.
Latent Class Analysis of Early Developmental Trajectory in Baby Siblings of Children with Autism
Landa, Rebecca J.; Gross, Alden L.; Stuart, Elizabeth A.; Bauman, Margaret
2012-01-01
Background Siblings of children with autism (sibs-A) are at increased genetic risk for autism spectrum disorders (ASD) and milder impairments. To elucidate diversity and contour of early developmental trajectories exhibited by sibs-A, regardless of diagnostic classification, latent class modeling was used. Methods Sibs-A (n=204) were assessed with the Mullen Scales of Early Learning from age 6–36 months. Mullen T scores served as dependent variables. Outcome classifications at age 36 months included: ASD (n=52); non-ASD social/communication delay (broader autism phenotype; BAP) (n=31); and unaffected (n=121). Child-specific patterns of performance were studied using latent class growth analysis. Latent class membership was then related to diagnostic outcome through estimation of within-class proportions of children assigned to each diagnostic classification. Results A 4-class model was favored. Class 1 represented accelerated development and consisted of 25.7% of the sample, primarily unaffected children. Class 2 (40.0% of the sample), was characterized by normative development with above-average nonverbal cognitive outcome. Class 3 (22.3% of the sample) was characterized by receptive language, and gross and fine motor delay. Class 4 (12.0% of the sample), was characterized by widespread delayed skill acquisition, reflected by declining trajectories. Children with an outcome diagnosis of ASD were spread across Classes 2, 3, and 4. Conclusions Results support a category of ASD that involves slowing in early non-social development. Receptive language and motor development is vulnerable to early delay in sibs-A with and without ASD outcomes. Non-ASD sibs-A are largely distributed across classes depicting average or accelerated development. Developmental trajectories of motor, language, and cognition appear independent of communication and social delays in non-ASD sibs-A. PMID:22574686
Gillham, Michael; Howells, Gareth; Spurgeon, Sarah; McElroy, Ben
2013-01-01
Assistive robotic applications require systems capable of interaction in the human world, a workspace which is highly dynamic and not always predictable. Mobile assistive devices face the additional and complex problem of when and if intervention should occur; therefore before any trajectory assistance is given, the robotic device must know where it is in real-time, without unnecessary disruption or delay to the user requirements. In this paper, we demonstrate a novel robust method for determining room identification from floor features in a real-time computational frame for autonomous and assistive robotics in the human environment. We utilize two inexpensive sensors: an optical mouse sensor for straightforward and rapid, texture or pattern sampling, and a four color photodiode light sensor for fast color determination. We show how data relating floor texture and color obtained from typical dynamic human environments, using these two sensors, compares favorably with data obtained from a standard webcam. We show that suitable data can be extracted from these two sensors at a rate 16 times faster than a standard webcam, and that these data are in a form which can be rapidly processed using readily available classification techniques, suitable for real-time system application. We achieved a 95% correct classification accuracy identifying 133 rooms' flooring from 35 classes, suitable for fast coarse global room localization application, boundary crossing detection, and additionally some degree of surface type identification. PMID:24351647
Gillham, Michael; Howells, Gareth; Spurgeon, Sarah; McElroy, Ben
2013-12-17
Assistive robotic applications require systems capable of interaction in the human world, a workspace which is highly dynamic and not always predictable. Mobile assistive devices face the additional and complex problem of when and if intervention should occur; therefore before any trajectory assistance is given, the robotic device must know where it is in real-time, without unnecessary disruption or delay to the user requirements. In this paper, we demonstrate a novel robust method for determining room identification from floor features in a real-time computational frame for autonomous and assistive robotics in the human environment. We utilize two inexpensive sensors: an optical mouse sensor for straightforward and rapid, texture or pattern sampling, and a four color photodiode light sensor for fast color determination. We show how data relating floor texture and color obtained from typical dynamic human environments, using these two sensors, compares favorably with data obtained from a standard webcam. We show that suitable data can be extracted from these two sensors at a rate 16 times faster than a standard webcam, and that these data are in a form which can be rapidly processed using readily available classification techniques, suitable for real-time system application. We achieved a 95% correct classification accuracy identifying 133 rooms' flooring from 35 classes, suitable for fast coarse global room localization application, boundary crossing detection, and additionally some degree of surface type identification.
You Can't Think and Hit at the Same Time: Neural Correlates of Baseball Pitch Classification.
Sherwin, Jason; Muraskin, Jordan; Sajda, Paul
2012-01-01
Hitting a baseball is often described as the most difficult thing to do in sports. A key aptitude of a good hitter is the ability to determine which pitch is coming. This rapid decision requires the batter to make a judgment in a fraction of a second based largely on the trajectory and spin of the ball. When does this decision occur relative to the ball's trajectory and is it possible to identify neural correlates that represent how the decision evolves over a split second? Using single-trial analysis of electroencephalography (EEG) we address this question within the context of subjects discriminating three types of pitches (fastball, curveball, slider) based on pitch trajectories. We find clear neural signatures of pitch classification and, using signal detection theory, we identify the times of discrimination on a trial-to-trial basis. Based on these neural signatures we estimate neural discrimination distributions as a function of the distance the ball is from the plate. We find all three pitches yield unique distributions, namely the timing of the discriminating neural signatures relative to the position of the ball in its trajectory. For instance, fastballs are discriminated at the earliest points in their trajectory, relative to the two other pitches, which is consistent with the need for some constant time to generate and execute the motor plan for the swing (or inhibition of the swing). We also find incorrect discrimination of a pitch (errors) yields neural sources in Brodmann Area 10, which has been implicated in prospective memory, recall, and task difficulty. In summary, we show that single-trial analysis of EEG yields informative distributions of the relative point in a baseball's trajectory when the batter makes a decision on which pitch is coming.
Shaffer, Franklin D.
2013-03-12
The application relates to particle trajectory recognition from a Centroid Population comprised of Centroids having an (x, y, t) or (x, y, f) coordinate. The method is applicable to visualization and measurement of particle flow fields of high particle. In one embodiment, the centroids are generated from particle images recorded on camera frames. The application encompasses digital computer systems and distribution mediums implementing the method disclosed and is particularly applicable to recognizing trajectories of particles in particle flows of high particle concentration. The method accomplishes trajectory recognition by forming Candidate Trajectory Trees and repeated searches at varying Search Velocities, such that initial search areas are set to a minimum size in order to recognize only the slowest, least accelerating particles which produce higher local concentrations. When a trajectory is recognized, the centroids in that trajectory are removed from consideration in future searches.
Convolutional Neural Network-Based Robot Navigation Using Uncalibrated Spherical Images.
Ran, Lingyan; Zhang, Yanning; Zhang, Qilin; Yang, Tao
2017-06-12
Vision-based mobile robot navigation is a vibrant area of research with numerous algorithms having been developed, the vast majority of which either belong to the scene-oriented simultaneous localization and mapping (SLAM) or fall into the category of robot-oriented lane-detection/trajectory tracking. These methods suffer from high computational cost and require stringent labelling and calibration efforts. To address these challenges, this paper proposes a lightweight robot navigation framework based purely on uncalibrated spherical images. To simplify the orientation estimation, path prediction and improve computational efficiency, the navigation problem is decomposed into a series of classification tasks. To mitigate the adverse effects of insufficient negative samples in the "navigation via classification" task, we introduce the spherical camera for scene capturing, which enables 360° fisheye panorama as training samples and generation of sufficient positive and negative heading directions. The classification is implemented as an end-to-end Convolutional Neural Network (CNN), trained on our proposed Spherical-Navi image dataset, whose category labels can be efficiently collected. This CNN is capable of predicting potential path directions with high confidence levels based on a single, uncalibrated spherical image. Experimental results demonstrate that the proposed framework outperforms competing ones in realistic applications.
Soleymani, Ali; Pennekamp, Frank; Petchey, Owen L.; Weibel, Robert
2015-01-01
Recent advances in tracking technologies such as GPS or video tracking systems describe the movement paths of individuals in unprecedented details and are increasingly used in different fields, including ecology. However, extracting information from raw movement data requires advanced analysis techniques, for instance to infer behaviors expressed during a certain period of the recorded trajectory, or gender or species identity in case data is obtained from remote tracking. In this paper, we address how different movement features affect the ability to automatically classify the species identity, using a dataset of unicellular microbes (i.e., ciliates). Previously, morphological attributes and simple movement metrics, such as speed, were used for classifying ciliate species. Here, we demonstrate that adding advanced movement features, in particular such based on discrete wavelet transform, to morphological features can improve classification. These results may have practical applications in automated monitoring of waste water facilities as well as environmental monitoring of aquatic systems. PMID:26680591
NASA Technical Reports Server (NTRS)
Koczo, Stefan, Jr.
2013-01-01
Safety analyses of the Traffic Aware Strategic Aircrew Requests (TASAR) Electronic Flight Bag (EFB) application are provided to establish its Failure Effects Classification which affects certification and operational approval requirements. TASAR was developed by NASA Langley Research Center to offer flight path improvement opportunities to the pilot during flight for operational benefits (e.g., reduced fuel, flight time). TASAR, using own-ship and network-enabled information concerning the flight and its environment, including weather and Air Traffic Control (ATC) system constraints, provides recommended improvements to the flight trajectory that the pilot can choose to request via Change Requests to ATC for revised clearance. This study reviews the Change Request process of requesting updates to the current clearance, examines the intended function of TASAR, and utilizes two safety assessment methods to establish the Failure Effects Classification of TASAR. Considerable attention has been given in this report to the identification of operational hazards potentially associated with TASAR.
Trajectory Based Behavior Analysis for User Verification
NASA Astrophysics Data System (ADS)
Pao, Hsing-Kuo; Lin, Hong-Yi; Chen, Kuan-Ta; Fadlil, Junaidillah
Many of our activities on computer need a verification step for authorized access. The goal of verification is to tell apart the true account owner from intruders. We propose a general approach for user verification based on user trajectory inputs. The approach is labor-free for users and is likely to avoid the possible copy or simulation from other non-authorized users or even automatic programs like bots. Our study focuses on finding the hidden patterns embedded in the trajectories produced by account users. We employ a Markov chain model with Gaussian distribution in its transitions to describe the behavior in the trajectory. To distinguish between two trajectories, we propose a novel dissimilarity measure combined with a manifold learnt tuning for catching the pairwise relationship. Based on the pairwise relationship, we plug-in any effective classification or clustering methods for the detection of unauthorized access. The method can also be applied for the task of recognition, predicting the trajectory type without pre-defined identity. Given a trajectory input, the results show that the proposed method can accurately verify the user identity, or suggest whom owns the trajectory if the input identity is not provided.
Human Classification Based on Gestural Motions by Using Components of PCA
NASA Astrophysics Data System (ADS)
Aziz, Azri A.; Wan, Khairunizam; Za'aba, S. K.; B, Shahriman A.; Adnan, Nazrul H.; H, Asyekin; R, Zuradzman M.
2013-12-01
Lately, a study of human capabilities with the aim to be integrated into machine is the famous topic to be discussed. Moreover, human are bless with special abilities that they can hear, see, sense, speak, think and understand each other. Giving such abilities to machine for improvement of human life is researcher's aim for better quality of life in the future. This research was concentrating on human gesture, specifically arm motions for differencing the individuality which lead to the development of the hand gesture database. We try to differentiate the human physical characteristic based on hand gesture represented by arm trajectories. Subjects are selected from different type of the body sizes, and then acquired data undergo resampling process. The results discuss the classification of human based on arm trajectories by using Principle Component Analysis (PCA).
Novel optical-based methods and analyses for elucidating cellular mechanics and dynamics
NASA Astrophysics Data System (ADS)
Koo, Peter K.
Resolving distinct biochemical interaction states by analyzing the diffusive behaviors of individual protein trajectories is challenging due to the limited statistics provided by short trajectories and experimental noise sources, which are intimately coupled into each proteins localization. In the first part of this thesis, we introduce a novel, a machine-learning based classification methodology, called perturbation expectation-maximization (pEM), which simultaneously analyzes a population of protein trajectories to uncover the system of short-time diffusive behaviors which collectively result from distinct biochemical interactions. We then discuss an experimental application of pEM to Rho GTPase, an integral regulator of cytoskeletal dynamics and cellular homeostasis, inside live cells. We also derive the maximum likelihood estimator (MLE) for driven diffusion, confined diffusion, and fractional Brownian motion. We demonstrate that MLE yields improved estimates in comparison with traditional diffusion analysis, namely mean squared displacement analysis. In addition, we also introduce mleBayes, which is an empirical Bayesian model selection scheme to classify an individual protein trajectory to a given diffusion mode. By employing mleBayes on simulated data, we demonstrate that accurate determination of the underlying diffusive properties, beyond normal diffusion, remains challenging when analyzing particle trajectories on an individual basis. To improve upon the statistical limitations of classification from analyzing trajectories on an individual basis, we extend pEM with a new version (pEMv2) to simultaneously analyzing a collection of particle trajectories to uncover the system of interactions which give rise to unique normal or non-normal diffusive states. We test the performance of pEMv2 on various sets of simulated particle trajectories which transition between various modes of normal and non-normal diffusive states to highlight considerations when employing pEMv2 analysis. We envision the presented methodologies will be applicable to a wide range of single protein tracking data where different interactions result in distinct diffusive behaviors. More generally, this study brings us an important step closer to the possibility of monitoring the endogenous biochemistry of diffusing proteins within live cells with single molecule resolution. In the second part of this thesis, the role of chromatin association to the nuclear envelope in nuclear mechanics is explored. Changes in the mechanical properties of the nucleus are increasingly found to be critical for development and disease. However, relatively little is known about the variables that cells modulate to define nuclear mechanics. The best understood player is lamin A, a protein linked to a diverse set of genetic diseases termed laminopathies. The properties of lamin A that are compromised in these diseases (and therefore underlie their pathology) remains poorly understood. One model focuses on a mechanical role for a polymeric network of lamins associated with the nuclear envelope (NE), which supports nuclear integrity. However, because heterochromatin is strongly associated with lamina, it remains unclear whether it is the lamin polymer, the associated chromatin, or both that allow the lamina to mechanically stabilize nuclei. Decoupling the impact of the lamin polymer itself from that of the associated chromatin has proven very challenging. Here, we take advantage of the model organism, S pombe, which does not express lamies, as an experimental framework in which to address the impact of chromatin and its association with the nuclear periphery on nuclear mechanics. Using a combination of new image analysis tools for in vivo imaging of nuclear dynamics and a novel optical tweezers assay capable of directly probing nuclear mechanics, we find that the association of chromatin with the NE through integral membrane proteins plays a critical role in supporting nuclear integrity. When chromatin is decoupled from the NE, nuclei are softer, undergo much larger nuclear fluctuations in vivo in response to microtubule forces, and are defective at resolving nuclear deformations. Our data further suggest that association of chromatin with the NE attenuates the flow of chromatin into nuclear fluctuations thereby preventing permanent changes in nuclear shape.
Iravani, B; Towhidkhah, F; Roghani, M
2014-12-01
Parkinson Disease (PD) is one of the most common neural disorders worldwide. Different treatments such as medication and deep brain stimulation (DBS) have been proposed to minimize and control Parkinson's symptoms. DBS has been recognized as an effective approach to decrease most movement disorders of PD. In this study, a new method is proposed for feature extraction and separation of treated and untreated Parkinsonan rats. For this purpose, unilateral intrastriatal 6-hydroxydopamine (6-OHDA, 12.5 μg/5 μl of saline-ascorbate)-lesioned rats were treated with DBS. We performed a behavioral experiment and video tracked traveled trajectories of rats. Then, we investigated the effect of deep brain stimulation of subthalamus nucleus on their behavioral movements. Time, frequency and chaotic features of traveled trajectories were extracted. These features provide the ability to quantify the behavioral movements of Parkinsonian rats. The results showed that the traveled trajectories of untreated were more convoluted with the different time/frequency response. Compared to the traditional features used before to quantify the animals' behavior, the new features improved classification accuracy up to 80 % for untreated and treated rats.
An Efficient Universal Trajectory Language
NASA Technical Reports Server (NTRS)
Hagen, George E.; Guerreiro, Nelson M.; Maddalon, Jeffrey M.; Butler, Ricky W.
2017-01-01
The Efficient Universal Trajectory Language (EUTL) is a language for specifying and representing trajectories for Air Traffic Management (ATM) concepts such as Trajectory-Based Operations (TBO). In these concepts, the communication of a trajectory between an aircraft and ground automation is fundamental. Historically, this trajectory exchange has not been done, leading to trajectory definitions that have been centered around particular application domains and, therefore, are not well suited for TBO applications. The EUTL trajectory language has been defined in the Prototype Verification System (PVS) formal specification language, which provides an operational semantics for the EUTL language. The hope is that EUTL will provide a foundation for mathematically verified algorithms that manipulate trajectories. Additionally, the EUTL language provides well-defined methods to unambiguously determine position and velocity information between the reported trajectory points. In this paper, we present the EUTL trajectory language in mathematical detail.
Latent class analysis of early developmental trajectory in baby siblings of children with autism.
Landa, Rebecca J; Gross, Alden L; Stuart, Elizabeth A; Bauman, Margaret
2012-09-01
Siblings of children with autism (sibs-A) are at increased genetic risk for autism spectrum disorders (ASD) and milder impairments. To elucidate diversity and contour of early developmental trajectories exhibited by sibs-A, regardless of diagnostic classification, latent class modeling was used. Sibs-A (N = 204) were assessed with the Mullen Scales of Early Learning from age 6 to 36 months. Mullen T scores served as dependent variables. Outcome classifications at age 36 months included: ASD (N = 52); non-ASD social/communication delay (broader autism phenotype; BAP; N = 31); and unaffected (N = 121). Child-specific patterns of performance were studied using latent class growth analysis. Latent class membership was then related to diagnostic outcome through estimation of within-class proportions of children assigned to each diagnostic classification. A 4-class model was favored. Class 1 represented accelerated development and consisted of 25.7% of the sample, primarily unaffected children. Class 2 (40.0% of the sample), was characterized by normative development with above-average nonverbal cognitive outcome. Class 3 (22.3% of the sample) was characterized by receptive language, and gross and fine motor delay. Class 4 (12.0% of the sample), was characterized by widespread delayed skill acquisition, reflected by declining trajectories. Children with an outcome diagnosis of ASD were spread across Classes 2, 3, and 4. Results support a category of ASD that involves slowing in early non-social development. Receptive language and motor development is vulnerable to early delay in sibs-A with and without ASD outcomes. Non-ASD sibs-A are largely distributed across classes depicting average or accelerated development. Developmental trajectories of motor, language, and cognition appear independent of communication and social delays in non-ASD sibs-A. © 2012 The Authors. Journal of Child Psychology and Psychiatry © 2012 Association for Child and Adolescent Mental Health.
Exercise recognition for Kinect-based telerehabilitation.
Antón, D; Goñi, A; Illarramendi, A
2015-01-01
An aging population and people's higher survival to diseases and traumas that leave physical consequences are challenging aspects in the context of an efficient health management. This is why telerehabilitation systems are being developed, to allow monitoring and support of physiotherapy sessions at home, which could reduce healthcare costs while also improving the quality of life of the users. Our goal is the development of a Kinect-based algorithm that provides a very accurate real-time monitoring of physical rehabilitation exercises and that also provides a friendly interface oriented both to users and physiotherapists. The two main constituents of our algorithm are the posture classification method and the exercises recognition method. The exercises consist of series of movements. Each movement is composed of an initial posture, a final posture and the angular trajectories of the limbs involved in the movement. The algorithm was designed and tested with datasets of real movements performed by volunteers. We also explain in the paper how we obtained the optimal values for the trade-off values for posture and trajectory recognition. Two relevant aspects of the algorithm were evaluated in our tests, classification accuracy and real-time data processing. We achieved 91.9% accuracy in posture classification and 93.75% accuracy in trajectory recognition. We also checked whether the algorithm was able to process the data in real-time. We found that our algorithm could process more than 20,000 postures per second and all the required trajectory data-series in real-time, which in practice guarantees no perceptible delays. Later on, we carried out two clinical trials with real patients that suffered shoulder disorders. We obtained an exercise monitoring accuracy of 95.16%. We present an exercise recognition algorithm that handles the data provided by Kinect efficiently. The algorithm has been validated in a real scenario where we have verified its suitability. Moreover, we have received a positive feedback from both users and the physiotherapists who took part in the tests.
Single-cell technologies to study the immune system.
Proserpio, Valentina; Mahata, Bidesh
2016-02-01
The immune system is composed of a variety of cells that act in a coordinated fashion to protect the organism against a multitude of different pathogens. The great variability of existing pathogens corresponds to a similar high heterogeneity of the immune cells. The study of individual immune cells, the fundamental unit of immunity, has recently transformed from a qualitative microscopic imaging to a nearly complete quantitative transcriptomic analysis. This shift has been driven by the rapid development of multiple single-cell technologies. These new advances are expected to boost the detection of less frequent cell types and transient or intermediate cell states. They will highlight the individuality of each single cell and greatly expand the resolution of current available classifications and differentiation trajectories. In this review we discuss the recent advancement and application of single-cell technologies, their limitations and future applications to study the immune system. © 2015 The Authors. Immunology Published by John Wiley & Sons Ltd.
Optimal trajectories of aircraft and spacecraft
NASA Technical Reports Server (NTRS)
Miele, A.
1990-01-01
Work done on algorithms for the numerical solutions of optimal control problems and their application to the computation of optimal flight trajectories of aircraft and spacecraft is summarized. General considerations on calculus of variations, optimal control, numerical algorithms, and applications of these algorithms to real-world problems are presented. The sequential gradient-restoration algorithm (SGRA) is examined for the numerical solution of optimal control problems of the Bolza type. Both the primal formulation and the dual formulation are discussed. Aircraft trajectories, in particular, the application of the dual sequential gradient-restoration algorithm (DSGRA) to the determination of optimal flight trajectories in the presence of windshear are described. Both take-off trajectories and abort landing trajectories are discussed. Take-off trajectories are optimized by minimizing the peak deviation of the absolute path inclination from a reference value. Abort landing trajectories are optimized by minimizing the peak drop of altitude from a reference value. Abort landing trajectories are optimized by minimizing the peak drop of altitude from a reference value. The survival capability of an aircraft in a severe windshear is discussed, and the optimal trajectories are found to be superior to both constant pitch trajectories and maximum angle of attack trajectories. Spacecraft trajectories, in particular, the application of the primal sequential gradient-restoration algorithm (PSGRA) to the determination of optimal flight trajectories for aeroassisted orbital transfer are examined. Both the coplanar case and the noncoplanar case are discussed within the frame of three problems: minimization of the total characteristic velocity; minimization of the time integral of the square of the path inclination; and minimization of the peak heating rate. The solution of the second problem is called nearly-grazing solution, and its merits are pointed out as a useful engineering compromise between energy requirements and aerodynamics heating requirements.
Davies, Christopher E; Glonek, Gary Fv; Giles, Lynne C
2017-08-01
One purpose of a longitudinal study is to gain a better understanding of how an outcome of interest changes among a given population over time. In what follows, a trajectory will be taken to mean the series of measurements of the outcome variable for an individual. Group-based trajectory modelling methods seek to identify subgroups of trajectories within a population, such that trajectories that are grouped together are more similar to each other than to trajectories in distinct groups. Group-based trajectory models generally assume a certain structure in the covariances between measurements, for example conditional independence, homogeneous variance between groups or stationary variance over time. Violations of these assumptions could be expected to result in poor model performance. We used simulation to investigate the effect of covariance misspecification on misclassification of trajectories in commonly used models under a range of scenarios. To do this we defined a measure of performance relative to the ideal Bayesian correct classification rate. We found that the more complex models generally performed better over a range of scenarios. In particular, incorrectly specified covariance matrices could significantly bias the results but using models with a correct but more complicated than necessary covariance matrix incurred little cost.
Mapping mountain pine beetle mortality through growth trend analysis of time-series landsat data
Liang, Lu; Chen, Yanlei; Hawbaker, Todd J.; Zhu, Zhi-Liang; Gong, Peng
2014-01-01
Disturbances are key processes in the carbon cycle of forests and other ecosystems. In recent decades, mountain pine beetle (MPB; Dendroctonus ponderosae) outbreaks have become more frequent and extensive in western North America. Remote sensing has the ability to fill the data gaps of long-term infestation monitoring, but the elimination of observational noise and attributing changes quantitatively are two main challenges in its effective application. Here, we present a forest growth trend analysis method that integrates Landsat temporal trajectories and decision tree techniques to derive annual forest disturbance maps over an 11-year period. The temporal trajectory component successfully captures the disturbance events as represented by spectral segments, whereas decision tree modeling efficiently recognizes and attributes events based upon the characteristics of the segments. Validated against a point set sampled across a gradient of MPB mortality, 86.74% to 94.00% overall accuracy was achieved with small variability in accuracy among years. In contrast, the overall accuracies of single-date classifications ranged from 37.20% to 75.20% and only become comparable with our approach when the training sample size was increased at least four-fold. This demonstrates that the advantages of this time series work flow exist in its small training sample size requirement. The easily understandable, interpretable and modifiable characteristics of our approach suggest that it could be applicable to other ecoregions.
3D hand motion trajectory prediction from EEG mu and beta bandpower.
Korik, A; Sosnik, R; Siddique, N; Coyle, D
2016-01-01
A motion trajectory prediction (MTP) - based brain-computer interface (BCI) aims to reconstruct the three-dimensional (3D) trajectory of upper limb movement using electroencephalography (EEG). The most common MTP BCI employs a time series of bandpass-filtered EEG potentials (referred to here as the potential time-series, PTS, model) for reconstructing the trajectory of a 3D limb movement using multiple linear regression. These studies report the best accuracy when a 0.5-2Hz bandpass filter is applied to the EEG. In the present study, we show that spatiotemporal power distribution of theta (4-8Hz), mu (8-12Hz), and beta (12-28Hz) bands are more robust for movement trajectory decoding when the standard PTS approach is replaced with time-varying bandpower values of a specified EEG band, ie, with a bandpower time-series (BTS) model. A comprehensive analysis comprising of three subjects performing pointing movements with the dominant right arm toward six targets is presented. Our results show that the BTS model produces significantly higher MTP accuracy (R~0.45) compared to the standard PTS model (R~0.2). In the case of the BTS model, the highest accuracy was achieved across the three subjects typically in the mu (8-12Hz) and low-beta (12-18Hz) bands. Additionally, we highlight a limitation of the commonly used PTS model and illustrate how this model may be suboptimal for decoding motion trajectory relevant information. Although our results, showing that the mu and beta bands are prominent for MTP, are not in line with other MTP studies, they are consistent with the extensive literature on classical multiclass sensorimotor rhythm-based BCI studies (classification of limbs as opposed to motion trajectory prediction), which report the best accuracy of imagined limb movement classification using power values of mu and beta frequency bands. The methods proposed here provide a positive step toward noninvasive decoding of imagined 3D hand movements for movement-free BCIs. © 2016 Elsevier B.V. All rights reserved.
Development of Vision Based Multiview Gait Recognition System with MMUGait Database
Ng, Hu; Tan, Wooi-Haw; Tong, Hau-Lee
2014-01-01
This paper describes the acquisition setup and development of a new gait database, MMUGait. This database consists of 82 subjects walking under normal condition and 19 subjects walking with 11 covariate factors, which were captured under two views. This paper also proposes a multiview model-based gait recognition system with joint detection approach that performs well under different walking trajectories and covariate factors, which include self-occluded or external occluded silhouettes. In the proposed system, the process begins by enhancing the human silhouette to remove the artifacts. Next, the width and height of the body are obtained. Subsequently, the joint angular trajectories are determined once the body joints are automatically detected. Lastly, crotch height and step-size of the walking subject are determined. The extracted features are smoothened by Gaussian filter to eliminate the effect of outliers. The extracted features are normalized with linear scaling, which is followed by feature selection prior to the classification process. The classification experiments carried out on MMUGait database were benchmarked against the SOTON Small DB from University of Southampton. Results showed correct classification rate above 90% for all the databases. The proposed approach is found to outperform other approaches on SOTON Small DB in most cases. PMID:25143972
Evaluating data mining algorithms using molecular dynamics trajectories.
Tatsis, Vasileios A; Tjortjis, Christos; Tzirakis, Panagiotis
2013-01-01
Molecular dynamics simulations provide a sample of a molecule's conformational space. Experiments on the mus time scale, resulting in large amounts of data, are nowadays routine. Data mining techniques such as classification provide a way to analyse such data. In this work, we evaluate and compare several classification algorithms using three data sets which resulted from computer simulations, of a potential enzyme mimetic biomolecule. We evaluated 65 classifiers available in the well-known data mining toolkit Weka, using 'classification' errors to assess algorithmic performance. Results suggest that: (i) 'meta' classifiers perform better than the other groups, when applied to molecular dynamics data sets; (ii) Random Forest and Rotation Forest are the best classifiers for all three data sets; and (iii) classification via clustering yields the highest classification error. Our findings are consistent with bibliographic evidence, suggesting a 'roadmap' for dealing with such data.
Decision Manifold Approximation for Physics-Based Simulations
NASA Technical Reports Server (NTRS)
Wong, Jay Ming; Samareh, Jamshid A.
2016-01-01
With the recent surge of success in big-data driven deep learning problems, many of these frameworks focus on the notion of architecture design and utilizing massive databases. However, in some scenarios massive sets of data may be difficult, and in some cases infeasible, to acquire. In this paper we discuss a trajectory-based framework that quickly learns the underlying decision manifold of binary simulation classifications while judiciously selecting exploratory target states to minimize the number of required simulations. Furthermore, we draw particular attention to the simulation prediction application idealized to the case where failures in simulations can be predicted and avoided, providing machine intelligence to novice analysts. We demonstrate this framework in various forms of simulations and discuss its efficacy.
Developmental Trajectories for Children With Dyslexia and Low IQ Poor Readers
2016-01-01
Reading difficulties are found in children with both high and low IQ and it is now clear that both groups exhibit difficulties in phonological processing. Here, we apply the developmental trajectories approach, a new methodology developed for studying language and cognitive impairments in developmental disorders, to both poor reader groups. The trajectory methodology enables identification of atypical versus delayed development in datasets gathered using group matching designs. Regarding the cognitive predictors of reading, which here are phonological awareness, phonological short-term memory (PSTM) and rapid automatized naming (RAN), the method showed that trajectories for the two groups diverged markedly. Children with dyslexia showed atypical development in phonological awareness, while low IQ poor readers showed developmental delay. Low IQ poor readers showed atypical PSTM and RAN development, but children with dyslexia showed developmental delay. These divergent trajectories may have important ramifications for supporting each type of poor reader, although all poor readers showed weakness in all areas. Regarding auditory processing, the developmental trajectories were very similar for the two poor reader groups. However, children with dyslexia demonstrated developmental delay for auditory discrimination of Duration, while the low IQ children showed atypical development on this measure. The data show that, regardless of IQ, poor readers have developmental trajectories that differ from typically developing children. The trajectories approach enables differences in trajectory classification to be identified across poor reader group, as well as specifying the individual nature of these trajectories. PMID:27110928
NASA Astrophysics Data System (ADS)
Zhu, Zhe
2017-08-01
The free and open access to all archived Landsat images in 2008 has completely changed the way of using Landsat data. Many novel change detection algorithms based on Landsat time series have been developed We present a comprehensive review of four important aspects of change detection studies based on Landsat time series, including frequencies, preprocessing, algorithms, and applications. We observed the trend that the more recent the study, the higher the frequency of Landsat time series used. We reviewed a series of image preprocessing steps, including atmospheric correction, cloud and cloud shadow detection, and composite/fusion/metrics techniques. We divided all change detection algorithms into six categories, including thresholding, differencing, segmentation, trajectory classification, statistical boundary, and regression. Within each category, six major characteristics of different algorithms, such as frequency, change index, univariate/multivariate, online/offline, abrupt/gradual change, and sub-pixel/pixel/spatial were analyzed. Moreover, some of the widely-used change detection algorithms were also discussed. Finally, we reviewed different change detection applications by dividing these applications into two categories, change target and change agent detection.
A neural net approach to space vehicle guidance
NASA Technical Reports Server (NTRS)
Caglayan, Alper K.; Allen, Scott M.
1990-01-01
The space vehicle guidance problem is formulated using a neural network approach, and the appropriate neural net architecture for modeling optimum guidance trajectories is investigated. In particular, an investigation is made of the incorporation of prior knowledge about the characteristics of the optimal guidance solution into the neural network architecture. The online classification performance of the developed network is demonstrated using a synthesized network trained with a database of optimum guidance trajectories. Such a neural-network-based guidance approach can readily adapt to environment uncertainties such as those encountered by an AOTV during atmospheric maneuvers.
Low Thrust Mission Trajectories to Near Earth Asteroids
NASA Technical Reports Server (NTRS)
Saripalli, Pratik; Cardiff, Eric
2017-01-01
The discovery of 2016 HO3 and its classification as a quasi-satellite has sparked a stronger interest towards Near Earth Asteroids (NEAs). This work presents low-thrust low-power mission designs to various NEAs using an EELV Secondary Payload Adapter (ESPA). A global trajectory optimizer (EMTG) was used to generate mission solutions to a select 13 NEAs using a 200 watt BHT-200 thruster as a proof of concept. The missions presented here demonstrate that a low-cost electric propulsion ESPA mission to NEAs is a feasible concept for many asteroids.
MATSurv: multisensor air traffic surveillance system
NASA Astrophysics Data System (ADS)
Yeddanapudi, Murali; Bar-Shalom, Yaakov; Pattipati, Krishna R.; Gassner, Richard R.
1995-09-01
This paper deals with the design and implementation of MATSurv 1--an experimental Multisensor Air Traffic Surveillance system. The proposed system consists of a Kalman filter based state estimator used in conjunction with a 2D sliding window assignment algorithm. Real data from two FAA radars is used to evaluate the performance of this algorithm. The results indicate that the proposed algorithm provides a superior classification of the measurements into tracks (i.e., the most likely aircraft trajectories) when compared to the aircraft trajectories obtained using the measurement IDs (squawk or IFF code).
Kroll, Alexandra; Haramagatti, Chandrashekara R.; Lipinski, Hans-Gerd; Wiemann, Martin
2017-01-01
Darkfield and confocal laser scanning microscopy both allow for a simultaneous observation of live cells and single nanoparticles. Accordingly, a characterization of nanoparticle uptake and intracellular mobility appears possible within living cells. Single particle tracking allows to measure the size of a diffusing particle close to a cell. However, within the more complex system of a cell’s cytoplasm normal, confined or anomalous diffusion together with directed motion may occur. In this work we present a method to automatically classify and segment single trajectories into their respective motion types. Single trajectories were found to contain more than one motion type. We have trained a random forest with 9 different features. The average error over all motion types for synthetic trajectories was 7.2%. The software was successfully applied to trajectories of positive controls for normal- and constrained diffusion. Trajectories captured by nanoparticle tracking analysis served as positive control for normal diffusion. Nanoparticles inserted into a diblock copolymer membrane was used to generate constrained diffusion. Finally we segmented trajectories of diffusing (nano-)particles in V79 cells captured with both darkfield- and confocal laser scanning microscopy. The software called “TraJClassifier” is freely available as ImageJ/Fiji plugin via https://git.io/v6uz2. PMID:28107406
Applications of low lift to drag ratio aerobrakes using angle of attack variation for control
NASA Technical Reports Server (NTRS)
Mulqueen, J. A.
1991-01-01
Several applications of low lift to drag ratio aerobrakes are investigated which use angle of attack variation for control. The applications are: return from geosynchronous or lunar orbit to low Earth orbit; and planetary aerocapture at Earth and Mars. A number of aerobrake design considerations are reviewed. It was found that the flow impingement behind the aerobrake and the aerodynamic heating loads are the primary factors that control the sizing of an aerobrake. The heating loads and other loads, such as maximum acceleration, are determined by the vehicle ballistic coefficient, the atmosphere entry conditions, and the trajectory design. Several formulations for defining an optimum trajectory are reviewed, and the various performance indices that can be used are evaluated. The 'nearly grazing' optimal trajectory was found to provide the best compromise between the often conflicting goals of minimizing the vehicle propulsive requirements and minimizing vehicle loads. The relationship between vehicle and trajectory design is investigated further using the results of numerical simulations of trajectories for each aerobrake application. The data show the sensitivity of the trajectories to several vehicle parameters and atmospheric density variations. The results of the trajectory analysis show that low lift to drag ratio aerobrakes, which use angle of attack variation for control, can potentially be used for a wide range of aerobrake applications.
NASA Astrophysics Data System (ADS)
Pérez, Isidro A.; Sánchez, M. Luisa; García, M. Ángeles; Pardo, Nuria
2018-01-01
This study presents a simpler procedure for grouping air parcel back trajectories than others previously applied. Two-day air parcel back trajectories reaching an unpolluted site in the centre of the northern plateau of the Iberian Peninsula were calculated over a three-year period using the METEX model. A procedure based on the kernel density calculation was applied to the direction of each trajectory centroid to determine groups of trajectories. This method is much faster than the cluster procedure when it comes to retaining the directional details of groups. Seasonal analysis of six groups of trajectories revealed that the Atlantic origin prevailed against displacement from northern Europe. Moreover, Mediterranean and particularly African trajectories were infrequent, probably due to the rough peninsular orography in these directions. The location of air trajectories reaching the study site was described using a surface classification below the air parcels with improved spatial resolution compared to previous analyses. Local contribution was very marked, particularly in summer. Mean trajectories were calculated for each group together with meteorological features and CO2 and CH4 concentrations. Groups may be identified by their mean temperature, wind speed, elevation and distance values. However, only two groups should be considered when analysing the two trace gases, one for trajectories from the Atlantic Ocean and the second for trajectories from the continent. Contrasts of about 4 ppm for CO2 in summer and 0.023 ppm for CH4 in winter were observed, revealing that air trajectories from the Atlantic Ocean were cleaner than those arriving from the continent. These differences were attributed to higher air stagnation over land.
A Segment-Based Trajectory Similarity Measure in the Urban Transportation Systems.
Mao, Yingchi; Zhong, Haishi; Xiao, Xianjian; Li, Xiaofang
2017-03-06
With the rapid spread of built-in GPS handheld smart devices, the trajectory data from GPS sensors has grown explosively. Trajectory data has spatio-temporal characteristics and rich information. Using trajectory data processing techniques can mine the patterns of human activities and the moving patterns of vehicles in the intelligent transportation systems. A trajectory similarity measure is one of the most important issues in trajectory data mining (clustering, classification, frequent pattern mining, etc.). Unfortunately, the main similarity measure algorithms with the trajectory data have been found to be inaccurate, highly sensitive of sampling methods, and have low robustness for the noise data. To solve the above problems, three distances and their corresponding computation methods are proposed in this paper. The point-segment distance can decrease the sensitivity of the point sampling methods. The prediction distance optimizes the temporal distance with the features of trajectory data. The segment-segment distance introduces the trajectory shape factor into the similarity measurement to improve the accuracy. The three kinds of distance are integrated with the traditional dynamic time warping algorithm (DTW) algorithm to propose a new segment-based dynamic time warping algorithm (SDTW). The experimental results show that the SDTW algorithm can exhibit about 57%, 86%, and 31% better accuracy than the longest common subsequence algorithm (LCSS), and edit distance on real sequence algorithm (EDR) , and DTW, respectively, and that the sensitivity to the noise data is lower than that those algorithms.
Cale, Jesse; Smallbone, Stephen; Rayment-McHugh, Sue; Dowling, Chris
2016-12-01
The current study examines offending trajectories of adolescent sexual offenders (ASOs). Until recently, classification frameworks have not been designed to account for the heterogeneity of offending patterns in adolescence, how these are associated with the unfolding of sexual and non-sexual criminal activity, and whether and to what extent they are related to the characteristics of sex offenses in adolescence. The current study takes a longitudinal view of offending in adolescence by examining retrospective longitudinal data of 217 ASOs referred for treatment to a clinical service between 2001 and 2009 in Australia. General offending trajectories in adolescence were examined using semi-parametric group-based modeling, and compared according to non-violent non-sexual, violent-non-sexual, and sex offending criminal activity parameters (e.g., participation, onset, frequency, specialization/versatility) and the characteristics of the referral sexual offense. The results show distinct differences in the unfolding of sexual and non-sexual criminal activity along different offending trajectories of ASOs, and further, that these trajectories were differentially associated with the characteristics of the sexual offenses they committed. © The Author(s) 2015.
Transitioning from Acute to Chronic Pain: An Examination of Different Trajectories of Low-Back Pain.
Gatchel, Robert J; Bevers, Kelley; Licciardone, John C; Su, Jianzhong; Du, Ying; Brotto, Marco
2018-05-17
Traditionally, there has been a widely accepted notion that the transition from acute to chronic pain follows a linear trajectory, where an injury leads to acute episodes, subacute stages, and progresses to a chronic pain condition. However, it appears that pain progression is much more complicated and individualized than this original unsupported assumption. It is now becoming apparent that, while this linear progression may occur, it is not the only path that pain, specifically low-back pain, follows. It is clear there is a definite need to evaluate how low-back pain trajectories are classified and, subsequently, how we can more effectively intervene during these progression stages. In order to better understand and manage pain conditions, we must examine the different pain trajectories, and develop a standard by which to use these classifications, so that clinicians can better identify and predict patient-needs and customize treatments for maximum efficacy. The present article examines the most recent trajectory research, and highlights the importance of developing a broader model for patient evaluation.
The impact of biomass burning in North Korea to the air quality in Seoul, South Korea
NASA Astrophysics Data System (ADS)
Kim, I.; Lee, J.; Kim, Y.
2011-12-01
South Korea is contiguous to China, Japan and North Koreas, so air pollutants transported from outside South Korea should be investigated. Nevertheless, few researches have dealt with the influences of air pollutants from North Korea to other areas. The objectives of this study are to understand the influences of air pollutants' emission from North Korea to South Korea, especially Seoul, using the chemical mass balance (CMB) model and the backward trajectory analysis. CMB model were applied to analyze the source apportionment of PAHs at Seoul between 2006 and 2007. To understand the transport of air pollutants emitted from North Korea, the backward trajectories in sampling days were classified to four cases depending on which area the trajectories predominantly passed through. Based on the contribution of biomass burning calculated by CMB and the trajectories, the influence of air pollutants from North Korea to Seoul is quantified. In order to strengthen the uncertainty of CMB result, the trend of levoglucosan (1,6-anhydro-b-D-glucopyranose) concentration at Seoul is also discussed depending on the classification of trajectories.
Li, Wen-Long; Qu, Hai-Bin
2016-10-01
In this paper, the principle of NIRS (near infrared spectroscopy)-based process trajectory technology was introduced.The main steps of the technique include:① in-line collection of the processes spectra of different technics; ② unfolding of the 3-D process spectra;③ determination of the process trajectories and their normal limits;④ monitoring of the new batches with the established MSPC (multivariate statistical process control) models.Applications of the technology in the chemical and biological medicines were reviewed briefly. By a comprehensive introduction of our feasibility research on the monitoring of traditional Chinese medicine technical process using NIRS-based multivariate process trajectories, several important problems of the practical applications which need urgent solutions are proposed, and also the application prospect of the NIRS-based process trajectory technology is fully discussed and put forward in the end. Copyright© by the Chinese Pharmaceutical Association.
Machine Learning for Discriminating Quantum Measurement Trajectories and Improving Readout.
Magesan, Easwar; Gambetta, Jay M; Córcoles, A D; Chow, Jerry M
2015-05-22
Current methods for classifying measurement trajectories in superconducting qubit systems produce fidelities systematically lower than those predicted by experimental parameters. Here, we place current classification methods within the framework of machine learning (ML) algorithms and improve on them by investigating more sophisticated ML approaches. We find that nonlinear algorithms and clustering methods produce significantly higher assignment fidelities that help close the gap to the fidelity possible under ideal noise conditions. Clustering methods group trajectories into natural subsets within the data, which allows for the diagnosis of systematic errors. We find large clusters in the data associated with T1 processes and show these are the main source of discrepancy between our experimental and ideal fidelities. These error diagnosis techniques help provide a path forward to improve qubit measurements.
Automated robot-assisted surgical skill evaluation: Predictive analytics approach.
Fard, Mahtab J; Ameri, Sattar; Darin Ellis, R; Chinnam, Ratna B; Pandya, Abhilash K; Klein, Michael D
2018-02-01
Surgical skill assessment has predominantly been a subjective task. Recently, technological advances such as robot-assisted surgery have created great opportunities for objective surgical evaluation. In this paper, we introduce a predictive framework for objective skill assessment based on movement trajectory data. Our aim is to build a classification framework to automatically evaluate the performance of surgeons with different levels of expertise. Eight global movement features are extracted from movement trajectory data captured by a da Vinci robot for surgeons with two levels of expertise - novice and expert. Three classification methods - k-nearest neighbours, logistic regression and support vector machines - are applied. The result shows that the proposed framework can classify surgeons' expertise as novice or expert with an accuracy of 82.3% for knot tying and 89.9% for a suturing task. This study demonstrates and evaluates the ability of machine learning methods to automatically classify expert and novice surgeons using global movement features. Copyright © 2017 John Wiley & Sons, Ltd.
14 CFR Appendix B to Part 420 - Method for Defining a Flight Corridor
Code of Federal Regulations, 2010 CFR
2010-01-01
... trajectory simulation software. Trajectory time intervals shall be no greater than one second. If an... applicant shall construct a launch area of a flight corridor using the processes and equations of this paragraph for each trajectory position. An applicant shall repeat these processes at time points on the...
FVID: Fishing Vessel Type Identification Based on VMS Trajectories
NASA Astrophysics Data System (ADS)
Huang, Haiguang; Hong, Feng; Liu, Jing; Liu, Chao; Feng, Yuan; Guo, Zhongwen
2018-05-01
Vessel Monitoring System (VMS) provides a new opportunity for quantified fishing research. Many approaches have been proposed to recognize fishing activities with VMS trajectories based on the types of fishing vessels. However, one research problem is still calling for solutions, how to identify the fishing vessel type based on only VMS trajectories. This problem is important because it requires the fishing vessel type as a preliminary to recognize fishing activities from VMS trajectories. This paper proposes fishing vessel type identification scheme (FVID) based only on VMS trajectories. FVID exploits feature engineering and machine learning schemes of XGBoost as its two key blocks and classifies fishing vessels into nine types. The dataset contains all the fishing vessel trajectories in the East China Sea in March 2017, including 10031 pre-registered fishing vessels and 1350 unregistered vessels of unknown types. In order to verify type identification accuracy, we first conduct a 4-fold cross-validation on the trajectories of registered fishing vessels. The classification accuracy is 95.42%. We then apply FVID to the unregistered fishing vessels to identify their types. After classifying the unregistered fishing vessel types, their fishing activities are further recognized based upon their types. At last, we calculate and compare the fishing density distribution in the East China Sea before and after applying the unregistered fishing vessels, confirming the importance of type identification of unregistered fishing vessels.
Application of Taylor's series to trajectory propagation
NASA Technical Reports Server (NTRS)
Stanford, R. H.; Berryman, K. W.; Breckheimer, P. J.
1986-01-01
This paper describes the propagation of trajectories by the application of the preprocessor ATOMCC which uses Taylor's series to solve initial value problems in ordinary differential equations. Comparison of the results obtained with those from other methods are presented. The current studies indicate that the ATOMCC preprocessor is an easy, yet fast and accurate method for generating trajectories.
NASA Technical Reports Server (NTRS)
Horton, C. L. (Principal Investigator)
1981-01-01
The CLASFYT program is described in detail. The program produces a one-channel universal-formatted classification file. Trajectory coefficients and a composite set of tolerance values are calculated from five acquisitions of radiance values in each of the training fields corresponding to up to ten agricultural products. These coefficients and tolerance values are used to classify each pixel in the test field of the same segment to be the same agricultural product as one of the training fields, none of the products or a screened pixel.
NASA Astrophysics Data System (ADS)
Wang, Mingming; Luo, Jianjun; Yuan, Jianping; Walter, Ulrich
2018-05-01
Application of the multi-arm space robot will be more effective than single arm especially when the target is tumbling. This paper investigates the application of particle swarm optimization (PSO) strategy to coordinated trajectory planning of the dual-arm space robot in free-floating mode. In order to overcome the dynamics singularities issue, the direct kinematics equations in conjunction with constrained PSO are employed for coordinated trajectory planning of dual-arm space robot. The joint trajectories are parametrized with Bézier curve to simplify the calculation. Constrained PSO scheme with adaptive inertia weight is implemented to find the optimal solution of joint trajectories while specific objectives and imposed constraints are satisfied. The proposed method is not sensitive to the singularity issue due to the application of forward kinematic equations. Simulation results are presented for coordinated trajectory planning of two kinematically redundant manipulators mounted on a free-floating spacecraft and demonstrate the effectiveness of the proposed method.
New trends in astrodynamics and applications: optimal trajectories for space guidance.
Azimov, Dilmurat; Bishop, Robert
2005-12-01
This paper represents recent results on the development of optimal analytic solutions to the variation problem of trajectory optimization and their application in the construction of on-board guidance laws. The importance of employing the analytically integrated trajectories in a mission design is discussed. It is assumed that the spacecraft is equipped with a power-limited propulsion and moving in a central Newtonian field. Satisfaction of the necessary and sufficient conditions for optimality of trajectories is analyzed. All possible thrust arcs and corresponding classes of the analytical solutions are classified based on the propulsion system parameters and performance index of the problem. The solutions are presented in a form convenient for applications in escape, capture, and interorbital transfer problems. Optimal guidance and neighboring optimal guidance problems are considered. It is shown that the analytic solutions can be used as reference trajectories in constructing the guidance algorithms for the maneuver problems mentioned above. An illustrative example of a spiral trajectory that terminates on a given elliptical parking orbit is discussed.
Optimizing Mars Airplane Trajectory with the Application Navigation System
NASA Technical Reports Server (NTRS)
Frumkin, Michael; Riley, Derek
2004-01-01
Planning complex missions requires a number of programs to be executed in concert. The Application Navigation System (ANS), developed in the NAS Division, can execute many interdependent programs in a distributed environment. We show that the ANS simplifies user effort and reduces time in optimization of the trajectory of a martian airplane. We use a software package, Cart3D, to evaluate trajectories and a shortest path algorithm to determine the optimal trajectory. ANS employs the GridScape to represent the dynamic state of the available computer resources. Then, ANS uses a scheduler to dynamically assign ready task to machine resources and the GridScape for tracking available resources and forecasting completion time of running tasks. We demonstrate system capability to schedule and run the trajectory optimization application with efficiency exceeding 60% on 64 processors.
NASA Astrophysics Data System (ADS)
Baker, Ernest; van der Voort, Martijn; NATO Munitions Safety Information Analysis Centre Team
2017-06-01
Ballistics trajectory and impact conditions calculations were conducted in order to investigate the origin of the projection criteria for Insensitive Munitions (IM) and Hazard Classification (HC). The results show that the existing IM and HC projection criteria distance-mass relations are based on launch energy rather than impact conditions. The distance-mass relations were reproduced using TRAJCAN trajectory analysis by using launch energies of 8, 20 and 79J and calculating the maximum impact distance reached by a natural fragment (steel) launched from 1 m height. The analysis shows that at the maximum throw distances, the impact energy is generally much smaller than the launch energy. Using maximum distance projections, new distance-mass relations were developed that match the criteria based on impact energy at 15m and beyond rather than launch energy. Injury analysis was conducted using penetration injury and blunt injury models. The smallest projectile masses in the distance-mass relations are in the transition region from penetration injury to blunt injury. For this reason, blunt injury dominates the assessment of injury or lethality. State of the art blunt injury models predict only minor injury for a 20J impact. For a 79J blunt impact, major injury is likely to occur. MSIAC recommends changing the distance-mass relation that distinguishes a munitions burning response to a 20 J impact energy criterion at 15 m and updating of the UN Orange Book.
NASA Astrophysics Data System (ADS)
Cohen, Caroline; Darbois Texier, Baptiste; Quéré, David; Clanet, Christophe
2015-06-01
The conical shape of a shuttlecock allows it to flip on impact. As a light and extended particle, it flies with a pure drag trajectory. We first study the flip phenomenon and the dynamics of the flight and then discuss the implications on the game. Lastly, a possible classification of different shots is proposed.
Differential Effects of Treatments for Chronic Depression: A Latent Growth Model Reanalysis
ERIC Educational Resources Information Center
Stulz, Niklaus; Thase, Michael E.; Klein, Daniel N.; Manber, Rachel; Crits-Christoph, Paul
2010-01-01
Objective: Psychotherapy-pharmacotherapy combinations are frequently recommended for the treatment of chronic depressive disorders. Our aim in this novel reanalysis of archival data was to identify patient subgroups on the basis of symptom trajectories and examine the clinical significance of the resultant classification on basis of differential…
NASA Astrophysics Data System (ADS)
Choi, Hoseok; Lee, Jeyeon; Park, Jinsick; Lee, Seho; Ahn, Kyoung-ha; Kim, In Young; Lee, Kyoung-Min; Jang, Dong Pyo
2018-02-01
Objective. In arm movement BCIs (brain-computer interfaces), unimanual research has been much more extensively studied than its bimanual counterpart. However, it is well known that the bimanual brain state is different from the unimanual one. Conventional methodology used in unimanual studies does not take the brain stage into consideration, and therefore appears to be insufficient for decoding bimanual movements. In this paper, we propose the use of a two-staged (effector-then-trajectory) decoder, which combines the classification of movement conditions and uses a hand trajectory predicting algorithm for unimanual and bimanual movements, for application in real-world BCIs. Approach. Two micro-electrode patches (32 channels) were inserted over the dura mater of the left and right hemispheres of two rhesus monkeys, covering the motor related cortex for epidural electrocorticograph (ECoG). Six motion sensors (inertial measurement unit) were used to record the movement signals. The monkeys performed three types of arm movement tasks: left unimanual, right unimanual, bimanual. To decode these movements, we used a two-staged decoder, which combines the effector classifier for four states (left unimanual, right unimanual, bimanual movements, and stationary state) and movement predictor using regression. Main results. Using this approach, we successfully decoded both arm positions using the proposed decoder. The results showed that decoding performance for bimanual movements were improved compared to the conventional method, which does not consider the effector, and the decoding performance was significant and stable over a period of four months. In addition, we also demonstrated the feasibility of epidural ECoG signals, which provided an adequate level of decoding accuracy. Significance. These results provide evidence that brain signals are different depending on the movement conditions or effectors. Thus, the two-staged method could be useful if BCIs are used to generalize for both unimanual and bimanual operations in human applications and in various neuro-prosthetics fields.
Ekberg, J; Angbratt, M; Valter, L; Nordvall, M; Timpka, T
2012-04-01
To use epidemiological data and a standardized economic model to compare projected costs for obesity prevention in late adolescence accrued using a cross-sectional weight classification for selecting adolescents at age 15 years compared with a longitudinal classification. All children born in a Swedish county (population 440 000) in 1991 who participated in all regular measurements of height and weight at ages 5, 10 and 15 years (n=4312) were included in the study. The selection strategies were compared by calculating the projected financial load resulting from supply of obesity prevention services from providers at all levels in the health care system. The difference in marginal cost per 1000 children was used as the primary end point for the analyses. Using the cross-sectional selection strategy, 3.8% of adolescents at age 15 years were selected for evaluation by a pediatric specialist, and 96.2% were chosen for population-based interventions. In the trajectory-based strategy, 2.4% of the adolescents were selected for intensive pediatric care, 1.4% for individual clinical interventions in primary health care, 14.0% for individual primary obesity prevention using the Internet and 82.1% for population-based interventions. Costs for the cross-sectional selection strategy were projected to USD463 581 per 1000 adolescents and for the trajectory-based strategy were USD 302 016 per 1000 adolescents. Using projections from epidemiological data, we found that by basing the selection of adolescents for obesity prevention on weight trajectories, the load on highly specialized pediatric care can be reduced by one-third and total health service costs for obesity management among adolescents reduced by one-third. Before use in policies and prevention program planning, our findings warrant confirmation in prospective cost-benefit studies.
Multivariant function model generation
NASA Technical Reports Server (NTRS)
1974-01-01
The development of computer programs applicable to space vehicle guidance was conducted. The subjects discussed are as follows: (1) determination of optimum reentry trajectories, (2) development of equations for performance of trajectory computation, (3) vehicle control for fuel optimization, (4) development of equations for performance trajectory computations, (5) applications and solution of Hamilton-Jacobi equation, and (6) stresses in dome shaped shells with discontinuities at the apex.
Convolutional Neural Network-Based Robot Navigation Using Uncalibrated Spherical Images †
Ran, Lingyan; Zhang, Yanning; Zhang, Qilin; Yang, Tao
2017-01-01
Vision-based mobile robot navigation is a vibrant area of research with numerous algorithms having been developed, the vast majority of which either belong to the scene-oriented simultaneous localization and mapping (SLAM) or fall into the category of robot-oriented lane-detection/trajectory tracking. These methods suffer from high computational cost and require stringent labelling and calibration efforts. To address these challenges, this paper proposes a lightweight robot navigation framework based purely on uncalibrated spherical images. To simplify the orientation estimation, path prediction and improve computational efficiency, the navigation problem is decomposed into a series of classification tasks. To mitigate the adverse effects of insufficient negative samples in the “navigation via classification” task, we introduce the spherical camera for scene capturing, which enables 360° fisheye panorama as training samples and generation of sufficient positive and negative heading directions. The classification is implemented as an end-to-end Convolutional Neural Network (CNN), trained on our proposed Spherical-Navi image dataset, whose category labels can be efficiently collected. This CNN is capable of predicting potential path directions with high confidence levels based on a single, uncalibrated spherical image. Experimental results demonstrate that the proposed framework outperforms competing ones in realistic applications. PMID:28604624
Trajectory optimization for the National Aerospace Plane
NASA Technical Reports Server (NTRS)
Lu, Ping
1993-01-01
The objective of this second phase research is to investigate the optimal ascent trajectory for the National Aerospace Plane (NASP) from runway take-off to orbital insertion and address the unique problems associated with the hypersonic flight trajectory optimization. The trajectory optimization problem for an aerospace plane is a highly challenging problem because of the complexity involved. Previous work has been successful in obtaining sub-optimal trajectories by using energy-state approximation and time-scale decomposition techniques. But it is known that the energy-state approximation is not valid in certain portions of the trajectory. This research aims at employing full dynamics of the aerospace plane and emphasizing direct trajectory optimization methods. The major accomplishments of this research include the first-time development of an inverse dynamics approach in trajectory optimization which enables us to generate optimal trajectories for the aerospace plane efficiently and reliably, and general analytical solutions to constrained hypersonic trajectories that has wide application in trajectory optimization as well as in guidance and flight dynamics. Optimal trajectories in abort landing and ascent augmented with rocket propulsion and thrust vectoring control were also investigated. Motivated by this study, a new global trajectory optimization tool using continuous simulated annealing and a nonlinear predictive feedback guidance law have been under investigation and some promising results have been obtained, which may well lead to more significant development and application in the near future.
Method and Apparatus for Generating Flight-Optimizing Trajectories
NASA Technical Reports Server (NTRS)
Ballin, Mark G. (Inventor); Wing, David J. (Inventor)
2015-01-01
An apparatus for generating flight-optimizing trajectories for a first aircraft includes a receiver capable of receiving second trajectory information associated with at least one second aircraft. The apparatus also includes a traffic aware planner (TAP) module operably connected to the receiver to receive the second trajectory information. The apparatus also includes at least one internal input device on board the first aircraft to receive first trajectory information associated with the first aircraft and a TAP application capable of calculating an optimal trajectory for the first aircraft based at least on the first trajectory information and the second trajectory information. The optimal trajectory at least avoids conflicts between the first trajectory information and the second trajectory information.
Mixed anxiety depression should not be included in DSM-5.
Batelaan, Neeltje M; Spijker, Jan; de Graaf, Ron; Cuijpers, Pim
2012-06-01
Subthreshold anxiety and subthreshold depressive symptoms often co-occur in the general population and in primary care. Based on their associated significant distress and impairment, a psychiatric classification seems justified. To enable classification, mixed anxiety depression (MAD) has been proposed as a new diagnostic category in DSM-5. In this report, we discuss arguments against the classification of MAD. More research is needed before reifying a new category we know so little about. Moreover, we argue that in patients with MAD symptoms and a history of an anxiety or depressive disorder, symptoms should be labeled as part of the course trajectories of these disorders, rather than calling it a different diagnostic entity. In patients with incident co-occurring subthreshold anxiety and subthreshold depression, subthreshold categories of both anxiety and depression could be classified to maintain a consistent classification system at both threshold and subthreshold levels.
Adaptive estimation of hand movement trajectory in an EEG based brain-computer interface system
NASA Astrophysics Data System (ADS)
Robinson, Neethu; Guan, Cuntai; Vinod, A. P.
2015-12-01
Objective. The various parameters that define a hand movement such as its trajectory, speed, etc, are encoded in distinct brain activities. Decoding this information from neurophysiological recordings is a less explored area of brain-computer interface (BCI) research. Applying non-invasive recordings such as electroencephalography (EEG) for decoding makes the problem more challenging, as the encoding is assumed to be deep within the brain and not easily accessible by scalp recordings. Approach. EEG based BCI systems can be developed to identify the neural features underlying movement parameters that can be further utilized to provide a detailed and well defined control command set to a BCI output device. A real-time continuous control is better suited for practical BCI systems, and can be achieved by continuous adaptive reconstruction of movement trajectory than discrete brain activity classifications. In this work, we adaptively reconstruct/estimate the parameters of two-dimensional hand movement trajectory, namely movement speed and position, from multi-channel EEG recordings. The data for analysis is collected by performing an experiment that involved center-out right-hand movement tasks in four different directions at two different speeds in random order. We estimate movement trajectory using a Kalman filter that models the relation between brain activity and recorded parameters based on a set of defined predictors. We propose a method to define these predictor variables that includes spatial, spectral and temporally localized neural information and to select optimally informative variables. Main results. The proposed method yielded correlation of (0.60 ± 0.07) between recorded and estimated data. Further, incorporating the proposed predictor subset selection, the correlation achieved is (0.57 ± 0.07, p {\\lt }0.004) with significant gain in stability of the system, as well as dramatic reduction in number of predictors (76%) for the savings of computational time. Significance. The proposed system provides a real time movement control system using EEG-BCI with control over movement speed and position. These results are higher and statistically significant compared to existing techniques in EEG based systems and thus promise the applicability of the proposed method for efficient estimation of movement parameters and for continuous motor control.
Zebrafish tracking using convolutional neural networks.
Xu, Zhiping; Cheng, Xi En
2017-02-17
Keeping identity for a long term after occlusion is still an open problem in the video tracking of zebrafish-like model animals, and accurate animal trajectories are the foundation of behaviour analysis. We utilize the highly accurate object recognition capability of a convolutional neural network (CNN) to distinguish fish of the same congener, even though these animals are indistinguishable to the human eye. We used data augmentation and an iterative CNN training method to optimize the accuracy for our classification task, achieving surprisingly accurate trajectories of zebrafish of different size and age zebrafish groups over different time spans. This work will make further behaviour analysis more reliable.
Zebrafish tracking using convolutional neural networks
NASA Astrophysics Data System (ADS)
Xu, Zhiping; Cheng, Xi En
2017-02-01
Keeping identity for a long term after occlusion is still an open problem in the video tracking of zebrafish-like model animals, and accurate animal trajectories are the foundation of behaviour analysis. We utilize the highly accurate object recognition capability of a convolutional neural network (CNN) to distinguish fish of the same congener, even though these animals are indistinguishable to the human eye. We used data augmentation and an iterative CNN training method to optimize the accuracy for our classification task, achieving surprisingly accurate trajectories of zebrafish of different size and age zebrafish groups over different time spans. This work will make further behaviour analysis more reliable.
Björkenstam, Emma; Cheng, Siwei; Burström, Bo; Pebley, Anne R; Björkenstam, Charlotte; Kosidou, Kyriaki
2017-07-01
Childhood family income variation is an understudied aspect of households' economic context that may have distinct consequences for children. We identified trajectories of childhood family income over a 12-year period, and examined associations between these trajectories and later psychiatric disorders, among individuals born in Sweden between 1987 and 1991 (n=534 294). We used annual income data between the ages of 3-14 years and identified 5 trajectories (2 high-income upward, 1 downward and 2 low-income upward trajectories). Psychiatric disorders in the follow-up period after age 15 were defined from International Classification of Disease (ICD)-codes in a nationwide patient register. Multiadjusted risks for all psychiatric disorders, as well as for specific psychiatric diagnoses, were calculated as HRs with 95% CIs. Of the 5 identified income trajectories, the constant low and the downward trajectories were particularly associated with later psychiatric disorder. Children with these trajectories had increased risks for psychiatric disorder, including mood, anxiety, psychotic disorders and attention deficit/hyperactivity disorder. The association remained, even after adjusting for important variables including parental psychiatric disorder. In contrast, the relationship was reversed for eating disorders, for which children in higher income trajectories had elevated risks. Findings show that children growing up in a household characterised by low or decreasing family income have an increased risk for psychiatric disorder. Continued work is needed to reduce socioeconomic inequalities in psychiatric disorders. Policies and interventions for psychiatric disorders should consider the socioeconomic background of the family as an important risk or protective factor. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Classification and Lineage Tracing of SH2 Domains Throughout Eukaryotes.
Liu, Bernard A
2017-01-01
Today there exists a rapidly expanding number of sequenced genomes. Cataloging protein interaction domains such as the Src Homology 2 (SH2) domain across these various genomes can be accomplished with ease due to existing algorithms and predictions models. An evolutionary analysis of SH2 domains provides a step towards understanding how SH2 proteins integrated with existing signaling networks to position phosphotyrosine signaling as a crucial driver of robust cellular communication networks in metazoans. However organizing and tracing SH2 domain across organisms and understanding their evolutionary trajectory remains a challenge. This chapter describes several methodologies towards analyzing the evolutionary trajectory of SH2 domains including a global SH2 domain classification system, which facilitates annotation of new SH2 sequences essential for tracing the lineage of SH2 domains throughout eukaryote evolution. This classification utilizes a combination of sequence homology, protein domain architecture and the boundary positions between introns and exons within the SH2 domain or genes encoding these domains. Discrete SH2 families can then be traced across various genomes to provide insight into its origins. Furthermore, additional methods for examining potential mechanisms for divergence of SH2 domains from structural changes to alterations in the protein domain content and genome duplication will be discussed. Therefore a better understanding of SH2 domain evolution may enhance our insight into the emergence of phosphotyrosine signaling and the expansion of protein interaction domains.
Trajectory fitting in function space with application to analytic modeling of surfaces
NASA Technical Reports Server (NTRS)
Barger, Raymond L.
1992-01-01
A theory for representing a parameter-dependent function as a function trajectory is described. Additionally, a theory for determining a piecewise analytic fit to the trajectory is described. An example is given that illustrates the application of the theory to generating a smooth surface through a discrete set of input cross-section shapes. A simple procedure for smoothing in the parameter direction is discussed, and a computed example is given. Application of the theory to aerodynamic surface modeling is demonstrated by applying it to a blended wing-fuselage surface.
Expressions of Different-Trajectory Caused Motion Events in Chinese
ERIC Educational Resources Information Center
Paul, Jing Z.
2013-01-01
We perform motion events in all aspects of our daily life, from walking home to jumping into a pool, from throwing a frisbee to pushing a shopping cart. The fact that languages may encode such motion events in different fashions has raised intriguing questions regarding the typological classifications of natural languages in relation to…
Dalhuisen, Lydia; Koenraadt, Frans; Liem, Marieke
2017-02-01
Prior research has classified firesetters by motive. The multi-trajectory theory of adult firesetting (M-TTAF) takes a more aetiological perspective, differentiating between five hypothesised trajectories towards firesetting: antisocial cognition, grievance, fire interest, emotionally expressive/need for recognition and multifaceted trajectories. The objective of this study was to validate the five routes to firesetting as proposed in the M-TTAF. All 389 adult firesetters referred for forensic mental health assessment to one central clinic in the Netherlands between 1950 and 2012 were rated on variables linked to the M-TTAF. Cluster analysis was then applied. A reliable cluster solution emerged revealing five subtypes of firesetters - labelled instrumental, reward, multi-problem, disturbed relationship and disordered. Significant differences were observed regarding both offender and offence characteristics. Our five-cluster solution with five subtypes of firesetters partially validates the proposed M-TTAF trajectories and suggests that for offenders with and without mental disorder, this classification may be useful. If further validated with larger and more diverse samples, the M-TTAF could provide guidance on staging evidence-based treatment. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.
Classification and pose estimation of objects using nonlinear features
NASA Astrophysics Data System (ADS)
Talukder, Ashit; Casasent, David P.
1998-03-01
A new nonlinear feature extraction method called the maximum representation and discrimination feature (MRDF) method is presented for extraction of features from input image data. It implements transformations similar to the Sigma-Pi neural network. However, the weights of the MRDF are obtained in closed form, and offer advantages compared to nonlinear neural network implementations. The features extracted are useful for both object discrimination (classification) and object representation (pose estimation). We show its use in estimating the class and pose of images of real objects and rendered solid CAD models of machine parts from single views using a feature-space trajectory (FST) neural network classifier. We show more accurate classification and pose estimation results than are achieved by standard principal component analysis (PCA) and Fukunaga-Koontz (FK) feature extraction methods.
Direct Method Transcription for a Human-Class Translunar Injection Trajectory Optimization
NASA Technical Reports Server (NTRS)
Witzberger, Kevin E.; Zeiler, Tom
2012-01-01
This paper presents a new trajectory optimization software package developed in the framework of a low-to-high fidelity 3 degrees-of-freedom (DOF)/6-DOF vehicle simulation program named Mission Analysis Simulation Tool in Fortran (MASTIF) and its application to a translunar trajectory optimization problem. The functionality of the developed optimization package is implemented as a new "mode" in generalized settings to make it applicable for a general trajectory optimization problem. In doing so, a direct optimization method using collocation is employed for solving the problem. Trajectory optimization problems in MASTIF are transcribed to a constrained nonlinear programming (NLP) problem and solved with SNOPT, a commercially available NLP solver. A detailed description of the optimization software developed is provided as well as the transcription specifics for the translunar injection (TLI) problem. The analysis includes a 3-DOF trajectory TLI optimization and a 3-DOF vehicle TLI simulation using closed-loop guidance.
White, Simon R; Muniz-Terrera, Graciela; Matthews, Fiona E
2018-05-01
Many medical (and ecological) processes involve the change of shape, whereby one trajectory changes into another trajectory at a specific time point. There has been little investigation into the study design needed to investigate these models. We consider the class of fixed effect change-point models with an underlying shape comprised two joined linear segments, also known as broken-stick models. We extend this model to include two sub-groups with different trajectories at the change-point, a change and no change class, and also include a missingness model to account for individuals with incomplete follow-up. Through a simulation study, we consider the relationship of sample size to the estimates of the underlying shape, the existence of a change-point, and the classification-error of sub-group labels. We use a Bayesian framework to account for the missing labels, and the analysis of each simulation is performed using standard Markov chain Monte Carlo techniques. Our simulation study is inspired by cognitive decline as measured by the Mini-Mental State Examination, where our extended model is appropriate due to the commonly observed mixture of individuals within studies who do or do not exhibit accelerated decline. We find that even for studies of modest size ( n = 500, with 50 individuals observed past the change-point) in the fixed effect setting, a change-point can be detected and reliably estimated across a range of observation-errors.
Masked and unmasked error-related potentials during continuous control and feedback
NASA Astrophysics Data System (ADS)
Lopes Dias, Catarina; Sburlea, Andreea I.; Müller-Putz, Gernot R.
2018-06-01
The detection of error-related potentials (ErrPs) in tasks with discrete feedback is well established in the brain–computer interface (BCI) field. However, the decoding of ErrPs in tasks with continuous feedback is still in its early stages. Objective. We developed a task in which subjects have continuous control of a cursor’s position by means of a joystick. The cursor’s position was shown to the participants in two different modalities of continuous feedback: normal and jittered. The jittered feedback was created to mimic the instability that could exist if participants controlled the trajectory directly with brain signals. Approach. This paper studies the electroencephalographic (EEG)—measurable signatures caused by a loss of control over the cursor’s trajectory, causing a target miss. Main results. In both feedback modalities, time-locked potentials revealed the typical frontal-central components of error-related potentials. Errors occurring during the jittered feedback (masked errors) were delayed in comparison to errors occurring during normal feedback (unmasked errors). Masked errors displayed lower peak amplitudes than unmasked errors. Time-locked classification analysis allowed a good distinction between correct and error classes (average Cohen-, average TPR = 81.8% and average TNR = 96.4%). Time-locked classification analysis between masked error and unmasked error classes revealed results at chance level (average Cohen-, average TPR = 60.9% and average TNR = 58.3%). Afterwards, we performed asynchronous detection of ErrPs, combining both masked and unmasked trials. The asynchronous detection of ErrPs in a simulated online scenario resulted in an average TNR of 84.0% and in an average TPR of 64.9%. Significance. The time-locked classification results suggest that the masked and unmasked errors were indistinguishable in terms of classification. The asynchronous classification results suggest that the feedback modality did not hinder the asynchronous detection of ErrPs.
Twarog, Nathaniel R.; Low, Jonathan A.; Currier, Duane G.; Miller, Greg; Chen, Taosheng; Shelat, Anang A.
2016-01-01
Phenotypic screening through high-content automated microscopy is a powerful tool for evaluating the mechanism of action of candidate therapeutics. Despite more than a decade of development, however, high content assays have yielded mixed results, identifying robust phenotypes in only a small subset of compound classes. This has led to a combinatorial explosion of assay techniques, analyzing cellular phenotypes across dozens of assays with hundreds of measurements. Here, using a minimalist three-stain assay and only 23 basic cellular measurements, we developed an analytical approach that leverages informative dimensions extracted by linear discriminant analysis to evaluate similarity between the phenotypic trajectories of different compounds in response to a range of doses. This method enabled us to visualize biologically-interpretable phenotypic tracks populated by compounds of similar mechanism of action, cluster compounds according to phenotypic similarity, and classify novel compounds by comparing them to phenotypically active exemplars. Hierarchical clustering applied to 154 compounds from over a dozen different mechanistic classes demonstrated tight agreement with published compound mechanism classification. Using 11 phenotypically active mechanism classes, classification was performed on all 154 compounds: 78% were correctly identified as belonging to one of the 11 exemplar classes or to a different unspecified class, with accuracy increasing to 89% when less phenotypically active compounds were excluded. Importantly, several apparent clustering and classification failures, including rigosertib and 5-fluoro-2’-deoxycytidine, instead revealed more complex mechanisms or off-target effects verified by more recent publications. These results show that a simple, easily replicated, minimalist high-content assay can reveal subtle variations in the cellular phenotype induced by compounds and can correctly predict mechanism of action, as long as the appropriate analytical tools are used. PMID:26886014
Twarog, Nathaniel R; Low, Jonathan A; Currier, Duane G; Miller, Greg; Chen, Taosheng; Shelat, Anang A
2016-01-01
Phenotypic screening through high-content automated microscopy is a powerful tool for evaluating the mechanism of action of candidate therapeutics. Despite more than a decade of development, however, high content assays have yielded mixed results, identifying robust phenotypes in only a small subset of compound classes. This has led to a combinatorial explosion of assay techniques, analyzing cellular phenotypes across dozens of assays with hundreds of measurements. Here, using a minimalist three-stain assay and only 23 basic cellular measurements, we developed an analytical approach that leverages informative dimensions extracted by linear discriminant analysis to evaluate similarity between the phenotypic trajectories of different compounds in response to a range of doses. This method enabled us to visualize biologically-interpretable phenotypic tracks populated by compounds of similar mechanism of action, cluster compounds according to phenotypic similarity, and classify novel compounds by comparing them to phenotypically active exemplars. Hierarchical clustering applied to 154 compounds from over a dozen different mechanistic classes demonstrated tight agreement with published compound mechanism classification. Using 11 phenotypically active mechanism classes, classification was performed on all 154 compounds: 78% were correctly identified as belonging to one of the 11 exemplar classes or to a different unspecified class, with accuracy increasing to 89% when less phenotypically active compounds were excluded. Importantly, several apparent clustering and classification failures, including rigosertib and 5-fluoro-2'-deoxycytidine, instead revealed more complex mechanisms or off-target effects verified by more recent publications. These results show that a simple, easily replicated, minimalist high-content assay can reveal subtle variations in the cellular phenotype induced by compounds and can correctly predict mechanism of action, as long as the appropriate analytical tools are used.
Using Response Times to Assess Learning Progress: A Joint Model for Responses and Response Times
ERIC Educational Resources Information Center
Wang, Shiyu; Zhang, Susu; Douglas, Jeff; Culpepper, Steven
2018-01-01
Analyzing students' growth remains an important topic in educational research. Most recently, Diagnostic Classification Models (DCMs) have been used to track skill acquisition in a longitudinal fashion, with the purpose to provide an estimate of students' learning trajectories in terms of the change of fine-grained skills overtime. Response time…
Real-time classification of vehicles by type within infrared imagery
NASA Astrophysics Data System (ADS)
Kundegorski, Mikolaj E.; Akçay, Samet; Payen de La Garanderie, Grégoire; Breckon, Toby P.
2016-10-01
Real-time classification of vehicles into sub-category types poses a significant challenge within infra-red imagery due to the high levels of intra-class variation in thermal vehicle signatures caused by aspects of design, current operating duration and ambient thermal conditions. Despite these challenges, infra-red sensing offers significant generalized target object detection advantages in terms of all-weather operation and invariance to visual camouflage techniques. This work investigates the accuracy of a number of real-time object classification approaches for this task within the wider context of an existing initial object detection and tracking framework. Specifically we evaluate the use of traditional feature-driven bag of visual words and histogram of oriented gradient classification approaches against modern convolutional neural network architectures. Furthermore, we use classical photogrammetry, within the context of current target detection and classification techniques, as a means of approximating 3D target position within the scene based on this vehicle type classification. Based on photogrammetric estimation of target position, we then illustrate the use of regular Kalman filter based tracking operating on actual 3D vehicle trajectories. Results are presented using a conventional thermal-band infra-red (IR) sensor arrangement where targets are tracked over a range of evaluation scenarios.
Two-year trajectory of fall risk in people with Parkinson’s disease: a latent class analysis
Paul, Serene S; Thackeray, Anne; Duncan, Ryan P; Cavanaugh, James T; Ellis, Theresa D; Earhart, Gammon M; Ford, Matthew P; Foreman, K Bo; Dibble, Leland E
2015-01-01
Objective To examine fall risk trajectories occurring naturally in a sample of individuals with early to middle stage Parkinson’s disease (PD). Design Latent class analysis, specifically growth mixture modeling (GMM) of longitudinal fall risk trajectories. Setting Not applicable. Participants 230 community-dwelling PD participants of a longitudinal cohort study who attended at least two of five assessments over a two year period. Interventions Not applicable. Main Outcome Measures Fall risk trajectory (low, medium or high risk) and stability of fall risk trajectory (stable or fluctuating). Fall risk was determined at 6-monthly intervals using a simple clinical tool based on fall history, freezing of gait, and gait speed. Results The GMM optimally grouped participants into three fall risk trajectories that closely mirrored baseline fall risk status (p=.001). The high fall risk trajectory was most common (42.6%) and included participants with longer and more severe disease and with higher postural instability and gait disability (PIGD) scores than the low and medium risk trajectories (p<.001). Fluctuating fall risk (posterior probability <0.8 of belonging to any trajectory) was found in only 22.6% of the sample, most commonly among individuals who were transitioning to PIGD predominance. Conclusions Regardless of their baseline characteristics, most participants had clear and stable fall risk trajectories over two years. Further investigation is required to determine whether interventions to improve gait and balance may improve fall risk trajectories in people with PD. PMID:26606871
Topological classification of periodic orbits in the Kuramoto-Sivashinsky equation
NASA Astrophysics Data System (ADS)
Dong, Chengwei
2018-05-01
In this paper, we systematically research periodic orbits of the Kuramoto-Sivashinsky equation (KSe). In order to overcome the difficulties in the establishment of one-dimensional symbolic dynamics in the nonlinear system, two basic periodic orbits can be used as basic building blocks to initialize cycle searching, and we use the variational method to numerically determine all the periodic orbits under parameter ν = 0.02991. The symbolic dynamics based on trajectory topology are very successful for classifying all short periodic orbits in the KSe. The current research can be conveniently adapted to the identification and classification of periodic orbits in other chaotic systems.
An Operational Safety and Certification Assessment of a TASAR EFB Application
NASA Technical Reports Server (NTRS)
Koczo, Stefan; Wing, David
2013-01-01
This paper presents an overview of a Traffic Aware Strategic Aircrew Requests (TASAR) Electronic Flight Bag application intended to inform the pilot of trajectory improvement opportunities while en route that result in operational benefits. The results of safety analyses and a detailed review of Federal Aviation Administration (FAA) regulatory documents that establish certification and operational approval requirements are presented for TASAR. The safety analyses indicate that TASAR has a likely Failure Effects Classification of “No Effect,” and at most, is no worse than “Minor Effect.” Based on this safety assessment and the detailed review of FAA regulatory documents that determine certification and operational approval requirements, this study concludes that TASAR can be implemented in the flight deck as a Type B software application hosted on a Class 2 Portable Electronic Device (PED) Electronic Flight Bag (EFB). This implementation approach would provide a relatively low-cost path to certification and operational approval for both retrofit and forward fit implementation, while at the same time facilitating the business case for early ADS-B IN equipage. A preliminary review by FAA certification and operational approvers of the analyses presented here confirmed that the conclusions are appropriate and that TASAR will be considered a Type B application.
Spatiotemporal analysis of land use and land cover change in the Brazilian Amazon
Li, Guiying; Moran, Emilio; Hetrick, Scott
2013-01-01
This paper provides a comparative analysis of land use and land cover (LULC) changes among three study areas with different biophysical environments in the Brazilian Amazon at multiple scales, from per-pixel, polygon, census sector, to study area. Landsat images acquired in the years of 1990/1991, 1999/2000, and 2008/2010 were used to examine LULC change trajectories with the post-classification comparison approach. A classification system composed of six classes – forest, savanna, other-vegetation (secondary succession and plantations), agro-pasture, impervious surface, and water, was designed for this study. A hierarchical-based classification method was used to classify Landsat images into thematic maps. This research shows different spatiotemporal change patterns, composition and rates among the three study areas and indicates the importance of analyzing LULC change at multiple scales. The LULC change analysis over time for entire study areas provides an overall picture of change trends, but detailed change trajectories and their spatial distributions can be better examined at a per-pixel scale. The LULC change at the polygon scale provides the information of the changes in patch sizes over time, while the LULC change at census sector scale gives new insights on how human-induced activities (e.g., urban expansion, roads, and land use history) affect LULC change patterns and rates. This research indicates the necessity to implement change detection at multiple scales for better understanding the mechanisms of LULC change patterns and rates. PMID:24127130
Nonlinear features for classification and pose estimation of machined parts from single views
NASA Astrophysics Data System (ADS)
Talukder, Ashit; Casasent, David P.
1998-10-01
A new nonlinear feature extraction method is presented for classification and pose estimation of objects from single views. The feature extraction method is called the maximum representation and discrimination feature (MRDF) method. The nonlinear MRDF transformations to use are obtained in closed form, and offer significant advantages compared to nonlinear neural network implementations. The features extracted are useful for both object discrimination (classification) and object representation (pose estimation). We consider MRDFs on image data, provide a new 2-stage nonlinear MRDF solution, and show it specializes to well-known linear and nonlinear image processing transforms under certain conditions. We show the use of MRDF in estimating the class and pose of images of rendered solid CAD models of machine parts from single views using a feature-space trajectory neural network classifier. We show new results with better classification and pose estimation accuracy than are achieved by standard principal component analysis and Fukunaga-Koontz feature extraction methods.
Trajectory planning of free-floating space robot using Particle Swarm Optimization (PSO)
NASA Astrophysics Data System (ADS)
Wang, Mingming; Luo, Jianjun; Walter, Ulrich
2015-07-01
This paper investigates the application of Particle Swarm Optimization (PSO) strategy to trajectory planning of the kinematically redundant space robot in free-floating mode. Due to the path dependent dynamic singularities, the volume of available workspace of the space robot is limited and enormous joint velocities are required when such singularities are met. In order to overcome this effect, the direct kinematics equations in conjunction with PSO are employed for trajectory planning of free-floating space robot. The joint trajectories are parametrized with the Bézier curve to simplify the calculation. Constrained PSO scheme with adaptive inertia weight is implemented to find the optimal solution of joint trajectories while specific objectives and imposed constraints are satisfied. The proposed method is not sensitive to the singularity issue due to the application of forward kinematic equations. Simulation results are presented for trajectory planning of 7 degree-of-freedom (DOF) redundant manipulator mounted on a free-floating spacecraft and demonstrate the effectiveness of the proposed method.
Going beyond Clustering in MD Trajectory Analysis: An Application to Villin Headpiece Folding
Rajan, Aruna; Freddolino, Peter L.; Schulten, Klaus
2010-01-01
Recent advances in computing technology have enabled microsecond long all-atom molecular dynamics (MD) simulations of biological systems. Methods that can distill the salient features of such large trajectories are now urgently needed. Conventional clustering methods used to analyze MD trajectories suffer from various setbacks, namely (i) they are not data driven, (ii) they are unstable to noise and changes in cut-off parameters such as cluster radius and cluster number, and (iii) they do not reduce the dimensionality of the trajectories, and hence are unsuitable for finding collective coordinates. We advocate the application of principal component analysis (PCA) and a non-metric multidimensional scaling (nMDS) method to reduce MD trajectories and overcome the drawbacks of clustering. To illustrate the superiority of nMDS over other methods in reducing data and reproducing salient features, we analyze three complete villin headpiece folding trajectories. Our analysis suggests that the folding process of the villin headpiece is structurally heterogeneous. PMID:20419160
Going beyond clustering in MD trajectory analysis: an application to villin headpiece folding.
Rajan, Aruna; Freddolino, Peter L; Schulten, Klaus
2010-04-15
Recent advances in computing technology have enabled microsecond long all-atom molecular dynamics (MD) simulations of biological systems. Methods that can distill the salient features of such large trajectories are now urgently needed. Conventional clustering methods used to analyze MD trajectories suffer from various setbacks, namely (i) they are not data driven, (ii) they are unstable to noise and changes in cut-off parameters such as cluster radius and cluster number, and (iii) they do not reduce the dimensionality of the trajectories, and hence are unsuitable for finding collective coordinates. We advocate the application of principal component analysis (PCA) and a non-metric multidimensional scaling (nMDS) method to reduce MD trajectories and overcome the drawbacks of clustering. To illustrate the superiority of nMDS over other methods in reducing data and reproducing salient features, we analyze three complete villin headpiece folding trajectories. Our analysis suggests that the folding process of the villin headpiece is structurally heterogeneous.
Application of Modern Fortran to Spacecraft Trajectory Design and Optimization
NASA Technical Reports Server (NTRS)
Williams, Jacob; Falck, Robert D.; Beekman, Izaak B.
2018-01-01
In this paper, applications of the modern Fortran programming language to the field of spacecraft trajectory optimization and design are examined. Modern object-oriented Fortran has many advantages for scientific programming, although many legacy Fortran aerospace codes have not been upgraded to use the newer standards (or have been rewritten in other languages perceived to be more modern). NASA's Copernicus spacecraft trajectory optimization program, originally a combination of Fortran 77 and Fortran 95, has attempted to keep up with modern standards and makes significant use of the new language features. Various algorithms and methods are presented from trajectory tools such as Copernicus, as well as modern Fortran open source libraries and other projects.
NASA Astrophysics Data System (ADS)
Wang, Guochang; Cheng, Guojian; Carr, Timothy R.
2013-04-01
The organic-rich Marcellus Shale was deposited in a foreland basin during Middle Devonian. In terms of mineral composition and organic matter richness, we define seven mudrock lithofacies: three organic-rich lithofacies and four organic-poor lithofacies. The 3D lithofacies model is very helpful to determine geologic and engineering sweet spots, and consequently useful for designing horizontal well trajectories and stimulation strategies. The NeuroEvolution of Augmenting Topologies (NEAT) is relatively new idea in the design of neural networks, and shed light on classification (i.e., Marcellus Shale lithofacies prediction). We have successfully enhanced the capability and efficiency of NEAT in three aspects. First, we introduced two new attributes of node gene, the node location and recurrent connection (RCC), to increase the calculation efficiency. Second, we evolved the population size from an initial small value to big, instead of using the constant value, which saves time and computer memory, especially for complex learning tasks. Third, in multiclass pattern recognition problems, we combined feature selection of input variables and modular neural network to automatically select input variables and optimize network topology for each binary classifier. These improvements were tested and verified by true if an odd number of its arguments are true and false otherwise (XOR) experiments, and were powerful for classification.
Stationkeeping of Lissajous Trajectories in the Earth-Moon System with Applications to ARTEMIS
NASA Technical Reports Server (NTRS)
Folta, D. C.; Pavlak, T. A.; Howell, K. C.; Woodard, M. A.; Woodfork, D. W.
2010-01-01
In the last few decades, several missions have successfully exploited trajectories near the.Sun-Earth L1 and L2 libration points. Recently, the collinear libration points in the Earth-Moon system have emerged as locations with immediate application. Most libration point orbits, in any system, are inherently unstable. and must be controlled. To this end, several stationkeeping strategies are considered for application to ARTEMIS. Two approaches are examined to investigate the stationkeeping problem in this regime and the specific options. available for ARTEMIS given the mission and vehicle constraints. (I) A baseline orbit-targeting approach controls the vehicle to remain near a nominal trajectory; a related global optimum search method searches all possible maneuver angles to determine an optimal angle and magnitude; and (2) an orbit continuation method, with various formulations determines maneuver locations and minimizes costs. Initial results indicate that consistent stationkeeping costs can be achieved with both approaches and the costs are reasonable. These methods are then applied to Lissajous trajectories representing a baseline ARTEMIS libration orbit trajectory.
A wavefront reconstruction method for 3-D cylindrical subsurface radar imaging.
Flores-Tapia, Daniel; Thomas, Gabriel; Pistorius, Stephen
2008-10-01
In recent years, the use of radar technology has been proposed in a wide range of subsurface imaging applications. Traditionally, linear scan trajectories are used to acquire data in most subsurface radar applications. However, novel applications, such as breast microwave imaging and wood inspection, require the use of nonlinear scan trajectories in order to adjust to the geometry of the scanned area. This paper proposes a novel reconstruction algorithm for subsurface radar data acquired along cylindrical scan trajectories. The spectrum of the collected data is processed in order to locate the spatial origin of the target reflections and remove the spreading of the target reflections which results from the different signal travel times along the scan trajectory. The proposed algorithm was successfully tested using experimental data collected from phantoms that mimic high contrast subsurface radar scenarios, yielding promising results. Practical considerations such as spatial resolution and sampling constraints are discussed and illustrated as well.
Mixed ethnicity and behavioural problems in the Millennium Cohort Study
Zilanawala, Afshin; Sacker, Amanda; Kelly, Yvonne
2018-01-01
Background The population of mixed ethnicity individuals in the UK is growing. Despite this demographic trend, little is known about mixed ethnicity children and their problem behaviours. We examine trajectories of behavioural problems among non-mixed and mixed ethnicity children from early to middle childhood using nationally representative cohort data in the UK. Methods Data from 16 330 children from the Millennium Cohort Study with total difficulties scores were analysed. We estimated trajectories of behavioural problems by mixed ethnicity using growth curve models. Results White mixed (mean total difficulties score: 8.3), Indian mixed (7.7), Pakistani mixed (8.9) and Bangladeshi mixed (7.2) children had fewer problem behaviours than their non-mixed counterparts at age 3 (9.4, 10.1, 13.1 and 11.9, respectively). White mixed, Pakistani mixed and Bangladeshi mixed children had growth trajectories in problem behaviours significantly different from that of their non-mixed counterparts. Conclusions Using a detailed mixed ethnic classification revealed diverging trajectories between some non-mixed and mixed children across the early life course. Future studies should investigate the mechanisms, which may influence increasing behavioural problems in mixed ethnicity children. PMID:26912571
Freezer or non-freezer: clinical assessment of freezing of gait.
Snijders, Anke H; Haaxma, Charlotte A; Hagen, Yolien J; Munneke, Marten; Bloem, Bastiaan R
2012-02-01
Freezing of gait (FOG) is both common and debilitating in patients with Parkinson's disease (PD). Future pathophysiology studies will depend critically upon adequate classification of patients as being either 'freezers' or 'non-freezers'. This classification should be based ideally upon objective confirmation by an experienced observer during clinical assessment. Given the known difficulties to elicit FOG when examining patients, we aimed to investigate which simple clinical test would be the most sensitive to provoke FOG objectively. We examined 50 patients with PD, including 32 off-state freezers (defined as experiencing subjective 'gluing of the feet to the floor'). Assessment including a FOG trajectory (three trials: normal speed, fast speed, and with dual tasking) and several turning variants (180° vs. 360° turns; leftward vs. rightward turns; wide vs. narrow turning; and slow vs. fast turns). Sensitivity of the entire assessment to provoke FOG in subjective freezers was 0.74, specificity was 0.94. The most effective test to provoke FOG was rapid 360° turns in both directions and, if negative, combined with a gait trajectory with dual tasking. Repeated testing improved the diagnostic yield. The least informative tests included wide turns, 180° turns or normal speed full turns. Sensitivity to provoke objective FOG in subjective freezers was 0.65 for the rapid full turns in both directions and 0.63 for the FOG trajectory. The most efficient way to objectively ascertain FOG is asking patients to repeatedly make rapid 360° narrow turns from standstill, on the spot and in both directions. Copyright © 2011 Elsevier Ltd. All rights reserved.
Du, Hailong; Hu, Lei; Li, Changsheng; He, Chunqing; Zhang, Lihai; Tang, Peifu
2015-03-01
Balancing reduction accuracy with soft-tissue preservation is a challenge in orthopaedics. Computer-assisted orthopaedic surgery (CAOS) can improve accuracy and reduce radiation exposure. However, previous reports have not summarized the fracture patterns to which CAOS has been applied. We used a CAOS system and a stereolithography model to define a new fracture classification. Twenty reduction tests were performed to evaluate the effectiveness of preoperative trajectory planning. Twenty tests ran automatically and smoothly. Only three slight scratches occurred. Seventy-six path points represented displacement deviations of < 2 mm (average < 1 mm) and angulation deviation of < 1.5°. Because of the strength of muscles, mechanical sensors are used to prevent iatrogenic soft-tissue injury. Secondary fractures are prevented mainly through preoperative trajectory planning. Based on our data, a 1 mm gap between the edges of fractures spikes is sufficient to avoid emergency braking from spike interference. Copyright © 2014 John Wiley & Sons, Ltd.
Kenzie, Erin S.; Parks, Elle L.; Bigler, Erin D.; Wright, David W.; Lim, Miranda M.; Chesnutt, James C.; Hawryluk, Gregory W. J.; Gordon, Wayne; Wakeland, Wayne
2018-01-01
Despite increasing public awareness and a growing body of literature on the subject of concussion, or mild traumatic brain injury, an urgent need still exists for reliable diagnostic measures, clinical care guidelines, and effective treatments for the condition. Complexity and heterogeneity complicate research efforts and indicate the need for innovative approaches to synthesize current knowledge in order to improve clinical outcomes. Methods from the interdisciplinary field of systems science, including models of complex systems, have been increasingly applied to biomedical applications and show promise for generating insight for traumatic brain injury. The current study uses causal-loop diagramming to visualize relationships between factors influencing the pathophysiology and recovery trajectories of concussive injury, including persistence of symptoms and deficits. The primary output is a series of preliminary systems maps detailing feedback loops, intrinsic dynamics, exogenous drivers, and hubs across several scales, from micro-level cellular processes to social influences. Key system features, such as the role of specific restorative feedback processes and cross-scale connections, are examined and discussed in the context of recovery trajectories. This systems approach integrates research findings across disciplines and allows components to be considered in relation to larger system influences, which enables the identification of research gaps, supports classification efforts, and provides a framework for interdisciplinary collaboration and communication—all strides that would benefit diagnosis, prognosis, and treatment in the clinic. PMID:29670568
Complexity Science Applications to Dynamic Trajectory Management: Research Strategies
NASA Technical Reports Server (NTRS)
Sawhill, Bruce; Herriot, James; Holmes, Bruce J.; Alexandrov, Natalia
2009-01-01
The promise of the Next Generation Air Transportation System (NextGen) is strongly tied to the concept of trajectory-based operations in the national airspace system. Existing efforts to develop trajectory management concepts are largely focused on individual trajectories, optimized independently, then de-conflicted among each other, and individually re-optimized, as possible. The benefits in capacity, fuel, and time are valuable, though perhaps could be greater through alternative strategies. The concept of agent-based trajectories offers a strategy for automation of simultaneous multiple trajectory management. The anticipated result of the strategy would be dynamic management of multiple trajectories with interacting and interdependent outcomes that satisfy multiple, conflicting constraints. These constraints would include the business case for operators, the capacity case for the Air Navigation Service Provider (ANSP), and the environmental case for noise and emissions. The benefits in capacity, fuel, and time might be improved over those possible under individual trajectory management approaches. The proposed approach relies on computational agent-based modeling (ABM), combinatorial mathematics, as well as application of "traffic physics" concepts to the challenge, and modeling and simulation capabilities. The proposed strategy could support transforming air traffic control from managing individual aircraft behaviors to managing systemic behavior of air traffic in the NAS. A system built on the approach could provide the ability to know when regions of airspace approach being "full," that is, having non-viable local solution space for optimizing trajectories in advance.
Broken-Plane Maneuver Applications for Earth to Mars Trajectories
NASA Technical Reports Server (NTRS)
Abilleira, Fernando
2007-01-01
Optimization techniques are critical when investigating Earth to Mars trajectories since they have the potential of reducing the total (delta)V of a mission. A deep space maneuver (DSM) executed during the cruise may improve a trajectory by reducing the total mission V. Nonetheless, DSMs not only may improve trajectory performance (from an energetic point of view) but also open up new families of trajectories that would satisfy very specific mission requirements not achievable with ballistic trajectories. In the following pages, various specific examples showing the potential advantages of the usage of broken plane maneuvers will be introduced. These examples correspond to possible scenarios for Earth to Mars trajectories during the next decade (2010-2020).
Spatio-Temporal Pattern Mining on Trajectory Data Using Arm
NASA Astrophysics Data System (ADS)
Khoshahval, S.; Farnaghi, M.; Taleai, M.
2017-09-01
Preliminary mobile was considered to be a device to make human connections easier. But today the consumption of this device has been evolved to a platform for gaming, web surfing and GPS-enabled application capabilities. Embedding GPS in handheld devices, altered them to significant trajectory data gathering facilities. Raw GPS trajectory data is a series of points which contains hidden information. For revealing hidden information in traces, trajectory data analysis is needed. One of the most beneficial concealed information in trajectory data is user activity patterns. In each pattern, there are multiple stops and moves which identifies users visited places and tasks. This paper proposes an approach to discover user daily activity patterns from GPS trajectories using association rules. Finding user patterns needs extraction of user's visited places from stops and moves of GPS trajectories. In order to locate stops and moves, we have implemented a place recognition algorithm. After extraction of visited points an advanced association rule mining algorithm, called Apriori was used to extract user activity patterns. This study outlined that there are useful patterns in each trajectory that can be emerged from raw GPS data using association rule mining techniques in order to find out about multiple users' behaviour in a system and can be utilized in various location-based applications.
7 CFR 27.64 - Application for review of classification and for Micronaire determination; filing.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 7 Agriculture 2 2011-01-01 2011-01-01 false Application for review of classification and for... AGRICULTURE COMMODITY STANDARDS AND STANDARD CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification Reviews and Micronaire Determinations § 27.64 Application for review of...
7 CFR 27.64 - Application for review of classification and for Micronaire determination; filing.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 7 Agriculture 2 2010-01-01 2010-01-01 false Application for review of classification and for... AGRICULTURE COMMODITY STANDARDS AND STANDARD CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification Reviews and Micronaire Determinations § 27.64 Application for review of...
Dennis L. Mengel; D. Thompson Tew; [Editors
1991-01-01
Eighteen papers representing four categories-Regional Overviews; Classification System Development; Classification System Interpretation; Mapping/GIS Applications in Classification Systems-present the state of the art in forest-land classification and evaluation in the South. In addition, nine poster papers are presented.
Note on the displacement of a trajectory of hyperbolic motion in curved space-time
NASA Astrophysics Data System (ADS)
Krikorian, R. A.
2012-04-01
The object of this note is to present a physical application of the theory of the infinitesimal deformations or displacements of curves developed by Yano using the concept of Lie derivative. It is shown that an infinitesimal point transformation which carries a given trajectory of hyperbolic motion into a trajectory of the same type, and preserves the affine parametrization of the trajectory, defines a homothetic motion.
NASA Astrophysics Data System (ADS)
Archer, Reginald S.
This research focuses on measuring and monitoring long term recovery progress from the impacts of Hurricane Katrina on New Orleans, LA. Remote sensing has frequently been used for emergency response and damage assessment after natural disasters. However, techniques for analysis of long term disaster recovery using remote sensing have not been widely explored. With increased availability and lower costs, remote sensing offers an objective perspective, systematic and repeatable analysis, and provides a substitute to multiple site visits. In addition, remote sensing allows access to large geographical areas and areas where ground access may be disrupted, restricted or denied. This dissertation addressed the primary difficulties involved in the development of change detection methods capable of detecting changes experienced by disaster recovery indicators. Maximum likelihood classification and post-classification change detection were applied to multi-temporal high resolution aerial images to quantitatively measure the progress of recovery. Images were classified to automatically identify disaster recovery indicators and exploit the indicators that are visible within each image. The spectral analysis demonstrated that employing maximum likelihood classification to high resolution true color aerial images performed adequately and provided a good indication of spectral pattern recognition, despite the limited spectral information. Applying the change detection to the classified images was effective for determining the temporal trajectory of indicators categorized as blue tarps, FEMA trailers, houses, vegetation, bare earth and pavement. The results of the post classification change detection revealed a dominant change trajectory from bluetarp to house, as damaged houses became permanently repaired. Specifically, the level of activity of blue tarps, housing, vegetation, FEMA trailers (temporary housing) pavement and bare earth were derived from aerial image processing to measure and monitor the progress of recovery. Trajectories of recovery for each individual indicator were examined to provide a better understanding of activity during reconstruction. A collection of spatial metrics was explored in order to identify spatial patterns and characterize classes in terms of patches of pixels. One of the key findings of the spatial analysis is that patch shapes were more complex in the presence of debris and damaged or destroyed buildings. The combination of spectral, temporal, and spatial analysis provided a satisfactory, though limited, solution to the question of whether remote sensing alone, can be used to quantitatively assess and monitor the progress of long term recovery following a major disaster. The research described in this dissertation provided a detailed illustration of the level of activity experienced by different recovery indicators during the long term recovery process. It also addressed the primary difficulties involved in the development of change detection methods capable of detecting changes experienced by disaster recovery indicators identified from classified high resolution true color aerial imagery. The results produced in this research demonstrate that the observed trajectories for actual indicators of recovery indicate different levels of recovery activity even within the same community. The level of activity of the long term reconstruction phase observed in the Kates model is not consistent with the level of activity of key recovery indicators in the Lower 9th Ward during the same period. Used in the proper context, these methods and results provide decision making information for determining resources. KEYWORDS: Change detection, classification, Katrina, New Orleans, remote sensing, disaster recovery, spatial metrics
Computer program documentation user information for the MPAD trajectory tape print program (TRJPR1)
NASA Technical Reports Server (NTRS)
Gibbs, P. M.
1981-01-01
The Trajectory Tape Print Program (TRJPR1) was developed to print applicable information from a Space Trajectory tape created by the Mission Planning and Analysis Division (MPAD) in the MPAD Common Format for the on-orbit phase of the Mission. Instructions for TRJPR1's use are given.
NASA Astrophysics Data System (ADS)
Deschenes, Sylvain; Sheng, Yunlong; Chevrette, Paul C.
1998-03-01
3D object classification from 2D IR images is shown. The wavelet transform is used for edge detection. Edge tracking is used for removing noise effectively int he wavelet transform. The invariant Fourier descriptor is used to describe the contour curves. Invariance under out-of-plane rotation is achieved by the feature space trajectory neural network working as a classifier.
Numeric Computation of the Radar Cross Section of In-flight Projectiles
2016-11-01
SUBJECT TERMS computational electromagnetics , radar signature, ballistic trajectory, radar cross section, RCS 16. SECURITY CLASSIFICATION OF: 17...under the generic category of rockets, artillery, and mortar (RAM). The electromagnetic (EM) modeling team at the US Army Research Laboratory (ARL) is...ARL-TR-5145. 5. Balanis C. Advanced engineering electromagnetics . New York (NY): Wiley; 1989. 6. Ruck G, Barrick DE, Stuart WD, Krichbaum CK
Reentry trajectory optimization based on a multistage pseudospectral method.
Zhao, Jiang; Zhou, Rui; Jin, Xuelian
2014-01-01
Of the many direct numerical methods, the pseudospectral method serves as an effective tool to solve the reentry trajectory optimization for hypersonic vehicles. However, the traditional pseudospectral method is time-consuming due to large number of discretization points. For the purpose of autonomous and adaptive reentry guidance, the research herein presents a multistage trajectory control strategy based on the pseudospectral method, capable of dealing with the unexpected situations in reentry flight. The strategy typically includes two subproblems: the trajectory estimation and trajectory refining. In each processing stage, the proposed method generates a specified range of trajectory with the transition of the flight state. The full glide trajectory consists of several optimal trajectory sequences. The newly focused geographic constraints in actual flight are discussed thereafter. Numerical examples of free-space flight, target transition flight, and threat avoidance flight are used to show the feasible application of multistage pseudospectral method in reentry trajectory optimization.
Reentry Trajectory Optimization Based on a Multistage Pseudospectral Method
Zhou, Rui; Jin, Xuelian
2014-01-01
Of the many direct numerical methods, the pseudospectral method serves as an effective tool to solve the reentry trajectory optimization for hypersonic vehicles. However, the traditional pseudospectral method is time-consuming due to large number of discretization points. For the purpose of autonomous and adaptive reentry guidance, the research herein presents a multistage trajectory control strategy based on the pseudospectral method, capable of dealing with the unexpected situations in reentry flight. The strategy typically includes two subproblems: the trajectory estimation and trajectory refining. In each processing stage, the proposed method generates a specified range of trajectory with the transition of the flight state. The full glide trajectory consists of several optimal trajectory sequences. The newly focused geographic constraints in actual flight are discussed thereafter. Numerical examples of free-space flight, target transition flight, and threat avoidance flight are used to show the feasible application of multistage pseudospectral method in reentry trajectory optimization. PMID:24574929
Bayesian Decision Tree for the Classification of the Mode of Motion in Single-Molecule Trajectories
Türkcan, Silvan; Masson, Jean-Baptiste
2013-01-01
Membrane proteins move in heterogeneous environments with spatially (sometimes temporally) varying friction and with biochemical interactions with various partners. It is important to reliably distinguish different modes of motion to improve our knowledge of the membrane architecture and to understand the nature of interactions between membrane proteins and their environments. Here, we present an analysis technique for single molecule tracking (SMT) trajectories that can determine the preferred model of motion that best matches observed trajectories. The method is based on Bayesian inference to calculate the posteriori probability of an observed trajectory according to a certain model. Information theory criteria, such as the Bayesian information criterion (BIC), the Akaike information criterion (AIC), and modified AIC (AICc), are used to select the preferred model. The considered group of models includes free Brownian motion, and confined motion in 2nd or 4th order potentials. We determine the best information criteria for classifying trajectories. We tested its limits through simulations matching large sets of experimental conditions and we built a decision tree. This decision tree first uses the BIC to distinguish between free Brownian motion and confined motion. In a second step, it classifies the confining potential further using the AIC. We apply the method to experimental Clostridium Perfingens -toxin (CPT) receptor trajectories to show that these receptors are confined by a spring-like potential. An adaptation of this technique was applied on a sliding window in the temporal dimension along the trajectory. We applied this adaptation to experimental CPT trajectories that lose confinement due to disaggregation of confining domains. This new technique adds another dimension to the discussion of SMT data. The mode of motion of a receptor might hold more biologically relevant information than the diffusion coefficient or domain size and may be a better tool to classify and compare different SMT experiments. PMID:24376584
Delivering Sound Energy along an Arbitrary Convex Trajectory
Zhao, Sipei; Hu, Yuxiang; Lu, Jing; Qiu, Xiaojun; Cheng, Jianchun; Burnett, Ian
2014-01-01
Accelerating beams have attracted considerable research interest due to their peculiar properties and various applications. Although there have been numerous research on the generation and application of accelerating light beams, few results have been published on the generation of accelerating acoustic beams. Here we report on the experimental observation of accelerating acoustic beams along arbitrary convex trajectories. The desired trajectory is projected to the spatial phase profile on the boundary which is discretized and sampled spatially. The sound field distribution is formulated with the Green function and the integral equation method. Both the paraxial and the non-paraxial regimes are examined and observed in the experiments. The effect of obstacle scattering in the sound field is also investigated and the results demonstrate that the approach is robust against obstacle scattering. The realization of accelerating acoustic beams will have an impact on various applications where acoustic information and energy are required to be delivered along an arbitrary convex trajectory. PMID:25316353
Classifying aerosol type using in situ surface spectral aerosol optical properties
NASA Astrophysics Data System (ADS)
Schmeisser, Lauren; Andrews, Elisabeth; Ogren, John A.; Sheridan, Patrick; Jefferson, Anne; Sharma, Sangeeta; Kim, Jeong Eun; Sherman, James P.; Sorribas, Mar; Kalapov, Ivo; Arsov, Todor; Angelov, Christo; Mayol-Bracero, Olga L.; Labuschagne, Casper; Kim, Sang-Woo; Hoffer, András; Lin, Neng-Huei; Chia, Hao-Ping; Bergin, Michael; Sun, Junying; Liu, Peng; Wu, Hao
2017-10-01
Knowledge of aerosol size and composition is important for determining radiative forcing effects of aerosols, identifying aerosol sources and improving aerosol satellite retrieval algorithms. The ability to extrapolate aerosol size and composition, or type, from intensive aerosol optical properties can help expand the current knowledge of spatiotemporal variability in aerosol type globally, particularly where chemical composition measurements do not exist concurrently with optical property measurements. This study uses medians of the scattering Ångström exponent (SAE), absorption Ångström exponent (AAE) and single scattering albedo (SSA) from 24 stations within the NOAA/ESRL Federated Aerosol Monitoring Network to infer aerosol type using previously published aerosol classification schemes.Three methods are implemented to obtain a best estimate of dominant aerosol type at each station using aerosol optical properties. The first method plots station medians into an AAE vs. SAE plot space, so that a unique combination of intensive properties corresponds with an aerosol type. The second typing method expands on the first by introducing a multivariate cluster analysis, which aims to group stations with similar optical characteristics and thus similar dominant aerosol type. The third and final classification method pairs 3-day backward air mass trajectories with median aerosol optical properties to explore the relationship between trajectory origin (proxy for likely aerosol type) and aerosol intensive parameters, while allowing for multiple dominant aerosol types at each station.The three aerosol classification methods have some common, and thus robust, results. In general, estimating dominant aerosol type using optical properties is best suited for site locations with a stable and homogenous aerosol population, particularly continental polluted (carbonaceous aerosol), marine polluted (carbonaceous aerosol mixed with sea salt) and continental dust/biomass sites (dust and carbonaceous aerosol); however, current classification schemes perform poorly when predicting dominant aerosol type at remote marine and Arctic sites and at stations with more complex locations and topography where variable aerosol populations are not well represented by median optical properties. Although the aerosol classification methods presented here provide new ways to reduce ambiguity in typing schemes, there is more work needed to find aerosol typing methods that are useful for a larger range of geographic locations and aerosol populations.
Trajectory of a synthetic jet issuing into a high Reynolds number turbulent boundary layer
NASA Astrophysics Data System (ADS)
Berk, Tim; Baidya, Rio; de Silva, Charitha; Marusic, Ivan; Hutchins, Nicholas; Ganapathisubramani, Bharathram
2017-11-01
Synthetic jets are zero-net-mass-flux actuators that can be used in a range of flow control applications. For several pulsed/synthetic jet in cross-flow applications the variation of the jet trajectory in the mean flow with jet and boundary layer parameters is important. This trajectory will provide an indication of the penetration depth of the pulsed/synthetic jet into a boundary layer. Trajectories of a synthetic jet in a turbulent boundary layer are measured for a range of actuation parameters in both low- and high Reynolds numbers (up to Reτ = 13000). The important parameters influencing the trajectory are determined from these measurements. The Reynolds number of the boundary layer is shown to only have a small effect on the trajectory. In fact, the critical parameters are found to be the Strouhal number of the jet based on jet dimensions as well as the velocity ratio of the jet (defined as a ratio between peak jet velocity and the freestream velocity). An expression for the trajectory of the synthetic (or pulsed) jet is derived from the data, which (in the limit) is consistent with known expressions for the trajectory of a steady jet in a cross-flow. T.B. and B.G. are grateful to the support from the ERC (Grant Agreement No. 277472) and the EPSRC (Grant ref. no. EP/L006383/1).
Atmospheric guidance law for planar skip trajectories
NASA Technical Reports Server (NTRS)
Mease, K. D.; Mccreary, F. A.
1985-01-01
The applicability of an approximate, closed-form, analytical solution to the equations of motion, as a basis for a deterministic guidance law for controlling the in-plane motion during a skip trajectory, is investigated. The derivation of the solution by the method of matched asymptotic expansions is discussed. Specific issues that arise in the application of the solution to skip trajectories are addressed. Based on the solution, an explicit formula for the approximate energy loss due to an atmospheric pass is derived. A guidance strategy is proposed that illustrates the use of the approximate solution. A numerical example shows encouraging performance.
NASA Technical Reports Server (NTRS)
Raiszadeh, Behzad; Queen, Eric M.; Hotchko, Nathaniel J.
2009-01-01
A capability to simulate trajectories of multiple interacting rigid bodies has been developed, tested and validated. This capability uses the Program to Optimize Simulated Trajectories II (POST 2). The standard version of POST 2 allows trajectory simulation of multiple bodies without force interaction. In the current implementation, the force interaction between the parachute and the suspended bodies has been modeled using flexible lines, allowing accurate trajectory simulation of the individual bodies in flight. The POST 2 multibody capability is intended to be general purpose and applicable to any parachute entry trajectory simulation. This research paper explains the motivation for multibody parachute simulation, discusses implementation methods, and presents validation of this capability.
Automated Sensitivity Analysis of Interplanetary Trajectories
NASA Technical Reports Server (NTRS)
Knittel, Jeremy; Hughes, Kyle; Englander, Jacob; Sarli, Bruno
2017-01-01
This work describes a suite of Python tools known as the Python EMTG Automated Trade Study Application (PEATSA). PEATSA was written to automate the operation of trajectory optimization software, simplify the process of performing sensitivity analysis, and was ultimately found to out-perform a human trajectory designer in unexpected ways. These benefits will be discussed and demonstrated on sample mission designs.
Program For Simulation Of Trajectories And Events
NASA Technical Reports Server (NTRS)
Gottlieb, Robert G.
1992-01-01
Universal Simulation Executive (USE) program accelerates and eases generation of application programs for numerical simulation of continuous trajectories interrupted by or containing discrete events. Developed for simulation of multiple spacecraft trajectories with events as one spacecraft crossing the equator, two spacecraft meeting or parting, or firing rocket engine. USE also simulates operation of chemical batch processing factory. Written in Ada.
Lee, Christopher S; Mudd, James O; Gelow, Jill M; Nguyen, Thuan; Hiatt, Shirin O; Green, Jennifer K; Denfeld, Quin E; Bidwell, Julie T; Grady, Kathleen L
2014-01-01
Unexplained heterogeneity in response to ventricular assist device (VAD) implantation for the management of advanced heart failure impedes our ability to predict favorable outcomes, provide adequate patient and family education, and personalize monitoring and symptom management strategies. The purpose of this article was to describe the background and the design of a study entitled "Profiling Biobehavioral Responses to Mechanical Support in Advanced Heart Failure" (PREMISE). PREMISE is a prospective cohort study designed to (1) identify common and distinct trajectories of change in physical and psychological symptom burden; (2) characterize common trajectories of change in serum biomarkers of myocardial stress, systemic inflammation, and endothelial dysfunction; and (3) quantify associations between symptoms and biomarkers of pathogenesis in adults undergoing VAD implantation. Latent growth mixture modeling, including parallel process and cross-classification modeling, will be used to address the study aims and will entail identifying trajectories, quantifying associations between trajectories and both clinical and quality-of-life outcomes, and identifying predictors of favorable symptom and biomarker responses to VAD implantation. Research findings from the PREMISE study will be used to enhance shared patient and provider decision making and to shape a much-needed new breed of interventions and clinical management strategies that are tailored to differential symptom and pathogenic responses to VAD implantation.
Real-Time Detection of In-flight Aircraft Damage
Blair, Brenton; Lee, Herbert K. H.; Davies, Misty
2017-10-02
When there is damage to an aircraft, it is critical to be able to quickly detect and diagnose the problem so that the pilot can attempt to maintain control of the aircraft and land it safely. We develop methodology for real-time classification of flight trajectories to be able to distinguish between an undamaged aircraft and five different damage scenarios. Principal components analysis allows a lower-dimensional representation of multi-dimensional trajectory information in time. Random Forests provide a computationally efficient approach with sufficient accuracy to be able to detect and classify the different scenarios in real-time. We demonstrate our approach by classifyingmore » realizations of a 45 degree bank angle generated from the Generic Transport Model flight simulator in collaboration with NASA.« less
NASA Astrophysics Data System (ADS)
Shelomentsev, A. G.; Medvedev, M. A.; Isaichik, K. F.; Dyomina, M. I.; Berg, I. A.; Kit, M.
2017-12-01
This paper discusses comparative analysis of trajectories in the development of participating countries of the Eurasian Economic Union (EAEC) in a two-dimensional phase space. The coordinates in the space is represented by the value of a dynamic variable that is a key indicator of the country's development, and the rate of its relative growth. This allows for construction of a ternary classification diagram describing competitive behavior strategies of countries in question. The comparative analysis was run for two primary factors: the size of investment in the main capital and R&D spendings. The authors carried out analysis and identification of competitive strategies for the behavior of the EAEC countries, as well as he proposed conclusions and recommendations on improving the policy of economic development.
Real-Time Detection of In-flight Aircraft Damage
DOE Office of Scientific and Technical Information (OSTI.GOV)
Blair, Brenton; Lee, Herbert K. H.; Davies, Misty
When there is damage to an aircraft, it is critical to be able to quickly detect and diagnose the problem so that the pilot can attempt to maintain control of the aircraft and land it safely. We develop methodology for real-time classification of flight trajectories to be able to distinguish between an undamaged aircraft and five different damage scenarios. Principal components analysis allows a lower-dimensional representation of multi-dimensional trajectory information in time. Random Forests provide a computationally efficient approach with sufficient accuracy to be able to detect and classify the different scenarios in real-time. We demonstrate our approach by classifyingmore » realizations of a 45 degree bank angle generated from the Generic Transport Model flight simulator in collaboration with NASA.« less
A flexible and qualitatively stable model for cell cycle dynamics including DNA damage effects.
Jeffries, Clark D; Johnson, Charles R; Zhou, Tong; Simpson, Dennis A; Kaufmann, William K
2012-01-01
This paper includes a conceptual framework for cell cycle modeling into which the experimenter can map observed data and evaluate mechanisms of cell cycle control. The basic model exhibits qualitative stability, meaning that regardless of magnitudes of system parameters its instances are guaranteed to be stable in the sense that all feasible trajectories converge to a certain trajectory. Qualitative stability can also be described by the signs of real parts of eigenvalues of the system matrix. On the biological side, the resulting model can be tuned to approximate experimental data pertaining to human fibroblast cell lines treated with ionizing radiation, with or without disabled DNA damage checkpoints. Together these properties validate a fundamental, first order systems view of cell dynamics. Classification Codes: 15A68.
An inverse dynamics approach to trajectory optimization for an aerospace plane
NASA Technical Reports Server (NTRS)
Lu, Ping
1992-01-01
An inverse dynamics approach for trajectory optimization is proposed. This technique can be useful in many difficult trajectory optimization and control problems. The application of the approach is exemplified by ascent trajectory optimization for an aerospace plane. Both minimum-fuel and minimax types of performance indices are considered. When rocket augmentation is available for ascent, it is shown that accurate orbital insertion can be achieved through the inverse control of the rocket in the presence of disturbances.
Davis, Jordan P; Dumas, Tara M; Berey, Benjamin; Merrin, Gabriel J; Tan, Kevin; Madden, Danielle R
2018-05-01
Justice involved youth exposed to multiple forms of victimization (i.e., poly-victimization) may be at risk for long term substance use problems and difficulty in self-regulation, placing them at higher risk of long-term problematic behaviors. This study empirically identifies victimization classifications in a sample of justice involved youth and how long-term binge drinking is related to victimization experiences. We further sought to understand how self-regulatory abilities such as impulse control and emotion regulation effect emergent profiles and binge drinking trajectories. Based on a sample of 1354 justice involved youth from 15 to 25 years old, classes of victimization were extracted. Emergent classes were examined in relationship to their binge drinking trajectories using latent growth models. Finally, self-regulation was examined as a predictor of binge drinking trajectories across emergent classes. The analyses indicated three classes of victimization: poly-victimized, indirectly victimized, and lowly victimized. Latent growth models revealed that the poly-victimized class had significantly steeper growth in binge drinking as compared to the indirect and low victimized patterns. Impulse and emotional regulation both significantly decelerated binge drinking only for the indirect victimization group. Findings highlight the need to focus on poly-victimization in understanding binge drinking trajectories as well as the role impulse control and emotional regulation play among justice involved youth. Findings are discussed through the lens of adolescent development, coping strategies, and early traumatic experiences. Copyright © 2018 Elsevier B.V. All rights reserved.
Ares I-X Best Estimated Trajectory Analysis and Results
NASA Technical Reports Server (NTRS)
Karlgaard, Christopher D.; Beck, Roger E.; Starr, Brett R.; Derry, Stephen D.; Brandon, Jay; Olds, Aaron D.
2011-01-01
The Ares I-X trajectory reconstruction produced best estimated trajectories of the flight test vehicle ascent through stage separation, and of the first and upper stage entries after separation. The trajectory reconstruction process combines on-board, ground-based, and atmospheric measurements to produce the trajectory estimates. The Ares I-X vehicle had a number of on-board and ground based sensors that were available, including inertial measurement units, radar, air-data, and weather balloons. However, due to problems with calibrations and/or data, not all of the sensor data were used. The trajectory estimate was generated using an Iterative Extended Kalman Filter algorithm, which is an industry standard processing algorithm for filtering and estimation applications. This paper describes the methodology and results of the trajectory reconstruction process, including flight data preprocessing and input uncertainties, trajectory estimation algorithms, output transformations, and comparisons with preflight predictions.
Ares I-X Best Estimated Trajectory and Comparison with Pre-Flight Predictions
NASA Technical Reports Server (NTRS)
Karlgaard, Christopher D.; Beck, Roger E.; Derry, Stephen D.; Brandon, Jay M.; Starr, Brett R.; Tartabini, Paul V.; Olds, Aaron D.
2011-01-01
The Ares I-X trajectory reconstruction produced best estimated trajectories of the flight test vehicle ascent through stage separation, and of the first and upper stage entries after separation. The trajectory reconstruction process combines on-board, ground-based, and atmospheric measurements to produce the trajectory estimates. The Ares I-X vehicle had a number of on-board and ground based sensors that were available, including inertial measurement units, radar, air- data, and weather balloons. However, due to problems with calibrations and/or data, not all of the sensor data were used. The trajectory estimate was generated using an Iterative Extended Kalman Filter algorithm, which is an industry standard processing algorithm for filtering and estimation applications. This paper describes the methodology and results of the trajectory reconstruction process, including flight data preprocessing and input uncertainties, trajectory estimation algorithms, output transformations, and comparisons with preflight predictions.
43 CFR 2450.3 - Proposed classification decision.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Proposed classification decision. 2450.3... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) PETITION-APPLICATION CLASSIFICATION SYSTEM Petition-Application Procedures § 2450.3 Proposed classification decision. (a) The State Director...
Spiking, Bursting, and Population Dynamics in a Network of Growth Transform Neurons.
Gangopadhyay, Ahana; Chakrabartty, Shantanu
2018-06-01
This paper investigates the dynamical properties of a network of neurons, each of which implements an asynchronous mapping based on polynomial growth transforms. In the first part of this paper, we present a geometric approach for visualizing the dynamics of the network where each of the neurons traverses a trajectory in a dual optimization space, whereas the network itself traverses a trajectory in an equivalent primal optimization space. We show that as the network learns to solve basic classification tasks, different choices of primal-dual mapping produce unique but interpretable neural dynamics like noise shaping, spiking, and bursting. While the proposed framework is general enough, in this paper, we demonstrate its use for designing support vector machines (SVMs) that exhibit noise-shaping properties similar to those of modulators, and for designing SVMs that learn to encode information using spikes and bursts. It is demonstrated that the emergent switching, spiking, and burst dynamics produced by each neuron encodes its respective margin of separation from a classification hyperplane whose parameters are encoded by the network population dynamics. We believe that the proposed growth transform neuron model and the underlying geometric framework could serve as an important tool to connect well-established machine learning algorithms like SVMs to neuromorphic principles like spiking, bursting, population encoding, and noise shaping.
Study of orifice fabrication technologies for the liquid droplet radiator
NASA Technical Reports Server (NTRS)
Wallace, David B.; Hayes, Donald J.; Bush, J. Michael
1991-01-01
Eleven orifice fabrication technologies potentially applicable for a liquid droplet radiator are discussed. The evaluation is focused on technologies capable of yielding 25-150 microns diameter orifices with trajectory accuracies below 5 milliradians, ultimately in arrays of up to 4000 orifices. An initial analytical screening considering factors such as trajectory accuracy, manufacturability, and hydrodynamics of orifice flow is presented. Based on this screening, four technologies were selected for experimental evaluation. A jet straightness system used to test 50-orifice arrays made by electro-discharge machining (EDM), Fotoceram, and mechanical drilling is discussed. Measurements on orifice diameter control and jet trajectory accuracy are presented and discussed. Trajectory standard deviations are in the 4.6-10.0 milliradian range. Electroforming and EDM appear to have the greatest potential for Liquid Droplet Radiator applications. The direction of a future development effort is discussed.
Automated Sensitivity Analysis of Interplanetary Trajectories for Optimal Mission Design
NASA Technical Reports Server (NTRS)
Knittel, Jeremy; Hughes, Kyle; Englander, Jacob; Sarli, Bruno
2017-01-01
This work describes a suite of Python tools known as the Python EMTG Automated Trade Study Application (PEATSA). PEATSA was written to automate the operation of trajectory optimization software, simplify the process of performing sensitivity analysis, and was ultimately found to out-perform a human trajectory designer in unexpected ways. These benefits will be discussed and demonstrated on sample mission designs.
Hu, Weiming; Tian, Guodong; Kang, Yongxin; Yuan, Chunfeng; Maybank, Stephen
2017-09-25
In this paper, a new nonparametric Bayesian model called the dual sticky hierarchical Dirichlet process hidden Markov model (HDP-HMM) is proposed for mining activities from a collection of time series data such as trajectories. All the time series data are clustered. Each cluster of time series data, corresponding to a motion pattern, is modeled by an HMM. Our model postulates a set of HMMs that share a common set of states (topics in an analogy with topic models for document processing), but have unique transition distributions. For the application to motion trajectory modeling, topics correspond to motion activities. The learnt topics are clustered into atomic activities which are assigned predicates. We propose a Bayesian inference method to decompose a given trajectory into a sequence of atomic activities. On combining the learnt sources and sinks, semantic motion regions, and the learnt sequence of atomic activities, the action represented by the trajectory can be described in natural language in as automatic a way as possible. The effectiveness of our dual sticky HDP-HMM is validated on several trajectory datasets. The effectiveness of the natural language descriptions for motions is demonstrated on the vehicle trajectories extracted from a traffic scene.
James, Conrad D.; Aimone, James B.; Miner, Nadine E.; ...
2017-01-04
In this study, biological neural networks continue to inspire new developments in algorithms and microelectronic hardware to solve challenging data processing and classification problems. Here in this research, we survey the history of neural-inspired and neuromorphic computing in order to examine the complex and intertwined trajectories of the mathematical theory and hardware developed in this field. Early research focused on adapting existing hardware to emulate the pattern recognition capabilities of living organisms. Contributions from psychologists, mathematicians, engineers, neuroscientists, and other professions were crucial to maturing the field from narrowly-tailored demonstrations to more generalizable systems capable of addressing difficult problem classesmore » such as object detection and speech recognition. Algorithms that leverage fundamental principles found in neuroscience such as hierarchical structure, temporal integration, and robustness to error have been developed, and some of these approaches are achieving world-leading performance on particular data classification tasks. Additionally, novel microelectronic hardware is being developed to perform logic and to serve as memory in neuromorphic computing systems with optimized system integration and improved energy efficiency. Key to such advancements was the incorporation of new discoveries in neuroscience research, the transition away from strict structural replication and towards the functional replication of neural systems, and the use of mathematical theory frameworks to guide algorithm and hardware developments.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
James, Conrad D.; Aimone, James B.; Miner, Nadine E.
In this study, biological neural networks continue to inspire new developments in algorithms and microelectronic hardware to solve challenging data processing and classification problems. Here in this research, we survey the history of neural-inspired and neuromorphic computing in order to examine the complex and intertwined trajectories of the mathematical theory and hardware developed in this field. Early research focused on adapting existing hardware to emulate the pattern recognition capabilities of living organisms. Contributions from psychologists, mathematicians, engineers, neuroscientists, and other professions were crucial to maturing the field from narrowly-tailored demonstrations to more generalizable systems capable of addressing difficult problem classesmore » such as object detection and speech recognition. Algorithms that leverage fundamental principles found in neuroscience such as hierarchical structure, temporal integration, and robustness to error have been developed, and some of these approaches are achieving world-leading performance on particular data classification tasks. Additionally, novel microelectronic hardware is being developed to perform logic and to serve as memory in neuromorphic computing systems with optimized system integration and improved energy efficiency. Key to such advancements was the incorporation of new discoveries in neuroscience research, the transition away from strict structural replication and towards the functional replication of neural systems, and the use of mathematical theory frameworks to guide algorithm and hardware developments.« less
Theory and algorithms for image reconstruction on chords and within regions of interest
NASA Astrophysics Data System (ADS)
Zou, Yu; Pan, Xiaochuan; Sidky, Emilâ Y.
2005-11-01
We introduce a formula for image reconstruction on a chord of a general source trajectory. We subsequently develop three algorithms for exact image reconstruction on a chord from data acquired with the general trajectory. Interestingly, two of the developed algorithms can accommodate data containing transverse truncations. The widely used helical trajectory and other trajectories discussed in literature can be interpreted as special cases of the general trajectory, and the developed theory and algorithms are thus directly applicable to reconstructing images exactly from data acquired with these trajectories. For instance, chords on a helical trajectory are equivalent to the n-PI-line segments. In this situation, the proposed algorithms become the algorithms that we proposed previously for image reconstruction on PI-line segments. We have performed preliminary numerical studies, which include the study on image reconstruction on chords of two-circle trajectory, which is nonsmooth, and on n-PI lines of a helical trajectory, which is smooth. Quantitative results of these studies verify and demonstrate the proposed theory and algorithms.
46 CFR 8.240 - Application for recognition.
Code of Federal Regulations, 2010 CFR
2010-10-01
... ALTERNATIVES Recognition of a Classification Society § 8.240 Application for recognition. (a) A classification society must apply for recognition in writing to the Commandant (CG-521). (b) An application must indicate which specific authority the classification society seeks to have delegated. (c) Upon verification from...
46 CFR 8.240 - Application for recognition.
Code of Federal Regulations, 2011 CFR
2011-10-01
... ALTERNATIVES Recognition of a Classification Society § 8.240 Application for recognition. (a) A classification society must apply for recognition in writing to the Commandant (CG-521). (b) An application must indicate which specific authority the classification society seeks to have delegated. (c) Upon verification from...
Trajectory Optimization for Crewed Missions to an Earth-Moon L2 Halo Orbit
NASA Astrophysics Data System (ADS)
Dowling, Jennifer
Baseline trajectories to an Earth-Moon L2 halo orbit and round trip trajectories for crewed missions have been created in support of an advanced Orion mission concept. Various transfer durations and orbit insertion locations have been evaluated. The trajectories often include a deterministic mid-course maneuver that decreases the overall change in velocity in the trajectory. This paper presents the application of primer vector theory to study the existence, location, and magnitude of the mid-course maneuver in order to understand how to build an optimal round trip trajectory to an Earth-Moon L2 halo orbit. The lessons learned about when to add mid-course maneuvers can be applied to other mission designs.
Marechal, Luc; Shaohui Foong; Zhenglong Sun; Wood, Kristin L
2015-08-01
Motivated by the need for developing a neuronavigation system to improve efficacy of intracranial surgical procedures, a localization system using passive magnetic fields for real-time monitoring of the insertion process of an external ventricular drain (EVD) catheter is conceived and developed. This system operates on the principle of measuring the static magnetic field of a magnetic marker using an array of magnetic sensors. An artificial neural network (ANN) is directly used for solving the inverse problem of magnetic dipole localization for improved efficiency and precision. As the accuracy of localization system is highly dependent on the sensor spatial location, an optimization framework, based on understanding and classification of experimental sensor characteristics as well as prior knowledge of the general trajectory of the localization pathway, for design of such sensing assemblies is described and investigated in this paper. Both optimized and non-optimized sensor configurations were experimentally evaluated and results show superior performance from the optimized configuration. While the approach presented here utilizes ventriculostomy as an illustrative platform, it can be extended to other medical applications that require localization inside the body.
Information surfing with the JHU/APL coherent imager
NASA Astrophysics Data System (ADS)
Ratto, Christopher R.; Shipley, Kara R.; Beagley, Nathaniel; Wolfe, Kevin C.
2015-05-01
The ability to perform remote forensics in situ is an important application of autonomous undersea vehicles (AUVs). Forensics objectives may include remediation of mines and/or unexploded ordnance, as well as monitoring of seafloor infrastructure. At JHU/APL, digital holography is being explored for the potential application to underwater imaging and integration with an AUV. In previous work, a feature-based approach was developed for processing the holographic imagery and performing object recognition. In this work, the results of the image processing method were incorporated into a Bayesian framework for autonomous path planning referred to as information surfing. The framework was derived assuming that the location of the object of interest is known a priori, but the type of object and its pose are unknown. The path-planning algorithm adaptively modifies the trajectory of the sensing platform based on historical performance of object and pose classification. The algorithm is called information surfing because the direction of motion is governed by the local information gradient. Simulation experiments were carried out using holographic imagery collected from submerged objects. The autonomous sensing algorithm was compared to a deterministic sensing CONOPS, and demonstrated improved accuracy and faster convergence in several cases.
Surgical gesture classification from video and kinematic data.
Zappella, Luca; Béjar, Benjamín; Hager, Gregory; Vidal, René
2013-10-01
Much of the existing work on automatic classification of gestures and skill in robotic surgery is based on dynamic cues (e.g., time to completion, speed, forces, torque) or kinematic data (e.g., robot trajectories and velocities). While videos could be equally or more discriminative (e.g., videos contain semantic information not present in kinematic data), they are typically not used because of the difficulties associated with automatic video interpretation. In this paper, we propose several methods for automatic surgical gesture classification from video data. We assume that the video of a surgical task (e.g., suturing) has been segmented into video clips corresponding to a single gesture (e.g., grabbing the needle, passing the needle) and propose three methods to classify the gesture of each video clip. In the first one, we model each video clip as the output of a linear dynamical system (LDS) and use metrics in the space of LDSs to classify new video clips. In the second one, we use spatio-temporal features extracted from each video clip to learn a dictionary of spatio-temporal words, and use a bag-of-features (BoF) approach to classify new video clips. In the third one, we use multiple kernel learning (MKL) to combine the LDS and BoF approaches. Since the LDS approach is also applicable to kinematic data, we also use MKL to combine both types of data in order to exploit their complementarity. Our experiments on a typical surgical training setup show that methods based on video data perform equally well, if not better, than state-of-the-art approaches based on kinematic data. In turn, the combination of both kinematic and video data outperforms any other algorithm based on one type of data alone. Copyright © 2013 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Sunwoo, Y.; Kim, Y. J.; Kim, D.; Park, J. E.; Hong, K. H.
2016-12-01
Many volcanos are located within 1,500 km of Korea which implies that a potential disaster is always possible. Several eruption precursors were observed rather recently at Mt. Baekdu, which has sparked intensive research on volcanic disasters in Korea. For assessment of potential volcanic hazard in Korea, we developed classification method of volcanic eruption dates using the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT-4) regarding air quality impact. And, we conducted 3 dimensional chemistry transport modeling for selected eruption dates. WRF-ARW(version 3.6.1) meteorological modeling was employed for high resolution HYSPLIT input meteorological data,. The modeling domain covers Northeast Asia including Korea, Japan, east China, and part of Russia. Forward trajectories were calculated every 3 hours for 1 year (2010) and the trajectories were initiated from 3 volcanoes, Mt. Baekdu, Mt. Aso, and Mt. Tarumae. Selected eruption dates were classified into 5 classes using 4 parameters, PBL, trajectory retention time, initial trajectory altitude and exposed population. The number of significant days for volcanic eruption impact were 7 for Mt. Baekdu (spring and fall), 7 for Mt. Aso (summer), 1 for Mt. Tarumae (spring), and these were classified as class A, with the highest risk of incurring severe air pollution episodes in the receptor area. In addition, we analyzed the spatio-temporal distributions of these trajectories in the receptor area to help determine the period and domain of the volcanic eruption 3 dimensional chemistry transport modeling. Using class A eruption dates, we conducted CMAQ(v5.0.2) modeling for calculate full chemical reactions of volcanic gases and ashes in troposphere.
NASA Astrophysics Data System (ADS)
Dimitroulis, Christos; Raptis, Theophanes; Raptis, Vasilios
2015-12-01
We present an application for the calculation of radial distribution functions for molecular centres of mass, based on trajectories generated by molecular simulation methods (Molecular Dynamics, Monte Carlo). When designing this application, the emphasis was placed on ease of use as well as ease of further development. In its current version, the program can read trajectories generated by the well-known DL_POLY package, but it can be easily extended to handle other formats. It is also very easy to 'hack' the program so it can compute intermolecular radial distribution functions for groups of interaction sites rather than whole molecules.
Modified Angle's Classification for Primary Dentition.
Chandranee, Kaushik Narendra; Chandranee, Narendra Jayantilal; Nagpal, Devendra; Lamba, Gagandeep; Choudhari, Purva; Hotwani, Kavita
2017-01-01
This study aims to propose a modification of Angle's classification for primary dentition and to assess its applicability in children from Central India, Nagpur. Modification in Angle's classification has been proposed for application in primary dentition. Small roman numbers i/ii/iii are used for primary dentition notation to represent Angle's Class I/II/III molar relationships as in permanent dentition, respectively. To assess applicability of modified Angle's classification a cross-sectional preschool 2000 children population from central India; 3-6 years of age residing in Nagpur metropolitan city of Maharashtra state were selected randomly as per the inclusion and exclusion criteria. Majority 93.35% children were found to have bilateral Class i followed by 2.5% bilateral Class ii and 0.2% bilateral half cusp Class iii molar relationships as per the modified Angle's classification for primary dentition. About 3.75% children had various combinations of Class ii relationships and 0.2% children were having Class iii subdivision relationship. Modification of Angle's classification for application in primary dentition has been proposed. A cross-sectional investigation using new classification revealed various 6.25% Class ii and 0.4% Class iii molar relationships cases in preschool children population in a metropolitan city of Nagpur. Application of the modified Angle's classification to other population groups is warranted to validate its routine application in clinical pediatric dentistry.
An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.
Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei
2013-05-01
Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.
NASA Technical Reports Server (NTRS)
Ardema, Mark D.
1995-01-01
This report summarizes the work entitled 'Advances in Hypersonic Vehicle Synthesis with Application to Studies of Advanced Thermal Protection Systems.' The effort was in two areas: (1) development of advanced methods of trajectory and propulsion system optimization; and (2) development of advanced methods of structural weight estimation. The majority of the effort was spent in the trajectory area.
Code of Federal Regulations, 2010 CFR
2010-07-01
... boundary, classification, control, governing authority, or identity? 222.8 Section 222.8 Education... in its boundary, classification, control, governing authority, or identity? (a) Any applicant that is... its boundaries, classification, control, governing authority, or identity must provide the following...
ERIC Educational Resources Information Center
McIlwaine, I. C.
1997-01-01
Discusses the history and development of the Universal Decimal Classification (UDC). Topics include the relationship with Dewey Decimal Classification; revision process; structure; facet analysis; lack of standard rules for application; application in automated systems; influence of UDC on classification development; links with thesauri; and use…
Code of Federal Regulations, 2013 CFR
2013-07-01
... boundary, classification, control, governing authority, or identity? 222.8 Section 222.8 Education... in its boundary, classification, control, governing authority, or identity? (a) Any applicant that is... its boundaries, classification, control, governing authority, or identity must provide the following...
Code of Federal Regulations, 2011 CFR
2011-07-01
... boundary, classification, control, governing authority, or identity? 222.8 Section 222.8 Education... in its boundary, classification, control, governing authority, or identity? (a) Any applicant that is... its boundaries, classification, control, governing authority, or identity must provide the following...
Code of Federal Regulations, 2012 CFR
2012-07-01
... boundary, classification, control, governing authority, or identity? 222.8 Section 222.8 Education... in its boundary, classification, control, governing authority, or identity? (a) Any applicant that is... its boundaries, classification, control, governing authority, or identity must provide the following...
Code of Federal Regulations, 2014 CFR
2014-07-01
... boundary, classification, control, governing authority, or identity? 222.8 Section 222.8 Education... in its boundary, classification, control, governing authority, or identity? (a) Any applicant that is... its boundaries, classification, control, governing authority, or identity must provide the following...
Current State of the Regulatory Trajectory for Whole Slide Imaging Devices in the USA
Abels, Esther; Pantanowitz, Liron
2017-01-01
The regulatory field for digital pathology (DP) has advanced significantly. A major milestone was accomplished when the FDA allowed the first vendor to market their device for primary diagnostic use in the USA and published in the classification order that this device, and substantially equivalent devices of this generic type, should be classified into class II instead of class III as previously proposed. The Digital Pathology Association (DPA) regulatory task force had a major role in the accomplishment of getting the application request for Whole Slide Imaging (WSI) Systems recommended for a de novo. This article reviews the past and emerging regulatory environment of WSI for clinical use in the USA. A WSI system with integrated subsystems is defined in the context of medical device regulations. The FDA technical performance assessment guideline is also discussed as well as parameters involved in analytical testing and clinical studies to demonstrate that WSI devices are safe and effective for clinical use. PMID:28584684
Current State of the Regulatory Trajectory for Whole Slide Imaging Devices in the USA.
Abels, Esther; Pantanowitz, Liron
2017-01-01
The regulatory field for digital pathology (DP) has advanced significantly. A major milestone was accomplished when the FDA allowed the first vendor to market their device for primary diagnostic use in the USA and published in the classification order that this device, and substantially equivalent devices of this generic type, should be classified into class II instead of class III as previously proposed. The Digital Pathology Association (DPA) regulatory task force had a major role in the accomplishment of getting the application request for Whole Slide Imaging (WSI) Systems recommended for a de novo . This article reviews the past and emerging regulatory environment of WSI for clinical use in the USA. A WSI system with integrated subsystems is defined in the context of medical device regulations. The FDA technical performance assessment guideline is also discussed as well as parameters involved in analytical testing and clinical studies to demonstrate that WSI devices are safe and effective for clinical use.
Algorithmic psychometrics and the scalable subject.
Stark, Luke
2018-04-01
Recent public controversies, ranging from the 2014 Facebook 'emotional contagion' study to psychographic data profiling by Cambridge Analytica in the 2016 American presidential election, Brexit referendum and elsewhere, signal watershed moments in which the intersecting trajectories of psychology and computer science have become matters of public concern. The entangled history of these two fields grounds the application of applied psychological techniques to digital technologies, and an investment in applying calculability to human subjectivity. Today, a quantifiable psychological subject position has been translated, via 'big data' sets and algorithmic analysis, into a model subject amenable to classification through digital media platforms. I term this position the 'scalable subject', arguing it has been shaped and made legible by algorithmic psychometrics - a broad set of affordances in digital platforms shaped by psychology and the behavioral sciences. In describing the contours of this 'scalable subject', this paper highlights the urgent need for renewed attention from STS scholars on the psy sciences, and on a computational politics attentive to psychology, emotional expression, and sociality via digital media.
An automated cirrus classification
NASA Astrophysics Data System (ADS)
Gryspeerdt, Edward; Quaas, Johannes; Sourdeval, Odran; Goren, Tom
2017-04-01
Cirrus clouds play an important role in determining the radiation budget of the earth, but our understanding of the lifecycle and controls on cirrus clouds remains incomplete. Cirrus clouds can have very different properties and development depending on their environment, particularly during their formation. However, the relevant factors often cannot be distinguished using commonly retrieved satellite data products (such as cloud optical depth). In particular, the initial cloud phase has been identified as an important factor in cloud development, but although back-trajectory based methods can provide information on the initial cloud phase, they are computationally expensive and depend on the cloud parametrisations used in re-analysis products. In this work, a classification system (Identification and Classification of Cirrus, IC-CIR) is introduced. Using re-analysis and satellite data, cirrus clouds are separated in four main types: frontal, convective, orographic and in-situ. The properties of these classes show that this classification is able to provide useful information on the properties and initial phase of cirrus clouds, information that could not be provided by instantaneous satellite retrieved cloud properties alone. This classification is designed to be easily implemented in global climate models, helping to improve future comparisons between observations and models and reducing the uncertainty in cirrus clouds properties, leading to improved cloud parametrisations.
NASA Astrophysics Data System (ADS)
Shinnaka, Shinji
This paper presents a new unified analysis of estimate errors by model-matching extended-back-EMF estimation methods for sensorless drive of permanent-magnet synchronous motors. Analytical solutions about estimate errors, whose validity is confirmed by numerical experiments, are rich in universality and applicability. As an example of universality and applicability, a new trajectory-oriented vector control method is proposed, which can realize directly quasi-optimal strategy minimizing total losses with no additional computational loads by simply orienting one of vector-control coordinates to the associated quasi-optimal trajectory. The coordinate orientation rule, which is analytically derived, is surprisingly simple. Consequently the trajectory-oriented vector control method can be applied to a number of conventional vector control systems using model-matching extended-back-EMF estimation methods.
Geometrically derived difference formulae for the numerical integration of trajectory problems
NASA Technical Reports Server (NTRS)
Mcleod, R. J. Y.; Sanz-Serna, J. M.
1982-01-01
An initial value problem for the autonomous system of ordinary differential equations dy/dt = f(y), where y is a vector, is considered. In a number of practical applications the interest lies in obtaining the curve traced by the solution y. These applications include the computation of trajectories in mechanical problems. The term 'trajectory problem' is employed to refer to these cases. Lambert and McLeod (1979) have introduced a method involving local rotation of the axes in the y-plane for the two-dimensional case. The present investigation continues the study of difference schemes specifically derived for trajectory problems. A simple geometrical way of constructing such methods is presented, and the local accuracy of the schemes is investigated. A circularly exact, fixed-step predictor-corrector algorithm is defined, and a variable-step version of a circularly exact algorithm is presented.
Design and optimal control of multi-spacecraft interferometric imaging systems
NASA Astrophysics Data System (ADS)
Chakravorty, Suman
The objective of the proposed NASA Origins mission, Planet Imager, is the high-resolution imaging of exo-solar planets and similar high resolution astronomical imaging applications. The imaging is to be accomplished through the design of multi-spacecraft interferometric imaging systems (MSIIS). In this dissertation, we study the design of MSIIS. Assuming that the ultimate goal of imaging is the correct classification of the formed images, we formulate the design problem as minimization of some resource utilization of the system subject to the constraint that the probability of misclassification of any given image is below a pre-specified level. We model the process of image formation in an MSIIS and show that the Modulation Transfer function of and the noise corrupting the synthesized optical instrument are dependent on the trajectories of the constituent spacecraft. Assuming that the final goal of imaging is the correct classification of the formed image based on a given feature (a real valued function of the image variable), and a threshold on the feature, we find conditions on the noise corrupting the measurements such that the probability of misclassification is below some pre-specified level. These conditions translate into constraints on the trajectories of the constituent spacecraft. Thus, the design problem reduces to minimizing some resource utilization of the system, while satisfying the constraints placed on the system by the imaging requirements. We study the problem of designing minimum time maneuvers for MSIIS. We transform the time minimization problem into a "painting problem". The painting problem involves painting a large disk with smaller paintbrushes (coverage disks). We show that spirals form the dominant set for the solution to the painting problem. We frame the time minimization in the subspace of spirals and obtain a bilinear program, the double pantograph problem, in the design parameters of the spiral, the spiraling rate and the angular rate. We show that the solution of this problem is given by the solution to two associated linear programs. We illustrate our results through a simulation where the banded appearance of a fictitious exo-solar planet at a distance of 8 parsecs is detected.
Probabilistic Tracking and Trajectory Planning for Autonomous Ground Vehicles in Urban Environments
2016-03-05
SECURITY CLASSIFICATION OF: The aim of this research is to develop a unified theory for perception and planning in autonomous ground vehicles, with a...Report Title The aim of this research is to develop a unified theory for perception and planning in autonomous ground vehicles, with a specific focus on...a combination of experimentally collected vision data and Monte- Carlo simulations. Smoothing for improved perception and robustness in planning
NASA Technical Reports Server (NTRS)
Perkins, Sharon; Martin, Andrea; Bavinger, Bill
1990-01-01
The Trajectory Operations Applications Software Task (TOAST) is a software development project whose purpose is to provide trajectory operation pre-mission and real-time support for the Space Shuttle. The purpose of the evaluation was to evaluate TOAST as an Application Manager - to assess current and planned capabilities, compare capabilities to commercially-available off the shelf (COTS) software, and analyze requirements of MCC and Flight Analysis Design System (FADS) for TOAST implementation. As a major part of the data gathering for the evaluation, interviews were conducted with NASA and contractor personnel. Real-time and flight design users, orbit navigation users, the TOAST developers, and management were interviewed. Code reviews and demonstrations were also held. Each of these interviews was videotaped and transcribed as appropriate. Transcripts were edited and are presented chronologically.
Trajectory optimization for the National aerospace plane
NASA Technical Reports Server (NTRS)
Lu, Ping
1993-01-01
While continuing the application of the inverse dynamics approach in obtaining the optimal numerical solutions, the research during the past six months has been focused on the formulation and derivation of closed-form solutions for constrained hypersonic flight trajectories. Since it was found in the research of the first year that a dominant portion of the optimal ascent trajectory of the aerospace plane is constrained by dynamic pressure and heating constraints, the application of the analytical solutions significantly enhances the efficiency in trajectory optimization, provides a better insight to understanding of the trajectory and conceivably has great potential in guidance of the vehicle. Work of this period has been reported in four technical papers. Two of the papers were presented in the AIAA Guidance, Navigation, and Control Conference (Hilton Head, SC, August, 1992) and Fourth International Aerospace Planes Conference (Orlando, FL, December, 1992). The other two papers have been accepted for publication by Journal of Guidance, Control, and Dynamics, and will appear in 1993. This report briefly summarizes the work done in the past six months and work currently underway.
Optimal solar sail planetocentric trajectories
NASA Technical Reports Server (NTRS)
Sackett, L. L.
1977-01-01
The analysis of solar sail planetocentric optimal trajectory problem is described. A computer program was produced to calculate optimal trajectories for a limited performance analysis. A square sail model is included and some consideration is given to a heliogyro sail model. Orbit to a subescape point and orbit to orbit transfer are considered. Trajectories about the four inner planets can be calculated and shadowing, oblateness, and solar motion may be included. Equinoctial orbital elements are used to avoid the classical singularities, and the method of averaging is applied to increase computational speed. Solution of the two-point boundary value problem which arises from the application of optimization theory is accomplished with a Newton procedure. Time optimal trajectories are emphasized, but a penalty function has been considered to prevent trajectories which intersect a planet's surface.
Land cover classification for Puget Sound, 1974-1979
NASA Technical Reports Server (NTRS)
Eby, J. R.
1981-01-01
Digital analysis of LANDSAT data for land cover classification projects in the Puget Sound region is surveyed. Two early rural and urban land use classifications and their application are described. After acquisition of VICAR/IBIs software, another land use classification of the area was performed, and is described in more detail. Future applications are considered.
Modified Angle's Classification for Primary Dentition
Chandranee, Kaushik Narendra; Chandranee, Narendra Jayantilal; Nagpal, Devendra; Lamba, Gagandeep; Choudhari, Purva; Hotwani, Kavita
2017-01-01
Aim: This study aims to propose a modification of Angle's classification for primary dentition and to assess its applicability in children from Central India, Nagpur. Methods: Modification in Angle's classification has been proposed for application in primary dentition. Small roman numbers i/ii/iii are used for primary dentition notation to represent Angle's Class I/II/III molar relationships as in permanent dentition, respectively. To assess applicability of modified Angle's classification a cross-sectional preschool 2000 children population from central India; 3–6 years of age residing in Nagpur metropolitan city of Maharashtra state were selected randomly as per the inclusion and exclusion criteria. Results: Majority 93.35% children were found to have bilateral Class i followed by 2.5% bilateral Class ii and 0.2% bilateral half cusp Class iii molar relationships as per the modified Angle's classification for primary dentition. About 3.75% children had various combinations of Class ii relationships and 0.2% children were having Class iii subdivision relationship. Conclusions: Modification of Angle's classification for application in primary dentition has been proposed. A cross-sectional investigation using new classification revealed various 6.25% Class ii and 0.4% Class iii molar relationships cases in preschool children population in a metropolitan city of Nagpur. Application of the modified Angle's classification to other population groups is warranted to validate its routine application in clinical pediatric dentistry. PMID:29326514
NASA Astrophysics Data System (ADS)
Schlueter-Kuck, Kristy; Dabiri, John
2017-11-01
In recent years, there has been a proliferation of techniques that aim to characterize fluid flow kinematics on the basis of Lagrangian trajectories of collections of tracer particles. Most of these techniques depend on presence of tracer particles that are initially closely-spaced, in order to compute local gradients of their trajectories. In many applications, the requirement of close tracer spacing cannot be satisfied, especially when the tracers are naturally occurring and their distribution is dictated by the underlying flow. Moreover, current methods often focus on determination of the boundaries of coherent sets, whereas in practice it is often valuable to identify the complete set of trajectories that are coherent with an individual trajectory of interest. We extend the concept of Coherent Structure Coloring to achieve identification of the coherent set associated with individual Lagrangian trajectories. This algorithm is proven successful in identifying coherent structures of varying complexities in canonical unsteady flows. Importantly, although the method is demonstrated here in the context of fluid flow kinematics, the generality of the approach allows for its potential application to other unsupervised clustering problems in dynamical systems. This work was supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.
NASA Astrophysics Data System (ADS)
Chalupka, Uwe; Rothe, Hendrik
2012-03-01
The progress on a laser- and stereo-camera-based trajectory measurement system that we already proposed and described in recent publications is given. The system design was extended from one to two more powerful, DSP-controllable LASER systems. Experimental results of the extended system using different projectile-/weapon combinations will be shown and discussed. Automatic processing of acquired images using common 3DIP techniques was realized. Processing steps to extract trajectory segments from images as representative for the current application will be presented. Used algorithms for backward-calculation of the projectile trajectory will be shown. Verification of produced results is done against simulated trajectories, once in terms of detection robustness and once in terms of detection accuracy. Fields of use for the current system are within the ballistic domain. The first purpose is for trajectory measurement of small and middle caliber projectiles on a shooting range. Extension to big caliber projectiles as well as an application for sniper detection is imaginable, but would require further work. Beside classical RADAR, acoustic and optical projectile detection methods, the current system represents a further projectile location method under the new class of electro-optical methods that have been evolved in recent decades and that uses 3D imaging acquisition and processing techniques.
32 CFR 2103.21 - Definition and application.
Code of Federal Regulations, 2010 CFR
2010-07-01
....21 National Defense Other Regulations Relating to National Defense NATIONAL SECURITY COUNCIL... DECLASSIFIED Derivative Classification § 2103.21 Definition and application. Derivative classification is the... substance as information that is currently classified. Thus, derivative classification may be accomplished...
76 FR 72766 - Proposed Collection; Comment Request for Form 8952
Federal Register 2010, 2011, 2012, 2013, 2014
2011-11-25
... 8952, Application for Voluntary Classification Settlement Program. DATES: Written comments should [email protected] . SUPPLEMENTARY INFORMATION: Title: Application for Voluntary Classification Settlement... Classification Settlement Program. To participate in the program, taxpayers must meet certain eligibility...
Significance of clustering and classification applications in digital and physical libraries
NASA Astrophysics Data System (ADS)
Triantafyllou, Ioannis; Koulouris, Alexandros; Zervos, Spiros; Dendrinos, Markos; Giannakopoulos, Georgios
2015-02-01
Applications of clustering and classification techniques can be proved very significant in both digital and physical (paper-based) libraries. The most essential application, document classification and clustering, is crucial for the content that is produced and maintained in digital libraries, repositories, databases, social media, blogs etc., based on various tags and ontology elements, transcending the traditional library-oriented classification schemes. Other applications with very useful and beneficial role in the new digital library environment involve document routing, summarization and query expansion. Paper-based libraries can benefit as well since classification combined with advanced material characterization techniques such as FTIR (Fourier Transform InfraRed spectroscopy) can be vital for the study and prevention of material deterioration. An improved two-level self-organizing clustering architecture is proposed in order to enhance the discrimination capacity of the learning space, prior to classification, yielding promising results when applied to the above mentioned library tasks.
Anatomical nuances of the internal carotid artery in relation to the quadrangular space.
Dolci, Ricardo L L; Ditzel Filho, Leo F S; Goulart, Carlos R; Upadhyay, Smita; Buohliqah, Lamia; Lazarini, Paulo R; Prevedello, Daniel M; Carrau, Ricardo L
2018-01-01
OBJECTIVE The aim of this study was to evaluate the anatomical variations of the internal carotid artery (ICA) in relation to the quadrangular space (QS) and to propose a classification system based on the results. METHODS A total of 44 human cadaveric specimens were dissected endonasally under direct endoscopic visualization. During the dissection, the anatomical variations of the ICA and their relationship with the QS were noted. RESULTS The space between the paraclival ICAs (i.e., intercarotid space) can be classified as 1 of 3 different shapes (i.e., trapezoid, square, or hourglass) based on the trajectory of the ICAs. The ICA trajectories also directly influence the volumetric area of the QS. Based on its geometry, the QS was classified as one of the following: 1) Type A has the smallest QS area and is associated with a trapezoid intercarotid space, 2) Type B corresponds to the expected QS area (not minimized or enlarged) and is associated with a square intercarotid space, and 3) Type C has the largest QS area and is associated with an hourglass intercarotid space. CONCLUSIONS The different trajectories of the ICAs can modify the area of the QS and may be an essential parameter to consider for preoperative planning and defining the most appropriate corridor to reach Meckel's cave. In addition, ICA trajectories should be considered prior to surgery to avoid injuring the vessels.
George E. Host; Carl W. Ramm; Eunice A. Padley; Kurt S. Pregitzer; James B. Hart; David T. Cleland
1992-01-01
Presents technical documentation for development of an Ecological Classification System for the Manistee National Forest in northwest Lower Michigan, and suggests procedures applicable to other ecological land classification projects. Includes discussion of sampling design, field data collection, data summarization and analyses, development of classification units,...
ERIC Educational Resources Information Center
Noel, Jana; Earwicker, David P.
2015-01-01
This study was performed to document the strategies and methods used by successful applicants for the 2010 Carnegie Community Engagement Classification and to document the cultural shifts connected with the application process and receipt of the Classification. Four major findings emerged: (1) Applicants benefited from a team approach; (2)…
Surface modifications with Lissajous trajectories using atomic force microscopy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cai, Wei; Yao, Nan, E-mail: nyao@princeton.edu
2015-09-14
In this paper, we report a method for atomic force microscopy surface modifications with single-tone and multiple-resolution Lissajous trajectories. The tip mechanical scratching experiments with two series of Lissajous trajectories were carried out on monolayer films. The scratching processes with two scan methods have been illustrated. As an application, the tip-based triboelectrification phenomenon on the silicon dioxide surface with Lissajous trajectories was investigated. The triboelectric charges generated within the tip rubbed area on the surface were characterized in-situ by scanning Kelvin force microscopy. This method would provide a promising and cost-effective approach for surface modifications and nanofabrication.
Trajectory Design Tools for Libration and Cis-Lunar Environments
NASA Technical Reports Server (NTRS)
Folta, David C.; Webster, Cassandra M.; Bosanac, Natasha; Cox, Andrew; Guzzetti, Davide; Howell, Kathleen C.
2016-01-01
Innovative trajectory design tools are required to support challenging multi-body regimes with complex dynamics, uncertain perturbations, and the integration of propulsion influences. Two distinctive tools, Adaptive Trajectory Design and the General Mission Analysis Tool have been developed and certified to provide the astrodynamics community with the ability to design multi-body trajectories. In this paper we discuss the multi-body design process and the capabilities of both tools. Demonstrable applications to confirmed missions, the Lunar IceCube Cubesat lunar mission and the Wide-Field Infrared Survey Telescope (WFIRST) Sun-Earth L2 mission, are presented.
Minimum fuel trajectory for the aerospace-plane
NASA Technical Reports Server (NTRS)
Breakwell, John V.; Golan, Oded; Sauvageot, Anne
1990-01-01
An overall trajectory for a single-stage-to-orbit vehicle with an initial weight of 234 tons is calculated, and four different propulsion models including turbojet, ramjet, scramjet, and rocket are considered. First, the atmospheric flight in the thicker atmosphere is discussed with emphasis on trajectory optimization, optimization problem, aerodynamic problem, propulsion model, and initial conditions. The performance of turbojet and ramjet-scramjet engines is analyzed; and then the flight to orbit is assessed from the optimization point of view. It is shown that roll modulation saves little during the trajectory, and the combined application of airbreathing propulsion and aerodynamic lift is suggested.
2007-08-01
In the approach, photon trajectories are computed using a solution of the Eikonal equation (ray-tracing methods) rather than linear trajectories. The...coupling the radiative transport solution into heat transfer and damage models. 15. SUBJECT TERMS: B-Splines, Ray-Tracing, Eikonal Equation...multi-layer biological tissue model. In the approach, photon trajectories are computed using a solution of the Eikonal equation (ray-tracing methods
Investigations in adaptive processing of multispectral data
NASA Technical Reports Server (NTRS)
Kriegler, F. J.; Horwitz, H. M.
1973-01-01
Adaptive data processing procedures are applied to the problem of classifying objects in a scene scanned by multispectral sensor. These procedures show a performance improvement over standard nonadaptive techniques. Some sources of error in classification are identified and those correctable by adaptive processing are discussed. Experiments in adaptation of signature means by decision-directed methods are described. Some of these methods assume correlation between the trajectories of different signature means; for others this assumption is not made.
32 CFR 2700.21 - Definition and application.
Code of Federal Regulations, 2011 CFR
2011-07-01
... NEGOTIATIONS SECURITY INFORMATION REGULATIONS Derivative Classification § 2700.21 Definition and application. Derivative classification is the act of assigning a level of classification to information which is determined to be the same in substance as information which is currently classified. Thus, derivative...
40 CFR 432.1 - General Applicability.
Code of Federal Regulations, 2011 CFR
2011-07-01
... STANDARDS MEAT AND POULTRY PRODUCTS POINT SOURCE CATEGORY § 432.1 General Applicability. As defined more... the following industrial classification codes: Standard industrial classification 1 North Americanindustrial classification system 2 SIC 0751 NAICS 311611. SIC 2011 NAICS 311612. SIC 2013 NAICS 311615. SIC...
32 CFR 2700.21 - Definition and application.
Code of Federal Regulations, 2010 CFR
2010-07-01
... NEGOTIATIONS SECURITY INFORMATION REGULATIONS Derivative Classification § 2700.21 Definition and application. Derivative classification is the act of assigning a level of classification to information which is determined to be the same in substance as information which is currently classified. Thus, derivative...
Measuring diagnoses: ICD code accuracy.
O'Malley, Kimberly J; Cook, Karon F; Price, Matt D; Wildes, Kimberly Raiford; Hurdle, John F; Ashton, Carol M
2005-10-01
To examine potential sources of errors at each step of the described inpatient International Classification of Diseases (ICD) coding process. The use of disease codes from the ICD has expanded from classifying morbidity and mortality information for statistical purposes to diverse sets of applications in research, health care policy, and health care finance. By describing a brief history of ICD coding, detailing the process for assigning codes, identifying where errors can be introduced into the process, and reviewing methods for examining code accuracy, we help code users more systematically evaluate code accuracy for their particular applications. We summarize the inpatient ICD diagnostic coding process from patient admission to diagnostic code assignment. We examine potential sources of errors at each step and offer code users a tool for systematically evaluating code accuracy. Main error sources along the "patient trajectory" include amount and quality of information at admission, communication among patients and providers, the clinician's knowledge and experience with the illness, and the clinician's attention to detail. Main error sources along the "paper trail" include variance in the electronic and written records, coder training and experience, facility quality-control efforts, and unintentional and intentional coder errors, such as misspecification, unbundling, and upcoding. By clearly specifying the code assignment process and heightening their awareness of potential error sources, code users can better evaluate the applicability and limitations of codes for their particular situations. ICD codes can then be used in the most appropriate ways.
Campos, Eneida Rached; Moreira-Filho, Djalma de Carvalho; Silva, Marcos Tadeu Nolasco da
2018-05-01
Scores to predict treatment outcomes have earned a well-deserved place in healthcare practice. However, when used to help achieve excellence in the care of a given disease, scores should also take into account organizational and social aspects. This article aims to create scores to obtain key variables and its application in the management of care of a given disease. We present a method called Epidemiological Planning for Patient Care Trajectory (PELC) and its application in a research of HIV pediatric patients. This case study is presented by means of two studies. The first study deals with the development of the method PELC. The second is HIV Pediatric case-control study based on PELC method. HIV pediatric research - the first practical PELC application - found these four key variables to the individual quality level care trajectories: adherence to ART, attending at least one appointment with the otolaryngologist, attending at least one appointment with social services, and having missed one or more routine appointments. We believe PELC method can be used in researches about any kind of care trajectories, contributing to quality level advancements in health services, with emphasis on patient safety and equity in healthcare.
Erosion in radial inflow turbines. Volume 1: Erosive particle trajectory similarity
NASA Technical Reports Server (NTRS)
Clevenger, W. B., Jr.; Tabakoff, W.
1974-01-01
Similarity parameters from the equations of motion of particles immersed in a gas flow are derived. These parameters relate the particles which follow a certain trajectory in an equivalent cold gas turbine to particles that will follow the same trajectory in a real hot gas turbine. Numerical solutions of the trajectories that particles follow in the vortex and rotor regions of a radial inflow turbine are used to verify the range of Reynolds numbers in which the derived similarity parameters are applicable. In addition, an example is presented of typical particle sizes that can be observed in high speed photographic data collection and at the same time simulate the trajectories of particles in a real hot gas turbine.
Research on Classification of Chinese Text Data Based on SVM
NASA Astrophysics Data System (ADS)
Lin, Yuan; Yu, Hongzhi; Wan, Fucheng; Xu, Tao
2017-09-01
Data Mining has important application value in today’s industry and academia. Text classification is a very important technology in data mining. At present, there are many mature algorithms for text classification. KNN, NB, AB, SVM, decision tree and other classification methods all show good classification performance. Support Vector Machine’ (SVM) classification method is a good classifier in machine learning research. This paper will study the classification effect based on the SVM method in the Chinese text data, and use the support vector machine method in the chinese text to achieve the classify chinese text, and to able to combination of academia and practical application.
Sensitivity Analysis and Mitigation with Applications to Ballistic and Low-thrust Trajectory Design
NASA Astrophysics Data System (ADS)
Alizadeh, Iman
The ever increasing desire to expand space mission capabilities within the limited budgets of space industries requires new approaches to the old problem of spacecraft trajectory design. For example, recent initiatives for space exploration involve developing new tools to design low-cost, fail-safe trajectories to visit several potential destinations beyond our celestial neighborhood such as Jupiter's moons, asteroids, etc. Designing and navigating spacecraft trajectories to reach these destinations safely are complex and challenging. In particular, fundamental questions of orbital stability imposed by planetary protection requirements are not easily taken into account by standard optimal control schemes. The event of temporary engine loss or an unexpected missed thrust can indeed quickly lead to impact with planetary bodies or other unrecoverable trajectories. While electric propulsion technology provides superior efficiency compared to chemical engines, the very low-control authority and engine performance degradation can impose higher risk to the mission in strongly perturbed orbital environments. The risk is due to the complex gravitational field and its associated chaotic dynamics which causes large navigation dispersions in a short time if left un-controlled. Moreover, in these situations it can be outside the low-thrust propulsion system capability to correct the spacecraft trajectory in a reasonable time frame. These concerns can lead to complete or partial mission failure or even an infeasible mission concept at the early design stage. The goal of this research is to assess and increase orbital stability of ballistic and low-thrust transfer trajectories in multi-body systems. In particular, novel techniques are presented to characterize sensitivity and improve recovery characteristics of ballistic and low-thrust trajectories in unstable orbital environments. The techniques developed are based on perturbation analysis around ballistic trajectories to determine analytically the maximum divergence directions and also optimal control theory with nonstandard cost functions along with inverse dynamics applied to low-thrust trajectories. Several mission scenarios are shown to demonstrate the applicability of the techniques in the Earth-Moon and the Jupiter-Europa system. In addition, the results provide fundamental insight into design, stability analysis and guidance, navigation and control of low-thrust trajectories to meet challenging mission requirements in support of NASA's vision for space exploration.
NASA Astrophysics Data System (ADS)
Gao, Guoyou; Jiang, Chunsheng; Chen, Tao; Hui, Chun
2018-05-01
Industrial robots are widely used in various processes of surface manufacturing, such as thermal spraying. The established robot programming methods are highly time-consuming and not accurate enough to fulfil the demands of the actual market. There are many off-line programming methods developed to reduce the robot programming effort. This work introduces the principle of several based robot trajectory generation strategy on planar surface and curved surface. Since the off-line programming software is widely used and thus facilitates the robot programming efforts and improves the accuracy of robot trajectory, the analysis of this work is based on the second development of off-line programming software Robot studio™. To meet the requirements of automotive paint industry, this kind of software extension helps provide special functions according to the users defined operation parameters. The presented planning strategy generates the robot trajectory by moving an orthogonal surface according to the information of coating surface, a series of intersection curves are then employed to generate the trajectory points. The simulation results show that the path curve created with this method is successive and smooth, which corresponds to the requirements of automotive spray industrial applications.
Equilibrium sampling by reweighting nonequilibrium simulation trajectories
NASA Astrophysics Data System (ADS)
Yang, Cheng; Wan, Biao; Xu, Shun; Wang, Yanting; Zhou, Xin
2016-03-01
Based on equilibrium molecular simulations, it is usually difficult to efficiently visit the whole conformational space of complex systems, which are separated into some metastable regions by high free energy barriers. Nonequilibrium simulations could enhance transitions among these metastable regions and then be applied to sample equilibrium distributions in complex systems, since the associated nonequilibrium effects can be removed by employing the Jarzynski equality (JE). Here we present such a systematical method, named reweighted nonequilibrium ensemble dynamics (RNED), to efficiently sample equilibrium conformations. The RNED is a combination of the JE and our previous reweighted ensemble dynamics (RED) method. The original JE reproduces equilibrium from lots of nonequilibrium trajectories but requires that the initial distribution of these trajectories is equilibrium. The RED reweights many equilibrium trajectories from an arbitrary initial distribution to get the equilibrium distribution, whereas the RNED has both advantages of the two methods, reproducing equilibrium from lots of nonequilibrium simulation trajectories with an arbitrary initial conformational distribution. We illustrated the application of the RNED in a toy model and in a Lennard-Jones fluid to detect its liquid-solid phase coexistence. The results indicate that the RNED sufficiently extends the application of both the original JE and the RED in equilibrium sampling of complex systems.
Equilibrium sampling by reweighting nonequilibrium simulation trajectories.
Yang, Cheng; Wan, Biao; Xu, Shun; Wang, Yanting; Zhou, Xin
2016-03-01
Based on equilibrium molecular simulations, it is usually difficult to efficiently visit the whole conformational space of complex systems, which are separated into some metastable regions by high free energy barriers. Nonequilibrium simulations could enhance transitions among these metastable regions and then be applied to sample equilibrium distributions in complex systems, since the associated nonequilibrium effects can be removed by employing the Jarzynski equality (JE). Here we present such a systematical method, named reweighted nonequilibrium ensemble dynamics (RNED), to efficiently sample equilibrium conformations. The RNED is a combination of the JE and our previous reweighted ensemble dynamics (RED) method. The original JE reproduces equilibrium from lots of nonequilibrium trajectories but requires that the initial distribution of these trajectories is equilibrium. The RED reweights many equilibrium trajectories from an arbitrary initial distribution to get the equilibrium distribution, whereas the RNED has both advantages of the two methods, reproducing equilibrium from lots of nonequilibrium simulation trajectories with an arbitrary initial conformational distribution. We illustrated the application of the RNED in a toy model and in a Lennard-Jones fluid to detect its liquid-solid phase coexistence. The results indicate that the RNED sufficiently extends the application of both the original JE and the RED in equilibrium sampling of complex systems.
Compositionality in neural control: an interdisciplinary study of scribbling movements in primates
Abeles, Moshe; Diesmann, Markus; Flash, Tamar; Geisel, Theo; Herrmann, Michael; Teicher, Mina
2013-01-01
This article discusses the compositional structure of hand movements by analyzing and modeling neural and behavioral data obtained from experiments where a monkey (Macaca fascicularis) performed scribbling movements induced by a search task. Using geometrically based approaches to movement segmentation, it is shown that the hand trajectories are composed of elementary segments that are primarily parabolic in shape. The segments could be categorized into a small number of classes on the basis of decreasing intra-class variance over the course of training. A separate classification of the neural data employing a hidden Markov model showed a coincidence of the neural states with the behavioral categories. An additional analysis of both types of data by a data mining method provided evidence that the neural activity patterns underlying the behavioral primitives were formed by sets of specific and precise spike patterns. A geometric description of the movement trajectories, together with precise neural timing data indicates a compositional variant of a realistic synfire chain model. This model reproduces the typical shapes and temporal properties of the trajectories; hence the structure and composition of the primitives may reflect meaningful behavior. PMID:24062679
Design of fast earth-return trajectories from a lunar base
NASA Astrophysics Data System (ADS)
Anhorn, Walter
1991-09-01
The Apollo Lunar Program utilized efficient transearth trajectories which employed parking orbits in order to minimize energy requirements. This thesis concentrates on a different type of transearth trajectory. These are direct-ascent, hyperbolic trajectories which omit the parking orbits in order to achieve short flight times to and from a future lunar base. The object of the thesis is the development of a three-dimensional transearth trajectory model and associated computer program for exploring trade-offs between flight-time and energy, given various mission constraints. The program also targets the Moon with a hyperbolic trajectory, which can be used for targeting Earth impact points. The first-order model is based on an Earth-centered conic and a massless spherical Moon, using MathCAD version 3.0. This model is intended as the basis for future patched-conic formulations for the design of fast Earth-return trajectories. Applications include placing nuclear deterrent arsenals on the Moon, various space support related activities, and finally protection against Earth-threatening asteroids and comets using lunar bases.
NASA Astrophysics Data System (ADS)
Shinnaka, Shinji; Sano, Kousuke
This paper presents a new unified analysis of estimate errors by model-matching phase-estimation methods such as rotor-flux state-observers, back EMF state-observers, and back EMF disturbance-observers, for sensorless drive of permanent-magnet synchronous motors. Analytical solutions about estimate errors, whose validity is confirmed by numerical experiments, are rich in universality and applicability. As an example of universality and applicability, a new trajectory-oriented vector control method is proposed, which can realize directly quasi-optimal strategy minimizing total losses with no additional computational loads by simply orienting one of vector-control coordinates to the associated quasi-optimal trajectory. The coordinate orientation rule, which is analytically derived, is surprisingly simple. Consequently the trajectory-oriented vector control method can be applied to a number of conventional vector control systems using one of the model-matching phase-estimation methods.
High Efficiency Multi-shot Interleaved Spiral-In/Out Acquisition for High Resolution BOLD fMRI
Jung, Youngkyoo; Samsonov, Alexey A.; Liu, Thomas T.; Buracas, Giedrius T.
2012-01-01
Growing demand for high spatial resolution BOLD functional MRI faces a challenge of the spatial resolution vs. coverage or temporal resolution tradeoff, which can be addressed by methods that afford increased acquisition efficiency. Spiral acquisition trajectories have been shown to be superior to currently prevalent echo-planar imaging in terms of acquisition efficiency, and high spatial resolution can be achieved by employing multiple-shot spiral acquisition. The interleaved spiral in-out trajectory is preferred over spiral-in due to increased BOLD signal CNR and higher acquisition efficiency than that of spiral-out or non-interleaved spiral in/out trajectories (1), but to date applicability of the multi-shot interleaved spiral in-out for high spatial resolution imaging has not been studied. Herein we propose multi-shot interleaved spiral in-out acquisition and investigate its applicability for high spatial resolution BOLD fMRI. Images reconstructed from interleaved spiral-in and -out trajectories possess artifacts caused by differences in T2* decay, off-resonance and k-space errors associated with the two trajectories. We analyze the associated errors and demonstrate that application of conjugate phase reconstruction and spectral filtering can substantially mitigate these image artifacts. After applying these processing steps, the multishot interleaved spiral in-out pulse sequence yields high BOLD CNR images at in-plane resolution below 1x1 mm while preserving acceptable temporal resolution (4 s) and brain coverage (15 slices of 2 mm thickness). Moreover, this method yields sufficient BOLD CNR at 1.5 mm isotropic resolution for detection of activation in hippocampus associated with cognitive tasks (Stern memory task). The multi-shot interleaved spiral in-out acquisition is a promising technique for high spatial resolution BOLD fMRI applications. PMID:23023395
Windfield and trajectory models for tornado-propelled objects. Final report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Redmann, G.H.; Radbill, J.R.; Marte, J.E.
1983-03-01
This is the final report of a three-phased research project to develop a six-degree-of-freedom mathematical model to predict the trajectories of tornado-propelled objects. The model is based on the meteorological, aerodynamic, and dynamic processes that govern the trajectories of missiles in a tornadic windfield. The aerodynamic coefficients for the postulated missiles were obtained from full-scale wind tunnel tests on a 12-inch pipe and car and from drop tests. Rocket sled tests were run whereby the 12-inch pipe and car were injected into a worst-case tornado windfield in order to verify the trajectory model. To simplify and facilitate the use ofmore » the trajectory model for design applications without having to run the computer program, this report gives the trajectory data for NRC-postulated missiles in tables based on given variables of initial conditions of injection and tornado windfield. Complete descriptions of the tornado windfield and trajectory models are presented. The trajectory model computer program is also included for those desiring to perform trajectory or sensitivity analyses beyond those included in the report or for those wishing to examine other missiles and use other variables.« less
Silvatti, Amanda P; Cerveri, Pietro; Telles, Thiago; Dias, Fábio A S; Baroni, Guido; Barros, Ricardo M L
2013-01-01
In this study we aim at investigating the applicability of underwater 3D motion capture based on submerged video cameras in terms of 3D accuracy analysis and trajectory reconstruction. Static points with classical direct linear transform (DLT) solution, a moving wand with bundle adjustment and a moving 2D plate with Zhang's method were considered for camera calibration. As an example of the final application, we reconstructed the hand motion trajectories in different swimming styles and qualitatively compared this with Maglischo's model. Four highly trained male swimmers performed butterfly, breaststroke and freestyle tasks. The middle fingertip trajectories of both hands in the underwater phase were considered. The accuracy (mean absolute error) of the two calibration approaches (wand: 0.96 mm - 2D plate: 0.73 mm) was comparable to out of water results and highly superior to the classical DLT results (9.74 mm). Among all the swimmers, the hands' trajectories of the expert swimmer in the style were almost symmetric and in good agreement with Maglischo's model. The kinematic results highlight symmetry or asymmetry between the two hand sides, intra- and inter-subject variability in terms of the motion patterns and agreement or disagreement with the model. The two outcomes, calibration results and trajectory reconstruction, both move towards the quantitative 3D underwater motion analysis.
Applications of Multi-Body Dynamical Environments: The ARTEMIS Transfer Trajectory Design
NASA Technical Reports Server (NTRS)
Folta, David C.; Woodard, Mark; Howell, Kathleen; Patterson, Chris; Schlei, Wayne
2010-01-01
The application of forces in multi-body dynamical environments to pennit the transfer of spacecraft from Earth orbit to Sun-Earth weak stability regions and then return to the Earth-Moon libration (L1 and L2) orbits has been successfully accomplished for the first time. This demonstrated transfer is a positive step in the realization of a design process that can be used to transfer spacecraft with minimal Delta-V expenditures. Initialized using gravity assists to overcome fuel constraints; the ARTEMIS trajectory design has successfully placed two spacecraft into EarthMoon libration orbits by means of these applications.
NASA Astrophysics Data System (ADS)
Nwaogu, Chukwudi; Okeke, Onyedikachi J.; Fadipe, Olusola O.; Bashiru, Kehinde A.; Pechanec, Vilém
2017-12-01
Onitsha is one of the largest commercial cities in Africa with its population growth rate increasing arithmetically for the past two decades. This situation has direct and indirect effects on the natural resources including vegetation and water. The study aimed at assessing land use-land cover (LULC) change and its effects on the vegetation and landscape from 1987 to 2015 using geoinformatics. Supervised and unsupervised classifications including maximum likelihood algorithm were performed using ENVI 4.7 and ArcGIS 10.1 versions. The LULC was classified into 7 classes: built-up areas (settlement), waterbody, thick vegetation, light vegetation, riparian vegetation, sand deposit (bare soil) and floodplain. The result revealed that all the three vegetation types decreased in areas throughout the study period while, settlement, sand deposit and floodplain areas have remarkable increase of about 100% in 2015 when compared with the total in 1987. Number of dominant plant species decreased continuously during the study. The overall classification accuracies in 1987, 2002 and 2015 was 90.7%, 92.9% and 95.5% respectively. The overall kappa coefficient of the image classification for 1987, 2002 and 2015 was 0.98, 0.93 and 0.96 respectively. In general, the average classification was above 90%, a proof that the classification was reliable and acceptable.
Numerical analysis of the asymptotic two-point boundary value solution for N-body trajectories.
NASA Technical Reports Server (NTRS)
Lancaster, J. E.; Allemann, R. A.
1972-01-01
Previously published asymptotic solutions for lunar and interplanetary trajectories have been modified and combined to formulate a general analytical boundary value solution applicable to a broad class of trajectory problems. In addition, the earlier first-order solutions have been extended to second-order to determine if improved accuracy is possible. Comparisons between the asymptotic solution and numerical integration for several lunar and interplanetary trajectories show that the asymptotic solution is generally quite accurate. Also, since no iterations are required, a solution to the boundary value problem is obtained in a fraction of the time required for numerically integrated solutions.
PVDF flux/mass/velocity/trajectory systems and their applications in space
NASA Technical Reports Server (NTRS)
Tuzzolino, Anthony J.
1994-01-01
The current status of the University of Chicago Polyvinylidene Fluoride (PVDF) flux/mass/velocity/trajectory instrumentation is summarized. The particle response and thermal stability characteristics of pure PVDF and PVDF copolymer sensors are described, as well as the characteristics of specially constructed two-dimensional position-sensing PVDF sensors. The performance of high-flux systems and of velocity/trajectory systems using these sensors is discussed, and the objectives and designs of a PVDF velocity/trajectory dust instrument for launch on the Advanced Research and Global Observation Satellite (ARGOS) in 1995 and of a high-flux dust instrument for launch on the Cassini spacecraft to Saturn in 1997 are summarized.
Overview of the Development for a Suite of Low-Thrust Trajectory Analysis Tools
NASA Technical Reports Server (NTRS)
Kos, Larry D.; Polsgrove, Tara; Hopkins, Randall; Thomas, Dan; Sims, Jon A.
2006-01-01
A NASA intercenter team has developed a suite of low-thrust trajectory analysis tools to make a significant improvement in three major facets of low-thrust trajectory and mission analysis. These are: 1) ease of use, 2) ability to more robustly converge to solutions, and 3) higher fidelity modeling and accuracy of results. Due mostly to the short duration of the development, the team concluded that a suite of tools was preferred over having one integrated tool. This tool-suite, their characteristics, and their applicability will be described. Trajectory analysts can read this paper and determine which tool is most appropriate for their problem.
Serra, Laura; López Gómez, María Andrée; Sanchez-Niubo, Albert; Delclos, George L; Benavides, Fernando G
2017-01-01
Objective The aim of this study was to describe the application of latent class growth analysis (LCGA) to identify different working life trajectories (WLT) using employed working time by year as a repeated measure. Methods Trajectories are estimated using LCGA, which considers all individuals within a trajectory to be homogeneous. The methodology was applied to a subsample of the Spanish WORKing life Social Security (WORKss) cohort, limited to persons born 1956-1965 (N=247 475). The number of days worked per year is used as a repeated measure across 32 time points (1981-2013). Results According to the model-fit results and further guided by expert knowledge, a four WTL model was selected as the optimal approach: WLT1 or "high labor force participation" (N=99 591; 40.2%); WLT2 or "decreased labor force participation" (N= 22 846; 9.2%); WLT3 or "increased labor force participation" (N=59 213; 23.9%); and WLT4 or "low labor force participation" (N=65 827; 26.6%). WLT1 consisted mainly of men with more years of work experience (>19 years) while WLT4 was mainly composed by women with <9 years. The other two trajectories had opposite trends and no sex differences. The occupational category variable had little influence in the trajectories. Conclusions Longitudinal data that are regularly collected by administrative systems can benefit from LCGA approaches to identify different trajectory patterns that may be associated with an outcome of interest. In occupational epidemiology, this study represents a step forward by using this modeling approach to identify different WLT.
Bio-inspired energy-harvesting mechanisms and patterns of dynamic soaring.
Liu, Duo-Neng; Hou, Zhong-Xi; Guo, Zheng; Yang, Xi-Xiang; Gao, Xian-Zhong
2017-01-30
Albatrosses can make use of the dynamic soaring technique extracting energy from the wind field to achieve large-scale movement without a flap, which stimulates interest in effortless flight with small unmanned aerial vehicles (UAVs). However, mechanisms of energy harvesting in terms of the energy transfer from the wind to the flyer (albatross or UAV) are still indeterminate and controversial when using different reference frames in previous studies. In this paper, the classical four-phase Rayleigh cycle, includes sequentially upwind climb, downwind turn, downwind dive and upwind turn, is introduced in analyses of energy gain with the albatross's equation of motions and the simulated trajectory in dynamic soaring. Analytical and numerical results indicate that the energy gain in the air-relative frame mostly originates from large wind gradients at lower part of the climb and dive, while the energy gain in the inertial frame comes from the lift vector inclined to the wind speed direction during the climb, dive and downwind turn at higher altitude. These two energy-gain mechanisms are not equivalent in terms of energy sources and reference frames but have to be simultaneously satisfied in terms of the energy-neutral dynamic soaring cycle. For each reference frame, energy-loss phases are necessary to connect energy-gain ones. Based on these four essential phases in dynamic soaring and the albatrosses' flight trajectory, different dynamic soaring patterns are schematically depicted and corresponding optimal trajectories are computed. The optimal dynamic soaring trajectories are classified into two closed patterns including 'O' shape and '8' shape, and four travelling patterns including 'Ω' shape, 'α' shape, 'C' shape and 'S' shape. The correlation among these patterns are analysed and discussed. The completeness of the classification for different patterns is confirmed by listing and summarising dynamic soaring trajectories shown in studies over the past decades.
Computer Aided Ballistic Orbit Classification Around Small Bodies
NASA Astrophysics Data System (ADS)
Villac, Benjamin F.; Anderson, Rodney L.; Pini, Alex J.
2016-09-01
Orbital dynamics around small bodies are as varied as the shapes and dynamical states of these bodies. While various classes of orbits have been analyzed in detail, the global overview of relevant ballistic orbits at particular bodies is not easily computed or organized. Yet, correctly categorizing these orbits will ease their future use in the overall trajectory design process. This paper overviews methods that have been used to organize orbits, focusing on periodic orbits in particular, and introduces new methods based on clustering approaches.
Remote optical configuration of pigmented lesion detection and diagnosis of bone fractures
NASA Astrophysics Data System (ADS)
Ozana, Nisan; Bishitz, Yael; Beiderman, Yevgeny; Garcia, Javier; Zalevsky, Zeev; Schwarz, Ariel
2016-02-01
In this paper we present a novel approach of realizing a safe, simple, and inexpensive sensor applicable to bone fractures and pigmented lesions detection. The approach is based on temporal tracking of back-reflected secondary speckle pattern generated while illuminating the affected area with a laser and applying periodic pressure to the surface via a controlled vibration. The use of such a concept was already demonstrated for non-contact monitoring of various bio-medical parameters such as heart rate, blood pulse pressure, concentration of alcohol and glucose in the blood stream and intraocular pressure. The presented technique is a safe and effective method of detecting bone fractures in populations at risk. When applied to pigmented lesions, the technique is superior to visual examination in avoiding many false positives and resultant unnecessary biopsies. Applying a series of different vibration frequencies at the examined tissue and analyzing the 2-D speckle pattern trajectory in response to the applied periodic pressure creates a unique signature for each and different pigmented lesion. Analyzing these signatures is the first step toward detection of malignant melanoma. In this paper we present preliminary experiments that show the validity of the developed sensor for both applications: the detection of damaged bones as well as the classification of pigmented lesions.
Evaluation of the Trajectory Operations Applications Software Task (TOAST)
NASA Technical Reports Server (NTRS)
Perkins, Sharon; Martin, Andrea; Bavinger, Bill
1990-01-01
The Trajectory Operations Applications Software Task (TOAST) is a software development project under the auspices of the Mission Operations Directorate. Its purpose is to provide trajectory operation pre-mission and real-time support for the Space Shuttle program. As an Application Manager, TOAST provides an isolation layer between the underlying Unix operating system and the series of user programs. It provides two main services: a common interface to operating system functions with semantics appropriate for C or FORTRAN, and a structured input and output package that can be utilized by user application programs. In order to evaluate TOAST as an Application Manager, the task was to assess current and planned capabilities, compare capabilities to functions available in commercially-available off the shelf (COTS) and Flight Analysis Design System (FADS) users for TOAST implementation. As a result of the investigation, it was found that the current version of TOAST is well implemented and meets the needs of the real-time users. The plans for migrating TOAST to the X Window System are essentially sound; the Executive will port with minor changes, while Menu Handler will require a total rewrite. A series of recommendations for future TOAST directions are included.
Trend-Residual Dual Modeling for Detection of Outliers in Low-Cost GPS Trajectories.
Chen, Xiaojian; Cui, Tingting; Fu, Jianhong; Peng, Jianwei; Shan, Jie
2016-12-01
Low-cost GPS (receiver) has become a ubiquitous and integral part of our daily life. Despite noticeable advantages such as being cheap, small, light, and easy to use, its limited positioning accuracy devalues and hampers its wide applications for reliable mapping and analysis. Two conventional techniques to remove outliers in a GPS trajectory are thresholding and Kalman-based methods, which are difficult in selecting appropriate thresholds and modeling the trajectories. Moreover, they are insensitive to medium and small outliers, especially for low-sample-rate trajectories. This paper proposes a model-based GPS trajectory cleaner. Rather than examining speed and acceleration or assuming a pre-determined trajectory model, we first use cubic smooth spline to adaptively model the trend of the trajectory. The residuals, i.e., the differences between the trend and GPS measurements, are then further modeled by time series method. Outliers are detected by scoring the residuals at every GPS trajectory point. Comparing to the conventional procedures, the trend-residual dual modeling approach has the following features: (a) it is able to model trajectories and detect outliers adaptively; (b) only one critical value for outlier scores needs to be set; (c) it is able to robustly detect unapparent outliers; and (d) it is effective in cleaning outliers for GPS trajectories with low sample rates. Tests are carried out on three real-world GPS trajectories datasets. The evaluation demonstrates an average of 9.27 times better performance in outlier detection for GPS trajectories than thresholding and Kalman-based techniques.
47 CFR 1.929 - Classification of filings as major or minor.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 47 Telecommunication 1 2011-10-01 2011-10-01 false Classification of filings as major or minor. 1.929 Section 1.929 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE... Classification of filings as major or minor. Applications and amendments to applications for stations in the...
Applications of Diagnostic Classification Models: A Literature Review and Critical Commentary
ERIC Educational Resources Information Center
Sessoms, John; Henson, Robert A.
2018-01-01
Diagnostic classification models (DCMs) classify examinees based on the skills they have mastered given their test performance. This classification enables targeted feedback that can inform remedial instruction. Unfortunately, applications of DCMs have been criticized (e.g., no validity support). Generally, these evaluations have been brief and…
Robust flight design for an advanced launch system vehicle
NASA Astrophysics Data System (ADS)
Dhand, Sanjeev K.; Wong, Kelvin K.
Current launch vehicle trajectory design philosophies are generally based on maximizing payload capability. This approach results in an expensive trajectory design process for each mission. Two concepts of robust flight design have been developed to significantly reduce this cost: Standardized Trajectories and Command Multiplier Steering (CMS). These concepts were analyzed for an Advanced Launch System (ALS) vehicle, although their applicability is not restricted to any particular vehicle. Preliminary analysis has demonstrated the feasibility of these concepts at minimal loss in payload capability.
1985-01-01
general introduction to the basic principles of flight test instrumentation engineering and is composed from contributions by several specialized authors...Required measuring accuracy 17 OPTICAL METHODS OF TRAJECTORY MEASUREMENTS 19 3.1 Introduction 19 3.2 Kinetheodolites 19 3.2.1 General principles 19...without photographic cameras 30 3.5.1 General introduction 30 3.5.2 Trajectory measurements using lasers 31 3.5.2.1 General aspects 31 3.5.2.2
Optimal Trajectories Generation in Robotic Fiber Placement Systems
NASA Astrophysics Data System (ADS)
Gao, Jiuchun; Pashkevich, Anatol; Caro, Stéphane
2017-06-01
The paper proposes a methodology for optimal trajectories generation in robotic fiber placement systems. A strategy to tune the parameters of the optimization algorithm at hand is also introduced. The presented technique transforms the original continuous problem into a discrete one where the time-optimal motions are generated by using dynamic programming. The developed strategy for the optimization algorithm tuning allows essentially reducing the computing time and obtaining trajectories satisfying industrial constraints. Feasibilities and advantages of the proposed methodology are confirmed by an application example.
19 CFR 146.41 - Privileged foreign status.
Code of Federal Regulations, 2010 CFR
2010-04-01
... change in tariff classification will be given status as privileged foreign merchandise on proper application to the port director. (b) Application. Each application for this status will be made on Customs... which has effected a change in tariff classification. (c) Supporting documentation. Each applicant for...
Rapid near-optimal aerospace plane trajectory generation and guidance
NASA Technical Reports Server (NTRS)
Calise, A. J.; Corban, J. E.; Markopoulos, N.
1991-01-01
Effort was directed toward the problems of the real time trajectory optimization and guidance law development for the National Aerospace Plane (NASP) applications. In particular, singular perturbation methods were used to develop guidance algorithms suitable for onboard, real time implementation. The progress made in this research effort is reported.
Trajectory-Based Loads for the Ares I-X Test Flight Vehicle
NASA Technical Reports Server (NTRS)
Vause, Roland F.; Starr, Brett R.
2011-01-01
In trajectory-based loads, the structural engineer treats each point on the trajectory as a load case. Distributed aero, inertial, and propulsion forces are developed for the structural model which are equivalent to the integrated values of the trajectory model. Free-body diagrams are then used to solve for the internal forces, or loads, that keep the applied aero, inertial, and propulsion forces in dynamic equilibrium. There are several advantages to using trajectory-based loads. First, consistency is maintained between the integrated equilibrium equations of the trajectory analysis and the distributed equilibrium equations of the structural analysis. Second, the structural loads equations are tied to the uncertainty model for the trajectory systems analysis model. Atmosphere, aero, propulsion, mass property, and controls uncertainty models all feed into the dispersions that are generated for the trajectory systems analysis model. Changes in any of these input models will affect structural loads response. The trajectory systems model manages these inputs as well as the output from the structural model over thousands of dispersed cases. Large structural models with hundreds of thousands of degrees of freedom would execute too slowly to be an efficient part of several thousand system analyses. Trajectory-based loads provide a means for the structures discipline to be included in the integrated systems analysis. Successful applications of trajectory-based loads methods for the Ares I-X vehicle are covered in this paper. Preliminary design loads were based on 2000 trajectories using Monte Carlo dispersions. Range safety loads were tied to 8423 malfunction turn trajectories. In addition, active control system loads were based on 2000 preflight trajectories using Monte Carlo dispersions.
Optimal short-range trajectories for helicopters
DOE Office of Scientific and Technical Information (OSTI.GOV)
Slater, G.L.; Erzberger, H.
1982-12-01
An optimal flight path algorithm using a simplified altitude state model and a priori climb cruise descent flight profile was developed and applied to determine minimum fuel and minimum cost trajectories for a helicopter flying a fixed range trajectory. In addition, a method was developed for obtaining a performance model in simplified form which is based on standard flight manual data and which is applicable to the computation of optimal trajectories. The entire performance optimization algorithm is simple enough that on line trajectory optimization is feasible with a relatively small computer. The helicopter model used is the Silorsky S-61N. Themore » results show that for this vehicle the optimal flight path and optimal cruise altitude can represent a 10% fuel saving on a minimum fuel trajectory. The optimal trajectories show considerable variability because of helicopter weight, ambient winds, and the relative cost trade off between time and fuel. In general, reasonable variations from the optimal velocities and cruise altitudes do not significantly degrade the optimal cost. For fuel optimal trajectories, the optimum cruise altitude varies from the maximum (12,000 ft) to the minimum (0 ft) depending on helicopter weight.« less
An automated cirrus classification
NASA Astrophysics Data System (ADS)
Gryspeerdt, Edward; Quaas, Johannes; Goren, Tom; Klocke, Daniel; Brueck, Matthias
2018-05-01
Cirrus clouds play an important role in determining the radiation budget of the earth, but many of their properties remain uncertain, particularly their response to aerosol variations and to warming. Part of the reason for this uncertainty is the dependence of cirrus cloud properties on the cloud formation mechanism, which itself is strongly dependent on the local meteorological conditions. In this work, a classification system (Identification and Classification of Cirrus or IC-CIR) is introduced to identify cirrus clouds by the cloud formation mechanism. Using reanalysis and satellite data, cirrus clouds are separated into four main types: orographic, frontal, convective and synoptic. Through a comparison to convection-permitting model simulations and back-trajectory-based analysis, it is shown that these observation-based regimes can provide extra information on the cloud-scale updraughts and the frequency of occurrence of liquid-origin ice, with the convective regime having higher updraughts and a greater occurrence of liquid-origin ice compared to the synoptic regimes. Despite having different cloud formation mechanisms, the radiative properties of the regimes are not distinct, indicating that retrieved cloud properties alone are insufficient to completely describe them. This classification is designed to be easily implemented in GCMs, helping improve future model-observation comparisons and leading to improved parametrisations of cirrus cloud processes.
Task driven optimal leg trajectories in insect-scale legged microrobots
NASA Astrophysics Data System (ADS)
Doshi, Neel; Goldberg, Benjamin; Jayaram, Kaushik; Wood, Robert
Origami inspired layered manufacturing techniques and 3D-printing have enabled the development of highly articulated legged robots at the insect-scale, including the 1.43g Harvard Ambulatory MicroRobot (HAMR). Research on these platforms has expanded its focus from manufacturing aspects to include design optimization and control for application-driven tasks. Consequently, the choice of gait selection, body morphology, leg trajectory, foot design, etc. have become areas of active research. HAMR has two controlled degrees-of-freedom per leg, making it an ideal candidate for exploring leg trajectory. We will discuss our work towards optimizing HAMR's leg trajectories for two different tasks: climbing using electroadhesives and level ground running (5-10 BL/s). These tasks demonstrate the ability of single platform to adapt to vastly different locomotive scenarios: quasi-static climbing with controlled ground contact, and dynamic running with un-controlled ground contact. We will utilize trajectory optimization methods informed by existing models and experimental studies to determine leg trajectories for each task. We also plan to discuss how task specifications and choice of objective function have contributed to the shape of these optimal leg trajectories.
Computational Approaches to Simulation and Optimization of Global Aircraft Trajectories
NASA Technical Reports Server (NTRS)
Ng, Hok Kwan; Sridhar, Banavar
2016-01-01
This study examines three possible approaches to improving the speed in generating wind-optimal routes for air traffic at the national or global level. They are: (a) using the resources of a supercomputer, (b) running the computations on multiple commercially available computers and (c) implementing those same algorithms into NASAs Future ATM Concepts Evaluation Tool (FACET) and compares those to a standard implementation run on a single CPU. Wind-optimal aircraft trajectories are computed using global air traffic schedules. The run time and wait time on the supercomputer for trajectory optimization using various numbers of CPUs ranging from 80 to 10,240 units are compared with the total computational time for running the same computation on a single desktop computer and on multiple commercially available computers for potential computational enhancement through parallel processing on the computer clusters. This study also re-implements the trajectory optimization algorithm for further reduction of computational time through algorithm modifications and integrates that with FACET to facilitate the use of the new features which calculate time-optimal routes between worldwide airport pairs in a wind field for use with existing FACET applications. The implementations of trajectory optimization algorithms use MATLAB, Python, and Java programming languages. The performance evaluations are done by comparing their computational efficiencies and based on the potential application of optimized trajectories. The paper shows that in the absence of special privileges on a supercomputer, a cluster of commercially available computers provides a feasible approach for national and global air traffic system studies.
Principal Component 2-D Long Short-Term Memory for Font Recognition on Single Chinese Characters.
Tao, Dapeng; Lin, Xu; Jin, Lianwen; Li, Xuelong
2016-03-01
Chinese character font recognition (CCFR) has received increasing attention as the intelligent applications based on optical character recognition becomes popular. However, traditional CCFR systems do not handle noisy data effectively. By analyzing in detail the basic strokes of Chinese characters, we propose that font recognition on a single Chinese character is a sequence classification problem, which can be effectively solved by recurrent neural networks. For robust CCFR, we integrate a principal component convolution layer with the 2-D long short-term memory (2DLSTM) and develop principal component 2DLSTM (PC-2DLSTM) algorithm. PC-2DLSTM considers two aspects: 1) the principal component layer convolution operation helps remove the noise and get a rational and complete font information and 2) simultaneously, 2DLSTM deals with the long-range contextual processing along scan directions that can contribute to capture the contrast between character trajectory and background. Experiments using the frequently used CCFR dataset suggest the effectiveness of PC-2DLSTM compared with other state-of-the-art font recognition methods.
Code of Federal Regulations, 2010 CFR
2010-10-01
... Compliance Program § 8.410 Applicability. This subpart applies to: (a) Recognized classification societies... recognized classification society that is authorized by the Coast Guard to participate in the Alternate...
Code of Federal Regulations, 2011 CFR
2011-10-01
... Compliance Program § 8.410 Applicability. This subpart applies to: (a) Recognized classification societies... recognized classification society that is authorized by the Coast Guard to participate in the Alternate...
10 CFR 1045.2 - Applicability.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 10 Energy 4 2010-01-01 2010-01-01 false Applicability. 1045.2 Section 1045.2 Energy DEPARTMENT OF ENERGY (GENERAL PROVISIONS) NUCLEAR CLASSIFICATION AND DECLASSIFICATION Program Management of the Restricted Data and Formerly Restricted Data Classification System § 1045.2 Applicability. This subpart...
Trend-Residual Dual Modeling for Detection of Outliers in Low-Cost GPS Trajectories
Chen, Xiaojian; Cui, Tingting; Fu, Jianhong; Peng, Jianwei; Shan, Jie
2016-01-01
Low-cost GPS (receiver) has become a ubiquitous and integral part of our daily life. Despite noticeable advantages such as being cheap, small, light, and easy to use, its limited positioning accuracy devalues and hampers its wide applications for reliable mapping and analysis. Two conventional techniques to remove outliers in a GPS trajectory are thresholding and Kalman-based methods, which are difficult in selecting appropriate thresholds and modeling the trajectories. Moreover, they are insensitive to medium and small outliers, especially for low-sample-rate trajectories. This paper proposes a model-based GPS trajectory cleaner. Rather than examining speed and acceleration or assuming a pre-determined trajectory model, we first use cubic smooth spline to adaptively model the trend of the trajectory. The residuals, i.e., the differences between the trend and GPS measurements, are then further modeled by time series method. Outliers are detected by scoring the residuals at every GPS trajectory point. Comparing to the conventional procedures, the trend-residual dual modeling approach has the following features: (a) it is able to model trajectories and detect outliers adaptively; (b) only one critical value for outlier scores needs to be set; (c) it is able to robustly detect unapparent outliers; and (d) it is effective in cleaning outliers for GPS trajectories with low sample rates. Tests are carried out on three real-world GPS trajectories datasets. The evaluation demonstrates an average of 9.27 times better performance in outlier detection for GPS trajectories than thresholding and Kalman-based techniques. PMID:27916944
Tian, Sheng; Sun, Huiyong; Pan, Peichen; Li, Dan; Zhen, Xuechu; Li, Youyong; Hou, Tingjun
2014-10-27
In this study, to accommodate receptor flexibility, based on multiple receptor conformations, a novel ensemble docking protocol was developed by using the naïve Bayesian classification technique, and it was evaluated in terms of the prediction accuracy of docking-based virtual screening (VS) of three important targets in the kinase family: ALK, CDK2, and VEGFR2. First, for each target, the representative crystal structures were selected by structural clustering, and the capability of molecular docking based on each representative structure to discriminate inhibitors from non-inhibitors was examined. Then, for each target, 50 ns molecular dynamics (MD) simulations were carried out to generate an ensemble of the conformations, and multiple representative structures/snapshots were extracted from each MD trajectory by structural clustering. On average, the representative crystal structures outperform the representative structures extracted from MD simulations in terms of the capabilities to separate inhibitors from non-inhibitors. Finally, by using the naïve Bayesian classification technique, an integrated VS strategy was developed to combine the prediction results of molecular docking based on different representative conformations chosen from crystal structures and MD trajectories. It was encouraging to observe that the integrated VS strategy yields better performance than the docking-based VS based on any single rigid conformation. This novel protocol may provide an improvement over existing strategies to search for more diverse and promising active compounds for a target of interest.
Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhu, Lei; Holden, Jacob R.; Gonder, Jeffrey D.
With the development of smartphones and portable GPS devices, large-scale, high-resolution GPS data can be collected. Map matching is a critical step in studying vehicle driving activity and recognizing network traffic conditions from the data. A new trajectory segmentation map-matching algorithm is proposed to deal accurately and efficiently with large-scale, high-resolution GPS trajectory data. The new algorithm separated the GPS trajectory into segments. It found the shortest path for each segment in a scientific manner and ultimately generated a best-matched path for the entire trajectory. The similarity of a trajectory segment and its matched path is described by a similaritymore » score system based on the longest common subsequence. The numerical experiment indicated that the proposed map-matching algorithm was very promising in relation to accuracy and computational efficiency. Large-scale data set applications verified that the proposed method is robust and capable of dealing with real-world, large-scale GPS data in a computationally efficient and accurate manner.« less
Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data
Zhu, Lei; Holden, Jacob R.; Gonder, Jeffrey D.
2017-01-01
With the development of smartphones and portable GPS devices, large-scale, high-resolution GPS data can be collected. Map matching is a critical step in studying vehicle driving activity and recognizing network traffic conditions from the data. A new trajectory segmentation map-matching algorithm is proposed to deal accurately and efficiently with large-scale, high-resolution GPS trajectory data. The new algorithm separated the GPS trajectory into segments. It found the shortest path for each segment in a scientific manner and ultimately generated a best-matched path for the entire trajectory. The similarity of a trajectory segment and its matched path is described by a similaritymore » score system based on the longest common subsequence. The numerical experiment indicated that the proposed map-matching algorithm was very promising in relation to accuracy and computational efficiency. Large-scale data set applications verified that the proposed method is robust and capable of dealing with real-world, large-scale GPS data in a computationally efficient and accurate manner.« less
Improved dense trajectories for action recognition based on random projection and Fisher vectors
NASA Astrophysics Data System (ADS)
Ai, Shihui; Lu, Tongwei; Xiong, Yudian
2018-03-01
As an important application of intelligent monitoring system, the action recognition in video has become a very important research area of computer vision. In order to improve the accuracy rate of the action recognition in video with improved dense trajectories, one advanced vector method is introduced. Improved dense trajectories combine Fisher Vector with Random Projection. The method realizes the reduction of the characteristic trajectory though projecting the high-dimensional trajectory descriptor into the low-dimensional subspace based on defining and analyzing Gaussian mixture model by Random Projection. And a GMM-FV hybrid model is introduced to encode the trajectory feature vector and reduce dimension. The computational complexity is reduced by Random Projection which can drop Fisher coding vector. Finally, a Linear SVM is used to classifier to predict labels. We tested the algorithm in UCF101 dataset and KTH dataset. Compared with existed some others algorithm, the result showed that the method not only reduce the computational complexity but also improved the accuracy of action recognition.
Families of Ellipses and their Orthogonal Trajectories
ERIC Educational Resources Information Center
Ayoub, Ayoub B.
2004-01-01
The topic of orthogonal trajectories is taught as a geometric application of first order differential equations. Instructors usually elaborate on the concept of a family of curves to emphasize that they are different even if their members are of the same type. In this article the author considers five families of ellipses, discusses their…
Benchmarking Foot Trajectory Estimation Methods for Mobile Gait Analysis
Ollenschläger, Malte; Roth, Nils; Klucken, Jochen
2017-01-01
Mobile gait analysis systems based on inertial sensing on the shoe are applied in a wide range of applications. Especially for medical applications, they can give new insights into motor impairment in, e.g., neurodegenerative disease and help objectify patient assessment. One key component in these systems is the reconstruction of the foot trajectories from inertial data. In literature, various methods for this task have been proposed. However, performance is evaluated on a variety of datasets due to the lack of large, generally accepted benchmark datasets. This hinders a fair comparison of methods. In this work, we implement three orientation estimation and three double integration schemes for use in a foot trajectory estimation pipeline. All methods are drawn from literature and evaluated against a marker-based motion capture reference. We provide a fair comparison on the same dataset consisting of 735 strides from 16 healthy subjects. As a result, the implemented methods are ranked and we identify the most suitable processing pipeline for foot trajectory estimation in the context of mobile gait analysis. PMID:28832511
Accurately tracking single-cell movement trajectories in microfluidic cell sorting devices.
Jeong, Jenny; Frohberg, Nicholas J; Zhou, Enlu; Sulchek, Todd; Qiu, Peng
2018-01-01
Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.
Controlling particle trajectories using oscillating microbubbles
NASA Astrophysics Data System (ADS)
Jalikop, Shreyas; Wang, Cheng; Hilgenfeldt, Sascha
2010-11-01
In many applications of microfluidics and biotechnology, such as cytometry and drug delivery, it is vital to manipulate the trajectories of microparticles such as vesicles or cells. On this small scale, inertial or gravitational effects are often too weak to exploit. We propose a mechanism to selectively trap and direct particles based on their size in creeping transport flows (Re1). We employ Rayleigh-Nyborg-Westervelt (RNW) streaming generated by an oscillating microbubble, which in turn generates a streaming flow component around the mobile particles. The result is an attractive interaction that draws the particle closer to the bubble. The impenetrability of the bubble interface destroys time-reversal symmetry and forces the particles onto either narrow trajectory bundles or well-defined closed trajectories, where they are trapped. The effect is dependent on particle size and thus allows for the passive focusing and sorting of selected sizes, on scales much smaller than the geometry of the microfluidic device. The device could eliminate the need for complicated microchannel designs with external magnetic or electric fields in applications such as particle focusing and size-based sorting.
Application of the SNoW machine learning paradigm to a set of transportation imaging problems
NASA Astrophysics Data System (ADS)
Paul, Peter; Burry, Aaron M.; Wang, Yuheng; Kozitsky, Vladimir
2012-01-01
Machine learning methods have been successfully applied to image object classification problems where there is clear distinction between classes and where a comprehensive set of training samples and ground truth are readily available. The transportation domain is an area where machine learning methods are particularly applicable, since the classification problems typically have well defined class boundaries and, due to high traffic volumes in most applications, massive roadway data is available. Though these classes tend to be well defined, the particular image noises and variations can be challenging. Another challenge is the extremely high accuracy typically required in most traffic applications. Incorrect assignment of fines or tolls due to imaging mistakes is not acceptable in most applications. For the front seat vehicle occupancy detection problem, classification amounts to determining whether one face (driver only) or two faces (driver + passenger) are detected in the front seat of a vehicle on a roadway. For automatic license plate recognition, the classification problem is a type of optical character recognition problem encompassing multiple class classification. The SNoW machine learning classifier using local SMQT features is shown to be successful in these two transportation imaging applications.
Higgins, L J; Koshy, J; Mitchell, S E; Weiss, C R; Carson, K A; Huisman, T A G M; Tekes, A
2016-01-01
To evaluate the relative accuracy of contrast-enhanced time-resolved angiography with interleaved stochastic trajectories versus conventional contrast-enhanced magnetic resonance imaging (MRI) following International Society for the Study of Vascular Anomalies updated 2014-based classification of soft-tissue vascular anomalies in the head and neck in children. Time-resolved angiography with interleaved stochastic trajectories versus conventional contrast-enhanced MRI of children with diagnosis of soft-tissue vascular anomalies in the head and neck referred for MRI between 2008 and 2014 were retrospectively reviewed. Forty-seven children (0-18 years) were evaluated. Two paediatric neuroradiologists evaluated time-resolved MRA and conventional MRI in two different sessions (30 days apart). Blood-pool endovascular MRI contrast agent gadofosveset trisodium was used. The present cohort had the following diagnoses: infantile haemangioma (n=6), venous malformation (VM; n=23), lymphatic malformation (LM; n=16), arteriovenous malformation (AVM; n=2). Time-resolved MRA alone accurately classified 38/47 (81%) and conventional MRI 42/47 (89%), respectively. Although time-resolved MRA alone is slightly superior to conventional MRI alone for diagnosis of infantile haemangioma, conventional MRI is slightly better for diagnosis of venous and LMs. Neither time-resolved MRA nor conventional MRI was sufficient for accurate diagnosis of AVM in this cohort. Conventional MRI combined with time-resolved MRA accurately classified 44/47 cases (94%). Time-resolved MRA using gadofosveset trisodium can accurately classify soft-tissue vascular anomalies in the head and neck in children. The addition of time-resolved MRA to existing conventional MRI protocols provides haemodynamic information, assisting the diagnosis of vascular anomalies in the paediatric population at one-third of the dose of other MRI contrast agents. Copyright © 2015 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
43 CFR 2450.4 - Protests: Initial classification decision.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Protests: Initial classification decision... CLASSIFICATION SYSTEM Petition-Application Procedures § 2450.4 Protests: Initial classification decision. (a) For a period of 30 days after the proposed classification decision has been served upon the parties...
Accelerating Airy beams with non-parabolic trajectories
NASA Astrophysics Data System (ADS)
Besieris, Ioannis M.; Shaarawi, Amr M.
2014-11-01
A class of Airy accelerating beams with non-parabolic trajectories are derived by means of a novel application of a conformal transformation originally due to Bateman. It is also shown that the salient features of these beams are very simply incorporated in a solution which is derived by applying a conventional conformal transformation together with a Galilean translation to the basic accelerating Airy beam solution of the two-dimensional paraxial equation. Motivation for the non-parabolic beam trajectories is provided and the effects of finite-energy requirements are discussed.
Trajectory Software With Upper Atmosphere Model
NASA Technical Reports Server (NTRS)
Barrett, Charles
2012-01-01
The Trajectory Software Applications 6.0 for the Dec Alpha platform has an implementation of the Jacchia-Lineberry Upper Atmosphere Density Model used in the Mission Control Center for International Space Station support. Previous trajectory software required an upper atmosphere to support atmosphere drag calculations in the Mission Control Center. The Functional operation will differ depending on the end-use of the module. In general, the calling routine will use function-calling arguments to specify input to the processor. The atmosphere model will then compute and return atmospheric density at the time of interest.
Synthesis and size classification of metal oxide nanoparticles for biomedical applications
NASA Astrophysics Data System (ADS)
Atsumi, Takashi; Jeyadevan, Balachandran; Sato, Yoshinori; Tamura, Kazuchika; Aiba, Setsuya; Tohji, Kazuyuki
2004-12-01
Magnetic nanoparticles are considered for biomedical applications, such as the medium in magnetic resonance imaging, hyperthermia, drug delivery, and for the purification or classification of DNA or virus. The performance of magnetic nanoparticles in biomedical application such as hyperthermia depends very much on the magnetic properties, size and size distribution. We briefly described the basic idea behind their use in drug delivery, magnetic separation and hyperthermia and discussed the prerequisite properties magnetic particles for biomedical applications. Finally reported the synthesis and classification scheme to prepare magnetite (Fe3O4) nanoparticles with narrow size distribution for magnetic fluid hyperthermia.
Homotopy method for optimization of variable-specific-impulse low-thrust trajectories
NASA Astrophysics Data System (ADS)
Chi, Zhemin; Yang, Hongwei; Chen, Shiyu; Li, Junfeng
2017-11-01
The homotopy method has been used as a useful tool in solving fuel-optimal trajectories with constant-specific-impulse low thrust. However, the specific impulse is often variable for many practical solar electric power-limited thrusters. This paper investigates the application of the homotopy method for optimization of variable-specific-impulse low-thrust trajectories. Difficulties arise when the two commonly-used homotopy functions are employed for trajectory optimization. The optimal power throttle level and the optimal specific impulse are coupled with the commonly-used quadratic and logarithmic homotopy functions. To overcome these difficulties, a modified logarithmic homotopy function is proposed to serve as a gateway for trajectory optimization, leading to decoupled expressions of both the optimal power throttle level and the optimal specific impulse. The homotopy method based on this homotopy function is proposed. Numerical simulations validate the feasibility and high efficiency of the proposed method.
Trajectory tracking control for underactuated stratospheric airship
NASA Astrophysics Data System (ADS)
Zheng, Zewei; Huo, Wei; Wu, Zhe
2012-10-01
Stratospheric airship is a new kind of aerospace system which has attracted worldwide developing interests for its broad application prospects. Based on the trajectory linearization control (TLC) theory, a novel trajectory tracking control method for an underactuated stratospheric airship is presented in this paper. Firstly, the TLC theory is described sketchily, and the dynamic model of the stratospheric airship is introduced with kinematics and dynamics equations. Then, the trajectory tracking control strategy is deduced in detail. The designed control system possesses a cascaded structure which consists of desired attitude calculation, position control loop and attitude control loop. Two sub-loops are designed for the position and attitude control loops, respectively, including the kinematics control loop and dynamics control loop. Stability analysis shows that the controlled closed-loop system is exponentially stable. Finally, simulation results for the stratospheric airship to track typical trajectories are illustrated to verify effectiveness of the proposed approach.
Mixed Pattern Matching-Based Traffic Abnormal Behavior Recognition
Cui, Zhiming; Zhao, Pengpeng
2014-01-01
A motion trajectory is an intuitive representation form in time-space domain for a micromotion behavior of moving target. Trajectory analysis is an important approach to recognize abnormal behaviors of moving targets. Against the complexity of vehicle trajectories, this paper first proposed a trajectory pattern learning method based on dynamic time warping (DTW) and spectral clustering. It introduced the DTW distance to measure the distances between vehicle trajectories and determined the number of clusters automatically by a spectral clustering algorithm based on the distance matrix. Then, it clusters sample data points into different clusters. After the spatial patterns and direction patterns learned from the clusters, a recognition method for detecting vehicle abnormal behaviors based on mixed pattern matching was proposed. The experimental results show that the proposed technical scheme can recognize main types of traffic abnormal behaviors effectively and has good robustness. The real-world application verified its feasibility and the validity. PMID:24605045
High efficiency multishot interleaved spiral-in/out: acquisition for high-resolution BOLD fMRI.
Jung, Youngkyoo; Samsonov, Alexey A; Liu, Thomas T; Buracas, Giedrius T
2013-08-01
Growing demand for high spatial resolution blood oxygenation level dependent (BOLD) functional magnetic resonance imaging faces a challenge of the spatial resolution versus coverage or temporal resolution tradeoff, which can be addressed by methods that afford increased acquisition efficiency. Spiral acquisition trajectories have been shown to be superior to currently prevalent echo-planar imaging in terms of acquisition efficiency, and high spatial resolution can be achieved by employing multiple-shot spiral acquisition. The interleaved spiral in/out trajectory is preferred over spiral-in due to increased BOLD signal contrast-to-noise ratio (CNR) and higher acquisition efficiency than that of spiral-out or noninterleaved spiral in/out trajectories (Law & Glover. Magn Reson Med 2009; 62:829-834.), but to date applicability of the multishot interleaved spiral in/out for high spatial resolution imaging has not been studied. Herein we propose multishot interleaved spiral in/out acquisition and investigate its applicability for high spatial resolution BOLD functional magnetic resonance imaging. Images reconstructed from interleaved spiral-in and -out trajectories possess artifacts caused by differences in T2 decay, off-resonance, and k-space errors associated with the two trajectories. We analyze the associated errors and demonstrate that application of conjugate phase reconstruction and spectral filtering can substantially mitigate these image artifacts. After applying these processing steps, the multishot interleaved spiral in/out pulse sequence yields high BOLD CNR images at in-plane resolution below 1 × 1 mm while preserving acceptable temporal resolution (4 s) and brain coverage (15 slices of 2 mm thickness). Moreover, this method yields sufficient BOLD CNR at 1.5 mm isotropic resolution for detection of activation in hippocampus associated with cognitive tasks (Stern memory task). The multishot interleaved spiral in/out acquisition is a promising technique for high spatial resolution BOLD functional magnetic resonance imaging applications. © 2012 Wiley Periodicals, Inc.
NASA Technical Reports Server (NTRS)
Austin, J.
1986-01-01
Midstratospheric trajectories for February and March 1979 are calculated using geopotential analyses derived from limb infrared monitor of the stratosphere data. These trajectories are compared with the corresponding results using stratospheric sounding unit data. The trajectories are quasi-isentropic in that a radiation scheme is used to simply cross-isentrope flow. The results show that in disturbed conditions, quantitative agreement the trajectories, that is, within 25 great circle degrees (GCD) (one GCD about 110 km) may be valid for only 3 or 4 days, whereas during quiescent periods, quantitative agreement may last up to 10 days. By comparing trajectories calculated with different data some insight can be gained as to errors due to vertical resolution and horizontal resolution (due to infrequent sampling) in the analyzed geopotential height fields. For the disturbed trajectories described in this paper the horizontal resolution of the data was more important than vertical resolution; however, for the quiescent trajectories, which could be calculated accurately for a longer duration because of the absence of appreciable transients, the vertical resolution of the data was found to be more important than the horizontal resolution. It is speculated that these characteristics are also applicable to trajectories calculated during disturbed and quiescent periods in general. A review of some recently published trajectories shows that the qualitative conclusions of such works remains unaffected when the calculations are repeated using different data.
Dawes, Richard; Passalacqua, Alessio; Wagner, Albert F; Sewell, Thomas D; Minkoff, Michael; Thompson, Donald L
2009-04-14
We develop two approaches for growing a fitted potential energy surface (PES) by the interpolating moving least-squares (IMLS) technique using classical trajectories. We illustrate both approaches by calculating nitrous acid (HONO) cis-->trans isomerization trajectories under the control of ab initio forces from low-level HF/cc-pVDZ electronic structure calculations. In this illustrative example, as few as 300 ab initio energy/gradient calculations are required to converge the isomerization rate constant at a fixed energy to approximately 10%. Neither approach requires any preliminary electronic structure calculations or initial approximate representation of the PES (beyond information required for trajectory initial conditions). Hessians are not required. Both approaches rely on the fitting error estimation properties of IMLS fits. The first approach, called IMLS-accelerated direct dynamics, propagates individual trajectories directly with no preliminary exploratory trajectories. The PES is grown "on the fly" with the computation of new ab initio data only when a fitting error estimate exceeds a prescribed tight tolerance. The second approach, called dynamics-driven IMLS fitting, uses relatively inexpensive exploratory trajectories to both determine and fit the dynamically accessible configuration space. Once exploratory trajectories no longer find configurations with fitting error estimates higher than the designated accuracy, the IMLS fit is considered to be complete and usable in classical trajectory calculations or other applications.
Solid particle dynamic behavior through twisted blade rows
NASA Technical Reports Server (NTRS)
Hamed, A.
1982-01-01
The particle trajectory calculations provide the essential information which is required for predicting the pattern and intensity of turbomachinery erosion. Consequently, the evaluation of the machine performance deterioration due to erosion is extremely sensitive to the accuracy of the flow field and blade geometry representation in the trajectory computational model. A model is presented that is simple and efficient yet versatile and general to be applicable to axial, radial and mixed flow machines, and to inlets, nozzles, return passages and separators. The results of the computations are presented for the particle trajectories through a row of twisted vanes in the inlet flow field. The effect of the particle size on their trajectories, blade impacts, and on their redistribution and separation are discussed.
Fast Optimization for Aircraft Descent and Approach Trajectory
NASA Technical Reports Server (NTRS)
Luchinsky, Dmitry G.; Schuet, Stefan; Brenton, J.; Timucin, Dogan; Smith, David; Kaneshige, John
2017-01-01
We address problem of on-line scheduling of the aircraft descent and approach trajectory. We formulate a general multiphase optimal control problem for optimization of the descent trajectory and review available methods of its solution. We develop a fast algorithm for solution of this problem using two key components: (i) fast inference of the dynamical and control variables of the descending trajectory from the low dimensional flight profile data and (ii) efficient local search for the resulting reduced dimensionality non-linear optimization problem. We compare the performance of the proposed algorithm with numerical solution obtained using optimal control toolbox General Pseudospectral Optimal Control Software. We present results of the solution of the scheduling problem for aircraft descent using novel fast algorithm and discuss its future applications.
Two-Year Trajectory of Fall Risk in People With Parkinson Disease: A Latent Class Analysis.
Paul, Serene S; Thackeray, Anne; Duncan, Ryan P; Cavanaugh, James T; Ellis, Theresa D; Earhart, Gammon M; Ford, Matthew P; Foreman, K Bo; Dibble, Leland E
2016-03-01
To examine fall risk trajectories occurring naturally in a sample of individuals with early to middle stage Parkinson disease (PD). Latent class analysis, specifically growth mixture modeling (GMM), of longitudinal fall risk trajectories. Assessments were conducted at 1 of 4 universities. Community-dwelling participants with PD of a longitudinal cohort study who attended at least 2 of 5 assessments over a 2-year follow-up period (N=230). Not applicable. Fall risk trajectory (low, medium, or high risk) and stability of fall risk trajectory (stable or fluctuating). Fall risk was determined at 6 monthly intervals using a simple clinical tool based on fall history, freezing of gait, and gait speed. The GMM optimally grouped participants into 3 fall risk trajectories that closely mirrored baseline fall risk status (P=.001). The high fall risk trajectory was most common (42.6%) and included participants with longer and more severe disease and with higher postural instability and gait disability (PIGD) scores than the low and medium fall risk trajectories (P<.001). Fluctuating fall risk (posterior probability <0.8 of belonging to any trajectory) was found in only 22.6% of the sample, most commonly among individuals who were transitioning to PIGD predominance. Regardless of their baseline characteristics, most participants had clear and stable fall risk trajectories over 2 years. Further investigation is required to determine whether interventions to improve gait and balance may improve fall risk trajectories in people with PD. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chou, Chia-Chun, E-mail: ccchou@mx.nthu.edu.tw
2014-03-14
The complex quantum Hamilton-Jacobi equation-Bohmian trajectories (CQHJE-BT) method is introduced as a synthetic trajectory method for integrating the complex quantum Hamilton-Jacobi equation for the complex action function by propagating an ensemble of real-valued correlated Bohmian trajectories. Substituting the wave function expressed in exponential form in terms of the complex action into the time-dependent Schrödinger equation yields the complex quantum Hamilton-Jacobi equation. We transform this equation into the arbitrary Lagrangian-Eulerian version with the grid velocity matching the flow velocity of the probability fluid. The resulting equation describing the rate of change in the complex action transported along Bohmian trajectories is simultaneouslymore » integrated with the guidance equation for Bohmian trajectories, and the time-dependent wave function is readily synthesized. The spatial derivatives of the complex action required for the integration scheme are obtained by solving one moving least squares matrix equation. In addition, the method is applied to the photodissociation of NOCl. The photodissociation dynamics of NOCl can be accurately described by propagating a small ensemble of trajectories. This study demonstrates that the CQHJE-BT method combines the considerable advantages of both the real and the complex quantum trajectory methods previously developed for wave packet dynamics.« less
NASA Astrophysics Data System (ADS)
Sakuma, Jun; Wright, Rebecca N.
Privacy-preserving classification is the task of learning or training a classifier on the union of privately distributed datasets without sharing the datasets. The emphasis of existing studies in privacy-preserving classification has primarily been put on the design of privacy-preserving versions of particular data mining algorithms, However, in classification problems, preprocessing and postprocessing— such as model selection or attribute selection—play a prominent role in achieving higher classification accuracy. In this paper, we show generalization error of classifiers in privacy-preserving classification can be securely evaluated without sharing prediction results. Our main technical contribution is a new generalized Hamming distance protocol that is universally applicable to preprocessing and postprocessing of various privacy-preserving classification problems, such as model selection in support vector machine and attribute selection in naive Bayes classification.
Examining Cohort Effects in Developmental Trajectories of Substance Use
ERIC Educational Resources Information Center
Burns, Alison Reimuller; Hussong, Andrea M.; Solis, Jessica M.; Curran, Patrick J.; McGinley, James S.; Bauer, Daniel J.; Chassin, Laurie; Zucker, Robert A.
2017-01-01
The current study demonstrates the application of an analytic approach for incorporating multiple time trends in order to examine the impact of cohort effects on individual trajectories of eight drugs of abuse. Parallel analysis of two independent, longitudinal studies of high-risk youth that span ages 10 to 40 across 23 birth cohorts between 1968…
NASA Technical Reports Server (NTRS)
Hepner, George F.; Logan, Thomas; Ritter, Niles; Bryant, Nevin
1990-01-01
Recent research has shown an artificial neural network (ANN) to be capable of pattern recognition and the classification of image data. This paper examines the potential for the application of neural network computing to satellite image processing. A second objective is to provide a preliminary comparison and ANN classification. An artificial neural network can be trained to do land-cover classification of satellite imagery using selected sites representative of each class in a manner similar to conventional supervised classification. One of the major problems associated with recognition and classifications of pattern from remotely sensed data is the time and cost of developing a set of training sites. This reseach compares the use of an ANN back propagation classification procedure with a conventional supervised maximum likelihood classification procedure using a minimal training set. When using a minimal training set, the neural network is able to provide a land-cover classification superior to the classification derived from the conventional classification procedure. This research is the foundation for developing application parameters for further prototyping of software and hardware implementations for artificial neural networks in satellite image and geographic information processing.
NASA Astrophysics Data System (ADS)
Zhang, Chuan-Biao; Ming, Li; Xin, Zhou
2015-12-01
Ensemble simulations, which use multiple short independent trajectories from dispersive initial conformations, rather than a single long trajectory as used in traditional simulations, are expected to sample complex systems such as biomolecules much more efficiently. The re-weighted ensemble dynamics (RED) is designed to combine these short trajectories to reconstruct the global equilibrium distribution. In the RED, a number of conformational functions, named as basis functions, are applied to relate these trajectories to each other, then a detailed-balance-based linear equation is built, whose solution provides the weights of these trajectories in equilibrium distribution. Thus, the sufficient and efficient selection of basis functions is critical to the practical application of RED. Here, we review and present a few possible ways to generally construct basis functions for applying the RED in complex molecular systems. Especially, for systems with less priori knowledge, we could generally use the root mean squared deviation (RMSD) among conformations to split the whole conformational space into a set of cells, then use the RMSD-based-cell functions as basis functions. We demonstrate the application of the RED in typical systems, including a two-dimensional toy model, the lattice Potts model, and a short peptide system. The results indicate that the RED with the constructions of basis functions not only more efficiently sample the complex systems, but also provide a general way to understand the metastable structure of conformational space. Project supported by the National Natural Science Foundation of China (Grant No. 11175250).
40 CFR 152.171 - Restrictions other than those relating to use by certified applicators.
Code of Federal Regulations, 2014 CFR
2014-07-01
... PROTECTION AGENCY (CONTINUED) PESTICIDE PROGRAMS PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152.171 Restrictions other than those relating to use by certified applicators...
40 CFR 152.171 - Restrictions other than those relating to use by certified applicators.
Code of Federal Regulations, 2011 CFR
2011-07-01
... PROTECTION AGENCY (CONTINUED) PESTICIDE PROGRAMS PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152.171 Restrictions other than those relating to use by certified applicators...
40 CFR 152.171 - Restrictions other than those relating to use by certified applicators.
Code of Federal Regulations, 2012 CFR
2012-07-01
... PROTECTION AGENCY (CONTINUED) PESTICIDE PROGRAMS PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152.171 Restrictions other than those relating to use by certified applicators...
40 CFR 152.171 - Restrictions other than those relating to use by certified applicators.
Code of Federal Regulations, 2010 CFR
2010-07-01
... PROTECTION AGENCY (CONTINUED) PESTICIDE PROGRAMS PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152.171 Restrictions other than those relating to use by certified applicators...
Maufroy, Alexandra; Chassot, Emmanuel; Joo, Rocío; Kaplan, David Michael
2015-01-01
Since the 1990s, massive use of drifting Fish Aggregating Devices (dFADs) to aggregate tropical tunas has strongly modified global purse-seine fisheries. For the first time, a large data set of GPS positions from buoys deployed by French purse-seiners to monitor dFADs is analysed to provide information on spatio-temporal patterns of dFAD use in the Atlantic and Indian Oceans during 2007-2011. First, we select among four classification methods the model that best separates "at sea" from "on board" buoy positions. A random forest model had the best performance, both in terms of the rate of false "at sea" predictions and the amount of over-segmentation of "at sea" trajectories (i.e., artificial division of trajectories into multiple, shorter pieces due to misclassification). Performance is improved via post-processing removing unrealistically short "at sea" trajectories. Results derived from the selected model enable us to identify the main areas and seasons of dFAD deployment and the spatial extent of their drift. We find that dFADs drift at sea on average for 39.5 days, with time at sea being shorter and distance travelled longer in the Indian than in the Atlantic Ocean. 9.9% of all trajectories end with a beaching event, suggesting that 1,500-2,000 may be lost onshore each year, potentially impacting sensitive habitat areas, such as the coral reefs of the Maldives, the Chagos Archipelago, and the Seychelles.
Maufroy, Alexandra; Chassot, Emmanuel; Joo, Rocío; Kaplan, David Michael
2015-01-01
Since the 1990s, massive use of drifting Fish Aggregating Devices (dFADs) to aggregate tropical tunas has strongly modified global purse-seine fisheries. For the first time, a large data set of GPS positions from buoys deployed by French purse-seiners to monitor dFADs is analysed to provide information on spatio-temporal patterns of dFAD use in the Atlantic and Indian Oceans during 2007-2011. First, we select among four classification methods the model that best separates “at sea” from “on board” buoy positions. A random forest model had the best performance, both in terms of the rate of false “at sea” predictions and the amount of over-segmentation of “at sea” trajectories (i.e., artificial division of trajectories into multiple, shorter pieces due to misclassification). Performance is improved via post-processing removing unrealistically short “at sea” trajectories. Results derived from the selected model enable us to identify the main areas and seasons of dFAD deployment and the spatial extent of their drift. We find that dFADs drift at sea on average for 39.5 days, with time at sea being shorter and distance travelled longer in the Indian than in the Atlantic Ocean. 9.9% of all trajectories end with a beaching event, suggesting that 1,500-2,000 may be lost onshore each year, potentially impacting sensitive habitat areas, such as the coral reefs of the Maldives, the Chagos Archipelago, and the Seychelles. PMID:26010151
A new paradigm for atomically detailed simulations of kinetics in biophysical systems.
Elber, Ron
2017-01-01
The kinetics of biochemical and biophysical events determined the course of life processes and attracted considerable interest and research. For example, modeling of biological networks and cellular responses relies on the availability of information on rate coefficients. Atomically detailed simulations hold the promise of supplementing experimental data to obtain a more complete kinetic picture. However, simulations at biological time scales are challenging. Typical computer resources are insufficient to provide the ensemble of trajectories at the correct length that is required for straightforward calculations of time scales. In the last years, new technologies emerged that make atomically detailed simulations of rate coefficients possible. Instead of computing complete trajectories from reactants to products, these approaches launch a large number of short trajectories at different positions. Since the trajectories are short, they are computed trivially in parallel on modern computer architecture. The starting and termination positions of the short trajectories are chosen, following statistical mechanics theory, to enhance efficiency. These trajectories are analyzed. The analysis produces accurate estimates of time scales as long as hours. The theory of Milestoning that exploits the use of short trajectories is discussed, and several applications are described.
Code of Federal Regulations, 2011 CFR
2011-01-01
... may be made at the same time as the request for initial classification. The written application may... 7 Agriculture 2 2011-01-01 2011-01-01 false Conditions for review of classification and for... CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification Reviews and Micronaire Determinations...
Code of Federal Regulations, 2010 CFR
2010-01-01
... may be made at the same time as the request for initial classification. The written application may... 7 Agriculture 2 2010-01-01 2010-01-01 false Conditions for review of classification and for... CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification Reviews and Micronaire Determinations...
Xu, Dan; King, Kevin F; Liang, Zhi-Pei
2007-10-01
A new class of spiral trajectories called variable slew-rate spirals is proposed. The governing differential equations for a variable slew-rate spiral are derived, and both numeric and analytic solutions to the equations are given. The primary application of variable slew-rate spirals is peak B(1) amplitude reduction in 2D RF pulse design. The reduction of peak B(1) amplitude is achieved by changing the gradient slew-rate profile, and gradient amplitude and slew-rate constraints are inherently satisfied by the design of variable slew-rate spiral gradient waveforms. A design example of 2D RF pulses is given, which shows that under the same hardware constraints the RF pulse using a properly chosen variable slew-rate spiral trajectory can be much shorter than that using a conventional constant slew-rate spiral trajectory, thus having greater immunity to resonance frequency offsets.
Yang, Wen; Zhu, Jin-Yong; Lu, Kai-Hong; Wan, Li; Mao, Xiao-Hua
2014-06-01
Appropriate schemes for classification of freshwater phytoplankton are prerequisites and important tools for revealing phytoplanktonic succession and studying freshwater ecosystems. An alternative approach, functional group of freshwater phytoplankton, has been proposed and developed due to the deficiencies of Linnaean and molecular identification in ecological applications. The functional group of phytoplankton is a classification scheme based on autoecology. In this study, the theoretical basis and classification criterion of functional group (FG), morpho-functional group (MFG) and morphology-based functional group (MBFG) were summarized, as well as their merits and demerits. FG was considered as the optimal classification approach for the aquatic ecology research and aquatic environment evaluation. The application status of FG was introduced, with the evaluation standards and problems of two approaches to assess water quality on the basis of FG, index methods of Q and QR, being briefly discussed.
The role of psychosocial processes in the development and maintenance of chronic pain disorders
Edwards, Robert R.; Dworkin, Robert H.; Sullivan, Mark D.; Turk, Dennis; Wasan, Ajay D.
2016-01-01
The recently-proposed ACTTION-APS Pain Taxonomy provides an evidence-based, multidimensional, chronic pain classification system. Psychosocial factors play a crucial role within several dimensions of the Taxonomy. In this paper, we discuss the evaluation of psychosocial factors that influence the diagnosis and trajectory of chronic pain disorders. We review studies in individuals with a variety of persistent pain conditions, and describe evidence that psychosocial variables play key roles in conferring risk for the development of pain, in shaping long-term pain-related adjustment, and in modulating pain treatment outcomes. We consider both “general” psychosocial variables such as negative affect, childhood trauma, and social support, as well as “pain-specific” psychosocial variables that include pain-related catastrophizing, self-efficacy for managing pain, and pain-related coping. Collectively, the complexity and profound variability in chronic pain highlights the need to better understand the multidimensional array of interacting forces that determine the trajectory of chronic pain conditions. PMID:27586832
Addressing location uncertainties in GPS-based activity monitoring: A methodological framework
Wan, Neng; Lin, Ge; Wilson, Gaines J.
2016-01-01
Location uncertainty has been a major barrier in information mining from location data. Although the development of electronic and telecommunication equipment has led to an increased amount and refined resolution of data about individuals’ spatio-temporal trajectories, the potential of such data, especially in the context of environmental health studies, has not been fully realized due to the lack of methodology that addresses location uncertainties. This article describes a methodological framework for deriving information about people’s continuous activities from individual-collected Global Positioning System (GPS) data, which is vital for a variety of environmental health studies. This framework is composed of two major methods that address critical issues at different stages of GPS data processing: (1) a fuzzy classification method for distinguishing activity patterns; and (2) a scale-adaptive method for refining activity locations and outdoor/indoor environments. Evaluation of this framework based on smartphone-collected GPS data indicates that it is robust to location errors and is able to generate useful information about individuals’ life trajectories. PMID:28943777
Neurogliaform cortical interneurons derive from cells in the preoptic area
Cadilhac, Christelle; Prados, Julien; Holtmaat, Anthony
2018-01-01
Delineating the basic cellular components of cortical inhibitory circuits remains a fundamental issue in order to understand their specific contributions to microcircuit function. It is still unclear how current classifications of cortical interneuron subtypes relate to biological processes such as their developmental specification. Here we identified the developmental trajectory of neurogliaform cells (NGCs), the main effectors of a powerful inhibitory motif recruited by long-range connections. Using in vivo genetic lineage-tracing in mice, we report that NGCs originate from a specific pool of 5-HT3AR-expressing Hmx3+ cells located in the preoptic area (POA). Hmx3-derived 5-HT3AR+ cortical interneurons (INs) expressed the transcription factors PROX1, NR2F2, the marker reelin but not VIP and exhibited the molecular, morphological and electrophysiological profile of NGCs. Overall, these results indicate that NGCs are a distinct class of INs with a unique developmental trajectory and open the possibility to study their specific functional contribution to cortical inhibitory microcircuit motifs. PMID:29557780
Mirza, Nazrat; Phan, Thao-Ly; Tester, June; Fals, Angela; Fernandez, Cristina; Datto, George; Estrada, Elizabeth; Eneli, Ihuoma
2018-05-23
Severe obesity defined as an age- and gender-specific body mass index ≥120% of the 95th percentile in children younger than 5 years is well recognized as a significant challenge for prevention and treatment. This article provides an overview of the prevalence, classification of obesity severity, patterns of weight gain trajectory, medical and genetic risk factors, and comorbid disorders among young children with an emphasis on severe obesity. Studies suggest rapid weight gain trajectory in infancy, maternal smoking, maternal gestational diabetes, and genetic conditions are associated with an increased risk for severe obesity in early childhood. Among populations of young children with severe obesity seeking care, co-morbid conditions such as dyslipidemia and fatty liver disease are present and families report behavioral concerns and developmental delays. Children with severe obesity by age 5 represent a vulnerable population of children at high medical risk and need to be identified early and appropriately managed.
7 CFR 27.57 - Request for postponement.
Code of Federal Regulations, 2010 CFR
2010-01-01
... REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Postponed Classification § 27.57 Request for postponement. If the applicant desires the postponement of the classification of any cotton covered by a classification request filed pursuant to the regulations in this subpart until later...
7 CFR 27.57 - Request for postponement.
Code of Federal Regulations, 2011 CFR
2011-01-01
... REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Postponed Classification § 27.57 Request for postponement. If the applicant desires the postponement of the classification of any cotton covered by a classification request filed pursuant to the regulations in this subpart until later...
2011-01-01
Background In view of the long term discussion on the appropriateness of the dengue classification into dengue fever (DF), dengue haemorrhagic fever (DHF) and dengue shock syndrome (DSS), the World Health Organization (WHO) has outlined in its new global dengue guidelines a revised classification into levels of severity: dengue fever with an intermediary group of "dengue fever with warning sings", and severe dengue. The objective of this paper was to compare the two classification systems regarding applicability in clinical practice and surveillance, as well as user-friendliness and acceptance by health staff. Methods A mix of quantitative (prospective and retrospective review of medical charts by expert reviewers, formal staff interviews), semi-quantitative (open questions in staff interviews) and qualitative methods (focus group discussions) were used in 18 countries. Quality control of data collected was undertaken by external monitors. Results The applicability of the DF/DHF/DSS classification was limited, even when strict DHF criteria were not applied (13.7% of dengue cases could not be classified using the DF/DHF/DSS classification by experienced reviewers, compared to only 1.6% with the revised classification). The fact that some severe dengue cases could not be classified in the DF/DHF/DSS system was of particular concern. Both acceptance and perceived user-friendliness of the revised system were high, particularly in relation to triage and case management. The applicability of the revised classification to retrospective data sets (of importance for dengue surveillance) was also favourable. However, the need for training, dissemination and further research on the warning signs was highlighted. Conclusions The revised dengue classification has a high potential for facilitating dengue case management and surveillance. PMID:21510901
Point-Mass Aircraft Trajectory Prediction Using a Hierarchical, Highly-Adaptable Software Design
NASA Technical Reports Server (NTRS)
Karr, David A.; Vivona, Robert A.; Woods, Sharon E.; Wing, David J.
2017-01-01
A highly adaptable and extensible method for predicting four-dimensional trajectories of civil aircraft has been developed. This method, Behavior-Based Trajectory Prediction, is based on taxonomic concepts developed for the description and comparison of trajectory prediction software. A hierarchical approach to the "behavioral" layer of a point-mass model of aircraft flight, a clear separation between the "behavioral" and "mathematical" layers of the model, and an abstraction of the methods of integrating differential equations in the "mathematical" layer have been demonstrated to support aircraft models of different types (in particular, turbojet vs. turboprop aircraft) using performance models at different levels of detail and in different formats, and promise to be easily extensible to other aircraft types and sources of data. The resulting trajectories predict location, altitude, lateral and vertical speeds, and fuel consumption along the flight path of the subject aircraft accurately and quickly, accounting for local conditions of wind and outside air temperature. The Behavior-Based Trajectory Prediction concept was implemented in NASA's Traffic Aware Planner (TAP) flight-optimizing cockpit software application.
NASA Technical Reports Server (NTRS)
Chen, Guanrong
1991-01-01
An optimal trajectory planning problem for a single-link, flexible joint manipulator is studied. A global feedback-linearization is first applied to formulate the nonlinear inequality-constrained optimization problem in a suitable way. Then, an exact and explicit structural formula for the optimal solution of the problem is derived and the solution is shown to be unique. It turns out that the optimal trajectory planning and control can be done off-line, so that the proposed method is applicable to both theoretical analysis and real time tele-robotics control engineering.
SeGRAm - A practical and versatile tool for spacecraft trajectory optimization
NASA Technical Reports Server (NTRS)
Rishikof, Brian H.; Mccormick, Bernell R.; Pritchard, Robert E.; Sponaugle, Steven J.
1991-01-01
An implementation of the Sequential Gradient/Restoration Algorithm, SeGRAm, is presented along with selected examples. This spacecraft trajectory optimization and simulation program uses variational calculus to solve problems of spacecraft flying under the influence of one or more gravitational bodies. It produces a series of feasible solutions to problems involving a wide range of vehicles, environments and optimization functions, until an optimal solution is found. The examples included highlight the various capabilities of the program and emphasize in particular its versatility over a wide spectrum of applications from ascent to interplanetary trajectories.
Multiobjective Optimization of Low-Energy Trajectories Using Optimal Control on Dynamical Channels
NASA Technical Reports Server (NTRS)
Coffee, Thomas M.; Anderson, Rodney L.; Lo, Martin W.
2011-01-01
We introduce a computational method to design efficient low-energy trajectories by extracting initial solutions from dynamical channels formed by invariant manifolds, and improving these solutions through variational optimal control. We consider trajectories connecting two unstable periodic orbits in the circular restricted 3-body problem (CR3BP). Our method leverages dynamical channels to generate a range of solutions, and approximates the areto front for impulse and time of flight through a multiobjective optimization of these solutions based on primer vector theory. We demonstrate the application of our method to a libration orbit transfer in the Earth-Moon system.
48 CFR 47.305-9 - Commodity description and freight classification.
Code of Federal Regulations, 2010 CFR
2010-10-01
... freight classification. 47.305-9 Section 47.305-9 Federal Acquisition Regulations System FEDERAL... Commodity description and freight classification. (a) Generally, the freight rate for supplies is based on the rating applicable to the freight classification description published in the National Motor...
Best-Fit Conic Approximation of Spacecraft Trajectory
NASA Technical Reports Server (NTRS)
Singh, Gurkipal
2005-01-01
A computer program calculates a best conic fit of a given spacecraft trajectory. Spacecraft trajectories are often propagated as conics onboard. The conic-section parameters as a result of the best-conic-fit are uplinked to computers aboard the spacecraft for use in updating predictions of the spacecraft trajectory for operational purposes. In the initial application for which this program was written, there is a requirement to fit a single conic section (necessitated by onboard memory constraints) accurate within 200 microradians to a sequence of positions measured over a 4.7-hour interval. The present program supplants a prior one that could not cover the interval with fewer than four successive conic sections. The present program is based on formulating the best-fit conic problem as a parameter-optimization problem and solving the problem numerically, on the ground, by use of a modified steepest-descent algorithm. For the purpose of this algorithm, optimization is defined as minimization of the maximum directional propagation error across the fit interval. In the specific initial application, the program generates a single 4.7-hour conic, the directional propagation of which is accurate to within 34 microradians easily exceeding the mission constraints by a wide margin.
NASA Astrophysics Data System (ADS)
MacKenzie, Rob; Fawole, Olusegun Gabriel; Levine, James; Cai, Xiaoming
2016-04-01
Gas flaring, the disposal of gas through stacks in an open-air flame, is a common feature in the processing of crude oil, especially in oil-rich regions of the world. Gas flaring is a prominent source of volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAH), CO, CO2, nitrogen oxides (NOx), SO2 (in "sour" gas only), and soot (black carbon), as well as the release of locally significant amounts of heat. The rates of emission of these pollutants from gas flaring depend on a number of factors including, but not limited to, fuel composition and quantity, stack geometry, flame/combustion characteristics, and prevailing meteorological conditions. Here, we derive new estimated emission factors (EFs) for carbon-containing pollutants (excluding PAH). The air pollution dispersion model, ADMS5, is used to simulate the dispersion of the pollutants from flaring stacks in the Niger delta. A seasonal variation of the dispersion pattern of the pollutant within a year is studied in relation to the movements of the West Africa Monsoon (WAM) and other prevailing meteorological factors. Further, we have clustered AERONET aerosol signals using trajectory analysis to identify dominant aerosol sources at the Ilorin site in West Africa (4.34 oE, 8.32 oN). A 10-year trajectory-based analysis was undertaken (2005-2015, excluding 2010). Of particular interest are air masses that have passed through the gas flaring region in the Niger Delta area en-route the AERONET site. 7-day back trajectories were calculated using the UK Universities Global Atmospheric Modelling Programme (UGAMP) trajectory model which is driven by analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF). From the back-trajectory calculations, dominant sources are identified, using literature classifications: desert dust (DD); Biomass burning (BB); and Urban-Industrial (UI). We use a combination of synoptic trajectories and aerosol optical properties to distinguish a fourth source: that due to gas flaring. We discuss the relative impact of these different aerosol sources on the overall radiative forcing at Ilorin AERONET site.
Crocker, Anne G; Nicholls, Tonia L; Seto, Michael C; Côté, Gilles; Charette, Yanick; Caulet, Malijai
2015-01-01
The National Trajectory Project examined longitudinal data from a large sample of people found not criminally responsible on account of mental disorder (NCRMD) to assess the presence of provincial differences in the application of the law, to examine the characteristics of people with serious mental illness who come into conflict with the law and receive this verdict, and to investigate the trajectories of NCRMD–accused people as they traverse the mental health and criminal justice systems. Our paper describes the rationale for the National Trajectory Project and the methods used to collect data in Quebec, Ontario, and British Columbia, the 3 most populous provinces in Canada and the 3 provinces with the most people found NCRMD. PMID:25886685
Surface Modeling of Workpiece and Tool Trajectory Planning for Spray Painting Robot
Tang, Yang; Chen, Wei
2015-01-01
Automated tool trajectory planning for spray-painting robots is still a challenging problem, especially for a large free-form surface. A grid approximation of a free-form surface is adopted in CAD modeling in this paper. A free-form surface model is approximated by a set of flat patches. We describe here an efficient and flexible tool trajectory optimization scheme using T-Bézier curves calculated in a new way from trigonometrical bases. The distance between the spray gun and the free-form surface along the normal vector is varied. Automotive body parts, which are large free-form surfaces, are used to test the scheme. The experimental results show that the trajectory planning algorithm achieves satisfactory performance. This algorithm can also be extended to other applications. PMID:25993663
Surface modeling of workpiece and tool trajectory planning for spray painting robot.
Tang, Yang; Chen, Wei
2015-01-01
Automated tool trajectory planning for spray-painting robots is still a challenging problem, especially for a large free-form surface. A grid approximation of a free-form surface is adopted in CAD modeling in this paper. A free-form surface model is approximated by a set of flat patches. We describe here an efficient and flexible tool trajectory optimization scheme using T-Bézier curves calculated in a new way from trigonometrical bases. The distance between the spray gun and the free-form surface along the normal vector is varied. Automotive body parts, which are large free-form surfaces, are used to test the scheme. The experimental results show that the trajectory planning algorithm achieves satisfactory performance. This algorithm can also be extended to other applications.
On the design of fuzzified trajectory shaping guidance law.
Lin, Chun-Liang; Lin, Yu-Ping; Chen, Kai-Ming
2009-04-01
Midcourse guidance is commonly designed to save as much energy as possible so that the missile's final speed can be maximized while entering the homing stage. For this purpose, a competitive guidance design should be able to generate an admissible flight trajectory as to bring the interceptor to a superior altitude for a favorable target engagement. In this paper, a new adaptive trajectory shaping guidance scheme based on the adaptive fuzzy inference system, which is capable of generating a variety of trajectories for efficient target interception, is presented. The guidance law is developed with the aim of saving the interceptor's energy conservation while improving performance robustness. Applications of the presented approach have included a variety of mission oriented guidance, such as cruise missile guidance, anti-ballistic missile guidance, etc.
Autonomous underwater vehicle adaptive path planning for target classification
NASA Astrophysics Data System (ADS)
Edwards, Joseph R.; Schmidt, Henrik
2002-11-01
Autonomous underwater vehicles (AUVs) are being rapidly developed to carry sensors into the sea in ways that have previously not been possible. The full use of the vehicles, however, is still not near realization due to lack of the true vehicle autonomy that is promised in the label (AUV). AUVs today primarily attempt to follow as closely as possible a preplanned trajectory. The key to increasing the autonomy of the AUV is to provide the vehicle with a means to make decisions based on its sensor receptions. The current work examines the use of active sonar returns from mine-like objects (MLOs) as a basis for sensor-based adaptive path planning, where the path planning objective is to discriminate between real mines and rocks. Once a target is detected in the mine hunting phase, the mine classification phase is initialized with a derivative cost function to emphasize signal differences and enhance classification capability. The AUV moves adaptively to minimize the cost function. The algorithm is verified using at-sea data derived from the joint MIT/SACLANTCEN GOATS experiments and advanced acoustic simulation using SEALAB. The mission oriented operating system (MOOS) real-time simulator is then used to test the onboard implementation of the algorithm.
An automatic aerosol classification for earlinet: application and results
NASA Astrophysics Data System (ADS)
Papagiannopoulos, Nikolaos; Mona, Lucia; Amiridis, Vassilis; Binietoglou, Ioannis; D'Amico, Giuseppe; Guma-Claramunt, P.; Schwarz, Anja; Alados-Arboledas, Lucas; Amodeo, Aldo; Apituley, Arnoud; Baars, Holger; Bortoli, Daniele; Comeron, Adolfo; Guerrero-Rascado, Juan Luis; Kokkalis, Panos; Nicolae, Doina; Papayannis, Alex; Pappalardo, Gelsomina; Wandinger, Ulla; Wiegner, Matthias
2018-04-01
Aerosol typing is essential for understanding the impact of the different aerosol sources on climate, weather system and air quality. An aerosol classification method for EARLINET (European Aerosol Research Lidar Network) measurements is introduced which makes use the Mahalanobis distance classifier. The performance of the automatic classification is tested against manually classified EARLINET data. Results of the application of the method to an extensive aerosol dataset will be presented.
48 CFR 22.406-3 - Additional classifications.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 48 Federal Acquisition Regulations System 1 2010-10-01 2010-10-01 false Additional classifications... Involving Construction 22.406-3 Additional classifications. (a) If any laborer or mechanic is to be employed in a classification that is not listed in the wage determination applicable to the contract, the...
49 CFR 1105.6 - Classification of actions.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 49 Transportation 8 2011-10-01 2011-10-01 false Classification of actions. 1105.6 Section 1105.6... Classification of actions. (a) Environmental Impact Statements will normally be prepared for rail construction... classifications in this section apply without regard to whether the action is proposed by application, petition...
Average Likelihood Methods of Classification of Code Division Multiple Access (CDMA)
2016-05-01
case of cognitive radio applications. Modulation classification is part of a broader problem known as blind or uncooperative demodulation the goal of...Introduction 2 2.1 Modulation Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.2 Research Objectives...6 3 Modulation Classification Methods 7 3.0.1 Ad Hoc
48 CFR 22.406-3 - Additional classifications.
Code of Federal Regulations, 2013 CFR
2013-10-01
... 48 Federal Acquisition Regulations System 1 2013-10-01 2013-10-01 false Additional classifications... Involving Construction 22.406-3 Additional classifications. (a) If any laborer or mechanic is to be employed in a classification that is not listed in the wage determination applicable to the contract, the...
48 CFR 22.406-3 - Additional classifications.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 48 Federal Acquisition Regulations System 1 2012-10-01 2012-10-01 false Additional classifications... Involving Construction 22.406-3 Additional classifications. (a) If any laborer or mechanic is to be employed in a classification that is not listed in the wage determination applicable to the contract, the...
48 CFR 22.406-3 - Additional classifications.
Code of Federal Regulations, 2014 CFR
2014-10-01
... 48 Federal Acquisition Regulations System 1 2014-10-01 2014-10-01 false Additional classifications... Involving Construction 22.406-3 Additional classifications. (a) If any laborer or mechanic is to be employed in a classification that is not listed in the wage determination applicable to the contract, the...
12 CFR 560.160 - Asset classification.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 12 Banks and Banking 6 2014-01-01 2012-01-01 true Asset classification. 560.160 Section 560.160... Lending and Investment Provisions Applicable to all Savings Associations § 560.160 Asset classification... consistent with, or reconcilable to, the asset classification system used by OTS in its Thrift Activities...
12 CFR 560.160 - Asset classification.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 12 Banks and Banking 6 2013-01-01 2012-01-01 true Asset classification. 560.160 Section 560.160... Lending and Investment Provisions Applicable to all Savings Associations § 560.160 Asset classification... consistent with, or reconcilable to, the asset classification system used by OTS in its Thrift Activities...
12 CFR 560.160 - Asset classification.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 12 Banks and Banking 6 2012-01-01 2012-01-01 false Asset classification. 560.160 Section 560.160... Lending and Investment Provisions Applicable to all Savings Associations § 560.160 Asset classification... consistent with, or reconcilable to, the asset classification system used by OTS in its Thrift Activities...
49 CFR 1105.6 - Classification of actions.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 49 Transportation 8 2010-10-01 2010-10-01 false Classification of actions. 1105.6 Section 1105.6... Classification of actions. (a) Environmental Impact Statements will normally be prepared for rail construction... classifications in this section apply without regard to whether the action is proposed by application, petition...
48 CFR 22.406-3 - Additional classifications.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 48 Federal Acquisition Regulations System 1 2011-10-01 2011-10-01 false Additional classifications... Involving Construction 22.406-3 Additional classifications. (a) If any laborer or mechanic is to be employed in a classification that is not listed in the wage determination applicable to the contract, the...
12 CFR 560.160 - Asset classification.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 12 Banks and Banking 5 2011-01-01 2011-01-01 false Asset classification. 560.160 Section 560.160... Lending and Investment Provisions Applicable to all Savings Associations § 560.160 Asset classification... consistent with, or reconcilable to, the asset classification system used by OTS in its Thrift Activities...
Wu, Johnny; Witkiewitz, Katie; McMahon, Robert J; Dodge, Kenneth A
2010-10-01
Conduct problems, substance use, and risky sexual behavior have been shown to coexist among adolescents, which may lead to significant health problems. The current study was designed to examine relations among these problem behaviors in a community sample of children at high risk for conduct disorder. A latent growth model of childhood conduct problems showed a decreasing trend from grades K to 5. During adolescence, four concurrent conduct problem and substance use trajectory classes were identified (high conduct problems and high substance use, increasing conduct problems and increasing substance use, minimal conduct problems and increasing substance use, and minimal conduct problems and minimal substance use) using a parallel process growth mixture model. Across all substances (tobacco, binge drinking, and marijuana use), higher levels of childhood conduct problems during kindergarten predicted a greater probability of classification into more problematic adolescent trajectory classes relative to less problematic classes. For tobacco and binge drinking models, increases in childhood conduct problems over time also predicted a greater probability of classification into more problematic classes. For all models, individuals classified into more problematic classes showed higher proportions of early sexual intercourse, infrequent condom use, receiving money for sexual services, and ever contracting an STD. Specifically, tobacco use and binge drinking during early adolescence predicted higher levels of sexual risk taking into late adolescence. Results highlight the importance of studying the conjoint relations among conduct problems, substance use, and risky sexual behavior in a unified model. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Brauer, G. L.; Cornick, D. E.; Stevenson, R.
1977-01-01
The capabilities and applications of the three-degree-of-freedom (3DOF) version and the six-degree-of-freedom (6DOF) version of the Program to Optimize Simulated Trajectories (POST) are summarized. The document supplements the detailed program manuals by providing additional information that motivates and clarifies basic capabilities, input procedures, applications and computer requirements of these programs. The information will enable prospective users to evaluate the programs, and to determine if they are applicable to their problems. Enough information is given to enable managerial personnel to evaluate the capabilities of the programs and describes the POST structure, formulation, input and output procedures, sample cases, and computer requirements. The report also provides answers to basic questions concerning planet and vehicle modeling, simulation accuracy, optimization capabilities, and general input rules. Several sample cases are presented.
Image Analysis and Classification Based on Soil Strength
2016-08-01
Satellite imagery classification is useful for a variety of commonly used ap- plications, such as land use classification, agriculture , wetland...required use of a coinci- dent digital elevation model (DEM) and a high-resolution orthophoto- graph collected by the National Agriculture Imagery Program...14. ABSTRACT Satellite imagery classification is useful for a variety of commonly used applications, such as land use classification, agriculture
NASA Astrophysics Data System (ADS)
Hughes, Kyle M.
Gravity-assist trajectories to Uranus and Neptune are found (with the allowance of impulsive maneuvers using chemical propulsion) for launch dates ranging from 2024 to 2038 for Uranus and 2020 to 2070 for Neptune. Solutions are found using a patched conic model with analytical ephemeris via the Satellite Tour Design Program (STOUR), originally developed at the Jet Propulsion Laboratory (JPL). Delivered payload mass is computed for all solutions for select launch vehicles, and attractive solutions are identified as those that deliver a specified amount of payload mass into orbit at the target body in minimum time. The best cases for each launch year are cataloged for orbiter missions to Uranus and Neptune. Solutions with sufficient delivered payload for a multi-planet mission (e.g. sending a probe to Saturn on the way to delivering an orbiter at Uranus) become available when the Space Launch System (SLS) launch vehicle is employed. A set of possible approach trajectories are modeled at the target planet to assess what (if any) adjustments are needed for ring avoidance, and to determine the probe entry conditions. Mars free-return trajectories are found with an emphasis on short flight times for application to near-term human flyby missions (similar to that of Inspiration Mars). Venus free-returns are also investigated and proposed as an alternative to a human Mars flyby mission. Attractive Earth-Mars free-return opportunities are identified that use an intermediate Venus flyby. One such opportunity, in 2021, has been adopted by the Inspiration Mars Foundation as a backup to the currently considered 2018 Mars free-return opportunity. Methods to establish spacecraft into Earth-Mars cycler trajectories are also investigated to reduce the propellant cost required to inject a 95-metric ton spacecraft into a cycler orbit. The establishment trajectories considered use either a V-infinity leveraging maneuver or low thrust. The V-infinity leveraging establishment trajectories are validated using patched conics via the STOUR program. Establishment trajectories that use low-thrust were investigated with particular focus on validating the patched-conic based solutions at instances where Earth encounter times are not negligible.
Federal Register 2010, 2011, 2012, 2013, 2014
2013-07-02
... Proposed Classification of Public Lands/Minerals for State Indemnity Selection, Colorado AGENCY: Bureau of Land Management, Interior. ACTION: Notice of Proposed Classification. SUMMARY: The Colorado State Board of Land Commissioners (State) has filed a petition for classification and application to obtain...
7 CFR 28.177 - Request for classification and comparison of cotton.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 7 Agriculture 2 2014-01-01 2014-01-01 false Request for classification and comparison of cotton... STANDARD CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.177 Request for classification and comparison of cotton. The applicant shall make a separate...
7 CFR 28.177 - Request for classification and comparison of cotton.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 7 Agriculture 2 2010-01-01 2010-01-01 false Request for classification and comparison of cotton... STANDARD CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.177 Request for classification and comparison of cotton. The applicant shall make a separate...
7 CFR 28.177 - Request for classification and comparison of cotton.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 7 Agriculture 2 2012-01-01 2012-01-01 false Request for classification and comparison of cotton... STANDARD CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.177 Request for classification and comparison of cotton. The applicant shall make a separate...
7 CFR 28.177 - Request for classification and comparison of cotton.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 7 Agriculture 2 2013-01-01 2013-01-01 false Request for classification and comparison of cotton... STANDARD CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.177 Request for classification and comparison of cotton. The applicant shall make a separate...
7 CFR 28.177 - Request for classification and comparison of cotton.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 7 Agriculture 2 2011-01-01 2011-01-01 false Request for classification and comparison of cotton... STANDARD CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.177 Request for classification and comparison of cotton. The applicant shall make a separate...
Pair-Wise Trajectory Management-Oceanic (PTM-O) . [Concept of Operations—Version 3.9
NASA Technical Reports Server (NTRS)
Jones, Kenneth M.
2014-01-01
This document describes the Pair-wise Trajectory Management-Oceanic (PTM-O) Concept of Operations (ConOps). Pair-wise Trajectory Management (PTM) is a concept that includes airborne and ground-based capabilities designed to enable and to benefit from, airborne pair-wise distance-monitoring capability. PTM includes the capabilities needed for the controller to issue a PTM clearance that resolves a conflict for a specific pair of aircraft. PTM avionics include the capabilities needed for the flight crew to manage their trajectory relative to specific designated aircraft. Pair-wise Trajectory Management PTM-Oceanic (PTM-O) is a regional specific application of the PTM concept. PTM is sponsored by the National Aeronautics and Space Administration (NASA) Concept and Technology Development Project (part of NASA's Airspace Systems Program). The goal of PTM is to use enhanced and distributed communications and surveillance along with airborne tools to permit reduced separation standards for given aircraft pairs, thereby increasing the capacity and efficiency of aircraft operations at a given altitude or volume of airspace.
NASA Astrophysics Data System (ADS)
Schlueter-Kuck, Kristy L.; Dabiri, John O.
2017-09-01
We present a method for identifying the coherent structures associated with individual Lagrangian flow trajectories even where only sparse particle trajectory data are available. The method, based on techniques in spectral graph theory, uses the Coherent Structure Coloring vector and associated eigenvectors to analyze the distance in higher-dimensional eigenspace between a selected reference trajectory and other tracer trajectories in the flow. By analyzing this distance metric in a hierarchical clustering, the coherent structure of which the reference particle is a member can be identified. This algorithm is proven successful in identifying coherent structures of varying complexities in canonical unsteady flows. Additionally, the method is able to assess the relative coherence of the associated structure in comparison to the surrounding flow. Although the method is demonstrated here in the context of fluid flow kinematics, the generality of the approach allows for its potential application to other unsupervised clustering problems in dynamical systems such as neuronal activity, gene expression, or social networks.
Particle trajectory computation on a 3-dimensional engine inlet. Final Report Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Kim, J. J.
1986-01-01
A 3-dimensional particle trajectory computer code was developed to compute the distribution of water droplet impingement efficiency on a 3-dimensional engine inlet. The computed results provide the essential droplet impingement data required for the engine inlet anti-icing system design and analysis. The droplet trajectories are obtained by solving the trajectory equation using the fourth order Runge-Kutta and Adams predictor-corrector schemes. A compressible 3-D full potential flow code is employed to obtain a cylindrical grid definition of the flowfield on and about the engine inlet. The inlet surface is defined mathematically through a system of bi-cubic parametric patches in order to compute the droplet impingement points accurately. Analysis results of the 3-D trajectory code obtained for an axisymmetric droplet impingement problem are in good agreement with NACA experimental data. Experimental data are not yet available for the engine inlet impingement problem analyzed. Applicability of the method to solid particle impingement problems, such as engine sand ingestion, is also demonstrated.
Neural Network Training by Integration of Adjoint Systems of Equations Forward in Time
NASA Technical Reports Server (NTRS)
Toomarian, Nikzad (Inventor); Barhen, Jacob (Inventor)
1999-01-01
A method and apparatus for supervised neural learning of time dependent trajectories exploits the concepts of adjoint operators to enable computation of the gradient of an objective functional with respect to the various parameters of the network architecture in a highly efficient manner. Specifically. it combines the advantage of dramatic reductions in computational complexity inherent in adjoint methods with the ability to solve two adjoint systems of equations together forward in time. Not only is a large amount of computation and storage saved. but the handling of real-time applications becomes also possible. The invention has been applied it to two examples of representative complexity which have recently been analyzed in the open literature and demonstrated that a circular trajectory can be learned in approximately 200 iterations compared to the 12000 reported in the literature. A figure eight trajectory was achieved in under 500 iterations compared to 20000 previously required. Tbc trajectories computed using our new method are much closer to the target trajectories than was reported in previous studies.
Neural network training by integration of adjoint systems of equations forward in time
NASA Technical Reports Server (NTRS)
Toomarian, Nikzad (Inventor); Barhen, Jacob (Inventor)
1992-01-01
A method and apparatus for supervised neural learning of time dependent trajectories exploits the concepts of adjoint operators to enable computation of the gradient of an objective functional with respect to the various parameters of the network architecture in a highly efficient manner. Specifically, it combines the advantage of dramatic reductions in computational complexity inherent in adjoint methods with the ability to solve two adjoint systems of equations together forward in time. Not only is a large amount of computation and storage saved, but the handling of real-time applications becomes also possible. The invention has been applied it to two examples of representative complexity which have recently been analyzed in the open literature and demonstrated that a circular trajectory can be learned in approximately 200 iterations compared to the 12000 reported in the literature. A figure eight trajectory was achieved in under 500 iterations compared to 20000 previously required. The trajectories computed using our new method are much closer to the target trajectories than was reported in previous studies.
NASA Astrophysics Data System (ADS)
Mukherjee, Sayak; Stewart, David; Stewart, William; Lanier, Lewis L.; Das, Jayajit
2017-08-01
Single-cell responses are shaped by the geometry of signalling kinetic trajectories carved in a multidimensional space spanned by signalling protein abundances. It is, however, challenging to assay a large number (more than 3) of signalling species in live-cell imaging, which makes it difficult to probe single-cell signalling kinetic trajectories in large dimensions. Flow and mass cytometry techniques can measure a large number (4 to more than 40) of signalling species but are unable to track single cells. Thus, cytometry experiments provide detailed time-stamped snapshots of single-cell signalling kinetics. Is it possible to use the time-stamped cytometry data to reconstruct single-cell signalling trajectories? Borrowing concepts of conserved and slow variables from non-equilibrium statistical physics we develop an approach to reconstruct signalling trajectories using snapshot data by creating new variables that remain invariant or vary slowly during the signalling kinetics. We apply this approach to reconstruct trajectories using snapshot data obtained from in silico simulations, live-cell imaging measurements, and, synthetic flow cytometry datasets. The application of invariants and slow variables to reconstruct trajectories provides a radically different way to track objects using snapshot data. The approach is likely to have implications for solving matching problems in a wide range of disciplines.
Timing of transients: quantifying reaching times and transient behavior in complex systems
NASA Astrophysics Data System (ADS)
Kittel, Tim; Heitzig, Jobst; Webster, Kevin; Kurths, Jürgen
2017-08-01
In dynamical systems, one may ask how long it takes for a trajectory to reach the attractor, i.e. how long it spends in the transient phase. Although for a single trajectory the mathematically precise answer may be infinity, it still makes sense to compare different trajectories and quantify which of them approaches the attractor earlier. In this article, we categorize several problems of quantifying such transient times. To treat them, we propose two metrics, area under distance curve and regularized reaching time, that capture two complementary aspects of transient dynamics. The first, area under distance curve, is the distance of the trajectory to the attractor integrated over time. It measures which trajectories are ‘reluctant’, i.e. stay distant from the attractor for long, or ‘eager’ to approach it right away. Regularized reaching time, on the other hand, quantifies the additional time (positive or negative) that a trajectory starting at a chosen initial condition needs to approach the attractor as compared to some reference trajectory. A positive or negative value means that it approaches the attractor by this much ‘earlier’ or ‘later’ than the reference, respectively. We demonstrated their substantial potential for application with multiple paradigmatic examples uncovering new features.
SOM Classification of Martian TES Data
NASA Technical Reports Server (NTRS)
Hogan, R. C.; Roush, T. L.
2002-01-01
A classification scheme based on unsupervised self-organizing maps (SOM) is described. Results from its application to the ASU mineral spectral database are presented. Applications to the Martian Thermal Emission Spectrometer data are discussed. Additional information is contained in the original extended abstract.
NASA Astrophysics Data System (ADS)
Belciug, Smaranda; Serbanescu, Mircea-Sebastian
2015-09-01
Feature selection is considered a key factor in classifications/decision problems. It is currently used in designing intelligent decision systems to choose the best features which allow the best performance. This paper proposes a regression-based approach to select the most important predictors to significantly increase the classification performance. Application to breast cancer detection and recurrence using publically available datasets proved the efficiency of this technique.
Effects of uncertainty and variability on population declines and IUCN Red List classifications.
Rueda-Cediel, Pamela; Anderson, Kurt E; Regan, Tracey J; Regan, Helen M
2018-01-22
The International Union for Conservation of Nature (IUCN) Red List Categories and Criteria is a quantitative framework for classifying species according to extinction risk. Population models may be used to estimate extinction risk or population declines. Uncertainty and variability arise in threat classifications through measurement and process error in empirical data and uncertainty in the models used to estimate extinction risk and population declines. Furthermore, species traits are known to affect extinction risk. We investigated the effects of measurement and process error, model type, population growth rate, and age at first reproduction on the reliability of risk classifications based on projected population declines on IUCN Red List classifications. We used an age-structured population model to simulate true population trajectories with different growth rates, reproductive ages and levels of variation, and subjected them to measurement error. We evaluated the ability of scalar and matrix models parameterized with these simulated time series to accurately capture the IUCN Red List classification generated with true population declines. Under all levels of measurement error tested and low process error, classifications were reasonably accurate; scalar and matrix models yielded roughly the same rate of misclassifications, but the distribution of errors differed; matrix models led to greater overestimation of extinction risk than underestimations; process error tended to contribute to misclassifications to a greater extent than measurement error; and more misclassifications occurred for fast, rather than slow, life histories. These results indicate that classifications of highly threatened taxa (i.e., taxa with low growth rates) under criterion A are more likely to be reliable than for less threatened taxa when assessed with population models. Greater scrutiny needs to be placed on data used to parameterize population models for species with high growth rates, particularly when available evidence indicates a potential transition to higher risk categories. © 2018 Society for Conservation Biology.
ERIC Educational Resources Information Center
Lu, Yi
2016-01-01
To model students' math growth trajectory, three conventional growth curve models and three growth mixture models are applied to the Early Childhood Longitudinal Study Kindergarten-Fifth grade (ECLS K-5) dataset in this study. The results of conventional growth curve model show gender differences on math IRT scores. When holding socio-economic…
Network-based study of Lagrangian transport and mixing
NASA Astrophysics Data System (ADS)
Padberg-Gehle, Kathrin; Schneide, Christiane
2017-10-01
Transport and mixing processes in fluid flows are crucially influenced by coherent structures and the characterization of these Lagrangian objects is a topic of intense current research. While established mathematical approaches such as variational methods or transfer-operator-based schemes require full knowledge of the flow field or at least high-resolution trajectory data, this information may not be available in applications. Recently, different computational methods have been proposed to identify coherent behavior in flows directly from Lagrangian trajectory data, that is, numerical or measured time series of particle positions in a fluid flow. In this context, spatio-temporal clustering algorithms have been proven to be very effective for the extraction of coherent sets from sparse and possibly incomplete trajectory data. Inspired by these recent approaches, we consider an unweighted, undirected network, where Lagrangian particle trajectories serve as network nodes. A link is established between two nodes if the respective trajectories come close to each other at least once in the course of time. Classical graph concepts are then employed to analyze the resulting network. In particular, local network measures such as the node degree, the average degree of neighboring nodes, and the clustering coefficient serve as indicators of highly mixing regions, whereas spectral graph partitioning schemes allow us to extract coherent sets. The proposed methodology is very fast to run and we demonstrate its applicability in two geophysical flows - the Bickley jet as well as the Antarctic stratospheric polar vortex.
Kianmehr, Keivan; Alhajj, Reda
2008-09-01
In this study, we aim at building a classification framework, namely the CARSVM model, which integrates association rule mining and support vector machine (SVM). The goal is to benefit from advantages of both, the discriminative knowledge represented by class association rules and the classification power of the SVM algorithm, to construct an efficient and accurate classifier model that improves the interpretability problem of SVM as a traditional machine learning technique and overcomes the efficiency issues of associative classification algorithms. In our proposed framework: instead of using the original training set, a set of rule-based feature vectors, which are generated based on the discriminative ability of class association rules over the training samples, are presented to the learning component of the SVM algorithm. We show that rule-based feature vectors present a high-qualified source of discrimination knowledge that can impact substantially the prediction power of SVM and associative classification techniques. They provide users with more conveniences in terms of understandability and interpretability as well. We have used four datasets from UCI ML repository to evaluate the performance of the developed system in comparison with five well-known existing classification methods. Because of the importance and popularity of gene expression analysis as real world application of the classification model, we present an extension of CARSVM combined with feature selection to be applied to gene expression data. Then, we describe how this combination will provide biologists with an efficient and understandable classifier model. The reported test results and their biological interpretation demonstrate the applicability, efficiency and effectiveness of the proposed model. From the results, it can be concluded that a considerable increase in classification accuracy can be obtained when the rule-based feature vectors are integrated in the learning process of the SVM algorithm. In the context of applicability, according to the results obtained from gene expression analysis, we can conclude that the CARSVM system can be utilized in a variety of real world applications with some adjustments.
Validating the performance of vehicle classification stations.
DOT National Transportation Integrated Search
2012-05-01
Vehicle classification is used in many transportation applications, e.g., infrastructure management and planning. Typical of most : developed countries, every state in the US maintains a network of vehicle classification stations to explicitly sort v...
Towns, Megan; Rosenbaum, Peter; Palisano, Robert; Wright, F Virginia
2018-02-01
This literature review addressed four questions. (1) In which populations other than cerebral palsy (CP) has the Gross Motor Function Classification System (GMFCS) been applied? (2) In what types of study, and why was it used? (3) How was it modified to facilitate these applications? (4) What justifications and evidence of psychometric adequacy were used to support its application? A search of PubMed, MEDLINE, and Embase databases (January 1997 to April 2017) using the terms: 'GMFCS' OR 'Gross Motor Function Classification System' yielded 2499 articles. 118 met inclusion criteria and reported children/adults with 133 health conditions/clinical descriptions other than CP. Three broad GMFCS applications were observed: as a categorization tool, independent variable, or outcome measure. While the GMFCS is widely used for children with health conditions/clinical description other than CP, researchers rarely provided adequate justification for these uses. We offer recommendations for development/validation of other condition-specific classification systems and discuss the potential need for a generic gross motor function classification system. The Gross Motor Function Classification System should not be used outside cerebral palsy or as an outcome measure. The authors provide recommendations for development and validation of condition-specific or generic classification systems. © 2017 Mac Keith Press.
Acosta-Mesa, Héctor-Gabriel; Rechy-Ramírez, Fernando; Mezura-Montes, Efrén; Cruz-Ramírez, Nicandro; Hernández Jiménez, Rodolfo
2014-06-01
In this work, we present a novel application of time series discretization using evolutionary programming for the classification of precancerous cervical lesions. The approach optimizes the number of intervals in which the length and amplitude of the time series should be compressed, preserving the important information for classification purposes. Using evolutionary programming, the search for a good discretization scheme is guided by a cost function which considers three criteria: the entropy regarding the classification, the complexity measured as the number of different strings needed to represent the complete data set, and the compression rate assessed as the length of the discrete representation. This discretization approach is evaluated using a time series data based on temporal patterns observed during a classical test used in cervical cancer detection; the classification accuracy reached by our method is compared with the well-known times series discretization algorithm SAX and the dimensionality reduction method PCA. Statistical analysis of the classification accuracy shows that the discrete representation is as efficient as the complete raw representation for the present application, reducing the dimensionality of the time series length by 97%. This representation is also very competitive in terms of classification accuracy when compared with similar approaches. Copyright © 2014 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Solano, M.
2016-02-01
The present study discusses the accuracy of a high-resolution ocean forecasting system in predicting floating drifter trajectories and the uncertainty of modeled particle dispersion in coastal areas. Trajectories were calculated using an offline particle-tracking algorithm coupled to the operational model developed for the region of Puerto Rico by CariCOOS. Both, a simple advection algorithm as well as the Larval TRANSport (LTRANS) model, a more sophisticated offline particle-tracking application, were coupled to the ocean model. Numerical results are compared with 12 floating drifters deployed in the near-shore of Puerto Rico during February and March 2015, and tracked for several days using Global Positioning Systems mounted on the drifters. In addition the trajectories have also been calculated with the AmSeas Navy Coastal Ocean Model (NCOM). The operational model is based on the Regional Ocean Modeling System (ROMS) with a uniform horizontal resolution of 1/100 degrees (1.1km). Initial, surface and open boundary conditions are taken from NCOM, except for wind stress, which is computed using winds from the National Digital Forecasting Database. Probabilistic maps were created to quantify the uncertainty of particle trajectories at different locations. Results show that the forecasted trajectories are location dependent, with tidally active regions having the largest error. The predicted trajectories by both the ROMS and NCOM models show good agreement on average, however both perform differently at particular locations. The effect of wind stress on the drifter trajectories is investigated to account for wind slippage. Furthermore, a real case scenario is presented where simulated trajectories show good agreement when compared to the actual drifter trajectories.
Trajectory correction propulsion for TOPS
NASA Technical Reports Server (NTRS)
Long, H. R.; Bjorklund, R. A.
1972-01-01
A blowdown-pressurized hydrazine propulsion system was selected to provide trajectory correction impulse for outer planet flyby spacecraft as the result of cost/mass/reliability tradeoff analyses. Present hydrazine component and system technology and component designs were evaluated for application to the Thermoelectric Outer Planet Spacecraft (TOPS); while general hydrazine technology was adequate, component design changes were deemed necessary for TOPS-type missions. A prototype hydrazine propulsion system was fabricated and fired nine times for a total of 1600 s to demonstrate the operation and performance of the TOPS propulsion configuration. A flight-weight trajectory correction propulsion subsystem (TCPS) was designed for the TOPS based on actual and estimated advanced components.
System and method for bullet tracking and shooter localization
Roberts, Randy S [Livermore, CA; Breitfeller, Eric F [Dublin, CA
2011-06-21
A system and method of processing infrared imagery to determine projectile trajectories and the locations of shooters with a high degree of accuracy. The method includes image processing infrared image data to reduce noise and identify streak-shaped image features, using a Kalman filter to estimate optimal projectile trajectories, updating the Kalman filter with new image data, determining projectile source locations by solving a combinatorial least-squares solution for all optimal projectile trajectories, and displaying all of the projectile source locations. Such a shooter-localization system is of great interest for military and law enforcement applications to determine sniper locations, especially in urban combat scenarios.
Code of Federal Regulations, 2011 CFR
2011-10-01
... classification of U.S. international carriers from dominant to non-dominant. 63.13 Section 63.13... for modifying regulatory classification of U.S. international carriers from dominant to non-dominant... in its application to demonstrate that it qualifies for non-dominant classification pursuant to § 63...
Code of Federal Regulations, 2010 CFR
2010-10-01
... classification of U.S. international carriers from dominant to non-dominant. 63.13 Section 63.13... for modifying regulatory classification of U.S. international carriers from dominant to non-dominant... in its application to demonstrate that it qualifies for non-dominant classification pursuant to § 63...
7 CFR 28.116 - Amounts of fees for classification; exemption.
Code of Federal Regulations, 2011 CFR
2011-01-01
... not applicable to review of classification if made on the same sample as the original class or... 7 Agriculture 2 2011-01-01 2011-01-01 false Amounts of fees for classification; exemption. 28.116... Standards Act Fees and Costs § 28.116 Amounts of fees for classification; exemption. (a) For the...
7 CFR 28.116 - Amounts of fees for classification; exemption.
Code of Federal Regulations, 2010 CFR
2010-01-01
... not applicable to review of classification if made on the same sample as the original class or... 7 Agriculture 2 2010-01-01 2010-01-01 false Amounts of fees for classification; exemption. 28.116... Standards Act Fees and Costs § 28.116 Amounts of fees for classification; exemption. (a) For the...
The Classification of Romanian High-Schools
ERIC Educational Resources Information Center
Ivan, Ion; Milodin, Daniel; Naie, Lucian
2006-01-01
The article tries to tackle the issue of high-schools classification from one city, district or from Romania. The classification criteria are presented. The National Database of Education is also presented and the application of criteria is illustrated. An algorithm for high-school multi-rang classification is proposed in order to build classes of…
Kinematic evaluation of virtual walking trajectories.
Cirio, Gabriel; Olivier, Anne-Hélène; Marchal, Maud; Pettré, Julien
2013-04-01
Virtual walking, a fundamental task in Virtual Reality (VR), is greatly influenced by the locomotion interface being used, by the specificities of input and output devices, and by the way the virtual environment is represented. No matter how virtual walking is controlled, the generation of realistic virtual trajectories is absolutely required for some applications, especially those dedicated to the study of walking behaviors in VR, navigation through virtual places for architecture, rehabilitation and training. Previous studies focused on evaluating the realism of locomotion trajectories have mostly considered the result of the locomotion task (efficiency, accuracy) and its subjective perception (presence, cybersickness). Few focused on the locomotion trajectory itself, but in situation of geometrically constrained task. In this paper, we study the realism of unconstrained trajectories produced during virtual walking by addressing the following question: did the user reach his destination by virtually walking along a trajectory he would have followed in similar real conditions? To this end, we propose a comprehensive evaluation framework consisting on a set of trajectographical criteria and a locomotion model to generate reference trajectories. We consider a simple locomotion task where users walk between two oriented points in space. The travel path is analyzed both geometrically and temporally in comparison to simulated reference trajectories. In addition, we demonstrate the framework over a user study which considered an initial set of common and frequent virtual walking conditions, namely different input devices, output display devices, control laws, and visualization modalities. The study provides insight into the relative contributions of each condition to the overall realism of the resulting virtual trajectories.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cotton, Stephen J.; Miller, William H., E-mail: millerwh@berkeley.edu
A recently described symmetrical windowing methodology [S. J. Cotton and W. H. Miller, J. Phys. Chem. A 117, 7190 (2013)] for quasi-classical trajectory simulations is applied here to the Meyer-Miller [H.-D. Meyer and W. H. Miller, J. Chem. Phys. 70, 3214 (1979)] model for the electronic degrees of freedom in electronically non-adiabatic dynamics. Results generated using this classical approach are observed to be in very good agreement with accurate quantum mechanical results for a variety of test applications, including problems where coherence effects are significant such as the challenging asymmetric spin-boson system.
White matter fiber tracking computation based on diffusion tensor imaging for clinical applications.
Dellani, Paulo R; Glaser, Martin; Wille, Paulo R; Vucurevic, Goran; Stadie, Axel; Bauermann, Thomas; Tropine, Andrei; Perneczky, Axel; von Wangenheim, Aldo; Stoeter, Peter
2007-03-01
Fiber tracking allows the in vivo reconstruction of human brain white matter fiber trajectories based on magnetic resonance diffusion tensor imaging (MR-DTI), but its application in the clinical routine is still in its infancy. In this study, we present a new software for fiber tracking, developed on top of a general-purpose DICOM (digital imaging and communications in medicine) framework, which can be easily integrated into existing picture archiving and communication system (PACS) of radiological institutions. Images combining anatomical information and the localization of different fiber tract trajectories can be encoded and exported in DICOM and Analyze formats, which are valuable resources in the clinical applications of this method. Fiber tracking was implemented based on existing line propagation algorithms, but it includes a heuristic for fiber crossings in the case of disk-shaped diffusion tensors. We successfully performed fiber tracking on MR-DTI data sets from 26 patients with different types of brain lesions affecting the corticospinal tracts. In all cases, the trajectories of the central spinal tract (pyramidal tract) were reconstructed and could be applied at the planning phase of the surgery as well as in intraoperative neuronavigation.
Mining spatiotemporal patterns of urban dwellers from taxi trajectory data
NASA Astrophysics Data System (ADS)
Mao, Feng; Ji, Minhe; Liu, Ting
2016-06-01
With the widespread adoption of locationaware technology, obtaining long-sequence, massive and high-accuracy spatiotemporal trajectory data of individuals has become increasingly popular in various geographic studies. Trajectory data of taxis, one of the most widely used inner-city travel modes, contain rich information about both road network traffic and travel behavior of passengers. Such data can be used to study the microscopic activity patterns of individuals as well as the macro system of urban spatial structures. This paper focuses on trajectories obtained from GPS-enabled taxis and their applications for mining urban commuting patterns. A novel approach is proposed to discover spatiotemporal patterns of household travel from the taxi trajectory dataset with a large number of point locations. The approach involves three critical steps: spatial clustering of taxi origin-destination (OD) based on urban traffic grids to discover potentially meaningful places, identifying threshold values from statistics of the OD clusters to extract urban jobs-housing structures, and visualization of analytic results to understand the spatial distribution and temporal trends of the revealed urban structures and implied household commuting behavior. A case study with a taxi trajectory dataset in Shanghai, China is presented to demonstrate and evaluate the proposed method.
NASA Astrophysics Data System (ADS)
Zhou, Wenyong; Yuan, Jianping; Luo, Jianjun
2005-11-01
Autonomous on-orbit servicing provides flexibility to space systems and has great value both in civil and in military. When a satellite performs on-orbit servicing tasks, flying around is the basic type of motion. This paper is concerned with the design and control problems of a chaser satellite flying around a target spacecraft in non-coplanar elliptical orbit for a long time. At first, a mathematical model used to design a long-term flying around trajectory is presented, which is applicable to the situation that the target spacecraft flies in an elliptical orbit. The conditions of the target at the centre of the flying around path are deduced. Considering the safety and task requirements, a long-term flying around trajectory is designed. Taking into account perturbations and navigation errors which can cause the trajectory unstable and mission impossible, a two-impulse control method is put forward. Genetic algorithm is used to minimize the cost function which considers fuel consumption and bias simultaneously. Some simulation works are carried out and the results indicate the flying around mathematical model and the trajectory control method can be used in the design and control of a long-term flying around trajectory.
Efficient Optimization of Low-Thrust Spacecraft Trajectories
NASA Technical Reports Server (NTRS)
Lee, Seungwon; Fink, Wolfgang; Russell, Ryan; Terrile, Richard; Petropoulos, Anastassios; vonAllmen, Paul
2007-01-01
A paper describes a computationally efficient method of optimizing trajectories of spacecraft driven by propulsion systems that generate low thrusts and, hence, must be operated for long times. A common goal in trajectory-optimization problems is to find minimum-time, minimum-fuel, or Pareto-optimal trajectories (here, Pareto-optimality signifies that no other solutions are superior with respect to both flight time and fuel consumption). The present method utilizes genetic and simulated-annealing algorithms to search for globally Pareto-optimal solutions. These algorithms are implemented in parallel form to reduce computation time. These algorithms are coupled with either of two traditional trajectory- design approaches called "direct" and "indirect." In the direct approach, thrust control is discretized in either arc time or arc length, and the resulting discrete thrust vectors are optimized. The indirect approach involves the primer-vector theory (introduced in 1963), in which the thrust control problem is transformed into a co-state control problem and the initial values of the co-state vector are optimized. In application to two example orbit-transfer problems, this method was found to generate solutions comparable to those of other state-of-the-art trajectory-optimization methods while requiring much less computation time.
NASA Technical Reports Server (NTRS)
Tuzzolino, A. J.; Simpson, J. A.; Mckibben, R. B.; Voss, H. D.; Gursky, H.
1993-01-01
The characteristics of a space dust instrument which would be ideally suited to carry out near-Earth dust measurements on a possible Long Duraction Exposure Facility reflight mission (LDEF 2) is discussed. As a model for the trajectory portion of the instrument proposed for LDEF 2, the characteristics of a SPAce DUSt instrument (SPADUS) currently under development for flight on the USA ARGOS mission to measure the flux, mass, velocity, and trajectory of near-Earth dust is summarized. Since natural (cosmic) dust and man-made dust particles (orbital debris) have different velocity and trajectory distributions, they are distinguished by means of the SPADUS velocity/trajectory information. The SPADUS measurements will cover the dust mass range approximately 5 x 10(exp -12) g (2 microns diameter) to approximately 1 x 10(exp -5) g (200 microns diameter), with an expected mean error in particle trajectory of approximately 7 deg (isotropic flux). Arrays of capture cell devices positioned behind the trajectory instrumentation would provide for Earth-based chemical and isotopic analysis of captured dust. The SPADUS measurement principles, characteristics, its role in the ARGOS mission, and its application to an LDEF 2 mission are summarized.
Looking at the ICF and human communication through the lens of classification theory.
Walsh, Regina
2011-08-01
This paper explores the insights that classification theory can provide about the application of the International Classification of Functioning, Disability and Health (ICF) to communication. It first considers the relationship between conceptual models and classification systems, highlighting that classification systems in speech-language pathology (SLP) have not historically been based on conceptual models of human communication. It then overviews the key concepts and criteria of classification theory. Applying classification theory to the ICF and communication raises a number of issues, some previously highlighted through clinical application. Six focus questions from classification theory are used to explore these issues, and to propose the creation of an ICF-related conceptual model of communicating for the field of communication disability, which would address some of the issues raised. Developing a conceptual model of communication for SLP purposes closely articulated with the ICF would foster productive intra-professional discourse, while at the same time allow the profession to continue to use the ICF for purposes in inter-disciplinary discourse. The paper concludes by suggesting the insights of classification theory can assist professionals to apply the ICF to communication with the necessary rigour, and to work further in developing a conceptual model of human communication.
Research on Remote Sensing Image Classification Based on Feature Level Fusion
NASA Astrophysics Data System (ADS)
Yuan, L.; Zhu, G.
2018-04-01
Remote sensing image classification, as an important direction of remote sensing image processing and application, has been widely studied. However, in the process of existing classification algorithms, there still exists the phenomenon of misclassification and missing points, which leads to the final classification accuracy is not high. In this paper, we selected Sentinel-1A and Landsat8 OLI images as data sources, and propose a classification method based on feature level fusion. Compare three kind of feature level fusion algorithms (i.e., Gram-Schmidt spectral sharpening, Principal Component Analysis transform and Brovey transform), and then select the best fused image for the classification experimental. In the classification process, we choose four kinds of image classification algorithms (i.e. Minimum distance, Mahalanobis distance, Support Vector Machine and ISODATA) to do contrast experiment. We use overall classification precision and Kappa coefficient as the classification accuracy evaluation criteria, and the four classification results of fused image are analysed. The experimental results show that the fusion effect of Gram-Schmidt spectral sharpening is better than other methods. In four kinds of classification algorithms, the fused image has the best applicability to Support Vector Machine classification, the overall classification precision is 94.01 % and the Kappa coefficients is 0.91. The fused image with Sentinel-1A and Landsat8 OLI is not only have more spatial information and spectral texture characteristics, but also enhances the distinguishing features of the images. The proposed method is beneficial to improve the accuracy and stability of remote sensing image classification.
New Perspectives on Intelligence Collection and Processing
2016-06-01
gained attention in recent years with applications in areas such as web advertising , classification, and decision making. In this thesis, we develop a...research that has gained attention in recent years with applications in areas such as web advertising , classification, and decision making. In this
Valle, Xavier; Alentorn-Geli, Eduard; Tol, Johannes L; Hamilton, Bruce; Garrett, William E; Pruna, Ricard; Til, Lluís; Gutierrez, Josep Antoni; Alomar, Xavier; Balius, Ramón; Malliaropoulos, Nikos; Monllau, Joan Carles; Whiteley, Rodney; Witvrouw, Erik; Samuelsson, Kristian; Rodas, Gil
2017-07-01
Muscle injuries are among the most common injuries in sport and continue to be a major concern because of training and competition time loss, challenging decision making regarding treatment and return to sport, and a relatively high recurrence rate. An adequate classification of muscle injury is essential for a full understanding of the injury and to optimize its management and return-to-play process. The ongoing failure to establish a classification system with broad acceptance has resulted from factors such as limited clinical applicability, and the inclusion of subjective findings and ambiguous terminology. The purpose of this article was to describe a classification system for muscle injuries with easy clinical application, adequate grouping of injuries with similar functional impairment, and potential prognostic value. This evidence-informed and expert consensus-based classification system for muscle injuries is based on a four-letter initialism system: MLG-R, respectively referring to the mechanism of injury (M), location of injury (L), grading of severity (G), and number of muscle re-injuries (R). The goal of the classification is to enhance communication between healthcare and sports-related professionals and facilitate rehabilitation and return-to-play decision making.
Vetter, Jeffrey S.
2005-02-01
The method and system described herein presents a technique for performance analysis that helps users understand the communication behavior of their message passing applications. The method and system described herein may automatically classifies individual communication operations and reveal the cause of communication inefficiencies in the application. This classification allows the developer to quickly focus on the culprits of truly inefficient behavior, rather than manually foraging through massive amounts of performance data. Specifically, the method and system described herein trace the message operations of Message Passing Interface (MPI) applications and then classify each individual communication event using a supervised learning technique: decision tree classification. The decision tree may be trained using microbenchmarks that demonstrate both efficient and inefficient communication. Since the method and system described herein adapt to the target system's configuration through these microbenchmarks, they simultaneously automate the performance analysis process and improve classification accuracy. The method and system described herein may improve the accuracy of performance analysis and dramatically reduce the amount of data that users must encounter.
On the Relativistic Correction of Particles Trajectory in Tandem Type Electrostatic Accelerator
NASA Astrophysics Data System (ADS)
Minárik, Stanislav
2015-08-01
A constant potential is applied to the acceleration of the ion-beam in the tandem type electrostatic accelerator. However, not just one voltage is applied, but instead a number of applications can be made in succession by means of the tandem arrangement of high voltage tubes. This number of voltage applications, which is the number of so-called "stages" of a tandem accelerator, may be two, three, or four, depending on the chosen design. Electrostatic field with approximately constant intensity acts on ions in any stage. In general, non-relativistic dynamics is used for the description of the ion transport in tandem accelerator. Energies of accelerated ions are too low and relativistic effects cannot be commonly observed by standard experimental technique. Estimation of possible relativistic correction of ion trajectories is therefore only a matter of calculation. In this note, we briefly present such calculation. Our aim is to show how using the relativistic dynamics modifies the particles trajectory in tandem type accelerator and what parameters determine this modification.
Reduction of lunar landing fuel requirements by utilizing lunar ballistic capture.
Johnson, Michael D; Belbruno, Edward A
2005-12-01
Ballistic lunar capture trajectories have been successfully utilized for lunar orbital missions since 1991. Recent interest in lunar landing trajectories has occurred due to a directive from President Bush to return humans to the Moon by 2015. NASA requirements for humans to return to the lunar surface include separation of crew and cargo missions, all lunar surface access, and anytime-abort to return to Earth. Such requirements are very demanding from a propellant standpoint. The subject of this paper is the application of lunar ballistic capture for the reduction of lunar landing propellant requirements. Preliminary studies of the application of weak stability boundary (WSB) trajectories and ballistic capture have shown that considerable savings in low Earth orbit (LEO) mission mass may be realized, on the order of 36% less than conventional Hohmann transfer orbit missions. Other advantages, such as reduction in launch window constraints and reduction of lunar orbit maintenance propellant requirements, have also surfaced from this study.
Spline Trajectory Algorithm Development: Bezier Curve Control Point Generation for UAVs
NASA Technical Reports Server (NTRS)
Howell, Lauren R.; Allen, B. Danette
2016-01-01
A greater need for sophisticated autonomous piloting systems has risen in direct correlation with the ubiquity of Unmanned Aerial Vehicle (UAV) technology. Whether surveying unknown or unexplored areas of the world, collecting scientific data from regions in which humans are typically incapable of entering, locating lost or wanted persons, or delivering emergency supplies, an unmanned vehicle moving in close proximity to people and other vehicles, should fly smoothly and predictably. The mathematical application of spline interpolation can play an important role in autopilots' on-board trajectory planning. Spline interpolation allows for the connection of Three-Dimensional Euclidean Space coordinates through a continuous set of smooth curves. This paper explores the motivation, application, and methodology used to compute the spline control points, which shape the curves in such a way that the autopilot trajectory is able to meet vehicle-dynamics limitations. The spline algorithms developed used to generate these curves supply autopilots with the information necessary to compute vehicle paths through a set of coordinate waypoints.
NASA Technical Reports Server (NTRS)
Idris, Husni; Shen, Ni; Wing, David J.
2011-01-01
The growing demand for air travel is increasing the need for mitigating air traffic congestion and complexity problems, which are already at high levels. At the same time new surveillance, navigation, and communication technologies are enabling major transformations in the air traffic management system, including net-based information sharing and collaboration, performance-based access to airspace resources, and trajectory-based rather than clearance-based operations. The new system will feature different schemes for allocating tasks and responsibilities between the ground and airborne agents and between the human and automation, with potential capacity and cost benefits. Therefore, complexity management requires new metrics and methods that can support these new schemes. This paper presents metrics and methods for preserving trajectory flexibility that have been proposed to support a trajectory-based approach for complexity management by airborne or ground-based systems. It presents extensions to these metrics as well as to the initial research conducted to investigate the hypothesis that using these metrics to guide user and service provider actions will naturally mitigate traffic complexity. The analysis showed promising results in that: (1) Trajectory flexibility preservation mitigated traffic complexity as indicated by inducing self-organization in the traffic patterns and lowering traffic complexity indicators such as dynamic density and traffic entropy. (2)Trajectory flexibility preservation reduced the potential for secondary conflicts in separation assurance. (3) Trajectory flexibility metrics showed potential application to support user and service provider negotiations for minimizing the constraints imposed on trajectories without jeopardizing their objectives.
Cluster Method Analysis of K. S. C. Image
NASA Technical Reports Server (NTRS)
Rodriguez, Joe, Jr.; Desai, M.
1997-01-01
Information obtained from satellite-based systems has moved to the forefront as a method in the identification of many land cover types. Identification of different land features through remote sensing is an effective tool for regional and global assessment of geometric characteristics. Classification data acquired from remote sensing images have a wide variety of applications. In particular, analysis of remote sensing images have special applications in the classification of various types of vegetation. Results obtained from classification studies of a particular area or region serve towards a greater understanding of what parameters (ecological, temporal, etc.) affect the region being analyzed. In this paper, we make a distinction between both types of classification approaches although, focus is given to the unsupervised classification method using 1987 Thematic Mapped (TM) images of Kennedy Space Center.
An aircraft noise pollution model for trajectory optimization
NASA Technical Reports Server (NTRS)
Barkana, A.; Cook, G.
1976-01-01
A mathematical model describing the generation of aircraft noise is developed with the ultimate purpose of reducing noise (noise-optimizing landing trajectories) in terminal areas. While the model is for a specific aircraft (Boeing 737), the methodology would be applicable to a wide variety of aircraft. The model is used to obtain a footprint on the ground inside of which the noise level is at or above 70 dB.
ERIC Educational Resources Information Center
Prendergast, Michael; Huang, David; Hser, Yih-Ing
2008-01-01
Drug abusers vary considerably in their drug use and criminal behavior over time, and these trajectories are likely to influence drug treatment participation and treatment outcomes. Drawing on longitudinal natural history data from three samples of adult male drug users, we identify four groups with distinctive drug use and crime trajectories…
Finding Lagrangian Structures via the Application of Braid Theory
2010-10-16
the horizontal plane is the physical domain and the vertical axis is time. These three dimensional...three dimensional strands are projected onto the plane containing the x-axis and time then Figure 2a becomes Figure 2b. The collection of strands make...trajectories shown in the physical plane . An “x” represents the initial condition of the trajectory and a dot represents the current position. (b) The
Zufiria, Pedro J; Pastor-Escuredo, David; Úbeda-Medina, Luis; Hernandez-Medina, Miguel A; Barriales-Valbuena, Iker; Morales, Alfredo J; Jacques, Damien C; Nkwambi, Wilfred; Diop, M Bamba; Quinn, John; Hidalgo-Sanchís, Paula; Luengo-Oroz, Miguel
2018-01-01
We propose a framework for the systematic analysis of mobile phone data to identify relevant mobility profiles in a population. The proposed framework allows finding distinct human mobility profiles based on the digital trace of mobile phone users characterized by a Matrix of Individual Trajectories (IT-Matrix). This matrix gathers a consistent and regularized description of individual trajectories that enables multi-scale representations along time and space, which can be used to extract aggregated indicators such as a dynamic multi-scale population count. Unsupervised clustering of individual trajectories generates mobility profiles (clusters of similar individual trajectories) which characterize relevant group behaviors preserving optimal aggregation levels for detailed and privacy-secured mobility characterization. The application of the proposed framework is illustrated by analyzing fully anonymized data on human mobility from mobile phones in Senegal at the arrondissement level over a calendar year. The analysis of monthly mobility patterns at the livelihood zone resolution resulted in the discovery and characterization of seasonal mobility profiles related with economic activities, agricultural calendars and rainfalls. The use of these mobility profiles could support the timely identification of mobility changes in vulnerable populations in response to external shocks (such as natural disasters, civil conflicts or sudden increases of food prices) to monitor food security.
Learning State Space Dynamics in Recurrent Networks
NASA Astrophysics Data System (ADS)
Simard, Patrice Yvon
Fully recurrent (asymmetrical) networks can be used to learn temporal trajectories. The network is unfolded in time, and backpropagation is used to train the weights. The presence of recurrent connections creates internal states in the system which vary as a function of time. The resulting dynamics can provide interesting additional computing power but learning is made more difficult by the existence of internal memories. This study first exhibits the properties of recurrent networks in terms of convergence when the internal states of the system are unknown. A new energy functional is provided to change the weights of the units in order to the control the stability of the fixed points of the network's dynamics. The power of the resultant algorithm is illustrated with the simulation of a content addressable memory. Next, the more general case of time trajectories on a recurrent network is studied. An application is proposed in which trajectories are generated to draw letters as a function of an input. In another application of recurrent systems, a neural network certain temporal properties observed in human callosally sectioned brains. Finally the proposed algorithm for stabilizing dynamics around fixed points is extended to one for stabilizing dynamics around time trajectories. Its effects are illustrated on a network which generates Lisajous curves.
Ecology for the shrinking city (JA) | Science Inventory | US ...
This article brings together the concepts of shrinking cities—the hundreds of cities worldwide experiencing long-term population loss—and ecology for the city. Ecology for the city is the application of a social–ecological understanding to shaping urban form and function along sustainable trajectories. Ecology for the shrinking city therefore acknowledges that urban transformations to sustainable trajectories may be quite different in shrinking cities as compared with growing cities. Shrinking cities are well poised for transformations, because shrinking is perceived as a crisis and can mobilize the social capacity to change. Ecology is particularly well suited to contribute solutions because of the extent of vacant land in shrinking cities that can be leveraged for ecosystem-services provisioning. A crucial role of an ecology for the shrinking city is identifying innovative pathways that create locally desired amenities that provide ecosystem services and contribute to urban sustainability at multiple scales. This paper brings together the concepts of ecology for the city and shrinking cities – the hundreds of cities worldwide experiencing long-term population loss. Ecology for the city is the application of social-ecological understanding to shaping urban form and function along sustainable trajectories. Ecology for the shrinking city acknowledges that urban transformations to sustainable trajectories may be quite different in shrinking cities as compa
Applications of Support Vector Machines In Chemo And Bioinformatics
NASA Astrophysics Data System (ADS)
Jayaraman, V. K.; Sundararajan, V.
2010-10-01
Conventional linear & nonlinear tools for classification, regression & data driven modeling are being replaced on a rapid scale by newer techniques & tools based on artificial intelligence and machine learning. While the linear techniques are not applicable for inherently nonlinear problems, newer methods serve as attractive alternatives for solving real life problems. Support Vector Machine (SVM) classifiers are a set of universal feed-forward network based classification algorithms that have been formulated from statistical learning theory and structural risk minimization principle. SVM regression closely follows the classification methodology. In this work recent applications of SVM in Chemo & Bioinformatics will be described with suitable illustrative examples.
Why credit risk markets are predestined for exhibiting log-periodic power law structures
NASA Astrophysics Data System (ADS)
Wosnitza, Jan Henrik; Leker, Jens
2014-01-01
Recent research has established the existence of log-periodic power law (LPPL) patterns in financial institutions’ credit default swap (CDS) spreads. The main purpose of this paper is to clarify why credit risk markets are predestined for exhibiting LPPL structures. To this end, the credit risk prediction of two variants of logistic regression, i.e. polynomial logistic regression (PLR) and kernel logistic regression (KLR), are firstly compared to the standard logistic regression (SLR). In doing so, the question whether the performances of rating systems based on balance sheet ratios can be improved by nonlinear transformations of the explanatory variables is resolved. Building on the result that nonlinear balance sheet ratio transformations hardly improve the SLR’s predictive power in our case, we secondly compare the classification performance of a multivariate SLR to the discriminative powers of probabilities of default derived from three different capital market data, namely bonds, CDSs, and stocks. Benefiting from the prompt inclusion of relevant information, the capital market data in general and CDSs in particular increasingly outperform the SLR while approaching the time of the credit event. Due to the higher classification performances, it seems plausible for creditors to align their investment decisions with capital market-based default indicators, i.e., to imitate the aggregate opinion of the market participants. Since imitation is considered to be the source of LPPL structures in financial time series, it is highly plausible to scan CDS spread developments for LPPL patterns. By establishing LPPL patterns in governmental CDS spread trajectories of some European crisis countries, the LPPL’s application to credit risk markets is extended. This novel piece of evidence further strengthens the claim that credit risk markets are adequate breeding grounds for LPPL patterns.
NASA Astrophysics Data System (ADS)
Jiang, Jifa; Niu, Lei
2017-12-01
We study three dimensional competitive differential equations with linearly determined nullclines and prove that they always have 33 stable nullcline classes in total. Each class is given in terms of inequalities on the intrinsic growth rates and competitive coefficients and is independent of generating functions. The common characteristics are that every trajectory converges to an equilibrium in classes 1-25, that Hopf bifurcations do not occur within class 32, and that there is always a heteroclinic cycle in class 27. Nontrivial dynamical behaviors, such as the existence and multiplicity of limit cycles, only may occur in classes 26-33, but these nontrivial dynamical behaviors depend on generating functions. We show that Hopf bifurcation can occur within each of classes 26-31 for continuous-time Leslie/Gower system and Ricker system, the same as Lotka-Volterra system; but it only occurs in classes 26 and 27 for continuous-time Atkinson/Allen system and Gompertz system. There is an apparent distinction between Lotka-Volterra system and Leslie/Gower system, Ricker system, Atkinson/Allen system, and Gompertz system with the identical growth rate. Lotka-Volterra system with the identical growth rate has no limit cycle, but admits a center on the carrying simplex in classes 26 and 27. But Leslie/Gower system, Ricker system, Atkinson/Allen system, and Gompertz system with the identical growth rate do possess limit cycles. At last, we provide examples to show that Leslie/Gower system and Ricker system can also admit two limit cycles. This general classification greatly widens applications of Zeeman's method and makes it possible to investigate the existence and multiplicity of limit cycles, centers and stability of heteroclinic cycles for three dimensional competitive systems with linearly determined nullclines, as done in planar systems.
NASA Astrophysics Data System (ADS)
Yu, Zhicong; Wunderlich, Adam; Dennerlein, Frank; Lauritsch, Günter; Noo, Frédéric
2011-06-01
Cone-beam imaging with C-arm systems has become a valuable tool in interventional radiology. Currently, a simple circular trajectory is used, but future applications should use more sophisticated source trajectories, not only to avoid cone-beam artifacts but also to allow extended volume imaging. One attractive strategy to achieve these two goals is to use a source trajectory that consists of two parallel circular arcs connected by a line segment, possibly with repetition. In this work, we address the question of R-line coverage for such a trajectory. More specifically, we examine to what extent R-lines for such a trajectory cover a central cylindrical region of interest (ROI). An R-line is a line segment connecting any two points on the source trajectory. Knowledge of R-line coverage is crucial because a general theory for theoretically exact and stable image reconstruction from axially truncated data is only known for the points in the scanned object that lie on R-lines. Our analysis starts by examining the R-line coverage for the elemental trajectories consisting of (i) two parallel circular arcs and (ii) a circular arc connected orthogonally to a line segment. Next, we utilize our understanding of the R-lines for the aforementioned elemental trajectories to determine the R-line coverage for the trajectory consisting of two parallel circular arcs connected by a tightly fit line segment. For this trajectory, we find that the R-line coverage is insufficient to completely cover any central ROI. Because extension of the line segment beyond the circular arcs helps to increase the R-line coverage, we subsequently propose a trajectory composed of two parallel circular arcs connected by an extended line. We show that the R-lines for this trajectory can fully cover a central ROI if the line extension is long enough. Our presentation includes a formula for the minimum line extension needed to achieve full R-line coverage of an ROI with a specified size, and also includes a preliminary study on the required detector size, showing that the R-lines added by the line extension are not constraining.
Library of Congress Classification Adapted for Children's Sound Recordings.
ERIC Educational Resources Information Center
Perkins, John W.; And Others
This publication describes how the Library of Congress classification adapted for children's books by the Inglewood Public Library can also be used in the classification of children's sound recordings. One of the major features of the classification system is its applicability to various media, as it provides a method by which the same work can be…
Predictive modeling of respiratory tumor motion for real-time prediction of baseline shifts
NASA Astrophysics Data System (ADS)
Balasubramanian, A.; Shamsuddin, R.; Prabhakaran, B.; Sawant, A.
2017-03-01
Baseline shifts in respiratory patterns can result in significant spatiotemporal changes in patient anatomy (compared to that captured during simulation), in turn, causing geometric and dosimetric errors in the administration of thoracic and abdominal radiotherapy. We propose predictive modeling of the tumor motion trajectories for predicting a baseline shift ahead of its occurrence. The key idea is to use the features of the tumor motion trajectory over a 1 min window, and predict the occurrence of a baseline shift in the 5 s that immediately follow (lookahead window). In this study, we explored a preliminary trend-based analysis with multi-class annotations as well as a more focused binary classification analysis. In both analyses, a number of different inter-fraction and intra-fraction training strategies were studied, both offline as well as online, along with data sufficiency and skew compensation for class imbalances. The performance of different training strategies were compared across multiple machine learning classification algorithms, including nearest neighbor, Naïve Bayes, linear discriminant and ensemble Adaboost. The prediction performance is evaluated using metrics such as accuracy, precision, recall and the area under the curve (AUC) for repeater operating characteristics curve. The key results of the trend-based analysis indicate that (i) intra-fraction training strategies achieve highest prediction accuracies (90.5-91.4%) (ii) the predictive modeling yields lowest accuracies (50-60%) when the training data does not include any information from the test patient; (iii) the prediction latencies are as low as a few hundred milliseconds, and thus conducive for real-time prediction. The binary classification performance is promising, indicated by high AUCs (0.96-0.98). It also confirms the utility of prior data from previous patients, and also the necessity of training the classifier on some initial data from the new patient for reasonable prediction performance. The ability to predict a baseline shift with a sufficient look-ahead window will enable clinical systems or even human users to hold the treatment beam in such situations, thereby reducing the probability of serious geometric and dosimetric errors.
Predictive modeling of respiratory tumor motion for real-time prediction of baseline shifts
Balasubramanian, A; Shamsuddin, R; Prabhakaran, B; Sawant, A
2017-01-01
Baseline shifts in respiratory patterns can result in significant spatiotemporal changes in patient anatomy (compared to that captured during simulation), in turn, causing geometric and dosimetric errors in the administration of thoracic and abdominal radiotherapy. We propose predictive modeling of the tumor motion trajectories for predicting a baseline shift ahead of its occurrence. The key idea is to use the features of the tumor motion trajectory over a 1 min window, and predict the occurrence of a baseline shift in the 5 s that immediately follow (lookahead window). In this study, we explored a preliminary trend-based analysis with multi-class annotations as well as a more focused binary classification analysis. In both analyses, a number of different inter-fraction and intra-fraction training strategies were studied, both offline as well as online, along with data sufficiency and skew compensation for class imbalances. The performance of different training strategies were compared across multiple machine learning classification algorithms, including nearest neighbor, Naïve Bayes, linear discriminant and ensemble Adaboost. The prediction performance is evaluated using metrics such as accuracy, precision, recall and the area under the curve (AUC) for repeater operating characteristics curve. The key results of the trend-based analysis indicate that (i) intra-fraction training strategies achieve highest prediction accuracies (90.5–91.4%); (ii) the predictive modeling yields lowest accuracies (50–60%) when the training data does not include any information from the test patient; (iii) the prediction latencies are as low as a few hundred milliseconds, and thus conducive for real-time prediction. The binary classification performance is promising, indicated by high AUCs (0.96–0.98). It also confirms the utility of prior data from previous patients, and also the necessity of training the classifier on some initial data from the new patient for reasonable prediction performance. The ability to predict a baseline shift with a sufficient lookahead window will enable clinical systems or even human users to hold the treatment beam in such situations, thereby reducing the probability of serious geometric and dosimetric errors. PMID:28075331
Predictive modeling of respiratory tumor motion for real-time prediction of baseline shifts.
Balasubramanian, A; Shamsuddin, R; Prabhakaran, B; Sawant, A
2017-03-07
Baseline shifts in respiratory patterns can result in significant spatiotemporal changes in patient anatomy (compared to that captured during simulation), in turn, causing geometric and dosimetric errors in the administration of thoracic and abdominal radiotherapy. We propose predictive modeling of the tumor motion trajectories for predicting a baseline shift ahead of its occurrence. The key idea is to use the features of the tumor motion trajectory over a 1 min window, and predict the occurrence of a baseline shift in the 5 s that immediately follow (lookahead window). In this study, we explored a preliminary trend-based analysis with multi-class annotations as well as a more focused binary classification analysis. In both analyses, a number of different inter-fraction and intra-fraction training strategies were studied, both offline as well as online, along with data sufficiency and skew compensation for class imbalances. The performance of different training strategies were compared across multiple machine learning classification algorithms, including nearest neighbor, Naïve Bayes, linear discriminant and ensemble Adaboost. The prediction performance is evaluated using metrics such as accuracy, precision, recall and the area under the curve (AUC) for repeater operating characteristics curve. The key results of the trend-based analysis indicate that (i) intra-fraction training strategies achieve highest prediction accuracies (90.5-91.4%); (ii) the predictive modeling yields lowest accuracies (50-60%) when the training data does not include any information from the test patient; (iii) the prediction latencies are as low as a few hundred milliseconds, and thus conducive for real-time prediction. The binary classification performance is promising, indicated by high AUCs (0.96-0.98). It also confirms the utility of prior data from previous patients, and also the necessity of training the classifier on some initial data from the new patient for reasonable prediction performance. The ability to predict a baseline shift with a sufficient look-ahead window will enable clinical systems or even human users to hold the treatment beam in such situations, thereby reducing the probability of serious geometric and dosimetric errors.
46 CFR 8.430 - U.S. Supplement to class rules.
Code of Federal Regulations, 2011 CFR
2011-10-01
... authorization to participate in the ACP, a recognized classification society must prepare, and receive Commandant (CG-521) approval of, a U.S. Supplement to the recognized classification society's class rules... of that classification society or applicable international regulations. ...
46 CFR 8.430 - U.S. Supplement to class rules.
Code of Federal Regulations, 2010 CFR
2010-10-01
... authorization to participate in the ACP, a recognized classification society must prepare, and receive Commandant (CG-521) approval of, a U.S. Supplement to the recognized classification society's class rules... of that classification society or applicable international regulations. ...
Classification of cloud fields based on textural characteristics
NASA Technical Reports Server (NTRS)
Welch, R. M.; Sengupta, S. K.; Chen, D. W.
1987-01-01
The present study reexamines the applicability of texture-based features for automatic cloud classification using very high spatial resolution (57 m) Landsat multispectral scanner digital data. It is concluded that cloud classification can be accomplished using only a single visible channel.
Survey and Method for Determination of Trajectory Predictor Requirements
NASA Technical Reports Server (NTRS)
Rentas, Tamika L.; Green, Steven M.; Cate, Karen Tung
2009-01-01
A survey of air-traffic-management researchers, representing a broad range of automation applications, was conducted to document trajectory-predictor requirements for future decision-support systems. Results indicated that the researchers were unable to articulate a basic set of trajectory-prediction requirements for their automation concepts. Survey responses showed the need to establish a process to help developers determine the trajectory-predictor-performance requirements for their concepts. Two methods for determining trajectory-predictor requirements are introduced. A fast-time simulation method is discussed that captures the sensitivity of a concept to the performance of its trajectory-prediction capability. A characterization method is proposed to provide quicker, yet less precise results, based on analysis and simulation to characterize the trajectory-prediction errors associated with key modeling options for a specific concept. Concept developers can then identify the relative sizes of errors associated with key modeling options, and qualitatively determine which options lead to significant errors. The characterization method is demonstrated for a case study involving future airport surface traffic management automation. Of the top four sources of error, results indicated that the error associated with accelerations to and from turn speeds was unacceptable, the error associated with the turn path model was acceptable, and the error associated with taxi-speed estimation was of concern and needed a higher fidelity concept simulation to obtain a more precise result
NASA Technical Reports Server (NTRS)
Hughes, Kyle M.; Knittel, Jeremy M.; Englander, Jacob A.
2017-01-01
This work presents an automated method of calculating mass (or time) optimal gravity-assist trajectories without a priori knowledge of the flyby-body combination. Since gravity assists are particularly crucial for reaching the outer Solar System, we use the Ice Giants, Uranus and Neptune, as example destinations for this work. Catalogs are also provided that list the most attractive trajectories found over launch dates ranging from 2024 to 2038. The tool developed to implement this method, called the Python EMTG Automated Trade Study Application (PEATSA), iteratively runs the Evolutionary Mission Trajectory Generator (EMTG), a NASA Goddard Space Flight Center in-house trajectory optimization tool. EMTG finds gravity-assist trajectories with impulsive maneuvers using a multiple-shooting structure along with stochastic methods (such as monotonic basin hopping) and may be run with or without an initial guess provided. PEATSA runs instances of EMTG in parallel over a grid of launch dates. After each set of runs completes, the best results within a neighborhood of launch dates are used to seed all other cases in that neighborhood-allowing the solutions across the range of launch dates to improve over each iteration. The results here are compared against trajectories found using a grid-search technique, and PEATSA is found to outperform the grid-search results for most launch years considered.
NASA Technical Reports Server (NTRS)
Hughes, Kyle M.; Knittel, Jeremy M.; Englander, Jacob A.
2017-01-01
This work presents an automated method of calculating mass (or time) optimal gravity-assist trajectories without a priori knowledge of the flyby-body combination. Since gravity assists are particularly crucial for reaching the outer Solar System, we use the Ice Giants, Uranus and Neptune, as example destinations for this work. Catalogs are also provided that list the most attractive trajectories found over launch dates ranging from 2024 to 2038. The tool developed to implement this method, called the Python EMTG Automated Trade Study Application (PEATSA), iteratively runs the Evolutionary Mission Trajectory Generator (EMTG), a NASA Goddard Space Flight Center in-house trajectory optimization tool. EMTG finds gravity-assist trajectories with impulsive maneuvers using a multiple-shooting structure along with stochastic methods (such as monotonic basin hopping) and may be run with or without an initial guess provided. PEATSA runs instances of EMTG in parallel over a grid of launch dates. After each set of runs completes, the best results within a neighborhood of launch dates are used to seed all other cases in that neighborhood---allowing the solutions across the range of launch dates to improve over each iteration. The results here are compared against trajectories found using a grid-search technique, and PEATSA is found to outperform the grid-search results for most launch years considered.
Boundary value problem for the solution of magnetic cutoff rigidities and some special applications
NASA Technical Reports Server (NTRS)
Edmonds, Larry
1987-01-01
Since a planet's magnetic field can sometimes provide a spacecraft with some protection against cosmic ray and solar flare particles, it is important to be able to quantify this protection. This is done by calculating cutoff rigidities. An alternate to the conventional method (particle trajectory tracing) is introduced, which is to treat the problem as a boundary value problem. In this approach trajectory tracing is only needed to supply boundary conditions. In some special cases, trajectory tracing is not needed at all because the problem can be solved analytically. A differential equation governing cutoff rigidities is derived for static magnetic fields. The presense of solid objects, which can block a trajectory and other force fields are not included. A few qualititative comments, on existence and uniqueness of solutions, are made which may be useful when deciding how the boundary conditions should be set up. Also included are topics on axially symmetric fields.
Real-time fuzzy inference based robot path planning
NASA Technical Reports Server (NTRS)
Pacini, Peter J.; Teichrow, Jon S.
1990-01-01
This project addresses the problem of adaptive trajectory generation for a robot arm. Conventional trajectory generation involves computing a path in real time to minimize a performance measure such as expended energy. This method can be computationally intensive, and it may yield poor results if the trajectory is weakly constrained. Typically some implicit constraints are known, but cannot be encoded analytically. The alternative approach used here is to formulate domain-specific knowledge, including implicit and ill-defined constraints, in terms of fuzzy rules. These rules utilize linguistic terms to relate input variables to output variables. Since the fuzzy rulebase is determined off-line, only high-level, computationally light processing is required in real time. Potential applications for adaptive trajectory generation include missile guidance and various sophisticated robot control tasks, such as automotive assembly, high speed electrical parts insertion, stepper alignment, and motion control for high speed parcel transfer systems.
Analysis of Video-Based Microscopic Particle Trajectories Using Kalman Filtering
Wu, Pei-Hsun; Agarwal, Ashutosh; Hess, Henry; Khargonekar, Pramod P.; Tseng, Yiider
2010-01-01
Abstract The fidelity of the trajectories obtained from video-based particle tracking determines the success of a variety of biophysical techniques, including in situ single cell particle tracking and in vitro motility assays. However, the image acquisition process is complicated by system noise, which causes positioning error in the trajectories derived from image analysis. Here, we explore the possibility of reducing the positioning error by the application of a Kalman filter, a powerful algorithm to estimate the state of a linear dynamic system from noisy measurements. We show that the optimal Kalman filter parameters can be determined in an appropriate experimental setting, and that the Kalman filter can markedly reduce the positioning error while retaining the intrinsic fluctuations of the dynamic process. We believe the Kalman filter can potentially serve as a powerful tool to infer a trajectory of ultra-high fidelity from noisy images, revealing the details of dynamic cellular processes. PMID:20550894
Entangled trajectories Hamiltonian dynamics for treating quantum nuclear effects
NASA Astrophysics Data System (ADS)
Smith, Brendan; Akimov, Alexey V.
2018-04-01
A simple and robust methodology, dubbed Entangled Trajectories Hamiltonian Dynamics (ETHD), is developed to capture quantum nuclear effects such as tunneling and zero-point energy through the coupling of multiple classical trajectories. The approach reformulates the classically mapped second-order Quantized Hamiltonian Dynamics (QHD-2) in terms of coupled classical trajectories. The method partially enforces the uncertainty principle and facilitates tunneling. The applicability of the method is demonstrated by studying the dynamics in symmetric double well and cubic metastable state potentials. The methodology is validated using exact quantum simulations and is compared to QHD-2. We illustrate its relationship to the rigorous Bohmian quantum potential approach, from which ETHD can be derived. Our simulations show a remarkable agreement of the ETHD calculation with the quantum results, suggesting that ETHD may be a simple and inexpensive way of including quantum nuclear effects in molecular dynamics simulations.
From Periodic Properties to a Periodic Table Arrangement
ERIC Educational Resources Information Center
Besalú, Emili
2013-01-01
A periodic table is constructed from the consideration of periodic properties and the application of the principal components analysis technique. This procedure is useful for objects classification and data reduction and has been used in the field of chemistry for many applications, such as lanthanides, molecules, or conformers classification.…
77 FR 32010 - Applications (Classification, Advisory, and License) and Documentation
Federal Register 2010, 2011, 2012, 2013, 2014
2012-05-31
... DEPARTMENT OF COMMERCE Bureau of Industry and Security 15 CFR Part 748 Applications (Classification, Advisory, and License) and Documentation CFR Correction 0 In Title 15 of the Code of Federal... fourth column of the table, the two entries for ``National Semiconductor Hong Kong Limited'' are removed...
The rotate-plus-shift C-arm trajectory: complete CT data with limited angular rotation
NASA Astrophysics Data System (ADS)
Ritschl, Ludwig; Kuntz, Jan; Kachelrieß, Marc
2015-03-01
In the last decade C-arm-based cone-beam CT became a widely used modality for intraoperative imaging. Typically a C-arm scan is performed using a circle-like trajectory around a region of interest. Therefor an angular range of at least 180° plus fan-angle must be covered to ensure a completely sampled data set. This fact defines some constraints on the geometry and technical specifications of a C-arm system, for example a larger C radius or a smaller C opening respectively. These technical modifications are usually not beneficial in terms of handling and usability of the C-arm during classical 2D applications like fluoroscopy. The method proposed in this paper relaxes the constraint of 180° plus fan-angle rotation to acquire a complete data set. The proposed C-arm trajectory requires a motorization of the orbital axis of the C and of ideally two orthogonal axis in the C plane. The trajectory consists of three parts: A rotation of the C around a defined iso-center and two translational movements parallel to the detector plane at the begin and at the end of the rotation. Combining these three parts to one trajectory enables for the acquisition of a completely sampled dataset using only 180° minus fan-angle of rotation. To evaluate the method we show animal and cadaver scans acquired with a mobile C-arm prototype. We expect that the transition of this method into clinical routine will lead to a much broader use of intraoperative 3D imaging in a wide field of clinical applications.
Information Gain Based Dimensionality Selection for Classifying Text Documents
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dumidu Wijayasekara; Milos Manic; Miles McQueen
2013-06-01
Selecting the optimal dimensions for various knowledge extraction applications is an essential component of data mining. Dimensionality selection techniques are utilized in classification applications to increase the classification accuracy and reduce the computational complexity. In text classification, where the dimensionality of the dataset is extremely high, dimensionality selection is even more important. This paper presents a novel, genetic algorithm based methodology, for dimensionality selection in text mining applications that utilizes information gain. The presented methodology uses information gain of each dimension to change the mutation probability of chromosomes dynamically. Since the information gain is calculated a priori, the computational complexitymore » is not affected. The presented method was tested on a specific text classification problem and compared with conventional genetic algorithm based dimensionality selection. The results show an improvement of 3% in the true positives and 1.6% in the true negatives over conventional dimensionality selection methods.« less
Global Stress Classification System for Materials Used in Solar Energy Applications
NASA Astrophysics Data System (ADS)
Slamova, Karolina; Schill, Christian; Herrmann, Jan; Datta, Pawan; Chih Wang, Chien
2016-08-01
Depending on the geographical location, the individual or combined impact of environmental stress factors and corresponding performance losses for solar applications varies significantly. Therefore, as a strategy to reduce investment risks and operating and maintenance costs, it is necessary to adapt the materials and components of solar energy systems specifically to regional environmental conditions. The project «GloBe Solar» supports this strategy by focusing on the development of a global stress classification system for materials in solar energy applications. The aim of this classification system is to assist in the identification of the individual stress conditions for every location on the earth's surface. The stress classification system could serve as a decision support tool for the industry (manufacturers, investors, lenders and project developers) and help to improve knowledge and services that can provide higher confidence to solar power systems.
NASA Astrophysics Data System (ADS)
Broderick, Ciaran; Fealy, Rowan
2013-04-01
Circulation type classifications (CTCs) compiled as part of the COST733 Action, entitled 'Harmonisation and Application of Weather Type Classifications for European Regions', are examined for their synoptic and climatological applicability to Ireland based on their ability to characterise surface temperature and precipitation. In all 16 different objective classification schemes, representative of four different methodological approaches to circulation typing (optimization algorithms, threshold based methods, eigenvector techniques and leader algorithms) are considered. Several statistical metrics which variously quantify the ability of CTCs to discretize daily data into well-defined homogeneous groups are used to evaluate and compare different approaches to synoptic typing. The records from 14 meteorological stations located across the island of Ireland are used in the study. The results indicate that while it was not possible to identify a single optimum classification or approach to circulation typing - conditional on the location and surface variables considered - a number of general assertions regarding the performance of different schemes can be made. The findings for surface temperature indicate that that those classifications based on predefined thresholds (e.g. Litynski, GrossWetterTypes and original Lamb Weather Type) perform well, as do the Kruizinga and Lund classification schemes. Similarly for precipitation predefined type classifications return high skill scores, as do those classifications derived using some optimization procedure (e.g. SANDRA, Self Organizing Maps and K-Means clustering). For both temperature and precipitation the results generally indicate that the classifications perform best for the winter season - reflecting the closer coupling between large-scale circulation and surface conditions during this period. In contrast to the findings for temperature, spatial patterns in the performance of classifications were more evident for precipitation. In the case of this variable those more westerly synoptic stations open to zonal airflow and less influenced by regional scale forcings generally exhibited a stronger link with large-scale circulation.
Visiting Vehicle Ground Trajectory Tool
NASA Technical Reports Server (NTRS)
Hamm, Dustin
2013-01-01
The International Space Station (ISS) Visiting Vehicle Group needed a targeting tool for vehicles that rendezvous with the ISS. The Visiting Vehicle Ground Trajectory targeting tool provides the ability to perform both realtime and planning operations for the Visiting Vehicle Group. This tool provides a highly reconfigurable base, which allows the Visiting Vehicle Group to perform their work. The application is composed of a telemetry processing function, a relative motion function, a targeting function, a vector view, and 2D/3D world map type graphics. The software tool provides the ability to plan a rendezvous trajectory for vehicles that visit the ISS. It models these relative trajectories using planned and realtime data from the vehicle. The tool monitors ongoing rendezvous trajectory relative motion, and ensures visiting vehicles stay within agreed corridors. The software provides the ability to update or re-plan a rendezvous to support contingency operations. Adding new parameters and incorporating them into the system was previously not available on-the-fly. If an unanticipated capability wasn't discovered until the vehicle was flying, there was no way to update things.
Techniques for shuttle trajectory optimization
NASA Technical Reports Server (NTRS)
Edge, E. R.; Shieh, C. J.; Powers, W. F.
1973-01-01
The application of recently developed function-space Davidon-type techniques to the shuttle ascent trajectory optimization problem is discussed along with an investigation of the recently developed PRAXIS algorithm for parameter optimization. At the outset of this analysis, the major deficiency of the function-space algorithms was their potential storage problems. Since most previous analyses of the methods were with relatively low-dimension problems, no storage problems were encountered. However, in shuttle trajectory optimization, storage is a problem, and this problem was handled efficiently. Topics discussed include: the shuttle ascent model and the development of the particular optimization equations; the function-space algorithms; the operation of the algorithm and typical simulations; variable final-time problem considerations; and a modification of Powell's algorithm.
NASA Astrophysics Data System (ADS)
Tercero, Carlos; Ikeda, Seiichi; Fukuda, Toshio; Arai, Fumihito; Negoro, Makoto; Takahashi, Ikuo
2011-10-01
There is a need to develop quantitative evaluation for simulator based training in medicine. Photoelastic stress analysis can be used in human tissue modeling materials; this enables the development of simulators that measure respect for tissue. For applying this to endovascular surgery, first we present a model of saccular aneurism where stress variation during micro-coils deployment is measured, and then relying on a bi-planar vision system we measure a catheter trajectory and compare it to a reference trajectory considering respect for tissue. New photoelastic tissue modeling materials will expand the applications of this technology to other medical training domains.
Flight trajectories with maximum tangential thrust in a central Newtonian field
NASA Astrophysics Data System (ADS)
Azizov, A. G.; Korshunova, N. A.
1983-07-01
The paper examines the two-dimensional problem of determining the optimal trajectories of a point moving with a limited per-second mass consumption in a central Newtonian field. It is shown that one of the cases in which the variational equations in the Meier formulation can be integrated in quadratures is motion with maximum tangential thrust. Trajectories corresponding to this motion are determined. By way of application, attention is given to the problem of determining the thrust which assures maximum kinetic energy for the point at the moment t = t1, corresponding to the mass consumption M0 - M1, where M0 and M1 are, respectively, the initial and final mass.
DOE Office of Scientific and Technical Information (OSTI.GOV)
García-Sánchez, Tania; Gómez-Lázaro, Emilio; Muljadi, E.
An alternative approach to characterise real voltage dips is proposed and evaluated in this study. The proposed methodology is based on voltage-space vector solutions, identifying parameters for ellipses trajectories by using the least-squares algorithm applied on a sliding window along the disturbance. The most likely patterns are then estimated through a clustering process based on the k-means algorithm. The objective is to offer an efficient and easily implemented alternative to characterise faults and visualise the most likely instantaneous phase-voltage evolution during events through their corresponding voltage-space vector trajectories. This novel solution minimises the data to be stored but maintains extensivemore » information about the dips including starting and ending transients. The proposed methodology has been applied satisfactorily to real voltage dips obtained from intensive field-measurement campaigns carried out in a Spanish wind power plant up to a time period of several years. A comparison to traditional minimum root mean square-voltage and time-duration classifications is also included in this study.« less
A scheme for a flexible classification of dietary and health biomarkers.
Gao, Qian; Praticò, Giulia; Scalbert, Augustin; Vergères, Guy; Kolehmainen, Marjukka; Manach, Claudine; Brennan, Lorraine; Afman, Lydia A; Wishart, David S; Andres-Lacueva, Cristina; Garcia-Aloy, Mar; Verhagen, Hans; Feskens, Edith J M; Dragsted, Lars O
2017-01-01
Biomarkers are an efficient means to examine intakes or exposures and their biological effects and to assess system susceptibility. Aided by novel profiling technologies, the biomarker research field is undergoing rapid development and new putative biomarkers are continuously emerging in the scientific literature. However, the existing concepts for classification of biomarkers in the dietary and health area may be ambiguous, leading to uncertainty about their application. In order to better understand the potential of biomarkers and to communicate their use and application, it is imperative to have a solid scheme for biomarker classification that will provide a well-defined ontology for the field. In this manuscript, we provide an improved scheme for biomarker classification based on their intended use rather than the technology or outcomes (six subclasses are suggested: food compound intake biomarkers (FCIBs), food or food component intake biomarkers (FIBs), dietary pattern biomarkers (DPBs), food compound status biomarkers (FCSBs), effect biomarkers, physiological or health state biomarkers). The application of this scheme is described in detail for the dietary and health area and is compared with previous biomarker classification for this field of research.
Hierarchic Agglomerative Clustering Methods for Automatic Document Classification.
ERIC Educational Resources Information Center
Griffiths, Alan; And Others
1984-01-01
Considers classifications produced by application of single linkage, complete linkage, group average, and word clustering methods to Keen and Cranfield document test collections, and studies structure of hierarchies produced, extent to which methods distort input similarity matrices during classification generation, and retrieval effectiveness…
Development of bimanual performance in young children with cerebral palsy.
Klevberg, Gunvor L; Elvrum, Ann-Kristin G; Zucknick, Manuela; Elkjaer, Sonja; Østensjø, Sigrid; Krumlinde-Sundholm, Lena; Kjeken, Ingvild; Jahnsen, Reidun
2018-05-01
To describe the development of bimanual performance among young children with unilateral or bilateral cerebral palsy (CP). A population-based sample of 102 children (53 males, 49 females), median age 28.5 months (interquartile range [IQR] 16mo) at first assessment and 47 months (IQR 18mo) at last assessment, was assessed half-yearly with the Assisting Hand Assessment (AHA) or the Both Hands Assessment (BoHA) for a total of 329 assessments. Developmental limits and rates were estimated by nonlinear mixed-effects models. Developmental trajectories were compared between levels of manual ability (Mini-Manual Ability Classification System [Mini-MACS] and MACS) and AHA or BoHA performance at 18 months of age (AHA-18/BoHA-18) for both CP subgroups, and additionally between children with bilateral CP with symmetric or asymmetric hand use. For both CP subgroups, children classified in Mini-MACS/MACS level I, and those with high AHA-18 or BoHA-18 reached the highest limits of performance. For children with bilateral CP the developmental change was small, and children with symmetric hand use reached the highest limits. Mini-MACS/MACS levels and AHA-18 or BoHA-18 distinguished between various developmental trajectories both for children with unilateral and bilateral CP. Children with bilateral CP changed their performance to a smaller extent than children with unilateral CP. Manual Ability Classification System levels and Assisting Hand Assessment/Both Hands Assessment performance at 18 months are important predictors of hand use development in cerebral palsy (CP). Children with bilateral CP improved less than those with unilateral CP. Children with bilateral CP and symmetric hand use reached higher limits than those with asymmetry. © 2018 Mac Keith Press.
Liu, Hongye; Kho, Alvin T; Kohane, Isaac S; Sun, Yao
2006-01-01
Background The histopathologic heterogeneity of lung cancer remains a significant confounding factor in its diagnosis and prognosis—spurring numerous recent efforts to find a molecular classification of the disease that has clinical relevance. Methods and Findings Molecular profiles of tumors from 186 patients representing four different lung cancer subtypes (and 17 normal lung tissue samples) were compared with a mouse lung development model using principal component analysis in both temporal and genomic domains. An algorithm for the classification of lung cancers using a multi-scale developmental framework was developed. Kaplan–Meier survival analysis was conducted for lung adenocarcinoma patient subgroups identified via their developmental association. We found multi-scale genomic similarities between four human lung cancer subtypes and the developing mouse lung that are prognostically meaningful. Significant association was observed between the localization of human lung cancer cases along the principal mouse lung development trajectory and the corresponding patient survival rate at three distinct levels of classical histopathologic resolution: among different lung cancer subtypes, among patients within the adenocarcinoma subtype, and within the stage I adenocarcinoma subclass. The earlier the genomic association between a human tumor profile and the mouse lung development sequence, the poorer the patient's prognosis. Furthermore, decomposing this principal lung development trajectory identified a gene set that was significantly enriched for pyrimidine metabolism and cell-adhesion functions specific to lung development and oncogenesis. Conclusions From a multi-scale disease modeling perspective, the molecular dynamics of murine lung development provide an effective framework that is not only data driven but also informed by the biology of development for elucidating the mechanisms of human lung cancer biology and its clinical outcome. PMID:16800721
Identification of aerosol types over an urban site based on air-mass trajectory classification
NASA Astrophysics Data System (ADS)
Pawar, G. V.; Devara, P. C. S.; Aher, G. R.
2015-10-01
Columnar aerosol properties retrieved from MICROTOPS II Sun Photometer measurements during 2010-2013 over Pune (18°32‧N; 73°49‧E, 559 m amsl), a tropical urban station in India, are analyzed to identify aerosol types in the atmospheric column. Identification/classification is carried out on the basis of dominant airflow patterns, and the method of discrimination of aerosol types on the basis of relation between aerosol optical depth (AOD500 nm) and Ångström exponent (AE, α). Five potential advection pathways viz., NW/N, SW/S, N, SE/E and L have been identified over the observing site by employing the NOAA-HYSPLIT air mass back trajectory analysis. Based on AE against AOD500 nm scatter plot and advection pathways followed five major aerosol types viz., continental average (CA), marine continental average (MCA), urban/industrial and biomass burning (UB), desert dust (DD) and indeterminate or mixed type (MT) have been identified. In winter, sector SE/E, a representative of air masses traversed over Bay of Bengal and Eastern continental Indian region has relatively small AOD (τpλ = 0.43 ± 0.13) and high AE (α = 1.19 ± 0.15). These values imply the presence of accumulation/sub-micron size anthropogenic aerosols. During pre-monsoon, aerosols from the NW/N sector have high AOD (τpλ = 0.61 ± 0.21), and low AE (α = 0.54 ± 0.14) indicating an increase in the loading of coarse-mode particles over Pune. Dominance of UB type in winter season for all the years (i.e. 2010-2013) may be attributed to both local/transported aerosols. During pre-monsoon seasons, MT is the dominant aerosol type followed by UB and DD, while the background aerosols are insignificant.
Torrens, Francisco; Castellano, Gloria
2014-06-05
Pesticide residues in wine were analyzed by liquid chromatography-tandem mass spectrometry. Retentions are modelled by structure-property relationships. Bioplastic evolution is an evolutionary perspective conjugating effect of acquired characters and evolutionary indeterminacy-morphological determination-natural selection principles; its application to design co-ordination index barely improves correlations. Fractal dimensions and partition coefficient differentiate pesticides. Classification algorithms are based on information entropy and its production. Pesticides allow a structural classification by nonplanarity, and number of O, S, N and Cl atoms and cycles; different behaviours depend on number of cycles. The novelty of the approach is that the structural parameters are related to retentions. Classification algorithms are based on information entropy. When applying procedures to moderate-sized sets, excessive results appear compatible with data suffering a combinatorial explosion. However, equipartition conjecture selects criterion resulting from classification between hierarchical trees. Information entropy permits classifying compounds agreeing with principal component analyses. Periodic classification shows that pesticides in the same group present similar properties; those also in equal period, maximum resemblance. The advantage of the classification is to predict the retentions for molecules not included in the categorization. Classification extends to phenyl/sulphonylureas and the application will be to predict their retentions.
Ecosystem classifications based on summer and winter conditions.
Andrew, Margaret E; Nelson, Trisalyn A; Wulder, Michael A; Hobart, George W; Coops, Nicholas C; Farmer, Carson J Q
2013-04-01
Ecosystem classifications map an area into relatively homogenous units for environmental research, monitoring, and management. However, their effectiveness is rarely tested. Here, three classifications are (1) defined and characterized for Canada along summertime productivity (moderate-resolution imaging spectrometer fraction of absorbed photosynthetically active radiation) and wintertime snow conditions (special sensor microwave/imager snow water equivalent), independently and in combination, and (2) comparatively evaluated to determine the ability of each classification to represent the spatial and environmental patterns of alternative schemes, including the Canadian ecozone framework. All classifications depicted similar patterns across Canada, but detailed class distributions differed. Class spatial characteristics varied with environmental conditions within classifications, but were comparable between classifications. There was moderate correspondence between classifications. The strongest association was between productivity classes and ecozones. The classification along both productivity and snow balanced these two sets of variables, yielding intermediate levels of association in all pairwise comparisons. Despite relatively low spatial agreement between classifications, they successfully captured patterns of the environmental conditions underlying alternate schemes (e.g., snow classes explained variation in productivity and vice versa). The performance of ecosystem classifications and the relevance of their input variables depend on the environmental patterns and processes used for applications and evaluation. Productivity or snow regimes, as constructed here, may be desirable when summarizing patterns controlled by summer- or wintertime conditions, respectively, or of climate change responses. General purpose ecosystem classifications should include both sets of drivers. Classifications should be carefully, quantitatively, and comparatively evaluated relative to a particular application prior to their implementation as monitoring and assessment frameworks.
Automated simultaneous multiple feature classification of MTI data
NASA Astrophysics Data System (ADS)
Harvey, Neal R.; Theiler, James P.; Balick, Lee K.; Pope, Paul A.; Szymanski, John J.; Perkins, Simon J.; Porter, Reid B.; Brumby, Steven P.; Bloch, Jeffrey J.; David, Nancy A.; Galassi, Mark C.
2002-08-01
Los Alamos National Laboratory has developed and demonstrated a highly capable system, GENIE, for the two-class problem of detecting a single feature against a background of non-feature. In addition to the two-class case, however, a commonly encountered remote sensing task is the segmentation of multispectral image data into a larger number of distinct feature classes or land cover types. To this end we have extended our existing system to allow the simultaneous classification of multiple features/classes from multispectral data. The technique builds on previous work and its core continues to utilize a hybrid evolutionary-algorithm-based system capable of searching for image processing pipelines optimized for specific image feature extraction tasks. We describe the improvements made to the GENIE software to allow multiple-feature classification and describe the application of this system to the automatic simultaneous classification of multiple features from MTI image data. We show the application of the multiple-feature classification technique to the problem of classifying lava flows on Mauna Loa volcano, Hawaii, using MTI image data and compare the classification results with standard supervised multiple-feature classification techniques.
Shin, Younghak; Lee, Seungchan; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan; Lee, Heung-No
2015-11-01
One of the main problems related to electroencephalogram (EEG) based brain-computer interface (BCI) systems is the non-stationarity of the underlying EEG signals. This results in the deterioration of the classification performance during experimental sessions. Therefore, adaptive classification techniques are required for EEG based BCI applications. In this paper, we propose simple adaptive sparse representation based classification (SRC) schemes. Supervised and unsupervised dictionary update techniques for new test data and a dictionary modification method by using the incoherence measure of the training data are investigated. The proposed methods are very simple and additional computation for the re-training of the classifier is not needed. The proposed adaptive SRC schemes are evaluated using two BCI experimental datasets. The proposed methods are assessed by comparing classification results with the conventional SRC and other adaptive classification methods. On the basis of the results, we find that the proposed adaptive schemes show relatively improved classification accuracy as compared to conventional methods without requiring additional computation. Copyright © 2015 Elsevier Ltd. All rights reserved.
Horstick, Olaf; Jaenisch, Thomas; Martinez, Eric; Kroeger, Axel; See, Lucy Lum Chai; Farrar, Jeremy; Ranzinger, Silvia Runge
2014-09-01
The 1997 and 2009 WHO dengue case classifications were compared in a systematic review with 12 eligible studies (4 prospective). Ten expert opinion articles were used for discussion. For the 2009 WHO classification studies show: when determining severe dengue sensitivity ranges between 59-98% (88%/98%: prospective studies), specificity between 41-99% (99%: prospective study) - comparing the 1997 WHO classification: sensitivity 24.8-89.9% (24.8%/74%: prospective studies), specificity: 25%/100% (100%: prospective study). The application of the 2009 WHO classification is easy, however for (non-severe) dengue there may be a risk of monitoring increased case numbers. Warning signs validation studies are needed. For epidemiological/pathogenesis research use of the 2009 WHO classification, opinion papers show that ease of application, increased sensitivity (severe dengue) and international comparability are advantageous; 3 severe dengue criteria (severe plasma leakage, severe bleeding, severe organ manifestation) are useful research endpoints. The 2009 WHO classification has clear advantages for clinical use, use in epidemiology is promising and research use may at least not be a disadvantage. © The American Society of Tropical Medicine and Hygiene.
Measurement Of Water Sprays Generated By Airplane Tires
NASA Technical Reports Server (NTRS)
Daugherty, Robert H.; Stubbs, Sandy M.
1990-01-01
Experimental investigation conducted at NASA Langley Research Center to measure rate of flow and trajectory of water spray generated by tire operating on flooded runway. Potential application to both aircraft and automotive industries, with particular application to manufacturers of tires.
[Research progress in molecular classification of gastric cancer].
Zhou, Menglong; Li, Guichao; Zhang, Zhen
2016-09-25
Gastric cancer(GC) is a highly heterogeneous malignancy. The present widely used histopathological classifications have gradually failed to meet the needs of individualized diagnosis and treatment. Development of technologies such as microarray and next-generation sequencing (NGS) has allowed GC to be studied at the molecular level. Mechanisms about tumorigenesis and progression of GC can be elucidated in the aspects of gene mutations, chromosomal alterations, transcriptional and epigenetic changes, on the basis of which GC can be divided into several subtypes. The classifications of Tan's, Lei's, TCGA and ACRG are relatively comprehensive. Especially the TCGA and ACRG classifications have large sample size and abundant molecular profiling data, thus, the genomic characteristics of GC can be depicted more accurately. However, significant differences between both classifications still exist so that they cannot be substituted for each other. So far there is no widely accepted molecular classification of GC. Compared with TCGA classification, ACRG system may have more clinical significance in Chinese GC patients since the samples are mostly from Asian population and show better association with prognosis. The molecular classification of GC may provide the theoretical and experimental basis for early diagnosis, therapeutic efficacy prediction and treatment stratification while their clinical application is still limited. Future work should involve the application of molecular classifications in the clinical settings for improving the medical management of GC.
NASA Technical Reports Server (NTRS)
Benediktsson, J. A.; Swain, P. H.; Ersoy, O. K.
1993-01-01
Application of neural networks to classification of remote sensing data is discussed. Conventional two-layer backpropagation is found to give good results in classification of remote sensing data but is not efficient in training. A more efficient variant, based on conjugate-gradient optimization, is used for classification of multisource remote sensing and geographic data and very-high-dimensional data. The conjugate-gradient neural networks give excellent performance in classification of multisource data, but do not compare as well with statistical methods in classification of very-high-dimentional data.
1980-12-05
classification procedures that are common in speech processing. The anesthesia level classification by EEG time series population screening problem example is in...formance. The use of the KL number type metric in NN rule classification, in a delete-one subj ect ’s EE-at-a-time KL-NN and KL- kNN classification of the...17 individual labeled EEG sample population using KL-NN and KL- kNN rules. The results obtained are shown in Table 1. The entries in the table indicate
NASA Technical Reports Server (NTRS)
Rado, B. Q.
1975-01-01
Automatic classification techniques are described in relation to future information and natural resource planning systems with emphasis on application to Georgia resource management problems. The concept, design, and purpose of Georgia's statewide Resource AS Assessment Program is reviewed along with participation in a workshop at the Earth Resources Laboratory. Potential areas of application discussed include: agriculture, forestry, water resources, environmental planning, and geology.
Equitable Estoppel: Its Genesis, Development, and Application in Government Contracting
1988-09-30
NO. CCESSION NO. ,1. T:ITLE (include Security Classification) (UNCLASSIFIED) Equitable Estoppel : Its Genesis, Development, and Application in...sE.UkRm/ CLASSIFICATION OF THIS PAGE AFIT/CI’ "OVERPRINT" Equitable Estoppel : Its Genesis, Development, and Application in Government CoritractingQ By...John Cibinic,Jr. and Ralph C. Nash,Jr. Professors of Law 90 02 12 031 -Table of Contents 1. The Doctrine of Equitable Estoppel -................... 1
NASA Astrophysics Data System (ADS)
Duffy, P.; Keller, M.; Longo, M.; Morton, D. C.; dos-Santos, M. N.; Pinagé, E. R.
2017-12-01
There is an urgent need to quantify the effects of land use and land cover change on carbon stocks in tropical forests to support REDD+ policies and improve characterization of global carbon budgets. This need is underscored by the fact that the variability in forest biomass estimates from global forest carbon maps is artificially low relative to estimates generated from forest inventory and high-resolution airborne lidar data. Both deforestation and degradation processes (e.g. logging, fire, and fragmentation) affect carbon fluxes at varying spatial and temporal scales. While the spatial extent and impact of deforestation has been relatively well characterized, the quantification of degradation processes is still poorly constrained. In the Brazilian Amazon, the largest source of uncertainty in CO2 emissions estimates is data on changes in tropical forest carbon stocks through time, followed closely by incomplete information on the carbon losses from forest degradation. In this work, we present a method for classifying the degradation status of tropical forests using higher order moments (skewness and kurtosis) of lidar return distributions aggregated at grids with resolution ranging from 50 m to 250 m. Across multiple spatial resolutions, we quantify the strength of the functional relationship between the lidar returns and the classification based on historical time series of Landsat imagery. Our results show that the higher order moments of the lidar return distributions provide sufficient information to build multinomial models that accurately classify the landscape into intact, logged, and burned forests. Model fit improved with coarser spatial resolution with Kappa statistics of 0.70 at 50 m, and 0.77 at 250 m. In addition, multi-class AUC was estimated as 0.87 at 50 m, and 0.95 at 250 m. This classification provides important information regarding the applicability of the use of lidar data for regional monitoring of recent logging, as well as the trajectory of the carbon budget. Differentiating between the biomass changes associated with deforestation and degradation processes is critical for accurate accounting of disturbance impacts on carbon cycling within the Brazilian Amazon and global tropical forests.
Layered classification techniques for remote sensing applications
NASA Technical Reports Server (NTRS)
Swain, P. H.; Wu, C. L.; Landgrebe, D. A.; Hauska, H.
1975-01-01
The single-stage method of pattern classification utilizes all available features in a single test which assigns the unknown to a category according to a specific decision strategy (such as the maximum likelihood strategy). The layered classifier classifies the unknown through a sequence of tests, each of which may be dependent on the outcome of previous tests. Although the layered classifier was originally investigated as a means of improving classification accuracy and efficiency, it was found that in the context of remote sensing data analysis, other advantages also accrue due to many of the special characteristics of both the data and the applications pursued. The layered classifier method and several of the diverse applications of this approach are discussed.
Designing and Implementation of River Classification Assistant Management System
NASA Astrophysics Data System (ADS)
Zhao, Yinjun; Jiang, Wenyuan; Yang, Rujun; Yang, Nan; Liu, Haiyan
2018-03-01
In an earlier publication, we proposed a new Decision Classifier (DCF) for Chinese river classification based on their structures. To expand, enhance and promote the application of the DCF, we build a computer system to support river classification named River Classification Assistant Management System. Based on ArcEngine and ArcServer platform, this system implements many functions such as data management, extraction of river network, river classification, and results publication under combining Client / Server with Browser / Server framework.
12 CFR 560.160 - Asset classification.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 12 Banks and Banking 5 2010-01-01 2010-01-01 false Asset classification. 560.160 Section 560.160 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY LENDING AND INVESTMENT Lending and Investment Provisions Applicable to all Savings Associations § 560.160 Asset classification...
Myakalwar, Ashwin Kumar; Sreedhar, S.; Barman, Ishan; Dingari, Narahara Chari; Rao, S. Venugopal; Kiran, P. Prem; Tewari, Surya P.; Kumar, G. Manoj
2012-01-01
We report the effectiveness of laser-induced breakdown spectroscopy (LIBS) in probing the content of pharmaceutical tablets and also investigate its feasibility for routine classification. This method is particularly beneficial in applications where its exquisite chemical specificity and suitability for remote and on site characterization significantly improves the speed and accuracy of quality control and assurance process. Our experiments reveal that in addition to the presence of carbon, hydrogen, nitrogen and oxygen, which can be primarily attributed to the active pharmaceutical ingredients, specific inorganic atoms were also present in all the tablets. Initial attempts at classification by a ratiometric approach using oxygen to nitrogen compositional values yielded an optimal value (at 746.83 nm) with the least relative standard deviation but nevertheless failed to provide an acceptable classification. To overcome this bottleneck in the detection process, two chemometric algorithms, i.e. principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA), were implemented to exploit the multivariate nature of the LIBS data demonstrating that LIBS has the potential to differentiate and discriminate among pharmaceutical tablets. We report excellent prospective classification accuracy using supervised classification via the SIMCA algorithm, demonstrating its potential for future applications in process analytical technology, especially for fast on-line process control monitoring applications in the pharmaceutical industry. PMID:22099648
Multi-level discriminative dictionary learning with application to large scale image classification.
Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua
2015-10-01
The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.
Properties of the ellipse-line-ellipse trajectory with asymmetrical variations
NASA Astrophysics Data System (ADS)
Guo, Zijia; Noo, Frédéric; Maier, Andreas; Lauritsch, Guenter
2016-03-01
Three-dimensional cone-beam (CB) imaging using a multi-axis floor-mounted (or ceiling-mounted) C-arm system has become an important tool in interventional radiology. This success motivates new developments to improve image quality. One direction in which advancement is sought is the data acquisition geometry and related CB artifacts. Currently, data acquisition is performed using the circular short-scan trajectory, which yields limited axial coverage and also provides incomplete data for accurate reconstruction. To improve the image quality, as well as to increase the coverage in the longitudinal direction of the patient, we recently introduced the ellipse- line-ellipse trajectory and showed that this trajectory provides full R-line coverage within the field-of-view, which is a key property for accurate reconstruction from truncated data. An R-line is any segment of line that connects two source positions. Here, we examine how the application of asymmetrical variations to the definition of the ELE trajectory impacts the R-line coverage. This question is significant to understand how much flexibility can be used in the implementation of the ELE trajectory, particularly to adapt the scan to patient anatomy and imaging task of interest. Two types of asymmetrical variations, called axial and angular variations, are investigated.
Analysis of self-overlap reveals trade-offs in plankton swimming trajectories
Bianco, Giuseppe; Mariani, Patrizio; Visser, Andre W.; Mazzocchi, Maria Grazia; Pigolotti, Simone
2014-01-01
Movement is a fundamental behaviour of organisms that not only brings about beneficial encounters with resources and mates, but also at the same time exposes the organism to dangerous encounters with predators. The movement patterns adopted by organisms should reflect a balance between these contrasting processes. This trade-off can be hypothesized as being evident in the behaviour of plankton, which inhabit a dilute three-dimensional environment with few refuges or orienting landmarks. We present an analysis of the swimming path geometries based on a volumetric Monte Carlo sampling approach, which is particularly adept at revealing such trade-offs by measuring the self-overlap of the trajectories. Application of this method to experimentally measured trajectories reveals that swimming patterns in copepods are shaped to efficiently explore volumes at small scales, while achieving a large overlap at larger scales. Regularities in the observed trajectories make the transition between these two regimes always sharper than in randomized trajectories or as predicted by random walk theory. Thus, real trajectories present a stronger separation between exploration for food and exposure to predators. The specific scale and features of this transition depend on species, gender and local environmental conditions, pointing at adaptation to state and stage-dependent evolutionary trade-offs. PMID:24789560
NASA Astrophysics Data System (ADS)
Wang, Mingming; Luo, Jianjun; Fang, Jing; Yuan, Jianping
2018-03-01
The existence of the path dependent dynamic singularities limits the volume of available workspace of free-floating space robot and induces enormous joint velocities when such singularities are met. In order to overcome this demerit, this paper presents an optimal joint trajectory planning method using forward kinematics equations of free-floating space robot, while joint motion laws are delineated with application of the concept of reaction null-space. Bézier curve, in conjunction with the null-space column vectors, are applied to describe the joint trajectories. Considering the forward kinematics equations of the free-floating space robot, the trajectory planning issue is consequently transferred to an optimization issue while the control points to construct the Bézier curve are the design variables. A constrained differential evolution (DE) scheme with premature handling strategy is implemented to find the optimal solution of the design variables while specific objectives and imposed constraints are satisfied. Differ from traditional methods, we synthesize null-space and specialized curve to provide a novel viewpoint for trajectory planning of free-floating space robot. Simulation results are presented for trajectory planning of 7 degree-of-freedom (DOF) kinematically redundant manipulator mounted on a free-floating spacecraft and demonstrate the feasibility and effectiveness of the proposed method.
Waadeland, Carl Haakon
2017-01-01
Results from different empirical investigations on gestural aspects of timed rhythmic movements indicate that the production of asymmetric movement trajectories is a feature that seems to be a common characteristic of various performances of repetitive rhythmic patterns. The behavioural or neural origin of these asymmetrical trajectories is, however, not identified. In the present study we outline a theoretical model that is capable of producing syntheses of asymmetric movement trajectories documented in empirical investigations by Balasubramaniam et al. (2004). Characteristic qualities of the extension/flexion profiles in the observed asymmetric trajectories are reproduced, and we conduct an experiment similar to Balasubramaniam et al. (2004) to show that the empirically documented movement trajectories and our modelled approximations share the same spectral components. The model is based on an application of frequency modulated movements, and a theoretical interpretation offered by the model is to view paced rhythmic movements as a result of an unpaced movement being "stretched" and "compressed", caused by the presence of a metronome. We discuss our model construction within the framework of event-based and emergent timing, and argue that a change between these timing modes might be reflected by the strength of the modulation in our model. Copyright © 2016 Elsevier B.V. All rights reserved.
Advances in the Application of Decision Theory to Test-Based Decision Making.
ERIC Educational Resources Information Center
van der Linden, Wim J.
This paper reviews recent research in the Netherlands on the application of decision theory to test-based decision making about personnel selection and student placement. The review is based on an earlier model proposed for the classification of decision problems, and emphasizes an empirical Bayesian framework. Classification decisions with…
NASA Astrophysics Data System (ADS)
Xu, Yunjun; Remeikas, Charles; Pham, Khanh
2014-03-01
Cooperative trajectory planning is crucial for networked vehicles to respond rapidly in cluttered environments and has a significant impact on many applications such as air traffic or border security monitoring and assessment. One of the challenges in cooperative planning is to find a computationally efficient algorithm that can accommodate both the complexity of the environment and real hardware and configuration constraints of vehicles in the formation. Inspired by a local pursuit strategy observed in foraging ants, feasible and optimal trajectory planning algorithms are proposed in this paper for a class of nonlinear constrained cooperative vehicles in environments with densely populated obstacles. In an iterative hierarchical approach, the local behaviours, such as the formation stability, obstacle avoidance, and individual vehicle's constraints, are considered in each vehicle's (i.e. follower's) decentralised optimisation. The cooperative-level behaviours, such as the inter-vehicle collision avoidance, are considered in the virtual leader's centralised optimisation. Early termination conditions are derived to reduce the computational cost by not wasting time in the local-level optimisation if the virtual leader trajectory does not satisfy those conditions. The expected advantages of the proposed algorithms are (1) the formation can be globally asymptotically maintained in a decentralised manner; (2) each vehicle decides its local trajectory using only the virtual leader and its own information; (3) the formation convergence speed is controlled by one single parameter, which makes it attractive for many practical applications; (4) nonlinear dynamics and many realistic constraints, such as the speed limitation and obstacle avoidance, can be easily considered; (5) inter-vehicle collision avoidance can be guaranteed in both the formation transient stage and the formation steady stage; and (6) the computational cost in finding both the feasible and optimal solutions is low. In particular, the feasible solution can be computed in a very quick fashion. The minimum energy trajectory planning for a group of robots in an obstacle-laden environment is simulated to showcase the advantages of the proposed algorithms.
High-Speed Solution of Spacecraft Trajectory Problems Using Taylor Series Integration
NASA Technical Reports Server (NTRS)
Scott, James R.; Martini, Michael C.
2010-01-01
It has been known for some time that Taylor series (TS) integration is among the most efficient and accurate numerical methods in solving differential equations. However, the full benefit of the method has yet to be realized in calculating spacecraft trajectories, for two main reasons. First, most applications of Taylor series to trajectory propagation have focused on relatively simple problems of orbital motion or on specific problems and have not provided general applicability. Second, applications that have been more general have required use of a preprocessor, which inevitably imposes constraints on computational efficiency. The latter approach includes the work of Berryman et al., who solved the planetary n-body problem with relativistic effects. Their work specifically noted the computational inefficiencies arising from use of a preprocessor and pointed out the potential benefit of manually coding derivative routines. In this Engineering Note, we report on a systematic effort to directly implement Taylor series integration in an operational trajectory propagation code: the Spacecraft N-Body Analysis Program (SNAP). The present Taylor series implementation is unique in that it applies to spacecraft virtually anywhere in the solar system and can be used interchangeably with another integration method. SNAP is a high-fidelity trajectory propagator that includes force models for central body gravitation with N X N harmonics, other body gravitation with N X N harmonics, solar radiation pressure, atmospheric drag (for Earth orbits), and spacecraft thrusting (including shadowing). The governing equations are solved using an eighth-order Runge-Kutta Fehlberg (RKF) single-step method with variable step size control. In the present effort, TS is implemented by way of highly integrated subroutines that can be used interchangeably with RKF. This makes it possible to turn TS on or off during various phases of a mission. Current TS force models include central body gravitation with the J2 spherical harmonic, other body gravitation, thrust, constant atmospheric drag from Earth's atmosphere, and solar radiation pressure for a sphere under constant illumination. The purpose of this Engineering Note is to demonstrate the performance of TS integration in an operational trajectory analysis code and to compare it with a standard method, eighth-order RKF. Results show that TS is 16.6 times faster on average and is more accurate in 87.5% of the cases presented.
About decomposition approach for solving the classification problem
NASA Astrophysics Data System (ADS)
Andrianova, A. A.
2016-11-01
This article describes the features of the application of an algorithm with using of decomposition methods for solving the binary classification problem of constructing a linear classifier based on Support Vector Machine method. Application of decomposition reduces the volume of calculations, in particular, due to the emerging possibilities to build parallel versions of the algorithm, which is a very important advantage for the solution of problems with big data. The analysis of the results of computational experiments conducted using the decomposition approach. The experiment use known data set for binary classification problem.
Applications of remote sensing, volume 1
NASA Technical Reports Server (NTRS)
Landgrebe, D. A. (Principal Investigator)
1977-01-01
The author has identified the following significant results. ECHO successfully exploits the redundancy of states characteristics of sampled imagery of ground scenes to achieve better classification accuracy, reduce the number of classifications required, and reduce the variability of classification results. The information required to produce ECHO classifications are cell size, cell homogeneity, cell-to-field annexation parameters, input data, and a class conditional marginal density statistics deck.
An Energy-Aware Trajectory Optimization Layer for sUAS
NASA Astrophysics Data System (ADS)
Silva, William A.
The focus of this work is the implementation of an energy-aware trajectory optimization algorithm that enables small unmanned aircraft systems (sUAS) to operate in unknown, dynamic severe weather environments. The software is designed as a component of an Energy-Aware Dynamic Data Driven Application System (EA-DDDAS) for sUAS. This work addresses the challenges of integrating and executing an online trajectory optimization algorithm during mission operations in the field. Using simplified aircraft kinematics, the energy-aware algorithm enables extraction of kinetic energy from measured winds to optimize thrust use and endurance during flight. The optimization layer, based upon a nonlinear program formulation, extracts energy by exploiting strong wind velocity gradients in the wind field, a process known as dynamic soaring. The trajectory optimization layer extends the energy-aware path planner developed by Wenceslao Shaw-Cortez te{Shaw-cortez2013} to include additional mission configurations, simulations with a 6-DOF model, and validation of the system with flight testing in June 2015 in Lubbock, Texas. The trajectory optimization layer interfaces with several components within the EA-DDDAS to provide an sUAS with optimal flight trajectories in real-time during severe weather. As a result, execution timing, data transfer, and scalability are considered in the design of the software. Severe weather also poses a measure of unpredictability to the system with respect to communication between systems and available data resources during mission operations. A heuristic mission tree with different cost functions and constraints is implemented to provide a level of adaptability to the optimization layer. Simulations and flight experiments are performed to assess the efficacy of the trajectory optimization layer. The results are used to assess the feasibility of flying dynamic soaring trajectories with existing controllers as well as to verify the interconnections between EA-DDDAS components. Results also demonstrate the usage of the trajectory optimization layer in conjunction with a lattice-based path planner as a method of guiding the optimization layer and stitching together subsequent trajectories.
Analysis on the application of background parameters on remote sensing classification
NASA Astrophysics Data System (ADS)
Qiao, Y.
Drawing accurate crop cultivation acreage, dynamic monitoring of crops growing and yield forecast are some important applications of remote sensing to agriculture. During the 8th 5-Year Plan period, the task of yield estimation using remote sensing technology for the main crops in major production regions in China once was a subtopic to the national research task titled "Study on Application of Remote sensing Technology". In 21 century in a movement launched by Chinese Ministry of Agriculture to combine high technology to farming production, remote sensing has given full play to farm crops' growth monitoring and yield forecast. And later in 2001 Chinese Ministry of Agriculture entrusted the Northern China Center of Agricultural Remote Sensing to forecast yield of some main crops like wheat, maize and rice in rather short time to supply information for the government decision maker. Present paper is a report for this task. It describes the application of background parameters in image recognition, classification and mapping with focuses on plan of the geo-science's theory, ecological feature and its cartographical objects or scale, the study of phrenology for image optimal time for classification of the ground objects, the analysis of optimal waveband composition and the application of background data base to spatial information recognition ;The research based on the knowledge of background parameters is indispensable for improving the accuracy of image classification and mapping quality and won a secondary reward of tech-science achievement from Chinese Ministry of Agriculture. Keywords: Spatial image; Classification; Background parameter
Russell, Ginny; Kelly, Susan E; Ford, Tamsin; Steer, Colin
2012-11-01
Jutel and Nettleton (2011) discuss diagnosis as not only a major classification tool for medicine but also an interactive social process that itself may have ramifications for health. Consideration of diagnosis as a social determinant of health outcomes led to the formulation of our research question: Can we detect a change in the development of prosocial symptoms before and after an Autism Spectrum Disorder (ASD) diagnosis? We examined the developmental trajectory of prosocial skills of children, as impairment in social skills is given as a core symptom for children with ASD. We used a validated scale measuring prosocial behaviour for a sample of 57 children where the measure was repeatedly recorded over ten years. We plotted the developmental trajectory of the prosocial trait in this sample who were enrolled in a longitudinal birth cohort study based in South West England. Multi-factorial fixed effect modelling suggests that the developmental trajectory of this measure of behaviour was not significantly altered by ASD diagnosis, or the consequences of diagnosis, either for better or worse. Further analysis was conducted on a subset of 33 of the children who had both pre-diagnosis and post-diagnosis information, and the same result obtained. The results indicate that prosocial behaviours may be resistant to typical 'treatments': provision of educational and specialist health services triggered by a clinical ASD diagnosis. The implications of this for considering diagnosis as a social determinant are discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.
Groenendyk, Derek G.; Ferré, Ty P.A.; Thorp, Kelly R.; Rice, Amy K.
2015-01-01
Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth’s surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape function, suggest that hydrologic-process-based classifications should be incorporated into environmental process models and can be used to define application-specific maps of hydrologic function. PMID:26121466
Groenendyk, Derek G; Ferré, Ty P A; Thorp, Kelly R; Rice, Amy K
2015-01-01
Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth's surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape function, suggest that hydrologic-process-based classifications should be incorporated into environmental process models and can be used to define application-specific maps of hydrologic function.
Nineteen hundred seventy three significant accomplishments. [Landsat satellite data applications
NASA Technical Reports Server (NTRS)
1974-01-01
Data collected by the Skylab remote sensing satellites was used to develop applications techniques and to combine automatic data classification with statistical clustering methods. Continuing research was concentrated in the correlation and registration of data products and in the definition of the atmospheric effects on remote sensing. The causes of errors encountered in the automated classification of agricultural data are identified. Other applications in forestry, geography, environmental geology, and land use are discussed.
Landstedt, Evelina; Hammarström, Anne; Fairweather-Schmidt, A Kate; Wade, Tracey
2018-05-01
To date, no longitudinal, community-based studies have examined the association between disordered eating emerging in adolescence and long-term physical well-being. This study sought to explore the longitudinal associations between risk for restrictive disordered eating (DE-R; those not presenting with binge-purge symptoms) in adolescence and trajectories of functional somatic symptoms (FSS) and body mass index (BMI), and several indicators of poor physical well-being across early- to mid-adulthood, including medication, number of doctor visits, and sick leave. Data were obtained from the Northern Swedish Cohort Study (N = 1,001), a prospective longitudinal study including four time points from age 16 to 42 years. A cumulative measure of DE-R risk was computed. Latent class growth analysis was used to identify subpopulation trajectories of FSS and BMI. The three-step method for auxiliary variables and logistic regressions were used to assess associations between DE-R and the trajectory classes as well as indicators of poor physical well-being. Three trajectories were identified for FSS. A gender by BMI interaction led to a classification of four BMI trajectories in men, but three in women. The presence of DE-R risk in adolescence increased odds of unfavourable FSS development, increasing BMI in women, and continually low BMI in men. Indicators of poor physical well-being at ages 21, 30, and 42 years were associated with DE-R risk in adolescence. Data spanning nearly three decades suggest that physical well-being impairment is related to DE-R risk measured earlier in life, underscoring the urgency for targeted, gender-sensitive preventive interventions for teenagers. Statement of contribution What is already known on this subject? Disordered eating is linked to poor physical and mental well-being and quality of life. No longitudinal studies have examined long-term physical well-being consequences of adolescent disordered eating risk. What does this study add? Non-purging disordered eating symptoms in adolescence predict adverse physical well-being outcomes in middle-aged men and women. Targeted interventions and preventative work during adolescence are needed. © 2018 The British Psychological Society.
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32 CFR 1627.3 - Classification of volunteers.
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Land Type Associations Conference: Summary Comments
Thomas R. Crow
2002-01-01
Holding a conference on Landtype Associations in Madison seems appropriate given the amount of research and application on ecological classification that has taken place here and elsewhere within the region. In fact, a previous conference held at the University of Wisconsin, Madison, in March 1984 on ecosystem classification entitled "Forest Land Classifications:...
46 CFR 8.440 - Vessel enrollment in the Alternate Compliance Program.
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2014-10-01
... classification society and accepted by the Coast Guard, the cognizant OCMI may decline to issue a certificate of... recognized classification society authorized by the Coast Guard to determine compliance with applicable international treaties and agreements, the classification society's class rules, and the U.S. supplement...
46 CFR 8.440 - Vessel enrollment in the Alternate Compliance Program.
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2012-10-01
... classification society and accepted by the Coast Guard, the cognizant OCMI may decline to issue a certificate of... recognized classification society authorized by the Coast Guard to determine compliance with applicable international treaties and agreements, the classification society's class rules, and the U.S. Supplement...
46 CFR 8.440 - Vessel enrollment in the Alternate Compliance Program.
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2013-10-01
... classification society and accepted by the Coast Guard, the cognizant OCMI may decline to issue a certificate of... recognized classification society authorized by the Coast Guard to determine compliance with applicable international treaties and agreements, the classification society's class rules, and the U.S. supplement...
Speech Music Discrimination Using Class-Specific Features
2004-08-01
Speech Music Discrimination Using Class-Specific Features Thomas Beierholm...between speech and music . Feature extraction is class-specific and can therefore be tailored to each class meaning that segment size, model orders...interest. Some of the applications of audio signal classification are speech/ music classification [1], acoustical environmental classification [2][3
46 CFR 8.440 - Vessel enrollment in the Alternate Compliance Program.
Code of Federal Regulations, 2010 CFR
2010-10-01
... issuance or renewal of a COI may submit the vessel for classification, plan review and inspection by a recognized classification society authorized by the Coast Guard to determine compliance with applicable international treaties and agreements, the classification society's class rules, and the U.S. Supplement...
46 CFR 8.440 - Vessel enrollment in the Alternate Compliance Program.
Code of Federal Regulations, 2011 CFR
2011-10-01
... issuance or renewal of a COI may submit the vessel for classification, plan review and inspection by a recognized classification society authorized by the Coast Guard to determine compliance with applicable international treaties and agreements, the classification society's class rules, and the U.S. Supplement...
Automatic Classification Using Supervised Learning in a Medical Document Filtering Application.
ERIC Educational Resources Information Center
Mostafa, J.; Lam, W.
2000-01-01
Presents a multilevel model of the information filtering process that permits document classification. Evaluates a document classification approach based on a supervised learning algorithm, measures the accuracy of the algorithm in a neural network that was trained to classify medical documents on cell biology, and discusses filtering…
Comparison of Low-Thrust Control Laws for Application in Planetocentric Space
NASA Technical Reports Server (NTRS)
Falck, Robert D.; Sjauw, Waldy K.; Smith, David A.
2014-01-01
Recent interest at NASA for the application of solar electric propulsion for the transfer of significant payloads in cislunar space has led to the development of high-fidelity simulations of such missions. With such transfers involving transfer times on the order of months, simulation time can be significant. In the past, the examination of such missions typically began with the use of lower-fidelity trajectory optimization tools such as SEPSPOT to develop and tune guidance laws which delivered optimal or near- optimal trajectories, where optimal is generally defined as minimizing propellant expenditure or time of flight. The transfer of these solutions to a high-fidelity simulation is typically an iterative process whereby the initial solution may nearly, but not precisely, meet mission objectives. Further tuning of the guidance algorithm is typically necessary when accounting for high-fidelity perturbations such as those due to more detailed gravity models, secondary-body effects, solar radiation pressure, etc. While trajectory optimization is a useful method for determining optimal performance metrics, algorithms which deliver nearly optimal performance with minimal tuning are an attractive alternative.
Feedback laws for fuel minimization for transport aircraft
NASA Technical Reports Server (NTRS)
Price, D. B.; Gracey, C.
1984-01-01
The Theoretical Mechanics Branch has as one of its long-range goals to work toward solving real-time trajectory optimization problems on board an aircraft. This is a generic problem that has application to all aspects of aviation from general aviation through commercial to military. Overall interest is in the generic problem, but specific problems to achieve concrete results are examined. The problem is to develop control laws that generate approximately optimal trajectories with respect to some criteria such as minimum time, minimum fuel, or some combination of the two. These laws must be simple enough to be implemented on a computer that is flown on board an aircraft, which implies a major simplification from the two point boundary value problem generated by a standard trajectory optimization problem. In addition, the control laws allow for changes in end conditions during the flight, and changes in weather along a planned flight path. Therefore, a feedback control law that generates commands based on the current state rather than a precomputed open-loop control law is desired. This requirement, along with the need for order reduction, argues for the application of singular perturbation techniques.
Eliseyev, Andrey; Aksenova, Tetiana
2016-01-01
In the current paper the decoding algorithms for motor-related BCI systems for continuous upper limb trajectory prediction are considered. Two methods for the smooth prediction, namely Sobolev and Polynomial Penalized Multi-Way Partial Least Squares (PLS) regressions, are proposed. The methods are compared to the Multi-Way Partial Least Squares and Kalman Filter approaches. The comparison demonstrated that the proposed methods combined the prediction accuracy of the algorithms of the PLS family and trajectory smoothness of the Kalman Filter. In addition, the prediction delay is significantly lower for the proposed algorithms than for the Kalman Filter approach. The proposed methods could be applied in a wide range of applications beyond neuroscience. PMID:27196417
Stilwell, Daniel J; Bishop, Bradley E; Sylvester, Caleb A
2005-08-01
An approach to real-time trajectory generation for platoons of autonomous vehicles is developed from well-known control techniques for redundant robotic manipulators. The partially decentralized structure of this approach permits each vehicle to independently compute its trajectory in real-time using only locally generated information and low-bandwidth feedback generated by a system exogenous to the platoon. Our work is motivated by applications for which communications bandwidth is severely limited, such for platoons of autonomous underwater vehicles. The communication requirements for our trajectory generation approach are independent of the number of vehicles in the platoon, enabling platoons composed of a large number of vehicles to be coordinated despite limited communication bandwidth.
Quasi-Airy beams along tunable propagation trajectories and directions.
Qian, Yixian; Zhang, Site
2016-05-02
We present a theoretical and experimental exhibit that accelerates quasi-Airy beams propagating along arbitrarily appointed parabolic trajectories and directions in free space. We also demonstrate that such quasi-Airy beams can be generated by a tunable phase pattern, where two disturbance factors are introduced. The topological structures of quasi-Airy beams are readily manipulated with tunable phase patterns. Quasi-Airy beams still possess the characteristics of non-diffraction, self-healing to some extent, although they are not the solutions for paraxial wave equation. The experiments show the results are consistent with theoretical predictions. It is believed that the property of propagation along arbitrarily desired parabolic trajectories will provide a broad application in trapping atom and living cell manipulation.
76 FR 47531 - Approval of Classification Societies
Federal Register 2010, 2011, 2012, 2013, 2014
2011-08-05
... proposed rulemaking (NPRM) proposing application procedures and performance standards that classification... exempt from Coast Guard approval prior to working in the United States. Because [[Page 47532
Barbés, Benigno; Azcona, Juan Diego; Prieto, Elena; de Foronda, José Manuel; García, Marina; Burguete, Javier
2015-09-08
A simple and independent system to detect and measure the position of a number of points in space was devised and implemented. Its application aimed to detect patient motion during radiotherapy treatments, alert of out-of-tolerances motion, and record the trajectories for subsequent studies. The system obtains the 3D position of points in space, through its projections in 2D images recorded by two cameras. It tracks black dots on a white sticker placed on the surface of the moving object. The system was tested with linear displacements of a phantom, circular trajectories of a rotating disk, oscillations of an in-house phantom, and oscillations of a 4D phantom. It was also used to track 461 trajectories of points on the surface of patients during their radiotherapy treatments. Trajectories of several points were reproduced with accuracy better than 0.3 mm in the three spatial directions. The system was able to follow periodic motion with amplitudes lower than 0.5 mm, to follow trajectories of rotating points at speeds up to 11.5 cm/s, and to track accurately the motion of a respiratory phantom. The technique has been used to track the motion of patients during radiotherapy and to analyze that motion. The method is flexible. Its installation and calibration are simple and quick. It is easy to use and can be implemented at a very affordable price. Data collection does not involve any discomfort to the patient and does not delay the treatment, so the system can be used routinely in all treatments. It has an accuracy similar to that of other, more sophisticated, commercially available systems. It is suitable to implement a gating system or any other application requiring motion detection, such as 4D CT, MRI or PET.
Spectral CT of the extremities with a silicon strip photon counting detector
NASA Astrophysics Data System (ADS)
Sisniega, A.; Zbijewski, W.; Stayman, J. W.; Xu, J.; Taguchi, K.; Siewerdsen, J. H.
2015-03-01
Purpose: Photon counting x-ray detectors (PCXDs) are an important emerging technology for spectral imaging and material differentiation with numerous potential applications in diagnostic imaging. We report development of a Si-strip PCXD system originally developed for mammography with potential application to spectral CT of musculoskeletal extremities, including challenges associated with sparse sampling, spectral calibration, and optimization for higher energy x-ray beams. Methods: A bench-top CT system was developed incorporating a Si-strip PCXD, fixed anode x-ray source, and rotational and translational motions to execute complex acquisition trajectories. Trajectories involving rotation and translation combined with iterative reconstruction were investigated, including single and multiple axial scans and longitudinal helical scans. The system was calibrated to provide accurate spectral separation in dual-energy three-material decomposition of soft-tissue, bone, and iodine. Image quality and decomposition accuracy were assessed in experiments using a phantom with pairs of bone and iodine inserts (3, 5, 15 and 20 mm) and an anthropomorphic wrist. Results: The designed trajectories improved the sampling distribution from 56% minimum sampling of voxels to 75%. Use of iterative reconstruction (viz., penalized likelihood with edge preserving regularization) in combination with such trajectories resulted in a very low level of artifacts in images of the wrist. For large bone or iodine inserts (>5 mm diameter), the error in the estimated material concentration was <16% for (50 mg/mL) bone and <8% for (5 mg/mL) iodine with strong regularization. For smaller inserts, errors of 20-40% were observed and motivate improved methods for spectral calibration and optimization of the edge-preserving regularizer. Conclusion: Use of PCXDs for three-material decomposition in joint imaging proved feasible through a combination of rotation-translation acquisition trajectories and iterative reconstruction with optimized regularization.
2014-09-30
This ONR grant promotes the development and application of advanced machine learning techniques for detection and classification of marine mammal...sounds. The objective is to engage a broad community of data scientists in the development and application of advanced machine learning techniques for detection and classification of marine mammal sounds.
MURI: Optimal Quantum Dynamic Discrimination of Chemical and Biological Agents
2008-06-12
multiparameter) Hilbert space for enhanced detection and classification: an application of receiver operating curve statistics to laser-based mass...Adaptive reshaping of objects in (multiparameter) Hilbert space for enhanced detection and classification: an application of receiver operating curve...Doctoral Associate Muhannad Zamari, Graduate Student Ilya Greenberg , Computer Consultant Getahun Menkir, Graduate Student Lalinda Palliyaguru, Graduate
Wauters, Lauri D J; Miguel-Moragas, Joan San; Mommaerts, Maurice Y
2015-11-01
To gain insight into the methodology of different computer-aided design-computer-aided manufacturing (CAD-CAM) applications for the reconstruction of cranio-maxillo-facial (CMF) defects. We reviewed and analyzed the available literature pertaining to CAD-CAM for use in CMF reconstruction. We proposed a classification system of the techniques of implant and cutting, drilling, and/or guiding template design and manufacturing. The system consisted of 4 classes (I-IV). These classes combine techniques used for both the implant and template to most accurately describe the methodology used. Our classification system can be widely applied. It should facilitate communication and immediate understanding of the methodology of CAD-CAM applications for the reconstruction of CMF defects.
Leveraging natural dynamical structures to explore multi-body systems
NASA Astrophysics Data System (ADS)
Bosanac, Natasha
Multi-body systems have become the target of an increasing number of mission concepts and observations, supplying further information about the composition, origin and dynamical environment of bodies within the solar system and beyond. In many of these scenarios, identification and characterization of the particular solutions that exist in a circular restricted three-body model is valuable. This insight into the underlying natural dynamical structures is achieved via the application of dynamical systems techniques. One application of such analysis is trajectory design for CubeSats, which are intended to explore cislunar space and other planetary systems. These increasingly complex mission objectives necessitate innovative trajectory design strategies for spacecraft within our solar system, as well as the capability for rapid and well-informed redesign. Accordingly, a trajectory design framework is constructed using dynamical systems techniques and demonstrated for the Lunar IceCube mission. An additional application explored in this investigation involves the motion of an exoplanet near a binary star system. Due to the strong gravitational field near a binary star, physicists have previously leveraged these systems as testbeds for examining the validity of gravitational and relativistic theories. In this investigation, a preliminary analysis into the effect of an additional three-body interaction on the dynamical environment near a large mass ratio binary system is conducted. As demonstrated through both of these sample applications, identification and characterization of the natural particular solutions that exist within a multi-body system supports a well-informed and guided analysis.
Results of prototype software development for automation of shuttle proximity operations
NASA Technical Reports Server (NTRS)
Hiers, Hal; Olszweski, Oscar
1991-01-01
The effort involves demonstration of expert system technology application to Shuttle rendezvous operations in a high-fidelity, real-time simulation environment. The JSC Systems Engineering Simulator (SES) served as the test bed for the demonstration. Rendezvous applications were focused on crew procedures and monitoring of sensor health and trajectory status. Proximity operations applications were focused on monitoring, crew advisory, and control of the approach trajectory. Guidance, Navigation, and Control areas of emphasis included the approach, transition and stationkeeping guidance, and laser docking sensor navigation. Operator interface displays for monitor and control functions were developed. A rule-based expert system was developed to manage the relative navigation system/sensors for nominal operations and simple failure contingencies. Testing resulted in the following findings; (1) the developed guidance is applicable for operations with LVLH stabilized targets; (2) closing rates less than 0.05 feet per second are difficult to maintain due to the Shuttle translational/rotational cross-coupling; (3) automated operations result in reduced propellant consumption and plume impingement effects on the target as compared to manual operations; and (4) braking gates are beneficial for trajectory management. A versatile guidance design was demonstrated. An accurate proximity operations sensor/navigation system to provide relative attitude information within 30 feet is required and redesign of the existing Shuttle digital autopilot should be considered to reduce the cross-coupling effects. This activity has demonstrated the feasibility of automated Shuttle proximity operations with the Space Station Freedom. Indications are that berthing operations as well as docking can be supported.
NASA Technical Reports Server (NTRS)
Hein, C.; Meystel, A.
1994-01-01
There are many multi-stage optimization problems that are not easily solved through any known direct method when the stages are coupled. For instance, we have investigated the problem of planning a vehicle's control sequence to negotiate obstacles and reach a goal in minimum time. The vehicle has a known mass, and the controlling forces have finite limits. We have developed a technique that finds admissible control trajectories which tend to minimize the vehicle's transit time through the obstacle field. The immediate applications is that of a space robot which must rapidly traverse around 2-or-3 dimensional structures via application of a rotating thruster or non-rotating on-off for such vehicles is located at the Marshall Space Flight Center in Huntsville Alabama. However, it appears that the development method is applicable to a general set of optimization problems in which the cost function and the multi-dimensional multi-state system can be any nonlinear functions, which are continuous in the operating regions. Other applications included the planning of optimal navigation pathways through a transversability graph; the planning of control input for under-water maneuvering vehicles which have complex control state-space relationships; the planning of control sequences for milling and manufacturing robots; the planning of control and trajectories for automated delivery vehicles; and the optimization and athletic training in slalom sports.
SPIRAL-SPRITE: a rapid single point MRI technique for application to porous media.
Szomolanyi, P; Goodyear, D; Balcom, B; Matheson, D
2001-01-01
This study presents the application of a new, rapid, single point MRI technique which samples k space with spiral trajectories. The general principles of the technique are outlined along with application to porous concrete samples, solid pharmaceutical tablets and gas phase imaging. Each sample was chosen to highlight specific features of the method.
Santos, Tatiana B; Lana, Milene S; Santos, Allan E M; Silveira, Larissa R C
2017-01-01
Many authors have been proposed several correlation equations between geomechanical classifications and strength parameters. However, these correlation equations have been based in rock masses with different characteristics when compared to Brazilian rock masses. This paper aims to study the applicability of the geomechanical classifications to obtain strength parameters of three Brazilian rock masses. Four classification systems have been used; the Rock Mass Rating (RMR), the Rock Mass Quality (Q), the Geological Strength Index (GSI) and the Rock Mass Index (RMi). A strong rock mass and two soft rock masses with different degrees of weathering located in the cities of Ouro Preto and Mariana, Brazil; were selected for the study. Correlation equations were used to estimate the strength properties of these rock masses. However, such correlations do not always provide compatible results with the rock mass behavior. For the calibration of the strength values obtained through the use of classification systems, stability analyses of failures in these rock masses have been done. After calibration of these parameters, the applicability of the various correlation equations found in the literature have been discussed. According to the results presented in this paper, some of these equations are not suitable for the studied rock masses.
Pirooznia, Mehdi; Deng, Youping
2006-12-12
Graphical user interface (GUI) software promotes novelty by allowing users to extend the functionality. SVM Classifier is a cross-platform graphical application that handles very large datasets well. The purpose of this study is to create a GUI application that allows SVM users to perform SVM training, classification and prediction. The GUI provides user-friendly access to state-of-the-art SVM methods embodied in the LIBSVM implementation of Support Vector Machine. We implemented the java interface using standard swing libraries. We used a sample data from a breast cancer study for testing classification accuracy. We achieved 100% accuracy in classification among the BRCA1-BRCA2 samples with RBF kernel of SVM. We have developed a java GUI application that allows SVM users to perform SVM training, classification and prediction. We have demonstrated that support vector machines can accurately classify genes into functional categories based upon expression data from DNA microarray hybridization experiments. Among the different kernel functions that we examined, the SVM that uses a radial basis kernel function provides the best performance. The SVM Classifier is available at http://mfgn.usm.edu/ebl/svm/.
Robust feature detection and local classification for surfaces based on moment analysis.
Clarenz, Ulrich; Rumpf, Martin; Telea, Alexandru
2004-01-01
The stable local classification of discrete surfaces with respect to features such as edges and corners or concave and convex regions, respectively, is as quite difficult as well as indispensable for many surface processing applications. Usually, the feature detection is done via a local curvature analysis. If concerned with large triangular and irregular grids, e.g., generated via a marching cube algorithm, the detectors are tedious to treat and a robust classification is hard to achieve. Here, a local classification method on surfaces is presented which avoids the evaluation of discretized curvature quantities. Moreover, it provides an indicator for smoothness of a given discrete surface and comes together with a built-in multiscale. The proposed classification tool is based on local zero and first moments on the discrete surface. The corresponding integral quantities are stable to compute and they give less noisy results compared to discrete curvature quantities. The stencil width for the integration of the moments turns out to be the scale parameter. Prospective surface processing applications are the segmentation on surfaces, surface comparison, and matching and surface modeling. Here, a method for feature preserving fairing of surfaces is discussed to underline the applicability of the presented approach.
NASA Astrophysics Data System (ADS)
Raziff, Abdul Rafiez Abdul; Sulaiman, Md Nasir; Mustapha, Norwati; Perumal, Thinagaran
2017-10-01
Gait recognition is widely used in many applications. In the application of the gait identification especially in people, the number of classes (people) is many which may comprise to more than 20. Due to the large amount of classes, the usage of single classification mapping (direct classification) may not be suitable as most of the existing algorithms are mostly designed for the binary classification. Furthermore, having many classes in a dataset may result in the possibility of having a high degree of overlapped class boundary. This paper discusses the application of multiclass classifier mappings such as one-vs-all (OvA), one-vs-one (OvO) and random correction code (RCC) on handheld based smartphone gait signal for person identification. The results is then compared with a single J48 decision tree for benchmark. From the result, it can be said that using multiclass classification mapping method thus partially improved the overall accuracy especially on OvO and RCC with width factor more than 4. For OvA, the accuracy result is worse than a single J48 due to a high number of classes.
Particle trajectory computer program for icing analysis of axisymmetric bodies
NASA Technical Reports Server (NTRS)
Frost, Walter; Chang, Ho-Pen; Kimble, Kenneth R.
1982-01-01
General aviation aircraft and helicopters exposed to an icing environment can accumulate ice resulting in a sharp increase in drag and reduction of maximum lift causing hazardous flight conditions. NASA Lewis Research Center (LeRC) is conducting a program to examine, with the aid of high-speed computer facilities, how the trajectories of particles contribute to the ice accumulation on airfoils and engine inlets. This study, as part of the NASA/LeRC research program, develops a computer program for the calculation of icing particle trajectories and impingement limits relative to axisymmetric bodies in the leeward-windward symmetry plane. The methodology employed in the current particle trajectory calculation is to integrate the governing equations of particle motion in a flow field computed by the Douglas axisymmetric potential flow program. The three-degrees-of-freedom (horizontal, vertical, and pitch) motion of the particle is considered. The particle is assumed to be acted upon by aerodynamic lift and drag forces, gravitational forces, and for nonspherical particles, aerodynamic moments. The particle momentum equation is integrated to determine the particle trajectory. Derivation of the governing equations and the method of their solution are described in Section 2.0. General features, as well as input/output instructions for the particle trajectory computer program, are described in Section 3.0. The details of the computer program are described in Section 4.0. Examples of the calculation of particle trajectories demonstrating application of the trajectory program to given axisymmetric inlet test cases are presented in Section 5.0. For the examples presented, the particles are treated as spherical water droplets. In Section 6.0, limitations of the program relative to excessive computer time and recommendations in this regard are discussed.
Anderson, Emma L; Tilling, Kate; Fraser, Abigail; Macdonald-Wallis, Corrie; Emmett, Pauline; Cribb, Victoria; Northstone, Kate; Lawlor, Debbie A; Howe, Laura D
2013-07-01
Methods for the assessment of changes in dietary intake across the life course are underdeveloped. We demonstrate the use of linear-spline multilevel models to summarize energy-intake trajectories through childhood and adolescence and their application as exposures, outcomes, or mediators. The Avon Longitudinal Study of Parents and Children assessed children's dietary intake several times between ages 3 and 13 years, using both food frequency questionnaires (FFQs) and 3-day food diaries. We estimated energy-intake trajectories for 12,032 children using linear-spline multilevel models. We then assessed the associations of these trajectories with maternal body mass index (BMI), and later offspring BMI, and also their role in mediating the relation between maternal and offspring BMIs. Models estimated average and individual energy intake at 3 years, and linear changes in energy intake from age 3 to 7 years and from age 7 to 13 years. By including the exposure (in this example, maternal BMI) in the multilevel model, we were able to estimate the average energy-intake trajectories across levels of the exposure. When energy-intake trajectories are the exposure for a later outcome (in this case offspring BMI) or a mediator (between maternal and offspring BMI), results were similar, whether using a two-step process (exporting individual-level intercepts and slopes from multilevel models and using these in linear regression/path analysis), or a single-step process (multivariate multilevel models). Trajectories were similar when FFQs and food diaries were assessed either separately, or when combined into one model. Linear-spline multilevel models provide useful summaries of trajectories of dietary intake that can be used as an exposure, outcome, or mediator.
Feedback control for fuel-optimal descents using singular perturbation techniques
NASA Technical Reports Server (NTRS)
Price, D. B.
1984-01-01
In response to rising fuel costs and reduced profit margins for the airline companies, the optimization of the paths flown by transport aircraft has been considered. It was found that application of optimal control theory to the considered problem can result in savings in fuel, time, and direct operating costs. The best solution to the aircraft trajectory problem is an onboard real-time feedback control law. The present paper presents a technique which shows promise of becoming a part of a complete solution. The application of singular perturbation techniques to the problem is discussed, taking into account the benefits and some problems associated with them. A different technique for handling the descent part of a trajectory is also discussed.
Definition and Demonstration of a Methodology for Validating Aircraft Trajectory Predictors
NASA Technical Reports Server (NTRS)
Vivona, Robert A.; Paglione, Mike M.; Cate, Karen T.; Enea, Gabriele
2010-01-01
This paper presents a new methodology for validating an aircraft trajectory predictor, inspired by the lessons learned from a number of field trials, flight tests and simulation experiments for the development of trajectory-predictor-based automation. The methodology introduces new techniques and a new multi-staged approach to reduce the effort in identifying and resolving validation failures, avoiding the potentially large costs associated with failures during a single-stage, pass/fail approach. As a case study, the validation effort performed by the Federal Aviation Administration for its En Route Automation Modernization (ERAM) system is analyzed to illustrate the real-world applicability of this methodology. During this validation effort, ERAM initially failed to achieve six of its eight requirements associated with trajectory prediction and conflict probe. The ERAM validation issues have since been addressed, but to illustrate how the methodology could have benefited the FAA effort, additional techniques are presented that could have been used to resolve some of these issues. Using data from the ERAM validation effort, it is demonstrated that these new techniques could have identified trajectory prediction error sources that contributed to several of the unmet ERAM requirements.
[Study on the center-driven multiple degrees of freedom upper limb rehabilitation training robot].
Huang, Xiaohai; Yu, Hongliu; Wang, Jinchao; Dong, Qi; Zhang, Linling; Meng, Qiaoling; Li, Sujiao; Wang, Duojin
2018-03-01
With the aging of the society, the number of stroke patients has been increasing year by year. Compared with the traditional rehabilitation therapy, the application of upper limb rehabilitation robot has higher efficiency and better rehabilitation effect, and has become an important development direction in the field of rehabilitation. In view of the current development status and the deficiency of upper limb rehabilitation robot system, combined with the development trend of all kinds of products of the upper limb rehabilitation robot, this paper designed a center-driven upper limb rehabilitation training robot for cable transmission which can help the patients complete 6 degrees of freedom (3 are driven, 3 are underactuated) training. Combined the structure of robot with more joints rehabilitation training, the paper choosed a cubic polynomial trajectory planning method in the joint space planning to design two trajectories of eating and lifting arm. According to the trajectory equation, the movement trajectory of each joint of the robot was drawn in MATLAB. It laid a foundation for scientific and effective rehabilitation training. Finally, the experimental prototype is built, and the mechanical structure and design trajectories are verified.
Fuel-Conservation Guidance System for Powered-Lift Aircraft
NASA Technical Reports Server (NTRS)
Erzberger, Heinz; McLean, John D.
1981-01-01
A technique is described for the design of fuel-conservative guidance systems and is applied to a system that was flight tested on board NASA's sugmentor wing jet STOL research aircraft. An important operational feature of the system is its ability to rapidly synthesize fuel-efficient trajectories for a large set of initial aircraft positions, altitudes, and headings. This feature allows the aircraft to be flown efficiently under conditions of changing winds and air traffic control vectors. Rapid synthesis of fuel-efficient trajectories is accomplished in the airborne computer by fast-time trajectory integration using a simplified dynamic performance model of the aircraft. This technique also ensures optimum flap deployment and, for powered-lift STOL aircraft, optimum transition to low-speed flight. Also included in the design is accurate prediction of touchdown time for use in four-dimensional guidance applications. Flight test results have demonstrated that the automatically synthesized trajectories produce significant fuel savings relative to manually flown conventional approaches.