A Risk-Based Multi-Objective Optimization Concept for Early-Warning Monitoring Networks

NASA Astrophysics Data System (ADS)

Bode, F.; Loschko, M.; Nowak, W.

2014-12-01

Groundwater is a resource for drinking water and hence needs to be protected from contaminations. However, many well catchments include an inventory of known and unknown risk sources which cannot be eliminated, especially in urban regions. As matter of risk control, all these risk sources should be monitored. A one-to-one monitoring situation for each risk source would lead to a cost explosion and is even impossible for unknown risk sources. However, smart optimization concepts could help to find promising low-cost monitoring network designs.In this work we develop a concept to plan monitoring networks using multi-objective optimization. Our considered objectives are to maximize the probability of detecting all contaminations and the early warning time and to minimize the installation and operating costs of the monitoring network. A qualitative risk ranking is used to prioritize the known risk sources for monitoring. The unknown risk sources can neither be located nor ranked. Instead, we represent them by a virtual line of risk sources surrounding the production well.We classify risk sources into four different categories: severe, medium and tolerable for known risk sources and an extra category for the unknown ones. With that, early warning time and detection probability become individual objectives for each risk class. Thus, decision makers can identify monitoring networks which are valid for controlling the top risk sources, and evaluate the capabilities (or search for least-cost upgrade) to also cover moderate, tolerable and unknown risk sources. Monitoring networks which are valid for the remaining risk also cover all other risk sources but the early-warning time suffers.The data provided for the optimization algorithm are calculated in a preprocessing step by a flow and transport model. Uncertainties due to hydro(geo)logical phenomena are taken into account by Monte-Carlo simulations. To avoid numerical dispersion during the transport simulations we use the particle-tracking random walk method.

Adult Age Differences in Categorization and Multiple-Cue Judgment

ERIC Educational Resources Information Center

Mata, Rui; von Helversen, Bettina; Karlsson, Linnea; Cupper, Lutz

2012-01-01

We often need to infer unknown properties of objects from observable ones, just like detectives must infer guilt from observable clues and behavior. But how do inferential processes change with age? We examined young and older adults' reliance on rule-based and similarity-based processes in an inference task that can be considered either a…

Market-Based Coordination of Thermostatically Controlled Loads—Part II: Unknown Parameters and Case Studies

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

Li, Sen; Zhang, Wei; Lian, Jianming

This two-part paper considers the coordination of a population of Thermostatically Controlled Loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the bidding and market clearing strategy to motivate self-interested users to realize efficient energy allocation subject to a peak power constraint. The companion paper (Part I) formulates the problem and proposes a load coordination framework using the mechanism design approach. To address the unknown parameters, Part II of this paper presents a joint state and parameter estimation framework based on the expectation maximization algorithm. The overall framework is then validated using real-world weather data andmore » price data, and is compared with other approaches in terms of aggregated power response. Simulation results indicate that our coordination framework can effectively improve the efficiency of the power grid operations and reduce power congestion at key times.« less

Market-Based Coordination of Thermostatically Controlled Loads—Part I: A Mechanism Design Formulation

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

Li, Sen; Zhang, Wei; Lian, Jianming

This paper focuses on the coordination of a population of Thermostatically Controlled Loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the bidding and market clearing strategy to motivate self-interested users to realize efficient energy allocation subject to a peak power constraint. Using the mechanism design approach, we propose a market-based coordination framework, which can effectively incorporate heterogeneous load dynamics, systematically deal with user preferences, account for the unknown load model parameters, and enable the real-world implementation with limited communication resources. This paper is divided into two parts. Part I presents a mathematical formulation of themore » problem and develops a coordination framework using the mechanism design approach. Part II presents a learning scheme to account for the unknown load model parameters, and evaluates the proposed framework through realistic simulations.« less

Hospital based ethics, current situation in France: between “Espaces” and committees

PubMed Central

Guerrier, M

2006-01-01

Unlike research ethics committees, which were created in 1988, the number of functioning hospital based ethical organisations in France, such as clinical ethics committees, is unknown. The objectives of such structures are diverse. A recent law created regional ethical forums, the objectives of which are education, debate, and research in relation to healthcare ethics. This paper discusses the current situation in France and the possible evolution and conflicts induced by this law. The creation of official healthcare ethics structures raises several issues. PMID:16943328

Fast grasping of unknown objects using cylinder searching on a single point cloud

NASA Astrophysics Data System (ADS)

Lei, Qujiang; Wisse, Martijn

2017-03-01

Grasping of unknown objects with neither appearance data nor object models given in advance is very important for robots that work in an unfamiliar environment. The goal of this paper is to quickly synthesize an executable grasp for one unknown object by using cylinder searching on a single point cloud. Specifically, a 3D camera is first used to obtain a partial point cloud of the target unknown object. An original method is then employed to do post treatment on the partial point cloud to minimize the uncertainty which may lead to grasp failure. In order to accelerate the grasp searching, surface normal of the target object is then used to constrain the synthetization of the cylinder grasp candidates. Operability analysis is then used to select out all executable grasp candidates followed by force balance optimization to choose the most reliable grasp as the final grasp execution. In order to verify the effectiveness of our algorithm, Simulations on a Universal Robot arm UR5 and an under-actuated Lacquey Fetch gripper are used to examine the performance of this algorithm, and successful results are obtained.

Point Pairing Method Based on the Principle of Material Frame Indifference for the Characterization of Unknown Space Objects using Non-Resolved Photometry Data

DTIC Science & Technology

2013-09-01

provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB...the satellite. The material constitutive laws of interest are the bidirectional reflectance distribution functions ( BRDF ) for diffuse and specular...solar panel can be related to each other using the BRDF definition. This creates a set of three independent equations and three unknowns, which can be

DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field.

PubMed

Christiansen, Peter; Nielsen, Lars N; Steen, Kim A; Jørgensen, Rasmus N; Karstoft, Henrik

2016-11-11

Convolutional neural network (CNN)-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel classification (semantic segmentation) algorithms are trained for detecting and classifying a predefined set of object types. These algorithms have difficulties in detecting distant and heavily occluded objects and are, by definition, not capable of detecting unknown object types or unusual scenarios. The visual characteristics of an agriculture field is homogeneous, and obstacles, like people, animals and other obstacles, occur rarely and are of distinct appearance compared to the field. This paper introduces DeepAnomaly, an algorithm combining deep learning and anomaly detection to exploit the homogenous characteristics of a field to perform anomaly detection. We demonstrate DeepAnomaly as a fast state-of-the-art detector for obstacles that are distant, heavily occluded and unknown. DeepAnomaly is compared to state-of-the-art obstacle detectors including "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks" (RCNN). In a human detector test case, we demonstrate that DeepAnomaly detects humans at longer ranges (45-90 m) than RCNN. RCNN has a similar performance at a short range (0-30 m). However, DeepAnomaly has much fewer model parameters and (182 ms/25 ms =) a 7.28-times faster processing time per image. Unlike most CNN-based methods, the high accuracy, the low computation time and the low memory footprint make it suitable for a real-time system running on a embedded GPU (Graphics Processing Unit).

DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field

PubMed Central

Christiansen, Peter; Nielsen, Lars N.; Steen, Kim A.; Jørgensen, Rasmus N.; Karstoft, Henrik

2016-01-01

Convolutional neural network (CNN)-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel classification (semantic segmentation) algorithms are trained for detecting and classifying a predefined set of object types. These algorithms have difficulties in detecting distant and heavily occluded objects and are, by definition, not capable of detecting unknown object types or unusual scenarios. The visual characteristics of an agriculture field is homogeneous, and obstacles, like people, animals and other obstacles, occur rarely and are of distinct appearance compared to the field. This paper introduces DeepAnomaly, an algorithm combining deep learning and anomaly detection to exploit the homogenous characteristics of a field to perform anomaly detection. We demonstrate DeepAnomaly as a fast state-of-the-art detector for obstacles that are distant, heavily occluded and unknown. DeepAnomaly is compared to state-of-the-art obstacle detectors including “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks” (RCNN). In a human detector test case, we demonstrate that DeepAnomaly detects humans at longer ranges (45–90 m) than RCNN. RCNN has a similar performance at a short range (0–30 m). However, DeepAnomaly has much fewer model parameters and (182 ms/25 ms =) a 7.28-times faster processing time per image. Unlike most CNN-based methods, the high accuracy, the low computation time and the low memory footprint make it suitable for a real-time system running on a embedded GPU (Graphics Processing Unit). PMID:27845717

An approach to the analysis of SDSS spectroscopic outliers based on self-organizing maps. Designing the outlier analysis software package for the next Gaia survey

NASA Astrophysics Data System (ADS)

Fustes, D.; Manteiga, M.; Dafonte, C.; Arcay, B.; Ulla, A.; Smith, K.; Borrachero, R.; Sordo, R.

2013-11-01

Aims: A new method applied to the segmentation and further analysis of the outliers resulting from the classification of astronomical objects in large databases is discussed. The method is being used in the framework of the Gaia satellite Data Processing and Analysis Consortium (DPAC) activities to prepare automated software tools that will be used to derive basic astrophysical information that is to be included in final Gaia archive. Methods: Our algorithm has been tested by means of simulated Gaia spectrophotometry, which is based on SDSS observations and theoretical spectral libraries covering a wide sample of astronomical objects. Self-organizing maps networks are used to organize the information in clusters of objects, as homogeneously as possible according to their spectral energy distributions, and to project them onto a 2D grid where the data structure can be visualized. Results: We demonstrate the usefulness of the method by analyzing the spectra that were rejected by the SDSS spectroscopic classification pipeline and thus classified as "UNKNOWN". First, our method can help distinguish between astrophysical objects and instrumental artifacts. Additionally, the application of our algorithm to SDSS objects of unknown nature has allowed us to identify classes of objects with similar astrophysical natures. In addition, the method allows for the potential discovery of hundreds of new objects, such as white dwarfs and quasars. Therefore, the proposed method is shown to be very promising for data exploration and knowledge discovery in very large astronomical databases, such as the archive from the upcoming Gaia mission.

On position/force tracking control problem of cooperative robot manipulators using adaptive fuzzy backstepping approach.

PubMed

Baigzadehnoe, Barmak; Rahmani, Zahra; Khosravi, Alireza; Rezaie, Behrooz

2017-09-01

In this paper, the position and force tracking control problem of cooperative robot manipulator system handling a common rigid object with unknown dynamical models and unknown external disturbances is investigated. The universal approximation properties of fuzzy logic systems are employed to estimate the unknown system dynamics. On the other hand, by defining new state variables based on the integral and differential of position and orientation errors of the grasped object, the error system of coordinated robot manipulators is constructed. Subsequently by defining the appropriate change of coordinates and using the backstepping design strategy, an adaptive fuzzy backstepping position tracking control scheme is proposed for multi-robot manipulator systems. By utilizing the properties of internal forces, extra terms are also added to the control signals to consider the force tracking problem. Moreover, it is shown that the proposed adaptive fuzzy backstepping position/force control approach ensures all the signals of the closed loop system uniformly ultimately bounded and tracking errors of both positions and forces can converge to small desired values by proper selection of the design parameters. Finally, the theoretic achievements are tested on the two three-link planar robot manipulators cooperatively handling a common object to illustrate the effectiveness of the proposed approach. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Adherence index based on the AHA 2006 diet and lifestyle recommendations is associated with select cardiovascular disease risk factors in older Puerto Ricans

USDA-ARS?s Scientific Manuscript database

Background: The effect of adherence to the American Heart Association (AHA) 2006 Diet and Lifestyle recommendations is unknown. Objective: To develop a unique diet and lifestyle score based on the AHA 2006 Diet and Lifestyle (AHA DL) recommendations. We evaluated this score in relation to available ...

The Information Available to a Moving Observer on Shape with Unknown, Isotropic BRDFs.

PubMed

Chandraker, Manmohan

2016-07-01

Psychophysical studies show motion cues inform about shape even with unknown reflectance. Recent works in computer vision have considered shape recovery for an object of unknown BRDF using light source or object motions. This paper proposes a theory that addresses the remaining problem of determining shape from the (small or differential) motion of the camera, for unknown isotropic BRDFs. Our theory derives a differential stereo relation that relates camera motion to surface depth, which generalizes traditional Lambertian assumptions. Under orthographic projection, we show differential stereo may not determine shape for general BRDFs, but suffices to yield an invariant for several restricted (still unknown) BRDFs exhibited by common materials. For the perspective case, we show that differential stereo yields the surface depth for unknown isotropic BRDF and unknown directional lighting, while additional constraints are obtained with restrictions on the BRDF or lighting. The limits imposed by our theory are intrinsic to the shape recovery problem and independent of choice of reconstruction method. We also illustrate trends shared by theories on shape from differential motion of light source, object or camera, to relate the hardness of surface reconstruction to the complexity of imaging setup.

A dynamical approach in exploring the unknown mass in the Solar system using pulsar timing arrays

NASA Astrophysics Data System (ADS)

Guo, Y. J.; Lee, K. J.; Caballero, R. N.

2018-04-01

The error in the Solar system ephemeris will lead to dipolar correlations in the residuals of pulsar timing array for widely separated pulsars. In this paper, we utilize such correlated signals, and construct a Bayesian data-analysis framework to detect the unknown mass in the Solar system and to measure the orbital parameters. The algorithm is designed to calculate the waveform of the induced pulsar-timing residuals due to the unmodelled objects following the Keplerian orbits in the Solar system. The algorithm incorporates a Bayesian-analysis suit used to simultaneously analyse the pulsar-timing data of multiple pulsars to search for coherent waveforms, evaluate the detection significance of unknown objects, and to measure their parameters. When the object is not detectable, our algorithm can be used to place upper limits on the mass. The algorithm is verified using simulated data sets, and cross-checked with analytical calculations. We also investigate the capability of future pulsar-timing-array experiments in detecting the unknown objects. We expect that the future pulsar-timing data can limit the unknown massive objects in the Solar system to be lighter than 10-11-10-12 M⊙, or measure the mass of Jovian system to a fractional precision of 10-8-10-9.

Effects of memory colour on colour constancy for unknown coloured objects

PubMed Central

Granzier, Jeroen J M; Gegenfurtner, Karl R

2012-01-01

The perception of an object's colour remains constant despite large variations in the chromaticity of the illumination—colour constancy. Hering suggested that memory colours, the typical colours of objects, could help in estimating the illuminant's colour and therefore be an important factor in establishing colour constancy. Here we test whether the presence of objects with diagnostical colours (fruits, vegetables, etc) within a scene influence colour constancy for unknown coloured objects in the scene. Subjects matched one of four Munsell papers placed in a scene illuminated under either a reddish or a greenish lamp with the Munsell book of colour illuminated by a neutral lamp. The Munsell papers were embedded in four different scenes—one scene containing diagnostically coloured objects, one scene containing incongruent coloured objects, a third scene with geometrical objects of the same colour as the diagnostically coloured objects, and one scene containing non-diagnostically coloured objects (eg, a yellow coffee mug). All objects were placed against a black background. Colour constancy was on average significantly higher for the scene containing the diagnostically coloured objects compared with the other scenes tested. We conclude that the colours of familiar objects help in obtaining colour constancy for unknown objects. PMID:23145282

Effects of memory colour on colour constancy for unknown coloured objects.

PubMed

Granzier, Jeroen J M; Gegenfurtner, Karl R

2012-01-01

The perception of an object's colour remains constant despite large variations in the chromaticity of the illumination-colour constancy. Hering suggested that memory colours, the typical colours of objects, could help in estimating the illuminant's colour and therefore be an important factor in establishing colour constancy. Here we test whether the presence of objects with diagnostical colours (fruits, vegetables, etc) within a scene influence colour constancy for unknown coloured objects in the scene. Subjects matched one of four Munsell papers placed in a scene illuminated under either a reddish or a greenish lamp with the Munsell book of colour illuminated by a neutral lamp. The Munsell papers were embedded in four different scenes-one scene containing diagnostically coloured objects, one scene containing incongruent coloured objects, a third scene with geometrical objects of the same colour as the diagnostically coloured objects, and one scene containing non-diagnostically coloured objects (eg, a yellow coffee mug). All objects were placed against a black background. Colour constancy was on average significantly higher for the scene containing the diagnostically coloured objects compared with the other scenes tested. We conclude that the colours of familiar objects help in obtaining colour constancy for unknown objects.

Saliency-Guided Detection of Unknown Objects in RGB-D Indoor Scenes.

PubMed

Bao, Jiatong; Jia, Yunyi; Cheng, Yu; Xi, Ning

2015-08-27

This paper studies the problem of detecting unknown objects within indoor environments in an active and natural manner. The visual saliency scheme utilizing both color and depth cues is proposed to arouse the interests of the machine system for detecting unknown objects at salient positions in a 3D scene. The 3D points at the salient positions are selected as seed points for generating object hypotheses using the 3D shape. We perform multi-class labeling on a Markov random field (MRF) over the voxels of the 3D scene, combining cues from object hypotheses and 3D shape. The results from MRF are further refined by merging the labeled objects, which are spatially connected and have high correlation between color histograms. Quantitative and qualitative evaluations on two benchmark RGB-D datasets illustrate the advantages of the proposed method. The experiments of object detection and manipulation performed on a mobile manipulator validate its effectiveness and practicability in robotic applications.

Saliency-Guided Detection of Unknown Objects in RGB-D Indoor Scenes

PubMed Central

Bao, Jiatong; Jia, Yunyi; Cheng, Yu; Xi, Ning

2015-01-01

This paper studies the problem of detecting unknown objects within indoor environments in an active and natural manner. The visual saliency scheme utilizing both color and depth cues is proposed to arouse the interests of the machine system for detecting unknown objects at salient positions in a 3D scene. The 3D points at the salient positions are selected as seed points for generating object hypotheses using the 3D shape. We perform multi-class labeling on a Markov random field (MRF) over the voxels of the 3D scene, combining cues from object hypotheses and 3D shape. The results from MRF are further refined by merging the labeled objects, which are spatially connected and have high correlation between color histograms. Quantitative and qualitative evaluations on two benchmark RGB-D datasets illustrate the advantages of the proposed method. The experiments of object detection and manipulation performed on a mobile manipulator validate its effectiveness and practicability in robotic applications. PMID:26343656

Why Atens Enjoy Enhanced Accessibility for Human Space Flight

NASA Technical Reports Server (NTRS)

Barbee, Brent W.; Adamo, Daniel R.

2011-01-01

Near-Earth objects can be grouped into multiple orbit classifications, among them being the Aten group, whose members have orbits crossing Earth's with semi-major axes less than 1 astronomical unit. Atens comprise well under 10% of known near-Earth objects. This is in dramatic contrast to results from recent human space flight near-Earth object accessibility studies, where the most favorable known destinations are typically almost 50% Atens. Geocentric dynamics explain this enhanced Aten accessibility and lead to an understanding of where the most accessible near-Earth objects reside. Without a comprehensive space-based survey, however, highly accessible Atens will remain largely unknown.

Object-based modeling, identification, and labeling of medical images for content-based retrieval by querying on intervals of attribute values

NASA Astrophysics Data System (ADS)

Thies, Christian; Ostwald, Tamara; Fischer, Benedikt; Lehmann, Thomas M.

2005-04-01

The classification and measuring of objects in medical images is important in radiological diagnostics and education, especially when using large databases as knowledge resources, for instance a picture archiving and communication system (PACS). The main challenge is the modeling of medical knowledge and the diagnostic context to label the sought objects. This task is referred to as closing the semantic gap between low-level pixel information and high level application knowledge. This work describes an approach which allows labeling of a-priori unknown objects in an intuitive way. Our approach consists of four main components. At first an image is completely decomposed into all visually relevant partitions on different scales. This provides a hierarchical organized set of regions. Afterwards, for each of the obtained regions a set of descriptive features is computed. In this data structure objects are represented by regions with characteristic attributes. The actual object identification is the formulation of a query. It consists of attributes on which intervals are defined describing those regions that correspond to the sought objects. Since the objects are a-priori unknown, they are described by a medical expert by means of an intuitive graphical user interface (GUI). This GUI is the fourth component. It enables complex object definitions by browsing the data structure and examinating the attributes to formulate the query. The query is executed and if the sought objects have not been identified its parameterization is refined. By using this heuristic approach, object models for hand radiographs have been developed to extract bones from a single hand in different anatomical contexts. This demonstrates the applicability of the labeling concept. By using a rule for metacarpal bones on a series of 105 images, this type of bone could be retrieved with a precision of 0.53 % and a recall of 0.6%.

Adaptive Actor-Critic Design-Based Integral Sliding-Mode Control for Partially Unknown Nonlinear Systems With Input Disturbances.

PubMed

Fan, Quan-Yong; Yang, Guang-Hong

2016-01-01

This paper is concerned with the problem of integral sliding-mode control for a class of nonlinear systems with input disturbances and unknown nonlinear terms through the adaptive actor-critic (AC) control method. The main objective is to design a sliding-mode control methodology based on the adaptive dynamic programming (ADP) method, so that the closed-loop system with time-varying disturbances is stable and the nearly optimal performance of the sliding-mode dynamics can be guaranteed. In the first step, a neural network (NN)-based observer and a disturbance observer are designed to approximate the unknown nonlinear terms and estimate the input disturbances, respectively. Based on the NN approximations and disturbance estimations, the discontinuous part of the sliding-mode control is constructed to eliminate the effect of the disturbances and attain the expected equivalent sliding-mode dynamics. Then, the ADP method with AC structure is presented to learn the optimal control for the sliding-mode dynamics online. Reconstructed tuning laws are developed to guarantee the stability of the sliding-mode dynamics and the convergence of the weights of critic and actor NNs. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.

Line width determination using a biomimetic fly eye vision system.

PubMed

Benson, John B; Wright, Cameron H G; Barrett, Steven F

2007-01-01

Developing a new vision system based on the vision of the common house fly, Musca domestica, has created many interesting design challenges. One of those problems is line width determination, which is the topic of this paper. It has been discovered that line width can be determined with a single sensor as long as either the sensor, or the object in question, has a constant, known velocity. This is an important first step for determining the width of any arbitrary object, with unknown velocity.

Family-Based Genome-Wide Association Scan of Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Mick, Eric; Todorov, Alexandre; Smalley, Susan; Hu, Xiaolan; Loo, Sandra; Todd, Richard D.; Biederman, Joseph; Byrne, Deirdre; Dechairo, Bryan; Guiney, Allan; McCracken, James; McGough, James; Nelson, Stanley F.; Reiersen, Angela M.; Wilens, Timothy E.; Wozniak, Janet; Neale, Benjamin M.; Faraone, Stephen V.

2010-01-01

Objective: Genes likely play a substantial role in the etiology of attention-deficit/hyperactivity disorder (ADHD). However, the genetic architecture of the disorder is unknown, and prior genome-wide association studies (GWAS) have not identified a genome-wide significant association. We have conducted a third, independent, multisite GWAS of…

The search for red AGN with 2MASS

NASA Technical Reports Server (NTRS)

Cutri, R. M.; Nelson, B. O.; Kirkpatrick, J. D.; Huchra, J. P.; Smith, P. S.

2001-01-01

We present the results of a simple, highly efficient 2MASS color-based survey that has already discovered 140 previously unknown red AGN and QSOs. These objects are near-infrared-bright and relatively nearby; the media redshift of the sample is z=0.25, and all but two have z<0.7.

Stereoscopic augmented reality with pseudo-realistic global illumination effects

NASA Astrophysics Data System (ADS)

de Sorbier, Francois; Saito, Hideo

2014-03-01

Recently, augmented reality has become very popular and has appeared in our daily life with gaming, guiding systems or mobile phone applications. However, inserting object in such a way their appearance seems natural is still an issue, especially in an unknown environment. This paper presents a framework that demonstrates the capabilities of Kinect for convincing augmented reality in an unknown environment. Rather than pre-computing a reconstruction of the scene like proposed by most of the previous method, we propose a dynamic capture of the scene that allows adapting to live changes of the environment. Our approach, based on the update of an environment map, can also detect the position of the light sources. Combining information from the environment map, the light sources and the camera tracking, we can display virtual objects using stereoscopic devices with global illumination effects such as diffuse and mirror reflections, refractions and shadows in real time.

Finite-time tracking control for multiple non-holonomic mobile robots based on visual servoing

NASA Astrophysics Data System (ADS)

Ou, Meiying; Li, Shihua; Wang, Chaoli

2013-12-01

This paper investigates finite-time tracking control problem of multiple non-holonomic mobile robots via visual servoing. It is assumed that the pinhole camera is fixed to the ceiling, and camera parameters are unknown. The desired reference trajectory is represented by a virtual leader whose states are available to only a subset of the followers, and the followers have only interaction. First, the camera-objective visual kinematic model is introduced by utilising the pinhole camera model for each mobile robot. Second, a unified tracking error system between camera-objective visual servoing model and desired reference trajectory is introduced. Third, based on the neighbour rule and by using finite-time control method, continuous distributed cooperative finite-time tracking control laws are designed for each mobile robot with unknown camera parameters, where the communication topology among the multiple mobile robots is assumed to be a directed graph. Rigorous proof shows that the group of mobile robots converges to the desired reference trajectory in finite time. Simulation example illustrates the effectiveness of our method.

Adherence index based on the American Heart Association 2006 diet and lifestyle recommendations: associations with cardiovascular disease risk factors in the Boston Puerto Rican health study

USDA-ARS?s Scientific Manuscript database

In 2006, the AHA released diet and lifestyle recommendations (AHA-DLR) for cardiovascular disease (CVD) risk reduction. The effect of adherence to these recommendations on CVD risk is unknown. Our objective was to develop a unique diet and lifestyle score based on the AHA-DLR and to evaluate this sc...

Structural damage identification using piezoelectric impedance measurement with sparse inverse analysis

NASA Astrophysics Data System (ADS)

Cao, Pei; Qi, Shuai; Tang, J.

2018-03-01

The impedance/admittance measurements of a piezoelectric transducer bonded to or embedded in a host structure can be used as damage indicator. When a credible model of the healthy structure, such as the finite element model, is available, using the impedance/admittance change information as input, it is possible to identify both the location and severity of damage. The inverse analysis, however, may be under-determined as the number of unknowns in high-frequency analysis is usually large while available input information is limited. The fundamental challenge thus is how to find a small set of solutions that cover the true damage scenario. In this research we cast the damage identification problem into a multi-objective optimization framework to tackle this challenge. With damage locations and severities as unknown variables, one of the objective functions is the difference between impedance-based model prediction in the parametric space and the actual measurements. Considering that damage occurrence generally affects only a small number of elements, we choose the sparsity of the unknown variables as another objective function, deliberately, the l 0 norm. Subsequently, a multi-objective Dividing RECTangles (DIRECT) algorithm is developed to facilitate the inverse analysis where the sparsity is further emphasized by sigmoid transformation. As a deterministic technique, this approach yields results that are repeatable and conclusive. In addition, only one algorithmic parameter, the number of function evaluations, is needed. Numerical and experimental case studies demonstrate that the proposed framework is capable of obtaining high-quality damage identification solutions with limited measurement information.

Global Learning Spectral Archive- A new Way to deal with Unknown Urban Spectra -

NASA Astrophysics Data System (ADS)

Jilge, M.; Heiden, U.; Habermeyer, M.; Jürgens, C.

2015-12-01

Rapid urbanization processes and the need of identifying urban materials demand urban planners and the remote sensing community since years. Urban planners cannot overcome the issue of up-to-date information of urban materials due to time-intensive fieldwork. Hyperspectral remote sensing can facilitate this issue by interpreting spectral signals to provide information of occurring materials. However, the complexity of urban areas and the occurrence of diverse urban materials vary due to regional and cultural aspects as well as the size of a city, which makes identification of surface materials a challenging analysis task. For the various surface material identification approaches, spectral libraries containing pure material spectra are commonly used, which are derived from field, laboratory or the hyperspectral image itself. One of the requirements for successful image analysis is that all spectrally different surface materials are represented by the library. Currently, a universal library, applicable in every urban area worldwide and taking each spectral variability into account, is and will not be existent. In this study, the issue of unknown surface material spectra and the demand of an urban site-specific spectral library is tackled by the development of a learning spectral archive tool. Starting with an incomplete library of labelled image spectra from several German cities, surface materials of pure image pixels will be identified in a hyperspectral image based on a similarity measure (e.g. SID-SAM). Additionally, unknown image spectra of urban objects are identified based on an object- and spectral-based-rule set. The detected unknown surface material spectra are entered with additional metadata, such as regional occurrence into the existing spectral library and thus, are reusable for further studies. Our approach is suitable for pure surface material detection of urban hyperspectral images that is globally applicable by taking incompleteness into account. The generically development enables the implementation of different hyperspectral sensors.

Autonomous mental development with selective attention, object perception, and knowledge representation

NASA Astrophysics Data System (ADS)

Ban, Sang-Woo; Lee, Minho

2008-04-01

Knowledge-based clustering and autonomous mental development remains a high priority research topic, among which the learning techniques of neural networks are used to achieve optimal performance. In this paper, we present a new framework that can automatically generate a relevance map from sensory data that can represent knowledge regarding objects and infer new knowledge about novel objects. The proposed model is based on understating of the visual what pathway in our brain. A stereo saliency map model can selectively decide salient object areas by additionally considering local symmetry feature. The incremental object perception model makes clusters for the construction of an ontology map in the color and form domains in order to perceive an arbitrary object, which is implemented by the growing fuzzy topology adaptive resonant theory (GFTART) network. Log-polar transformed color and form features for a selected object are used as inputs of the GFTART. The clustered information is relevant to describe specific objects, and the proposed model can automatically infer an unknown object by using the learned information. Experimental results with real data have demonstrated the validity of this approach.

77 FR 40901 - Notice of Inventory Completion: Gregg County Historical Museum, Longview, TX

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-11

... adult, one adult of unknown sex, and one juvenile of unknown sex. The human remains from Burial 6 include an occipital cranial bone fragment of one adult of unknown sex. The human remains from Burial 7 include one adult of unknown sex. No known individuals were identified. The 11 associated funerary objects...

Opportunistic pathology-based screening for diabetes

PubMed Central

Simpson, Aaron J; Krowka, Renata; Kerrigan, Jennifer L; Southcott, Emma K; Wilson, J Dennis; Potter, Julia M; Nolan, Christopher J; Hickman, Peter E

2013-01-01

Objective To determine the potential of opportunistic glycated haemoglobin (HbA1c) testing of pathology samples to detect previously unknown diabetes. Design Pathology samples from participants collected for other reasons and suitable for HbA1c testing were utilised for opportunistic diabetes screening. HbA1c was measured with a Biorad Variant II turbo analyser and HbA1c levels of ≥6.5% (48 mmol/mol) were considered diagnostic for diabetes. Confirmation of previously unknown diabetes status was obtained by a review of hospital medical records and phone calls to general practitioners. Setting Hospital pathology laboratory receiving samples from hospital-based and community-based (CB) settings. Participants Participants were identified based on the blood sample collection location in the CB, emergency department (ED) and inpatient (IP) groups. Exclusions pretesting were made based on the electronic patient history of: age <18 years, previous diabetes diagnosis, query for diabetes status in the past 12 months, evidence of pregnancy and sample collected postsurgery or transfusion. Only one sample per individual participant was tested. Results Of the 22 396 blood samples collected, 4505 (1142 CB, 1113 ED, 2250 IP) were tested of which 327 (7.3%) had HbA1c levels ≥6.5% (48 mmol/mol). Of these 120 (2.7%) were determined to have previously unknown diabetes (11 (1%) CB, 21 (1.9%) ED, 88 (3.9%) IP). The prevalence of previously unknown diabetes was substantially higher (5.4%) in hospital-based (ED and IP) participants aged over 54 years. Conclusions Opportunistic testing of referred pathology samples can be an effective method of screening for diabetes, especially in hospital-based and older persons. PMID:24065696

Perceptual asymmetries in greyscales: object-based versus space-based influences.

PubMed

Thomas, Nicole A; Elias, Lorin J

2012-05-01

Neurologically normal individuals exhibit leftward spatial biases, resulting from object- and space-based biases; however their relative contributions to the overall bias remain unknown. Relative position within the display has not often been considered, with similar spatial conditions being collapsed across. Study 1 used the greyscales task to investigate the influence of relative position and object- and space-based contributions. One image in each greyscale pair was shifted towards the left or the right. A leftward object-based bias moderated by a bias to the centre was expected. Results confirmed this as a left object-based bias occurred in the right visual field, where the left side of the greyscale pairs was located in the centre visual field. Further, only lower visual field images exhibited a significant left bias in the left visual field. The left bias was also stronger when images were partially overlapping in the right visual field, demonstrating the importance of examining proximity. The second study examined whether object-based biases were stronger when actual objects, with directional lighting biases, were used. Direction of luminosity was congruent or incongruent with spatial location. A stronger object-based bias emerged overall; however a leftward bias was seen in congruent conditions and a rightward bias was seen in incongruent conditions. In conditions with significant biases, the lower visual field image was chosen most often. Results show that object- and space-based biases both contribute; however stimulus type allows either space- or object-based biases to be stronger. A lower visual field bias also interacts with these biases, leading the left bias to be eliminated under certain conditions. The complex interaction occurring between frame of reference and visual field makes spatial location extremely important in determining the strength of the leftward bias. Copyright © 2010 Elsevier Srl. All rights reserved.

3D noise-resistant segmentation and tracking of unknown and occluded objects using integral imaging

NASA Astrophysics Data System (ADS)

Aloni, Doron; Jung, Jae-Hyun; Yitzhaky, Yitzhak

2017-10-01

Three dimensional (3D) object segmentation and tracking can be useful in various computer vision applications, such as: object surveillance for security uses, robot navigation, etc. We present a method for 3D multiple-object tracking using computational integral imaging, based on accurate 3D object segmentation. The method does not employ object detection by motion analysis in a video as conventionally performed (such as background subtraction or block matching). This means that the movement properties do not significantly affect the detection quality. The object detection is performed by analyzing static 3D image data obtained through computational integral imaging With regard to previous works that used integral imaging data in such a scenario, the proposed method performs the 3D tracking of objects without prior information about the objects in the scene, and it is found efficient under severe noise conditions.

Vision System for Coarsely Estimating Motion Parameters for Unknown Fast Moving Objects in Space

PubMed Central

Chen, Min; Hashimoto, Koichi

2017-01-01

Motivated by biological interests in analyzing navigation behaviors of flying animals, we attempt to build a system measuring their motion states. To do this, in this paper, we build a vision system to detect unknown fast moving objects within a given space, calculating their motion parameters represented by positions and poses. We proposed a novel method to detect reliable interest points from images of moving objects, which can be hardly detected by general purpose interest point detectors. 3D points reconstructed using these interest points are then grouped and maintained for detected objects, according to a careful schedule, considering appearance and perspective changes. In the estimation step, a method is introduced to adapt the robust estimation procedure used for dense point set to the case for sparse set, reducing the potential risk of greatly biased estimation. Experiments are conducted against real scenes, showing the capability of the system of detecting multiple unknown moving objects and estimating their positions and poses. PMID:29206189

Multi-objective optimization in quantum parameter estimation

NASA Astrophysics Data System (ADS)

Gong, BeiLi; Cui, Wei

2018-04-01

We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is improved, it usually introduces a significant deformation to the system state. Moreover, we propose a multi-objective model to optimize the two conflicting objectives: (1) maximizing the Fisher information, improving the parameter estimation precision, and (2) minimizing the deformation of the system state, which maintains its fidelity. Finally, simulations of a simplified ɛ-constrained model demonstrate the feasibility of the Hamiltonian control in improving the precision of the quantum parameter estimation.

Etiology and clinical presentation of birth defects: population based study

PubMed Central

Carey, John C; Byrne, Janice L B; Krikov, Sergey; Botto, Lorenzo D

2017-01-01

Objective To assess causation and clinical presentation of major birth defects. Design Population based case cohort. Setting Cases of birth defects in children born 2005-09 to resident women, ascertained through Utah’s population based surveillance system. All records underwent clinical re-review. Participants 5504 cases among 270 878 births (prevalence 2.03%), excluding mild isolated conditions (such as muscular ventricular septal defects, distal hypospadias). Main outcome measures The primary outcomes were the proportion of birth defects with a known etiology (chromosomal, genetic, human teratogen, twinning) or unknown etiology, by morphology (isolated, multiple, minors only), and by pathogenesis (sequence, developmental field defect, or known pattern of birth defects). Results Definite cause was assigned in 20.2% (n=1114) of cases: chromosomal or genetic conditions accounted for 94.4% (n=1052), teratogens for 4.1% (n=46, mostly poorly controlled pregestational diabetes), and twinning for 1.4% (n=16, conjoined or acardiac). The 79.8% (n=4390) remaining were classified as unknown etiology; of these 88.2% (n=3874) were isolated birth defects. Family history (similarly affected first degree relative) was documented in 4.8% (n=266). In this cohort, 92.1% (5067/5504) were live born infants (isolated and non-isolated birth defects): 75.3% (4147/5504) were classified as having an isolated birth defect (unknown or known etiology). Conclusions These findings underscore the gaps in our knowledge regarding the causes of birth defects. For the causes that are known, such as smoking or diabetes, assigning causation in individual cases remains challenging. Nevertheless, the ongoing impact of these exposures on fetal development highlights the urgency and benefits of population based preventive interventions. For the causes that are still unknown, better strategies are needed. These can include greater integration of the key elements of etiology, morphology, and pathogenesis into epidemiologic studies; greater collaboration between researchers (such as developmental biologists), clinicians (such as medical geneticists), and epidemiologists; and better ways to objectively measure fetal exposures (beyond maternal self reports) and closer (prenatally) to the critical period of organogenesis. PMID:28559234

Visual laterality in dolphins: importance of the familiarity of stimuli

PubMed Central

2012-01-01

Background Many studies of cerebral asymmetries in different species lead, on the one hand, to a better understanding of the functions of each cerebral hemisphere and, on the other hand, to develop an evolutionary history of hemispheric laterality. Our animal model is particularly interesting because of its original evolutionary path, i.e. return to aquatic life after a terrestrial phase. The rare reports concerning visual laterality of marine mammals investigated mainly discrimination processes. As dolphins are migrant species they are confronted to a changing environment. Being able to categorize new versus familiar objects would allow dolphins a rapid adaptation to novel environments. Visual laterality could be a prerequisite to this adaptability. To date, no study, to our knowledge, has analyzed the environmental factors that could influence their visual laterality. Results We investigated visual laterality expressed spontaneously at the water surface by a group of five common bottlenose dolphins (Tursiops truncatus) in response to various stimuli. The stimuli presented ranged from very familiar objects (known and manipulated previously) to familiar objects (known but never manipulated) to unfamiliar objects (unknown, never seen previously). At the group level, dolphins used their left eye to observe very familiar objects and their right eye to observe unfamiliar objects. However, eyes are used indifferently to observe familiar objects with intermediate valence. Conclusion Our results suggest different visual cerebral processes based either on the global shape of well-known objects or on local details of unknown objects. Moreover, the manipulation of an object appears necessary for these dolphins to construct a global representation of an object enabling its immediate categorization for subsequent use. Our experimental results pointed out some cognitive capacities of dolphins which might be crucial for their wild life given their fission-fusion social system and migratory behaviour. PMID:22239860

Visual laterality in dolphins: importance of the familiarity of stimuli.

PubMed

Blois-Heulin, Catherine; Crével, Mélodie; Böye, Martin; Lemasson, Alban

2012-01-12

Many studies of cerebral asymmetries in different species lead, on the one hand, to a better understanding of the functions of each cerebral hemisphere and, on the other hand, to develop an evolutionary history of hemispheric laterality. Our animal model is particularly interesting because of its original evolutionary path, i.e. return to aquatic life after a terrestrial phase. The rare reports concerning visual laterality of marine mammals investigated mainly discrimination processes. As dolphins are migrant species they are confronted to a changing environment. Being able to categorize new versus familiar objects would allow dolphins a rapid adaptation to novel environments. Visual laterality could be a prerequisite to this adaptability. To date, no study, to our knowledge, has analyzed the environmental factors that could influence their visual laterality. We investigated visual laterality expressed spontaneously at the water surface by a group of five common bottlenose dolphins (Tursiops truncatus) in response to various stimuli. The stimuli presented ranged from very familiar objects (known and manipulated previously) to familiar objects (known but never manipulated) to unfamiliar objects (unknown, never seen previously). At the group level, dolphins used their left eye to observe very familiar objects and their right eye to observe unfamiliar objects. However, eyes are used indifferently to observe familiar objects with intermediate valence. Our results suggest different visual cerebral processes based either on the global shape of well-known objects or on local details of unknown objects. Moreover, the manipulation of an object appears necessary for these dolphins to construct a global representation of an object enabling its immediate categorization for subsequent use. Our experimental results pointed out some cognitive capacities of dolphins which might be crucial for their wild life given their fission-fusion social system and migratory behaviour.

Navigation through unknown and dynamic open spaces using topological notions

NASA Astrophysics Data System (ADS)

Miguel-Tomé, Sergio

2018-04-01

Until now, most algorithms used for navigation have had the purpose of directing system towards one point in space. However, humans communicate tasks by specifying spatial relations among elements or places. In addition, the environments in which humans develop their activities are extremely dynamic. The only option that allows for successful navigation in dynamic and unknown environments is making real-time decisions. Therefore, robots capable of collaborating closely with human beings must be able to make decisions based on the local information registered by the sensors and interpret and express spatial relations. Furthermore, when one person is asked to perform a task in an environment, this task is communicated given a category of goals so the person does not need to be supervised. Thus, two problems appear when one wants to create multifunctional robots: how to navigate in dynamic and unknown environments using spatial relations and how to accomplish this without supervision. In this article, a new architecture to address the two cited problems is presented, called the topological qualitative navigation architecture. In previous works, a qualitative heuristic called the heuristic of topological qualitative semantics (HTQS) has been developed to establish and identify spatial relations. However, that heuristic only allows for establishing one spatial relation with a specific object. In contrast, navigation requires a temporal sequence of goals with different objects. The new architecture attains continuous generation of goals and resolves them using HTQS. Thus, the new architecture achieves autonomous navigation in dynamic or unknown open environments.

An Evidence-Based Review Literature About Risk Indicators and Management of Unknown-Origin Xerostomia

PubMed Central

Agha-Hosseini, Farzaneh; Moosavi, Mahdieh-Sadat

2013-01-01

This evidence-based article reviews risk indicators and management of unknown-origin xerostomia. Xerostomia and hyposalivation refer to different aspects of dry mouth. Xerostomia is a subjective sensation of dry mouth, whilst hyposalivation is defined as an objective assessment of reduced salivary flow rate. About 30% of the elderly (65 years and older) experience xerostomia and hyposalivation. Structural and functional factors, or both may lead to salivary gland dysfunction. The EBM literature search was conducted by using the medical literature database MEDLINE via PubMed and OvidMedline search engines. Results were limited to English language articles (1965 to present) including clinical trials (CT), randomized controlled trials (RCT), systematic reviews and review articles. Case control or cohort studies were included for the etiology. Neuropathic etiology such as localized oral alteration of thermal sensations, saliva composition change (for example higher levels of K, Cl, Ca, IgA, amylase, calcium, PTH and cortisol), lower levels of estrogen and progesterone, smaller salivary gland size, and illnesses such as lichen planus, are risk indicators for unknown-origin xerostomia. The management is palliative and preventative. Management of symptoms includes drug administration (systemic secretogogues, saliva substitutes and bile secretion-stimulator), night guard, diet and habit modifications. Other managements may be indicated to treat adverse effects. Neuropathic etiology, saliva composition change, smaller salivary gland size, and illnesses such as oral lichen planus can be suggestive causes for unknown-origin xerostomia. However, longitudinal studies will be important to elucidate the causes of unknown-origin xerostomia. PMID:25512755

A Space Object Detection Algorithm using Fourier Domain Likelihood Ratio Test

NASA Astrophysics Data System (ADS)

Becker, D.; Cain, S.

Space object detection is of great importance in the highly dependent yet competitive and congested space domain. Detection algorithms employed play a crucial role in fulfilling the detection component in the situational awareness mission to detect, track, characterize and catalog unknown space objects. Many current space detection algorithms use a matched filter or a spatial correlator to make a detection decision at a single pixel point of a spatial image based on the assumption that the data follows a Gaussian distribution. This paper explores the potential for detection performance advantages when operating in the Fourier domain of long exposure images of small and/or dim space objects from ground based telescopes. A binary hypothesis test is developed based on the joint probability distribution function of the image under the hypothesis that an object is present and under the hypothesis that the image only contains background noise. The detection algorithm tests each pixel point of the Fourier transformed images to make the determination if an object is present based on the criteria threshold found in the likelihood ratio test. Using simulated data, the performance of the Fourier domain detection algorithm is compared to the current algorithm used in space situational awareness applications to evaluate its value.

A comparison between Gauss-Newton and Markov chain Monte Carlo basedmethods for inverting spectral induced polarization data for Cole-Coleparameters

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

Chen, Jinsong; Kemna, Andreas; Hubbard, Susan S.

2008-05-15

We develop a Bayesian model to invert spectral induced polarization (SIP) data for Cole-Cole parameters using Markov chain Monte Carlo (MCMC) sampling methods. We compare the performance of the MCMC based stochastic method with an iterative Gauss-Newton based deterministic method for Cole-Cole parameter estimation through inversion of synthetic and laboratory SIP data. The Gauss-Newton based method can provide an optimal solution for given objective functions under constraints, but the obtained optimal solution generally depends on the choice of initial values and the estimated uncertainty information is often inaccurate or insufficient. In contrast, the MCMC based inversion method provides extensive globalmore » information on unknown parameters, such as the marginal probability distribution functions, from which we can obtain better estimates and tighter uncertainty bounds of the parameters than with the deterministic method. Additionally, the results obtained with the MCMC method are independent of the choice of initial values. Because the MCMC based method does not explicitly offer single optimal solution for given objective functions, the deterministic and stochastic methods can complement each other. For example, the stochastic method can first be used to obtain the means of the unknown parameters by starting from an arbitrary set of initial values and the deterministic method can then be initiated using the means as starting values to obtain the optimal estimates of the Cole-Cole parameters.« less

Three-dimensional cinematography with control object of unknown shape.

PubMed

Dapena, J; Harman, E A; Miller, J A

1982-01-01

A technique for reconstruction of three-dimensional (3D) motion which involves a simple filming procedure but allows the deduction of coordinates in large object volumes was developed. Internal camera parameters are calculated from measurements of the film images of two calibrated crosses while external camera parameters are calculated from the film images of points in a control object of unknown shape but at least one known length. The control object, which includes the volume in which the activity is to take place, is formed by a series of poles placed at unknown locations, each carrying two targets. From the internal and external camera parameters, and from locations of the images of point in the films of the two cameras, 3D coordinates of the point can be calculated. Root mean square errors of the three coordinates of points in a large object volume (5m x 5m x 1.5m) were 15 mm, 13 mm, 13 mm and 6 mm, and relative errors in lengths averaged 0.5%, 0.7% and 0.5%, respectively.

A recurrent neural model for proto-object based contour integration and figure-ground segregation.

PubMed

Hu, Brian; Niebur, Ernst

2017-12-01

Visual processing of objects makes use of both feedforward and feedback streams of information. However, the nature of feedback signals is largely unknown, as is the identity of the neuronal populations in lower visual areas that receive them. Here, we develop a recurrent neural model to address these questions in the context of contour integration and figure-ground segregation. A key feature of our model is the use of grouping neurons whose activity represents tentative objects ("proto-objects") based on the integration of local feature information. Grouping neurons receive input from an organized set of local feature neurons, and project modulatory feedback to those same neurons. Additionally, inhibition at both the local feature level and the object representation level biases the interpretation of the visual scene in agreement with principles from Gestalt psychology. Our model explains several sets of neurophysiological results (Zhou et al. Journal of Neuroscience, 20(17), 6594-6611 2000; Qiu et al. Nature Neuroscience, 10(11), 1492-1499 2007; Chen et al. Neuron, 82(3), 682-694 2014), and makes testable predictions about the influence of neuronal feedback and attentional selection on neural responses across different visual areas. Our model also provides a framework for understanding how object-based attention is able to select both objects and the features associated with them.

Low-Altitude Operation of Unmanned Rotorcraft

NASA Astrophysics Data System (ADS)

Scherer, Sebastian

Currently deployed unmanned rotorcraft rely on preplanned missions or teleoperation and do not actively incorporate information about obstacles, landing sites, wind, position uncertainty, and other aerial vehicles during online motion planning. Prior work has successfully addressed some tasks such as obstacle avoidance at slow speeds, or landing at known to be good locations. However, to enable autonomous missions in cluttered environments, the vehicle has to react quickly to previously unknown obstacles, respond to changing environmental conditions, and find unknown landing sites. We consider the problem of enabling autonomous operation at low-altitude with contributions to four problems. First we address the problem of fast obstacle avoidance for a small aerial vehicle and present results from over a 1000 rims at speeds up to 10 m/s. Fast response is achieved through a reactive algorithm whose response is learned based on observing a pilot. Second, we show an algorithm to update the obstacle cost expansion for path planning quickly and demonstrate it on a micro aerial vehicle, and an autonomous helicopter avoiding obstacles. Next, we examine the mission of finding a place to land near a ground goal. Good landing sites need to be detected and found and the final touch down goal is unknown. To detect the landing sites we convey a model based algorithm for landing sites that incorporates many helicopter relevant constraints such as landing sites, approach, abort, and ground paths in 3D range data. The landing site evaluation algorithm uses a patch-based coarse evaluation for slope and roughness, and a fine evaluation that fits a 3D model of the helicopter and landing gear to calculate a goodness measure. The data are evaluated in real-time to enable the helicopter to decide on a place to land. We show results from urban, vegetated, and desert environments, and demonstrate the first autonomous helicopter that selects its own landing sites. We present a generalized planning framework that enables reaching a goal point, searching for unknown landing sites, and approaching a landing zone. In the framework, sub-objective functions, constraints, and a state machine define the mission and behavior of an UAV. As the vehicle gathers information by moving through the environment, the objective functions account for this new information. The operator in this framework can directly specify his intent as an objective function that defines the mission rather than giving a sequence of pre-specified goal points. This allows the robot to react to new information received and adjust its path accordingly. The objective is used in a combined coarse planning and trajectory optimization algorithm to determine the best patch the robot should take. We show simulated results for several different missions and in particular focus on active landing zone search. We presented several effective approaches for perception and action for low-altitude flight and demonstrated their effectiveness in field experiments on three autonomous aerial vehicles: a 1m quadrocopter, a 36m helicopter, and a hill-size helicopter. These techniques permit rotorcraft to operate where they have their greatest advantage: In unstructured, unknown environments at low-altitude.

Inertial parameter identification using contact force information for an unknown object captured by a space manipulator

NASA Astrophysics Data System (ADS)

Chu, Zhongyi; Ma, Ye; Hou, Yueyang; Wang, Fengwen

2017-02-01

This paper presents a novel identification method for the intact inertial parameters of an unknown object in space captured by a manipulator in a space robotic system. With strong dynamic and kinematic coupling existing in the robotic system, the inertial parameter identification of the unknown object is essential for the ideal control strategy based on changes in the attitude and trajectory of the space robot via capturing operations. Conventional studies merely refer to the principle and theory of identification, and an error analysis process of identification is deficient for a practical scenario. To solve this issue, an analysis of the effect of errors on identification is illustrated first, and the accumulation of measurement or estimation errors causing poor identification precision is demonstrated. Meanwhile, a modified identification equation incorporating the contact force, as well as the force/torque of the end-effector, is proposed to weaken the accumulation of errors and improve the identification accuracy. Furthermore, considering a severe disturbance condition caused by various measured noises, the hybrid immune algorithm, Recursive Least Squares and Affine Projection Sign Algorithm (RLS-APSA), is employed to decode the modified identification equation to ensure a stable identification property. Finally, to verify the validity of the proposed identification method, the co-simulation of ADAMS-MATLAB is implemented by multi-degree of freedom models of a space robotic system, and the numerical results show a precise and stable identification performance, which is able to guarantee the execution of aerospace operations and prevent failed control strategies.

Solution Strategies, Modes of Representation and Justifications of Primary Five Pupils in Solving Pre Algebra Problems: An Experience of Using Task-Based Interview and Verbal Protocol Analysis

ERIC Educational Resources Information Center

Ling, Gan We; Ghazali, Munirah

2007-01-01

This descriptive study was aimed at looking into how Primary 5 pupils solve pre-algebra problems concerning patterns and unknown quantities. Specifically, objectives of this study were to describe Primary 5 pupils' solution strategies, modes of representations and justifications in: (a) discovering, describing and using numerical and geometrical…

3D Laser Scanner for Underwater Manipulation.

PubMed

Palomer, Albert; Ridao, Pere; Youakim, Dina; Ribas, David; Forest, Josep; Petillot, Yvan

2018-04-04

Nowadays, research in autonomous underwater manipulation has demonstrated simple applications like picking an object from the sea floor, turning a valve or plugging and unplugging a connector. These are fairly simple tasks compared with those already demonstrated by the mobile robotics community, which include, among others, safe arm motion within areas populated with a priori unknown obstacles or the recognition and location of objects based on their 3D model to grasp them. Kinect-like 3D sensors have contributed significantly to the advance of mobile manipulation providing 3D sensing capabilities in real-time at low cost. Unfortunately, the underwater robotics community is lacking a 3D sensor with similar capabilities to provide rich 3D information of the work space. In this paper, we present a new underwater 3D laser scanner and demonstrate its capabilities for underwater manipulation. In order to use this sensor in conjunction with manipulators, a calibration method to find the relative position between the manipulator and the 3D laser scanner is presented. Then, two different advanced underwater manipulation tasks beyond the state of the art are demonstrated using two different manipulation systems. First, an eight Degrees of Freedom (DoF) fixed-base manipulator system is used to demonstrate arm motion within a work space populated with a priori unknown fixed obstacles. Next, an eight DoF free floating Underwater Vehicle-Manipulator System (UVMS) is used to autonomously grasp an object from the bottom of a water tank.

Running Improves Pattern Separation during Novel Object Recognition.

PubMed

Bolz, Leoni; Heigele, Stefanie; Bischofberger, Josef

2015-10-09

Running increases adult neurogenesis and improves pattern separation in various memory tasks including context fear conditioning or touch-screen based spatial learning. However, it is unknown whether pattern separation is improved in spontaneous behavior, not emotionally biased by positive or negative reinforcement. Here we investigated the effect of voluntary running on pattern separation during novel object recognition in mice using relatively similar or substantially different objects.We show that running increases hippocampal neurogenesis but does not affect object recognition memory with 1.5 h delay after sample phase. By contrast, at 24 h delay, running significantly improves recognition memory for similar objects, whereas highly different objects can be distinguished by both, running and sedentary mice. These data show that physical exercise improves pattern separation, independent of negative or positive reinforcement. In sedentary mice there is a pronounced temporal gradient for remembering object details. In running mice, however, increased neurogenesis improves hippocampal coding and temporally preserves distinction of novel objects from familiar ones.

Near real-time measurement of forces applied by an optical trap to a rigid cylindrical object

NASA Astrophysics Data System (ADS)

Glaser, Joseph; Hoeprich, David; Resnick, Andrew

2014-07-01

An automated data acquisition and processing system is established to measure the force applied by an optical trap to an object of unknown composition in real time. Optical traps have been in use for the past 40 years to manipulate microscopic particles, but the magnitude of applied force is often unknown and requires extensive instrument characterization. Measuring or calculating the force applied by an optical trap to nonspherical particles presents additional difficulties which are also overcome with our system. Extensive experiments and measurements using well-characterized objects were performed to verify the system performance.

Tracking of Maneuvering Complex Extended Object with Coupled Motion Kinematics and Extension Dynamics Using Range Extent Measurements

PubMed Central

Sun, Lifan; Ji, Baofeng; Lan, Jian; He, Zishu; Pu, Jiexin

2017-01-01

The key to successful maneuvering complex extended object tracking (MCEOT) using range extent measurements provided by high resolution sensors lies in accurate and effective modeling of both the extension dynamics and the centroid kinematics. During object maneuvers, the extension dynamics of an object with a complex shape is highly coupled with the centroid kinematics. However, this difficult but important problem is rarely considered and solved explicitly. In view of this, this paper proposes a general approach to modeling a maneuvering complex extended object based on Minkowski sum, so that the coupled turn maneuvers in both the centroid states and extensions can be described accurately. The new model has a concise and unified form, in which the complex extension dynamics can be simply and jointly characterized by multiple simple sub-objects’ extension dynamics based on Minkowski sum. The proposed maneuvering model fits range extent measurements very well due to its favorable properties. Based on this model, an MCEOT algorithm dealing with motion and extension maneuvers is also derived. Two different cases of the turn maneuvers with known/unknown turn rates are specifically considered. The proposed algorithm which jointly estimates the kinematic state and the object extension can also be easily implemented. Simulation results demonstrate the effectiveness of the proposed modeling and tracking approaches. PMID:28937629

Integrating planning perception and action for informed object search.

PubMed

Manso, Luis J; Gutierrez, Marco A; Bustos, Pablo; Bachiller, Pilar

2018-05-01

This paper presents a method to reduce the time spent by a robot with cognitive abilities when looking for objects in unknown locations. It describes how machine learning techniques can be used to decide which places should be inspected first, based on images that the robot acquires passively. The proposal is composed of two concurrent processes. The first one uses the aforementioned images to generate a description of the types of objects found in each object container seen by the robot. This is done passively, regardless of the task being performed. The containers can be tables, boxes, shelves or any other kind of container of known shape whose contents can be seen from a distance. The second process uses the previously computed estimation of the contents of the containers to decide which is the most likely container having the object to be found. This second process is deliberative and takes place only when the robot needs to find an object, whether because it is explicitly asked to locate one or because it is needed as a step to fulfil the mission of the robot. Upon failure to guess the right container, the robot can continue making guesses until the object is found. Guesses are made based on the semantic distance between the object to find and the description of the types of the objects found in each object container. The paper provides quantitative results comparing the efficiency of the proposed method and two base approaches.

Performance study of LMS based adaptive algorithms for unknown system identification

NASA Astrophysics Data System (ADS)

Javed, Shazia; Ahmad, Noor Atinah

2014-07-01

Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.

Performance study of LMS based adaptive algorithms for unknown system identification

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

Javed, Shazia; Ahmad, Noor Atinah

Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signalmore » is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.« less

Community detection in complex networks by using membrane algorithm

NASA Astrophysics Data System (ADS)

Liu, Chuang; Fan, Linan; Liu, Zhou; Dai, Xiang; Xu, Jiamei; Chang, Baoren

Community detection in complex networks is a key problem of network analysis. In this paper, a new membrane algorithm is proposed to solve the community detection in complex networks. The proposed algorithm is based on membrane systems, which consists of objects, reaction rules, and a membrane structure. Each object represents a candidate partition of a complex network, and the quality of objects is evaluated according to network modularity. The reaction rules include evolutionary rules and communication rules. Evolutionary rules are responsible for improving the quality of objects, which employ the differential evolutionary algorithm to evolve objects. Communication rules implement the information exchanged among membranes. Finally, the proposed algorithm is evaluated on synthetic, real-world networks with real partitions known and the large-scaled networks with real partitions unknown. The experimental results indicate the superior performance of the proposed algorithm in comparison with other experimental algorithms.

Analyzing the Critical Supply Chain For Unmanned Aircraft Systems

DTIC Science & Technology

2017-03-23

with a decision support tool that facilitates interdiction strategy planning. Overall, the different models developed in the study provide modeling...allow adaptation to different levels of fidelity of the supply chain, based on the user’s mission objectives and available data. A House of Quality...priorities are unknown or incorrect. 1.7 Implications The models presented in this research can be utilized from two different perspectives of

Evolutionary Fuzzy Control and Navigation for Two Wheeled Robots Cooperatively Carrying an Object in Unknown Environments.

PubMed

Juang, Chia-Feng; Lai, Min-Ge; Zeng, Wan-Ting

2015-09-01

This paper presents a method that allows two wheeled, mobile robots to navigate unknown environments while cooperatively carrying an object. In the navigation method, a leader robot and a follower robot cooperatively perform either obstacle boundary following (OBF) or target seeking (TS) to reach a destination. The two robots are controlled by fuzzy controllers (FC) whose rules are learned through an adaptive fusion of continuous ant colony optimization and particle swarm optimization (AF-CACPSO), which avoids the time-consuming task of manually designing the controllers. The AF-CACPSO-based evolutionary fuzzy control approach is first applied to the control of a single robot to perform OBF. The learning approach is then applied to achieve cooperative OBF with two robots, where an auxiliary FC designed with the AF-CACPSO is used to control the follower robot. For cooperative TS, a rule for coordination of the two robots is developed. To navigate cooperatively, a cooperative behavior supervisor is introduced to select between cooperative OBF and cooperative TS. The performance of the AF-CACPSO is verified through comparisons with various population-based optimization algorithms for the OBF learning problem. Simulations and experiments verify the effectiveness of the approach for cooperative navigation of two robots.

Object-graphs for context-aware visual category discovery.

PubMed

Lee, Yong Jae; Grauman, Kristen

2012-02-01

How can knowing about some categories help us to discover new ones in unlabeled images? Unsupervised visual category discovery is useful to mine for recurring objects without human supervision, but existing methods assume no prior information and thus tend to perform poorly for cluttered scenes with multiple objects. We propose to leverage knowledge about previously learned categories to enable more accurate discovery, and address challenges in estimating their familiarity in unsegmented, unlabeled images. We introduce two variants of a novel object-graph descriptor to encode the 2D and 3D spatial layout of object-level co-occurrence patterns relative to an unfamiliar region and show that by using them to model the interaction between an image’s known and unknown objects, we can better detect new visual categories. Rather than mine for all categories from scratch, our method identifies new objects while drawing on useful cues from familiar ones. We evaluate our approach on several benchmark data sets and demonstrate clear improvements in discovery over conventional purely appearance-based baselines.

Fully invariant wavelet enhanced minimum average correlation energy filter for object recognition in cluttered and occluded environments

NASA Astrophysics Data System (ADS)

Tehsin, Sara; Rehman, Saad; Riaz, Farhan; Saeed, Omer; Hassan, Ali; Khan, Muazzam; Alam, Muhammad S.

2017-05-01

A fully invariant system helps in resolving difficulties in object detection when camera or object orientation and position are unknown. In this paper, the proposed correlation filter based mechanism provides the capability to suppress noise, clutter and occlusion. Minimum Average Correlation Energy (MACE) filter yields sharp correlation peaks while considering the controlled correlation peak value. Difference of Gaussian (DOG) Wavelet has been added at the preprocessing stage in proposed filter design that facilitates target detection in orientation variant cluttered environment. Logarithmic transformation is combined with a DOG composite minimum average correlation energy filter (WMACE), capable of producing sharp correlation peaks despite any kind of geometric distortion of target object. The proposed filter has shown improved performance over some of the other variant correlation filters which are discussed in the result section.

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.

Material Identification and Quantification in Spectral X-ray Micro-CT

NASA Astrophysics Data System (ADS)

Holmes, Thomas Wesley

The identification and quantification of all the voxels within a reconstructed microCT image was possible through making comparisons of the attenuation profile from an unknown voxel with precalculated signatures of known materials. This was accomplished through simulations with the MCNP6 general-purpose radiation-transport package that modeled a CdTe detector array consisting of 200 elements which were able to differentiate between 100 separate energy bins over the entire range of the emitted 110 kVp tungsten x-ray spectra. The information from each of the separate energy bins was then used to create a single reconstructed image that was then grouped back together to produce a final image where each voxel had a corresponding attenuation pro le. A library of known attenuation profiles was created for each of the materials expected to be within an object with otherwise unknown parameters. A least squares analysis was performed, and comparisons were then made for each voxel's attenuation profile in the unknown object and combinations of each possible library combination of attenuation profiles. Based on predetermined thresholds that the results must meet, some of the combinations were then removed. Of the remaining combinations, a voting system based on statistical evaluations of the fits was designed to select the most appropriate material combination to the input unknown voxel. This was performed over all of the voxels in the reconstructed image and a final resulting material map was produced. These material locations were then quantified by creating an equation of the response from several different densities of the same material and recording the response of the base library. This entire process was called the All Combinations Library Least Squares (ACLLS)analysis and was used to test several Different models. These models investigated a range of densities for the x-ray contrast agents of gold and gadolinium that can be used in many medical applications, as well as a range of densities of bone to test the ACLLS ability to be used with bone density estimation. A final test used a model with five different materials present within the object and consisted of two separate features with mixtures of three materials as gold, iodine and water, and another feature with gadolinium, iodine and water. The remaining four features were all mixtures of water with bone, gold, gadolinium, and iodine. All of the various material mixtures were successfully identified and quantified using the ACLLS analysis package within an acceptable statistical range. The ACLLS method has proven itself as a viable analysis tool for determining both the physical locations and the amount of all the materials present within a given object. This tool could be implemented in the future so as to further assist a team of medical practitioners in diagnosing a subject through reducing ambiguities in an image and providing a quantifiable solution to all of the voxels.

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

Nurhandoko, Bagus Endar B.; Wely, Woen; Setiadi, Herlan

It is already known that tomography has a great impact for analyzing and mapping unknown objects based on inversion, travel time as well as waveform inversion. Therefore, tomography has used in wide area, not only in medical but also in petroleum as well as mining. Recently, tomography method is being applied in several mining industries. A case study of tomography imaging has been carried out in DOZ ( Deep Ore Zone ) block caving mine, Tembagapura, Papua. Many researchers are undergoing to investigate the properties of DOZ cave not only outside but also inside which is unknown. Tomography takes amore » part for determining this objective.The sources are natural from the seismic events that caused by mining induced seismicity and rocks deformation activity, therefore it is called as passive seismic. These microseismic travel time data are processed by Simultaneous Iterative Reconstruction Technique (SIRT). The result of the inversion can be used for DOZ cave monitoring. These information must be used for identifying weak zone inside the cave. In addition, these results of tomography can be used to determine DOZ and cave information to support mine activity in PT. Freeport Indonesia.« less

The Development of Invariant Object Recognition Requires Visual Experience with Temporally Smooth Objects

ERIC Educational Resources Information Center

Wood, Justin N.; Wood, Samantha M. W.

2018-01-01

How do newborns learn to recognize objects? According to temporal learning models in computational neuroscience, the brain constructs object representations by extracting smoothly changing features from the environment. To date, however, it is unknown whether newborns depend on smoothly changing features to build invariant object representations.…

Integrative and distinctive coding of visual and conceptual object features in the ventral visual stream

PubMed Central

Douglas, Danielle; Newsome, Rachel N; Man, Louisa LY

2018-01-01

A significant body of research in cognitive neuroscience is aimed at understanding how object concepts are represented in the human brain. However, it remains unknown whether and where the visual and abstract conceptual features that define an object concept are integrated. We addressed this issue by comparing the neural pattern similarities among object-evoked fMRI responses with behavior-based models that independently captured the visual and conceptual similarities among these stimuli. Our results revealed evidence for distinctive coding of visual features in lateral occipital cortex, and conceptual features in the temporal pole and parahippocampal cortex. By contrast, we found evidence for integrative coding of visual and conceptual object features in perirhinal cortex. The neuroanatomical specificity of this effect was highlighted by results from a searchlight analysis. Taken together, our findings suggest that perirhinal cortex uniquely supports the representation of fully specified object concepts through the integration of their visual and conceptual features. PMID:29393853

Acquisition and Neural Network Prediction of 3D Deformable Object Shape Using a Kinect and a Force-Torque Sensor.

PubMed

Tawbe, Bilal; Cretu, Ana-Maria

2017-05-11

The realistic representation of deformations is still an active area of research, especially for deformable objects whose behavior cannot be simply described in terms of elasticity parameters. This paper proposes a data-driven neural-network-based approach for capturing implicitly and predicting the deformations of an object subject to external forces. Visual data, in the form of 3D point clouds gathered by a Kinect sensor, is collected over an object while forces are exerted by means of the probing tip of a force-torque sensor. A novel approach based on neural gas fitting is proposed to describe the particularities of a deformation over the selectively simplified 3D surface of the object, without requiring knowledge of the object material. An alignment procedure, a distance-based clustering, and inspiration from stratified sampling support this process. The resulting representation is denser in the region of the deformation (an average of 96.6% perceptual similarity with the collected data in the deformed area), while still preserving the object's overall shape (86% similarity over the entire surface) and only using on average of 40% of the number of vertices in the mesh. A series of feedforward neural networks is then trained to predict the mapping between the force parameters characterizing the interaction with the object and the change in the object shape, as captured by the fitted neural gas nodes. This series of networks allows for the prediction of the deformation of an object when subject to unknown interactions.

A combined ANN-GA and experimental based technique for the estimation of the unknown heat flux for a conjugate heat transfer problem

NASA Astrophysics Data System (ADS)

M K, Harsha Kumar; P S, Vishweshwara; N, Gnanasekaran; C, Balaji

2018-05-01

The major objectives in the design of thermal systems are obtaining the information about thermophysical, transport and boundary properties. The main purpose of this paper is to estimate the unknown heat flux at the surface of a solid body. A constant area mild steel fin is considered and the base is subjected to constant heat flux. During heating, natural convection heat transfer occurs from the fin to ambient. The direct solution, which is the forward problem, is developed as a conjugate heat transfer problem from the fin and the steady state temperature distribution is recorded for any assumed heat flux. In order to model the natural convection heat transfer from the fin, an extended domain is created near the fin geometry and air is specified as a fluid medium and Navier Stokes equation is solved by incorporating the Boussinesq approximation. The computational time involved in executing the forward model is then reduced by developing a neural network (NN) between heat flux values and temperatures based on back propagation algorithm. The conjugate heat transfer NN model is now coupled with Genetic algorithm (GA) for the solution of the inverse problem. Initially, GA is applied to the pure surrogate data, the results are then used as input to the Levenberg- Marquardt method and such hybridization is proven to result in accurate estimation of the unknown heat flux. The hybrid method is then applied for the experimental temperature to estimate the unknown heat flux. A satisfactory agreement between the estimated and actual heat flux is achieved by incorporating the hybrid method.

Vision Algorithms to Determine Shape and Distance for Manipulation of Unmodeled Objects

NASA Technical Reports Server (NTRS)

Montes, Leticia; Bowers, David; Lumia, Ron

1998-01-01

This paper discusses the development of a robotic system for general use in an unstructured environment. This is illustrated through pick and place of randomly positioned, un-modeled objects. There are many applications for this project, including rock collection for the Mars Surveyor Program. This system is demonstrated with a Puma560 robot, Barrett hand, Cognex vision system, and Cimetrix simulation and control, all running on a PC. The demonstration consists of two processes: vision system and robotics. The vision system determines the size and location of the unknown objects. The robotics part consists of moving the robot to the object, configuring the hand based on the information from the vision system, then performing the pick/place operation. This work enhances and is a part of the Low Cost Virtual Collaborative Environment which provides remote simulation and control of equipment.

Manipulation of Unknown Objects to Improve the Grasp Quality Using Tactile Information.

PubMed

Montaño, Andrés; Suárez, Raúl

2018-05-03

This work presents a novel and simple approach in the area of manipulation of unknown objects considering both geometric and mechanical constraints of the robotic hand. Starting with an initial blind grasp, our method improves the grasp quality through manipulation considering the three common goals of the manipulation process: improving the hand configuration, the grasp quality and the object positioning, and, at the same time, prevents the object from falling. Tactile feedback is used to obtain local information of the contacts between the fingertips and the object, and no additional exteroceptive feedback sources are considered in the approach. The main novelty of this work lies in the fact that the grasp optimization is performed on-line as a reactive procedure using the tactile and kinematic information obtained during the manipulation. Experimental results are shown to illustrate the efficiency of the approach.

Attributes from NMIS Time Coincidence, Fast-Neutron Imaging, Fission Mapping, And Gamma-Ray Spectrometry Data

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

Swift, Alicia L; Grogan, Brandon R; Mullens, James Allen

This work tests a systematic procedure for analyzing data acquired by the Nuclear Materials Identification System (NMIS) at Oak Ridge National Laboratory with fast-neutron imaging and high-purity germanium (HPGe) gamma spectrometry capabilities. NMIS has been under development by the US Department of Energy Office of Nuclear Verification since the mid-1990s, and prior to that by the National Nuclear Security Administration Y-12 National Security Complex, with NMIS having been used at Y-12 for template matching to confirm inventory and receipts. In this present work, a complete set of NMIS time coincidence, fast-neutron imaging, fission mapping, and HPGe gamma-ray spectrometry data wasmore » obtained from Monte Carlo simulations for a configuration of fissile and nonfissile materials. The data were then presented for analysis to someone who had no prior knowledge of the unknown object to accurately determine the description of the object by applying the previously-mentioned procedure to the simulated data. The best approximation indicated that the unknown object was composed of concentric cylinders: a void inside highly enriched uranium (HEU) (84.7 {+-} 1.9 wt % {sup 235}U), surrounded by depleted uranium, surrounded by polyethylene. The final estimation of the unknown object had the correct materials and geometry, with error in the radius estimates of material regions varying from 1.58% at best and 4.25% at worst; error in the height estimates varied from 2% to 12%. The error in the HEU enrichment estimate was 5.9 wt % (within 2.5{sigma} of the true value). The accuracies of the determinations could be adequate for arms control applications. Future work will apply this iterative reconstructive procedure to other unknown objects to further test and refine it.« less

50 CFR 635.27 - Quotas.

Code of Federal Regulations, 2014 CFR

2014-10-01

... and overfishing. (vi) Effects of the adjustment on accomplishing the objectives of the fishery... declared to be overfished, to have overfishing occurring, or to have an unknown status, NMFS may not adjust... declared to be overfished, to have overfishing occurring, or to have an unknown status, NMFS may increase...

Object-Image Correspondence for Algebraic Curves under Projections

NASA Astrophysics Data System (ADS)

Burdis, Joseph M.; Kogan, Irina A.; Hong, Hoon

2013-03-01

We present a novel algorithm for deciding whether a given planar curve is an image of a given spatial curve, obtained by a central or a parallel projection with unknown parameters. The motivation comes from the problem of establishing a correspondence between an object and an image, taken by a camera with unknown position and parameters. A straightforward approach to this problem consists of setting up a system of conditions on the projection parameters and then checking whether or not this system has a solution. The computational advantage of the algorithm presented here, in comparison to algorithms based on the straightforward approach, lies in a significant reduction of a number of real parameters that need to be eliminated in order to establish existence or non-existence of a projection that maps a given spatial curve to a given planar curve. Our algorithm is based on projection criteria that reduce the projection problem to a certain modification of the equivalence p! roblem of planar curves under affine and projective transformations. To solve the latter problem we make an algebraic adaptation of signature construction that has been used to solve the equivalence problems for smooth curves. We introduce a notion of a classifying set of rational differential invariants and produce explicit formulas for such invariants for the actions of the projective and the affine groups on the plane.

Physical properties of lunar craters

NASA Astrophysics Data System (ADS)

Joshi, Maitri P.; Bhatt, Kushal P.; Jain, Rajmal

2017-02-01

The surface of the Moon is highly cratered due to impacts of meteorites, asteroids, comets and other celestial objects. The origin, size, structure, age and composition vary among craters. We study a total of 339 craters observed by the Lunar Reconnaissance Orbiter Camera (LROC). Out of these 339 craters, 214 craters are known (named craters included in the IAU Gazetteer of Planetary Nomenclature) and 125 craters are unknown (craters that are not named and objects that are absent in the IAU Gazetteer). We employ images taken by LROC at the North and South Poles and near side of the Moon. We report for the first time the study of unknown craters, while we also review the study of known craters conducted earlier by previous researchers. Our study is focused on measurements of diameter, depth, latitude and longitude of each crater for both known and unknown craters. The diameter measurements are based on considering the Moon to be a spherical body. The LROC website also provides a plot which enables us to measure the depth and diameter. We found that out of 214 known craters, 161 craters follow a linear relationship between depth (d) and diameter (D), but 53 craters do not follow this linear relationship. We study physical dimensions of these 53 craters and found that either the depth does not change significantly with diameter or the depths are extremely high relative to diameter (conical). Similarly, out of 125 unknown craters, 78 craters follow the linear relationship between depth (d) and diameter (D) but 47 craters do not follow the linear relationship. We propose that the craters following the scaling law of depth and diameter, also popularly known as the linear relationship between d and D, are formed by the impact of meteorites having heavy metals with larger dimension, while those with larger diameter but less depth are formed by meteorites/celestial objects having low density material but larger diameter. The craters with very high depth and with very small diameter are perhaps formed by the impact of meteorites that have very high density but small diameter with a conical shape. Based on analysis of the data selected for the current investigation, we further found that out of 339 craters, 100 (29.5%) craters exist near the equator, 131 (38.6%) are in the northern hemisphere and 108 (31.80%) are in the southern hemisphere. This suggests the Moon is heavily cratered at higher latitudes and near the equatorial zone.

On Space Exploration and Human Error: A Paper on Reliability and Safety

NASA Technical Reports Server (NTRS)

Bell, David G.; Maluf, David A.; Gawdiak, Yuri

2005-01-01

NASA space exploration should largely address a problem class in reliability and risk management stemming primarily from human error, system risk and multi-objective trade-off analysis, by conducting research into system complexity, risk characterization and modeling, and system reasoning. In general, in every mission we can distinguish risk in three possible ways: a) known-known, b) known-unknown, and c) unknown-unknown. It is probably almost certain that space exploration will partially experience similar known or unknown risks embedded in the Apollo missions, Shuttle or Station unless something alters how NASA will perceive and manage safety and reliability

Stochastic Individual-Based Modeling of Bacterial Growth and Division Using Flow Cytometry.

PubMed

García, Míriam R; Vázquez, José A; Teixeira, Isabel G; Alonso, Antonio A

2017-01-01

A realistic description of the variability in bacterial growth and division is critical to produce reliable predictions of safety risks along the food chain. Individual-based modeling of bacteria provides the theoretical framework to deal with this variability, but it requires information about the individual behavior of bacteria inside populations. In this work, we overcome this problem by estimating the individual behavior of bacteria from population statistics obtained with flow cytometry. For this objective, a stochastic individual-based modeling framework is defined based on standard assumptions during division and exponential growth. The unknown single-cell parameters required for running the individual-based modeling simulations, such as cell size growth rate, are estimated from the flow cytometry data. Instead of using directly the individual-based model, we make use of a modified Fokker-Plank equation. This only equation simulates the population statistics in function of the unknown single-cell parameters. We test the validity of the approach by modeling the growth and division of Pediococcus acidilactici within the exponential phase. Estimations reveal the statistics of cell growth and division using only data from flow cytometry at a given time. From the relationship between the mother and daughter volumes, we also predict that P. acidilactici divide into two successive parallel planes.

Group prioritisation with unknown expert weights in incomplete linguistic context

NASA Astrophysics Data System (ADS)

Cheng, Dong; Cheng, Faxin; Zhou, Zhili; Wang, Juan

2017-09-01

In this paper, we study a group prioritisation problem in situations when the expert weights are completely unknown and their judgement preferences are linguistic and incomplete. Starting from the theory of relative entropy (RE) and multiplicative consistency, an optimisation model is provided for deriving an individual priority vector without estimating the missing value(s) of an incomplete linguistic preference relation. In order to address the unknown expert weights in the group aggregating process, we define two new kinds of expert weight indicators based on RE: proximity entropy weight and similarity entropy weight. Furthermore, a dynamic-adjusting algorithm (DAA) is proposed to obtain an objective expert weight vector and capture the dynamic properties involved in it. Unlike the extant literature of group prioritisation, the proposed RE approach does not require pre-allocation of expert weights and can solve incomplete preference relations. An interesting finding is that once all the experts express their preference relations, the final expert weight vector derived from the DAA is fixed irrespective of the initial settings of expert weights. Finally, an application example is conducted to validate the effectiveness and robustness of the RE approach.

Implementing a Bayes Filter in a Neural Circuit: The Case of Unknown Stimulus Dynamics.

PubMed

Sokoloski, Sacha

2017-09-01

In order to interact intelligently with objects in the world, animals must first transform neural population responses into estimates of the dynamic, unknown stimuli that caused them. The Bayesian solution to this problem is known as a Bayes filter, which applies Bayes' rule to combine population responses with the predictions of an internal model. The internal model of the Bayes filter is based on the true stimulus dynamics, and in this note, we present a method for training a theoretical neural circuit to approximately implement a Bayes filter when the stimulus dynamics are unknown. To do this we use the inferential properties of linear probabilistic population codes to compute Bayes' rule and train a neural network to compute approximate predictions by the method of maximum likelihood. In particular, we perform stochastic gradient descent on the negative log-likelihood of the neural network parameters with a novel approximation of the gradient. We demonstrate our methods on a finite-state, a linear, and a nonlinear filtering problem and show how the hidden layer of the neural network develops tuning curves consistent with findings in experimental neuroscience.

Model-based pH monitor for sensor assessment.

PubMed

van Schagen, Kim; Rietveld, Luuk; Veersma, Alex; Babuska, Robert

2009-01-01

Owing to the nature of the treatment processes, monitoring the processes based on individual online measurements is difficult or even impossible. However, the measurements (online and laboratory) can be combined with a priori process knowledge, using mathematical models, to objectively monitor the treatment processes and measurement devices. The pH measurement is a commonly used measurement at different stages in the drinking water treatment plant, although it is a unreliable instrument, requiring significant maintenance. It is shown that, using a grey-box model, it is possible to assess the measurement devices effectively, even if detailed information of the specific processes is unknown.

Path Planning for Robot based on Chaotic Artificial Potential Field Method

NASA Astrophysics Data System (ADS)

Zhang, Cheng

2018-03-01

Robot path planning in unknown environments is one of the hot research topics in the field of robot control. Aiming at the shortcomings of traditional artificial potential field methods, we propose a new path planning for Robot based on chaotic artificial potential field method. The path planning adopts the potential function as the objective function and introduces the robot direction of movement as the control variables, which combines the improved artificial potential field method with chaotic optimization algorithm. Simulations have been carried out and the results demonstrate that the superior practicality and high efficiency of the proposed method.

Incoherent coincidence imaging of space objects

NASA Astrophysics Data System (ADS)

Mao, Tianyi; Chen, Qian; He, Weiji; Gu, Guohua

2016-10-01

Incoherent Coincidence Imaging (ICI), which is based on the second or higher order correlation of fluctuating light field, has provided great potentialities with respect to standard conventional imaging. However, the deployment of reference arm limits its practical applications in the detection of space objects. In this article, an optical aperture synthesis with electronically connected single-pixel photo-detectors was proposed to remove the reference arm. The correlation in our proposed method is the second order correlation between the intensity fluctuations observed by any two detectors. With appropriate locations of single-pixel detectors, this second order correlation is simplified to absolute-square Fourier transform of source and the unknown object. We demonstrate the image recovery with the Gerchberg-Saxton-like algorithms and investigate the reconstruction quality of our approach. Numerical experiments has been made to show that both binary and gray-scale objects can be recovered. This proposed method provides an effective approach to promote detection of space objects and perhaps even the exo-planets.

Exploration of mineral resource deposits based on analysis of aerial and satellite image data employing artificial intelligence methods

NASA Astrophysics Data System (ADS)

Osipov, Gennady

2013-04-01

We propose a solution to the problem of exploration of various mineral resource deposits, determination of their forms / classification of types (oil, gas, minerals, gold, etc.) with the help of satellite photography of the region of interest. Images received from satellite are processed and analyzed to reveal the presence of specific signs of deposits of various minerals. Course of data processing and making forecast can be divided into some stages: Pre-processing of images. Normalization of color and luminosity characteristics, determination of the necessary contrast level and integration of a great number of separate photos into a single map of the region are performed. Construction of semantic map image. Recognition of bitmapped image and allocation of objects and primitives known to system are realized. Intelligent analysis. At this stage acquired information is analyzed with the help of a knowledge base, which contain so-called "attention landscapes" of experts. Used methods of recognition and identification of images: a) combined method of image recognition, b)semantic analysis of posterized images, c) reconstruction of three-dimensional objects from bitmapped images, d)cognitive technology of processing and interpretation of images. This stage is fundamentally new and it distinguishes suggested technology from all others. Automatic registration of allocation of experts` attention - registration of so-called "attention landscape" of experts - is the base of the technology. Landscapes of attention are, essentially, highly effective filters that cut off unnecessary information and emphasize exactly the factors used by an expert for making a decision. The technology based on denoted principles involves the next stages, which are implemented in corresponding program agents. Training mode -> Creation of base of ophthalmologic images (OI) -> Processing and making generalized OI (GOI) -> Mode of recognition and interpretation of unknown images. Training mode includes noncontact registration of eye motion, reconstruction of "attention landscape" fixed by the expert, recording the comments of the expert who is a specialist in the field of images` interpretation, and transfer this information into knowledge base.Creation of base of ophthalmologic images (OI) includes making semantic contacts from great number of OI based on analysis of OI and expert's comments.Processing of OI and making generalized OI (GOI) is realized by inductive logic algorithms and consists in synthesis of structural invariants of OI. The mode of recognition and interpretation of unknown images consists of several stages, which include: comparison of unknown image with the base of structural invariants of OI; revealing of structural invariants in unknown images; ynthesis of interpretive message of the structural invariants base and OI base (the experts` comments stored in it). We want to emphasize that the training mode does not assume special involvement of experts to teach the system - it is realized in the process of regular experts` work on image interpretation and it becomes possible after installation of a special apparatus for non contact registration of experts` attention. Consequently, the technology, which principles is described there, provides fundamentally new effective solution to the problem of exploration of mineral resource deposits based on computer analysis of aerial and satellite image data.

Segmentation-free statistical image reconstruction for polyenergetic x-ray computed tomography with experimental validation.

PubMed

Idris A, Elbakri; Fessler, Jeffrey A

2003-08-07

This paper describes a statistical image reconstruction method for x-ray CT that is based on a physical model that accounts for the polyenergetic x-ray source spectrum and the measurement nonlinearities caused by energy-dependent attenuation. Unlike our earlier work, the proposed algorithm does not require pre-segmentation of the object into the various tissue classes (e.g., bone and soft tissue) and allows mixed pixels. The attenuation coefficient of each voxel is modelled as the product of its unknown density and a weighted sum of energy-dependent mass attenuation coefficients. We formulate a penalized-likelihood function for this polyenergetic model and develop an iterative algorithm for estimating the unknown density of each voxel. Applying this method to simulated x-ray CT measurements of objects containing both bone and soft tissue yields images with significantly reduced beam hardening artefacts relative to conventional beam hardening correction methods. We also apply the method to real data acquired from a phantom containing various concentrations of potassium phosphate solution. The algorithm reconstructs an image with accurate density values for the different concentrations, demonstrating its potential for quantitative CT applications.

An exploratory analysis of task-interspersal procedures while teaching object labels to children with autism.

PubMed

Volkert, Valerie M; Lerman, Dorothea C; Trosclair, Nicole; Addison, Laura; Kodak, Tiffany

2008-01-01

Research has demonstrated that interspersing mastered tasks with new tasks facilitates learning under certain conditions; however, little is known about factors that influence the effectiveness of this treatment strategy. The initial purpose of the current investigation was to evaluate the effects of similar versus dissimilar interspersed tasks while teaching object labels to children diagnosed with autism or developmental delays. We then conducted a series of exploratory analyses involving the type of reinforcer delivered for correct responses on trials with unknown or known object labels. Performance was enhanced under the interspersal condition only when either brief praise was delivered for all correct responses or presumably more preferred reinforcers were provided for performance on known trials rather than on unknown trials.

Self-Organized Behavior Generation for Musculoskeletal Robots.

PubMed

Der, Ralf; Martius, Georg

2017-01-01

With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object's identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors "waiting" to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self-learning robot not only generate interesting and potentially useful behaviors, but may also help to better understand what subjective human muscle feelings are, how they can be rooted in sensorimotor patterns, and how these concepts may feed back on robotics.

Self-Organized Behavior Generation for Musculoskeletal Robots

PubMed Central

Der, Ralf; Martius, Georg

2017-01-01

With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object's identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors “waiting” to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self-learning robot not only generate interesting and potentially useful behaviors, but may also help to better understand what subjective human muscle feelings are, how they can be rooted in sensorimotor patterns, and how these concepts may feed back on robotics. PMID:28360852

Monocular depth perception using image processing and machine learning

NASA Astrophysics Data System (ADS)

Hombali, Apoorv; Gorde, Vaibhav; Deshpande, Abhishek

2011-10-01

This paper primarily exploits some of the more obscure, but inherent properties of camera and image to propose a simpler and more efficient way of perceiving depth. The proposed method involves the use of a single stationary camera at an unknown perspective and an unknown height to determine depth of an object on unknown terrain. In achieving so a direct correlation between a pixel in an image and the corresponding location in real space has to be formulated. First, a calibration step is undertaken whereby the equation of the plane visible in the field of view is calculated along with the relative distance between camera and plane by using a set of derived spatial geometrical relations coupled with a few intrinsic properties of the system. The depth of an unknown object is then perceived by first extracting the object under observation using a series of image processing steps followed by exploiting the aforementioned mapping of pixel and real space coordinate. The performance of the algorithm is greatly enhanced by the introduction of reinforced learning making the system independent of hardware and environment. Furthermore the depth calculation function is modified with a supervised learning algorithm giving consistent improvement in results. Thus, the system uses the experience in past and optimizes the current run successively. Using the above procedure a series of experiments and trials are carried out to prove the concept and its efficacy.

Spike Timing Matters in Novel Neuronal Code Involved in Vibrotactile Frequency Perception.

PubMed

Birznieks, Ingvars; Vickery, Richard M

2017-05-22

Skin vibrations sensed by tactile receptors contribute significantly to the perception of object properties during tactile exploration [1-4] and to sensorimotor control during object manipulation [5]. Sustained low-frequency skin vibration (<60 Hz) evokes a distinct tactile sensation referred to as flutter whose frequency can be clearly perceived [6]. How afferent spiking activity translates into the perception of frequency is still unknown. Measures based on mean spike rates of neurons in the primary somatosensory cortex are sufficient to explain performance in some frequency discrimination tasks [7-11]; however, there is emerging evidence that stimuli can be distinguished based also on temporal features of neural activity [12, 13]. Our study's advance is to demonstrate that temporal features are fundamental for vibrotactile frequency perception. Pulsatile mechanical stimuli were used to elicit specified temporal spike train patterns in tactile afferents, and subsequently psychophysical methods were employed to characterize human frequency perception. Remarkably, the most salient temporal feature determining vibrotactile frequency was not the underlying periodicity but, rather, the duration of the silent gap between successive bursts of neural activity. This burst gap code for frequency represents a previously unknown form of neural coding in the tactile sensory system, which parallels auditory pitch perception mechanisms based on purely temporal information where longer inter-pulse intervals receive higher perceptual weights than short intervals [14]. Our study also demonstrates that human perception of stimuli can be determined exclusively by temporal features of spike trains independent of the mean spike rate and without contribution from population response factors. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neural Network Based Sensory Fusion for Landmark Detection

NASA Technical Reports Server (NTRS)

Kumbla, Kishan -K.; Akbarzadeh, Mohammad R.

1997-01-01

NASA is planning to send numerous unmanned planetary missions to explore the space. This requires autonomous robotic vehicles which can navigate in an unstructured, unknown, and uncertain environment. Landmark based navigation is a new area of research which differs from the traditional goal-oriented navigation, where a mobile robot starts from an initial point and reaches a destination in accordance with a pre-planned path. The landmark based navigation has the advantage of allowing the robot to find its way without communication with the mission control station and without exact knowledge of its coordinates. Current algorithms based on landmark navigation however pose several constraints. First, they require large memories to store the images. Second, the task of comparing the images using traditional methods is computationally intensive and consequently real-time implementation is difficult. The method proposed here consists of three stages, First stage utilizes a heuristic-based algorithm to identify significant objects. The second stage utilizes a neural network (NN) to efficiently classify images of the identified objects. The third stage combines distance information with the classification results of neural networks for efficient and intelligent navigation.

Cognitive learning during surgical residency. A model for curriculum evaluation.

PubMed

Rhodes, R S; Wile, M Z; Persons, M L; Shuck, J M

1987-02-01

The program summary of the American Board of Surgery In-Service Training Exam (ABSITE) can be used to quantitate cognitive learning during a surgical residency and to identify areas of curricular weakness in a residency program. Knowledge on each question is categorized as high (known) or low (unknown) depending on the percentage of residents who answered correctly. Knowledge of Level 1 (entry) residents is then compared with Level 5 (exit) residents. Each ABSITE question can thus be categorized on entry versus exit as known-known, unknown-unknown, unknown-known, and known-unknown. Only about half of unknown knowledge on entry appears to become known on exit. Very little knowledge known on entry becomes unknown on exit. Weaknesses in specific subject areas can be readily identified by ranking questions according to the number of exiting residents who answer incorrectly. Use of this technique to quantitate cognitive learning in a residency program may allow objective assessment of changes in curriculum.

ADART: an adaptive algebraic reconstruction algorithm for discrete tomography.

PubMed

Maestre-Deusto, F Javier; Scavello, Giovanni; Pizarro, Joaquín; Galindo, Pedro L

2011-08-01

In this paper we suggest an algorithm based on the Discrete Algebraic Reconstruction Technique (DART) which is capable of computing high quality reconstructions from substantially fewer projections than required for conventional continuous tomography. Adaptive DART (ADART) goes a step further than DART on the reduction of the number of unknowns of the associated linear system achieving a significant reduction in the pixel error rate of reconstructed objects. The proposed methodology automatically adapts the border definition criterion at each iteration, resulting in a reduction of the number of pixels belonging to the border, and consequently of the number of unknowns in the general algebraic reconstruction linear system to be solved, being this reduction specially important at the final stage of the iterative process. Experimental results show that reconstruction errors are considerably reduced using ADART when compared to original DART, both in clean and noisy environments.

Planar maneuvering control of underwater snake robots using virtual holonomic constraints.

PubMed

Kohl, Anna M; Kelasidi, Eleni; Mohammadi, Alireza; Maggiore, Manfredi; Pettersen, Kristin Y

2016-11-24

This paper investigates the problem of planar maneuvering control for bio-inspired underwater snake robots that are exposed to unknown ocean currents. The control objective is to make a neutrally buoyant snake robot which is subject to hydrodynamic forces and ocean currents converge to a desired planar path and traverse the path with a desired velocity. The proposed feedback control strategy enforces virtual constraints which encode biologically inspired gaits on the snake robot configuration. The virtual constraints, parametrized by states of dynamic compensators, are used to regulate the orientation and forward speed of the snake robot. A two-state ocean current observer based on relative velocity sensors is proposed. It enables the robot to follow the path in the presence of unknown constant ocean currents. The efficacy of the proposed control algorithm for several biologically inspired gaits is verified both in simulations for different path geometries and in experiments.

An Exploratory Analysis of Task-Interspersal Procedures While Teaching Object Labels to Children with Autism

PubMed Central

Volkert, Valerie M; Lerman, Dorothea C; Trosclair, Nicole; Addison, Laura; Kodak, Tiffany

2008-01-01

Research has demonstrated that interspersing mastered tasks with new tasks facilitates learning under certain conditions; however, little is known about factors that influence the effectiveness of this treatment strategy. The initial purpose of the current investigation was to evaluate the effects of similar versus dissimilar interspersed tasks while teaching object labels to children diagnosed with autism or developmental delays. We then conducted a series of exploratory analyses involving the type of reinforcer delivered for correct responses on trials with unknown or known object labels. Performance was enhanced under the interspersal condition only when either brief praise was delivered for all correct responses or presumably more preferred reinforcers were provided for performance on known trials rather than on unknown trials. PMID:18816973

Selective attention increases choice certainty in human decision making.

PubMed

Zizlsperger, Leopold; Sauvigny, Thomas; Haarmeier, Thomas

2012-01-01

Choice certainty is a probabilistic estimate of past performance and expected outcome. In perceptual decisions the degree of confidence correlates closely with choice accuracy and reaction times, suggesting an intimate relationship to objective performance. Here we show that spatial and feature-based attention increase human subjects' certainty more than accuracy in visual motion discrimination tasks. Our findings demonstrate for the first time a dissociation of choice accuracy and certainty with a significantly stronger influence of voluntary top-down attention on subjective performance measures than on objective performance. These results reveal a so far unknown mechanism of the selection process implemented by attention and suggest a unique biological valence of choice certainty beyond a faithful reflection of the decision process.

Observer-based distributed adaptive fault-tolerant containment control of multi-agent systems with general linear dynamics.

PubMed

Ye, Dan; Chen, Mengmeng; Li, Kui

2017-11-01

In this paper, we consider the distributed containment control problem of multi-agent systems with actuator bias faults based on observer method. The objective is to drive the followers into the convex hull spanned by the dynamic leaders, where the input is unknown but bounded. By constructing an observer to estimate the states and bias faults, an effective distributed adaptive fault-tolerant controller is developed. Different from the traditional method, an auxiliary controller gain is designed to deal with the unknown inputs and bias faults together. Moreover, the coupling gain can be adjusted online through the adaptive mechanism without using the global information. Furthermore, the proposed control protocol can guarantee that all the signals of the closed-loop systems are bounded and all the followers converge to the convex hull with bounded residual errors formed by the dynamic leaders. Finally, a decoupled linearized longitudinal motion model of the F-18 aircraft is used to demonstrate the effectiveness. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A Computational Model of Spatial Development

NASA Astrophysics Data System (ADS)

Hiraki, Kazuo; Sashima, Akio; Phillips, Steven

Psychological experiments on children's development of spatial knowledge suggest experience at self-locomotion with visual tracking as important factors. Yet, the mechanism underlying development is unknown. We propose a robot that learns to mentally track a target object (i.e., maintaining a representation of an object's position when outside the field-of-view) as a model for spatial development. Mental tracking is considered as prediction of an object's position given the previous environmental state and motor commands, and the current environment state resulting from movement. Following Jordan & Rumelhart's (1992) forward modeling architecture the system consists of two components: an inverse model of sensory input to desired motor commands; and a forward model of motor commands to desired sensory input (goals). The robot was tested on the `three cups' paradigm (where children are required to select the cup containing the hidden object under various movement conditions). Consistent with child development, without the capacity for self-locomotion the robot's errors are self-center based. When given the ability of self-locomotion the robot responds allocentrically.

Optical Reflection Spectroscopy of GEO Objects

NASA Technical Reports Server (NTRS)

Seitzer, Patrick; Cardona, Tammaso; Lederer, Susan M.; Cowardin, Heather; Abercromby, Kira J.; Barker, Edwin S.; Bedard, Donald

2013-01-01

We report on optical reflection spectroscopy of geosynchronous (GEO) objects in the US Space Surveillance Network (SSN) catalog. These observations were obtained using imaging spectrographs on the 6.5-m Magellan telescopes at the Las Campanas Observatory in Chile. Our goal is to determine the composition of these objects by comparing these spectral observations with ground-based laboratory measurements of spacecraft materials. The observations are all low resolution (1 nm after smoothing) obtained through a 5 arcsecond wide slit and using a grism as the dispersing element. The spectral range covered was from 450 nm to 800 nm. All spectra were flux calibrated using observations of standard stars with the exact same instrumental setup. An effort was made to obtain all observations within a limited range of topocentric phase angle, although the solar incident angle is unknown due to the lack of any knowledge of the attitude of the observed surface at the time of observation.

Identification of Interesting Objects in Large Spectral Surveys Using Highly Parallelized Machine Learning

NASA Astrophysics Data System (ADS)

Škoda, Petr; Palička, Andrej; Koza, Jakub; Shakurova, Ksenia

2017-06-01

The current archives of LAMOST multi-object spectrograph contain millions of fully reduced spectra, from which the automatic pipelines have produced catalogues of many parameters of individual objects, including their approximate spectral classification. This is, however, mostly based on the global shape of the whole spectrum and on integral properties of spectra in given bandpasses, namely presence and equivalent width of prominent spectral lines, while for identification of some interesting object types (e.g. Be stars or quasars) the detailed shape of only a few lines is crucial. Here the machine learning is bringing a new methodology capable of improving the reliability of classification of such objects even in boundary cases. We present results of Spark-based semi-supervised machine learning of LAMOST spectra attempting to automatically identify the single and double-peak emission of Hα line typical for Be and B[e] stars. The labelled sample was obtained from archive of 2m Perek telescope at Ondřejov observatory. A simple physical model of spectrograph resolution was used in domain adaptation to LAMOST training domain. The resulting list of candidates contains dozens of Be stars (some are likely yet unknown), but also a bunch of interesting objects resembling spectra of quasars and even blazars, as well as many instrumental artefacts. The verification of a nature of interesting candidates benefited considerably from cross-matching and visualisation in the Virtual Observatory environment.

Mathematical Methods of Subjective Modeling in Scientific Research: I. The Mathematical and Empirical Basis

NASA Astrophysics Data System (ADS)

Pyt'ev, Yu. P.

2018-01-01

mathematical formalism for subjective modeling, based on modelling of uncertainty, reflecting unreliability of subjective information and fuzziness that is common for its content. The model of subjective judgments on values of an unknown parameter x ∈ X of the model M( x) of a research object is defined by the researcher-modeler as a space1 ( X, p( X), P{I^{\\bar x}}, Be{l^{\\bar x}}) with plausibility P{I^{\\bar x}} and believability Be{l^{\\bar x}} measures, where x is an uncertain element taking values in X that models researcher—modeler's uncertain propositions about an unknown x ∈ X, measures P{I^{\\bar x}}, Be{l^{\\bar x}} model modalities of a researcher-modeler's subjective judgments on the validity of each x ∈ X: the value of P{I^{\\bar x}}(\\tilde x = x) determines how relatively plausible, in his opinion, the equality (\\tilde x = x) is, while the value of Be{l^{\\bar x}}(\\tilde x = x) determines how the inequality (\\tilde x = x) should be relatively believed in. Versions of plausibility Pl and believability Bel measures and pl- and bel-integrals that inherit some traits of probabilities, psychophysics and take into account interests of researcher-modeler groups are considered. It is shown that the mathematical formalism of subjective modeling, unlike "standard" mathematical modeling, •enables a researcher-modeler to model both precise formalized knowledge and non-formalized unreliable knowledge, from complete ignorance to precise knowledge of the model of a research object, to calculate relative plausibilities and believabilities of any features of a research object that are specified by its subjective model M(\\tilde x), and if the data on observations of a research object is available, then it: •enables him to estimate the adequacy of subjective model to the research objective, to correct it by combining subjective ideas and the observation data after testing their consistency, and, finally, to empirically recover the model of a research object.

Solutions of large-scale electromagnetics problems involving dielectric objects with the parallel multilevel fast multipole algorithm.

PubMed

Ergül, Özgür

2011-11-01

Fast and accurate solutions of large-scale electromagnetics problems involving homogeneous dielectric objects are considered. Problems are formulated with the electric and magnetic current combined-field integral equation and discretized with the Rao-Wilton-Glisson functions. Solutions are performed iteratively by using the multilevel fast multipole algorithm (MLFMA). For the solution of large-scale problems discretized with millions of unknowns, MLFMA is parallelized on distributed-memory architectures using a rigorous technique, namely, the hierarchical partitioning strategy. Efficiency and accuracy of the developed implementation are demonstrated on very large problems involving as many as 100 million unknowns.

78 FR 50107 - Notice of Intent To Repatriate Cultural Items: University of Colorado Museum of Natural History...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-16

... organizations, has determined that the cultural items listed in this notice meet the definition of sacred... University of Colorado Museum of Natural History, Boulder, CO that meet the definition of sacred objects and.... Dr. Wheat acquired this item from an unknown individual. The sacred object and object of cultural...

Only Self-Generated Actions Create Sensori-Motor Systems in the Developing Brain

ERIC Educational Resources Information Center

James, Karin Harman; Swain, Shelley N.

2011-01-01

Previous research shows that sensory and motor systems interact during perception, but how these connections among systems are created during development is unknown. The current work exposes young children to novel "verbs" and objects through either (a) actively exploring the objects or (b) by seeing an experimenter interact with the objects.…

VLT/X-shooter Spectroscopy of a dusty planetary nebula discovered with Spitzer/IRS

NASA Astrophysics Data System (ADS)

Oliveira, I.; Overzier, R. A.; Pontoppidan, K. M.; van Dishoeck, E. F.; Spezzi, L.

2011-02-01

As part of a mid-infrared spectroscopic survey of young stars with the Spitzer Space Telescope, an unclassified red emission line object was discovered. Based on its high ionization state indicated by the Spitzer spectrum, this object could either be a dusty supernova remnant (SNR) or a planetary nebula (PN). In this research note, the object is classified and the available spectroscopic data are presented to the community for further analysis. UV/optical/NIR spectra were obtained during the science verification run of the VLT/X-shooter. A large number of emission lines are identified allowing the determination of the nature of this object. The presence of strong, narrow (Δv ~8 - 74 km s-1) emission lines, combined with very low line ratios of, e.g., [N ii]/Hα and [S ii]/Hα show that the object is a PN that lies at an undetermined distance behind the Serpens Molecular Cloud. This illustrates the potential of X-shooter as an efficient tool for constraining the nature of faint sources with unknown spectral properties or colors.

Visual object agnosia is associated with a breakdown of object-selective responses in the lateral occipital cortex.

PubMed

Ptak, Radek; Lazeyras, François; Di Pietro, Marie; Schnider, Armin; Simon, Stéphane R

2014-07-01

Patients with visual object agnosia fail to recognize the identity of visually presented objects despite preserved semantic knowledge. Object agnosia may result from damage to visual cortex lying close to or overlapping with the lateral occipital complex (LOC), a brain region that exhibits selectivity to the shape of visually presented objects. Despite this anatomical overlap the relationship between shape processing in the LOC and shape representations in object agnosia is unknown. We studied a patient with object agnosia following isolated damage to the left occipito-temporal cortex overlapping with the LOC. The patient showed intact processing of object structure, yet often made identification errors that were mainly based on the global visual similarity between objects. Using functional Magnetic Resonance Imaging (fMRI) we found that the damaged as well as the contralateral, structurally intact right LOC failed to show any object-selective fMRI activity, though the latter retained selectivity for faces. Thus, unilateral damage to the left LOC led to a bilateral breakdown of neural responses to a specific stimulus class (objects and artefacts) while preserving the response to a different stimulus class (faces). These findings indicate that representations of structure necessary for the identification of objects crucially rely on bilateral, distributed coding of shape features. Copyright © 2014 Elsevier Ltd. All rights reserved.

Online Object Tracking, Learning and Parsing with And-Or Graphs.

PubMed

Wu, Tianfu; Lu, Yang; Zhu, Song-Chun

2017-12-01

This paper presents a method, called AOGTracker, for simultaneously tracking, learning and parsing (TLP) of unknown objects in video sequences with a hierarchical and compositional And-Or graph (AOG) representation. The TLP method is formulated in the Bayesian framework with a spatial and a temporal dynamic programming (DP) algorithms inferring object bounding boxes on-the-fly. During online learning, the AOG is discriminatively learned using latent SVM [1] to account for appearance (e.g., lighting and partial occlusion) and structural (e.g., different poses and viewpoints) variations of a tracked object, as well as distractors (e.g., similar objects) in background. Three key issues in online inference and learning are addressed: (i) maintaining purity of positive and negative examples collected online, (ii) controling model complexity in latent structure learning, and (iii) identifying critical moments to re-learn the structure of AOG based on its intrackability. The intrackability measures uncertainty of an AOG based on its score maps in a frame. In experiments, our AOGTracker is tested on two popular tracking benchmarks with the same parameter setting: the TB-100/50/CVPR2013 benchmarks  , [3] , and the VOT benchmarks [4] -VOT 2013, 2014, 2015 and TIR2015 (thermal imagery tracking). In the former, our AOGTracker outperforms state-of-the-art tracking algorithms including two trackers based on deep convolutional network   [5] , [6] . In the latter, our AOGTracker outperforms all other trackers in VOT2013 and is comparable to the state-of-the-art methods in VOT2014, 2015 and TIR2015.

Translating Missions in James Worral's Game "Grand Theft Auto's Missions"

ERIC Educational Resources Information Center

Rahmi, Zelika

2018-01-01

The objectives of the study was to know the difficult words encountered by the gamers and to know their strategies in translating this unknown word. The researcher used interview as the instrument to collect the material needed for this particular study. It is found that unknown word combined with certain feeling such as disappointment creates…

Effects of alternative styles of risk information on EMF risk perception.

PubMed

Nielsen, Jesper Bo; Elstein, Arthur; Gyrd-Hansen, Dorte; Kildemoes, Helle Wallach; Kristiansen, Ivar Sønbø; Støvring, Henrik

2010-10-01

Risk scenarios characterized by exposures to new technologies with unknown health effects, together with limited appreciation of benefits pose a challenge to risk communication. The present report illustrates this situation through a study of the perceived risk from mobile phones and mobile masts in residential areas. Good information should objectively convey the current state of knowledge. The research question is then how to inform lay people so that they trust and understand the information. We used an Internet-based survey with 1687 Danish participants randomized to three types of information about radiation from mobile phones and masts. The objective was to study whether different types of information were rated as equally useful, informative, comprehensible, and trustworthy. Moreover, an important issue was whether information would influence risk perception and intended behavior. The conclusion is that lay people rate information about risks associated with a new and largely unknown technology more useful and trustworthy when provided with brief statements about how to handle the risk, rather than more lengthy technical information about why the technology may or may not entail health hazards. Further, the results demonstrate that information may increase concern among a large proportion of the population, and that discrepancies exist between expressed concern and intended behavior.

Neural-adaptive control of single-master-multiple-slaves teleoperation for coordinated multiple mobile manipulators with time-varying communication delays and input uncertainties.

PubMed

Li, Zhijun; Su, Chun-Yi

2013-09-01

In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties for multiple mobile manipulators carrying a common object in a cooperative manner. Firstly, concise dynamics of teleoperation systems consisting of a single master robot, multiple coordinated slave robots, and the object are developed in the task space. To handle asymmetric time-varying delays in communication channels and unknown asymmetric input dead zones, the nonlinear dynamics of the teleoperation system are transformed into two subsystems through feedback linearization: local master or slave dynamics including the unknown input dead zones and delayed dynamics for the purpose of synchronization. Then, a model reference neural network control strategy based on linear matrix inequalities (LMI) and adaptive techniques is proposed. The developed control approach ensures that the defined tracking errors converge to zero whereas the coordination internal force errors remain bounded and can be made arbitrarily small. Throughout this paper, stability analysis is performed via explicit Lyapunov techniques under specific LMI conditions. The proposed adaptive neural network control scheme is robust against motion disturbances, parametric uncertainties, time-varying delays, and input dead zones, which is validated by simulation studies.

How to Decide? Multi-Objective Early-Warning Monitoring Networks for Water Suppliers

NASA Astrophysics Data System (ADS)

Bode, Felix; Loschko, Matthias; Nowak, Wolfgang

2015-04-01

Groundwater is a resource for drinking water and hence needs to be protected from contaminations. However, many well catchments include an inventory of known and unknown risk sources, which cannot be eliminated, especially in urban regions. As a matter of risk control, all these risk sources should be monitored. A one-to-one monitoring situation for each risk source would lead to a cost explosion and is even impossible for unknown risk sources. However, smart optimization concepts could help to find promising low-cost monitoring network designs. In this work we develop a concept to plan monitoring networks using multi-objective optimization. Our considered objectives are to maximize the probability of detecting all contaminations, to enhance the early warning time before detected contaminations reach the drinking water well, and to minimize the installation and operating costs of the monitoring network. Using multi-objectives optimization, we avoid the problem of having to weight these objectives to a single objective-function. These objectives are clearly competing, and it is impossible to know their mutual trade-offs beforehand - each catchment differs in many points and it is hardly possible to transfer knowledge between geological formations and risk inventories. To make our optimization results more specific to the type of risk inventory in different catchments we do risk prioritization of all known risk sources. Due to the lack of the required data, quantitative risk ranking is impossible. Instead, we use a qualitative risk ranking to prioritize the known risk sources for monitoring. Additionally, we allow for the existence of unknown risk sources that are totally uncertain in location and in their inherent risk. Therefore, they can neither be located nor ranked. Instead, we represent them by a virtual line of risk sources surrounding the production well. We classify risk sources into four different categories: severe, medium and tolerable for known risk sources and an extra category for the unknown ones. With that, early warning time and detection probability become individual objectives for each risk class. Thus, decision makers can identify monitoring networks valid for controlling the top risk sources, and evaluate the capabilities (or search for least-cost upgrades) to also cover moderate, tolerable and unknown risk sources. Monitoring networks, which are valid for the remaining risk also cover all other risk sources, but only with a relatively poor early-warning time. The data provided for the optimization algorithm are calculated in a preprocessing step by a flow and transport model. It simulates, which potential contaminant plumes from the risk sources would be detectable where and when by all possible candidate positions for monitoring wells. Uncertainties due to hydro(geo)logical phenomena are taken into account by Monte-Carlo simulations. These include uncertainty in ambient flow direction of the groundwater, uncertainty of the conductivity field, and different scenarios for the pumping rates of the production wells. To avoid numerical dispersion during the transport simulations, we use particle-tracking random walk methods when simulating transport.

Exceptional Solar-System Objects

NASA Astrophysics Data System (ADS)

Zellner, Benjamin

1990-12-01

This is a target-of-opportunity proposal for HST observations to be executed if a previously unknown, truly exceptional solar-system object or phenomenon is discovered either in the normal course of HST work or by anyone, anywhere. Trails due to unknown moving objects will often appear on HST images made for other purposes. A short trail seen near the opposition point or at high ecliptic latitude could represent a major addition to our knowledge of the solar system. Thus we further propose that all short trials seen on HST images taken in favorable regions of the sky be given a quick analysis in the Observation Support System for their possible significance. If an unusual object is found we propose to: (1) Seek from the owner of data rights permission to proceed as may be appropriate; (2) Contact the Minor Planet Center for an evaluation of the significance of the discovery; and (3) For an object that appears to be of great significance where effective groundbased followup appears unlikely, request the HST schedule be replanned for followup images and physical studies using HST.

Subsurface classification of objects under turbid waters by means of regularization techniques applied to real hyperspectral data

NASA Astrophysics Data System (ADS)

Carpena, Emmanuel; Jiménez, Luis O.; Arzuaga, Emmanuel; Fonseca, Sujeily; Reyes, Ernesto; Figueroa, Juan

2017-05-01

Improved benthic habitat mapping is needed to monitor coral reefs around the world and to assist coastal zones management programs. A fundamental challenge to remotely sensed mapping of coastal shallow waters is due to the significant disparity in the optical properties of the water column caused by the interaction between the coast and the sea. The objects to be classified have weak signals that interact with turbid waters that include sediments. In real scenarios, the absorption and backscattering coefficients are unknown with different sources of variability (river discharges and coastal interactions). Under normal circumstances, another unknown variable is the depth of shallow waters. This paper presents the development of algorithms for retrieving information and its application to the classification and mapping of objects under coastal shallow waters with different unknown concentrations of sediments. A mathematical model that simplifies the radiative transfer equation was used to quantify the interaction between the object of interest, the medium and the sensor. The retrieval of information requires the development of mathematical models and processing tools in the area of inversion, image reconstruction and classification of hyperspectral data. The algorithms developed were applied to one set of real hyperspectral imagery taken in a tank filled with water and TiO2 that emulates turbid coastal shallow waters. Tikhonov method of regularization was used in the inversion process to estimate the bottom albedo of the water tank using a priori information in the form of stored spectral signatures, previously measured, of objects of interest.

If You're Not Measuring, You're Guessing: The Advent of Objective Concussion Assessments.

PubMed

Broglio, Steven P; Guskiewicz, Kevin M; Norwig, John

2017-03-01

Sport-related concussion remains one of the most complex injuries presented to sports medicine professionals. Although the injury has been recognized since ancient times, the concussion-assessment process has seen significant advances over the last 30 years. This review outlines the addition of objective measures to the clinical evaluation of the concussed athlete, beginning in the 1980s and continuing through the modern age. International and domestic organizations now describe standardized symptom reports, neurostatus and neurocognitive-function evaluations, and postural-control measures as standards of medical care, a significant shift from a short time ago. Despite this progression, much about the injury remains unknown, including new clinical and research-based assessment techniques and how the injury may influence the athlete's cognitive health over the long term.

Symbolic feature detection for image understanding

NASA Astrophysics Data System (ADS)

Aslan, Sinem; Akgül, Ceyhun Burak; Sankur, Bülent

2014-03-01

In this study we propose a model-driven codebook generation method used to assign probability scores to pixels in order to represent underlying local shapes they reside in. In the first version of the symbol library we limited ourselves to photometric and similarity transformations applied on eight prototypical shapes of flat plateau , ramp, valley, ridge, circular and elliptic respectively pit and hill and used randomized decision forest as the statistical classifier to compute shape class ambiguity of each pixel. We achieved90% accuracy in identification of known objects from alternate views, however, we could not outperform texture, global and local shape methods, but only color-based method in recognition of unknown objects. We present a progress plan to be accomplished as a future work to improve the proposed approach further.

Unified sensor management in unknown dynamic clutter

NASA Astrophysics Data System (ADS)

Mahler, Ronald; El-Fallah, Adel

2010-04-01

In recent years the first author has developed a unified, computationally tractable approach to multisensor-multitarget sensor management. This approach consists of closed-loop recursion of a PHD or CPHD filter with maximization of a "natural" sensor management objective function called PENT (posterior expected number of targets). In this paper we extend this approach so that it can be used in unknown, dynamic clutter backgrounds.

A robust approach towards unknown transformation, regional adjacency graphs, multigraph matching, segmentation video frames from unnamed aerial vehicles (UAV)

NASA Astrophysics Data System (ADS)

Gohatre, Umakant Bhaskar; Patil, Venkat P.

2018-04-01

In computer vision application, the multiple object detection and tracking, in real-time operation is one of the important research field, that have gained a lot of attentions, in last few years for finding non stationary entities in the field of image sequence. The detection of object is advance towards following the moving object in video and then representation of object is step to track. The multiple object recognition proof is one of the testing assignment from detection multiple objects from video sequence. The picture enrollment has been for quite some time utilized as a reason for the location the detection of moving multiple objects. The technique of registration to discover correspondence between back to back casing sets in view of picture appearance under inflexible and relative change. The picture enrollment is not appropriate to deal with event occasion that can be result in potential missed objects. In this paper, for address such problems, designs propose novel approach. The divided video outlines utilizing area adjancy diagram of visual appearance and geometric properties. Then it performed between graph sequences by using multi graph matching, then getting matching region labeling by a proposed graph coloring algorithms which assign foreground label to respective region. The plan design is robust to unknown transformation with significant improvement in overall existing work which is related to moving multiple objects detection in real time parameters.

Window-based method for approximating the Hausdorff in three-dimensional range imagery

DOEpatents

Koch, Mark W [Albuquerque, NM

2009-06-02

One approach to pattern recognition is to use a template from a database of objects and match it to a probe image containing the unknown. Accordingly, the Hausdorff distance can be used to measure the similarity of two sets of points. In particular, the Hausdorff can measure the goodness of a match in the presence of occlusion, clutter, and noise. However, existing 3D algorithms for calculating the Hausdorff are computationally intensive, making them impractical for pattern recognition that requires scanning of large databases. The present invention is directed to a new method that can efficiently, in time and memory, compute the Hausdorff for 3D range imagery. The method uses a window-based approach.

Results of the new processing of images obtained from the surface of Venus in a TV experiment onboard the VENERA-9 lander (1975)

NASA Astrophysics Data System (ADS)

Ksanfomality, L. V.

2012-09-01

Data on the results of the analysis of the content of re-processed panorama of the VENERA-9 lander are presented. The panorama was transmitted historically for the first time from the surface of Venus in 1975. The low noise of the VENERA-9 data allowed allocating a large object of an unusual regular structure. Earlier, its fuzzy image was repeatedly cited in the literature being interpreted as a "strange stone". The complex shape and its other features suggest that the object may be a real habitant of the planet. It is not excluded that another similar object observed was damaged during the VENERA-9 landing. From the evidence of its movement and position of some other similar objects it is concluded that because of the limited energy capacity, the physical action of the Venusian fauna may be much slower than that of the Earth fauna. Another question considered is what sources of energy could be used by life in the conditions of the high temperature oxygenless atmosphere of the planet. It is natural to assume that, like on Earth, the Venusian fauna is heterotrophic and should be based on hypothetical flora, using photosynthesis (based on an unknown high temperature biophysical mechanism).

Adaptive neural output-feedback control for nonstrict-feedback time-delay fractional-order systems with output constraints and actuator nonlinearities.

PubMed

Zouari, Farouk; Ibeas, Asier; Boulkroune, Abdesselem; Cao, Jinde; Mehdi Arefi, Mohammad

2018-06-01

This study addresses the issue of the adaptive output tracking control for a category of uncertain nonstrict-feedback delayed incommensurate fractional-order systems in the presence of nonaffine structures, unmeasured pseudo-states, unknown control directions, unknown actuator nonlinearities and output constraints. Firstly, the mean value theorem and the Gaussian error function are introduced to eliminate the difficulties that arise from the nonaffine structures and the unknown actuator nonlinearities, respectively. Secondly, the immeasurable tracking error variables are suitably estimated by constructing a fractional-order linear observer. Thirdly, the neural network, the Razumikhin Lemma, the variable separation approach, and the smooth Nussbaum-type function are used to deal with the uncertain nonlinear dynamics, the unknown time-varying delays, the nonstrict feedback and the unknown control directions, respectively. Fourthly, asymmetric barrier Lyapunov functions are employed to overcome the violation of the output constraints and to tune online the parameters of the adaptive neural controller. Through rigorous analysis, it is proved that the boundedness of all variables in the closed-loop system and the semi global asymptotic tracking are ensured without transgression of the constraints. The principal contributions of this study can be summarized as follows: (1) based on Caputo's definitions and new lemmas, methods concerning the controllability, observability and stability analysis of integer-order systems are extended to fractional-order ones, (2) the output tracking objective for a relatively large class of uncertain systems is achieved with a simple controller and less tuning parameters. Finally, computer-simulation studies from the robotic field are given to demonstrate the effectiveness of the proposed controller. Copyright © 2018 Elsevier Ltd. All rights reserved.

Verification of road databases using multiple road models

NASA Astrophysics Data System (ADS)

Ziems, Marcel; Rottensteiner, Franz; Heipke, Christian

2017-08-01

In this paper a new approach for automatic road database verification based on remote sensing images is presented. In contrast to existing methods, the applicability of the new approach is not restricted to specific road types, context areas or geographic regions. This is achieved by combining several state-of-the-art road detection and road verification approaches that work well under different circumstances. Each one serves as an independent module representing a unique road model and a specific processing strategy. All modules provide independent solutions for the verification problem of each road object stored in the database in form of two probability distributions, the first one for the state of a database object (correct or incorrect), and a second one for the state of the underlying road model (applicable or not applicable). In accordance with the Dempster-Shafer Theory, both distributions are mapped to a new state space comprising the classes correct, incorrect and unknown. Statistical reasoning is applied to obtain the optimal state of a road object. A comparison with state-of-the-art road detection approaches using benchmark datasets shows that in general the proposed approach provides results with larger completeness. Additional experiments reveal that based on the proposed method a highly reliable semi-automatic approach for road data base verification can be designed.

Do cultural factors affect causal beliefs? Rational and magical thinking in Britain and Mexico.

PubMed

Subbotsky, Eugene; Quinteros, Graciela

2002-11-01

In two experiments, unusual phenomena (spontaneous destruction of objects in an empty wooden box) were demonstrated to adult participants living in rural communities in Mexico. These were accompanied by actions which had no physical link to the destroyed object but could suggest either scientifically based (the effect of an unknown physical device) or non-scientifically based (the effect of a 'magic spell') causal explanations of the event. The results were compared to the results of the matching two experiments from the earlier study made in Britain. The expectation that scientifically based explanations would prevail in British participants' judgments and behaviours, whereas Mexican participants would be more tolerant toward magical explanations, received only partial support. The prevalence of scientific explanations over magical explanations was evident in British participants' verbal judgments but not in Mexican participants' judgments. In their behavioural responses under the low-risk condition, British participants rejected magical explanations more frequently than did Mexican participants. However, when the risk of disregarding the possible causal effect of magic was increased, participants in both samples showed an equal degree of credulity in the possible effect of magic. The data are interpreted in terms of the relationships between scientific and 'folk' representations of causality and object permanence.

Estimation of object motion parameters from noisy images.

PubMed

Broida, T J; Chellappa, R

1986-01-01

An approach is presented for the estimation of object motion parameters based on a sequence of noisy images. The problem considered is that of a rigid body undergoing unknown rotational and translational motion. The measurement data consists of a sequence of noisy image coordinates of two or more object correspondence points. By modeling the object dynamics as a function of time, estimates of the model parameters (including motion parameters) can be extracted from the data using recursive and/or batch techniques. This permits a desired degree of smoothing to be achieved through the use of an arbitrarily large number of images. Some assumptions regarding object structure are presently made. Results are presented for a recursive estimation procedure: the case considered here is that of a sequence of one dimensional images of a two dimensional object. Thus, the object moves in one transverse dimension, and in depth, preserving the fundamental ambiguity of the central projection image model (loss of depth information). An iterated extended Kalman filter is used for the recursive solution. Noise levels of 5-10 percent of the object image size are used. Approximate Cramer-Rao lower bounds are derived for the model parameter estimates as a function of object trajectory and noise level. This approach may be of use in situations where it is difficult to resolve large numbers of object match points, but relatively long sequences of images (10 to 20 or more) are available.

Cortical mechanisms for the segregation and representation of acoustic textures.

PubMed

Overath, Tobias; Kumar, Sukhbinder; Stewart, Lauren; von Kriegstein, Katharina; Cusack, Rhodri; Rees, Adrian; Griffiths, Timothy D

2010-02-10

Auditory object analysis requires two fundamental perceptual processes: the definition of the boundaries between objects, and the abstraction and maintenance of an object's characteristic features. Although it is intuitive to assume that the detection of the discontinuities at an object's boundaries precedes the subsequent precise representation of the object, the specific underlying cortical mechanisms for segregating and representing auditory objects within the auditory scene are unknown. We investigated the cortical bases of these two processes for one type of auditory object, an "acoustic texture," composed of multiple frequency-modulated ramps. In these stimuli, we independently manipulated the statistical rules governing (1) the frequency-time space within individual textures (comprising ramps with a given spectrotemporal coherence) and (2) the boundaries between textures (adjacent textures with different spectrotemporal coherences). Using functional magnetic resonance imaging, we show mechanisms defining boundaries between textures with different coherences in primary and association auditory cortices, whereas texture coherence is represented only in association cortex. Furthermore, participants' superior detection of boundaries across which texture coherence increased (as opposed to decreased) was reflected in a greater neural response in auditory association cortex at these boundaries. The results suggest a hierarchical mechanism for processing acoustic textures that is relevant to auditory object analysis: boundaries between objects are first detected as a change in statistical rules over frequency-time space, before a representation that corresponds to the characteristics of the perceived object is formed.

Real and virtual explorations of the environment and interactive tracking of movable objects for the blind on the basis of tactile-acoustical maps and 3D environment models.

PubMed

Hub, Andreas; Hartter, Tim; Kombrink, Stefan; Ertl, Thomas

2008-01-01

PURPOSE.: This study describes the development of a multi-functional assistant system for the blind which combines localisation, real and virtual navigation within modelled environments and the identification and tracking of fixed and movable objects. The approximate position of buildings is determined with a global positioning sensor (GPS), then the user establishes exact position at a specific landmark, like a door. This location initialises indoor navigation, based on an inertial sensor, a step recognition algorithm and map. Tracking of movable objects is provided by another inertial sensor and a head-mounted stereo camera, combined with 3D environmental models. This study developed an algorithm based on shape and colour to identify objects and used a common face detection algorithm to inform the user of the presence and position of others. The system allows blind people to determine their position with approximately 1 metre accuracy. Virtual exploration of the environment can be accomplished by moving one's finger on a touch screen of a small portable tablet PC. The name of rooms, building features and hazards, modelled objects and their positions are presented acoustically or in Braille. Given adequate environmental models, this system offers blind people the opportunity to navigate independently and safely, even within unknown environments. Additionally, the system facilitates education and rehabilitation by providing, in several languages, object names, features and relative positions.

ROOT.NET: Using ROOT from .NET languages like C# and F#

NASA Astrophysics Data System (ADS)

Watts, G.

2012-12-01

ROOT.NET provides an interface between Microsoft's Common Language Runtime (CLR) and .NET technology and the ubiquitous particle physics analysis tool, ROOT. ROOT.NET automatically generates a series of efficient wrappers around the ROOT API. Unlike pyROOT, these wrappers are statically typed and so are highly efficient as compared to the Python wrappers. The connection to .NET means that one gains access to the full series of languages developed for the CLR including functional languages like F# (based on OCaml). Many features that make ROOT objects work well in the .NET world are added (properties, IEnumerable interface, LINQ compatibility, etc.). Dynamic languages based on the CLR can be used as well, of course (Python, for example). Additionally it is now possible to access ROOT objects that are unknown to the translation tool. This poster will describe the techniques used to effect this translation, along with performance comparisons, and examples. All described source code is posted on the open source site CodePlex.

Machine learning for real time remote detection

NASA Astrophysics Data System (ADS)

Labbé, Benjamin; Fournier, Jérôme; Henaff, Gilles; Bascle, Bénédicte; Canu, Stéphane

2010-10-01

Infrared systems are key to providing enhanced capability to military forces such as automatic control of threats and prevention from air, naval and ground attacks. Key requirements for such a system to produce operational benefits are real-time processing as well as high efficiency in terms of detection and false alarm rate. These are serious issues since the system must deal with a large number of objects and categories to be recognized (small vehicles, armored vehicles, planes, buildings, etc.). Statistical learning based algorithms are promising candidates to meet these requirements when using selected discriminant features and real-time implementation. This paper proposes a new decision architecture benefiting from recent advances in machine learning by using an effective method for level set estimation. While building decision function, the proposed approach performs variable selection based on a discriminative criterion. Moreover, the use of level set makes it possible to manage rejection of unknown or ambiguous objects thus preserving the false alarm rate. Experimental evidences reported on real world infrared images demonstrate the validity of our approach.

Bayesian Abel Inversion in Quantitative X-Ray Radiography

DOE PAGES

Howard, Marylesa; Fowler, Michael; Luttman, Aaron; ...

2016-05-19

A common image formation process in high-energy X-ray radiography is to have a pulsed power source that emits X-rays through a scene, a scintillator that absorbs X-rays and uoresces in the visible spectrum in response to the absorbed photons, and a CCD camera that images the visible light emitted from the scintillator. The intensity image is related to areal density, and, for an object that is radially symmetric about a central axis, the Abel transform then gives the object's volumetric density. Two of the primary drawbacks to classical variational methods for Abel inversion are their sensitivity to the type andmore » scale of regularization chosen and the lack of natural methods for quantifying the uncertainties associated with the reconstructions. In this work we cast the Abel inversion problem within a statistical framework in order to compute volumetric object densities from X-ray radiographs and to quantify uncertainties in the reconstruction. A hierarchical Bayesian model is developed with a likelihood based on a Gaussian noise model and with priors placed on the unknown density pro le, the data precision matrix, and two scale parameters. This allows the data to drive the localization of features in the reconstruction and results in a joint posterior distribution for the unknown density pro le, the prior parameters, and the spatial structure of the precision matrix. Results of the density reconstructions and pointwise uncertainty estimates are presented for both synthetic signals and real data from a U.S. Department of Energy X-ray imaging facility.« less

Mapping land water and energy balance relations through conditional sampling of remote sensing estimates of atmospheric forcing and surface states

NASA Astrophysics Data System (ADS)

Farhadi, Leila; Entekhabi, Dara; Salvucci, Guido

2016-04-01

In this study, we develop and apply a mapping estimation capability for key unknown parameters that link the surface water and energy balance equations. The method is applied to the Gourma region in West Africa. The accuracy of the estimation method at point scale was previously examined using flux tower data. In this study, the capability is scaled to be applicable with remotely sensed data products and hence allow mapping. Parameters of the system are estimated through a process that links atmospheric forcing (precipitation and incident radiation), surface states, and unknown parameters. Based on conditional averaging of land surface temperature and moisture states, respectively, a single objective function is posed that measures moisture and temperature-dependent errors solely in terms of observed forcings and surface states. This objective function is minimized with respect to parameters to identify evapotranspiration and drainage models and estimate water and energy balance flux components. The uncertainty of the estimated parameters (and associated statistical confidence limits) is obtained through the inverse of Hessian of the objective function, which is an approximation of the covariance matrix. This calibration-free method is applied to the mesoscale region of Gourma in West Africa using multiplatform remote sensing data. The retrievals are verified against tower-flux field site data and physiographic characteristics of the region. The focus is to find the functional form of the evaporative fraction dependence on soil moisture, a key closure function for surface and subsurface heat and moisture dynamics, using remote sensing data.

An anti-disturbing real time pose estimation method and system

NASA Astrophysics Data System (ADS)

Zhou, Jian; Zhang, Xiao-hu

2011-08-01

Pose estimation relating two-dimensional (2D) images to three-dimensional (3D) rigid object need some known features to track. In practice, there are many algorithms which perform this task in high accuracy, but all of these algorithms suffer from features lost. This paper investigated the pose estimation when numbers of known features or even all of them were invisible. Firstly, known features were tracked to calculate pose in the current and the next image. Secondly, some unknown but good features to track were automatically detected in the current and the next image. Thirdly, those unknown features which were on the rigid and could match each other in the two images were retained. Because of the motion characteristic of the rigid object, the 3D information of those unknown features on the rigid could be solved by the rigid object's pose at the two moment and their 2D information in the two images except only two case: the first one was that both camera and object have no relative motion and camera parameter such as focus length, principle point, and etc. have no change at the two moment; the second one was that there was no shared scene or no matched feature in the two image. Finally, because those unknown features at the first time were known now, pose estimation could go on in the followed images in spite of the missing of known features in the beginning by repeating the process mentioned above. The robustness of pose estimation by different features detection algorithms such as Kanade-Lucas-Tomasi (KLT) feature, Scale Invariant Feature Transform (SIFT) and Speed Up Robust Feature (SURF) were compared and the compact of the different relative motion between camera and the rigid object were discussed in this paper. Graphic Processing Unit (GPU) parallel computing was also used to extract and to match hundreds of features for real time pose estimation which was hard to work on Central Processing Unit (CPU). Compared with other pose estimation methods, this new method can estimate pose between camera and object when part even all known features are lost, and has a quick response time benefit from GPU parallel computing. The method present here can be used widely in vision-guide techniques to strengthen its intelligence and generalization, which can also play an important role in autonomous navigation and positioning, robots fields at unknown environment. The results of simulation and experiments demonstrate that proposed method could suppress noise effectively, extracted features robustly, and achieve the real time need. Theory analysis and experiment shows the method is reasonable and efficient.

The Role of Binocular Disparity in Stereoscopic Images of Objects in the Macaque Anterior Intraparietal Area

PubMed Central

Romero, Maria C.; Van Dromme, Ilse C. L.; Janssen, Peter

2013-01-01

Neurons in the macaque Anterior Intraparietal area (AIP) encode depth structure in random-dot stimuli defined by gradients of binocular disparity, but the importance of binocular disparity in real-world objects for AIP neurons is unknown. We investigated the effect of binocular disparity on the responses of AIP neurons to images of real-world objects during passive fixation. We presented stereoscopic images of natural and man-made objects in which the disparity information was congruent or incongruent with disparity gradients present in the real-world objects, and images of the same objects where such gradients were absent. Although more than half of the AIP neurons were significantly affected by binocular disparity, the great majority of AIP neurons remained image selective even in the absence of binocular disparity. AIP neurons tended to prefer stimuli in which the depth information derived from binocular disparity was congruent with the depth information signaled by monocular depth cues, indicating that these monocular depth cues have an influence upon AIP neurons. Finally, in contrast to neurons in the inferior temporal cortex, AIP neurons do not represent images of objects in terms of categories such as animate-inanimate, but utilize representations based upon simple shape features including aspect ratio. PMID:23408970

Generating Complaint Motion of Objects with an Articulated Hand

DTIC Science & Technology

1985-06-01

we consider the motions of rigid objects as the solhtions to a con- straint problem. We will examine the task of manipulation in the context of...describe the motion of a rigid object is equivalent to specifying sufficient constraint equations on these unknowns such that they are uniquely...assumption of rigidity . When a rigid object is constrained by a set of contacts, its motion must be consistent with those of the contacts, i.e. its

Differential efficacy of human mesenchymal stem cells based on source of origin

PubMed Central

Collins, Erin; Gu, Fei; Qi, Maosong; Molano, Ivan; Ruiz, Phillip; Sun, Linyun; Gilkeson, Gary S.

2014-01-01

Mesenchymal stem cells (MSCs) are useful in tissue repair, but also possess immunomodulatory properties. Murine and uncontrolled human trials suggest efficacy of MSCs in treating lupus. Autologous cells are preferable, however, recent studies suggest that lupus derived MSCs lack efficacy in treating disease. Thus, the optimum derivation of MSCs for use in lupus is unknown. It is also unknown which in vitro assays of MSC function predict in vivo efficacy. The objectives for this study were to provide insight into the optimum source of MSCs and to identify in vitro assays that predict in vivo efficacy. We derived MSCs from four umbilical cords (UC), four healthy bone marrows (HBM) and four lupus bone marrows (LBM). In diseased MRL/lpr mice, MSCs from HBM and UC significantly decreased renal disease, while LBM-MSCs only delayed disease. Current in vitro assays did not differentiate efficacy of the different MSCs. Inhibition of B cell proliferation did differentiate based on efficacy. Our results suggest that autologous MSCs from lupus patients are not effective in treating disease. Furthermore, standard in vitro assays for MSC licensing are not predictive of in vivo efficacy, while inhibiting B cell proliferation appears to differentiate effective from ineffective MSCs. PMID:25274529

Joint Geophysical Inversion With Multi-Objective Global Optimization Methods

NASA Astrophysics Data System (ADS)

Lelievre, P. G.; Bijani, R.; Farquharson, C. G.

2015-12-01

Pareto multi-objective global optimization (PMOGO) methods generate a suite of solutions that minimize multiple objectives (e.g. data misfits and regularization terms) in a Pareto-optimal sense. Providing a suite of models, as opposed to a single model that minimizes a weighted sum of objectives, allows a more complete assessment of the possibilities and avoids the often difficult choice of how to weight each objective. We are applying PMOGO methods to three classes of inverse problems. The first class are standard mesh-based problems where the physical property values in each cell are treated as continuous variables. The second class of problems are also mesh-based but cells can only take discrete physical property values corresponding to known or assumed rock units. In the third class we consider a fundamentally different type of inversion in which a model comprises wireframe surfaces representing contacts between rock units; the physical properties of each rock unit remain fixed while the inversion controls the position of the contact surfaces via control nodes. This third class of problem is essentially a geometry inversion, which can be used to recover the unknown geometry of a target body or to investigate the viability of a proposed Earth model. Joint inversion is greatly simplified for the latter two problem classes because no additional mathematical coupling measure is required in the objective function. PMOGO methods can solve numerically complicated problems that could not be solved with standard descent-based local minimization methods. This includes the latter two classes of problems mentioned above. There are significant increases in the computational requirements when PMOGO methods are used but these can be ameliorated using parallelization and problem dimension reduction strategies.

Do domestic dogs learn words based on humans' referential behaviour?

PubMed

Tempelmann, Sebastian; Kaminski, Juliane; Tomasello, Michael

2014-01-01

Some domestic dogs learn to comprehend human words, although the nature and basis of this learning is unknown. In the studies presented here we investigated whether dogs learn words through an understanding of referential actions by humans rather than simple association. In three studies, each modelled on a study conducted with human infants, we confronted four word-experienced dogs with situations involving no spatial-temporal contiguity between the word and the referent; the only available cues were referential actions displaced in time from exposure to their referents. We found that no dogs were able to reliably link an object with a label based on social-pragmatic cues alone in all the tests. However, one dog did show skills in some tests, possibly indicating an ability to learn based on social-pragmatic cues.

Watch the hands: infants can learn to follow gaze by seeing adults manipulate objects.

PubMed

Deák, Gedeon O; Krasno, Anna M; Triesch, Jochen; Lewis, Joshua; Sepeta, Leigh

2014-03-01

Infants gradually learn to share attention, but it is unknown how they acquire skills such as gaze-following. Deák and Triesch (2006) suggest that gaze-following could be acquired if infants learn that adults' gaze direction is likely to be aligned with interesting sights. This hypothesis stipulates that adults tend to look at things that infants find interesting, and that infants could learn by noticing this tendency. We tested the plausibility of this hypothesis through video-based micro-behavioral analysis of naturalistic parent-infant play. The results revealed that 3- to 11-month-old infants strongly preferred watching caregivers handle objects. In addition, when caregivers looked away from their infant they tended to look at their own object-handling. Finally, when infants looked toward the caregiver while she was looking at her own hands, the infant's next eye movement was often toward the caregiver's object-handling. In this way infants receive adequate naturalistic input to learn associations between their parent's gaze direction and the locations of interesting sights. © 2014 John Wiley & Sons Ltd.

GEOMETRY-INDEPENDENT DETERMINATION OF RADIAL DENSITY DISTRIBUTIONS IN MOLECULAR CLOUD CORES AND OTHER ASTRONOMICAL OBJECTS

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

Krčo, Marko; Goldsmith, Paul F., E-mail: marko@astro.cornell.edu

2016-05-01

We present a geometry-independent method for determining the shapes of radial volume density profiles of astronomical objects whose geometries are unknown, based on a single column density map. Such profiles are often critical to understand the physics and chemistry of molecular cloud cores, in which star formation takes place. The method presented here does not assume any geometry for the object being studied, thus removing a significant source of bias. Instead, it exploits contour self-similarity in column density maps, which appears to be common in data for astronomical objects. Our method may be applied to many types of astronomical objectsmore » and observable quantities so long as they satisfy a limited set of conditions, which we describe in detail. We derive the method analytically, test it numerically, and illustrate its utility using 2MASS-derived dust extinction in molecular cloud cores. While not having made an extensive comparison of different density profiles, we find that the overall radial density distribution within molecular cloud cores is adequately described by an attenuated power law.« less

Upon the opportunity to apply ART2 Neural Network for clusterization of biodiesel fuels

NASA Astrophysics Data System (ADS)

Petkov, T.; Mustafa, Z.; Sotirov, S.; Milina, R.; Moskovkina, M.

2016-03-01

A chemometric approach using artificial neural network for clusterization of biodiesels was developed. It is based on artificial ART2 neural network. Gas chromatography (GC) and Gas Chromatography - mass spectrometry (GC-MS) were used for quantitative and qualitative analysis of biodiesels, produced from different feedstocks, and FAME (fatty acid methyl esters) profiles were determined. Totally 96 analytical results for 7 different classes of biofuel plants: sunflower, rapeseed, corn, soybean, palm, peanut, "unknown" were used as objects. The analysis of biodiesels showed the content of five major FAME (C16:0, C18:0, C18:1, C18:2, C18:3) and those components were used like inputs in the model. After training with 6 samples, for which the origin was known, ANN was verified and tested with ninety "unknown" samples. The present research demonstrated the successful application of neural network for recognition of biodiesels according to their feedstock which give information upon their properties and handling.

Capture-recapture studies for multiple strata including non-markovian transitions

USGS Publications Warehouse

Brownie, C.; Hines, J.E.; Nichols, J.D.; Pollock, K.H.; Hestbeck, J.B.

1993-01-01

We consider capture-recapture studies where release and recapture data are available from each of a number of strata on every capture occasion. Strata may, for example, be geographic locations or physiological states. Movement of animals among strata occurs with unknown probabilities, and estimation of these unknown transition probabilities is the objective. We describe a computer routine for carrying out the analysis under a model that assumes Markovian transitions and under reduced parameter versions of this model. We also introduce models that relax the Markovian assumption and allow 'memory' to operate (i.e., allow dependence of the transition probabilities on the previous state). For these models, we sugg st an analysis based on a conditional likelihood approach. Methods are illustrated with data from a large study on Canada geese (Branta canadensis) banded in three geographic regions. The assumption of Markovian transitions is rejected convincingly for these data, emphasizing the importance of the more general models that allow memory.

Contemporary group estimates adjusted for climatic effects provide a finer definition of the unknown environmental challenges experienced by growing pigs.

PubMed

Guy, S Z Y; Li, L; Thomson, P C; Hermesch, S

2017-12-01

Environmental descriptors derived from mean performances of contemporary groups (CGs) are assumed to capture any known and unknown environmental challenges. The objective of this paper was to obtain a finer definition of the unknown challenges, by adjusting CG estimates for the known climatic effects of monthly maximum air temperature (MaxT), minimum air temperature (MinT) and monthly rainfall (Rain). As the unknown component could include infection challenges, these refined descriptors may help to better model varying responses of sire progeny to environmental infection challenges for the definition of disease resilience. Data were recorded from 1999 to 2013 at a piggery in south-east Queensland, Australia (n = 31,230). Firstly, CG estimates of average daily gain (ADG) and backfat (BF) were adjusted for MaxT, MinT and Rain, which were fitted as splines. In the models used to derive CG estimates for ADG, MaxT and MinT were significant variables. The models that contained these significant climatic variables had CG estimates with a lower variance compared to models without significant climatic variables. Variance component estimates were similar across all models, suggesting that these significant climatic variables accounted for some known environmental variation captured in CG estimates. No climatic variables were significant in the models used to derive the CG estimates for BF. These CG estimates were used to categorize environments. There was no observable sire by environment interaction (Sire×E) for ADG when using the environmental descriptors based on CG estimates on BF. For the environmental descriptors based on CG estimates of ADG, there was significant Sire×E only when MinT was included in the model (p = .01). Therefore, this new definition of the environment, preadjusted by MinT, increased the ability to detect Sire×E. While the unknown challenges captured in refined CG estimates need verification for infection challenges, this may provide a practical approach for the genetic improvement of disease resilience. © 2017 Blackwell Verlag GmbH.

Neural activity associated with self, other, and object-based counterfactual thinking.

PubMed

De Brigard, Felipe; Nathan Spreng, R; Mitchell, Jason P; Schacter, Daniel L

2015-04-01

Previous research has shown that autobiographical episodic counterfactual thinking-i.e., mental simulations about alternative ways in which one's life experiences could have occurred-engages the brain's default network (DN). However, it remains unknown whether or not the DN is also engaged during impersonal counterfactual thoughts, specifically those involving other people or objects. The current study compares brain activity during counterfactual simulations involving the self, others and objects. In addition, counterfactual thoughts involving others were manipulated in terms of similarity and familiarity with the simulated characters. The results indicate greater involvement of DN during person-based (i.e., self and other) as opposed to object-based counterfactual simulations. However, the involvement of different regions of the DN during other-based counterfactual simulations was modulated by how close and/or similar the simulated character was perceived to be by the participant. Simulations involving unfamiliar characters preferentially recruited dorsomedial prefrontal cortex. Simulations involving unfamiliar similar characters, characters with whom participants identified personality traits, recruited lateral temporal gyrus. Finally, our results also revealed differential coupling of right hippocampus with lateral prefrontal and temporal cortex during counterfactual simulations involving familiar similar others, but with left transverse temporal gyrus and medial frontal and inferior temporal gyri during counterfactual simulations involving either oneself or unfamiliar dissimilar others. These results suggest that different brain mechanisms are involved in the simulation of personal and impersonal counterfactual thoughts, and that the extent to which regions associated with autobiographical memory are recruited during the simulation of counterfactuals involving others depends on the perceived similarity and familiarity with the simulated individuals. Copyright © 2015 Elsevier Inc. All rights reserved.

Neural activity associated with self, other, and object-based counterfactual thinking

PubMed Central

De Brigard, Felipe; Spreng, R. Nathan; Mitchell, Jason P.; Schacter, Daniel L.

2016-01-01

Previous research has shown that autobiographical episodic counterfactual thinking—i.e., mental simulations about alternative ways in which one’s life experiences could have occurred—engages the brain’s default network (DN). However, it remains unknown whether or not the DN is also engaged during impersonal counterfactual thoughts, specifically those involving other people or objects. The current study compares brain activity during counterfactual simulations involving the self, others and objects. In addition, counterfactual thoughts involving others were manipulated in terms of similarity and familiarity with the simulated characters. The results indicate greater involvement of DN during person-based (i.e., self and other) as opposed to object-based counterfactual simulations. However, the involvement of different regions of the DN during other-based counterfactual simulations was modulated by how close and/or similar the simulated character was perceived to be by the participant. Simulations involving unfamiliar characters preferentially recruited dorsomedial prefrontal cortex. Simulations involving unfamiliar similar characters, characters with whom participants identified personality traits, recruited lateral temporal gyrus. Finally, our results also revealed differential coupling of right hippocampus with lateral prefrontal and temporal cortex during counterfactual simulations involving familiar similar others, but with left transverse temporal gyrus and medial frontal and inferior temporal gyri during counterfactual simulations involving either oneself or unfamiliar dissimilar others. These results suggest that different brain mechanisms are involved in the simulation of personal and impersonal counterfactual thoughts, and that the extent to which regions associated with autobiographical memory are recruited during the simulation of counterfactuals involving others depends on the perceived similarity and familiarity with the simulated individuals. PMID:25579447

This is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms--theory and practice.

PubMed

Harmany, Zachary T; Marcia, Roummel F; Willett, Rebecca M

2012-03-01

Observations in many applications consist of counts of discrete events, such as photons hitting a detector, which cannot be effectively modeled using an additive bounded or Gaussian noise model, and instead require a Poisson noise model. As a result, accurate reconstruction of a spatially or temporally distributed phenomenon (f*) from Poisson data (y) cannot be effectively accomplished by minimizing a conventional penalized least-squares objective function. The problem addressed in this paper is the estimation of f* from y in an inverse problem setting, where the number of unknowns may potentially be larger than the number of observations and f* admits sparse approximation. The optimization formulation considered in this paper uses a penalized negative Poisson log-likelihood objective function with nonnegativity constraints (since Poisson intensities are naturally nonnegative). In particular, the proposed approach incorporates key ideas of using separable quadratic approximations to the objective function at each iteration and penalization terms related to l1 norms of coefficient vectors, total variation seminorms, and partition-based multiscale estimation methods.

Marginal estimator for the aberrations of a space telescope by phase diversity

NASA Astrophysics Data System (ADS)

Blanc, Amandine; Mugnier, Laurent; Idier, Jérôme

2017-11-01

In this communication, we propose a novel method for estimating the aberrations of a space telescope from phase diversity data. The images recorded by such a telescope can be degraded by optical aberrations due to design, fabrication or misalignments. Phase diversity is a technique that allows the estimation of aberrations. The only estimator found in the relevant literature is based on a joint estimation of the aberrated phase and the observed object. We recall this approach and study the behavior of this joint estimator by means of simulations. We propose a novel marginal estimator of the sole phase. it is obtained by integrating the observed object out of the problem; indeed, this object is a nuisance parameter in our problem. This reduces drastically the number of unknown and provides better asymptotic properties. This estimator is implemented and its properties are validated by simulation. its performance is equal or even better than that of the joint estimator for the same computing cost.

Face value: amygdala response reflects the validity of first impressions.

PubMed

Rule, Nicholas O; Moran, Joseph M; Freeman, Jonathan B; Whitfield-Gabrieli, Susan; Gabrieli, John D E; Ambady, Nalini

2011-01-01

The human amygdala responds to first impressions of people as judged from their faces, such as normative judgments about the trustworthiness of strangers. It is unknown, however, whether amygdala responses to first impressions can be validated by objective criteria. Here, we examined amygdala responses to faces of Chief Executive Officers (CEOs) where real-world outcomes could be measured objectively by the amounts of profits made by each CEO's company. During fMRI scanning, participants made incidental judgments about the symmetry of each CEO's face. After scanning, participants rated each CEO's face on leadership ability. Parametric analyses showed that greater left amygdala response to the CEOs' faces was associated with higher post-scan ratings of the CEOs' leadership ability. In addition, greater left amygdala response was also associated with greater profits made by the CEOs' companies and this relationship was statistically mediated by external raters' perceptions of arousal. Thus, amygdala response reflected both subjective judgments and objective measures of leadership ability based on first impressions. Copyright © 2010 Elsevier Inc. All rights reserved.

Catalogue Creation for Space Situational Awareness with Optical Sensors

NASA Astrophysics Data System (ADS)

Hobson, T.; Clarkson, I.; Bessell, T.; Rutten, M.; Gordon, N.; Moretti, N.; Morreale, B.

2016-09-01

In order to safeguard the continued use of space-based technologies, effective monitoring and tracking of man-made resident space objects (RSOs) is paramount. The diverse characteristics, behaviours and trajectories of RSOs make space surveillance a challenging application of the discipline that is tracking and surveillance. When surveillance systems are faced with non-canonical scenarios, it is common for human operators to intervene while researchers adapt and extend traditional tracking techniques in search of a solution. A complementary strategy for improving the robustness of space surveillance systems is to place greater emphasis on the anticipation of uncertainty. Namely, give the system the intelligence necessary to autonomously react to unforeseen events and to intelligently and appropriately act on tenuous information rather than discard it. In this paper we build from our 2015 campaign and describe the progression of a low-cost intelligent space surveillance system capable of autonomously cataloguing and maintaining track of RSOs. It currently exploits robotic electro-optical sensors, high-fidelity state-estimation and propagation as well as constrained initial orbit determination (IOD) to intelligently and adaptively manage its sensors in order to maintain an accurate catalogue of RSOs. In a step towards fully autonomous cataloguing, the system has been tasked with maintaining surveillance of a portion of the geosynchronous (GEO) belt. Using a combination of survey and track-refinement modes, the system is capable of maintaining a track of known RSOs and initiating tracks on previously unknown objects. Uniquely, due to the use of high-fidelity representations of a target's state uncertainty, as few as two images of previously unknown RSOs may be used to subsequently initiate autonomous search and reacquisition. To achieve this capability, particularly within the congested environment of the GEO-belt, we use a constrained admissible region (CAR) to generate a plausible estimate of the unknown RSO's state probability density function and disambiguate measurements using a particle-based joint probability data association (JPDA) method. Additionally, the use of alternative CAR generation methods, incorporating catalogue-based priors, is explored and tested. We also present the findings of two field trials of an experimental system that incorporates these techniques. The results demonstrate that such a system is capable of autonomously searching for an RSO that was briefly observed days prior in a GEO-survey and discriminating it from the measurements of other previously catalogued RSOs.

Detecting outliers and learning complex structures with large spectroscopic surveys - a case study with APOGEE stars

NASA Astrophysics Data System (ADS)

Reis, Itamar; Poznanski, Dovi; Baron, Dalya; Zasowski, Gail; Shahaf, Sahar

2018-05-01

In this work, we apply and expand on a recently introduced outlier detection algorithm that is based on an unsupervised random forest. We use the algorithm to calculate a similarity measure for stellar spectra from the Apache Point Observatory Galactic Evolution Experiment (APOGEE). We show that the similarity measure traces non-trivial physical properties and contains information about complex structures in the data. We use it for visualization and clustering of the data set, and discuss its ability to find groups of highly similar objects, including spectroscopic twins. Using the similarity matrix to search the data set for objects allows us to find objects that are impossible to find using their best-fitting model parameters. This includes extreme objects for which the models fail, and rare objects that are outside the scope of the model. We use the similarity measure to detect outliers in the data set, and find a number of previously unknown Be-type stars, spectroscopic binaries, carbon rich stars, young stars, and a few that we cannot interpret. Our work further demonstrates the potential for scientific discovery when combining machine learning methods with modern survey data.

Shape-based ultrasound tomography using a Born model with application to high intensity focused ultrasound therapy.

PubMed

Ulker Karbeyaz, Başak; Miller, Eric L; Cleveland, Robin O

2008-05-01

A shaped-based ultrasound tomography method is proposed to reconstruct ellipsoidal objects using a linearized scattering model. The method is motivated by the desire to detect the presence of lesions created by high intensity focused ultrasound (HIFU) in applications of cancer therapy. The computational size and limited view nature of the relevant three-dimensional inverse problem renders impractical the use of traditional pixel-based reconstruction methods. However, by employing a shape-based parametrization it is only necessary to estimate a small number of unknowns describing the geometry of the lesion, in this paper assumed to be ellipsoidal. The details of the shape-based nonlinear inversion method are provided. Results obtained from a commercial ultrasound scanner and a tissue phantom containing a HIFU-like lesion demonstrate the feasibility of the approach where a 20 mm x 5 mm x 6 mm ellipsoidal inclusion was detected with an accuracy of around 5%.

Characterization of Glass-Like Fragments from the 3714 Building

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

Buck, Edgar C.

2010-02-23

This report describes characterization of a sample obtained from the 3714 building in the 300 Area. Characterization of this unknown material was required for the demonolition activities in the 300 Area. The object of the study was to dertermine the nature of the material, composition, possible structure, evidence for hazards components. The green material is a sodium alumino-silicate glass. This conclusion is based on the composition provided by SEM-EDS, and the images that suggest a glass-like morphology. Further analysis with Ramin and/or infrared could be used to determine the presence of any organics.

Time-of-flight camera via a single-pixel correlation image sensor

NASA Astrophysics Data System (ADS)

Mao, Tianyi; Chen, Qian; He, Weiji; Dai, Huidong; Ye, Ling; Gu, Guohua

2018-04-01

A time-of-flight imager based on single-pixel correlation image sensors is proposed for noise-free depth map acquisition in presence of ambient light. Digital micro-mirror device and time-modulated IR-laser provide spatial and temporal illumination on the unknown object. Compressed sensing and ‘four bucket principle’ method are combined to reconstruct the depth map from a sequence of measurements at a low sampling rate. Second-order correlation transform is also introduced to reduce the noise from the detector itself and direct ambient light. Computer simulations are presented to validate the computational models and improvement of reconstructions.

Adaptive Feedback in Local Coordinates for Real-time Vision-Based Motion Control Over Long Distances

NASA Astrophysics Data System (ADS)

Aref, M. M.; Astola, P.; Vihonen, J.; Tabus, I.; Ghabcheloo, R.; Mattila, J.

2018-03-01

We studied the differences in noise-effects, depth-correlated behavior of sensors, and errors caused by mapping between coordinate systems in robotic applications of machine vision. In particular, the highly range-dependent noise densities for semi-unknown object detection were considered. An equation is proposed to adapt estimation rules to dramatic changes of noise over longer distances. This algorithm also benefits the smooth feedback of wheels to overcome variable latencies of visual perception feedback. Experimental evaluation of the integrated system is presented with/without the algorithm to highlight its effectiveness.

Constraining the Drag Coefficients of Meteors in Dark Flight

NASA Technical Reports Server (NTRS)

Carter, R. T.; Jandir, P. S.; Kress, M. E.

2011-01-01

Based on data in the aeronautics literature, we have derived functions for the drag coefficients of spheres and cubes as a function of Mach number. Experiments have shown that spheres and cubes exhibit an abrupt factor-of-two decrease in the drag coefficient as the object slows through the transonic regime. Irregularly shaped objects such as meteorites likely exhibit a similar trend. These functions are implemented in an otherwise simple projectile motion model, which is applicable to the non-ablative dark flight of meteors (speeds less than .+3 km/s). We demonstrate how these functions may be used as upper and lower limits on the drag coefficient of meteors whose shape is unknown. A Mach-dependent drag coefficient is potentially important in other planetary and astrophysical situations, for instance, in the core accretion scenario for giant planet formation.

Competing for Consciousness: Prolonged Mask Exposure Reduces Object Substitution Masking

ERIC Educational Resources Information Center

Goodhew, Stephanie C.; Visser, Troy A. W.; Lipp, Ottmar V.; Dux, Paul E.

2011-01-01

In object substitution masking (OSM) a sparse, temporally trailing 4-dot mask impairs target identification, even though it has different contours from, and does not spatially overlap with the target. Here, we demonstrate a previously unknown characteristic of OSM: Observers show reduced masking at prolonged (e.g., 640 ms) relative to intermediate…

The Nature of Experience Determines Object Representations in the Visual System

ERIC Educational Resources Information Center

Wong, Yetta K.; Folstein, Jonathan R.; Gauthier, Isabel

2012-01-01

Visual perceptual learning (PL) and perceptual expertise (PE) traditionally lead to different training effects and recruit different brain areas, but reasons for these differences are largely unknown. Here, we tested how the learning history influences visual object representations. Two groups were trained with tasks typically used in PL or PE…

I saw where you have been--The topography of human demonstration affects dogs' search patterns and perseverative errors.

PubMed

Péter, András; Topál, József; Miklósi, Ádám; Pongrácz, Péter

2016-04-01

Performance in object search tasks is not only influenced by the subjects' object permanence ability. For example, ostensive cues of the human manipulating the target markedly affect dogs' choices. However, the interference between the target's location and the spatial cues of the human hiding the object is still unknown. In a five-location visible displacement task, the experimental groups differed in the hiding route of the experimenter. In the 'direct' condition he moved straight towards the actual location, hid the object and returned to the dog. In the 'indirect' conditions, he additionally walked behind each screen before returning. The two 'indirect' conditions differed from each other in that the human either visited the previously baited locations before (proactive interference) or after (retroactive interference) hiding the object. In the 'indirect' groups, dogs' performance was significantly lower than in the 'direct' group, demonstrating that for dogs, in an ostensive context, spatial cues of the hider are as important as the observed location of the target. Based on their incorrect choices, dogs were most attracted to the previously baited locations that the human visited after hiding the object in the actual trial. This underlines the importance of retroactive interference in multiple choice tasks. Copyright © 2016 Elsevier B.V. All rights reserved.

Reading visually embodied meaning from the brain: Visually grounded computational models decode visual-object mental imagery induced by written text.

PubMed

Anderson, Andrew James; Bruni, Elia; Lopopolo, Alessandro; Poesio, Massimo; Baroni, Marco

2015-10-15

Embodiment theory predicts that mental imagery of object words recruits neural circuits involved in object perception. The degree of visual imagery present in routine thought and how it is encoded in the brain is largely unknown. We test whether fMRI activity patterns elicited by participants reading objects' names include embodied visual-object representations, and whether we can decode the representations using novel computational image-based semantic models. We first apply the image models in conjunction with text-based semantic models to test predictions of visual-specificity of semantic representations in different brain regions. Representational similarity analysis confirms that fMRI structure within ventral-temporal and lateral-occipital regions correlates most strongly with the image models and conversely text models correlate better with posterior-parietal/lateral-temporal/inferior-frontal regions. We use an unsupervised decoding algorithm that exploits commonalities in representational similarity structure found within both image model and brain data sets to classify embodied visual representations with high accuracy (8/10) and then extend it to exploit model combinations to robustly decode different brain regions in parallel. By capturing latent visual-semantic structure our models provide a route into analyzing neural representations derived from past perceptual experience rather than stimulus-driven brain activity. Our results also verify the benefit of combining multimodal data to model human-like semantic representations. Copyright © 2015 Elsevier Inc. All rights reserved.

Post-operative therapy following transoral robotic surgery for unknown primary cancers of the head and neck.

PubMed

Patel, Sapna A; Parvathaneni, Aarthi; Parvathaneni, Upendra; Houlton, Jeffrey J; Karni, Ron J; Liao, Jay J; Futran, Neal D; Méndez, Eduardo

2017-09-01

Our primary objective is to describe the post- operative management in patients with an unknown primary squamous cell carcinoma of the head and neck (HNSCC) treated with trans-oral robotic surgery (TORS). We conducted a retrospective multi-institutional case series including all patients diagnosed with an unknown primary HNSCC who underwent TORS to identify the primary site from January 1, 2010 to June 30, 2016. We excluded those with recurrent disease, ≤6months of follow up from TORS, previous history of radiation therapy (RT) to the head and neck, or evidence of primary tumor site based on previous biopsies. Our main outcome measure was receipt of post-operative therapy. The tumor was identified in 26/35 (74.3%) subjects. Post-TORS, 2 subjects did not receive adjuvant therapy due to favorable pathology. Volume reduction of RT mucosal site coverage was achieved in 12/26 (46.1%) subjects who had lateralizing tumors, ie. those confined to the palatine tonsil or glossotonsillar sulcus. In addition, for 8/26 (30.1%), the contralateral neck RT was also avoided. In 9 subjects, no primary was identified (pT0); four of these received RT to the involved ipsilateral neck nodal basin only without pharyngeal mucosal irradiation. Surgical management of an unknown primary with TORS can lead to deintensification of adjuvant therapy including avoidance of chemotherapy and reduction in RT doses and volume. There was no increase in short term treatment failures. Treatment after TORS can vary significantly, thus we advocate adherence to NCCN guideline therapy post-TORS to avoid treatment-associated variability. Published by Elsevier Ltd.

Robustly Aligning a Shape Model and Its Application to Car Alignment of Unknown Pose.

PubMed

Li, Yan; Gu, Leon; Kanade, Takeo

2011-09-01

Precisely localizing in an image a set of feature points that form a shape of an object, such as car or face, is called alignment. Previous shape alignment methods attempted to fit a whole shape model to the observed data, based on the assumption of Gaussian observation noise and the associated regularization process. However, such an approach, though able to deal with Gaussian noise in feature detection, turns out not to be robust or precise because it is vulnerable to gross feature detection errors or outliers resulting from partial occlusions or spurious features from the background or neighboring objects. We address this problem by adopting a randomized hypothesis-and-test approach. First, a Bayesian inference algorithm is developed to generate a shape-and-pose hypothesis of the object from a partial shape or a subset of feature points. For alignment, a large number of hypotheses are generated by randomly sampling subsets of feature points, and then evaluated to find the one that minimizes the shape prediction error. This method of randomized subset-based matching can effectively handle outliers and recover the correct object shape. We apply this approach on a challenging data set of over 5,000 different-posed car images, spanning a wide variety of car types, lighting, background scenes, and partial occlusions. Experimental results demonstrate favorable improvements over previous methods on both accuracy and robustness.

Ground-to-satellite quantum teleportation.

PubMed

Ren, Ji-Gang; Xu, Ping; Yong, Hai-Lin; Zhang, Liang; Liao, Sheng-Kai; Yin, Juan; Liu, Wei-Yue; Cai, Wen-Qi; Yang, Meng; Li, Li; Yang, Kui-Xing; Han, Xuan; Yao, Yong-Qiang; Li, Ji; Wu, Hai-Yan; Wan, Song; Liu, Lei; Liu, Ding-Quan; Kuang, Yao-Wu; He, Zhi-Ping; Shang, Peng; Guo, Cheng; Zheng, Ru-Hua; Tian, Kai; Zhu, Zhen-Cai; Liu, Nai-Le; Lu, Chao-Yang; Shu, Rong; Chen, Yu-Ao; Peng, Cheng-Zhi; Wang, Jian-Yu; Pan, Jian-Wei

2017-09-07

An arbitrary unknown quantum state cannot be measured precisely or replicated perfectly. However, quantum teleportation enables unknown quantum states to be transferred reliably from one object to another over long distances, without physical travelling of the object itself. Long-distance teleportation is a fundamental element of protocols such as large-scale quantum networks and distributed quantum computation. But the distances over which transmission was achieved in previous teleportation experiments, which used optical fibres and terrestrial free-space channels, were limited to about 100 kilometres, owing to the photon loss of these channels. To realize a global-scale 'quantum internet' the range of quantum teleportation needs to be greatly extended. A promising way of doing so involves using satellite platforms and space-based links, which can connect two remote points on Earth with greatly reduced channel loss because most of the propagation path of the photons is in empty space. Here we report quantum teleportation of independent single-photon qubits from a ground observatory to a low-Earth-orbit satellite, through an uplink channel, over distances of up to 1,400 kilometres. To optimize the efficiency of the link and to counter the atmospheric turbulence in the uplink, we use a compact ultra-bright source of entangled photons, a narrow beam divergence and high-bandwidth and high-accuracy acquiring, pointing and tracking. We demonstrate successful quantum teleportation of six input states in mutually unbiased bases with an average fidelity of 0.80 ± 0.01, well above the optimal state-estimation fidelity on a single copy of a qubit (the classical limit). Our demonstration of a ground-to-satellite uplink for reliable and ultra-long-distance quantum teleportation is an essential step towards a global-scale quantum internet.

Ground-to-satellite quantum teleportation

NASA Astrophysics Data System (ADS)

Ren, Ji-Gang; Xu, Ping; Yong, Hai-Lin; Zhang, Liang; Liao, Sheng-Kai; Yin, Juan; Liu, Wei-Yue; Cai, Wen-Qi; Yang, Meng; Li, Li; Yang, Kui-Xing; Han, Xuan; Yao, Yong-Qiang; Li, Ji; Wu, Hai-Yan; Wan, Song; Liu, Lei; Liu, Ding-Quan; Kuang, Yao-Wu; He, Zhi-Ping; Shang, Peng; Guo, Cheng; Zheng, Ru-Hua; Tian, Kai; Zhu, Zhen-Cai; Liu, Nai-Le; Lu, Chao-Yang; Shu, Rong; Chen, Yu-Ao; Peng, Cheng-Zhi; Wang, Jian-Yu; Pan, Jian-Wei

2017-09-01

An arbitrary unknown quantum state cannot be measured precisely or replicated perfectly. However, quantum teleportation enables unknown quantum states to be transferred reliably from one object to another over long distances, without physical travelling of the object itself. Long-distance teleportation is a fundamental element of protocols such as large-scale quantum networks and distributed quantum computation. But the distances over which transmission was achieved in previous teleportation experiments, which used optical fibres and terrestrial free-space channels, were limited to about 100 kilometres, owing to the photon loss of these channels. To realize a global-scale ‘quantum internet’ the range of quantum teleportation needs to be greatly extended. A promising way of doing so involves using satellite platforms and space-based links, which can connect two remote points on Earth with greatly reduced channel loss because most of the propagation path of the photons is in empty space. Here we report quantum teleportation of independent single-photon qubits from a ground observatory to a low-Earth-orbit satellite, through an uplink channel, over distances of up to 1,400 kilometres. To optimize the efficiency of the link and to counter the atmospheric turbulence in the uplink, we use a compact ultra-bright source of entangled photons, a narrow beam divergence and high-bandwidth and high-accuracy acquiring, pointing and tracking. We demonstrate successful quantum teleportation of six input states in mutually unbiased bases with an average fidelity of 0.80 ± 0.01, well above the optimal state-estimation fidelity on a single copy of a qubit (the classical limit). Our demonstration of a ground-to-satellite uplink for reliable and ultra-long-distance quantum teleportation is an essential step towards a global-scale quantum internet.

Production of a Novel Mineral-based Sun Lotion for Protecting the Skin from Biohazards of Electromagnetic Radiation in the UV Region.

PubMed

Movahedi, M M; Alipour, A; Mortazavi, S A R; Tayebi, M

2014-03-01

Sun protection materials have been one of the major concerns in pharmaceutical in-dustry since almost one century ago. Various materials have been found to have such an effect but there are still many unknown substances that have not been discovered. Objective : To introduce a novel mineral-based sun lotion with considerable UV absorption properties compared to commercially available sunscreens.  UV absorption properties of transparent plas-tic sheets covered by a uniform cream layer of different mineral-based sun lotions and a commercially available sun lotion were tested. Sun lotions containing specific proportion of bentonite and zeolite minerals were capable of absorbing the highest level of UV light com-pared to that of the commercially available sun lotion. Mineral-based sun lotions can be considered as cost effective alternatives for current commercial sunscreens.

Production of a Novel Mineral-based Sun Lotion for Protecting the Skin from Biohazards of Electromagnetic Radiation in the UV Region

PubMed Central

Movahedi, M M; Alipour, A; Mortazavi, S A R; Tayebi, M

2014-01-01

Background: Sun protection materials have been one of the major concerns in pharmaceutical in­dustry since almost one century ago. Various materials have been found to have such an effect but there are still many unknown substances that have not been discovered. Objective: To introduce a novel mineral-based sun lotion with considerable UV absorption properties compared to commercially available sunscreens. Method:  UV absorption properties of transparent plas­tic sheets covered by a uniform cream layer of different mineral-based sun lotions and a commercially available sun lotion were tested. Results: Sun lotions containing specific proportion of bentonite and zeolite minerals were capable of absorbing the highest level of UV light com­pared to that of the commercially available sun lotion. Conclusion: Mineral-based sun lotions can be considered as cost effective alternatives for current commercial sunscreens. PMID:25505763

Metadata-Driven SOA-Based Application for Facilitation of Real-Time Data Warehousing

NASA Astrophysics Data System (ADS)

Pintar, Damir; Vranić, Mihaela; Skočir, Zoran

Service-oriented architecture (SOA) has already been widely recognized as an effective paradigm for achieving integration of diverse information systems. SOA-based applications can cross boundaries of platforms, operation systems and proprietary data standards, commonly through the usage of Web Services technology. On the other side, metadata is also commonly referred to as a potential integration tool given the fact that standardized metadata objects can provide useful information about specifics of unknown information systems with which one has interest in communicating with, using an approach commonly called "model-based integration". This paper presents the result of research regarding possible synergy between those two integration facilitators. This is accomplished with a vertical example of a metadata-driven SOA-based business process that provides ETL (Extraction, Transformation and Loading) and metadata services to a data warehousing system in need of a real-time ETL support.

Do Domestic Dogs Learn Words Based on Humans’ Referential Behaviour?

PubMed Central

Tempelmann, Sebastian; Kaminski, Juliane; Tomasello, Michael

2014-01-01

Some domestic dogs learn to comprehend human words, although the nature and basis of this learning is unknown. In the studies presented here we investigated whether dogs learn words through an understanding of referential actions by humans rather than simple association. In three studies, each modelled on a study conducted with human infants, we confronted four word-experienced dogs with situations involving no spatial-temporal contiguity between the word and the referent; the only available cues were referential actions displaced in time from exposure to their referents. We found that no dogs were able to reliably link an object with a label based on social-pragmatic cues alone in all the tests. However, one dog did show skills in some tests, possibly indicating an ability to learn based on social-pragmatic cues. PMID:24646732

Scalable Machine Learning for Massive Astronomical Datasets

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Gray, A.

2014-04-01

We present the ability to perform data mining and machine learning operations on a catalog of half a billion astronomical objects. This is the result of the combination of robust, highly accurate machine learning algorithms with linear scalability that renders the applications of these algorithms to massive astronomical data tractable. We demonstrate the core algorithms kernel density estimation, K-means clustering, linear regression, nearest neighbors, random forest and gradient-boosted decision tree, singular value decomposition, support vector machine, and two-point correlation function. Each of these is relevant for astronomical applications such as finding novel astrophysical objects, characterizing artifacts in data, object classification (including for rare objects), object distances, finding the important features describing objects, density estimation of distributions, probabilistic quantities, and exploring the unknown structure of new data. The software, Skytree Server, runs on any UNIX-based machine, a virtual machine, or cloud-based and distributed systems including Hadoop. We have integrated it on the cloud computing system of the Canadian Astronomical Data Centre, the Canadian Advanced Network for Astronomical Research (CANFAR), creating the world's first cloud computing data mining system for astronomy. We demonstrate results showing the scaling of each of our major algorithms on large astronomical datasets, including the full 470,992,970 objects of the 2 Micron All-Sky Survey (2MASS) Point Source Catalog. We demonstrate the ability to find outliers in the full 2MASS dataset utilizing multiple methods, e.g., nearest neighbors. This is likely of particular interest to the radio astronomy community given, for example, that survey projects contain groups dedicated to this topic. 2MASS is used as a proof-of-concept dataset due to its convenience and availability. These results are of interest to any astronomical project with large and/or complex datasets that wishes to extract the full scientific value from its data.

Scalable Machine Learning for Massive Astronomical Datasets

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Astronomy Data Centre, Canadian

2014-01-01

We present the ability to perform data mining and machine learning operations on a catalog of half a billion astronomical objects. This is the result of the combination of robust, highly accurate machine learning algorithms with linear scalability that renders the applications of these algorithms to massive astronomical data tractable. We demonstrate the core algorithms kernel density estimation, K-means clustering, linear regression, nearest neighbors, random forest and gradient-boosted decision tree, singular value decomposition, support vector machine, and two-point correlation function. Each of these is relevant for astronomical applications such as finding novel astrophysical objects, characterizing artifacts in data, object classification (including for rare objects), object distances, finding the important features describing objects, density estimation of distributions, probabilistic quantities, and exploring the unknown structure of new data. The software, Skytree Server, runs on any UNIX-based machine, a virtual machine, or cloud-based and distributed systems including Hadoop. We have integrated it on the cloud computing system of the Canadian Astronomical Data Centre, the Canadian Advanced Network for Astronomical Research (CANFAR), creating the world's first cloud computing data mining system for astronomy. We demonstrate results showing the scaling of each of our major algorithms on large astronomical datasets, including the full 470,992,970 objects of the 2 Micron All-Sky Survey (2MASS) Point Source Catalog. We demonstrate the ability to find outliers in the full 2MASS dataset utilizing multiple methods, e.g., nearest neighbors, and the local outlier factor. 2MASS is used as a proof-of-concept dataset due to its convenience and availability. These results are of interest to any astronomical project with large and/or complex datasets that wishes to extract the full scientific value from its data.

Evidence Based Assessment of Public Health Planning: A Case Study of the 2014 Crisis in Ukraine

DTIC Science & Technology

2015-06-12

Unknowns, Unknown Unknowns and the Propagation of Scientific Enquiry,” Journal of Experimental Botany 60, no. 3 (March 2009): 712-714. Risk...David C. Logan, “Known Knowns, Known Unknowns, Unknown Unknowns and the Propagation of Scientific Enquiry,” Journal of Experimental Botany 60, no. 3...Experimental Botany 60, no. 3 (March 2009): 712-714. Markel, Howard. “Facing Tuberculosis,” When Germs Travel: Six Major Epidemics That Have Invaded America

Detection of unknown targets from aerial camera and extraction of simple object fingerprints for the purpose of target reacquisition

NASA Astrophysics Data System (ADS)

Mundhenk, T. Nathan; Ni, Kang-Yu; Chen, Yang; Kim, Kyungnam; Owechko, Yuri

2012-01-01

An aerial multiple camera tracking paradigm needs to not only spot unknown targets and track them, but also needs to know how to handle target reacquisition as well as target handoff to other cameras in the operating theater. Here we discuss such a system which is designed to spot unknown targets, track them, segment the useful features and then create a signature fingerprint for the object so that it can be reacquired or handed off to another camera. The tracking system spots unknown objects by subtracting background motion from observed motion allowing it to find targets in motion, even if the camera platform itself is moving. The area of motion is then matched to segmented regions returned by the EDISON mean shift segmentation tool. Whole segments which have common motion and which are contiguous to each other are grouped into a master object. Once master objects are formed, we have a tight bound on which to extract features for the purpose of forming a fingerprint. This is done using color and simple entropy features. These can be placed into a myriad of different fingerprints. To keep data transmission and storage size low for camera handoff of targets, we try several different simple techniques. These include Histogram, Spatiogram and Single Gaussian Model. These are tested by simulating a very large number of target losses in six videos over an interval of 1000 frames each from the DARPA VIVID video set. Since the fingerprints are very simple, they are not expected to be valid for long periods of time. As such, we test the shelf life of fingerprints. This is how long a fingerprint is good for when stored away between target appearances. Shelf life gives us a second metric of goodness and tells us if a fingerprint method has better accuracy over longer periods. In videos which contain multiple vehicle occlusions and vehicles of highly similar appearance we obtain a reacquisition rate for automobiles of over 80% using the simple single Gaussian model compared with the null hypothesis of <20%. Additionally, the performance for fingerprints stays well above the null hypothesis for as much as 800 frames. Thus, a simple and highly compact single Gaussian model is useful for target reacquisition. Since the model is agnostic to view point and object size, it is expected to perform as well on a test of target handoff. Since some of the performance degradation is due to problems with the initial target acquisition and tracking, the simple Gaussian model may perform even better with an improved initial acquisition technique. Also, since the model makes no assumption about the object to be tracked, it should be possible to use it to fingerprint a multitude of objects, not just cars. Further accuracy may be obtained by creating manifolds of objects from multiple samples.

Characterization of ferromagnetic or conductive properties of metallic foreign objects embedded within the human body with magnetic iron detector (MID): Screening patients for MRI.

PubMed

Gianesin, Barbara; Zefiro, Daniele; Paparo, Francesco; Caminata, Alessio; Balocco, Manuela; Carrara, Paola; Quintino, Sabrina; Pinto, Valeria; Bacigalupo, Lorenzo; Rollandi, Gian Andrea; Marinelli, Mauro; Forni, Gian Luca

2015-05-01

A preliminary assessment of the MRI-compatibility of metallic object possibly embedded within the patient is required before conducting the MRI examination. The Magnetic Iron Detector (MID) is a highly sensitive susceptometer that uses a weak magnetic field to measure iron overload in the liver. MID might be used to perform a screening procedure for MRI by determining the ferromagnetic/conductive properties of embedded metallic objects. The study was composed by: (i) definition of MID sensitivity threshold; (ii) application of MID in a procedure to characterize the ferromagnetic/conductive properties of metallic foreign objects in 958 patients scheduled for MID examination. The detection threshold for ferromagnetic objects was found to be the equivalent of a piece of wire of length 2 mm and gauge 0.8 mm(2) and, representing purely conductive objects, an aluminum sheet of area 2 × 2 cm(2) . Of 958 patients, 165 had foreign bodies of unknown nature. MID was able to detect those with ferromagnetic and/or conducting properties based on fluctuations in the magnetic and eddy current signals versus control. The high sensitivity of MID makes it suitable for assessing the ferromagnetic/conductive properties of metallic foreign objects embedded within the body of patients scheduled for MRI. © 2015 Wiley Periodicals, Inc.

Pattern-Based Inverse Modeling for Characterization of Subsurface Flow Models with Complex Geologic Heterogeneity

NASA Astrophysics Data System (ADS)

Golmohammadi, A.; Jafarpour, B.; M Khaninezhad, M. R.

2017-12-01

Calibration of heterogeneous subsurface flow models leads to ill-posed nonlinear inverse problems, where too many unknown parameters are estimated from limited response measurements. When the underlying parameters form complex (non-Gaussian) structured spatial connectivity patterns, classical variogram-based geostatistical techniques cannot describe the underlying connectivity patterns. Modern pattern-based geostatistical methods that incorporate higher-order spatial statistics are more suitable for describing such complex spatial patterns. Moreover, when the underlying unknown parameters are discrete (geologic facies distribution), conventional model calibration techniques that are designed for continuous parameters cannot be applied directly. In this paper, we introduce a novel pattern-based model calibration method to reconstruct discrete and spatially complex facies distributions from dynamic flow response data. To reproduce complex connectivity patterns during model calibration, we impose a feasibility constraint to ensure that the solution follows the expected higher-order spatial statistics. For model calibration, we adopt a regularized least-squares formulation, involving data mismatch, pattern connectivity, and feasibility constraint terms. Using an alternating directions optimization algorithm, the regularized objective function is divided into a continuous model calibration problem, followed by mapping the solution onto the feasible set. The feasibility constraint to honor the expected spatial statistics is implemented using a supervised machine learning algorithm. The two steps of the model calibration formulation are repeated until the convergence criterion is met. Several numerical examples are used to evaluate the performance of the developed method.

Improving Cognitive Skills of the Industrial Robot

NASA Astrophysics Data System (ADS)

Bezák, Pavol

2015-08-01

At present, there are plenty of industrial robots that are programmed to do the same repetitive task all the time. Industrial robots doing such kind of job are not able to understand whether the action is correct, effective or good. Object detection, manipulation and grasping is challenging due to the hand and object modeling uncertainties, unknown contact type and object stiffness properties. In this paper, the proposal of an intelligent humanoid hand object detection and grasping model is presented assuming that the object properties are known. The control is simulated in the Matlab Simulink/ SimMechanics, Neural Network Toolbox and Computer Vision System Toolbox.

Learning the 3-D structure of objects from 2-D views depends on shape, not format

PubMed Central

Tian, Moqian; Yamins, Daniel; Grill-Spector, Kalanit

2016-01-01

Humans can learn to recognize new objects just from observing example views. However, it is unknown what structural information enables this learning. To address this question, we manipulated the amount of structural information given to subjects during unsupervised learning by varying the format of the trained views. We then tested how format affected participants' ability to discriminate similar objects across views that were rotated 90° apart. We found that, after training, participants' performance increased and generalized to new views in the same format. Surprisingly, the improvement was similar across line drawings, shape from shading, and shape from shading + stereo even though the latter two formats provide richer depth information compared to line drawings. In contrast, participants' improvement was significantly lower when training used silhouettes, suggesting that silhouettes do not have enough information to generate a robust 3-D structure. To test whether the learned object representations were format-specific or format-invariant, we examined if learning novel objects from example views transfers across formats. We found that learning objects from example line drawings transferred to shape from shading and vice versa. These results have important implications for theories of object recognition because they suggest that (a) learning the 3-D structure of objects does not require rich structural cues during training as long as shape information of internal and external features is provided and (b) learning generates shape-based object representations independent of the training format. PMID:27153196

Improving numeracy through values affirmation enhances decision and STEM outcomes

PubMed Central

Peters, Ellen; Tompkins, Mary Kate; Schley, Dan; Meilleur, Louise; Sinayev, Aleksander; Tusler, Martin; Wagner, Laura; Crocker, Jennifer

2017-01-01

Greater numeracy has been correlated with better health and financial outcomes in past studies, but causal effects in adults are unknown. In a 9-week longitudinal study, undergraduate students, all taking a psychology statistics course, were randomly assigned to a control condition or a values-affirmation manipulation intended to improve numeracy. By the final week in the course, the numeracy intervention (statistics-course enrollment combined with values affirmation) enhanced objective numeracy, subjective numeracy, and two decision-related outcomes (financial literacy and health-related behaviors). It also showed positive indirect-only effects on financial outcomes and a series of STEM-related outcomes (course grades, intentions to take more math-intensive courses, later math-intensive courses taken based on academic transcripts). All decision and STEM-related outcome effects were mediated by the changes in objective and/or subjective numeracy and demonstrated similar and robust enhancements. Improvements to abstract numeric reasoning can improve everyday outcomes. PMID:28704410

Holistic processing from learned attention to parts.

PubMed

Chua, Kao-Wei; Richler, Jennifer J; Gauthier, Isabel

2015-08-01

Attention helps us focus on what is most relevant to our goals, and prior work has shown that aspects of attention can be learned. Learned inattention to parts can abolish holistic processing of faces, but it is unknown whether learned attention to parts is sufficient to cause a change from part-based to holistic processing with objects. We trained subjects to individuate nonface objects (Greebles) from 2 categories: Ploks and Glips. Diagnostic information was in complementary halves for the 2 categories. Holistic processing was then tested with Plok-Glip composites that combined the kind of part that was diagnostic or nondiagnostic during training. Exposure to Greeble parts resulted in general failures of selective attention for nondiagnostic composites, but face-like holistic processing was only observed for diagnostic composites. These results demonstrated a novel link between learned attentional control and the acquisition of holistic processing. (c) 2015 APA, all rights reserved).

On global optimization using an estimate of Lipschitz constant and simplicial partition

NASA Astrophysics Data System (ADS)

Gimbutas, Albertas; Žilinskas, Antanas

2016-10-01

A new algorithm is proposed for finding the global minimum of a multi-variate black-box Lipschitz function with an unknown Lipschitz constant. The feasible region is initially partitioned into simplices; in the subsequent iteration, the most suitable simplices are selected and bisected via the middle point of the longest edge. The suitability of a simplex for bisection is evaluated by minimizing of a surrogate function which mimics the lower bound for the considered objective function over that simplex. The surrogate function is defined using an estimate of the Lipschitz constant and the objective function values at the vertices of a simplex. The novelty of the algorithm is the sophisticated method of estimating the Lipschitz constant, and the appropriate method to minimize the surrogate function. The proposed algorithm was tested using 600 random test problems of different complexity, showing competitive results with two popular advanced algorithms which are based on similar assumptions.

A Map of Anticipatory Activity in Mouse Motor Cortex.

PubMed

Chen, Tsai-Wen; Li, Nuo; Daie, Kayvon; Svoboda, Karel

2017-05-17

Activity in the mouse anterior lateral motor cortex (ALM) instructs directional movements, often seconds before movement initiation. It is unknown whether this preparatory activity is localized to ALM or widely distributed within motor cortex. Here we imaged activity across motor cortex while mice performed a whisker-based object localization task with a delayed, directional licking response. During tactile sensation and the delay epoch, object location was represented in motor cortex areas that are medial and posterior relative to ALM, including vibrissal motor cortex. Preparatory activity appeared first in deep layers of ALM, seconds before the behavioral response, and remained localized to ALM until the behavioral response. Later, widely distributed neurons represented the outcome of the trial. Cortical area was more predictive of neuronal selectivity than laminar location or axonal projection target. Motor cortex therefore represents sensory, motor, and outcome information in a spatially organized manner. Copyright © 2017 Elsevier Inc. All rights reserved.

Optimal path planning for a mobile robot using cuckoo search algorithm

NASA Astrophysics Data System (ADS)

Mohanty, Prases K.; Parhi, Dayal R.

2016-03-01

The shortest/optimal path planning is essential for efficient operation of autonomous vehicles. In this article, a new nature-inspired meta-heuristic algorithm has been applied for mobile robot path planning in an unknown or partially known environment populated by a variety of static obstacles. This meta-heuristic algorithm is based on the levy flight behaviour and brood parasitic behaviour of cuckoos. A new objective function has been formulated between the robots and the target and obstacles, which satisfied the conditions of obstacle avoidance and target-seeking behaviour of robots present in the terrain. Depending upon the objective function value of each nest (cuckoo) in the swarm, the robot avoids obstacles and proceeds towards the target. The smooth optimal trajectory is framed with this algorithm when the robot reaches its goal. Some simulation and experimental results are presented at the end of the paper to show the effectiveness of the proposed navigational controller.

A traffic priority language for collision-free navigation of autonomous mobile robots in dynamic environments.

PubMed

Bourbakis, N G

1997-01-01

This paper presents a generic traffic priority language, called KYKLOFORTA, used by autonomous robots for collision-free navigation in a dynamic unknown or known navigation space. In a previous work by X. Grossmman (1988), a set of traffic control rules was developed for the navigation of the robots on the lines of a two-dimensional (2-D) grid and a control center coordinated and synchronized their movements. In this work, the robots are considered autonomous: they are moving anywhere and in any direction inside the free space, and there is no need of a central control to coordinate and synchronize them. The requirements for each robot are i) visual perception, ii) range sensors, and iii) the ability of each robot to detect other moving objects in the same free navigation space, define the other objects perceived size, their velocity and their directions. Based on these assumptions, a traffic priority language is needed for each robot, making it able to decide during the navigation and avoid possible collision with other moving objects. The traffic priority language proposed here is based on a set of primitive traffic priority alphabet and rules which compose pattern of corridors for the application of the traffic priority rules.

Extended behavioural modelling of FET and lattice-mismatched HEMT devices

NASA Astrophysics Data System (ADS)

Khawam, Yahya; Albasha, Lutfi

2017-07-01

This study presents an improved large signal model that can be used for high electron mobility transistors (HEMTs) and field effect transistors using measurement-based behavioural modelling techniques. The steps for accurate large and small signal modelling for transistor are also discussed. The proposed DC model is based on the Fager model since it compensates between the number of model's parameters and accuracy. The objective is to increase the accuracy of the drain-source current model with respect to any change in gate or drain voltages. Also, the objective is to extend the improved DC model to account for soft breakdown and kink effect found in some variants of HEMT devices. A hybrid Newton's-Genetic algorithm is used in order to determine the unknown parameters in the developed model. In addition to accurate modelling of a transistor's DC characteristics, the complete large signal model is modelled using multi-bias s-parameter measurements. The way that the complete model is performed is by using a hybrid multi-objective optimisation technique (Non-dominated Sorting Genetic Algorithm II) and local minimum search (multivariable Newton's method) for parasitic elements extraction. Finally, the results of DC modelling and multi-bias s-parameters modelling are presented, and three-device modelling recommendations are discussed.

EEG Characteristic Extraction Method of Listening Music and Objective Estimation Method Based on Latency Structure Model in Individual Characteristics

NASA Astrophysics Data System (ADS)

Ito, Shin-Ichi; Mitsukura, Yasue; Nakamura Miyamura, Hiroko; Saito, Takafumi; Fukumi, Minoru

EEG is characterized by the unique and individual characteristics. Little research has been done to take into account the individual characteristics when analyzing EEG signals. Often the EEG has frequency components which can describe most of the significant characteristics. Then there is the difference of importance between the analyzed frequency components of the EEG. We think that the importance difference shows the individual characteristics. In this paper, we propose a new EEG extraction method of characteristic vector by a latency structure model in individual characteristics (LSMIC). The LSMIC is the latency structure model, which has personal error as the individual characteristics, based on normal distribution. The real-coded genetic algorithms (RGA) are used for specifying the personal error that is unknown parameter. Moreover we propose an objective estimation method that plots the EEG characteristic vector on a visualization space. Finally, the performance of the proposed method is evaluated using a realistic simulation and applied to a real EEG data. The result of our experiment shows the effectiveness of the proposed method.

77 FR 19694 - Notice of Intent To Repatriate Cultural Items: U.S. Department of Defense, Army Corps of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-02

... objects include 1 lot of fragmented mammal bones; 1 charcoal sample; 1 piece of mussel shell; 1 piece of... objects include 2 pieces of burned mammal bone; 1 burned rodent jaw; 28 pieces of debitage; 8 pipe bowl... other unknown burial numbers. The 658 unassociated funerary artifacts include 1 hollowed bone fragment...

Image registration of naval IR images

NASA Astrophysics Data System (ADS)

Rodland, Arne J.

1996-06-01

In a real world application an image from a stabilized sensor on a moving platform will not be 100 percent stabilized. There will always be a small unknown error in the stabilization due to factors such as dynamic deformations in the structure between sensor and reference Inertial Navigation Unit, servo inaccuracies, etc. For a high resolution imaging sensor this stabilization error causes the image to move several pixels in unknown direction between frames. TO be able to detect and track small moving objects from such a sensor, this unknown movement of the sensor image must be estimated. An algorithm that searches for land contours in the image has been evaluated. The algorithm searches for high contrast points distributed over the whole image. As long as moving objects in the scene only cover a small area of the scene, most of the points are located on solid ground. By matching the list of points from frame to frame, the movement of the image due to stabilization errors can be estimated and compensated. The point list is searched for points with diverging movement from the estimated stabilization error. These points are then assumed to be located on moving objects. Points assumed to be located on moving objects are gradually exchanged with new points located in the same area. Most of the processing is performed on the list of points and not on the complete image. The algorithm is therefore very fast and well suited for real time implementation. The algorithm has been tested on images from an experimental IR scanner. Stabilization errors were added artificially to the image such that the output from the algorithm could be compared with the artificially added stabilization errors.

Discriminant forest classification method and system

DOEpatents

Chen, Barry Y.; Hanley, William G.; Lemmond, Tracy D.; Hiller, Lawrence J.; Knapp, David A.; Mugge, Marshall J.

2012-11-06

A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

Similarity relations in visual search predict rapid visual categorization

PubMed Central

Mohan, Krithika; Arun, S. P.

2012-01-01

How do we perform rapid visual categorization?It is widely thought that categorization involves evaluating the similarity of an object to other category items, but the underlying features and similarity relations remain unknown. Here, we hypothesized that categorization performance is based on perceived similarity relations between items within and outside the category. To this end, we measured the categorization performance of human subjects on three diverse visual categories (animals, vehicles, and tools) and across three hierarchical levels (superordinate, basic, and subordinate levels among animals). For the same subjects, we measured their perceived pair-wise similarities between objects using a visual search task. Regardless of category and hierarchical level, we found that the time taken to categorize an object could be predicted using its similarity to members within and outside its category. We were able to account for several classic categorization phenomena, such as (a) the longer times required to reject category membership; (b) the longer times to categorize atypical objects; and (c) differences in performance across tasks and across hierarchical levels. These categorization times were also accounted for by a model that extracts coarse structure from an image. The striking agreement observed between categorization and visual search suggests that these two disparate tasks depend on a shared coarse object representation. PMID:23092947

Realtime motion planning for a mobile robot in an unknown environment using a neurofuzzy based approach

NASA Astrophysics Data System (ADS)

Zheng, Taixiong

2005-12-01

A neuro-fuzzy network based approach for robot motion in an unknown environment was proposed. In order to control the robot motion in an unknown environment, the behavior of the robot was classified into moving to the goal and avoiding obstacles. Then, according to the dynamics of the robot and the behavior character of the robot in an unknown environment, fuzzy control rules were introduced to control the robot motion. At last, a 6-layer neuro-fuzzy network was designed to merge from what the robot sensed to robot motion control. After being trained, the network may be used for robot motion control. Simulation results show that the proposed approach is effective for robot motion control in unknown environment.

Elucidation of the ‘Honeycrisp’ pedigree through haplotype analysis with a multi-family integrated SNP linkage map and a large apple (Malus×domestica) pedigree-connected SNP data set

PubMed Central

Howard, Nicholas P; van de Weg, Eric; Bedford, David S; Peace, Cameron P; Vanderzande, Stijn; Clark, Matthew D; Teh, Soon Li; Cai, Lichun; Luby, James J

2017-01-01

The apple (Malus×domestica) cultivar Honeycrisp has become important economically and as a breeding parent. An earlier study with SSR markers indicated the original recorded pedigree of ‘Honeycrisp’ was incorrect and ‘Keepsake’ was identified as one putative parent, the other being unknown. The objective of this study was to verify ‘Keepsake’ as a parent and identify and genetically describe the unknown parent and its grandparents. A multi-family based dense and high-quality integrated SNP map was created using the apple 8 K Illumina Infinium SNP array. This map was used alongside a large pedigree-connected data set from the RosBREED project to build extended SNP haplotypes and to identify pedigree relationships. ‘Keepsake’ was verified as one parent of ‘Honeycrisp’ and ‘Duchess of Oldenburg’ and ‘Golden Delicious’ were identified as grandparents through the unknown parent. Following this finding, siblings of ‘Honeycrisp’ were identified using the SNP data. Breeding records from several of these siblings suggested that the previously unreported parent is a University of Minnesota selection, MN1627. This selection is no longer available, but now is genetically described through imputed SNP haplotypes. We also present the mosaic grandparental composition of ‘Honeycrisp’ for each of its 17 chromosome pairs. This new pedigree and genetic information will be useful in future pedigree-based genetic studies to connect ‘Honeycrisp’ with other cultivars used widely in apple breeding programs. The created SNP linkage map will benefit future research using the data from the Illumina apple 8 and 20 K and Affymetrix 480 K SNP arrays. PMID:28243452

Discrete-time switching periodic adaptive control for time-varying parameters with unknown periodicity

NASA Astrophysics Data System (ADS)

Yu, Miao; Huang, Deqing; Yang, Wanqiu

2018-06-01

In this paper, we address the problem of unknown periodicity for a class of discrete-time nonlinear parametric systems without assuming any growth conditions on the nonlinearities. The unknown periodicity hides in the parametric uncertainties, which is difficult to estimate with existing techniques. By incorporating a logic-based switching mechanism, we identify the period and bound of unknown parameter simultaneously. Lyapunov-based analysis is given to demonstrate that a finite number of switchings can guarantee the asymptotic tracking for the nonlinear parametric systems. The simulation result also shows the efficacy of the proposed switching periodic adaptive control approach.

Probabilistic Multi-Person Tracking Using Dynamic Bayes Networks

NASA Astrophysics Data System (ADS)

Klinger, T.; Rottensteiner, F.; Heipke, C.

2015-08-01

Tracking-by-detection is a widely used practice in recent tracking systems. These usually rely on independent single frame detections that are handled as observations in a recursive estimation framework. If these observations are imprecise the generated trajectory is prone to be updated towards a wrong position. In contrary to existing methods our novel approach uses a Dynamic Bayes Network in which the state vector of a recursive Bayes filter, as well as the location of the tracked object in the image are modelled as unknowns. These unknowns are estimated in a probabilistic framework taking into account a dynamic model, and a state-of-the-art pedestrian detector and classifier. The classifier is based on the Random Forest-algorithm and is capable of being trained incrementally so that new training samples can be incorporated at runtime. This allows the classifier to adapt to the changing appearance of a target and to unlearn outdated features. The approach is evaluated on a publicly available benchmark. The results confirm that our approach is well suited for tracking pedestrians over long distances while at the same time achieving comparatively good geometric accuracy.

Clearing a Pile of Unknown Objects using Interactive Perception

DTIC Science & Technology

2012-11-01

blocks and the shampoo . The robot now decides to grasp the bottle of shampoo . Next, the tissue box and the chunk of wood are pushed and grasped. The...20 seconds. Poking an object requires 12 (a) Initial pile (b) Poking macaroni box (c) After poking (d) Grasping shampoo (e) After grasping (f) Pooking...objects: a tissue box, a chunk of wood, a bottle of shampoo , a box of macaroni, and toy blocks. The algorithm switches between pushing to verify

Diagnostic labelling influences self-rated health. A prospective cohort study: the HUNT Study, Norway

PubMed Central

Jørgensen, Pål; Langhammer, Arnulf; Krokstad, Steinar; Forsmo, Siri

2015-01-01

Background. Studies have shown an independent association between poor self-rated health (SRH) and increased mortality. Few studies, however, have investigated any possible impact on SRH of diagnostic labelling. Objective. To test whether SRH differed in persons with known and unknown hypothyroidism, diabetes mellitus (DM) or hypertension, opposed to persons without these conditions, after 11-year follow-up. Methods. Prospective population-based cohort study in North-Trøndelag County, Norway, HUNT2 (1995–97) to HUNT3 (2006–08). All inhabitants aged 20 years and older were invited. The response rate was 69.5% in HUNT2 and 54.1% in HUNT3. In total, 34144 persons aged 20–70 years were included in the study population. The outcome was poor SRH. Results. Persons with known disease had an increased odds ratio (OR) to report poor SRH at follow-up; figures ranging from 1.11 (0.68–1.79) to 2.52 (1.46–4.34) (men with hypothyroidism kept out owing to too few numbers). However, in persons not reporting, but having laboratory results indicating these diseases (unknown disease), no corresponding associations with SRH were found. Contrary, the OR for poor SRH in women with unknown hypothyroidism and unknown hypertension was 0.64 (0.38–1.06) and 0.89 (0.79–1.01), respectively. Conclusions. Awareness opposed to ignorance of hypothyroidism, DM and hypertension seemed to be associated with poor perceived health, suggesting that diagnostic labelling could have a negative effect on SRH. This relationship needs to be tested more thoroughly in future research but should be kept in mind regarding the benefits of early diagnosing of diseases. PMID:26240089

Optical Characterization of Deep-Space Object Rotation States

DTIC Science & Technology

2014-09-01

surface bi-directional reflectance distribution function ( BRDF ), and then estimate the asteroid’s shape via a best-fit parameterized model . This hybrid...approach can be used because asteroid BRDFs are relatively well studied, but their shapes are generally unknown [17]. Asteroid shape models range...can be accomplished using a shape-dependent method that employs a model of the shape and reflectance characteristics of the object. Our analysis

Bayesian nonlinear structural FE model and seismic input identification for damage assessment of civil structures

NASA Astrophysics Data System (ADS)

Astroza, Rodrigo; Ebrahimian, Hamed; Li, Yong; Conte, Joel P.

2017-09-01

A methodology is proposed to update mechanics-based nonlinear finite element (FE) models of civil structures subjected to unknown input excitation. The approach allows to jointly estimate unknown time-invariant model parameters of a nonlinear FE model of the structure and the unknown time histories of input excitations using spatially-sparse output response measurements recorded during an earthquake event. The unscented Kalman filter, which circumvents the computation of FE response sensitivities with respect to the unknown model parameters and unknown input excitations by using a deterministic sampling approach, is employed as the estimation tool. The use of measurement data obtained from arrays of heterogeneous sensors, including accelerometers, displacement sensors, and strain gauges is investigated. Based on the estimated FE model parameters and input excitations, the updated nonlinear FE model can be interrogated to detect, localize, classify, and assess damage in the structure. Numerically simulated response data of a three-dimensional 4-story 2-by-1 bay steel frame structure with six unknown model parameters subjected to unknown bi-directional horizontal seismic excitation, and a three-dimensional 5-story 2-by-1 bay reinforced concrete frame structure with nine unknown model parameters subjected to unknown bi-directional horizontal seismic excitation are used to illustrate and validate the proposed methodology. The results of the validation studies show the excellent performance and robustness of the proposed algorithm to jointly estimate unknown FE model parameters and unknown input excitations.

Super-Earth at a distance of less than 1,000 AU in solar system is absent

NASA Astrophysics Data System (ADS)

Vidmachenko, A. P.

2017-12-01

Numerous observations have shown that the Kuiper belt is a dynamically stable system. The source of cometary nuclei can be a scattered disk. It is an area created by outward-directed gravitational perturbations of the outer giant planets more than 4 billion years ago. The objects of the scattered disk are similar to the bodies of the Kuiper belt. But they go in their orbits for distances up to several hundred astronomical units (AU). In 2016 Brown and Batygin reported about indirect evidence of the existence of so far unknown ninth planet in the Solar system. They suggested, that orbits of 6 known trans-Neptunian objects of scattered disk are oriented so, that they can be influenced by a large, yet unknown body. We draw attention to the fact, that these 6 objects in close to their discovering moments were located at perihelion. We assume that for many orders of magnitude a larger number of the same trans-Neptunian objects should be located at a greater distance from the perihelion. Therefore, a possible number of the same trans-Neptunian objects should be counted in many thousands. We used the observation data obtained by Space Telescope "WISE" (Wide-Field Infrared Survey Explorer). It was established that there is no analogue of the giant planet Saturn at distances up to 30000 AU. This circumstance allowed us to calculate that at distances up to 1000 AU it would be clearly visible planetary body with a radius of more than 11000 km. That is, a planet with a possible mass of about 10 Earth masses and an "earth" density (5.52 t/m3). If we take into account that the density of the "average" trans-Neptunian object differs little from 2 t/m3, the radius of such a body will increase to 19200 km. And then the limit of detection of the body will increase by almost 4 times: up to 4000 AU. (!) Thus, either unknown 9th planet is now even further, or our results cannot be directly scaled for the planet "Super-Earth", which at such large distance can have a disproportionately low source of internal heat.

Performance in Object-Choice Aesop's Fable Tasks Are Influenced by Object Biases in New Caledonian Crows but not in Human Children.

PubMed

Miller, Rachael; Jelbert, Sarah A; Taylor, Alex H; Cheke, Lucy G; Gray, Russell D; Loissel, Elsa; Clayton, Nicola S

2016-01-01

The ability to reason about causality underlies key aspects of human cognition, but the extent to which non-humans understand causality is still largely unknown. The Aesop's Fable paradigm, where objects are inserted into water-filled tubes to obtain out-of-reach rewards, has been used to test casual reasoning in birds and children. However, success on these tasks may be influenced by other factors, specifically, object preferences present prior to testing or arising during pre-test stone-dropping training. Here, we assessed this 'object-bias' hypothesis by giving New Caledonian crows and 5-10 year old children two object-choice Aesop's Fable experiments: sinking vs. floating objects, and solid vs. hollow objects. Before each test, we assessed subjects' object preferences and/or trained them to prefer the alternative object. Both crows and children showed pre-test object preferences, suggesting that birds in previous Aesop's Fable studies may also have had initial preferences for objects that proved to be functional on test. After training to prefer the non-functional object, crows, but not children, performed more poorly on these two object-choice Aesop's Fable tasks than subjects in previous studies. Crows dropped the non-functional objects into the tube on their first trials, indicating that, unlike many children, they do not appear to have an a priori understanding of water displacement. Alternatively, issues with inhibition could explain their performance. The crows did, however, learn to solve the tasks over time. We tested crows further to determine whether their eventual success was based on learning about the functional properties of the objects, or associating dropping the functional object with reward. Crows inserted significantly more rewarded, non-functional objects than non-rewarded, functional objects. These findings suggest that the ability of New Caledonian crows to produce performances rivaling those of young children on object-choice Aesop's Fable tasks is partly due to pre-existing object preferences.

Automatic Camera Calibration for Cultural Heritage Applications Using Unstructured Planar Objects

NASA Astrophysics Data System (ADS)

Adam, K.; Kalisperakis, I.; Grammatikopoulos, L.; Karras, G.; Petsa, E.

2013-07-01

As a rule, image-based documentation of cultural heritage relies today on ordinary digital cameras and commercial software. As such projects often involve researchers not familiar with photogrammetry, the question of camera calibration is important. Freely available open-source user-friendly software for automatic camera calibration, often based on simple 2D chess-board patterns, are an answer to the demand for simplicity and automation. However, such tools cannot respond to all requirements met in cultural heritage conservation regarding possible imaging distances and focal lengths. Here we investigate the practical possibility of camera calibration from unknown planar objects, i.e. any planar surface with adequate texture; we have focused on the example of urban walls covered with graffiti. Images are connected pair-wise with inter-image homographies, which are estimated automatically through a RANSAC-based approach after extracting and matching interest points with the SIFT operator. All valid points are identified on all images on which they appear. Provided that the image set includes a "fronto-parallel" view, inter-image homographies with this image are regarded as emulations of image-to-world homographies and allow computing initial estimates for the interior and exterior orientation elements. Following this initialization step, the estimates are introduced into a final self-calibrating bundle adjustment. Measures are taken to discard unsuitable images and verify object planarity. Results from practical experimentation indicate that this method may produce satisfactory results. The authors intend to incorporate the described approach into their freely available user-friendly software tool, which relies on chess-boards, to assist non-experts in their projects with image-based approaches.

Sleep Misperception and Chronic Insomnia in the General Population: The Role of Objective Sleep Duration and Psychological Profiles

PubMed Central

Fernandez-Mendoza, Julio; Calhoun, Susan L.; Bixler, Edward O.; Karataraki, Maria; Liao, Duanping; Vela-Bueno, Antonio; Ramos-Platon, María Jose; Sauder, Katherine A.; Basta, Maria; Vgontzas, Alexandros N.

2011-01-01

Objective Sleep misperception is considered by some investigators a common characteristic of chronic insomnia, whereas others propose it as a separate diagnosis. The frequency and the determinants of sleep misperception in general population samples are unknown. In this study we examined the role of objective sleep duration, a novel marker in phenotyping insomnia, and psychological profiles on sleep misperception in a large, general population sample. Methods 142 insomniacs and 724 controls selected from a general random sample of 1,741 individuals (age ≥ 20 years) underwent a polysomnographic evaluation, completed the Minnesota Multiphasic Personality Inventory-2, and were split into two groups based on their objective sleep duration: “normal sleep duration” (≥ 6 hours) and “short sleep duration” (< 6 hours). Results The discrepancy between subjective and objective sleep duration was determined by two independent factors. Short sleepers reported more sleep than they objectively had and insomniacs reported less sleep than controls with similar objective sleep duration. The additive effect of these two factors resulted in underestimation only in insomniacs with normal sleep duration. Insomniacs with normal sleep duration showed a MMPI-2 profile of high depression and anxiety, and low ego strength, whereas insomniacs with short sleep duration showed a profile of a medical disorder. Conclusions Underestimation of sleep duration is prevalent among insomniacs with objective normal sleep duration. Anxious-ruminative traits and poor resources for coping with stress appear to mediate the underestimation of sleep duration. These data further support the validity and clinical utility of objective sleep measures in phenotyping insomnia. PMID:20978224

The trans-neptunian object UB313 is larger than Pluto.

PubMed

Bertoldi, F; Altenhoff, W; Weiss, A; Menten, K M; Thum, C

2006-02-02

The most distant known object in the Solar System, 2003 UB313 (97 au from the Sun), was recently discovered near its aphelion. Its high eccentricity and inclination to the ecliptic plane, along with its perihelion near the orbit of Neptune, identify it as a member of the 'scattered disk'. This disk of bodies probably originates in the Kuiper belt objects, which orbit near the ecliptic plane in circular orbits between 30 and 50 au, and may include Pluto as a member. The optical brightness of 2003 UB313, if adjusted to Pluto's distance, is greater than that of Pluto, which suggested that it might be larger than Pluto. The actual size, however, could not be determined from the optical measurements because the surface reflectivity (albedo) was unknown. Here we report observations of the thermal emission of 2003 UB313 at a wavelength of 1.2 mm, which in combination with the measured optical brightness leads to a diameter of 3,000 +/- 300 +/- 100 km. Here the first error reflects measurement uncertainties, while the second derives from the unknown object orientation. This makes 2003 UB313 the largest known trans-neptunian object, even larger than Pluto (2,300 km). The albedo is 0.60 +/- 0.10 +/- 0.05, which is strikingly similar to that of Pluto, suggesting that the methane seen in the optical spectrum causes a highly reflective icy surface.

On a problematic procedure to manipulate response biases in recognition experiments: the case of "implied" base rates.

PubMed

Bröder, Arndt; Malejka, Simone

2017-07-01

The experimental manipulation of response biases in recognition-memory tests is an important means for testing recognition models and for estimating their parameters. The textbook manipulations for binary-response formats either vary the payoff scheme or the base rate of targets in the recognition test, with the latter being the more frequently applied procedure. However, some published studies reverted to implying different base rates by instruction rather than actually changing them. Aside from unnecessarily deceiving participants, this procedure may lead to cognitive conflicts that prompt response strategies unknown to the experimenter. To test our objection, implied base rates were compared to actual base rates in a recognition experiment followed by a post-experimental interview to assess participants' response strategies. The behavioural data show that recognition-memory performance was estimated to be lower in the implied base-rate condition. The interview data demonstrate that participants used various second-order response strategies that jeopardise the interpretability of the recognition data. We thus advice researchers against substituting actual base rates with implied base rates.

Distributed Optimization Design of Continuous-Time Multiagent Systems With Unknown-Frequency Disturbances.

PubMed

Wang, Xinghu; Hong, Yiguang; Yi, Peng; Ji, Haibo; Kang, Yu

2017-05-24

In this paper, a distributed optimization problem is studied for continuous-time multiagent systems with unknown-frequency disturbances. A distributed gradient-based control is proposed for the agents to achieve the optimal consensus with estimating unknown frequencies and rejecting the bounded disturbance in the semi-global sense. Based on convex optimization analysis and adaptive internal model approach, the exact optimization solution can be obtained for the multiagent system disturbed by exogenous disturbances with uncertain parameters.

Associations of endothelial function and air temperature in diabetic subjects

EPA Science Inventory

Background and Objective: Epidemiological studies consistently show that air temperature is associated with changes in cardiovascular morbidity and mortality. However, the biological mechanisms underlying the association remain largely unknown. As one index of endothelial functio...

Promoting Community Health Resources: Preferred Communication Strategies

USDA-ARS?s Scientific Manuscript database

Background: Community health promotion efforts involve communicating resource information to priority populations. Which communication strategies are most effective is largely unknown for specific populations. Objective: A random-dialed telephone survey was conducted to assess health resource comm...

Epistemic and aleatory uncertainty in the study of dynamic human-water systems

NASA Astrophysics Data System (ADS)

Di Baldassarre, Giuliano; Brandimarte, Luigia; Beven, Keith

2016-04-01

Here we discuss epistemic and aleatory uncertainty in the study of dynamic human-water systems (e.g. socio-hydrology), which is one of the main topics of Panta Rhei, the current scientific decade of the International Association of Hydrological Sciences (IAHS). In particular, we identify three types of lack of understanding: (i) known unknowns, which are things we know we don't know; (ii) unknown unknowns, which are things we don't know we don't know; and (iii) wrong assumptions, things we think we know, but we actually don't know. We posit that a better understanding of human-water interactions and feedbacks can help coping with wrong assumptions and known unknowns. Moreover, being aware of the existence of unknown unknowns, and their potential capability to generate surprises or black swans, suggest the need to rely more on bottom-up approaches, based on social vulnerabilities and possibilities of failures, and less on top-down approaches, based on optimization and quantitative predictions.

Measurement of limb volume: laser scanning versus volume displacement.

PubMed

McKinnon, John Gregory; Wong, Vanessa; Temple, Walley J; Galbraith, Callum; Ferry, Paul; Clynch, George S; Clynch, Colin

2007-10-01

Determining the prevalence and treatment success of surgical lymphedema requires accurate and reproducible measurement. A new method of measurement of limb volume is described. A series of inanimate objects of known and unknown volume was measured using digital laser scanning and water displacement. A similar comparison was made with 10 human volunteers. Digital scanning was evaluated by comparison to the established method of water displacement, then to itself to determine reproducibility of measurement. (1) Objects of known volume: Laser scanning accurately measured the calculated volume but water displacement became less accurate as the size of the object increased. (2) Objects of unknown volume: As average volume increased, there was an increasing bias of underestimation of volume by the water displacement method. The coefficient of reproducibility of water displacement was 83.44 ml. In contrast, the reproducibility of the digital scanning method was 19.0 ml. (3) Human data: The mean difference between water displacement volume and laser scanning volume was 151.7 ml (SD +/- 189.5). The coefficient of reproducibility of water displacement was 450.8 ml whereas for laser scanning it was 174 ml. Laser scanning is an innovative method of measuring tissue volume that combines precision and reproducibility and may have clinical utility for measuring lymphedema. 2007 Wiley-Liss, Inc

Robust interval-based regulation for anaerobic digestion processes.

PubMed

Alcaraz-González, V; Harmand, J; Rapaport, A; Steyer, J P; González-Alvarez, V; Pelayo-Ortiz, C

2005-01-01

A robust regulation law is applied to the stabilization of a class of biochemical reactors exhibiting partially known highly nonlinear dynamic behavior. An uncertain environment with the presence of unknown inputs is considered. Based on some structural and operational conditions, this regulation law is shown to exponentially stabilize the aforementioned bioreactors around a desired set-point. This approach is experimentally applied and validated on a pilot-scale (1 m3) anaerobic digestion process for the treatment of raw industrial wine distillery wastewater where the objective is the regulation of the chemical oxygen demand (COD) by using the dilution rate as the manipulated variable. Despite large disturbances on the input COD and state and parametric uncertainties, this regulation law gave excellent performances leading the output COD towards its set-point and keeping it inside a pre-specified interval.

Economic outcomes of maintenance gefitinib for locally advanced/metastatic non-small-cell lung cancer with unknown EGFR mutations: a semi-Markov model analysis.

PubMed

Zeng, Xiaohui; Li, Jianhe; Peng, Liubao; Wang, Yunhua; Tan, Chongqing; Chen, Gannong; Wan, Xiaomin; Lu, Qiong; Yi, Lidan

2014-01-01

Maintenance gefitinib significantly prolonged progression-free survival (PFS) compared with placebo in patients from eastern Asian with locally advanced/metastatic non-small-cell lung cancer (NSCLC) after four chemotherapeutic cycles (21 days per cycle) of first-line platinum-based combination chemotherapy without disease progression. The objective of the current study was to evaluate the cost-effectiveness of maintenance gefitinib therapy after four chemotherapeutic cycle's stand first-line platinum-based chemotherapy for patients with locally advanced or metastatic NSCLC with unknown EGFR mutations, from a Chinese health care system perspective. A semi-Markov model was designed to evaluate cost-effectiveness of the maintenance gefitinib treatment. Two-parametric Weibull and Log-logistic distribution were fitted to PFS and overall survival curves independently. One-way and probabilistic sensitivity analyses were conducted to assess the stability of the model designed. The model base-case analysis suggested that maintenance gefitinib would increase benefits in a 1, 3, 6 or 10-year time horizon, with incremental $184,829, $19,214, $19,328, and $21,308 per quality-adjusted life-year (QALY) gained, respectively. The most sensitive influential variable in the cost-effectiveness analysis was utility of PFS plus rash, followed by utility of PFS plus diarrhoea, utility of progressed disease, price of gefitinib, cost of follow-up treatment in progressed survival state, and utility of PFS on oral therapy. The price of gefitinib is the most significant parameter that could reduce the incremental cost per QALY. Probabilistic sensitivity analysis indicated that the cost-effective probability of maintenance gefitinib was zero under the willingness-to-pay (WTP) threshold of $16,349 (3 × per-capita gross domestic product of China). The sensitivity analyses all suggested that the model was robust. Maintenance gefitinib following first-line platinum-based chemotherapy for patients with locally advanced/metastatic NSCLC with unknown EGFR mutations is not cost-effective. Decreasing the price of gefitinib may be a preferential choice for meeting widely treatment demands in China.

Partial autolysis of μ/m-calpain during post mortem aging of chicken muscle.

PubMed

Zhao, Liang; Jiang, Nanqi; Li, Miaozhen; Huang, Ming; Zhou, Guanghong

2016-12-01

The objective of this study was to investigate changes occurring in μ/m-calpain in post mortem chicken muscles and to determine the origin of the unknown bands found in calpain casein zymography. The unknown bands were reported with slightly greater mobility compared to conventional μ/m-calpain bands in casein zymography. Identification of these bands was accomplished using native polyacrylamide gel electrophoresis, liquid chromatography tandem mass spectrometry and with protein phosphatase treatment. Results showed that the unknown bands were corresponding to μ/m-calpain, and dephosphorylation by protein phosphatase did not change their appearance. The calpain samples were then incubated with various concentrations of Ca 2+ to determine the relationship between changes in μ/m-calpain and the appearance of the unknown bands. The products of μ/m-calpain partial autolysis were found to be consistent with the appearance of the unknown bands. Therefore, the appearance of these bands did not result from phosphorylation of μ/m-calpain as previously hypothesized, but from partial autolysis of μ/m-calpain. Also their presence suggests that μ/m-calpain undergoes partial autolysis during aging which may play certain roles in meat quality improvement. © 2016 Japanese Society of Animal Science.

Economic costs of recorded reasons for cow mortality and culling in a pasture-based dairy industry.

PubMed

Kerslake, J I; Amer, P R; O'Neill, P L; Wong, S L; Roche, J R; Phyn, C V C

2018-02-01

The objective of this study was to determine the economic costs associated with different reasons for cow culling or on-farm mortality in a pasture-based seasonal system. A bioeconomic model was developed to quantify costs associated with the different farmer-recorded reasons and timing of cow wastage. The model accounted for the parity and stage of lactation at which the cows were removed as well as the consequent effect on the replacement rate and average age structure of the herd. The costs and benefits associated with the change were quantified, including animal replacement cost, cull salvage value, milk production loss, and the profitability of altered genetic merit based on industry genetic trends for each parity. The total cost of cow wastage was estimated to be NZ$23,628/100 cows per year (NZ$1 = US$0.69) in a pasture-based system. Of this total cost, NZ$14,300/100 cows worth of removals were for nonpregnancy and unknown reasons, and another NZ$3,631/100 cows was attributed to low milk production, mastitis, and udder problems. The total cost for cow removals due to farmer-recorded biological reasons (excluding unknown, production, and management-related causes) was estimated to be NZ$13,632/100 cows per year. Of this cost, an estimated NZ$10,286/100 cows was attributed to nonpregnancy, mastitis, udder problems, calving trouble, and injury or accident. There is a strong economic case for the pasture-based dairy industries to invest in genetic, herd health, and production management research focused on reducing animal wastage due to reproductive failure, mastitis, udder problems, injuries or accidents, and calving difficulties. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Fuzzy similarity measures for ultrasound tissue characterization

NASA Astrophysics Data System (ADS)

Emara, Salem M.; Badawi, Ahmed M.; Youssef, Abou-Bakr M.

1995-03-01

Computerized ultrasound tissue characterization has become an objective means for diagnosis of diseases. It is difficult to differentiate diffuse liver diseases, namely cirrhotic and fatty liver from a normal one, by visual inspection from the ultrasound images. The visual criteria for differentiating diffused diseases is rather confusing and highly dependent upon the sonographer's experience. The need for computerized tissue characterization is thus justified to quantitatively assist the sonographer for accurate differentiation and to minimize the degree of risk from erroneous interpretation. In this paper we used the fuzzy similarity measure as an approximate reasoning technique to find the maximum degree of matching between an unknown case defined by a feature vector and a family of prototypes (knowledge base). The feature vector used for the matching process contains 8 quantitative parameters (textural, acoustical, and speckle parameters) extracted from the ultrasound image. The steps done to match an unknown case with the family of prototypes (cirr, fatty, normal) are: Choosing the membership functions for each parameter, then obtaining the fuzzification matrix for the unknown case and the family of prototypes, then by the linguistic evaluation of two fuzzy quantities we obtain the similarity matrix, then by a simple aggregation method and the fuzzy integrals we obtain the degree of similarity. Finally, we find that the similarity measure results are comparable to the neural network classification techniques and it can be used in medical diagnosis to determine the pathology of the liver and to monitor the extent of the disease.

Estimation of the incubation period of invasive aspergillosis by survival models in acute myeloid leukemia patients.

PubMed

Bénet, Thomas; Voirin, Nicolas; Nicolle, Marie-Christine; Picot, Stephane; Michallet, Mauricette; Vanhems, Philippe

2013-02-01

The duration of the incubation of invasive aspergillosis (IA) remains unknown. The objective of this investigation was to estimate the time interval between aplasia onset and that of IA symptoms in acute myeloid leukemia (AML) patients. A single-centre prospective survey (2004-2009) included all patients with AML and probable/proven IA. Parametric survival models were fitted to the distribution of the time intervals between aplasia onset and IA. Overall, 53 patients had IA after aplasia, with the median observed time interval between the two being 15 days. Based on log-normal distribution, the median estimated IA incubation period was 14.6 days (95% CI; 12.8-16.5 days).

Object aggregation using Neyman-Pearson analysis

NASA Astrophysics Data System (ADS)

Bai, Li; Hinman, Michael L.

2003-04-01

This paper presents a novel approach to: 1) distinguish military vehicle groups, and 2) identify names of military vehicle convoys in the level-2 fusion process. The data is generated from a generic Ground Moving Target Indication (GMTI) simulator that utilizes Matlab and Microsoft Access. This data is processed to identify the convoys and number of vehicles in the convoy, using the minimum timed distance variance (MTDV) measurement. Once the vehicle groups are formed, convoy association is done using hypothesis techniques based upon Neyman Pearson (NP) criterion. One characteristic of NP is the low error probability when a-priori information is unknown. The NP approach was demonstrated with this advantage over a Bayesian technique.

A novel SURE-based criterion for parametric PSF estimation.

PubMed

Xue, Feng; Blu, Thierry

2015-02-01

We propose an unbiased estimate of a filtered version of the mean squared error--the blur-SURE (Stein's unbiased risk estimate)--as a novel criterion for estimating an unknown point spread function (PSF) from the degraded image only. The PSF is obtained by minimizing this new objective functional over a family of Wiener processings. Based on this estimated blur kernel, we then perform nonblind deconvolution using our recently developed algorithm. The SURE-based framework is exemplified with a number of parametric PSF, involving a scaling factor that controls the blur size. A typical example of such parametrization is the Gaussian kernel. The experimental results demonstrate that minimizing the blur-SURE yields highly accurate estimates of the PSF parameters, which also result in a restoration quality that is very similar to the one obtained with the exact PSF, when plugged into our recent multi-Wiener SURE-LET deconvolution algorithm. The highly competitive results obtained outline the great potential of developing more powerful blind deconvolution algorithms based on SURE-like estimates.

Reconstruction of the unknown optimization cost functions from experimental recordings during static multi-finger prehension

PubMed Central

Niu, Xun; Terekhov, Alexander V.; Latash, Mark L.; Zatsiorsky, Vladimir M.

2013-01-01

The goal of the research is to reconstruct the unknown cost (objective) function(s) presumably used by the neural controller for sharing the total force among individual fingers in multi-finger prehension. The cost function was determined from experimental data by applying the recently developed Analytical Inverse Optimization (ANIO) method (Terekhov et al 2010). The core of the ANIO method is the Theorem of Uniqueness that specifies conditions for unique (with some restrictions) estimation of the objective functions. In the experiment, subjects (n=8) grasped an instrumented handle and maintained it at rest in the air with various external torques, loads, and target grasping forces applied to the object. The experimental data recorded from 80 trials showed a tendency to lie on a 2-dimensional hyperplane in the 4-dimensional finger-force space. Because the constraints in each trial were different, such a propensity is a manifestation of a neural mechanism (not the task mechanics). In agreement with the Lagrange principle for the inverse optimization, the plane of experimental observations was close to the plane resulting from the direct optimization. The latter plane was determined using the ANIO method. The unknown cost function was reconstructed successfully for each performer, as well as for the group data. The cost functions were found to be quadratic with non-zero linear terms. The cost functions obtained with the ANIO method yielded more accurate results than other optimization methods. The ANIO method has an evident potential for addressing the problem of optimization in motor control. PMID:22104742

Carcinoma of Unknown Primary—Health Professional Version

Cancer.gov

Carcinoma of unknown primary (CUP) is a rare disease in which malignant cells are found in the body but the site of the primary cancer is not known. Most CUPs are adenocarcinomas, or undifferentiated tumors. Find evidence-based information on the treatment for carcinoma of unknown primary.

Unknown Patients and Neurology Casualty Services in an Indian Metropolitan City: A Decades Experience

PubMed Central

Umesh, Achary; Gowda, Guru S; Kumar, Channaveerachari Naveen; Srinivas, Dwarakanath; Dawn, Bharath Rose; Botta, Ragasudha; Yadav, Ravi; Math, Suresh Bada

2017-01-01

Objectives: A large number of unknown patients without any personal, family, or other identification details represent a unique problem in the neurological emergency services of developing countries like India in a context of legal, humanitarian, and treatment issues. These patients pose a diagnostic and management challenge to treating physicians and staff. There are sparse data on these patients. The objective of this study was to know the clinical, socio-demographic, and investigational profile of “unknown” patients. Materials and Methods: We did retrospective chart review of all “Unknown” patients from January 2002 to December 2011, who was admitted under Neurology Emergency Service at a Tertiary Care Neuropsychiatry Center in South Indian Metropolitan City. Clinical and sociodemographic characteristics and clinical outcome of the sample were analyzed. Results: A total of 151 unknown patients were admitted during the 10 years. Out of these, 134 (88.7%) were males with the mean age of 43.8 ± 14.8 years and 95 (63%) were aged >40 years. Among them, 147 (97.4%) were from the urban vicinity, 126 (83.6%) were brought by police and 75 (49.7%) were registered as medico-legal cases. Out of these, only 3 (2%) patients had normal sensorium, whereas 101 (66.9%) presented with loss of consciousness. Forty-one (27.2%) unknown patients had a seizure disorder, 37 (24.5%) had metabolic encephalopathy, 26 (17.2%) had a stroke, 9 (6%) had neuro-infection, and 17 (11.3%) had a head injury. Deranged liver functions were seen in 65 (43%), renal derangement in 37 (24.5%), dyselectrolytemia in 42 (27.8%), and abnormal brain imaging finding in 95 (62.9%) patients. Furthermore, there were 14 (9.3%) deaths. Conclusions: Our findings demonstrate seizures, metabolic causes, and neuro-infections were the primary reasons for admission of unknown patients to neuro-emergency service. This novel Indian study data show the common causes of admission of unknown patients in neurology. This pattern can be useful to guide the approach of healthcare providers in India. PMID:28615894

An eigenvalue approach for the automatic scaling of unknowns in model-based reconstructions: Application to real-time phase-contrast flow MRI.

PubMed

Tan, Zhengguo; Hohage, Thorsten; Kalentev, Oleksandr; Joseph, Arun A; Wang, Xiaoqing; Voit, Dirk; Merboldt, K Dietmar; Frahm, Jens

2017-12-01

The purpose of this work is to develop an automatic method for the scaling of unknowns in model-based nonlinear inverse reconstructions and to evaluate its application to real-time phase-contrast (RT-PC) flow magnetic resonance imaging (MRI). Model-based MRI reconstructions of parametric maps which describe a physical or physiological function require the solution of a nonlinear inverse problem, because the list of unknowns in the extended MRI signal equation comprises multiple functional parameters and all coil sensitivity profiles. Iterative solutions therefore rely on an appropriate scaling of unknowns to numerically balance partial derivatives and regularization terms. The scaling of unknowns emerges as a self-adjoint and positive-definite matrix which is expressible by its maximal eigenvalue and solved by power iterations. The proposed method is applied to RT-PC flow MRI based on highly undersampled acquisitions. Experimental validations include numerical phantoms providing ground truth and a wide range of human studies in the ascending aorta, carotid arteries, deep veins during muscular exercise and cerebrospinal fluid during deep respiration. For RT-PC flow MRI, model-based reconstructions with automatic scaling not only offer velocity maps with high spatiotemporal acuity and much reduced phase noise, but also ensure fast convergence as well as accurate and precise velocities for all conditions tested, i.e. for different velocity ranges, vessel sizes and the simultaneous presence of signals with velocity aliasing. In summary, the proposed automatic scaling of unknowns in model-based MRI reconstructions yields quantitatively reliable velocities for RT-PC flow MRI in various experimental scenarios. Copyright © 2017 John Wiley & Sons, Ltd.

Research on laser protection: an overview of 20 years of activities at Fraunhofer IOSB

NASA Astrophysics Data System (ADS)

Ritt, G.; Walter, D.; Eberle, B.

2013-10-01

Since the advent of the laser in 1960, the protection of human eyes and sensors against intended or unintended damage by laser radiation is a hot research topic. As long as the parameters of a laser source such as the wavelength and the output power are known, adequate laser safety can be ensured simply by utilizing conventional laser protection filters which are based on absorption or interference effects. This is typically the case in cooperative environments like a laboratory or industrial facilities. A very different situation prevails in military defense or civil security. There, the parameters of encountering laser threats are usually unknown. Protection measures, helping against all types of laser threats, are the long desired objective of countless research activities. The biggest challenge in finding an effective measure arises from single laser pulses of unknown wavelength. The problem demands for a passive protection concept and may be based for example on intensity dependent effects. Moreover, the requested solutions shall comprise add-on possibilities like thin films to be put on existing optics, windshields or glasses. Unfortunately, such an all-embracing solution is still far out of reach. The Fraunhofer IOSB has been working on the evaluation and development of non-conventional laser protection methods for more than 20 years. An overview of the past and present research activities shall be presented, comprising protection measures against laser damaging and laser dazzling.

Fluctuating volume-current formulation of electromagnetic fluctuations in inhomogeneous media: Incandescence and luminescence in arbitrary geometries

NASA Astrophysics Data System (ADS)

Polimeridis, Athanasios G.; Reid, M. T. H.; Jin, Weiliang; Johnson, Steven G.; White, Jacob K.; Rodriguez, Alejandro W.

2015-10-01

We describe a fluctuating volume-current formulation of electromagnetic fluctuations that extends our recent work on heat exchange and Casimir interactions between arbitrarily shaped homogeneous bodies [A. W. Rodriguez, M. T. H. Reid, and S. G. Johnson, Phys. Rev. B 88, 054305 (2013), 10.1103/PhysRevB.88.054305] to situations involving incandescence and luminescence problems, including thermal radiation, heat transfer, Casimir forces, spontaneous emission, fluorescence, and Raman scattering, in inhomogeneous media. Unlike previous scattering formulations based on field and/or surface unknowns, our work exploits powerful techniques from the volume-integral equation (VIE) method, in which electromagnetic scattering is described in terms of volumetric, current unknowns throughout the bodies. The resulting trace formulas (boxed equations) involve products of well-studied VIE matrices and describe power and momentum transfer between objects with spatially varying material properties and fluctuation characteristics. We demonstrate that thanks to the low-rank properties of the associated matrices, these formulas are susceptible to fast-trace computations based on iterative methods, making practical calculations tractable. We apply our techniques to study thermal radiation, heat transfer, and fluorescence in complicated geometries, checking our method against established techniques best suited for homogeneous bodies as well as applying it to obtain predictions of radiation from complex bodies with spatially varying permittivities and/or temperature profiles.

Observer-based robust finite time H∞ sliding mode control for Markovian switching systems with mode-dependent time-varying delay and incomplete transition rate.

PubMed

Gao, Lijun; Jiang, Xiaoxiao; Wang, Dandan

2016-03-01

This paper investigates the problem of robust finite time H∞ sliding mode control for a class of Markovian switching systems. The system is subjected to the mode-dependent time-varying delay, partly unknown transition rate and unmeasurable state. The main difficulty is that, a sliding mode surface cannot be designed based on the unknown transition rate and unmeasurable state directly. To overcome this obstacle, the set of modes is firstly divided into two subsets standing for known transition rate subset and unknown one, based on which a state observer is established. A component robust finite-time sliding mode controller is also designed to cope with the effect of partially unknown transition rate. It is illustrated that the reachability, finite-time stability, finite-time boundedness, finite-time H∞ state feedback stabilization of sliding mode dynamics can be ensured despite the unknown transition rate. Finally, the simulation results verify the effectiveness of robust finite time control problem. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

WISE Observations of Comets, Centaurs, & Scattered Disk Objects

NASA Technical Reports Server (NTRS)

Bauer, J.; Walker, R.; Mainzer, A.; Masiero, J.; Grav, T.; Cutri, R.; Dailey, J.; McMillan, R.; Lisse, C. M.; Fernandez, Y. R.;

Vibrotactile sensory substitution for object manipulation: amplitude versus pulse train frequency modulation.

PubMed

Stepp, Cara E; Matsuoka, Yoky

2012-01-01

Incorporating sensory feedback with prosthetic devices is now possible, but the optimal methods of providing such feedback are still unknown. The relative utility of amplitude and pulse train frequency modulated stimulation paradigms for providing vibrotactile feedback for object manipulation was assessed in 10 participants. The two approaches were studied during virtual object manipulation using a robotic interface as a function of presentation order and a simultaneous cognitive load. Despite the potential pragmatic benefits associated with pulse train frequency modulated vibrotactile stimulation, comparison of the approach with amplitude modulation indicates that amplitude modulation vibrotactile stimulation provides superior feedback for object manipulation.

Matrix- and tensor-based recommender systems for the discovery of currently unknown inorganic compounds

NASA Astrophysics Data System (ADS)

Seko, Atsuto; Hayashi, Hiroyuki; Kashima, Hisashi; Tanaka, Isao

2018-01-01

Chemically relevant compositions (CRCs) and atomic arrangements of inorganic compounds have been collected as inorganic crystal structure databases. Machine learning is a unique approach to search for currently unknown CRCs from vast candidates. Herein we propose matrix- and tensor-based recommender system approaches to predict currently unknown CRCs from database entries of CRCs. Firstly, the performance of the recommender system approaches to discover currently unknown CRCs is examined. A Tucker decomposition recommender system shows the best discovery rate of CRCs as the majority of the top 100 recommended ternary and quaternary compositions correspond to CRCs. Secondly, systematic density functional theory (DFT) calculations are performed to investigate the phase stability of the recommended compositions. The phase stability of the 27 compositions reveals that 23 currently unknown compounds are newly found to be stable. These results indicate that the recommender system has great potential to accelerate the discovery of new compounds.

Understanding the function of visual short-term memory: transsaccadic memory, object correspondence, and gaze correction.

PubMed

Hollingworth, Andrew; Richard, Ashleigh M; Luck, Steven J

2008-02-01

Visual short-term memory (VSTM) has received intensive study over the past decade, with research focused on VSTM capacity and representational format. Yet, the function of VSTM in human cognition is not well understood. Here, the authors demonstrate that VSTM plays an important role in the control of saccadic eye movements. Intelligent human behavior depends on directing the eyes to goal-relevant objects in the world, yet saccades are very often inaccurate and require correction. The authors hypothesized that VSTM is used to remember the features of the current saccade target so that it can be rapidly reacquired after an errant saccade, a task faced by the visual system thousands of times each day. In 4 experiments, memory-based gaze correction was accurate, fast, automatic, and largely unconscious. In addition, a concurrent VSTM load interfered with memory-based gaze correction, but a verbal short-term memory load did not. These findings demonstrate that VSTM plays a direct role in a fundamentally important aspect of visually guided behavior, and they suggest the existence of previously unknown links between VSTM representations and the occulomotor system. PsycINFO Database Record (c) 2008 APA, all rights reserved.

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras.

PubMed

Li, Zhenyu; Wang, Bin; Liu, Hong

2016-08-30

Satellite capturing with free-floating space robots is still a challenging task due to the non-fixed base and unknown mass property issues. In this paper gyro and eye-in-hand camera data are adopted as an alternative choice for solving this problem. For this improved system, a new modeling approach that reduces the complexity of system control and identification is proposed. With the newly developed model, the space robot is equivalent to a ground-fixed manipulator system. Accordingly, a self-tuning control scheme is applied to handle such a control problem including unknown parameters. To determine the controller parameters, an estimator is designed based on the least-squares technique for identifying the unknown mass properties in real time. The proposed method is tested with a credible 3-dimensional ground verification experimental system, and the experimental results confirm the effectiveness of the proposed control scheme.

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras

PubMed Central

Li, Zhenyu; Wang, Bin; Liu, Hong

2016-01-01

Satellite capturing with free-floating space robots is still a challenging task due to the non-fixed base and unknown mass property issues. In this paper gyro and eye-in-hand camera data are adopted as an alternative choice for solving this problem. For this improved system, a new modeling approach that reduces the complexity of system control and identification is proposed. With the newly developed model, the space robot is equivalent to a ground-fixed manipulator system. Accordingly, a self-tuning control scheme is applied to handle such a control problem including unknown parameters. To determine the controller parameters, an estimator is designed based on the least-squares technique for identifying the unknown mass properties in real time. The proposed method is tested with a credible 3-dimensional ground verification experimental system, and the experimental results confirm the effectiveness of the proposed control scheme. PMID:27589748

Efficacy of chemotherapy after first-line gefitinib therapy in EGFR mutation-positive advanced non-small cell lung cancer-data from a randomized Phase III study comparing gefitinib with carboplatin plus paclitaxel (NEJ002).

PubMed

Miyauchi, Eisaku; Inoue, Akira; Kobayashi, Kunihiko; Maemondo, Makoto; Sugawara, Shunichi; Oizumi, Satoshi; Isobe, Hiroshi; Gemma, Akihiko; Saijo, Yasuo; Yoshizawa, Hirohisa; Hagiwara, Koichi; Nukiwa, Toshihiro

2015-07-01

Epidermal growth factor receptor tyrosine kinase inhibitors are effective as first-line therapy for advanced non-small cell lung cancer patients harboring epidermal growth factor receptor mutations. However, it is unknown whether second-line platinum-based chemotherapy after epidermal growth factor receptor tyrosine kinase inhibitor therapy could lead to better outcomes. We evaluated the efficacy of second-line platinum-based chemotherapy after gefitinib for advanced non-small cell lung cancers harboring epidermal growth factor receptor mutations (the NEJ002 study). Seventy-one non-small cell lung cancers, treated with gefitinib as first-line therapy and then receiving platinum-based chemotherapy as second-line therapy were evaluated in NEJ002. Patients were evaluated for antitumor response to second-line chemotherapy by computed tomography according to the criteria of the Response Evaluation Criteria in Solid Tumors group (version 1.0). Of the 71 patients receiving platinum-based chemotherapy after first-line gefitinib, a partial response was documented in 25.4% (18/71), stable disease in 43.7% (31/71) and progression of disease in 21.1% (15/71). The objective response and disease control rates were 25.4% (18/71) and 69% (49/71), respectively. There was no significant difference between first- and second-line chemotherapy in objective response and disease control rates for advanced non-small cell lung cancer harboring activating epidermal growth factor receptor mutations. In the analysis of epidermal growth factor receptor mutation types, the objective responses of deletions in exon 19 and a point mutation in exon 21 (L858R) were 27.3% (9/33) and 28.1% (9/32), respectively, but these differences between objective response rates were not significant. The efficacy of second-line platinum-based chemotherapy followed at progression by gefitinib was similar to first-line platinum-based chemotherapy, and epidermal growth factor receptor mutation types did not influence the efficacy of second-line platinum-based chemotherapy. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Extending birthday paradox theory to estimate the number of tags in RFID systems.

PubMed

Shakiba, Masoud; Singh, Mandeep Jit; Sundararajan, Elankovan; Zavvari, Azam; Islam, Mohammad Tariqul

2014-01-01

The main objective of Radio Frequency Identification systems is to provide fast identification for tagged objects. However, there is always a chance of collision, when tags transmit their data to the reader simultaneously. Collision is a time-consuming event that reduces the performance of RFID systems. Consequently, several anti-collision algorithms have been proposed in the literature. Dynamic Framed Slotted ALOHA (DFSA) is one of the most popular of these algorithms. DFSA dynamically modifies the frame size based on the number of tags. Since the real number of tags is unknown, it needs to be estimated. Therefore, an accurate tag estimation method has an important role in increasing the efficiency and overall performance of the tag identification process. In this paper, we propose a novel estimation technique for DFSA anti-collision algorithms that applies birthday paradox theory to estimate the number of tags accurately. The analytical discussion and simulation results prove that the proposed method increases the accuracy of tag estimation and, consequently, outperforms previous schemes.

Efficient Compressed Sensing Based MRI Reconstruction using Nonconvex Total Variation Penalties

NASA Astrophysics Data System (ADS)

Lazzaro, D.; Loli Piccolomini, E.; Zama, F.

2016-10-01

This work addresses the problem of Magnetic Resonance Image Reconstruction from highly sub-sampled measurements in the Fourier domain. It is modeled as a constrained minimization problem, where the objective function is a non-convex function of the gradient of the unknown image and the constraints are given by the data fidelity term. We propose an algorithm, Fast Non Convex Reweighted (FNCR), where the constrained problem is solved by a reweighting scheme, as a strategy to overcome the non-convexity of the objective function, with an adaptive adjustment of the penalization parameter. We propose a fast iterative algorithm and we can prove that it converges to a local minimum because the constrained problem satisfies the Kurdyka-Lojasiewicz property. Moreover the adaptation of non convex l0 approximation and penalization parameters, by means of a continuation technique, allows us to obtain good quality solutions, avoiding to get stuck in unwanted local minima. Some numerical experiments performed on MRI sub-sampled data show the efficiency of the algorithm and the accuracy of the solution.

Confidence Leak in Perceptual Decision Making.

PubMed

Rahnev, Dobromir; Koizumi, Ai; McCurdy, Li Yan; D'Esposito, Mark; Lau, Hakwan

2015-11-01

People live in a continuous environment in which the visual scene changes on a slow timescale. It has been shown that to exploit such environmental stability, the brain creates a continuity field in which objects seen seconds ago influence the perception of current objects. What is unknown is whether a similar mechanism exists at the level of metacognitive representations. In three experiments, we demonstrated a robust intertask confidence leak-that is, confidence in one's response on a given task or trial influencing confidence on the following task or trial. This confidence leak could not be explained by response priming or attentional fluctuations. Better ability to modulate confidence leak predicted higher capacity for metacognition as well as greater gray matter volume in the prefrontal cortex. A model based on normative principles from Bayesian inference explained the results by postulating that observers subjectively estimate the perceptual signal strength in a stable environment. These results point to the existence of a novel metacognitive mechanism mediated by regions in the prefrontal cortex. © The Author(s) 2015.

Extending Birthday Paradox Theory to Estimate the Number of Tags in RFID Systems

PubMed Central

Shakiba, Masoud; Singh, Mandeep Jit; Sundararajan, Elankovan; Zavvari, Azam; Islam, Mohammad Tariqul

2014-01-01

The main objective of Radio Frequency Identification systems is to provide fast identification for tagged objects. However, there is always a chance of collision, when tags transmit their data to the reader simultaneously. Collision is a time-consuming event that reduces the performance of RFID systems. Consequently, several anti-collision algorithms have been proposed in the literature. Dynamic Framed Slotted ALOHA (DFSA) is one of the most popular of these algorithms. DFSA dynamically modifies the frame size based on the number of tags. Since the real number of tags is unknown, it needs to be estimated. Therefore, an accurate tag estimation method has an important role in increasing the efficiency and overall performance of the tag identification process. In this paper, we propose a novel estimation technique for DFSA anti-collision algorithms that applies birthday paradox theory to estimate the number of tags accurately. The analytical discussion and simulation results prove that the proposed method increases the accuracy of tag estimation and, consequently, outperforms previous schemes. PMID:24752285

Solving inversion problems with neural networks

NASA Technical Reports Server (NTRS)

Kamgar-Parsi, Behzad; Gualtieri, J. A.

1990-01-01

A class of inverse problems in remote sensing can be characterized by Q = F(x), where F is a nonlinear and noninvertible (or hard to invert) operator, and the objective is to infer the unknowns, x, from the observed quantities, Q. Since the number of observations is usually greater than the number of unknowns, these problems are formulated as optimization problems, which can be solved by a variety of techniques. The feasibility of neural networks for solving such problems is presently investigated. As an example, the problem of finding the atmospheric ozone profile from measured ultraviolet radiances is studied.

Assessing Temporal Behavior in LIDAR Point Clouds of Urban Environments

NASA Astrophysics Data System (ADS)

Schachtschneider, J.; Schlichting, A.; Brenner, C.

2017-05-01

Self-driving cars and robots that run autonomously over long periods of time need high-precision and up-to-date models of the changing environment. The main challenge for creating long term maps of dynamic environments is to identify changes and adapt the map continuously. Changes can occur abruptly, gradually, or even periodically. In this work, we investigate how dense mapping data of several epochs can be used to identify the temporal behavior of the environment. This approach anticipates possible future scenarios where a large fleet of vehicles is equipped with sensors which continuously capture the environment. This data is then being sent to a cloud based infrastructure, which aligns all datasets geometrically and subsequently runs scene analysis on it, among these being the analysis for temporal changes of the environment. Our experiments are based on a LiDAR mobile mapping dataset which consists of 150 scan strips (a total of about 1 billion points), which were obtained in multiple epochs. Parts of the scene are covered by up to 28 scan strips. The time difference between the first and last epoch is about one year. In order to process the data, the scan strips are aligned using an overall bundle adjustment, which estimates the surface (about one billion surface element unknowns) as well as 270,000 unknowns for the adjustment of the exterior orientation parameters. After this, the surface misalignment is usually below one centimeter. In the next step, we perform a segmentation of the point clouds using a region growing algorithm. The segmented objects and the aligned data are then used to compute an occupancy grid which is filled by tracing each individual LiDAR ray from the scan head to every point of a segment. As a result, we can assess the behavior of each segment in the scene and remove voxels from temporal objects from the global occupancy grid.

Simplification of Visual Rendering in Simulated Prosthetic Vision Facilitates Navigation.

PubMed

Vergnieux, Victor; Macé, Marc J-M; Jouffrais, Christophe

2017-09-01

Visual neuroprostheses are still limited and simulated prosthetic vision (SPV) is used to evaluate potential and forthcoming functionality of these implants. SPV has been used to evaluate the minimum requirement on visual neuroprosthetic characteristics to restore various functions such as reading, objects and face recognition, object grasping, etc. Some of these studies focused on obstacle avoidance but only a few investigated orientation or navigation abilities with prosthetic vision. The resolution of current arrays of electrodes is not sufficient to allow navigation tasks without additional processing of the visual input. In this study, we simulated a low resolution array (15 × 18 electrodes, similar to a forthcoming generation of arrays) and evaluated the navigation abilities restored when visual information was processed with various computer vision algorithms to enhance the visual rendering. Three main visual rendering strategies were compared to a control rendering in a wayfinding task within an unknown environment. The control rendering corresponded to a resizing of the original image onto the electrode array size, according to the average brightness of the pixels. In the first rendering strategy, vision distance was limited to 3, 6, or 9 m, respectively. In the second strategy, the rendering was not based on the brightness of the image pixels, but on the distance between the user and the elements in the field of view. In the last rendering strategy, only the edges of the environments were displayed, similar to a wireframe rendering. All the tested renderings, except the 3 m limitation of the viewing distance, improved navigation performance and decreased cognitive load. Interestingly, the distance-based and wireframe renderings also improved the cognitive mapping of the unknown environment. These results show that low resolution implants are usable for wayfinding if specific computer vision algorithms are used to select and display appropriate information regarding the environment. © 2017 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Off-Policy Actor-Critic Structure for Optimal Control of Unknown Systems With Disturbances.

PubMed

Song, Ruizhuo; Lewis, Frank L; Wei, Qinglai; Zhang, Huaguang

2016-05-01

An optimal control method is developed for unknown continuous-time systems with unknown disturbances in this paper. The integral reinforcement learning (IRL) algorithm is presented to obtain the iterative control. Off-policy learning is used to allow the dynamics to be completely unknown. Neural networks are used to construct critic and action networks. It is shown that if there are unknown disturbances, off-policy IRL may not converge or may be biased. For reducing the influence of unknown disturbances, a disturbances compensation controller is added. It is proven that the weight errors are uniformly ultimately bounded based on Lyapunov techniques. Convergence of the Hamiltonian function is also proven. The simulation study demonstrates the effectiveness of the proposed optimal control method for unknown systems with disturbances.

The effects of familiarity and emotional expression on face processing examined by ERPs in patients with schizophrenia.

PubMed

Caharel, Stéphanie; Bernard, Christian; Thibaut, Florence; Haouzir, Sadec; Di Maggio-Clozel, Carole; Allio, Gabrielle; Fouldrin, Gaël; Petit, Michel; Lalonde, Robert; Rebaï, Mohamed

2007-09-01

The main objective of the study was to determine whether patients with schizophrenia are deficient relative to controls in the processing of faces at different levels of familiarity and types of emotion and the stage where such differences may occur. ERPs based on 18 patients with schizophrenia and 18 controls were compared in a face identification task at three levels of familiarity (unknown, familiar, subject's own) and for three types of emotion (disgust, smiling, neutral). The schizophrenic group was less accurate than controls in the face processing, especially for unknown faces and those expressing negative emotions such as disgust. P1 and N170 amplitudes were lower and P1, N170, P250 amplitudes were of slower onset in patients with schizophrenia. N170 and P250 amplitudes were modulated by familiarity and face expression in a different manner in patients than controls. Schizophrenia is associated with a genelarized defect of face processing, both in terms of familiarity and emotional expression, attributable to deficient processing at sensory (P1) and perceptual (N170) stages. These patients appear to have difficulty in encoding the structure of a face and thereby do not evaluate correctly familiarity and emotion.

Camera pose estimation for augmented reality in a small indoor dynamic scene

NASA Astrophysics Data System (ADS)

Frikha, Rawia; Ejbali, Ridha; Zaied, Mourad

2017-09-01

Camera pose estimation remains a challenging task for augmented reality (AR) applications. Simultaneous localization and mapping (SLAM)-based methods are able to estimate the six degrees of freedom camera motion while constructing a map of an unknown environment. However, these methods do not provide any reference for where to insert virtual objects since they do not have any information about scene structure and may fail in cases of occlusion of three-dimensional (3-D) map points or dynamic objects. This paper presents a real-time monocular piece wise planar SLAM method using the planar scene assumption. Using planar structures in the mapping process allows rendering virtual objects in a meaningful way on the one hand and improving the precision of the camera pose and the quality of 3-D reconstruction of the environment by adding constraints on 3-D points and poses in the optimization process on the other hand. We proposed to benefit from the 3-D planes rigidity motion in the tracking process to enhance the system robustness in the case of dynamic scenes. Experimental results show that using a constrained planar scene improves our system accuracy and robustness compared with the classical SLAM systems.

Probabilistic multi-person localisation and tracking in image sequences

NASA Astrophysics Data System (ADS)

Klinger, T.; Rottensteiner, F.; Heipke, C.

2017-05-01

The localisation and tracking of persons in image sequences in commonly guided by recursive filters. Especially in a multi-object tracking environment, where mutual occlusions are inherent, the predictive model is prone to drift away from the actual target position when not taking context into account. Further, if the image-based observations are imprecise, the trajectory is prone to be updated towards a wrong position. In this work we address both these problems by using a new predictive model on the basis of Gaussian Process Regression, and by using generic object detection, as well as instance-specific classification, for refined localisation. The predictive model takes into account the motion of every tracked pedestrian in the scene and the prediction is executed with respect to the velocities of neighbouring persons. In contrast to existing methods our approach uses a Dynamic Bayesian Network in which the state vector of a recursive Bayes filter, as well as the location of the tracked object in the image, are modelled as unknowns. This allows the detection to be corrected before it is incorporated into the recursive filter. Our method is evaluated on a publicly available benchmark dataset and outperforms related methods in terms of geometric precision and tracking accuracy.

Inverse modeling with RZWQM2 to predict water quality

USDA-ARS?s Scientific Manuscript database

Agricultural systems models such as RZWQM2 are complex and have numerous parameters that are unknown and difficult to estimate. Inverse modeling provides an objective statistical basis for calibration that involves simultaneous adjustment of model parameters and yields parameter confidence intervals...

Diesel Exhaust Exposure and Nasal Response to Attenuated Influenza in Normal and Allergic Volunteers

EPA Science Inventory

Rationale: Diesel exhaust enhances allergic inflammation, and pollutants are associated with heightened susceptibility to viral respiratory infections. The effects of combined diesel and virus exposure in humans are unknown. Objective: Test whether acute exposure to diesel modif...

Vascular and Cardiac Impairments in Rats Inhaling Ozone and Diesel Exhaust Particles

EPA Science Inventory

Background -Mechanisms of cardiovascular injuries from exposure to gas and particulate air pollutants are unknown. Objective -We hypothesized that episodic exposure of rats to ozone or diesel exhaust particles (DEP) will cause differential cardiovascular impairments, which will b...

Campylobacter prevalence in retail chicken liver

USDA-ARS?s Scientific Manuscript database

Foodborne campylobacteriosis has been linked to undercooked chicken liver. It is unknown how commonly chicken livers are contaminated with Campylobacter. The objective of this study was to determine the prevalence of Campylobacter on chicken livers available at retail. For each of five weeks, t...

Contamination assessment for OSSA space station IOC payloads

NASA Technical Reports Server (NTRS)

Wu, S. T.

1987-01-01

An assessment is made of NASA/OSSA space station IOC payloads. The report has two main objectives, i.e., to provide realistic contamination requirements for space station attached payloads, serviced payloads and platforms, and to determine unknowns or major impacts requiring further assessment.

Temporal gravity field modeling based on least square collocation with short-arc approach

NASA Astrophysics Data System (ADS)

ran, jiangjun; Zhong, Min; Xu, Houze; Liu, Chengshu; Tangdamrongsub, Natthachet

2014-05-01

After the launch of the Gravity Recovery And Climate Experiment (GRACE) in 2002, several research centers have attempted to produce the finest gravity model based on different approaches. In this study, we present an alternative approach to derive the Earth's gravity field, and two main objectives are discussed. Firstly, we seek the optimal method to estimate the accelerometer parameters, and secondly, we intend to recover the monthly gravity model based on least square collocation method. The method has been paid less attention compared to the least square adjustment method because of the massive computational resource's requirement. The positions of twin satellites are treated as pseudo-observations and unknown parameters at the same time. The variance covariance matrices of the pseudo-observations and the unknown parameters are valuable information to improve the accuracy of the estimated gravity solutions. Our analyses showed that introducing a drift parameter as an additional accelerometer parameter, compared to using only a bias parameter, leads to a significant improvement of our estimated monthly gravity field. The gravity errors outside the continents are significantly reduced based on the selected set of the accelerometer parameters. We introduced the improved gravity model namely the second version of Institute of Geodesy and Geophysics, Chinese Academy of Sciences (IGG-CAS 02). The accuracy of IGG-CAS 02 model is comparable to the gravity solutions computed from the Geoforschungszentrum (GFZ), the Center for Space Research (CSR) and the NASA Jet Propulsion Laboratory (JPL). In term of the equivalent water height, the correlation coefficients over the study regions (the Yangtze River valley, the Sahara desert, and the Amazon) among four gravity models are greater than 0.80.

Exploring Ackermann and LQR stability control of stochastic state-space model of hexacopter equipped with robotic arm

NASA Astrophysics Data System (ADS)

Ibrahim, I. N.; Akkad, M. A. Al; Abramov, I. V.

2018-05-01

This paper discusses the control of Unmanned Aerial Vehicles (UAVs) for active interaction and manipulation of objects. The manipulator motion with an unknown payload was analysed concerning force and moment disturbances, which influence the mass distribution, and the centre of gravity (CG). Therefore, a general dynamics mathematical model of a hexacopter was formulated where a stochastic state-space model was extracted in order to build anti-disturbance controllers. Based on the compound pendulum method, the disturbances model that simulates the robotic arm with a payload was inserted into the stochastic model. This study investigates two types of controllers in order to study the stability of a hexacopter. A controller based on Ackermann’s method and the other - on the linear quadratic regulator (LQR) approach - were presented. The latter constitutes a challenge for UAV control performance especially with the presence of uncertainties and disturbances.

Aspect: A Formal Specification Language for Detecting Bugs

DTIC Science & Technology

1992-06-01

the Aspect state from Chapter 6 and, below it, the definition of the approximating state used by the checker. The additional component Multilocs marks...stages. First, each collection object in Multilocs is expanded into a set of objects whose dependency and value sets are subsets of those of the... Multilocs x Prelocs Env = Var ý7 PLoc x PSource Store = Loc x Aspect F-k Val x PSource Vat = Unknown + PLoc Aspect = PlainAspect + Pointer + Collection

Allocating monitoring effort in the face of unknown unknowns

USGS Publications Warehouse

Wintle, B.A.; Runge, M.C.; Bekessy, S.A.

2010-01-01

There is a growing view that to make efficient use of resources, ecological monitoring should be hypothesis-driven and targeted to address specific management questions. 'Targeted' monitoring has been contrasted with other approaches in which a range of quantities are monitored in case they exhibit an alarming trend or provide ad hoc ecological insights. The second form of monitoring, described as surveillance, has been criticized because it does not usually aim to discern between competing hypotheses, and its benefits are harder to identify a priori. The alternative view is that the existence of surveillance data may enable rapid corroboration of emerging hypotheses or help to detect important 'unknown unknowns' that, if undetected, could lead to catastrophic outcomes or missed opportunities. We derive a model to evaluate and compare the efficiency of investments in surveillance and targeted monitoring. We find that a decision to invest in surveillance monitoring may be defensible if: (1) the surveillance design is more likely to discover or corroborate previously unknown phenomena than a targeted design and (2) the expected benefits (or avoided costs) arising from discovery are substantially higher than those arising from a well-planned targeted design. Our examination highlights the importance of being explicit about the objectives, costs and expected benefits of monitoring in a decision analytic framework. ?? 2010 Blackwell Publishing Ltd/CNRS.

All in the name of flavour, fragrance & freshness: Commonly used smokeless tobacco preparations in & around a tertiary hospital in India

PubMed Central

Dwivedi, Shridhar; Aggarwal, Amitesh; Dev, Munish

2012-01-01

Background & objectives: There is a general misconception that smokeless tobacco particularly sweetened and flavoured paan masala and gutkas are safe to use. The present study was undertaken with the objective of highlighting the deceptive and aggressive marketing techniques adopted by the manufacturers of smokeless tobacco preparations exploiting cultural, social and religious values. Another object was to highlight the lack of transparency in terms of content, weight, quality control and warning. Methods: All empty pouches of the used paan masalas, gutka, khaini or surti in and around a tertiary care hospital at east Delhi were collected. Their constituents were studied as per written declaration by the manufacturers on each packet. Information on net weight, cost, presence and type of warning, and quality assurance on each brand provided on side of the packets was noted. Results: A total of 1136 pouches of 33 brands/varieties were collected. Most of the gutka preparations contained tobacco, betel nut, unknown flavouring agents, undeclared spices and heavy metals. Warning regarding the harmful effect of tobacco was written in 90.9 per cent of brands with 81.8 per cent in English language only in minute font. Contents of the products were mentioned in 84.8 per cent of brands and only 27.3 per cent of those mentioned the net weight of the ingredients. Interpretation & conclusions: Seemingly ‘innocuous’ tobacco preparations in the form of paan masalas, gutka, khaini, surti or mouth fresheners contain various harmful substance like tobacco, betel nut, sugar coated fennel, saccharine, heavy metals like silver, unknown flavouring agents and undeclared spices in unknown quantities. Lack of transparency in terms of content, weight, quality control and warning is duping unsuspecting consumers. PMID:23287132

Photogrammetry Tool for Forensic Analysis

NASA Technical Reports Server (NTRS)

Lane, John

2012-01-01

A system allows crime scene and accident scene investigators the ability to acquire visual scene data using cameras for processing at a later time. This system uses a COTS digital camera, a photogrammetry calibration cube, and 3D photogrammetry processing software. In a previous instrument developed by NASA, the laser scaling device made use of parallel laser beams to provide a photogrammetry solution in 2D. This device and associated software work well under certain conditions. In order to make use of a full 3D photogrammetry system, a different approach was needed. When using multiple cubes, whose locations relative to each other are unknown, a procedure that would merge the data from each cube would be as follows: 1. One marks a reference point on cube 1, then marks points on cube 2 as unknowns. This locates cube 2 in cube 1 s coordinate system. 2. One marks reference points on cube 2, then marks points on cube 1 as unknowns. This locates cube 1 in cube 2 s coordinate system. 3. This procedure is continued for all combinations of cubes. 4. The coordinate of all of the found coordinate systems is then merged into a single global coordinate system. In order to achieve maximum accuracy, measurements are done in one of two ways, depending on scale: when measuring the size of objects, the coordinate system corresponding to the nearest cube is used, or when measuring the location of objects relative to a global coordinate system, a merged coordinate system is used. Presently, traffic accident analysis is time-consuming and not very accurate. Using cubes with differential GPS would give absolute positions of cubes in the accident area, so that individual cubes would provide local photogrammetry calibration to objects near a cube.

Blind Bayesian restoration of adaptive optics telescope images using generalized Gaussian Markov random field models

NASA Astrophysics Data System (ADS)

Jeffs, Brian D.; Christou, Julian C.

1998-09-01

This paper addresses post processing for resolution enhancement of sequences of short exposure adaptive optics (AO) images of space objects. The unknown residual blur is removed using Bayesian maximum a posteriori blind image restoration techniques. In the problem formulation, both the true image and the unknown blur psf's are represented by the flexible generalized Gaussian Markov random field (GGMRF) model. The GGMRF probability density function provides a natural mechanism for expressing available prior information about the image and blur. Incorporating such prior knowledge in the deconvolution optimization is crucial for the success of blind restoration algorithms. For example, space objects often contain sharp edge boundaries and geometric structures, while the residual blur psf in the corresponding partially corrected AO image is spectrally band limited, and exhibits while the residual blur psf in the corresponding partially corrected AO image is spectrally band limited, and exhibits smoothed, random , texture-like features on a peaked central core. By properly choosing parameters, GGMRF models can accurately represent both the blur psf and the object, and serve to regularize the deconvolution problem. These two GGMRF models also serve as discriminator functions to separate blur and object in the solution. Algorithm performance is demonstrated with examples from synthetic AO images. Results indicate significant resolution enhancement when applied to partially corrected AO images. An efficient computational algorithm is described.

Learning Rates and Known-to-Unknown Flash-Card Ratios: Comparing Effectiveness While Holding Instructional Time Constant

ERIC Educational Resources Information Center

Forbes, Bethany E.; Skinner, Christopher H.; Black, Michelle P.; Yaw, Jared; Booher, Joshua; Delisle, Jean

2013-01-01

Using alternating treatments designs, we compared learning rates across 2 computer-based flash-card interventions (3?min each): a traditional drill intervention with 15 unknown words and an interspersal intervention with 12 known words and 3 unknown words. Each student acquired more words under the traditional drill intervention. Discussion…

Lessons From Recruitment to an Internet-Based Survey for Degenerative Cervical Myelopathy: Comparison of Free and Fee-Based Methods

PubMed Central

2018-01-01

Background Degenerative Cervical Myelopathy (DCM) is a syndrome of subacute cervical spinal cord compression due to spinal degeneration. Although DCM is thought to be common, many fundamental questions such as the natural history and epidemiology of DCM remain unknown. In order to answer these, access to a large cohort of patients with DCM is required. With its unrivalled and efficient reach, the Internet has become an attractive tool for medical research and may overcome these limitations in DCM. The most effective recruitment strategy, however, is unknown. Objective To compare the efficacy of fee-based advertisement with alternative free recruitment strategies to a DCM Internet health survey. Methods An Internet health survey (SurveyMonkey) accessed by a new DCM Internet platform (myelopathy.org) was created. Using multiple survey collectors and the website’s Google Analytics, the efficacy of fee-based recruitment strategies (Google AdWords) and free alternatives (including Facebook, Twitter, and myelopathy.org) were compared. Results Overall, 760 surveys (513 [68%] fully completed) were accessed, 305 (40%) from fee-based strategies and 455 (60%) from free alternatives. Accounting for researcher time, fee-based strategies were more expensive ($7.8 per response compared to $3.8 per response for free alternatives) and identified a less motivated audience (Click-Through-Rate of 5% compared to 57% using free alternatives) but were more time efficient for the researcher (2 minutes per response compared to 16 minutes per response for free methods). Facebook was the most effective free strategy, providing 239 (31%) responses, where a single message to 4 existing communities yielded 133 (18%) responses within 7 days. Conclusions The Internet can efficiently reach large numbers of patients. Free and fee-based recruitment strategies both have merits. Facebook communities are a rich resource for Internet researchers. PMID:29402760

Visual discrimination in an orangutan (Pongo pygmaeus): measuring visual preference.

PubMed

Hanazuka, Yuki; Kurotori, Hidetoshi; Shimizu, Mika; Midorikawa, Akira

2012-04-01

Although previous studies have confirmed that trained orangutans visually discriminate between mammals and artificial objects, whether orangutans without operant conditioning can discriminate remains unknown. The visual discrimination ability in an orangutan (Pongo pygmaeus) with no experience in operant learning was examined using measures of visual preference. Sixteen color photographs of inanimate objects and of mammals with four legs were randomly presented to an orangutan. The results showed that the mean looking time at photographs of mammals with four legs was longer than that for inanimate objects, suggesting that the orangutan discriminated mammals with four legs from inanimate objects. The results implied that orangutans who have not experienced operant conditioning may possess the ability to discriminate visually.

A learning-based semi-autonomous controller for robotic exploration of unknown disaster scenes while searching for victims.

PubMed

Doroodgar, Barzin; Liu, Yugang; Nejat, Goldie

2014-12-01

Semi-autonomous control schemes can address the limitations of both teleoperation and fully autonomous robotic control of rescue robots in disaster environments by allowing a human operator to cooperate and share such tasks with a rescue robot as navigation, exploration, and victim identification. In this paper, we present a unique hierarchical reinforcement learning-based semi-autonomous control architecture for rescue robots operating in cluttered and unknown urban search and rescue (USAR) environments. The aim of the controller is to enable a rescue robot to continuously learn from its own experiences in an environment in order to improve its overall performance in exploration of unknown disaster scenes. A direction-based exploration technique is integrated in the controller to expand the search area of the robot via the classification of regions and the rubble piles within these regions. Both simulations and physical experiments in USAR-like environments verify the robustness of the proposed HRL-based semi-autonomous controller to unknown cluttered scenes with different sizes and varying types of configurations.

The microbiology "unknown" misadventure.

PubMed

Boyer, B; DeBenedictis, K J; Master, R; Jones, R S

1998-06-01

A 19-year-old nursing student was hospitalized after several days of nausea, vomiting, diarrhea, and fevers. Salmonella paratyphi A was isolated from multiple blood cultures. Because this is an unlikely isolate in the United States, an investigation ensued. Two and a half weeks earlier, the student had been working on a microbiology laboratory exercise "unknown." Both the "unknown" organism and the patient's blood culture isolates were identified as S. paratyphi A, with the same biochemical reactions and antimicrobial susceptibility results. The patient's condition improved with antibiotic therapy, and she was discharged after 9 days in the hospital. Conclusions related to our investigation are as follows: (1) relatively virulent organisms were unnecessary to fulfill the laboratory objectives, (2) pipetting by mouth must never be allowed, (3) proper labeling of specimens is imperative, (4) instructors should have knowledge of laboratory safety regulations, and (5) it is the obligation of laboratory directors and administrators to provide a safe academic environment.

Performance in Object-Choice Aesop’s Fable Tasks Are Influenced by Object Biases in New Caledonian Crows but not in Human Children

PubMed Central

Taylor, Alex H.; Cheke, Lucy G.; Gray, Russell D.; Loissel, Elsa; Clayton, Nicola S.

2016-01-01

The ability to reason about causality underlies key aspects of human cognition, but the extent to which non-humans understand causality is still largely unknown. The Aesop’s Fable paradigm, where objects are inserted into water-filled tubes to obtain out-of-reach rewards, has been used to test casual reasoning in birds and children. However, success on these tasks may be influenced by other factors, specifically, object preferences present prior to testing or arising during pre-test stone-dropping training. Here, we assessed this ‘object-bias’ hypothesis by giving New Caledonian crows and 5–10 year old children two object-choice Aesop’s Fable experiments: sinking vs. floating objects, and solid vs. hollow objects. Before each test, we assessed subjects’ object preferences and/or trained them to prefer the alternative object. Both crows and children showed pre-test object preferences, suggesting that birds in previous Aesop’s Fable studies may also have had initial preferences for objects that proved to be functional on test. After training to prefer the non-functional object, crows, but not children, performed more poorly on these two object-choice Aesop’s Fable tasks than subjects in previous studies. Crows dropped the non-functional objects into the tube on their first trials, indicating that, unlike many children, they do not appear to have an a priori understanding of water displacement. Alternatively, issues with inhibition could explain their performance. The crows did, however, learn to solve the tasks over time. We tested crows further to determine whether their eventual success was based on learning about the functional properties of the objects, or associating dropping the functional object with reward. Crows inserted significantly more rewarded, non-functional objects than non-rewarded, functional objects. These findings suggest that the ability of New Caledonian crows to produce performances rivaling those of young children on object-choice Aesop’s Fable tasks is partly due to pre-existing object preferences. PMID:27936242

Supernovas y Cosmología

NASA Astrophysics Data System (ADS)

Folatelli, G.

Supernovae are very relevant astrophysical objects because they indicate the violent end of certain stars and because they alter the interstellar medium. But most importantly, they have become an extremely useful tool for measuring cosmological distances. Based on highly precise distances to type Ia supernovae it was possible to find out that the expansion of the universe is currently accelerated. This led to introducing the concept of ``dark energy'' as a dominant and yet unknown component of the cosmos. In this article we will describe the method of distance measurements that leads to the determination of cosmological parameters. We will briefly review the current status of the field with emphasis on the importance of improving our knowledge about the physical nature of supernovae. FULL TEXT IN SPANISH

New control concepts for uncertain water resources systems: 1. Theory

NASA Astrophysics Data System (ADS)

Georgakakos, Aris P.; Yao, Huaming

1993-06-01

A major complicating factor in water resources systems management is handling unknown inputs. Stochastic optimization provides a sound mathematical framework but requires that enough data exist to develop statistical input representations. In cases where data records are insufficient (e.g., extreme events) or atypical of future input realizations, stochastic methods are inadequate. This article presents a control approach where input variables are only expected to belong in certain sets. The objective is to determine sets of admissible control actions guaranteeing that the system will remain within desirable bounds. The solution is based on dynamic programming and derived for the case where all sets are convex polyhedra. A companion paper (Yao and Georgakakos, this issue) addresses specific applications and problems in relation to reservoir system management.

Material Characterization for the Analysis of Skin/Stiffener Separation

NASA Technical Reports Server (NTRS)

Davila, Carlos G.; Leone, Frank A.; Song, Kyongchan; Ratcliffe, James G.; Rose, Cheryl A.

2017-01-01

Test results show that separation failure in co-cured skin/stiffener interfaces is characterized by dense networks of interacting cracks and crack path migrations that are not present in standard characterization tests for delamination. These crack networks result in measurable large-scale and sub-ply-scale R curve toughening mechanisms, such as fiber bridging, crack migration, and crack delving. Consequently, a number of unknown issues exist regarding the level of analysis detail that is required for sufficient predictive fidelity. The objective of the present paper is to examine some of the difficulties associated with modeling separation failure in stiffened composite structures. A procedure to characterize the interfacial material properties is proposed and the use of simplified models based on empirical interface properties is evaluated.

CHEMICAL CONTAMINATION AND TOXICITY ASSOCIATED WITH A COASTAL GOLF COURSE COMPLEX

EPA Science Inventory

The increasing density of golf courses represents a potential source of contamination to nearby coastal areas, the chemical and biological magnitude of which is almost unknown. The objective of this study was to compare the concentrations of contaminants and toxicities of sedime...

SEDIMENT CHEMICAL CONTAMINATION AND TOXICITY ASSOCIATED WITH A COASTAL GOLF COURSE COMPLEX.

EPA Science Inventory

The increasing density of golf courses represents a potential source of sediment contamination to nearby coastal areas, the chemical and biological magnitude of which is almost unknown. The objective of this study was to determine the concentrations of contaminants and toxicities...

Brain Magnetic Resonance Spectroscopy in Tourette's Disorder

ERIC Educational Resources Information Center

DeVito, Timothy J.; Drost, Dick J.; Pavlosky, William; Neufeld, Richard W.J.; Rajakumar, Nagalingam; McKinlay, B. Duncan; Williamson, Peter C.; Nicolson, Rob

2005-01-01

Objective: Although abnormalities of neural circuits involving the cortex, striatum, and thalamus are hypothesized to underlie Tourette's disorder, the neuronal abnormalities within components of these circuits are unknown. The purpose of this study was to examine the cellular neurochemistry within these circuits in Tourette's disorder using…

The contribution of local features to familiarity judgments in music.

PubMed

Bigand, Emmanuel; Gérard, Yannick; Molin, Paul

2009-07-01

The contributions of local and global features to object identification depend upon the context. For example, while local features play an essential role in identification of words and objects, the global features are more influential in face recognition. In order to evaluate the respective strengths of local and global features for face recognition, researchers usually ask participants to recognize human faces (famous or learned) in normal and scrambled pictures. In this paper, we address a similar issue in music. We present the results of an experiment in which musically untrained participants were asked to differentiate famous from unknown musical excerpts that were presented in normal or scrambled ways. Manipulating the size of the temporal window on which the scrambling procedure was applied allowed us to evaluate the minimal length of time necessary for participants to make a familiarity judgment. Quite surprisingly, the minimum duration for differentiation of famous from unknown pieces is extremely short. This finding highlights the contribution of very local features to music memory.

Integration of Component Knowledge in Penalized-Likelihood Reconstruction with Morphological and Spectral Uncertainties.

PubMed

Stayman, J Webster; Tilley, Steven; Siewerdsen, Jeffrey H

2014-01-01

Previous investigations [1-3] have demonstrated that integrating specific knowledge of the structure and composition of components like surgical implants, devices, and tools into a model-based reconstruction framework can improve image quality and allow for potential exposure reductions in CT. Using device knowledge in practice is complicated by uncertainties in the exact shape of components and their particular material composition. Such unknowns in the morphology and attenuation properties lead to errors in the forward model that limit the utility of component integration. In this work, a methodology is presented to accommodate both uncertainties in shape as well as unknown energy-dependent attenuation properties of the surgical devices. This work leverages the so-called known-component reconstruction (KCR) framework [1] with a generalized deformable registration operator and modifications to accommodate a spectral transfer function in the component model. Moreover, since this framework decomposes the object into separate background anatomy and "known" component factors, a mixed fidelity forward model can be adopted so that measurements associated with projections through the surgical devices can be modeled with much greater accuracy. A deformable KCR (dKCR) approach using the mixed fidelity model is introduced and applied to a flexible wire component with unknown structure and composition. Image quality advantages of dKCR over traditional reconstruction methods are illustrated in cone-beam CT (CBCT) data acquired on a testbench emulating a 3D-guided needle biopsy procedure - i.e., a deformable component (needle) with strong energy-dependent attenuation characteristics (steel) within a complex soft-tissue background.

Concurrent hyperthermia estimation schemes based on extended Kalman filtering and reduced-order modelling.

PubMed

Potocki, J K; Tharp, H S

1993-01-01

The success of treating cancerous tissue with heat depends on the temperature elevation, the amount of tissue elevated to that temperature, and the length of time that the tissue temperature is elevated. In clinical situations the temperature of most of the treated tissue volume is unknown, because only a small number of temperature sensors can be inserted into the tissue. A state space model based on a finite difference approximation of the bioheat transfer equation (BHTE) is developed for identification purposes. A full-order extended Kalman filter (EKF) is designed to estimate both the unknown blood perfusion parameters and the temperature at unmeasured locations. Two reduced-order estimators are designed as computationally less intensive alternatives to the full-order EKF. Simulation results show that the success of the estimation scheme depends strongly on the number and location of the temperature sensors. Superior results occur when a temperature sensor exists in each unknown blood perfusion zone, and the number of sensors is at least as large as the number of unknown perfusion zones. Unacceptable results occur when there are more unknown perfusion parameters than temperature sensors, or when the sensors are placed in locations that do not sample the unknown perfusion information.

A real-world size organization of object responses in occipito-temporal cortex

PubMed Central

Konkle, Talia; Oliva, Aude

2012-01-01

SUMMARY While there are selective regions of occipito-temporal cortex that respond to faces, letters, and bodies, the large-scale neural organization of most object categories remains unknown. Here we find that object representations can be differentiated along the ventral temporal cortex by their real-world size. In a functional neuroimaging experiment, observers were shown pictures of big and small real-world objects (e.g. table, bathtub; paperclip, cup), presented at the same retinal size. We observed a consistent medial-to-lateral organization of big and small object preferences in the ventral temporal cortex, mirrored along the lateral surface. Regions in the lateral-occipital, infero-temporal, and parahippocampal cortices showed strong peaks of differential real-world size selectivity, and maintained these preferences over changes in retinal size and in mental imagery. These data demonstrate that the real-world size of objects can provide insight into the spatial topography of object representation. PMID:22726840

Conjunctive Coding of Complex Object Features

PubMed Central

Erez, Jonathan; Cusack, Rhodri; Kendall, William; Barense, Morgan D.

2016-01-01

Critical to perceiving an object is the ability to bind its constituent features into a cohesive representation, yet the manner by which the visual system integrates object features to yield a unified percept remains unknown. Here, we present a novel application of multivoxel pattern analysis of neuroimaging data that allows a direct investigation of whether neural representations integrate object features into a whole that is different from the sum of its parts. We found that patterns of activity throughout the ventral visual stream (VVS), extending anteriorly into the perirhinal cortex (PRC), discriminated between the same features combined into different objects. Despite this sensitivity to the unique conjunctions of features comprising objects, activity in regions of the VVS, again extending into the PRC, was invariant to the viewpoints from which the conjunctions were presented. These results suggest that the manner in which our visual system processes complex objects depends on the explicit coding of the conjunctions of features comprising them. PMID:25921583

Multimodal Encoding of Goal-Directed Actions in Monkey Ventral Premotor Grasping Neurons.

PubMed

Bruni, Stefania; Giorgetti, Valentina; Fogassi, Leonardo; Bonini, Luca

2017-01-01

Visuo-motor neurons of the ventral premotor area F5 encode "pragmatic" representations of object in terms of the potential motor acts (e.g., precision grip) afforded by it. Likewise, objects with identical pragmatic features (e.g., small spheres) but different behavioral value (e.g., edible or inedible) convey different "semantic" information and thus afford different goal-directed behaviors (e.g., grasp-to-eat or grasp-to-place). However, whether F5 neurons can extract distinct behavioral affordances from objects with similar pragmatic features is unknown. We recorded 134 F5 visuo-motor neurons in 2 macaques during a contextually cued go/no-go task in which the monkey grasped, or refrained from grasping, a previously presented edible or inedible target to eat it or placing it, respectively. Sixty-nine visuo-motor neurons showed motor selectivity for the target (35 food and 34 object), and about half of them (N = 35) exhibited congruent visual preference. Interestingly, when the monkey grasped in complete darkness and could identify the target only based on haptic feedback, visuo-motor neurons lost their precontact selectivity, but most of them (80%) showed it again 60 ms after hand-target contact. These findings suggest that F5 neurons possess a multimodal access to semantic information on objects, which are transformed into motor representations of the potential goal-directed actions afforded by them. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Extraction of Extended Small-Scale Objects in Digital Images

NASA Astrophysics Data System (ADS)

Volkov, V. Y.

2015-05-01

Detection and localization problem of extended small-scale objects with different shapes appears in radio observation systems which use SAR, infra-red, lidar and television camera. Intensive non-stationary background is the main difficulty for processing. Other challenge is low quality of images, blobs, blurred boundaries; in addition SAR images suffer from a serious intrinsic speckle noise. Statistics of background is not normal, it has evident skewness and heavy tails in probability density, so it is hard to identify it. The problem of extraction small-scale objects is solved here on the basis of directional filtering, adaptive thresholding and morthological analysis. New kind of masks is used which are open-ended at one side so it is possible to extract ends of line segments with unknown length. An advanced method of dynamical adaptive threshold setting is investigated which is based on isolated fragments extraction after thresholding. Hierarchy of isolated fragments on binary image is proposed for the analysis of segmentation results. It includes small-scale objects with different shape, size and orientation. The method uses extraction of isolated fragments in binary image and counting points in these fragments. Number of points in extracted fragments is normalized to the total number of points for given threshold and is used as effectiveness of extraction for these fragments. New method for adaptive threshold setting and control maximises effectiveness of extraction. It has optimality properties for objects extraction in normal noise field and shows effective results for real SAR images.

Renovation of the fixing and loading factors of the beam by the spectral data of free flexural vibrations

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

Akhymbek, Meiram Erkanatuly; Yessirkegenov, Nurgissa Amankeldiuly; Sadybekov, Makhmud Abdysametovich

2015-09-18

In the current paper, the problem of bending vibrations of a beam in which the binding on the right end is unknown and not available for visual inspection is studied. The main objective is to study an inverse problem: find additional unknown boundary conditions by additional spectral data, i.e., the conditions of fixing the right end of the rod. In this work, unlike many other works, as such additional conditions we choose the first natural frequencies (eigenvalues) of two new problems corresponding to the problem of bending vibrations of a beam with loads of different weights at the central point.

Reactivation of Reward-Related Patterns from Single Past Episodes Supports Memory-Based Decision Making.

PubMed

Wimmer, G Elliott; Büchel, Christian

2016-03-09

Rewarding experiences exert a strong influence on later decision making. While decades of neuroscience research have shown how reinforcement gradually shapes preferences, decisions are often influenced by single past experiences. Surprisingly, relatively little is known about the influence of single learning episodes. Although recent work has proposed a role for episodes in decision making, it is largely unknown whether and how episodic experiences contribute to value-based decision making and how the values of single episodes are represented in the brain. In multiple behavioral experiments and an fMRI experiment, we tested whether and how rewarding episodes could support later decision making. Participants experienced episodes of high reward or low reward in conjunction with incidental, trial-unique neutral pictures. In a surprise test phase, we found that participants could indeed remember the associated level of reward, as evidenced by accurate source memory for value and preferences to re-engage with rewarded objects. Further, in a separate experiment, we found that high-reward objects shown as primes before a gambling task increased financial risk taking. Neurally, re-exposure to objects in the test phase led to significant reactivation of reward-related patterns. Importantly, individual variability in the strength of reactivation predicted value memory performance. Our results provide a novel demonstration that affect-related neural patterns are reactivated during later experience. Reactivation of value information represents a mechanism by which memory can guide decision making. Copyright © 2016 the authors 0270-6474/16/362868-13$15.00/0.

Diffusion of Helium Isotopes in Silicate Glasses and Minerals: Implications for Petrogenesis and Geochronology.

DTIC Science & Technology

1989-06-01

the Chemistry Department, and the WHOI Education Office for providing financial support and a nice place to work. Parts of this research was funded by...and erosion studies is unknown. c 1.5 OBJECTIVES The objectives of this research are 1) to quantify the diffusive mobility of helium isotopes in...specifically tailored for the diffusion experiments. Data is recorded on a hard disk and on paper , and is automatically backed up to floppy disks

Stress Disrupts Context-Dependent Memory

ERIC Educational Resources Information Center

Schwabe, Lars; Bohringer, Andreas; Wolf, Oliver T.

2009-01-01

Memory is facilitated when the retrieval context resembles the learning context. The brain structures underlying contextual influences on memory are susceptible to stress. Whether stress interferes with context-dependent memory is still unknown. We exposed healthy adults to stress or a control procedure before they learned an object-location task…

UP-REGULATION OF TISSUE FACTOR IN HUMAN PULMONARY ARTERY ENDOTHELIAL CELLS AFTER ULTRAFINE PARTICLE EXPOSURE

EPA Science Inventory

Background: Epidemiology studies have linked exposure to pollutant particles to

increased cardiovascular mortality and morbidity, but the mechanisms remain unknown.

Objectives: We tested the hypothesis that the ultrafine fraction of ambient pollutant

particle...

An evaluation of lithographed forest stereograms.

Treesearch

David A. Bernstein

1961-01-01

Aerial photo stereograms are valuable for showing neophyte photo interpreters the stereoscopic appearance of common objects and conditions. They are also useful for instruction in measuring heights, horizontal distances, and angles on photos. Collections of stereograms of known conditions are worthwhile reference material for interpretation work in unknown areas.

Adaptation of calcium absorption during treatment of nutritional rickets in Nigerian children

USDA-ARS?s Scientific Manuscript database

Nutritional rickets in Nigerian children has been effectively treated with Ca supplementation. High values of Ca absorption efficiency have been observed in untreated children, but whether Ca absorption efficiency changes during treatment with Ca is unknown. Our objective in conducting this study wa...

RecutClub.com: An Open Source, Whole Slide Image-based Pathology Education System

PubMed Central

Christensen, Paul A.; Lee, Nathan E.; Thrall, Michael J.; Powell, Suzanne Z.; Chevez-Barrios, Patricia; Long, S. Wesley

2017-01-01

Background: Our institution's pathology unknown conferences provide educational cases for our residents. However, the cases have not been previously available digitally, have not been collated for postconference review, and were not accessible to a wider audience. Our objective was to create an inexpensive whole slide image (WSI) education suite to address these limitations and improve the education of pathology trainees. Materials and Methods: We surveyed residents regarding their preference between four unique WSI systems. We then scanned weekly unknown conference cases and study set cases and uploaded them to our custom built WSI viewer located at RecutClub.com. We measured site utilization and conference participation. Results: Residents preferred our OpenLayers WSI implementation to Ventana Virtuoso, Google Maps API, and OpenSlide. Over 16 months, we uploaded 1366 cases from 77 conferences and ten study sets, occupying 793.5 GB of cloud storage. Based on resident evaluations, the interface was easy to use and demonstrated minimal latency. Residents are able to review cases from home and from their mobile devices. Worldwide, 955 unique IP addresses from 52 countries have viewed cases in our site. Conclusions: We implemented a low-cost, publicly available repository of WSI slides for resident education. Our trainees are very satisfied with the freedom to preview either the glass slides or WSI and review the WSI postconference. Both local users and worldwide users actively and repeatedly view cases in our study set. PMID:28382224

Estimating the center of mass of a free-floating body in microgravity.

PubMed

Lejeune, L; Casellato, C; Pattyn, N; Neyt, X; Migeotte, P-F

2013-01-01

This paper addresses the issue of estimating the position of the center of mass (CoM) of a free-floating object of unknown mass distribution in microgravity using a stereoscopic imaging system. The method presented here is applied to an object of known mass distribution for validation purposes. In the context of a study of 3-dimensional ballistocardiography in microgravity, and the elaboration of a physical model of the cardiovascular adaptation to weightlessness, the hypothesis that the fluid shift towards the head of astronauts induces a significant shift of their CoM needs to be tested. The experiments were conducted during the 57th parabolic flight campaign of the European Space Agency (ESA). At the beginning of the microgravity phase, the object was given an initial translational and rotational velocity. A 3D point cloud corresponding to the object was then generated, to which a motion-based method inspired by rigid body physics was applied. Through simulations, the effects of the centroid-to-CoM distance and the number of frames of the sequence are investigated. In experimental conditions, considering the important residual accelerations of the airplane during the microgravity phases, CoM estimation errors (16 to 76 mm) were consistent with simulations. Overall, our results suggest that the method has a good potential for its later generalization to a free-floating human body in a weightless environment.

Outcome prediction in home- and community-based brain injury rehabilitation using the Mayo-Portland Adaptability Inventory.

PubMed

Malec, James F; Parrot, Devan; Altman, Irwin M; Swick, Shannon

2015-01-01

The objective of the study was to develop statistical formulas to predict levels of community participation on discharge from post-hospital brain injury rehabilitation using retrospective data analysis. Data were collected from seven geographically distinct programmes in a home- and community-based brain injury rehabilitation provider network. Participants were 642 individuals with post-traumatic brain injury. Interventions consisted of home- and community-based brain injury rehabilitation. The main outcome measure was the Mayo-Portland Adaptability Inventory (MPAI-4) Participation Index. Linear discriminant models using admission MPAI-4 Participation Index score and log chronicity correctly predicted excellent (no to minimal participation limitations), very good (very mild participation limitations), good (mild participation limitations), and limited (significant participation limitations) outcome levels at discharge. Predicting broad outcome categories for post-hospital rehabilitation programmes based on admission assessment data appears feasible and valid. Equations to provide patients and families with probability statements on admission about expected levels of outcome are provided. It is unknown to what degree these prediction equations can be reliably applied and valid in other settings.

Synthesis and Characterization of Aldol Condensation Products from Unknown Aldehydes and Ketones: An Inquiry-Based Experiment in the Undergraduate Laboratory

ERIC Educational Resources Information Center

Angelo, Nicholas G.; Henchey, Laura K.; Waxman, Adam J.; Canary, James W.; Arora, Paramjit S.; Wink, Donald

2007-01-01

An experiment for the undergraduate chemistry laboratory in which students perform the aldol condensation on an unknown aldehyde and an unknown ketone is described. The experiment involves the use of techniques such as TLC, column chromatography, and recrystallization, and compounds are characterized by [to the first power]H NMR, GC-MS, and FTIR.…

Comparative study of methods for recognition of an unknown person's action from a video sequence

NASA Astrophysics Data System (ADS)

Hori, Takayuki; Ohya, Jun; Kurumisawa, Jun

2009-02-01

This paper proposes a Tensor Decomposition Based method that can recognize an unknown person's action from a video sequence, where the unknown person is not included in the database (tensor) used for the recognition. The tensor consists of persons, actions and time-series image features. For the observed unknown person's action, one of the actions stored in the tensor is assumed. Using the motion signature obtained from the assumption, the unknown person's actions are synthesized. The actions of one of the persons in the tensor are replaced by the synthesized actions. Then, the core tensor for the replaced tensor is computed. This process is repeated for the actions and persons. For each iteration, the difference between the replaced and original core tensors is computed. The assumption that gives the minimal difference is the action recognition result. For the time-series image features to be stored in the tensor and to be extracted from the observed video sequence, the human body silhouette's contour shape based feature is used. To show the validity of our proposed method, our proposed method is experimentally compared with Nearest Neighbor rule and Principal Component analysis based method. Experiments using 33 persons' seven kinds of action show that our proposed method achieves better recognition accuracies for the seven actions than the other methods.

Online fully automated three-dimensional surface reconstruction of unknown objects

NASA Astrophysics Data System (ADS)

Khalfaoui, Souhaiel; Aigueperse, Antoine; Fougerolle, Yohan; Seulin, Ralph; Fofi, David

2015-04-01

This paper presents a novel scheme for automatic and intelligent 3D digitization using robotic cells. The advantage of our procedure is that it is generic since it is not performed for a specific scanning technology. Moreover, it is not dependent on the methods used to perform the tasks associated with each elementary process. The comparison of results between manual and automatic scanning of complex objects shows that our digitization strategy is very efficient and faster than trained experts. The 3D models of the different objects are obtained with a strongly reduced number of acquisitions while moving efficiently the ranging device.

A Corpus-Based Approach for Automatic Thai Unknown Word Recognition Using Boosting Techniques

NASA Astrophysics Data System (ADS)

Techo, Jakkrit; Nattee, Cholwich; Theeramunkong, Thanaruk

While classification techniques can be applied for automatic unknown word recognition in a language without word boundary, it faces with the problem of unbalanced datasets where the number of positive unknown word candidates is dominantly smaller than that of negative candidates. To solve this problem, this paper presents a corpus-based approach that introduces a so-called group-based ranking evaluation technique into ensemble learning in order to generate a sequence of classification models that later collaborate to select the most probable unknown word from multiple candidates. Given a classification model, the group-based ranking evaluation (GRE) is applied to construct a training dataset for learning the succeeding model, by weighing each of its candidates according to their ranks and correctness when the candidates of an unknown word are considered as one group. A number of experiments have been conducted on a large Thai medical text to evaluate performance of the proposed group-based ranking evaluation approach, namely V-GRE, compared to the conventional naïve Bayes classifier and our vanilla version without ensemble learning. As the result, the proposed method achieves an accuracy of 90.93±0.50% when the first rank is selected while it gains 97.26±0.26% when the top-ten candidates are considered, that is 8.45% and 6.79% improvement over the conventional record-based naïve Bayes classifier and the vanilla version. Another result on applying only best features show 93.93±0.22% and up to 98.85±0.15% accuracy for top-1 and top-10, respectively. They are 3.97% and 9.78% improvement over naive Bayes and the vanilla version. Finally, an error analysis is given.

Descriptive sensory analysis of marinated and non-marinated woody breast fillet portions

USDA-ARS?s Scientific Manuscript database

The woody breast (WB) myopathy influences muscle composition and texture characteristics in broiler breast meat. It is unknown if marination lessens the negative influence of WB on meat quality or if WB effects are uniform throughout the Pectoralis major. The objective of this study was to determi...

Decreased Regional Cortical Thickness and Thinning Rate Are Associated with Inattention Symptoms in Healthy Children

ERIC Educational Resources Information Center

Ducharme, Simon; Hudziak, James J.; Botteron, Kelly N.; Albaugh, Matthew D.; Nguyen, Tuong-Vi; Karama, Sherif; Evans, Alan C.

2012-01-01

Objective: Children with attention-deficit/hyperactivity disorder (ADHD) have delayed cortical maturation, evidenced by regionally specific slower cortical thinning. However, the relationship between cortical maturation and attention capacities in typically developing children is unknown. This study examines cortical thickness correlates of…

Effects of Juniperus species and stage of maturity on nutritional, in vitro digestibility, and plant secondary compound characteristics

USDA-ARS?s Scientific Manuscript database

Rising feed costs and recurring feed shortages necessitate the investigation into alternative and underutilized feed resources. Nutritional characteristics of Juniperus species are either unknown or limited to leaves and ground material from small stems. Thus, the objective was to quantify nutrition...

Form Follows Function: Learning about Function Helps Children Learn about Shape

ERIC Educational Resources Information Center

Ware, Elizabeth A.; Booth, Amy E.

2010-01-01

Object functions help young children to organize new artifact categories. However, the scope of their influence is unknown. We explore whether functions highlight property dimensions that are relevant to artifact categories in general. Specifically, using a longitudinal training procedure, we assessed whether experience with functions highlights…

Complex Sentence Profiles in Children with Specific Language Impairment: Are They Really Atypical?

ERIC Educational Resources Information Center

Riches, Nick G.

2017-01-01

Children with Specific Language Impairment (SLI) have language difficulties of unknown origin. Syntactic profiles are atypical, with poor performance on non-canonical structures, e.g. object relatives, suggesting a localized deficit. However, existing analyses using ANOVAs are problematic because they do not systematically address unequal…

Internal Medicine Residents Do Not Accurately Assess Their Medical Knowledge

ERIC Educational Resources Information Center

Jones, Roger; Panda, Mukta; Desbiens, Norman

2008-01-01

Background: Medical knowledge is essential for appropriate patient care; however, the accuracy of internal medicine (IM) residents' assessment of their medical knowledge is unknown. Methods: IM residents predicted their overall percentile performance 1 week (on average) before and after taking the in-training exam (ITE), an objective and well…

Children with SLI Exhibit Delays Resolving Ambiguous Reference

ERIC Educational Resources Information Center

Estis, Julie M.; Beverly, Brenda L.

2015-01-01

Fast mapping weaknesses in children with specific language impairment (SLI) may be explained by differences in disambiguation, mapping an unknown word to an unnamed object. The impact of language ability and linguistic stimulus on disambiguation was investigated. Sixteen children with SLI (8 preschool, 8 school-age) and sixteen typically…

Hippocampal Shape Abnormalities of Patients with Childhood-Onset Schizophrenia and Their Unaffected Siblings

ERIC Educational Resources Information Center

Johnson, Sarah L. M.; Wang, Lei; Alpert, Kathryn I.; Greenstein, Deanna; Clasen, Liv; Lalonde, Francois; Miller, Rachel; Rapoport, Judith; Gogtay, Nitin

2013-01-01

Objective: The hippocampus has been implicated in the pathogenesis of schizophrenia, and hippocampal volume deficits have been a consistently reported abnormality, but the subregional specificity of the deficits remains unknown. The authors explored the nature and developmental trajectory of subregional shape abnormalities of the hippocampus in…

Accuracy of stated energy contents of restaurant foods in a multi-site study

USDA-ARS?s Scientific Manuscript database

Context National recommendations for prevention and treatment of obesity emphasize reducing energy intake. Foods purchased in restaurants provide approximately 35% of daily energy intake, but the accuracy of information on the energy contents of these foods is unknown. Objective To examine the a...

An early-killed rye cover crop has potential for weed management in edamame

USDA-ARS?s Scientific Manuscript database

The potential role of fall-seeded cover crops for weed management in edamame is unknown. Field experiments were conducted over three edamame growing seasons to test the following objectives: 1) determine the extent to which cover crop residue management systems influence edamame emergence while sele...

Cross-Situational Learning of Minimal Word Pairs

ERIC Educational Resources Information Center

Escudero, Paola; Mulak, Karen E.; Vlach, Haley A.

2016-01-01

"Cross-situational statistical learning" of words involves tracking co-occurrences of auditory words and objects across time to infer word-referent mappings. Previous research has demonstrated that learners can infer referents across sets of very phonologically distinct words (e.g., WUG, DAX), but it remains unknown whether learners can…

Effects of juniperus species and stage of maturity on nutritional, in vitro digestibility, and plant secondary compound characteristics

USDA-ARS?s Scientific Manuscript database

Rising feed costs and recurring feed shortages necessitate the investigation into alternative and underutilized feed resources. Nutritional characteristics of species are either unknown or limited to leaves and ground material from small stems. Therefore, the objective was to quantify nutritional ch...

Retention Initiatives Used by Professional Bachelor's Athletic Training Program Directors

ERIC Educational Resources Information Center

Bowman, Thomas G.; Mazerolle, Stephanie M.; Dodge, Thomas M.

2016-01-01

Context: Retaining athletic training students has been identified as problematic by approximately half of athletic training program (ATP) directors. It is unknown what ATP directors do to improve athletic training student retention. Objective: To identify initiatives that ATP directors use to improve the retention rates of athletic training…

Toxicity of clay flocculation of the toxic dinoflagellate, Karenia brevis, to estuarine invertebrates and fish

EPA Science Inventory

The benthic environmental effects of proposed control procedures for red tide events are relatively unknown but important to understand. The objective of this study was to determine the laboratory-derived toxicities of a clay flocculation technique proposed for the Florida red ti...

Striatal Sensitivity during Reward Processing in Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Paloyelis, Yannis; Mehta, Mitul A.; Faraone, Stephen V.; Asherson, Philip; Kuntsi, Jonna

2012-01-01

Objective: Attention-deficit/hyperactivity disorder (ADHD) has been linked to deficits in the dopaminergic reward-processing circuitry; yet, existing evidence is limited, and the influence of genetic variation affecting dopamine signaling remains unknown. We investigated striatal responsivity to rewards in ADHD combined type (ADHD-CT) using…

Separation and IR Analysis of a Mixture of Organic Compounds.

ERIC Educational Resources Information Center

Thompson, Evan M.; Almy, John

1982-01-01

Presents an experiment which includes fractional distillation with gas-liquid chromatography (GLC) and infrared analysis. Objectives are to introduce students to fractional distillation and analysis of each fraction by GLC, to induce them to decide if each fraction is sufficient for infrared analysis, and to identify unknowns. (Author/JN)

Reproductive toxicity of a mixture of regulated drinking-water disinfection by-products in a multigenerational rat bioassay

EPA Science Inventory

BACKGROUND:Trihalomethanes (THMs) and haloaretic acids (HAAs) are regulated disinfection by-products (DBPs); their joint reproductive toxicity in drinking water is unknown.OBJECTIVE: We aimed to evaluate a drinking water mixture of the four regulated THMs and five regulated HAAs ...

Programmatic Factors Associated with Undergraduate Athletic Training Student Retention and Attrition Decisions

ERIC Educational Resources Information Center

Bowman, Thomas G.; Hertel, Jay; Wathington, Heather D.

2015-01-01

Context: Athletic training programs (ATPs) are charged with meeting an increased demand for athletic trainers with adequate graduates. Currently, the retention rate of athletic training students in ATPs nationwide and the programmatic factors associated with these retention rates remain unknown. Objective: Determine the retention rate for athletic…

Simultaneous selection by object-based attention in visual and frontal cortex

PubMed Central

Pooresmaeili, Arezoo; Poort, Jasper; Roelfsema, Pieter R.

2014-01-01

Models of visual attention hold that top-down signals from frontal cortex influence information processing in visual cortex. It is unknown whether situations exist in which visual cortex actively participates in attentional selection. To investigate this question, we simultaneously recorded neuronal activity in the frontal eye fields (FEF) and primary visual cortex (V1) during a curve-tracing task in which attention shifts are object-based. We found that accurate performance was associated with similar latencies of attentional selection in both areas and that the latency in both areas increased if the task was made more difficult. The amplitude of the attentional signals in V1 saturated early during a trial, whereas these selection signals kept increasing for a longer time in FEF, until the moment of an eye movement, as if FEF integrated attentional signals present in early visual cortex. In erroneous trials, we observed an interareal latency difference because FEF selected the wrong curve before V1 and imposed its erroneous decision onto visual cortex. The neuronal activity in visual and frontal cortices was correlated across trials, and this trial-to-trial coupling was strongest for the attended curve. These results imply that selective attention relies on reciprocal interactions within a large network of areas that includes V1 and FEF. PMID:24711379

Identification of Occupational Cancer Risks in British Columbia, Canada: A Population-Based Case—Control Study of 1,155 Cases of Colon Cancer

PubMed Central

Fang, Raymond; Le, Nhu; Band, Pierre

2011-01-01

Objective Cancer has been recognized to have environmental origin, but occupational cancer risk studies have not been fully documented. The objective of this paper was to identify occupations and industries with elevated colon cancer risk based on lifetime occupational histories collected from 15,463 incident cancer cases. Method A group matched case-control design was used. All cases were diagnosed with histologically proven colon cancers, with cancer controls being all other cancer sites, excluding rectum, lung and unknown primary, diagnosed at the same period of time from the British Columbia Cancer Registry. Data analyses were done on all 597 Canadian standard occupation titles and 1,104 standard industry titles using conditional logistic regression for matched data sets and the likelihood ratio test. Results Excess colon cancer risks was observed in a number of occupations and industries, particularly those with low physical activity and those involving exposure to asbestos, wood dusts, engine exhaust and diesel engine emissions, and ammonia. Discussion The results of our study are in line with those from the literature and further suggest that exposure to wood dusts and to ammonia may carry an increased occupational risk of colon cancer. PMID:22073015

Optimal design of high-rise buildings with respect to fundamental eigenfrequency

NASA Astrophysics Data System (ADS)

Alavi, Arsalan; Rahgozar, Reza; Torkzadeh, Peyman; Hajabasi, Mohamad Ali

2017-12-01

In modern tall and slender structures, dynamic responses are usually the dominant design requirements, instead of strength criteria. Resonance is often a threatening phenomenon for such structures. To avoid this problem, the fundamental eigenfrequency, an eigenfrequency of higher order, should be maximized. An optimization problem with this objective is constructed in this paper and is applied to a high-rise building. Using variational method, the objective function is maximized, contributing to a particular profile for the first mode shape. Based on this preselected profile, a parametric formulation for flexural stiffness is calculated. Due to some near-zero values for stiffness, the obtained formulation will be modified by adding a lower bound constraint. To handle this constraint some new parameters are introduced; thereby allowing for construction of a model relating the unknown parameters. Based on this mathematical model, a design algorithmic procedure is presented. For the sake of convenience, a single-input design graph is presented as well. The main merit of the proposed method, compared to previous researches, is its hand calculation aspect, suitable for parametric studies and sensitivity analysis. As the presented formulations are dimensionless, they are applicable in any dimensional system. Accuracy and practicality of the proposed method is illustrated at the end by applying it to a real-life structure.

Compensating Unknown Time-Varying Delay in Opto-Electronic Platform Tracking Servo System.

PubMed

Xie, Ruihong; Zhang, Tao; Li, Jiaquan; Dai, Ming

2017-05-09

This paper investigates the problem of compensating miss-distance delay in opto-electronic platform tracking servo system. According to the characteristic of LOS (light-of-sight) motion, we setup the Markovian process model and compensate this unknown time-varying delay by feed-forward forecasting controller based on robust H∞ control. Finally, simulation based on double closed-loop PI (Proportion Integration) control system indicates that the proposed method is effective for compensating unknown time-varying delay. Tracking experiments on the opto-electronic platform indicate that RMS (root-mean-square) error is 1.253 mrad when tracking 10° 0.2 Hz signal.

Predictors of unknown HIV serostatus at the time of labor and delivery in Kampala, Uganda

PubMed Central

Ononge, Sam; Karamagi, Charles; Nakabiito, Clemensia; Wandabwa, Julius; Mirembe, Florence; Rukundo, Godfrey Z.; Jennings, Larissa

2014-01-01

Objective To determine factors associated with an unknown HIV serostatus among pregnant women admitted in labor to Mulago Hospital, Kampala, Uganda. Methods In total, 665 pregnant women admitted to Mulago Hospital were interviewed about their sociodemographic characteristics, obstetric history, access to prenatal care, fears regarding HIV testing, and knowledge about modes of mother-to-child-transmission (MTCT). Knowledge of the HIV serostatus was assessed by self-report and verified by prenatal card review. Results The prevalence of unknown HIV serostatus at the time of labor was 27.1%. Factors associated with an unknown HIV serostatus included high parity (odds ratio [OR] 1.9; 95% confidence interval [CI], 1.16–3.14), preterm delivery (OR 2.60; 95% CI, 1.06–6.34), prenatal care at a private clinic (OR 12.87; 95% CI, 5.68–29.14), residence more than 5 km from the nearest prenatal clinic (OR 2.86; 95% CI, 1.18–17.9), high knowledge about MTCT (OR 0.25; 95% CI, 0.07–0.86), and fears related to disclosing the test result to the partner (OR 3.60; 95% CI, 1.84–7.06). Conclusion The high prevalence of unknown HIV serostatus among women in labor highlights the need to improve accessibility to HIV testing services early during pregnancy to be able to take advantage of antiretroviral therapy. PMID:24290059

Multiple cueing dissociates location- and feature-based repetition effects

PubMed Central

Hu, Kesong; Zhan, Junya; Li, Bingzhao; He, Shuchang; Samuel, Arthur G.

2014-01-01

There is an extensive literature on the phenomenon of inhibition of return (IOR): When attention is drawn to a peripheral location and then removed, response time is delayed if a target appears in the previously inspected location. Recent research suggests that non-spatial attribute repetition (i.e., if a target shares a feature like color with the earlier, cueing, stimulus) can have a similar inhibitory effect, at least when the target appears in the previously cued location. What remains unknown is whether location- and feature-based inhibitory effects can be dissociated. In the present study, we used a multiple cueing approach to investigate the properties of location- and feature-based repetition effects. In two experiments (detection, and discrimination), location-based IOR was absent but feature-based inhibition was consistently observed. Thus, the present results indicate that feature- and location-based inhibitory effects are dissociable. The results also provide support for the view that the attentional consequences of multiple cues reflect the overall center of gravity of the cues. We suggest that the repetition costs associated with feature and location repetition may be best understood as a consequence of the pattern of activation for object files associated with the stimuli present in the displays. PMID:24907677

Intoxication from an accidentally ingested lead shot retained in the gastrointestinal tract.

PubMed

Gustavsson, Per; Gerhardsson, Lars

2005-04-01

A 45-year-old woman was referred to the Department of Occupational and Environmental Health in January 2002 because of increased blood lead concentrations of unknown origin. She suffered from malaise, fatigue, and diffuse gastrointestinal symptoms. She had a blood lead level of 550 microg/L (normal range < 40 microg/L). The patient had not been occupationally exposed to lead, and no potential lead sources, such as food products or lead-glazed pottery, could be identified. Her food habits were normal, but she did consume game occasionally. Clinical examination, including standard neurologic examination, was normal. No anemia was present. Laboratory tests showed an increased excretion of lead in the urine, but there were no signs of microproteinuria. An abdominal X ray in October 2002 revealed a 6-mm rounded metal object in the colon ascendens. Before the object could be further localized, the patient contracted winter vomiting disease (gastroenteritis) and the metal object was spontaneously released from the colon during a diarrhea attack. The object was a lead shot pellet, possibly but not normally used in Sweden for hunting wild boar or roe deer. Blood lead levels slowly decreased. Nine months later the patient's blood lead levels were almost normal (approximately 70 microg/L) and her symptoms had almost completely disappeared. In this case, a rare source of lead exposure was found. In investigations of blood lead elevations of unknown origin, we recommend abdominal X ray in parallel with repeated blood lead determinations.

Active vibration control for piezoelectricity cantilever beam: an adaptive feedforward control method

NASA Astrophysics Data System (ADS)

Zhu, Qiao; Yue, Jun-Zhou; Liu, Wei-Qun; Wang, Xu-Dong; Chen, Jun; Hu, Guang-Di

2017-04-01

This work is focused on the active vibration control of piezoelectric cantilever beam, where an adaptive feedforward controller (AFC) is utilized to reject the vibration with unknown multiple frequencies. First, the experiment setup and its mathematical model are introduced. Due to that the channel between the disturbance and the vibration output is unknown in practice, a concept of equivalent input disturbance (EID) is employed to put an equivalent disturbance into the input channel. In this situation, the vibration control can be achieved by setting the control input be the identified EID. Then, for the EID with known multiple frequencies, the AFC is introduced to perfectly reject the vibration but is sensitive to the frequencies. In order to accurately identify the unknown frequencies of EID in presence of the random disturbances and un-modeled nonlinear dynamics, the time-frequency-analysis (TFA) method is employed to precisely identify the unknown frequencies. Consequently, a TFA-based AFC algorithm is proposed to the active vibration control with unknown frequencies. Finally, four cases are given to illustrate the efficiency of the proposed TFA-based AFC algorithm by experiment.

A spline-based parameter estimation technique for static models of elastic structures

NASA Technical Reports Server (NTRS)

Dutt, P.; Taasan, S.

1986-01-01

The problem of identifying the spatially varying coefficient of elasticity using an observed solution to the forward problem is considered. Under appropriate conditions this problem can be treated as a first order hyperbolic equation in the unknown coefficient. Some continuous dependence results are developed for this problem and a spline-based technique is proposed for approximating the unknown coefficient, based on these results. The convergence of the numerical scheme is established and error estimates obtained.

Bi-static Optical Observations of GEO Objects

NASA Technical Reports Server (NTRS)

Seitzer, Patrick; Barker, Edwin S.; Cowardin, Heather; Lederer, Susan M.; Buckalew, Brent

2014-01-01

A bi-static study of objects at Geosynchronous Earth Orbit (GEO) was conducted using two ground-based wide-field optical telescopes. The University of Michigan's 0.6-m MODEST (Michigan Orbital Debris Survey Telescope) located at the Cerro Tololo Inter- American Observatory in Chile was employed in a series of coordinated observations with the U.S. Naval Observatory's (USNO) 1.3-m telescope at the USNO Flagstaff Station near Flagstaff, Arizona, USA. The goals of this project are twofold: (1) Obtain optical distances to known and unknown objects at GEO from the difference in the observed topocentric position of objects measured with respect to a reference star frame. The distance can be derived directly from these measurements, and is independent of any orbital solution. The wide geographical separation of these two telescopes means that the parallax difference is larger than ten degrees, and (2) Compare optical photometry in similar filters of GEO objects taken during the same time period from the two sites. The object's illuminated surfaces presented different angles of reflected sunlight to the two telescopes.During a four hour period on the night.of 22 February 2014 (UT), coordinated observations were obtained for eight different GEO positions. Each coordinated observation sequence was started on the hour or half-hour, and was selected to ensure the same cataloged GEO object was available in the field of view of both telescopes during the thirty minute observing sequence. GEO objects were chosen to be both controlled and uncontrolled at a range of orbital inclinations, and the objects were not tracked. Instead both telescopes were operated with all drives off in GEO survey mode to discover un-cataloged objects at GEO. The initial results from this proof-of-concept observing run will be presented, with the intent of laying the foundation for future large-scale bi-static observing campaigns of the GEO regime.

Ratbot automatic navigation by electrical reward stimulation based on distance measurement in unknown environments.

PubMed

Gao, Liqiang; Sun, Chao; Zhang, Chen; Zheng, Nenggan; Chen, Weidong; Zheng, Xiaoxiang

2013-01-01

Traditional automatic navigation methods for bio-robots are constrained to configured environments and thus can't be applied to tasks in unknown environments. With no consideration of bio-robot's own innate living ability and treating bio-robots in the same way as mechanical robots, those methods neglect the intelligence behavior of animals. This paper proposes a novel ratbot automatic navigation method in unknown environments using only reward stimulation and distance measurement. By utilizing rat's habit of thigmotaxis and its reward-seeking behavior, this method is able to incorporate rat's intrinsic intelligence of obstacle avoidance and path searching into navigation. Experiment results show that this method works robustly and can successfully navigate the ratbot to a target in the unknown environment. This work might put a solid base for application of ratbots and also has significant implication of automatic navigation for other bio-robots as well.

Distributed Adaptive Neural Network Output Tracking of Leader-Following High-Order Stochastic Nonlinear Multiagent Systems With Unknown Dead-Zone Input.

PubMed

Hua, Changchun; Zhang, Liuliu; Guan, Xinping

2017-01-01

This paper studies the problem of distributed output tracking consensus control for a class of high-order stochastic nonlinear multiagent systems with unknown nonlinear dead-zone under a directed graph topology. The adaptive neural networks are used to approximate the unknown nonlinear functions and a new inequality is used to deal with the completely unknown dead-zone input. Then, we design the controllers based on backstepping method and the dynamic surface control technique. It is strictly proved that the resulting closed-loop system is stable in probability in the sense of semiglobally uniform ultimate boundedness and the tracking errors between the leader and the followers approach to a small residual set based on Lyapunov stability theory. Finally, two simulation examples are presented to show the effectiveness and the advantages of the proposed techniques.

Learning of perceptual grouping for object segmentation on RGB-D data☆

PubMed Central

Richtsfeld, Andreas; Mörwald, Thomas; Prankl, Johann; Zillich, Michael; Vincze, Markus

2014-01-01

Object segmentation of unknown objects with arbitrary shape in cluttered scenes is an ambitious goal in computer vision and became a great impulse with the introduction of cheap and powerful RGB-D sensors. We introduce a framework for segmenting RGB-D images where data is processed in a hierarchical fashion. After pre-clustering on pixel level parametric surface patches are estimated. Different relations between patch-pairs are calculated, which we derive from perceptual grouping principles, and support vector machine classification is employed to learn Perceptual Grouping. Finally, we show that object hypotheses generation with Graph-Cut finds a globally optimal solution and prevents wrong grouping. Our framework is able to segment objects, even if they are stacked or jumbled in cluttered scenes. We also tackle the problem of segmenting objects when they are partially occluded. The work is evaluated on publicly available object segmentation databases and also compared with state-of-the-art work of object segmentation. PMID:24478571

If you watch it move, you'll recognize it in 3D: Transfer of depth cues between encoding and retrieval.

PubMed

Papenmeier, Frank; Schwan, Stephan

2016-02-01

Viewing objects with stereoscopic displays provides additional depth cues through binocular disparity supporting object recognition. So far, it was unknown whether this results from the representation of specific stereoscopic information in memory or a more general representation of an object's depth structure. Therefore, we investigated whether continuous object rotation acting as depth cue during encoding results in a memory representation that can subsequently be accessed by stereoscopic information during retrieval. In Experiment 1, we found such transfer effects from continuous object rotation during encoding to stereoscopic presentations during retrieval. In Experiments 2a and 2b, we found that the continuity of object rotation is important because only continuous rotation and/or stereoscopic depth but not multiple static snapshots presented without stereoscopic information caused the extraction of an object's depth structure into memory. We conclude that an object's depth structure and not specific depth cues are represented in memory. Copyright © 2015 Elsevier B.V. All rights reserved.

Viewpoint dependence in the recognition of non-elongated familiar objects: testing the effects of symmetry, front-back axis, and familiarity.

PubMed

Niimi, Ryosuke; Yokosawa, Kazuhiko

2009-01-01

Visual recognition of three-dimensional (3-D) objects is relatively impaired for some particular views, called accidental views. For most familiar objects, the front and top views are considered to be accidental views. Previous studies have shown that foreshortening of the axes of elongation of objects in these views impairs recognition, but the influence of other possible factors is largely unknown. Using familiar objects without a salient axis of elongation, we found that a foreshortened symmetry plane of the object and low familiarity of the viewpoint accounted for the relatively worse recognition for front views and top views, independently of the effect of a foreshortened axis of elongation. We found no evidence that foreshortened front-back axes impaired recognition in front views. These results suggest that the viewpoint dependence of familiar object recognition is not a unitary phenomenon. The possible role of symmetry (either 2-D or 3-D) in familiar object recognition is also discussed.

Control of Complex Dynamic Systems by Neural Networks

NASA Technical Reports Server (NTRS)

Spall, James C.; Cristion, John A.

1993-01-01

This paper considers the use of neural networks (NN's) in controlling a nonlinear, stochastic system with unknown process equations. The NN is used to model the resulting unknown control law. The approach here is based on using the output error of the system to train the NN controller without the need to construct a separate model (NN or other type) for the unknown process dynamics. To implement such a direct adaptive control approach, it is required that connection weights in the NN be estimated while the system is being controlled. As a result of the feedback of the unknown process dynamics, however, it is not possible to determine the gradient of the loss function for use in standard (back-propagation-type) weight estimation algorithms. Therefore, this paper considers the use of a new stochastic approximation algorithm for this weight estimation, which is based on a 'simultaneous perturbation' gradient approximation that only requires the system output error. It is shown that this algorithm can greatly enhance the efficiency over more standard stochastic approximation algorithms based on finite-difference gradient approximations.

The role of attention in figure-ground segregation in areas V1 and V4 of the visual cortex.

PubMed

Poort, Jasper; Raudies, Florian; Wannig, Aurel; Lamme, Victor A F; Neumann, Heiko; Roelfsema, Pieter R

2012-07-12

Our visual system segments images into objects and background. Figure-ground segregation relies on the detection of feature discontinuities that signal boundaries between the figures and the background and on a complementary region-filling process that groups together image regions with similar features. The neuronal mechanisms for these processes are not well understood and it is unknown how they depend on visual attention. We measured neuronal activity in V1 and V4 in a task where monkeys either made an eye movement to texture-defined figures or ignored them. V1 activity predicted the timing and the direction of the saccade if the figures were task relevant. We found that boundary detection is an early process that depends little on attention, whereas region filling occurs later and is facilitated by visual attention, which acts in an object-based manner. Our findings are explained by a model with local, bottom-up computations for boundary detection and feedback processing for region filling. Copyright © 2012 Elsevier Inc. All rights reserved.

Comparison of the pattern, efficacy, and tolerability of self-medicated drugs in primary dysmenorrhea: A questionnaire based survey

PubMed Central

Sugumar, Ramya; Krishnaiah, Vasundara; Channaveera, Gokul Shetty; Mruthyunjaya, Shilpa

2013-01-01

Objective: To compare the pattern, efficacy, and tolerability of self-medicated drugs and to assess the adequacy of their dose in primary dysmenorrhea (PD). Materials and Methods: A survey using a self-developed, validated, objective, and structured questionnaire as a tool was conducted among subjects with PD. Statistical analysis was carried out using Chi-square test and ANOVA with post-hoc Tuckey's test. Results: Out of 641 respondents, 42% were self-medicated. The pattern of drugs used was: Dicyclomine, an unknown drug, mefenamic acid, mefenamic acid + dicyclomine, and metamizole by 35%, 29%, 26%, 9%, and 1% of respondents, respectively. Mefenamic acid + dicyclomine, the combination was the most efficacious in comparison to other drugs in moderate to severe dysmenorrhea. There was better tolerability with mefenamic acid + dicyclomine group compared to other drugs. Sub-therapeutic doses were used by 86% of self-medicating respondents. Conclusions: The prevailing self-medication practices were inappropriate in a substantial proportion of women with inadequate knowledge regarding appropriate drug choice, therapeutic doses, and their associated side effects. PMID:23716896

Paramagnetic ionic liquids for measurements of density using magnetic levitation.

PubMed

Bwambok, David K; Thuo, Martin M; Atkinson, Manza B J; Mirica, Katherine A; Shapiro, Nathan D; Whitesides, George M

2013-09-03

Paramagnetic ionic liquids (PILs) provide new capabilities to measurements of density using magnetic levitation (MagLev). In a typical measurement, a diamagnetic object of unknown density is placed in a container containing a PIL. The container is placed between two magnets (typically NdFeB, oriented with like poles facing). The density of the diamagnetic object can be determined by measuring its position in the magnetic field along the vertical axis (levitation height, h), either as an absolute value or relative to internal standards of known density. For density measurements by MagLev, PILs have three advantages over solutions of paramagnetic salts in aqueous or organic solutions: (i) negligible vapor pressures; (ii) low melting points; (iii) high thermal stabilities. In addition, the densities, magnetic susceptibilities, glass transition temperatures, thermal decomposition temperatures, viscosities, and hydrophobicities of PILs can be tuned over broad ranges by choosing the cation-anion pair. The low melting points and high thermal stabilities of PILs provide large liquidus windows for density measurements. This paper demonstrates applications and advantages of PILs in density-based analyses using MagLev.

GPR random noise reduction using BPD and EMD

NASA Astrophysics Data System (ADS)

Ostoori, Roya; Goudarzi, Alireza; Oskooi, Behrooz

2018-04-01

Ground-penetrating radar (GPR) exploration is a new high-frequency technology that explores near-surface objects and structures accurately. The high-frequency antenna of the GPR system makes it a high-resolution method compared to other geophysical methods. The frequency range of recorded GPR is so wide that random noise recording is inevitable due to acquisition. This kind of noise comes from unknown sources and its correlation to the adjacent traces is nearly zero. This characteristic of random noise along with the higher accuracy of GPR system makes denoising very important for interpretable results. The main objective of this paper is to reduce GPR random noise based on pursuing denoising using empirical mode decomposition. Our results showed that empirical mode decomposition in combination with basis pursuit denoising (BPD) provides satisfactory outputs due to the sifting process compared to the time-domain implementation of the BPD method on both synthetic and real examples. Our results demonstrate that because of the high computational costs, the BPD-empirical mode decomposition technique should only be used for heavily noisy signals.

Robust Control Design for Uncertain Nonlinear Dynamic Systems

NASA Technical Reports Server (NTRS)

Kenny, Sean P.; Crespo, Luis G.; Andrews, Lindsey; Giesy, Daniel P.

2012-01-01

Robustness to parametric uncertainty is fundamental to successful control system design and as such it has been at the core of many design methods developed over the decades. Despite its prominence, most of the work on robust control design has focused on linear models and uncertainties that are non-probabilistic in nature. Recently, researchers have acknowledged this disparity and have been developing theory to address a broader class of uncertainties. This paper presents an experimental application of robust control design for a hybrid class of probabilistic and non-probabilistic parametric uncertainties. The experimental apparatus is based upon the classic inverted pendulum on a cart. The physical uncertainty is realized by a known additional lumped mass at an unknown location on the pendulum. This unknown location has the effect of substantially altering the nominal frequency and controllability of the nonlinear system, and in the limit has the capability to make the system neutrally stable and uncontrollable. Another uncertainty to be considered is a direct current motor parameter. The control design objective is to design a controller that satisfies stability, tracking error, control power, and transient behavior requirements for the largest range of parametric uncertainties. This paper presents an overview of the theory behind the robust control design methodology and the experimental results.

Fast method to compute scattering by a buried object under a randomly rough surface: PILE combined with FB-SA.

PubMed

Bourlier, Christophe; Kubické, Gildas; Déchamps, Nicolas

2008-04-01

A fast, exact numerical method based on the method of moments (MM) is developed to calculate the scattering from an object below a randomly rough surface. Déchamps et al. [J. Opt. Soc. Am. A23, 359 (2006)] have recently developed the PILE (propagation-inside-layer expansion) method for a stack of two one-dimensional rough interfaces separating homogeneous media. From the inversion of the impedance matrix by block (in which two impedance matrices of each interface and two coupling matrices are involved), this method allows one to calculate separately and exactly the multiple-scattering contributions inside the layer in which the inverses of the impedance matrices of each interface are involved. Our purpose here is to apply this method for an object below a rough surface. In addition, to invert a matrix of large size, the forward-backward spectral acceleration (FB-SA) approach of complexity O(N) (N is the number of unknowns on the interface) proposed by Chou and Johnson [Radio Sci.33, 1277 (1998)] is applied. The new method, PILE combined with FB-SA, is tested on perfectly conducting circular and elliptic cylinders located below a dielectric rough interface obeying a Gaussian process with Gaussian and exponential height autocorrelation functions.

Early malnutrition results in long-lasting impairments in pattern-separation for overlapping novel object and novel location memories and reduced hippocampal neurogenesis.

PubMed

Pérez-García, Georgina; Guzmán-Quevedo, Omar; Da Silva Aragão, Raquel; Bolaños-Jiménez, Francisco

2016-02-17

Numerous epidemiological studies indicate that malnutrition during in utero development and/or childhood induces long-lasting learning disabilities and enhanced susceptibility to develop psychiatric disorders. However, animal studies aimed to address this question have yielded inconsistent results due to the use of learning tasks involving negative or positive reinforces that interfere with the enduring changes in emotional reactivity and motivation produced by in utero and neonatal malnutrition. Consequently, the mechanisms underlying the learning deficits associated with malnutrition in early life remain unknown. Here we implemented a behavioural paradigm based on the combination of the novel object recognition and the novel object location tasks to define the impact of early protein-restriction on the behavioural, cellular and molecular basis of memory processing. Adult rats born to dams fed a low-protein diet during pregnancy and lactation, exhibited impaired encoding and consolidation of memory resulting from impaired pattern separation. This learning deficit was associated with reduced production of newly born hippocampal neurons and down regulation of BDNF gene expression. These data sustain the existence of a causal relationship between early malnutrition and impaired learning in adulthood and show that decreased adult neurogenesis is associated to the cognitive deficits induced by childhood exposure to poor nutrition.

Unsupervised Detection of Planetary Craters by a Marked Point Process

NASA Technical Reports Server (NTRS)

Troglio, G.; Benediktsson, J. A.; Le Moigne, J.; Moser, G.; Serpico, S. B.

2011-01-01

With the launch of several planetary missions in the last decade, a large amount of planetary images is being acquired. Preferably, automatic and robust processing techniques need to be used for data analysis because of the huge amount of the acquired data. Here, the aim is to achieve a robust and general methodology for crater detection. A novel technique based on a marked point process is proposed. First, the contours in the image are extracted. The object boundaries are modeled as a configuration of an unknown number of random ellipses, i.e., the contour image is considered as a realization of a marked point process. Then, an energy function is defined, containing both an a priori energy and a likelihood term. The global minimum of this function is estimated by using reversible jump Monte-Carlo Markov chain dynamics and a simulated annealing scheme. The main idea behind marked point processes is to model objects within a stochastic framework: Marked point processes represent a very promising current approach in the stochastic image modeling and provide a powerful and methodologically rigorous framework to efficiently map and detect objects and structures in an image with an excellent robustness to noise. The proposed method for crater detection has several feasible applications. One such application area is image registration by matching the extracted features.

Money, Food, and Daily Life Objects Are Similarly Shared in the Dictator Game. A Study among Poles and Tsimane'.

PubMed

Sorokowski, Piotr; Oleszkiewicz, Anna; Niemczyk, Agnieszka; Marczak, Michalina; Huanca, Tomas; Velasco, Esther C; Sorokowska, Agnieszka

2017-01-01

The dictator game (DG) is one of the most popular methods for measuring sharing behaviors. However, the matter of goods used in the game has rarely been examined and discussed. We conducted a study in which all participants played standard version of DG in one of the three versions - "money," "food," or "daily life objects" sharing. Further, we wanted to expand the generalizability of our findings by investigating whether patterns in sharing various goods are independent of culture and the level of market integration. Thus, the study was conducted among people who function daily under the conditions of low market integration (109 Tsimane' - forager-horticulturists from Bolivian Amazon) and in a society highly integrated with the market-based economy (85 Polish people). We observed that among both Polish and Tsimane' people the participants were equally likely to share money, food and small, daily life objects with an unknown partner, which implies that generosity might not be related with the type of possessed resources. However, regardless of the kind of goods given, Tsimane' people were less eager to share with anonymous others than Polish people. We present several implications of our findings for studies on generosity and altruism.

Early malnutrition results in long-lasting impairments in pattern-separation for overlapping novel object and novel location memories and reduced hippocampal neurogenesis

PubMed Central

Pérez-García, Georgina; Guzmán-Quevedo, Omar; Da Silva Aragão, Raquel; Bolaños-Jiménez, Francisco

2016-01-01

Numerous epidemiological studies indicate that malnutrition during in utero development and/or childhood induces long-lasting learning disabilities and enhanced susceptibility to develop psychiatric disorders. However, animal studies aimed to address this question have yielded inconsistent results due to the use of learning tasks involving negative or positive reinforces that interfere with the enduring changes in emotional reactivity and motivation produced by in utero and neonatal malnutrition. Consequently, the mechanisms underlying the learning deficits associated with malnutrition in early life remain unknown. Here we implemented a behavioural paradigm based on the combination of the novel object recognition and the novel object location tasks to define the impact of early protein-restriction on the behavioural, cellular and molecular basis of memory processing. Adult rats born to dams fed a low-protein diet during pregnancy and lactation, exhibited impaired encoding and consolidation of memory resulting from impaired pattern separation. This learning deficit was associated with reduced production of newly born hippocampal neurons and down regulation of BDNF gene expression. These data sustain the existence of a causal relationship between early malnutrition and impaired learning in adulthood and show that decreased adult neurogenesis is associated to the cognitive deficits induced by childhood exposure to poor nutrition. PMID:26882991

Does conservation on farmland contribute to halting the biodiversity decline?

PubMed

Kleijn, David; Rundlöf, Maj; Scheper, Jeroen; Smith, Henrik G; Tscharntke, Teja

2011-09-01

Biodiversity continues to decline, despite the implementation of international conservation conventions and measures. To counteract biodiversity loss, it is pivotal to know how conservation actions affect biodiversity trends. Focussing on European farmland species, we review what is known about the impact of conservation initiatives on biodiversity. We argue that the effects of conservation are a function of conservation-induced ecological contrast, agricultural land-use intensity and landscape context. We find that, to date, only a few studies have linked local conservation effects to national biodiversity trends. It is therefore unknown how the extensive European agri-environmental budget for conservation on farmland contributes to the policy objectives to halt biodiversity decline. Based on this review, we identify new research directions addressing this important knowledge gap. Copyright © 2011 Elsevier Ltd. All rights reserved.

Hamiltonian models for topological phases of matter in three spatial dimensions

NASA Astrophysics Data System (ADS)

Williamson, Dominic J.; Wang, Zhenghan

2017-02-01

We present commuting projector Hamiltonian realizations of a large class of (3 + 1)D topological models based on mathematical objects called unitary G-crossed braided fusion categories. This construction comes with a wealth of examples from the literature of symmetry-enriched topological phases. The spacetime counterparts to our Hamiltonians are unitary state sum topological quantum fields theories (TQFTs) that appear to capture all known constructions in the literature, including the Crane-Yetter-Walker-Wang and 2-Group gauge theory models. We also present Hamiltonian realizations of a state sum TQFT recently constructed by Kashaev whose relation to existing models was previously unknown. We argue that this TQFT is captured as a special case of the Crane-Yetter-Walker-Wang model, with a premodular input category in some instances.

Homeopathic drug discovery: theory update and methodological aspect.

PubMed

Khuda-Bukhsh, Anisur Rahman; Pathak, Surajit

2008-08-01

Homeopathy treats patient on the basis of totality of symptoms and is based on the principle of 'like cures like'. It uses ultra-low doses of highly diluted natural substances as remedies that originate from plants, minerals or animals. The objectives of this review are to discuss concepts, controversies and research related to understanding homeopathy in the light of modern science. Attempts have been made to focus on current views of homeopathy and to delineate its most plausible mechanism(s) of action. Although some areas of concern remain, research carried out so far both in vitro and in vivo validates the effects of highly diluted homeopathic medicines in a wide variety of organisms. The precise mechanism(s) and pathway(s) of action of highly diluted homeopathic drugs are still unknown.

Yogic exercises and health--a psycho-neuro immunological approach.

PubMed

Kulkarni, D D; Bera, T K

2009-01-01

Relaxation potential of yogic exercises seems to play a vital role in establishing psycho-physical health in reversing the psycho-immunology of emotions under stress based on breath and body awareness. However, mechanism of yogic exercises for restoring health and fitness components operating through psycho-neuro-immunological pathways is unknown. Therefore, a hybrid model of human information processing-psycho-neuroendocrine (HIP-PNE) network has been proposed to reveal the importance of yogic information processing. This study focuses on two major pathways of information processing involving cortical and hypothalamo-pituitary-adrenal axis (HPA) interactions with a deep reach molecular action on cellular, neuro-humoral and immune system in reversing stress mediated diseases. Further, the proposed HIP-PNE model has ample of experimental potential for objective evaluation of yogic view of health and fitness.

Electromagnetic spectrum management system

DOEpatents

Seastrand, Douglas R.

2017-01-31

A system for transmitting a wireless countermeasure signal to disrupt third party communications is disclosed that include an antenna configured to receive wireless signals and transmit wireless counter measure signals such that the wireless countermeasure signals are responsive to the received wireless signals. A receiver processes the received wireless signals to create processed received signal data while a spectrum control module subtracts known source signal data from the processed received signal data to generate unknown source signal data. The unknown source signal data is based on unknown wireless signals, such as enemy signals. A transmitter is configured to process the unknown source signal data to create countermeasure signals and transmit a wireless countermeasure signal over the first antenna or a second antenna to thereby interfere with the unknown wireless signals.

Using Project-Based Learning to Design, Build, and Test Student-Made Photometer by Measuring the Unknown Concentration of Colored Substances

ERIC Educational Resources Information Center

Diawati, Chansyanah; Liliasari; Setiabudi, Agus; Buchari

2018-01-01

Students learned the principles and practice of photometry through project-based learning. They addressed the challenge of measuring the unknown concentration of a colored substance using a photometer they were required to design, build, and test. Then, they used that instrument to carry out the experiment and fulfill the challenge. A photometer…

Minimal-Approximation-Based Distributed Consensus Tracking of a Class of Uncertain Nonlinear Multiagent Systems With Unknown Control Directions.

PubMed

Choi, Yun Ho; Yoo, Sung Jin

2017-03-28

A minimal-approximation-based distributed adaptive consensus tracking approach is presented for strict-feedback multiagent systems with unknown heterogeneous nonlinearities and control directions under a directed network. Existing approximation-based consensus results for uncertain nonlinear multiagent systems in lower-triangular form have used multiple function approximators in each local controller to approximate unmatched nonlinearities of each follower. Thus, as the follower's order increases, the number of the approximators used in its local controller increases. However, the proposed approach employs only one function approximator to construct the local controller of each follower regardless of the order of the follower. The recursive design methodology using a new error transformation is derived for the proposed minimal-approximation-based design. Furthermore, a bounding lemma on parameters of Nussbaum functions is presented to handle the unknown control direction problem in the minimal-approximation-based distributed consensus tracking framework and the stability of the overall closed-loop system is rigorously analyzed in the Lyapunov sense.

Optimal hemodynamic response model for functional near-infrared spectroscopy

PubMed Central

Kamran, Muhammad A.; Jeong, Myung Yung; Mannan, Malik M. N.

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an emerging non-invasive brain imaging technique and measures brain activities by means of near-infrared light of 650–950 nm wavelengths. The cortical hemodynamic response (HR) differs in attributes at different brain regions and on repetition of trials, even if the experimental paradigm is kept exactly the same. Therefore, an HR model that can estimate such variations in the response is the objective of this research. The canonical hemodynamic response function (cHRF) is modeled by two Gamma functions with six unknown parameters (four of them to model the shape and other two to scale and baseline respectively). The HRF model is supposed to be a linear combination of HRF, baseline, and physiological noises (amplitudes and frequencies of physiological noises are supposed to be unknown). An objective function is developed as a square of the residuals with constraints on 12 free parameters. The formulated problem is solved by using an iterative optimization algorithm to estimate the unknown parameters in the model. Inter-subject variations in HRF and physiological noises have been estimated for better cortical functional maps. The accuracy of the algorithm has been verified using 10 real and 15 simulated data sets. Ten healthy subjects participated in the experiment and their HRF for finger-tapping tasks have been estimated and analyzed. The statistical significance of the estimated activity strength parameters has been verified by employing statistical analysis (i.e., t-value > tcritical and p-value < 0.05). PMID:26136668

Optimal hemodynamic response model for functional near-infrared spectroscopy.

PubMed

Kamran, Muhammad A; Jeong, Myung Yung; Mannan, Malik M N

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an emerging non-invasive brain imaging technique and measures brain activities by means of near-infrared light of 650-950 nm wavelengths. The cortical hemodynamic response (HR) differs in attributes at different brain regions and on repetition of trials, even if the experimental paradigm is kept exactly the same. Therefore, an HR model that can estimate such variations in the response is the objective of this research. The canonical hemodynamic response function (cHRF) is modeled by two Gamma functions with six unknown parameters (four of them to model the shape and other two to scale and baseline respectively). The HRF model is supposed to be a linear combination of HRF, baseline, and physiological noises (amplitudes and frequencies of physiological noises are supposed to be unknown). An objective function is developed as a square of the residuals with constraints on 12 free parameters. The formulated problem is solved by using an iterative optimization algorithm to estimate the unknown parameters in the model. Inter-subject variations in HRF and physiological noises have been estimated for better cortical functional maps. The accuracy of the algorithm has been verified using 10 real and 15 simulated data sets. Ten healthy subjects participated in the experiment and their HRF for finger-tapping tasks have been estimated and analyzed. The statistical significance of the estimated activity strength parameters has been verified by employing statistical analysis (i.e., t-value > t critical and p-value < 0.05).

Navigation integrity monitoring and obstacle detection for enhanced-vision systems

NASA Astrophysics Data System (ADS)

Korn, Bernd; Doehler, Hans-Ullrich; Hecker, Peter

2001-08-01

Typically, Enhanced Vision (EV) systems consist of two main parts, sensor vision and synthetic vision. Synthetic vision usually generates a virtual out-the-window view using databases and accurate navigation data, e. g. provided by differential GPS (DGPS). The reliability of the synthetic vision highly depends on both, the accuracy of the used database and the integrity of the navigation data. But especially in GPS based systems, the integrity of the navigation can't be guaranteed. Furthermore, only objects that are stored in the database can be displayed to the pilot. Consequently, unexpected obstacles are invisible and this might cause severe problems. Therefore, additional information has to be extracted from sensor data to overcome these problems. In particular, the sensor data analysis has to identify obstacles and has to monitor the integrity of databases and navigation. Furthermore, if a lack of integrity arises, navigation data, e.g. the relative position of runway and aircraft, has to be extracted directly from the sensor data. The main contribution of this paper is about the realization of these three sensor data analysis tasks within our EV system, which uses the HiVision 35 GHz MMW radar of EADS, Ulm as the primary EV sensor. For the integrity monitoring, objects extracted from radar images are registered with both database objects and objects (e. g. other aircrafts) transmitted via data link. This results in a classification into known and unknown radar image objects and consequently, in a validation of the integrity of database and navigation. Furthermore, special runway structures are searched for in the radar image where they should appear. The outcome of this runway check contributes to the integrity analysis, too. Concurrent to this investigation a radar image based navigation is performed without using neither precision navigation nor detailed database information to determine the aircraft's position relative to the runway. The performance of our approach is demonstrated with real data acquired during extensive flight tests to several airports in Northern Germany.

Ground-based Characterization of Earth Quasi Satellite (469219) 2016 HO3

NASA Astrophysics Data System (ADS)

Reddy, Vishnu; Kuhn, Olga; Thirouin, Audrey; Conrad, Al; Malhotra, Renu; Sanchez, Juan A.; Veillet, Christian

2017-10-01

(469219) 2016 HO3 is a small, <100 meter-size, near-Earth object (NEO) that while orbiting the Sun, also appears to circle around the Earth just beyond the Hill sphere as a Earth quasi-satellite. Only five quasi-satellites have been discovered so far, but 2016 HO3 is the most stable of them. The provenance of this object is unknown. On timescales of many centuries, 2016 HO3 remains within 38-100 lunar distance from us making it a prime target for future robotic and human exploration, provided it can be established it is indeed a natural object. In an effort to constrain its rotation period and surface composition, we observed 2016 HO3 on April 14 and 18 2017 (UTC) with the Large Binocular Telescope (LBT) and the Discovery Channel Telescope (DCT). We derive a rotation period of about 28 minutes based on our lightcurve observations. We obtained low-resolution (R ˜ 150 - 500) spectra of 2016 HO3 on 2017 April 14 (UTC) using the pair of MODS spectrographs mounted at the direct Gregorian foci of the LBT, obtaining the entire spectrum from 0.39-0.97 microns simultaneously. The visible wavelength spectrum shows a sharp rise in reflectance between 0.4-0.65 microns with a broad plateau beyond. The scatter near 0.8 microns makes it challenging to confirm the presence of a silicate absorption band at ~1 micron. Color ratios derived from the spectrum all suggest an S taxonomic type. We also derive an updated diameter of 36 meters for 2016 HO3 using an absolute magnitude of 24.3 and S-type albedo of 0.25. The derived rotation period and the spectrum are not uncommon amongst small NEOs, suggesting that 2016 HO3 is a natural object of similar provenance to other small NEOs. NASA Near-Earth Object Observations Program Grant NNX17AJ19G (PI: Reddy) funded parts of this work.

[Clinical significance of four quadrant localization in the diagnosis and treatment of metastatic carcinoma of the neck with unknown primary].

PubMed

Gao, Y Y; Chen, X H

2017-06-05

Objective: The aim of this study is to investigate the clinical significance of four quadrant localization in the diagnosis and treatment of unknown primary cervical metastases. Method: The clinical data with unknown primary cervical metastases, were analyzed retrospectively. All the patients have not been found the original site in the initial treatment. There are four quadrants in the neck, the neck line as the longitudinal axis, and edge of cricoid cartilage as the horizontal axis. When cervical metastasis occurred in the left and right upper quadrant, the primary tumor site and radiotherapy from the skull base to the root of the neck; when appear in left and right lower quadrant, the primary investigation site and radiotherapy from neck to thoracic mediastinum, left lower abdomen also includes following primary search. At the same time, bilateral cervical metastasis cancers, focusing on the central line near the primary focus. Specific treatment strategies include ipsilateral total neck dissection and radical radiotherapy of the above radiotherapy site. Result: Left upper neck in 4 cases, right upper neck in 5 cases, left lower neck in 7 cases, lower right neck in 8 cases and mixed area in 6 cases. Only 10 of 30 patients (33.3%) with primary sites were found in the follow up period. In accordance with the four quadrant localization, the median time was 6 months. Conclusion: Four quadrant localization to locate the primary site is accurate, and individualized comprehensive treatment is the key to improve the curative effect. Copyright© by the Editorial Department of Journal of Clinical Otorhinolaryngology Head and Neck Surgery.

Treatment Patterns for Cervical Carcinoma In Situ in Michigan, 1998-2003

PubMed Central

Patel, Divya A.; Saraiya, Mona; Copeland, Glenn; Cote, Michele L.; Datta, S. Deblina; Sawaya, George F.

2015-01-01

Objective To characterize population-level surgical treatment patterns for cervical carcinoma in situ (CIS) reported to the Michigan Cancer Surveillance Program (MCSP), and to inform data collection strategies. Methods All cases of cervical carcinoma in situ (CIS) (including cervical intraepithelial neoplasia grade 3 and adenocarcinoma in situ [AIS]) reported to the MCSP during 1998–2003 were identified. First course of treatment (ablative procedure, cone biopsy, loop electrosurgical excisional procedure [LEEP], hysterectomy, unspecified surgical treatment, no surgical treatment, unknown if surgically treated) was described by histology, race, and age at diagnosis. Results Of 17,022 cases of cervical CIS, 82.8% were squamous CIS, 3% AIS/adenosquamous CIS, and 14.2% unspecified/other CIS. Over half (54.7%) of cases were diagnosed in women under age 30. Excisional treatments (LEEP, 32.3% and cone biopsy, 17.3%) were most common, though substantial proportions had no reported treatment (17.8%) or unknown treatment (21.1%). Less common were hysterectomy (7.2%) and ablative procedures (2.6%). LEEP was the most common treatment for squamous cases, while hysterectomy was the most treatment for AIS/adenosquamous CIS cases. Across histologic types, a sizeable proportion of women diagnosed ≤30 years of age underwent excision, either LEEP (20%–38.7%) or cone biopsy (13.7%–44%). Conclusion Despite evidence suggesting it may be safer and equally effective as excision, ablation was rarely used for treating cervical squamous CIS. These population-based data indicate some notable differences in treatment by histology and age at diagnosis, with observed patterns appearing consistent with consensus guidelines in place at the time of study, but favoring more aggressive procedures. Future data collection strategies may need to validate treatment information, including the large proportion of no or unknown treatment. PMID:24002133

The Immune System as a Model for Pattern Recognition and Classification

PubMed Central

Carter, Jerome H.

2000-01-01

Objective: To design a pattern recognition engine based on concepts derived from mammalian immune systems. Design: A supervised learning system (Immunos-81) was created using software abstractions of T cells, B cells, antibodies, and their interactions. Artificial T cells control the creation of B-cell populations (clones), which compete for recognition of “unknowns.” The B-cell clone with the “simple highest avidity” (SHA) or “relative highest avidity” (RHA) is considered to have successfully classified the unknown. Measurement: Two standard machine learning data sets, consisting of eight nominal and six continuous variables, were used to test the recognition capabilities of Immunos-81. The first set (Cleveland), consisting of 303 cases of patients with suspected coronary artery disease, was used to perform a ten-way cross-validation. After completing the validation runs, the Cleveland data set was used as a training set prior to presentation of the second data set, consisting of 200 unknown cases. Results: For cross-validation runs, correct recognition using SHA ranged from a high of 96 percent to a low of 63.2 percent. The average correct classification for all runs was 83.2 percent. Using the RHA metric, 11.2 percent were labeled “too close to determine” and no further attempt was made to classify them. Of the remaining cases, 85.5 percent were correctly classified. When the second data set was presented, correct classification occurred in 73.5 percent of cases when SHA was used and in 80.3 percent of cases when RHA was used. Conclusions: The immune system offers a viable paradigm for the design of pattern recognition systems. Additional research is required to fully exploit the nuances of immune computation. PMID:10641961

Map generation in unknown environments by AUKF-SLAM using line segment-type and point-type landmarks

NASA Astrophysics Data System (ADS)

Nishihta, Sho; Maeyama, Shoichi; Watanebe, Keigo

2018-02-01

Recently, autonomous mobile robots that collect information at disaster sites are being developed. Since it is difficult to obtain maps in advance in disaster sites, the robots being capable of autonomous movement under unknown environments are required. For this objective, the robots have to build maps, as well as the estimation of self-location. This is called a SLAM problem. In particular, AUKF-SLAM which uses corners in the environment as point-type landmarks has been developed as a solution method so far. However, when the robots move in an environment like a corridor consisting of few point-type features, the accuracy of self-location estimated by the landmark is decreased and it causes some distortions in the map. In this research, we propose AUKF-SLAM which uses walls in the environment as a line segment-type landmark. We demonstrate that the robot can generate maps in unknown environment by AUKF-SLAM, using line segment-type and point-type landmarks.

Magnetic Moment Quantifications of Small Spherical Objects in MRI

PubMed Central

Cheng, Yu-Chung N.; Hsieh, Ching-Yi; Tackett, Ronald; Kokeny, Paul; Regmi, Rajesh Kumar; Lawes, Gavin

2014-01-01

Purpose The purpose of this work is to develop a method for accurately quantifying effective magnetic moments of spherical-like small objects from magnetic resonance imaging (MRI). A standard 3D gradient echo sequence with only one echo time is intended for our approach to measure the effective magnetic moment of a given object of interest. Methods Our method sums over complex MR signals around the object and equates those sums to equations derived from the magnetostatic theory. With those equations, our method is able to determine the center of the object with subpixel precision. By rewriting those equations, the effective magnetic moment of the object becomes the only unknown to be solved. Each quantified effective magnetic moment has an uncertainty that is derived from the error propagation method. If the volume of the object can be measured from spin echo images, the susceptibility difference between the object and its surrounding can be further quantified from the effective magnetic moment. Numerical simulations, a variety of glass beads in phantom studies with different MR imaging parameters from a 1.5 T machine, and measurements from a SQUID (superconducting quantum interference device) based magnetometer have been conducted to test the robustness of our method. Results Quantified effective magnetic moments and susceptibility differences from different imaging parameters and methods all agree with each other within two standard deviations of estimated uncertainties. Conclusion An MRI method is developed to accurately quantify the effective magnetic moment of a given small object of interest. Most results are accurate within 10% of true values and roughly half of the total results are accurate within 5% of true values using very reasonable imaging parameters. Our method is minimally affected by the partial volume, dephasing, and phase aliasing effects. Our next goal is to apply this method to in vivo studies. PMID:25490517

[Searching for Rare Celestial Objects Automatically from Stellar Spectra of the Sloan Digital Sky Survey Data Release Eight].

PubMed

Si, Jian-min; Luo, A-li; Wu, Fu-zhao; Wu, Yi-hong

2015-03-01

There are many valuable rare and unusual objects in spectra dataset of Sloan Digital Sky Survey (SDSS) Data Release eight (DR8), such as special white dwarfs (DZ, DQ, DC), carbon stars, white dwarf main-sequence binaries (WDMS), cataclysmic variable (CV) stars and so on, so it is extremely significant to search for rare and unusual celestial objects from massive spectra dataset. A novel algorithm based on Kernel dense estimation and K-nearest neighborhoods (KNN) has been presented, and applied to search for rare and unusual celestial objects from 546 383 stellar spectra of SDSS DR8. Their densities are estimated using Gaussian kernel density estimation, the top 5 000 spectra in descend order by their densities are selected as rare objects, and the top 300 000 spectra in ascend order by their densities are selected as normal objects. Then, KNN were used to classify the rest objects, and simultaneously K nearest neighbors of the 5 000 rare spectra are also selected as rare objects. As a result, there are totally 21 193 spectra selected as initial rare spectra, which include error spectra caused by deletion, redden, bad calibration, spectra consisting of different physically irrelevant components, planetary nebulas, QSOs, special white dwarfs (DZ, DQ, DC), carbon stars, white dwarf main-sequence binaries (WDMS), cataclysmic variable (CV) stars and so on. By cross identification with SIMBAD, NED, ADS and major literature, it is found that three DZ white dwarfs, one WDMS, two CVs with company of G-type star, three CVs candidates, six DC white dwarfs, one DC white dwarf candidate and one BL Lacertae (BL lac) candidate are our new findings. We also have found one special DA white dwarf with emission lines of Ca II triple and Mg I, and one unknown object whose spectrum looks like a late M star with emission lines and its image looks like a galaxy or nebula.

Magnetic moment quantifications of small spherical objects in MRI.

PubMed

Cheng, Yu-Chung N; Hsieh, Ching-Yi; Tackett, Ronald; Kokeny, Paul; Regmi, Rajesh Kumar; Lawes, Gavin

2015-07-01

The purpose of this work is to develop a method for accurately quantifying effective magnetic moments of spherical-like small objects from magnetic resonance imaging (MRI). A standard 3D gradient echo sequence with only one echo time is intended for our approach to measure the effective magnetic moment of a given object of interest. Our method sums over complex MR signals around the object and equates those sums to equations derived from the magnetostatic theory. With those equations, our method is able to determine the center of the object with subpixel precision. By rewriting those equations, the effective magnetic moment of the object becomes the only unknown to be solved. Each quantified effective magnetic moment has an uncertainty that is derived from the error propagation method. If the volume of the object can be measured from spin echo images, the susceptibility difference between the object and its surrounding can be further quantified from the effective magnetic moment. Numerical simulations, a variety of glass beads in phantom studies with different MR imaging parameters from a 1.5T machine, and measurements from a SQUID (superconducting quantum interference device) based magnetometer have been conducted to test the robustness of our method. Quantified effective magnetic moments and susceptibility differences from different imaging parameters and methods all agree with each other within two standard deviations of estimated uncertainties. An MRI method is developed to accurately quantify the effective magnetic moment of a given small object of interest. Most results are accurate within 10% of true values, and roughly half of the total results are accurate within 5% of true values using very reasonable imaging parameters. Our method is minimally affected by the partial volume, dephasing, and phase aliasing effects. Our next goal is to apply this method to in vivo studies. Copyright © 2015 Elsevier Inc. All rights reserved.

Zirconia in fixed prosthesis. A literature review

PubMed Central

Román-Rodríguez, Juan L.; Ferreiroa, Alberto; Solá-Ruíz, María F.; Fons-Font, Antonio

2014-01-01

Statement of problem: Evidence is limited on the efficacy of zirconia-based fixed dental prostheses. Objective: To carry out a literature review of the behavior of zirconium oxide dental restorations. Material and Methods: This literature review searched the Pubmed, Scopus, Medline and Cochrane Library databases using key search words “zirconium oxide,” “zirconia,” “non-metal restorations,” “ceramic oxides,” “veneering ceramic,” “zirconia-based fixed dental prostheses”. Both in vivo and in vitro studies into zirconia-based prosthodontic restoration behavior were included. Results: Clinical studies have revealed a high rate of fracture for porcelain-veneered zirconia-based restorations that varies between 6% and 15% over a 3- to 5-year period, while for ceramo-metallic restorations the fracture rate ranges between 4 and 10% over ten years. These results provoke uncertainty as to the long-term prognosis for this material in the oral medium. The cause of veneering porcelain fractures is unknown but hypothetically they could be associated with bond failure between the veneer material and the zirconia sub-structure. Key words:Veneering ceramic, zirconia-based ceramic restoration, crown, zirconia, tooth-supported fixed prosthesis. PMID:24596638

The effects of diet ingredients on gastric ulceration and stereotypies in gestating sows

USDA-ARS?s Scientific Manuscript database

Stereotypies in swine can be altered with various feedstuffs, but it is unknown how this will affect the development of gastric ulcers. The objective of this experiment was to determine the effects of a proton pump inhibitor and sodium bicarbonate on ulcerations of the pars esophagea (UPE) region of...

TRACE METAL AVAILABILITY TO PERIPHYTON COLONIZED BELOW NEAR-COASTAL WASTEWATER DISCHARGES IN THE GULF OF MEXICO

EPA Science Inventory

The significance of the many wastewater discharges in the Gulf of Mexico region as sources of trace metal contamination to indigenous biota in nearby coastal areas is relatively unknown. The primary objective of this baseline survey was to provide some insight on this issue by d...

Brain-derived neurotrophic factor in human subjects with function-altering melanocortin-4 receptor variants

USDA-ARS?s Scientific Manuscript database

In rodents, hypothalamic brain-derived neurotrophic factor (BDNF) expression appears to be regulated by melanocortin-4 receptor (MC4R) activity. The impact of MC4R genetic variation on circulating BDNF in humans is unknown. The objective of this study is to compare BDNF concentrations of subjects wi...

Sport and Recreation Are Associated with Happiness across Countries

ERIC Educational Resources Information Center

Balish, Shea M.; Conacher, Dan; Dithurbide, Lori

2016-01-01

Purpose: Preliminary findings suggest sport participation is positively associated with happiness. However, it is unknown if this association is universal and how sport compares to other leisure activities in terms of an association with happiness. This study had 3 objectives: (a) to test if sport membership is associated with happiness, (b) to…

Motor Impairment in Sibling Pairs Concordant and Discordant for Autism Spectrum Disorders

ERIC Educational Resources Information Center

Hilton, Claudia List; Zhang, Yi; Whilte, Megan R.; Klohr, Cheryl L.; Constantino, John

2012-01-01

Aim: Although motor impairment is frequently observed in children with autism spectrum disorders (ASD), the manner in which these impairments aggregate in families affected by autism is unknown. We used a standardized measure of motor proficiency to objectively examine quantitative variation in motor proficiency in sibling pairs concordant and…

DETERMINING HOT SPOTS OF FECAL CONTAMINATION IN A TROPICAL WATERSHED BY COMBINING LAND-USE INFORMATION AND METEOROLOGICAL DATA WITH SOURCE-SPECIFIC ASSAYS

EPA Science Inventory

Microbial source tracking (MST) assays have been mostly employed in temperate climates. However, their value as monitoring tools in tropical and subtropical regions is unknown since the geographic and temporal stability of the assays has not been extensively tested. The objective...

Ground Ant Diversity (Hymenoptera: Formicidae) in the Iberá Nature Reserve, the Largest Wetland of Argentina

USDA-ARS?s Scientific Manuscript database

The Iberá Nature Reserve in northeastern Argentina protects one of the largest freshwater wetlands and reservoirs of species in South America. However, key invertebrate groups such as the ants (Hymenoptera: Formicidae) remain almost unknown. The main objective of this work was to study the ground an...

Arsenic is associated with reduced effect of folic acid in myelomeningocele prevention: a case control study in Bangladesh

USDA-ARS?s Scientific Manuscript database

Background: Arsenic induces neural tube defects in several animal models, but its potential to cause neural tube defects in humans is unknown. Our objective was to investigate the associations between maternal arsenic exposure, periconceptional folic acid supplementation, and risk of posterior neura...

Regulation of lipid synthesis genes and milk fat production in human mammary epithelial cells during secretory activation

USDA-ARS?s Scientific Manuscript database

Expression of genes for lipid biosynthetic enzymes during initiation of lactation in humans is unknown. Our objective was to study mRNA expression of lipid metabolic enzymes in human mammary epithelial cell (MEC) in conjunction with the measurement of milk fatty acid (FA) composition during secretor...

Immigration, Generational Status and Health Literacy in Canada

ERIC Educational Resources Information Center

Ng, Edward; Omariba, D. Walter R.

2014-01-01

Background: Immigrants, a fast-growing population in Canada, score below the national average in health literacy, but the reasons behind the low scores are largely unknown. Also, there is a need to understand the long-term impact of immigration by examining health literacy by generational status. Objective: To examine health literacy differentials…

Evaluation of the ruminal bacterial diversity of cattle fed diets containing citrus pulp pellets

USDA-ARS?s Scientific Manuscript database

The rumen microbial ecosystem remains a mystery from a quantitative perspective. Dietary components and changes cause shifts in the ruminal microbial ecology that can play a role in animal health and productivity, but the magnitude of these changes remains unknown. The objective of this study was ...

Arginine metabolism is altered in adults with A-B + ketosis-prone diabetes

USDA-ARS?s Scientific Manuscript database

A-B + ketosis-prone diabetes (KPD) is a subset of type 2 diabetes in which patients have severe but reversible B cell dysfunction of unknown etiology. Plasma metabolomic analysis indicates that abnormal arginine metabolism may be involved. The objective of this study was to determine the relation be...

Toward a fusion of optical coherence tomography and hyperspectral imaging for poultry meat quality assessment

USDA-ARS?s Scientific Manuscript database

An emerging poultry meat quality concern is associated with chicken breast fillets having an uncharacteristically hard or rigid feel (called the wooden breast condition). The cause of the wooden breast condition is still largely unknown, and there is no single objective evaluation method or system k...

Selecting a sampling method to aid in vegetation management decisions in loblolly pine plantations

Treesearch

David R. Weise; Glenn R. Glover

1993-01-01

Objective methods to evaluate hardwood competition in young loblolly pine (Pinustaeda L.) plantations are not widely used in the southeastern United States. Ability of common sampling rules to accurately estimate hardwood rootstock attributes at low sampling intensities and across varying rootstock spatial distributions is unknown. Fixed area plot...

Endocannabinoid concentrations in plasma during the finishing period are associated with feed efficiency and carcass composition of beef cattle

USDA-ARS?s Scientific Manuscript database

We previously have shown that plasma concentrations of endocannabinoids (EC) are positively correlated with feed efficiency and leaner carcasses in finishing steers. However, whether the animal growth during the finishing period affects the concentration of EC is unknown. The objective of this study...

19 CFR Appendix to Part 145 - Unknown Title

Code of Federal Regulations, 2010 CFR

2010-04-01

... either the sender or the addressee has been obtained in advance of the opening. Past practice indicates... indicate that merchandise or contraband (e.g., a hard object which may be jewelry, a stack of paper which... known to have mailed or received contraband or merchandise in violation of law in the past. 7. The...

Racial and Ethnic Disparities in ADHD Diagnosis from Kindergarten to Eighth Grade

ERIC Educational Resources Information Center

Morgan, Paul L.; Staff, Jeremy; Hillemeier, Marianne M.; Farkas, George; Maczuga, Steven

2013-01-01

Objective: Whether and to what extent racial/ethnic disparities in attention-deficit/hyperactivity disorder (ADHD) diagnosis occur across early and middle childhood is currently unknown. We examined the over-time dynamics of race/ethnic disparities in diagnosis from kindergarten to eighth grade and disparities in treatment in fifth and eighth…

The Negotiation of Lived Spaces by Unauthorized College Aged Youth

ERIC Educational Resources Information Center

Jacobo, Rodolfo

2010-01-01

Throughout the United States, undocumented students live in constant fear of their legal status being disclosed, and despite their educational success and professional objectives, face uncertainty and an unknown future. This study has put forward the question of what are the effects of the symbiotic relationship of a historical anti-Mexican…

Marination and cooking performance of portioned broiler breast fillets with the woody breast condition

USDA-ARS?s Scientific Manuscript database

The woody breast (WB) condition in broiler breast meat negatively influences technological meat quality. However, it is unknown if the WB effects are uniform throughout the Pectoralis major. The objective of this study was to determine the effects of WB on the marination and cooking performance of...

Filtrates and Residues: Qualitative Analysis of Some Transition Metals.

ERIC Educational Resources Information Center

Kilner, Cary

1985-01-01

Describes a qualitative analysis laboratory in which students examine specific precipitates that can be used to identify copper, cobalt, nickel, and iron cations. The objective of the laboratory is to determine which test or sequence of tests unambiguously identifies each cation and to use the results to identify several unknowns. (JN)

Changes of Pain Perception, Autonomic Function, and Endocrine Parameters during Treatment of Anorectic Adolescents

ERIC Educational Resources Information Center

Bar, Karl-Jurgen; Boettger, Silke; Wagner, Gerd; Wilsdorf, Christine; Gerhard, Uwe Jens; Boettger, Michael K.; Blanz, Bernhard; Sauer, Heinrich

2006-01-01

Objectives: The underlying mechanisms of reduced pain perception in anorexia nervosa (AN) are unknown. To gain more insight into the pathology, the authors investigated pain perception, autonomic function, and endocrine parameters before and during successful treatment of adolescent AN patients. Method: Heat pain perception was assessed in 15…

Mystery Powders. [Modified Primary]. Revised. Anchorage School District Elementary Science Program.

ERIC Educational Resources Information Center

Anchorage School District, AK.

This publication provides information and activities for identifying objects using the five senses and process skills including observing, classifying, collecting and interpreting data, inferring, and predicting. Lessons 1 through 3 deal with the identification of an unknown substance and the physical properties of powders. Lessons 4 through 6 are…

40 CFR 63.3400 - What notifications and reports must I submit?

Code of Federal Regulations, 2010 CFR

2010-07-01

... unknown causes. (I) The date of the latest CEMS and CPMS certification or audit. (J) A description of any... control device and you are required to conduct a performance test of the control device. This notification... of the control device determined during the performance test are maintained. Unless EPA objects to...

Self-expressive Dictionary Learning for Dynamic 3D Reconstruction.

PubMed

Zheng, Enliang; Ji, Dinghuang; Dunn, Enrique; Frahm, Jan-Michael

2017-08-22

We target the problem of sparse 3D reconstruction of dynamic objects observed by multiple unsynchronized video cameras with unknown temporal overlap. To this end, we develop a framework to recover the unknown structure without sequencing information across video sequences. Our proposed compressed sensing framework poses the estimation of 3D structure as the problem of dictionary learning, where the dictionary is defined as an aggregation of the temporally varying 3D structures. Given the smooth motion of dynamic objects, we observe any element in the dictionary can be well approximated by a sparse linear combination of other elements in the same dictionary (i.e. self-expression). Our formulation optimizes a biconvex cost function that leverages a compressed sensing formulation and enforces both structural dependency coherence across video streams, as well as motion smoothness across estimates from common video sources. We further analyze the reconstructability of our approach under different capture scenarios, and its comparison and relation to existing methods. Experimental results on large amounts of synthetic data as well as real imagery demonstrate the effectiveness of our approach.

A novel sensitivity-based method for damage detection of structures under unknown periodic excitations

NASA Astrophysics Data System (ADS)

Naseralavi, S. S.; Salajegheh, E.; Fadaee, M. J.; Salajegheh, J.

2014-06-01

This paper presents a technique for damage detection in structures under unknown periodic excitations using the transient displacement response. The method is capable of identifying the damage parameters without finding the input excitations. We first define the concept of displacement space as a linear space in which each point represents displacements of structure under an excitation and initial condition. Roughly speaking, the method is based on the fact that structural displacements under free and forced vibrations are associated with two parallel subspaces in the displacement space. Considering this novel geometrical viewpoint, an equation called kernel parallelization equation (KPE) is derived for damage detection under unknown periodic excitations and a sensitivity-based algorithm for solving KPE is proposed accordingly. The method is evaluated via three case studies under periodic excitations, which confirm the efficiency of the proposed method.

"Did you call me?" 5-month-old infants own name guides their attention.

PubMed

Parise, Eugenio; Friederici, Angela D; Striano, Tricia

2010-12-03

An infant's own name is a unique social cue. Infants are sensitive to their own name by 4 months of age, but whether they use their names as a social cue is unknown. Electroencephalogram (EEG) was measured as infants heard their own name or stranger's names and while looking at novel objects. Event related brain potentials (ERPs) in response to names revealed that infants differentiate their own name from stranger names from the first phoneme. The amplitude of the ERPs to objects indicated that infants attended more to objects after hearing their own names compared to another name. Thus, by 5 months of age infants not only detect their name, but also use it as a social cue to guide their attention to events and objects in the world.

Employing Machine-Learning Methods to Study Young Stellar Objects

NASA Astrophysics Data System (ADS)

Moore, Nicholas

2018-01-01

Vast amounts of data exist in the astronomical data archives, and yet a large number of sources remain unclassified. We developed a multi-wavelength pipeline to classify infrared sources. The pipeline uses supervised machine learning methods to classify objects into the appropriate categories. The program is fed data that is already classified to train it, and is then applied to unknown catalogues. The primary use for such a pipeline is the rapid classification and cataloging of data that would take a much longer time to classify otherwise. While our primary goal is to study young stellar objects (YSOs), the applications extend beyond the scope of this project. We present preliminary results from our analysis and discuss future applications.

Optical Observations of Space Debris

NASA Technical Reports Server (NTRS)

Seitzer, Patrick; Abercromby, Kira; Rodriquez, Heather; Barker, Edwin S.; Kelecy, Thomas

2008-01-01

This viewgraph presentation reviews the use of optical telescopes to observe space debris. .It will present a brief review of how the survey is conducted, and what some of the significant results encompass. The goal is to characterize the population of debris objects at GEO, with emphasis on the faint object population. Because the survey observations extend over a very short arc (5 minutes), a full six parameter orbit can not be determined. Recently we have begun to use a second telescope, the 0.9-m at CTIO, as a chase telescope to do follow-up observations of potential GEO debris candidates found by MODEST. With a long enough sequence of observations, a full six-parameter orbit including eccentricity can be determined. The project has used STK since inception for planning observing sessions based on the distribution of bright cataloged objects and the anti-solar point (to avoid eclipse). Recently, AGI's Orbit Determination Tool Kit (ODTK) has been used to determine orbits, including the effects of solar radiation pressure. Since an unknown fraction of the faint debris at GEO has a high area-to-mass ratio (A/M), the orbits are perturbed significantly by solar radiation. The ODTK analysis results indicate that temporal variations in the solar perturbations, possibly due to debris orientation dynamics, can be estimated in the OD process. Additionally, the best results appear to be achieved when solar forces orthogonal to the object-Sun line are considered. Determining the A/M of individual objects and the distribution of A/M values of a large sample of debris is important to understanding the total population of debris at GEO

An object cue is more effective than a word in ERP-based detection of deception.

PubMed

Cutmore, Tim R H; Djakovic, Tatjana; Kebbell, Mark R; Shum, David H K

2009-03-01

Recent studies of deception have used a form of the guilty knowledge test along with the oddball P300 event-related potential (ERP) to uncover hidden memories. These studies typically have used words as the cuing stimuli. In the present study, a mock crime was enacted by participants to prime their episodic memory and different memory cue types (Words, Pictures of Objects and Faces) were created to investigate their relative efficacy in identifying guilt. A peak-to peak (p-p) P300 response was computed for rare known non-guilty item (target), rare guilty knowledge item (probe) and frequently presented unknown items (irrelevant). Difference in this P300 measure between the probe and irrelevant was the key dependent variable. Object cues were found to be the most effective, particularly at the parietal site. A bootstrap procedure commonly used to detect deception in individual participants by comparing their probe and irrelevant P300 p-p showed the object cues to provide the best discrimination. Furthermore, using all three of the cue types together provided high detection accuracy (94%). These results confirm prior findings on the utility of ERPs for detecting deception. More importantly, they provide support for the hypothesis that direct cueing with a picture of the crime object may be more effective than using a word (consistent with the picture superiority effect reported in the literature). Finally, a face cue (e.g., crime victim) may also provide a useful probe for detection of guilty knowledge but this stimulus form needs to be chosen with due caution.

Somatostatin Signaling in Neuronal Cilia Is Criticalfor Object Recognition Memory

PubMed Central

Einstein, Emily B.; Patterson, Carlyn A.; Hon, Beverly J.; Regan, Kathleen A.; Reddi, Jyoti; Melnikoff, David E.; Mateer, Marcus J.; Schulz, Stefan; Johnson, Brian N.

2010-01-01

Most neurons possess a single, nonmotile cilium that projects out from the cell surface. These microtubule-based organelles are important in brain development and neurogenesis; however, their function in mature neurons is unknown. Cilia express a complement of proteins distinct from other neuronal compartments, one of which is the somatostatin receptor subtype SST3. We show here that SST3 is critical for object recognition memory in mice. sst3 knock-out mice are severely impaired in discriminating novel objects, whereas they retain normal memory for object location. Further, systemic injection of an SST3 antagonist (ACQ090) disrupts recall of familiar objects in wild-type mice. To examine mechanisms of SST3, we tested synaptic plasticity in CA1 hippocampus. Electrically evoked long-term potentiation (LTP) was normal in sst3 knock-out mice, while adenylyl cyclase/cAMP-mediated LTP was impaired. The SST3 antagonist also disrupted cAMP-mediated LTP. Basal cAMP levels in hippocampal lysate were reduced in sst3 knock-out mice compared with wild-type mice, while the forskolin-induced increase in cAMP levels was normal. The SST3 antagonist inhibited forskolin-stimulated cAMP increases, whereas the SST3 agonist L-796,778 increased basal cAMP levels in hippocampal slices but not hippocampal lysate. Our results show that somatostatin signaling in neuronal cilia is critical for recognition memory and suggest that the cAMP pathway is a conserved signaling motif in cilia. Neuronal cilia therefore represent a novel nonsynaptic compartment crucial for signaling involved in a specific form of synaptic plasticity and in novelty detection. PMID:20335466

Haptically Guided Grasping. fMRI Shows Right-Hemisphere Parietal Stimulus Encoding, and Bilateral Dorso-Ventral Parietal Gradients of Object- and Action-Related Processing during Grasp Execution

PubMed Central

Marangon, Mattia; Kubiak, Agnieszka; Króliczak, Gregory

2016-01-01

The neural bases of haptically-guided grasp planning and execution are largely unknown, especially for stimuli having no visual representations. Therefore, we used functional magnetic resonance imaging (fMRI) to monitor brain activity during haptic exploration of novel 3D complex objects, subsequent grasp planning, and the execution of the pre-planned grasps. Haptic object exploration, involving extraction of shape, orientation, and length of the to-be-grasped targets, was associated with the fronto-parietal, temporo-occipital, and insular cortex activity. Yet, only the anterior divisions of the posterior parietal cortex (PPC) of the right hemisphere were significantly more engaged in exploration of complex objects (vs. simple control disks). None of these regions were re-recruited during the planning phase. Even more surprisingly, the left-hemisphere intraparietal, temporal, and occipital areas that were significantly invoked for grasp planning did not show sensitivity to object features. Finally, grasp execution, involving the re-recruitment of the critical right-hemisphere PPC clusters, was also significantly associated with two kinds of bilateral parieto-frontal processes. The first represents transformations of grasp-relevant target features and is linked to the dorso-dorsal (lateral and medial) parieto-frontal networks. The second monitors grasp kinematics and belongs to the ventro-dorsal networks. Indeed, signal modulations associated with these distinct functions follow dorso-ventral gradients, with left aIPS showing significant sensitivity to both target features and the characteristics of the required grasp. Thus, our results from the haptic domain are consistent with the notion that the parietal processing for action guidance reflects primarily transformations from object-related to effector-related coding, and these mechanisms are rather independent of sensory input modality. PMID:26779002

Learning from other people’s fear: amygdala-based social reference learning in social anxiety disorder

PubMed Central

Blair, K. S.; Otero, M.; Teng, C.; Geraci, M.; Lewis, E.; Hollon, N.; Blair, R. J. R.; Ernst, Monique; Grillon, C.; Pine, D. S.

2016-01-01

Background Social anxiety disorder involves fear of social objects or situations. Social referencing may play an important role in the acquisition of this fear and could be a key determinant in future biomarkers and treatment pathways. However, the neural underpinnings mediating such learning in social anxiety are unknown. Using event-related functional magnetic resonance imaging, we examined social reference learning in social anxiety disorder. Specifically, would patients with the disorder show increased amygdala activity during social reference learning, and further, following social reference learning, show particularly increased response to objects associated with other people’s negative reactions? Method A total of 32 unmedicated patients with social anxiety disorder and 22 age-, intelligence quotient- and gender-matched healthy individuals responded to objects that had become associated with others’ fearful, angry, happy or neutral reactions. Results During the social reference learning phase, a significant group × social context interaction revealed that, relative to the comparison group, the social anxiety group showed a significantly greater response in the amygdala, as well as rostral, dorsomedial and lateral frontal and parietal cortices during the social, relative to non-social, referencing trials. In addition, during the object test phase, relative to the comparison group, the social anxiety group showed increased bilateral amygdala activation to objects associated with others’ fearful reactions, and a trend towards decreased amygdala activation to objects associated with others’ happy and neutral reactions. Conclusions These results suggest perturbed observational learning in social anxiety disorder. In addition, they further implicate the amygdala and dorsomedial prefrontal cortex in the disorder, and underscore their importance in future biomarker developments. PMID:27476529

Haptically Guided Grasping. fMRI Shows Right-Hemisphere Parietal Stimulus Encoding, and Bilateral Dorso-Ventral Parietal Gradients of Object- and Action-Related Processing during Grasp Execution.

PubMed

Marangon, Mattia; Kubiak, Agnieszka; Króliczak, Gregory

2015-01-01

The neural bases of haptically-guided grasp planning and execution are largely unknown, especially for stimuli having no visual representations. Therefore, we used functional magnetic resonance imaging (fMRI) to monitor brain activity during haptic exploration of novel 3D complex objects, subsequent grasp planning, and the execution of the pre-planned grasps. Haptic object exploration, involving extraction of shape, orientation, and length of the to-be-grasped targets, was associated with the fronto-parietal, temporo-occipital, and insular cortex activity. Yet, only the anterior divisions of the posterior parietal cortex (PPC) of the right hemisphere were significantly more engaged in exploration of complex objects (vs. simple control disks). None of these regions were re-recruited during the planning phase. Even more surprisingly, the left-hemisphere intraparietal, temporal, and occipital areas that were significantly invoked for grasp planning did not show sensitivity to object features. Finally, grasp execution, involving the re-recruitment of the critical right-hemisphere PPC clusters, was also significantly associated with two kinds of bilateral parieto-frontal processes. The first represents transformations of grasp-relevant target features and is linked to the dorso-dorsal (lateral and medial) parieto-frontal networks. The second monitors grasp kinematics and belongs to the ventro-dorsal networks. Indeed, signal modulations associated with these distinct functions follow dorso-ventral gradients, with left aIPS showing significant sensitivity to both target features and the characteristics of the required grasp. Thus, our results from the haptic domain are consistent with the notion that the parietal processing for action guidance reflects primarily transformations from object-related to effector-related coding, and these mechanisms are rather independent of sensory input modality.

Automated Classification of ROSAT Sources Using Heterogeneous Multiwavelength Source Catalogs

NASA Technical Reports Server (NTRS)

McGlynn, Thomas; Suchkov, A. A.; Winter, E. L.; Hanisch, R. J.; White, R. L.; Ochsenbein, F.; Derriere, S.; Voges, W.; Corcoran, M. F.

2004-01-01

We describe an on-line system for automated classification of X-ray sources, ClassX, and present preliminary results of classification of the three major catalogs of ROSAT sources, RASS BSC, RASS FSC, and WGACAT, into six class categories: stars, white dwarfs, X-ray binaries, galaxies, AGNs, and clusters of galaxies. ClassX is based on a machine learning technology. It represents a system of classifiers, each classifier consisting of a considerable number of oblique decision trees. These trees are built as the classifier is 'trained' to recognize various classes of objects using a training sample of sources of known object types. Each source is characterized by a preselected set of parameters, or attributes; the same set is then used as the classifier conducts classification of sources of unknown identity. The ClassX pipeline features an automatic search for X-ray source counterparts among heterogeneous data sets in on-line data archives using Virtual Observatory protocols; it retrieves from those archives all the attributes required by the selected classifier and inputs them to the classifier. The user input to ClassX is typically a file with target coordinates, optionally complemented with target IDs. The output contains the class name, attributes, and class probabilities for all classified targets. We discuss ways to characterize and assess the classifier quality and performance and present the respective validation procedures. Based on both internal and external validation, we conclude that the ClassX classifiers yield reasonable and reliable classifications for ROSAT sources and have the potential to broaden class representation significantly for rare object types.

Validity of Walk Score® as a measure of neighborhood walkability in Japan.

PubMed

Koohsari, Mohammad Javad; Sugiyama, Takemi; Hanibuchi, Tomoya; Shibata, Ai; Ishii, Kaori; Liao, Yung; Oka, Koichiro

2018-03-01

Objective measures of environmental attributes have been used to understand how neighborhood environments relate to physical activity. However, this method relies on detailed spatial data, which are often not easily available. Walk Score® is a free, publicly available web-based tool that shows how walkable a given location is based on objectively-derived proximity to several types of local destinations and street connectivity. To date, several studies have tested the concurrent validity of Walk Score as a measure of neighborhood walkability in the USA and Canada. However, it is unknown whether Walk Score is a valid measure in other regions. The current study examined how Walk Score is correlated with objectively-derived attributes of neighborhood walkability, for residential addresses in Japan. Walk Scores were obtained for 1072 residential addresses in urban and rural areas in Japan. Five environmental attributes (residential density, intersection density, number of local destinations, sidewalk availability, and access to public transportation) were calculated using geographic information systems for each address. Pearson's correlation coefficients between Walk Score and these environmental attributes were calculated (conducted in May 2017). Significant positive correlations were observed between Walk Score and environmental attributes relevant to walking. Walk Score was most closely associated with intersection density ( r  = 0.82) and with the number of local destinations ( r  = 0.77). Walk Score appears to be a valid measure of neighborhood walkability in Japan. Walk Score will allow urban designers and public health practitioners to identify walkability of local areas without relying on detailed geographic data.

Electromagnetic spectrum management system

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

Seastrand, Douglas R.

A system for transmitting a wireless countermeasure signal to disrupt third party communications is disclosed that include an antenna configured to receive wireless signals and transmit wireless counter measure signals such that the wireless countermeasure signals are responsive to the received wireless signals. A receiver processes the received wireless signals to create processed received signal data while a spectrum control module subtracts known source signal data from the processed received signal data to generate unknown source signal data. The unknown source signal data is based on unknown wireless signals, such as enemy signals. A transmitter is configured to process themore » unknown source signal data to create countermeasure signals and transmit a wireless countermeasure signal over the first antenna or a second antenna to thereby interfere with the unknown wireless signals.« less

Cooperative Coevolution with Formula-Based Variable Grouping for Large-Scale Global Optimization.

PubMed

Wang, Yuping; Liu, Haiyan; Wei, Fei; Zong, Tingting; Li, Xiaodong

2017-08-09

For a large-scale global optimization (LSGO) problem, divide-and-conquer is usually considered an effective strategy to decompose the problem into smaller subproblems, each of which can then be solved individually. Among these decomposition methods, variable grouping is shown to be promising in recent years. Existing variable grouping methods usually assume the problem to be black-box (i.e., assuming that an analytical model of the objective function is unknown), and they attempt to learn appropriate variable grouping that would allow for a better decomposition of the problem. In such cases, these variable grouping methods do not make a direct use of the formula of the objective function. However, it can be argued that many real-world problems are white-box problems, that is, the formulas of objective functions are often known a priori. These formulas of the objective functions provide rich information which can then be used to design an effective variable group method. In this article, a formula-based grouping strategy (FBG) for white-box problems is first proposed. It groups variables directly via the formula of an objective function which usually consists of a finite number of operations (i.e., four arithmetic operations "[Formula: see text]", "[Formula: see text]", "[Formula: see text]", "[Formula: see text]" and composite operations of basic elementary functions). In FBG, the operations are classified into two classes: one resulting in nonseparable variables, and the other resulting in separable variables. In FBG, variables can be automatically grouped into a suitable number of non-interacting subcomponents, with variables in each subcomponent being interdependent. FBG can easily be applied to any white-box problem and can be integrated into a cooperative coevolution framework. Based on FBG, a novel cooperative coevolution algorithm with formula-based variable grouping (so-called CCF) is proposed in this article for decomposing a large-scale white-box problem into several smaller subproblems and optimizing them respectively. To further enhance the efficiency of CCF, a new local search scheme is designed to improve the solution quality. To verify the efficiency of CCF, experiments are conducted on the standard LSGO benchmark suites of CEC'2008, CEC'2010, CEC'2013, and a real-world problem. Our results suggest that the performance of CCF is very competitive when compared with those of the state-of-the-art LSGO algorithms.

Robust Fault Detection for Switched Fuzzy Systems With Unknown Input.

PubMed

Han, Jian; Zhang, Huaguang; Wang, Yingchun; Sun, Xun

2017-10-03

This paper investigates the fault detection problem for a class of switched nonlinear systems in the T-S fuzzy framework. The unknown input is considered in the systems. A novel fault detection unknown input observer design method is proposed. Based on the proposed observer, the unknown input can be removed from the fault detection residual. The weighted H∞ performance level is considered to ensure the robustness. In addition, the weighted H₋ performance level is introduced, which can increase the sensibility of the proposed detection method. To verify the proposed scheme, a numerical simulation example and an electromechanical system simulation example are provided at the end of this paper.

Genomic and genotyping characterization of haplotype-based polymorphic microsatellites in Prunus

USDA-ARS?s Scientific Manuscript database

Efficient utilization of microsatellites in genetic studies remains impeded largely due to the unknown status of their primer reliability, chromosomal location, and allele polymorphism. Discovery and characterization of microsatellite polymorphisms in a taxon will disclose the unknowns and gain new ...

Photocopy of photograph (from NBPPNSY, CSF530663) photographer unknown, June 16, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Photocopy of photograph (from NBP-PNSY, CSF-530-6-63) photographer unknown, June 16, 1963 view of a blade for a variable-pitch propeller positioned for finish machining. - Naval Base Philadelphia-Philadelphia Naval Shipyard, League Island, Philadelphia, Philadelphia County, PA

Contemporary State of the Elbrus Volcanic Center (The Northern Caucasus)

NASA Astrophysics Data System (ADS)

Milyukov, Vadim; Rogozhin, Eugeny; Gorbatikov, Andrey; Mironov, Alexey; Myasnikov, Andrey; Stepanova, Marina

2018-05-01

The Elbrus volcanic center is located in southern Russia on the northern slope of the main ridge of the Greater Caucasus. Current classifications define Elbrus as a dormant volcano that could become active even after millennia of quiescence. In this study, we use two new geophysical methods to assess the contemporary state of the Elbrus volcano. The first method is based on an evaluation of parameters of resonant modes "reemitted" by the resonant structure (i.e., volcanic chamber) in response to the excitation of a seismic impact and recorded by a precise laser interferometer-strainmeter. The second method is based on low-frequency microseismic sounding and allows determination of the deep structure of complicated geological objects. Our study locates the magma chamber at depths of 1-8 km and extended magma source at depths of 15-40 km beneath the Elbrus eastern summit. An unknown magmatic structure, comparable to the Elbrus magmatic structure but currently much colder, was also identified 50 km from Mt. Elbrus. Based on our analysis, we assess the Elbrus volcano to be currently in a quasi-stable state of thermodynamic equilibrium.

A new numerical treatment based on Lucas polynomials for 1D and 2D sinh-Gordon equation

NASA Astrophysics Data System (ADS)

Oruç, Ömer

2018-04-01

In this paper, a new mixed method based on Lucas and Fibonacci polynomials is developed for numerical solutions of 1D and 2D sinh-Gordon equations. Firstly time variable discretized by central finite difference and then unknown function and its derivatives are expanded to Lucas series. With the help of these series expansion and Fibonacci polynomials, matrices for differentiation are derived. With this approach, finding the solution of sinh-Gordon equation transformed to finding the solution of an algebraic system of equations. Lucas series coefficients are acquired by solving this system of algebraic equations. Then by plugginging these coefficients into Lucas series expansion numerical solutions can be obtained consecutively. The main objective of this paper is to demonstrate that Lucas polynomial based method is convenient for 1D and 2D nonlinear problems. By calculating L2 and L∞ error norms of some 1D and 2D test problems efficiency and performance of the proposed method is monitored. Acquired accurate results confirm the applicability of the method.

Approximately adaptive neural cooperative control for nonlinear multiagent systems with performance guarantee

NASA Astrophysics Data System (ADS)

Wang, Jing; Yang, Tianyu; Staskevich, Gennady; Abbe, Brian

2017-04-01

This paper studies the cooperative control problem for a class of multiagent dynamical systems with partially unknown nonlinear system dynamics. In particular, the control objective is to solve the state consensus problem for multiagent systems based on the minimisation of certain cost functions for individual agents. Under the assumption that there exist admissible cooperative controls for such class of multiagent systems, the formulated problem is solved through finding the optimal cooperative control using the approximate dynamic programming and reinforcement learning approach. With the aid of neural network parameterisation and online adaptive learning, our method renders a practically implementable approximately adaptive neural cooperative control for multiagent systems. Specifically, based on the Bellman's principle of optimality, the Hamilton-Jacobi-Bellman (HJB) equation for multiagent systems is first derived. We then propose an approximately adaptive policy iteration algorithm for multiagent cooperative control based on neural network approximation of the value functions. The convergence of the proposed algorithm is rigorously proved using the contraction mapping method. The simulation results are included to validate the effectiveness of the proposed algorithm.

Assessing the performance of a motion tracking system based on optical joint transform correlation

NASA Astrophysics Data System (ADS)

Elbouz, M.; Alfalou, A.; Brosseau, C.; Ben Haj Yahia, N.; Alam, M. S.

2015-08-01

We present an optimized system specially designed for the tracking and recognition of moving subjects in a confined environment (such as an elderly remaining at home). In the first step of our study, we use a VanderLugt correlator (VLC) with an adapted pre-processing treatment of the input plane and a postprocessing of the correlation plane via a nonlinear function allowing us to make a robust decision. The second step is based on an optical joint transform correlation (JTC)-based system (NZ-NL-correlation JTC) for achieving improved detection and tracking of moving persons in a confined space. The proposed system has been found to have significantly superior discrimination and robustness capabilities allowing to detect an unknown target in an input scene and to determine the target's trajectory when this target is in motion. This system offers robust tracking performance of a moving target in several scenarios, such as rotational variation of input faces. Test results obtained using various real life video sequences show that the proposed system is particularly suitable for real-time detection and tracking of moving objects.

Point-spread function reconstruction in ground-based astronomy by l(1)-l(p) model.

PubMed

Chan, Raymond H; Yuan, Xiaoming; Zhang, Wenxing

2012-11-01

In ground-based astronomy, images of objects in outer space are acquired via ground-based telescopes. However, the imaging system is generally interfered by atmospheric turbulence, and hence images so acquired are blurred with unknown point-spread function (PSF). To restore the observed images, the wavefront of light at the telescope's aperture is utilized to derive the PSF. A model with the Tikhonov regularization has been proposed to find the high-resolution phase gradients by solving a least-squares system. Here we propose the l(1)-l(p) (p=1, 2) model for reconstructing the phase gradients. This model can provide sharper edges in the gradients while removing noise. The minimization models can easily be solved by the Douglas-Rachford alternating direction method of a multiplier, and the convergence rate is readily established. Numerical results are given to illustrate that the model can give better phase gradients and hence a more accurate PSF. As a result, the restored images are much more accurate when compared to the traditional Tikhonov regularization model.

Muscle strengthening activity associates with reduced all-cause mortality in COPD.

PubMed

Loprinzi, Paul D; Sng, Eveleen; Walker, Jerome F

2017-06-01

Objective Emerging research suggests that aerobic-based physical activity may help to promote survival among chronic obstructive pulmonary disease patients. However, the extent to which engagement in resistance training on survival among chronic obstructive pulmonary disease patients is relatively unknown. Therefore, the purpose of this study was to examine the independent associations of muscle strengthening activities on all-cause mortality among a national sample of U.S. adults with chronic obstructive pulmonary disease. We hypothesize that muscle strengthening activities will be inversely associated with all-cause mortality. Methods Data from the 2003-2006 NHANES were employed, with follow-up through 2011. Aerobic-based physical activity was objectively measured via accelerometry, muscle strengthening activities engagement was assessed via self-report, and chronic obstructive pulmonary disease was assessed via physician-diagnosis. Results Analysis included 385 adults (20 + yrs) with chronic obstructive pulmonary disease, who represent 13.3 million chronic obstructive pulmonary disease patients in the USA. The median follow-up period was 78 months (IQR=64-90), with 82 chronic obstructive pulmonary disease patients dying during this period. For a two muscle strengthening activity sessions/week increase (consistent with national guidelines), chronic obstructive pulmonary disease patients had a 29% reduced risk of all-cause mortality (HR=0.71; 95% CI: 0.51-0.99; P = 0.04). Conclusion Participation in muscle strengthening activities, independent of aerobic-based physical activity and other potential confounders, is associated with greater survival among chronic obstructive pulmonary disease patients.

The development of adaptive decision making: Recognition-based inference in children and adolescents.

PubMed

Horn, Sebastian S; Ruggeri, Azzurra; Pachur, Thorsten

2016-09-01

Judgments about objects in the world are often based on probabilistic information (or cues). A frugal judgment strategy that utilizes memory (i.e., the ability to discriminate between known and unknown objects) as a cue for inference is the recognition heuristic (RH). The usefulness of the RH depends on the structure of the environment, particularly the predictive power (validity) of recognition. Little is known about developmental differences in use of the RH. In this study, the authors examined (a) to what extent children and adolescents recruit the RH when making judgments, and (b) around what age adaptive use of the RH emerges. Primary schoolchildren (M = 9 years), younger adolescents (M = 12 years), and older adolescents (M = 17 years) made comparative judgments in task environments with either high or low recognition validity. Reliance on the RH was measured with a hierarchical multinomial model. Results indicated that primary schoolchildren already made systematic use of the RH. However, only older adolescents adaptively adjusted their strategy use between environments and were better able to discriminate between situations in which the RH led to correct versus incorrect inferences. These findings suggest that the use of simple heuristics does not progress unidirectionally across development but strongly depends on the task environment, in line with the perspective of ecological rationality. Moreover, adaptive heuristic inference seems to require experience and a developed base of domain knowledge. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Automated Detection of Small Bodies by Space Based Observation

NASA Astrophysics Data System (ADS)

Bidstrup, P. R.; Grillmayer, G.; Andersen, A. C.; Haack, H.; Jorgensen, J. L.

The number of known comets and asteroids is increasing every year. Up till now this number is including approximately 250,000 of the largest minor planets, as they are usually referred. These discoveries are due to the Earth-based observation which has intensified over the previous decades. Additionally larger telescopes and arrays of telescopes are being used for exploring our Solar System. It is believed that all near- Earth and Main-Belt asteroids of diameters above 10 to 30 km have been discovered, leaving these groups of objects as observationally complete. However, the cataloguing of smaller bodies is incomplete as only a very small fraction of the expected number has been discovered. It is estimated that approximately 1010 main belt asteroids in the size range 1 m to 1 km are too faint to be observed using Earth-based telescopes. In order to observe these small bodies, space-based search must be initiated to remove atmospheric disturbances and to minimize the distance to the asteroids and thereby minimising the requirement for long camera integration times. A new method of space-based detection of moving non-stellar objects is currently being developed utilising the Advanced Stellar Compass (ASC) built for spacecraft attitude determination by Ørsted, Danish Technical University. The ASC serves as a backbone technology in the project as it is capable of fully automated distinction of known and unknown celestial objects. By only processing objects of particular interest, i.e. moving objects, it will be possible to discover small bodies with a minimum of ground control, with the ultimate ambition of a fully automated space search probe. Currently, the ASC is being mounted on the Flying Laptop satellite of the Institute of Space Systems, Universität Stuttgart. It will, after a launch into a low Earth polar orbit in 2008, test the detection method with the ASC equipment that already had significant in-flight experience. A future use of the ASC based automated detection of small bodies is currently on a preliminary stage and known as the Bering project - a deep space survey to the asteroid Main-Belt. With a successful detection method, the Bering mission is expected to discover approximately 6 new small objects per day and 1 will thus during the course of a few years discover 5,000-10,000 new sub-kilometer asteroids. Discovery of new small bodies can: 1) Provide further links between groups of meteorites. 2) Constrain the cratering rate at planetary surfaces and thus allow significantly improved cratering ages for terrains on Mars and other planets. 3) Help determine processes that transfer small asteroids from orbits in the asteroid Main-Belt to the inner Solar System. 2

A novel procedure for detecting and focusing moving objects with SAR based on the Wigner-Ville distribution

NASA Astrophysics Data System (ADS)

Barbarossa, S.; Farina, A.

A novel scheme for detecting moving targets with synthetic aperture radar (SAR) is presented. The proposed approach is based on the use of the Wigner-Ville distribution (WVD) for simultaneously detecting moving targets and estimating their motion kinematic parameters. The estimation plays a key role for focusing the target and correctly locating it with respect to the stationary background. The method has a number of advantages: (i) the detection is efficiently performed on the samples in the time-frequency domain, provided the WVD, without resorting to the use of a bank of filters, each one matched to possible values of the unknown target motion parameters; (ii) the estimation of the target motion parameters can be done on the same time-frequency domain by locating the line where the maximum energy of the WVD is concentrated. A validation of the approach is given by both analytical and simulation means. In addition, the estimation of the target kinematic parameters and the corresponding image focusing are also demonstrated.

Multilevel fast multipole method based on a potential formulation for 3D electromagnetic scattering problems.

PubMed

Fall, Mandiaye; Boutami, Salim; Glière, Alain; Stout, Brian; Hazart, Jerome

2013-06-01

A combination of the multilevel fast multipole method (MLFMM) and boundary element method (BEM) can solve large scale photonics problems of arbitrary geometry. Here, MLFMM-BEM algorithm based on a scalar and vector potential formulation, instead of the more conventional electric and magnetic field formulations, is described. The method can deal with multiple lossy or lossless dielectric objects of arbitrary geometry, be they nested, in contact, or dispersed. Several examples are used to demonstrate that this method is able to efficiently handle 3D photonic scatterers involving large numbers of unknowns. Absorption, scattering, and extinction efficiencies of gold nanoparticle spheres, calculated by the MLFMM, are compared with Mie's theory. MLFMM calculations of the bistatic radar cross section (RCS) of a gold sphere near the plasmon resonance and of a silica coated gold sphere are also compared with Mie theory predictions. Finally, the bistatic RCS of a nanoparticle gold-silver heterodimer calculated with MLFMM is compared with unmodified BEM calculations.

Stable Local Volatility Calibration Using Kernel Splines

NASA Astrophysics Data System (ADS)

Coleman, Thomas F.; Li, Yuying; Wang, Cheng

2010-09-01

We propose an optimization formulation using L1 norm to ensure accuracy and stability in calibrating a local volatility function for option pricing. Using a regularization parameter, the proposed objective function balances the calibration accuracy with the model complexity. Motivated by the support vector machine learning, the unknown local volatility function is represented by a kernel function generating splines and the model complexity is controlled by minimizing the 1-norm of the kernel coefficient vector. In the context of the support vector regression for function estimation based on a finite set of observations, this corresponds to minimizing the number of support vectors for predictability. We illustrate the ability of the proposed approach to reconstruct the local volatility function in a synthetic market. In addition, based on S&P 500 market index option data, we demonstrate that the calibrated local volatility surface is simple and resembles the observed implied volatility surface in shape. Stability is illustrated by calibrating local volatility functions using market option data from different dates.

Causal Inference and Explaining Away in a Spiking Network

PubMed Central

Moreno-Bote, Rubén; Drugowitsch, Jan

2015-01-01

While the brain uses spiking neurons for communication, theoretical research on brain computations has mostly focused on non-spiking networks. The nature of spike-based algorithms that achieve complex computations, such as object probabilistic inference, is largely unknown. Here we demonstrate that a family of high-dimensional quadratic optimization problems with non-negativity constraints can be solved exactly and efficiently by a network of spiking neurons. The network naturally imposes the non-negativity of causal contributions that is fundamental to causal inference, and uses simple operations, such as linear synapses with realistic time constants, and neural spike generation and reset non-linearities. The network infers the set of most likely causes from an observation using explaining away, which is dynamically implemented by spike-based, tuned inhibition. The algorithm performs remarkably well even when the network intrinsically generates variable spike trains, the timing of spikes is scrambled by external sources of noise, or the network is mistuned. This type of network might underlie tasks such as odor identification and classification. PMID:26621426

Causal Inference and Explaining Away in a Spiking Network.

PubMed

Moreno-Bote, Rubén; Drugowitsch, Jan

2015-12-01

While the brain uses spiking neurons for communication, theoretical research on brain computations has mostly focused on non-spiking networks. The nature of spike-based algorithms that achieve complex computations, such as object probabilistic inference, is largely unknown. Here we demonstrate that a family of high-dimensional quadratic optimization problems with non-negativity constraints can be solved exactly and efficiently by a network of spiking neurons. The network naturally imposes the non-negativity of causal contributions that is fundamental to causal inference, and uses simple operations, such as linear synapses with realistic time constants, and neural spike generation and reset non-linearities. The network infers the set of most likely causes from an observation using explaining away, which is dynamically implemented by spike-based, tuned inhibition. The algorithm performs remarkably well even when the network intrinsically generates variable spike trains, the timing of spikes is scrambled by external sources of noise, or the network is mistuned. This type of network might underlie tasks such as odor identification and classification.

Hip Squeaking after Ceramic-on-ceramic Total Hip Arthroplasty

PubMed Central

Wu, Guo-Liang; Zhu, Wei; Zhao, Yan; Ma, Qi; Weng, Xi-Sheng

2016-01-01

Objective: The present study aimed to review the characteristics and influencing factors of squeaking after ceramic-on-ceramic (CoC) total hip arthroplasty (THA) and to analyze the possible mechanisms of the audible noise. Data Sources: The data analyzed in this review were based on articles from PubMed and Web of Science. Study Selection: The articles selected for review were original articles and reviews found based on the following search terms: “total hip arthroplasty”, “ceramic-on-ceramic”, “hip squeaking”, and “hip noise.” Results: The mechanism of the squeaking remains unknown. The possible explanations included stripe wear, edge loading, a third body, fracture of the ceramic liner, and resonance of the prosthesis components. Squeaking occurrence is influenced by patient, surgical, and implant factors. Conclusions: Most studies indicated that squeaking after CoC THA was the consequence of increasing wear or impingement, caused by prosthesis design, patient characteristics, or surgical factors. However, as conflicts exist among different articles, the major reasons for the squeaking remain to be identified. PMID:27453238

Myoanatomy of the velvet worm leg revealed by laboratory-based nanofocus X-ray source tomography.

PubMed

Müller, Mark; de Sena Oliveira, Ivo; Allner, Sebastian; Ferstl, Simone; Bidola, Pidassa; Mechlem, Korbinian; Fehringer, Andreas; Hehn, Lorenz; Dierolf, Martin; Achterhold, Klaus; Gleich, Bernhard; Hammel, Jörg U; Jahn, Henry; Mayer, Georg; Pfeiffer, Franz

2017-11-21

X-ray computed tomography (CT) is a powerful noninvasive technique for investigating the inner structure of objects and organisms. However, the resolution of laboratory CT systems is typically limited to the micrometer range. In this paper, we present a table-top nanoCT system in conjunction with standard processing tools that is able to routinely reach resolutions down to 100 nm without using X-ray optics. We demonstrate its potential for biological investigations by imaging a walking appendage of Euperipatoides rowelli , a representative of Onychophora-an invertebrate group pivotal for understanding animal evolution. Comparative analyses proved that the nanoCT can depict the external morphology of the limb with an image quality similar to scanning electron microscopy, while simultaneously visualizing internal muscular structures at higher resolutions than confocal laser scanning microscopy. The obtained nanoCT data revealed hitherto unknown aspects of the onychophoran limb musculature, enabling the 3D reconstruction of individual muscle fibers, which was previously impossible using any laboratory-based imaging technique.

Terahertz imaging and tomography as efficient instruments for testing polymer additive manufacturing objects.

PubMed

Perraud, J B; Obaton, A F; Bou-Sleiman, J; Recur, B; Balacey, H; Darracq, F; Guillet, J P; Mounaix, P

2016-05-01

Additive manufacturing (AM) technology is not only used to make 3D objects but also for rapid prototyping. In industry and laboratories, quality controls for these objects are necessary though difficult to implement compared to classical methods of fabrication because the layer-by-layer printing allows for very complex object manufacturing that is unachievable with standard tools. Furthermore, AM can induce unknown or unexpected defects. Consequently, we demonstrate terahertz (THz) imaging as an innovative method for 2D inspection of polymer materials. Moreover, THz tomography may be considered as an alternative to x-ray tomography and cheaper 3D imaging for routine control. This paper proposes an experimental study of 3D polymer objects obtained by additive manufacturing techniques. This approach allows us to characterize defects and to control dimensions by volumetric measurements on 3D data reconstructed by tomography.

Multimodal, high-dimensional, model-based, Bayesian inverse problems with applications in biomechanics

NASA Astrophysics Data System (ADS)

Franck, I. M.; Koutsourelakis, P. S.

2017-01-01

This paper is concerned with the numerical solution of model-based, Bayesian inverse problems. We are particularly interested in cases where the cost of each likelihood evaluation (forward-model call) is expensive and the number of unknown (latent) variables is high. This is the setting in many problems in computational physics where forward models with nonlinear PDEs are used and the parameters to be calibrated involve spatio-temporarily varying coefficients, which upon discretization give rise to a high-dimensional vector of unknowns. One of the consequences of the well-documented ill-posedness of inverse problems is the possibility of multiple solutions. While such information is contained in the posterior density in Bayesian formulations, the discovery of a single mode, let alone multiple, poses a formidable computational task. The goal of the present paper is two-fold. On one hand, we propose approximate, adaptive inference strategies using mixture densities to capture multi-modal posteriors. On the other, we extend our work in [1] with regard to effective dimensionality reduction techniques that reveal low-dimensional subspaces where the posterior variance is mostly concentrated. We validate the proposed model by employing Importance Sampling which confirms that the bias introduced is small and can be efficiently corrected if the analyst wishes to do so. We demonstrate the performance of the proposed strategy in nonlinear elastography where the identification of the mechanical properties of biological materials can inform non-invasive, medical diagnosis. The discovery of multiple modes (solutions) in such problems is critical in achieving the diagnostic objectives.

Childhood exposure to green space - A novel risk-decreasing mechanism for schizophrenia?

PubMed

Engemann, Kristine; Pedersen, Carsten Bøcker; Arge, Lars; Tsirogiannis, Constantinos; Mortensen, Preben Bo; Svenning, Jens-Christian

2018-03-21

Schizophrenia risk has been linked to urbanization, but the underlying mechanism remains unknown. Green space is hypothesized to positively influence mental health and might mediate risk of schizophrenia by mitigating noise and particle pollution exposure, stress relief, or other unknown mechanisms. The objectives for this study were to determine if green space are associated with schizophrenia risk, and if different measures of green space associate differently with risk. We used satellite data from the Landsat program to quantify green space in a new data set for Denmark at 30×30m resolution for the years 1985-2013. The effect of green space at different ages and within different distances from each person's place of residence on schizophrenia risk was estimated using Cox regression on a very large longitudinal population-based sample of the Danish population (943,027 persons). Living at the lowest amount of green space was associated with a 1.52-fold increased risk of developing schizophrenia compared to persons living at the highest level of green space. This association remained after adjusting for known risk factors for schizophrenia: urbanization, age, sex, and socioeconomic status. The strongest protective association was observed during the earliest childhood years and closest to place of residence. This is the first nationwide population-based study to demonstrate a protective association between green space during childhood and schizophrenia risk; suggesting limited green space as a novel environmental risk factor for schizophrenia. This study supports findings from other studies highlighting positive effects of exposure to natural environments for human health. Copyright © 2018 Elsevier B.V. All rights reserved.

Improved space object detection using short-exposure image data with daylight background.

PubMed

Becker, David; Cain, Stephen

2018-05-10

Space object detection is of great importance in the highly dependent yet competitive and congested space domain. The detection algorithms employed play a crucial role in fulfilling the detection component in the space situational awareness mission to detect, track, characterize, and catalog unknown space objects. Many current space detection algorithms use a matched filter or a spatial correlator on long-exposure data to make a detection decision at a single pixel point of a spatial image based on the assumption that the data follow a Gaussian distribution. Long-exposure imaging is critical to detection performance in these algorithms; however, for imaging under daylight conditions, it becomes necessary to create a long-exposure image as the sum of many short-exposure images. This paper explores the potential for increasing detection capabilities for small and dim space objects in a stack of short-exposure images dominated by a bright background. The algorithm proposed in this paper improves the traditional stack and average method of forming a long-exposure image by selectively removing short-exposure frames of data that do not positively contribute to the overall signal-to-noise ratio of the averaged image. The performance of the algorithm is compared to a traditional matched filter detector using data generated in MATLAB as well as laboratory-collected data. The results are illustrated on a receiver operating characteristic curve to highlight the increased probability of detection associated with the proposed algorithm.

Photogrammetric Analysis of Historical Image Repositories for Virtual Reconstruction in the Field of Digital Humanities

NASA Astrophysics Data System (ADS)

Maiwald, F.; Vietze, T.; Schneider, D.; Henze, F.; Münster, S.; Niebling, F.

2017-02-01

Historical photographs contain high density of information and are of great importance as sources in humanities research. In addition to the semantic indexing of historical images based on metadata, it is also possible to reconstruct geometric information about the depicted objects or the camera position at the time of the recording by employing photogrammetric methods. The approach presented here is intended to investigate (semi-) automated photogrammetric reconstruction methods for heterogeneous collections of historical (city) photographs and photographic documentation for the use in the humanities, urban research and history sciences. From a photogrammetric point of view, these images are mostly digitized photographs. For a photogrammetric evaluation, therefore, the characteristics of scanned analog images with mostly unknown camera geometry, missing or minimal object information and low radiometric and geometric resolution have to be considered. In addition, these photographs have not been created specifically for documentation purposes and so the focus of these images is often not on the object to be evaluated. The image repositories must therefore be subjected to a preprocessing analysis of their photogrammetric usability. Investigations are carried out on the basis of a repository containing historical images of the Kronentor ("crown gate") of the Dresden Zwinger. The initial step was to assess the quality and condition of available images determining their appropriateness for generating three-dimensional point clouds from historical photos using a structure-from-motion evaluation (SfM). Then, the generated point clouds were assessed by comparing them with current measurement data of the same object.

Multiple object tracking with non-unique data-to-object association via generalized hypothesis testing. [tracking several aircraft near each other or ships at sea

NASA Technical Reports Server (NTRS)

Porter, D. W.; Lefler, R. M.

1979-01-01

A generalized hypothesis testing approach is applied to the problem of tracking several objects where several different associations of data with objects are possible. Such problems occur, for instance, when attempting to distinctly track several aircraft maneuvering near each other or when tracking ships at sea. Conceptually, the problem is solved by first, associating data with objects in a statistically reasonable fashion and then, tracking with a bank of Kalman filters. The objects are assumed to have motion characterized by a fixed but unknown deterministic portion plus a random process portion modeled by a shaping filter. For example, the object might be assumed to have a mean straight line path about which it maneuvers in a random manner. Several hypothesized associations of data with objects are possible because of ambiguity as to which object the data comes from, false alarm/detection errors, and possible uncertainty in the number of objects being tracked. The statistical likelihood function is computed for each possible hypothesized association of data with objects. Then the generalized likelihood is computed by maximizing the likelihood over parameters that define the deterministic motion of the object.

Qualitative and quantitative detection of T7 bacteriophages using paper based sandwich ELISA.

PubMed

Khan, Mohidus Samad; Pande, Tripti; van de Ven, Theo G M

2015-08-01

Viruses cause many infectious diseases and consequently epidemic health threats. Paper based diagnostics and filters can offer attractive options for detecting and deactivating pathogens. However, due to their infectious characteristics, virus detection using paper diagnostics is more challenging compared to the detection of bacteria, enzymes, DNA or antigens. The major objective of this study was to prepare reliable, degradable and low cost paper diagnostics to detect viruses, without using sophisticated optical or microfluidic analytical instruments. T7 bacteriophage was used as a model virus. A paper based sandwich ELISA technique was developed to detect and quantify the T7 phages in solution. The paper based sandwich ELISA detected T7 phage concentrations as low as 100 pfu/mL to as high as 10(9) pfu/mL. The compatibility of paper based sandwich ELISA with the conventional titre count was tested using T7 phage solutions of unknown concentrations. The paper based sandwich ELISA technique is faster and economical compared to the traditional detection techniques. Therefore, with proper calibration and right reagents, and by following the biosafety regulations, the paper based technique can be said to be compatible and economical to the sophisticated laboratory diagnostic techniques applied to detect pathogenic viruses and other microorganisms. Copyright © 2015 Elsevier B.V. All rights reserved.

Ultra-wideband impedance sensor

DOEpatents

McEwan, Thomas E.

1999-01-01

The ultra-wideband impedance sensor (UWBZ sensor, or Z-sensor) is implemented in differential and single-ended configurations. The differential UWBZ sensor employs a sub-nanosecond impulse to determine the balance of an impedance bridge. The bridge is configured as a differential sample-and-hold circuit that has a reference impedance side and an unknown impedance side. The unknown impedance side includes a short transmission line whose impedance is a function of the near proximity of objects. The single-ended UWBZ sensor eliminates the reference side of the bridge and is formed of a sample and hold circuit having a transmission line whose impedance is a function of the near proximity of objects. The sensing range of the transmission line is bounded by the two-way travel time of the impulse, thereby eliminating spurious Doppler modes from large distant objects that would occur in a microwave CW impedance bridge. Thus, the UWBZ sensor is a range-gated proximity sensor. The Z-sensor senses the near proximity of various materials such as metal, plastic, wood, petroleum products, and living tissue. It is much like a capacitance sensor, yet it is impervious to moisture. One broad application area is the general replacement of magnetic sensors, particularly where nonferrous materials need to be sensed. Another broad application area is sensing full/empty levels in tanks, vats and silos, e.g., a full/empty switch in water or petroleum tanks.

Ultra-wideband impedance sensor

DOEpatents

McEwan, T.E.

1999-03-16

The ultra-wideband impedance sensor (UWBZ sensor, or Z-sensor) is implemented in differential and single-ended configurations. The differential UWBZ sensor employs a sub-nanosecond impulse to determine the balance of an impedance bridge. The bridge is configured as a differential sample-and-hold circuit that has a reference impedance side and an unknown impedance side. The unknown impedance side includes a short transmission line whose impedance is a function of the near proximity of objects. The single-ended UWBZ sensor eliminates the reference side of the bridge and is formed of a sample and hold circuit having a transmission line whose impedance is a function of the near proximity of objects. The sensing range of the transmission line is bounded by the two-way travel time of the impulse, thereby eliminating spurious Doppler modes from large distant objects that would occur in a microwave CW impedance bridge. Thus, the UWBZ sensor is a range-gated proximity sensor. The Z-sensor senses the near proximity of various materials such as metal, plastic, wood, petroleum products, and living tissue. It is much like a capacitance sensor, yet it is impervious to moisture. One broad application area is the general replacement of magnetic sensors, particularly where nonferrous materials need to be sensed. Another broad application area is sensing full/empty levels in tanks, vats and silos, e.g., a full/empty switch in water or petroleum tanks. 2 figs.

Sliding Mode Observer-Based Current Sensor Fault Reconstruction and Unknown Load Disturbance Estimation for PMSM Driven System.

PubMed

Zhao, Kaihui; Li, Peng; Zhang, Changfan; Li, Xiangfei; He, Jing; Lin, Yuliang

2017-12-06

This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for a permanent magnet synchronous motor (PMSM)-driven system. First, the original PMSM system is transformed into two subsystems; the first subsystem has unknown system load disturbances, which are unrelated to sensor faults, and the second subsystem has sensor faults, but is free from unknown load disturbances. Introducing a new state variable, the augmented subsystem that has sensor faults can be transformed into having actuator faults. Second, two sliding mode observers (SMOs) are designed: the unknown load disturbance is estimated by the first SMO in the subsystem, which has unknown load disturbance, and the sensor faults can be reconstructed using the second SMO in the augmented subsystem, which has sensor faults. The gains of the proposed SMOs and their stability analysis are developed via the solution of linear matrix inequality (LMI). Finally, the effectiveness of the proposed scheme was verified by simulations and experiments. The results demonstrate that the proposed scheme can reconstruct current sensor faults and estimate unknown load disturbance for the PMSM-driven system.

Adaptive Fault-Tolerant Control of Uncertain Nonlinear Large-Scale Systems With Unknown Dead Zone.

PubMed

Chen, Mou; Tao, Gang

2016-08-01

In this paper, an adaptive neural fault-tolerant control scheme is proposed and analyzed for a class of uncertain nonlinear large-scale systems with unknown dead zone and external disturbances. To tackle the unknown nonlinear interaction functions in the large-scale system, the radial basis function neural network (RBFNN) is employed to approximate them. To further handle the unknown approximation errors and the effects of the unknown dead zone and external disturbances, integrated as the compounded disturbances, the corresponding disturbance observers are developed for their estimations. Based on the outputs of the RBFNN and the disturbance observer, the adaptive neural fault-tolerant control scheme is designed for uncertain nonlinear large-scale systems by using a decentralized backstepping technique. The closed-loop stability of the adaptive control system is rigorously proved via Lyapunov analysis and the satisfactory tracking performance is achieved under the integrated effects of unknown dead zone, actuator fault, and unknown external disturbances. Simulation results of a mass-spring-damper system are given to illustrate the effectiveness of the proposed adaptive neural fault-tolerant control scheme for uncertain nonlinear large-scale systems.

14. Photocopy of historic photograph (original photograph on file at ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

14. Photocopy of historic photograph (original photograph on file at Fairchild Air Force Museum, Spokane, WA) Photographer unknown, date unknown BOMBER ALERT FACILITY, INTERIOR, SLEEPING QUARTERS - Fairchild Air Force Base, Bomber Alert Facility, 803G South Taxi Way, Spokane, Spokane County, WA

Photocopy of photograph (from NBPPNSY) photographer unknown, 1988 view east ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Photocopy of photograph (from NBP-PNSY) photographer unknown, 1988 view east of marine railway (Haer no. Pa-387-W). The railway was being dismantled at the time this photograph was taken. - Naval Base Philadelphia-Philadelphia Naval Shipyard, League Island, Philadelphia, Philadelphia County, PA

[Fast discrimination of edible vegetable oil based on Raman spectroscopy].

PubMed

Zhou, Xiu-Jun; Dai, Lian-Kui; Li, Sheng

2012-07-01

A novel method to fast discriminate edible vegetable oils by Raman spectroscopy is presented. The training set is composed of different edible vegetable oils with known classes. Based on their original Raman spectra, baseline correction and normalization were applied to obtain standard spectra. Two characteristic peaks describing the unsaturated degree of vegetable oil were selected as feature vectors; then the centers of all classes were calculated. For an edible vegetable oil with unknown class, the same pretreatment and feature extraction methods were used. The Euclidian distances between the feature vector of the unknown sample and the center of each class were calculated, and the class of the unknown sample was finally determined by the minimum distance. For 43 edible vegetable oil samples from seven different classes, experimental results show that the clustering effect of each class was more obvious and the class distance was much larger with the new feature extraction method compared with PCA. The above classification model can be applied to discriminate unknown edible vegetable oils rapidly and accurately.

Quantum Standard Teleportation Based on the Generic Measurement Bases

NASA Astrophysics Data System (ADS)

Hao, San-Ru; Hou, Bo-Yu; Xi, Xiao-Qiang; Yue, Rui-Hong

2003-10-01

We study the quantum standard teleportation based on the generic measurement bases. It is shown that the quantum standard teleportation does not depend on the explicit expression of the measurement bases. We have given the correspondence relation between the measurement performed by Alice and the unitary transformation performed by Bob. We also prove that the single particle unknown states and the two-particle unknown cat-like states can be exactly transmitted by means of the generic measurement bases and the correspondence unitary transformations. The project supported in part by National Natural Science Foundation of China, the Hunan Provincial Natural Science Foundation of China, and the Scientific Research Fund of Hunan Provincial Education Department

Fast Markerless Tracking for Augmented Reality in Planar Environment

NASA Astrophysics Data System (ADS)

Basori, Ahmad Hoirul; Afif, Fadhil Noer; Almazyad, Abdulaziz S.; AbuJabal, Hamza Ali S.; Rehman, Amjad; Alkawaz, Mohammed Hazim

2015-12-01

Markerless tracking for augmented reality should not only be accurate but also fast enough to provide a seamless synchronization between real and virtual beings. Current reported methods showed that a vision-based tracking is accurate but requires high computational power. This paper proposes a real-time hybrid-based method for tracking unknown environments in markerless augmented reality. The proposed method provides collaboration of vision-based approach with accelerometers and gyroscopes sensors as camera pose predictor. To align the augmentation relative to camera motion, the tracking method is done by substituting feature-based camera estimation with combination of inertial sensors with complementary filter to provide more dynamic response. The proposed method managed to track unknown environment with faster processing time compared to available feature-based approaches. Moreover, the proposed method can sustain its estimation in a situation where feature-based tracking loses its track. The collaboration of sensor tracking managed to perform the task for about 22.97 FPS, up to five times faster than feature-based tracking method used as comparison. Therefore, the proposed method can be used to track unknown environments without depending on amount of features on scene, while requiring lower computational cost.

A new serotyping method for Klebsiella species: evaluation of the technique.

PubMed Central

Riser, E; Noone, P; Bonnet, M L

1976-01-01

A new indirect fluorescent typing method for Klebsiella species is compared with an established method, capsular swelling. The fluorescent antibody (FA) technique was tested with standards and unknowns, and the results were checked by capsular swelling. Several unknowns were sent away for confirmation of typing, by capsular swelling. The FA method was also tried by a technician in the routine department for blind identification of standards. Fluorescence typing gives close correlation with the established capsular swelling technique but has greater sensitivity; allows more econimical use of expensive antisera; possesses greater objectivity as it requires less operator skill in the reading of results; resolves most of the cross reactions observed with capsular swelling; and has a higher per cent success rate in identification. PMID:777043

Sexualization of Awareness: Catchy, but Does It Actually Increase Knowledge of Breast Cancer?

ERIC Educational Resources Information Center

Burgess, Melinda C. R.; Murray, Ashley B.

2014-01-01

Currently, in the United States, there exist numerous public awareness campaigns about breast cancer. Many of these campaigns are highly sexualized, focusing on the breasts as an object of fun, as opposed to focusing on information about prevention/diagnosis/treatment. In spite of their popularity, it is unknown what effect they actually have on…

Recognition of Natural Scenes from Global Properties: Seeing the Forest without Representing the Trees

ERIC Educational Resources Information Center

Greene, Michelle R.; Oliva, Aude

2009-01-01

Human observers are able to rapidly and accurately categorize natural scenes, but the representation mediating this feat is still unknown. Here we propose a framework of rapid scene categorization that does not segment a scene into objects and instead uses a vocabulary of global, ecological properties that describe spatial and functional aspects…

Longevity of shallow subsurface drip irrigation tubing under three tillage practices

USDA-ARS?s Scientific Manuscript database

Shallow Sub-Surface drip irrigation (S3DI) has drip tubing buried about 2-in below the soil surface. It is unknown how long drip tubing would be viable at this shallow soil depth using strip- or no-tillage systems. The objectives were to determine drip tube longevity, resultant crop yield, and parti...

Algebraic invariants for reflection Mueller polarimetry via uncompensated double pass illumination-collection optics.

PubMed

Ossikovski, Razvigor; Vizet, Jérémy

2016-07-01

We report on the identification of the two algebraic invariants inherent to Mueller matrix polarimetry measurements performed through double pass illumination-collection optics (e.g., an optical fiber or an objective) of unknown polarimetric response. The practical use of the invariants, potentially applicable to the characterization of nonreciprocal media, is illustrated on experimental examples.

Child and parent perceived food-induced gastrointestinal symptoms and quality of life in children with functional gastrointestinal disorders

USDA-ARS?s Scientific Manuscript database

It is unknown whether children with functional gastrointestinal (GI) disorders identify specific foods that exacerbate their GI symptoms. The objectives of this study were to determine the perceived role of food on GI symptoms and to determine the impact of food-induced symptoms on quality of life (...

Persistent effects of pre-weaning in piglets on composition of fecal microbiota are diet-, genus-, and time-specific

USDA-ARS?s Scientific Manuscript database

The effects of diet on gut microbiota composition in the pre-weaning period have been characterized, but it is unknown whether differences in composition are sustained after weaning. The objective of this study was to determine if post-natal diet-induced differences in microbiota persist after weani...

Ground penetrating radar (GPR) detects fine roots of agricultural crops in the field

Treesearch

Xiuwei Liu; Xuejun Dong; Qingwu Xue; Daniel I. Leskovar; John Jifon; John R. Butnor; Thomas Marek

2018-01-01

Aim Ground penetrating radar (GPR) as a non-invasive technique is widely used in coarse root detection. However, the applicability of the technique to detect fine roots of agricultural crops is unknown. The objective of this study was to assess the feasibility of utilizing GPR to detect fine roots in the field.

Subitizing Reflects Visuo-Spatial Object Individuation Capacity

ERIC Educational Resources Information Center

Piazza, Manuela; Fumarola, Antonia; Chinello, Alessandro; Melcher, David

2011-01-01

Subitizing is the immediate apprehension of the exact number of items in small sets. Despite more than a 100 years of research around this phenomenon, its nature and origin are still unknown. One view posits that it reflects a number estimation process common for small and large sets, which precision decreases as the number of items increases,…

Gene variations of nitric oxide synthase regulate the effects of a saturated fat rich meal on endothelial function

USDA-ARS?s Scientific Manuscript database

Objective: Endothelial nitric oxide synthase gene variations have been linked to a higher risk for cardiovascular diseases by unknown mechanisms. Our aim was to determine if two SNPs located in NOS3 (E298D and i19342) interfere with microvascular endothelial function (MEF) and/or oxidative stress du...

12-Month Follow-Up of Fluoxetine and Cognitive Behavioral Therapy for Binge Eating Disorder

ERIC Educational Resources Information Center

Grilo, Carlos M.; Crosby, Ross D.; Wilson, G. Terence; Masheb, Robin M.

2012-01-01

Objective: The longer term efficacy of medication treatments for binge-eating disorder (BED) remains unknown. This study examined the longer term effects of fluoxetine and cognitive behavioral therapy (CBT) either with fluoxetine (CBT + fluoxetine) or with placebo (CBT + placebo) for BED through 12-month follow-up after completing treatments.…

HIV Post-Exposure Prophylaxis in Children and Adolescents Presenting for Reported Sexual Assault

ERIC Educational Resources Information Center

Girardet, Rebecca G.; Lemme, Scott; Biason, Tiffany A.; Bolton, Kelly; Lahoti, Sheela

2009-01-01

Background: The appropriate use of antiretroviral medications to protect against infection with human immunodeficiency virus (HIV) is unclear in cases of sexual assault of children, for whom the perpetrator's risk of HIV is often unknown, and physical proof of sexual contact is usually absent. Objective: In an effort to clarify prescribing…

Plasma concentrations of acyl-ghrelin are associated with average daily gain and feeding behavior in grow-finish pigs

USDA-ARS?s Scientific Manuscript database

Feeding behavior is an important component of growth and feed efficiency in swine. Acyl-ghrelin is a peptide produced in the stomach that is orexigenic. The role of ghrelin in regulating feeding behavior in swine under commercial conditions is unknown. The objectives of this study were to determine ...

Descriptive texture analyses of cooked patties made of chicken breast with the woody breast condition

USDA-ARS?s Scientific Manuscript database

The woody breast (WB) condition is known to negatively influence the texture characteristics and quality of intact broiler breast fillets, but the impact of WB on comminuted meat products are unknown. The objective of this study was to evaluate the effects of WB on the texture and cooking properties...

A Comparison of Punitive and Nonpunitive Truancy Program Outcomes in an Urban School District

ERIC Educational Resources Information Center

Bernard, Shelton D.

2014-01-01

Because the relationship between school disciplinary models and truancy outcomes is unknown, it is difficult for school leaders to understand the costs and benefits of punitive versus nonpunitive discipline. To achieve the State of Georgia's stated policy objectives of lowering truancy and its negative outcomes, this knowledge gap needs to be…

The Efficacy of Dictionary Use while Reading for Learning New Words

ERIC Educational Resources Information Center

Hamilton, Harley

2012-01-01

The researcher investigated the use of three types of dictionaries while reading by high school students with severe to profound hearing loss. The objective of the study was to determine the effectiveness of each type of dictionary for acquiring the meanings of unknown vocabulary in text. The three types of dictionaries were (a) an online…

Latent Learning and Deferred Imitation at 3 Months

ERIC Educational Resources Information Center

Campanella, Jennifer; Rovee-Collier, Carolyn

2005-01-01

Young infants spend most of their waking time looking around, but whether they learn anything about what they see is unknown. We used a sensory preconditioning paradigm and a deferred imitation task to assess if 3-month-olds formed a latent association between 2 objects (S[subscript 1], S[subscript 2]) that they merely saw together. Because…

Leucine and methionine deficiency induce catabolism through non-overlapping mechanisms in rainbow trout (Oncorhynchus mykiss) primary myoblasts

USDA-ARS?s Scientific Manuscript database

Amino acids (AA) have anabolic effects on protein accretion in muscle. In fish it is unknown if this anabolic response is directly attributed to a single AA or a specific AA profile. Therefore, our experimental objective was to determine if AAs or AA profiles regulate protein turnover and growth-r...

Adaptive Approximation-Based Regulation Control for a Class of Uncertain Nonlinear Systems Without Feedback Linearizability.

PubMed

Wang, Ning; Sun, Jing-Chao; Han, Min; Zheng, Zhongjiu; Er, Meng Joo

2017-09-06

In this paper, for a general class of uncertain nonlinear (cascade) systems, including unknown dynamics, which are not feedback linearizable and cannot be solved by existing approaches, an innovative adaptive approximation-based regulation control (AARC) scheme is developed. Within the framework of adding a power integrator (API), by deriving adaptive laws for output weights and prediction error compensation pertaining to single-hidden-layer feedforward network (SLFN) from the Lyapunov synthesis, a series of SLFN-based approximators are explicitly constructed to exactly dominate completely unknown dynamics. By the virtue of significant advancements on the API technique, an adaptive API methodology is eventually established in combination with SLFN-based adaptive approximators, and it contributes to a recursive mechanism for the AARC scheme. As a consequence, the output regulation error can asymptotically converge to the origin, and all other signals of the closed-loop system are uniformly ultimately bounded. Simulation studies and comprehensive comparisons with backstepping- and API-based approaches demonstrate that the proposed AARC scheme achieves remarkable performance and superiority in dealing with unknown dynamics.

Technical support for creating an artificial intelligence system for feature extraction and experimental design

NASA Technical Reports Server (NTRS)

Glick, B. J.

1985-01-01

Techniques for classifying objects into groups or clases go under many different names including, most commonly, cluster analysis. Mathematically, the general problem is to find a best mapping of objects into an index set consisting of class identifiers. When an a priori grouping of objects exists, the process of deriving the classification rules from samples of classified objects is known as discrimination. When such rules are applied to objects of unknown class, the process is denoted classification. The specific problem addressed involves the group classification of a set of objects that are each associated with a series of measurements (ratio, interval, ordinal, or nominal levels of measurement). Each measurement produces one variable in a multidimensional variable space. Cluster analysis techniques are reviewed and methods for incuding geographic location, distance measures, and spatial pattern (distribution) as parameters in clustering are examined. For the case of patterning, measures of spatial autocorrelation are discussed in terms of the kind of data (nominal, ordinal, or interval scaled) to which they may be applied.

Distance estimation and collision prediction for on-line robotic motion planning

NASA Technical Reports Server (NTRS)

Kyriakopoulos, K. J.; Saridis, G. N.

1992-01-01

An efficient method for computing the minimum distance and predicting collisions between moving objects is presented. This problem is incorporated into the framework of an in-line motion-planning algorithm to satisfy collision avoidance between a robot and moving objects modeled as convex polyhedra. In the beginning, the deterministic problem where the information about the objects is assumed to be certain is examined. L(1) or L(infinity) norms are used to represent distance and the problem becomes a linear programming problem. The stochastic problem is formulated where the uncertainty is induced by sensing and the unknown dynamics of the moving obstacles. Two problems are considered: First, filtering of the distance between the robot and the moving object at the present time. Second, prediction of the minimum distance in the future in order to predict the collision time.

“Did You Call Me?” 5-Month-Old Infants Own Name Guides Their Attention

PubMed Central

Parise, Eugenio; Friederici, Angela D.; Striano, Tricia

2010-01-01

An infant's own name is a unique social cue. Infants are sensitive to their own name by 4 months of age, but whether they use their names as a social cue is unknown. Electroencephalogram (EEG) was measured as infants heard their own name or stranger's names and while looking at novel objects. Event related brain potentials (ERPs) in response to names revealed that infants differentiate their own name from stranger names from the first phoneme. The amplitude of the ERPs to objects indicated that infants attended more to objects after hearing their own names compared to another name. Thus, by 5 months of age infants not only detect their name, but also use it as a social cue to guide their attention to events and objects in the world. PMID:21151971

Progressive compressive imager

NASA Astrophysics Data System (ADS)

Evladov, Sergei; Levi, Ofer; Stern, Adrian

2012-06-01

We have designed and built a working automatic progressive sampling imaging system based on the vector sensor concept, which utilizes a unique sampling scheme of Radon projections. This sampling scheme makes it possible to progressively add information resulting in tradeoff between compression and the quality of reconstruction. The uniqueness of our sampling is that in any moment of the acquisition process the reconstruction can produce a reasonable version of the image. The advantage of the gradual addition of the samples is seen when the sparsity rate of the object is unknown, and thus the number of needed measurements. We have developed the iterative algorithm OSO (Ordered Sets Optimization) which employs our sampling scheme for creation of nearly uniform distributed sets of samples, which allows the reconstruction of Mega-Pixel images. We present the good quality reconstruction from compressed data ratios of 1:20.

A new hero emerges: another exceptional mammalian spine and its potential adaptive significance.

PubMed

Stanley, William T; Robbins, Lynn W; Malekani, Jean M; Mbalitini, Sylvestre Gambalemoke; Migurimu, Dudu Akaibe; Mukinzi, Jean Claude; Hulselmans, Jan; Prévot, Vanya; Verheyen, Erik; Hutterer, Rainer; Doty, Jeffrey B; Monroe, Benjamin P; Nakazawa, Yoshinori J; Braden, Zachary; Carroll, Darin; Peterhans, Julian C Kerbis; Bates, John M; Esselstyn, Jacob A

2013-10-23

The hero shrew's (Scutisorex somereni) massive interlocking lumbar vertebrae represent the most extreme modification of the vertebral column known in mammals. No intermediate form of this remarkable morphology is known, nor is there any convincing theory to explain its functional significance. We document a new species in the heretofore monotypic genus Scutisorex; the new species possesses cranial and vertebral features representing intermediate character states between S. somereni and other shrews. Phylogenetic analyses of DNA sequences support a sister relationship between the new species and S. somereni. While the function of the unusual spine in Scutisorex is unknown, it gives these small animals incredible vertebral strength. Based on field observations, we hypothesize that the unique vertebral column is an adaptation allowing these shrews to lever heavy or compressive objects to access concentrated food resources inaccessible to other animals.

Novel endophytic lineages of Tolypocladium provide new insights into the ecology and evolution of Cordyceps-like fungi.

PubMed

Gazis, Romina; Skaltsas, Demetra; Chaverri, Priscila

2014-01-01

The objective of this study was to identify a group of unknown endophytic fungal isolates from the living sapwood of wild and planted Hevea (rubber tree) populations. Three novel lineages of Tolypocladium are described based on molecular and morphological data. Findings from this study open a window for novel hypotheses regarding the ecology and role of endophytes within plant communities as well as trait evolution and potential forces driving diversification of Cordyceps-like fungi. This study stresses the importance of integrating asexual and sexual fungal states for a more complete understanding of the natural history of this diverse group. In addition, it highlights the study of fungi in the sapwood of tropical trees as habitat for the discovery of novel fungal lineages and substrate associations. © 2014 by The Mycological Society of America.

Global regularizing flows with topology preservation for active contours and polygons.

PubMed

Sundaramoorthi, Ganesh; Yezzi, Anthony

2007-03-01

Active contour and active polygon models have been used widely for image segmentation. In some applications, the topology of the object(s) to be detected from an image is known a priori, despite a complex unknown geometry, and it is important that the active contour or polygon maintain the desired topology. In this work, we construct a novel geometric flow that can be added to image-based evolutions of active contours and polygons in order to preserve the topology of the initial contour or polygon. We emphasize that, unlike other methods for topology preservation, the proposed geometric flow continually adjusts the geometry of the original evolution in a gradual and graceful manner so as to prevent a topology change long before the curve or polygon becomes close to topology change. The flow also serves as a global regularity term for the evolving contour, and has smoothness properties similar to curvature flow. These properties of gradually adjusting the original flow and global regularization prevent geometrical inaccuracies common with simple discrete topology preservation schemes. The proposed topology preserving geometric flow is the gradient flow arising from an energy that is based on electrostatic principles. The evolution of a single point on the contour depends on all other points of the contour, which is different from traditional curve evolutions in the computer vision literature.

Visions and reality: the idea of competence-oriented assessment for German medical students is not yet realised in licensing examinations

PubMed Central

Huber-Lang, Markus; Palmer, Annette; Grab, Claudia; Boeckers, Anja; Boeckers, Tobias Maria; Oechsner, Wolfgang

2017-01-01

Objective: Competence orientation, often based on the CanMEDS model, has become an important goal for modern curricula in medical education. The National Competence Based Catalogue of Learning Objectives for Undergraduate Medical Education (NKLM) has been adopted in Germany. However, it is currently unknown whether the vision of competence orientation has also reached the licensing examination procedures. Methods: Therefore, a prospective, descriptive, single-centre, exemplary study design was applied to evaluate 4051 questions/tasks (from 28 examiners at 7 two-day licensing oral-practical exams) for undergraduate medical students at the University of Ulm. The oral and practical questions/tasks as well as the real bedside assessment were assigned to specific competence roles (NKLM section I), categories (NKLM section II) and taxonomy levels of learning domains. Results: Numerous questions/tasks were set per candidate (day 1/2: 70±24/86±19 questions) in the licensing oral-practical exam. Competence roles beyond the “medical expert” were scarcely considered. Furthermore, practical and communication skills at the bedside were hardly addressed (less than 3/15 min). Strikingly, there was a significant predominance of questions with a low-level taxonomy. Conclusions: The data indicate a misalignment of competence-oriented frameworks and the “real world” licensing practical-oral medical exam, which needs improvement in both evaluation and education processes. PMID:28584873

Spacecraft Orbit Anomaly Representation Using Thrust-Fourier-Coefficients with Orbit Determination Toolbox

NASA Astrophysics Data System (ADS)

Ko, H.; Scheeres, D.

2014-09-01

Representing spacecraft orbit anomalies between two separate states is a challenging but an important problem in achieving space situational awareness for an active spacecraft. Incorporation of such a capability could play an essential role in analyzing satellite behaviors as well as trajectory estimation of the space object. A general way to deal with the anomaly problem is to add an estimated perturbing acceleration such as dynamic model compensation (DMC) into an orbit determination process based on pre- and post-anomaly tracking data. It is a time-consuming numerical process to find valid coefficients to compensate for unknown dynamics for the anomaly. Even if the orbit determination filter with DMC can crudely estimate an unknown acceleration, this approach does not consider any fundamental element of the unknown dynamics for a given anomaly. In this paper, a new way of representing a spacecraft anomaly using an interpolation technique with the Thrust-Fourier-Coefficients (TFCs) is introduced and several anomaly cases are studied using this interpolation method. It provides a very efficient way of reconstructing the fundamental elements of the dynamics for a given spacecraft anomaly. Any maneuver performed by a satellite transitioning between two arbitrary orbital states can be represented as an equivalent maneuver using an interpolation technique with the TFCs. Given unconnected orbit states between two epochs due to a spacecraft anomaly, it is possible to obtain a unique control law using the TFCs that is able to generate the desired secular behavior for the given orbital changes. This interpolation technique can capture the fundamental elements of combined unmodeled anomaly events. The interpolated orbit trajectory, using the TFCs compensating for a given anomaly, can be used to improve the quality of orbit fits through the anomaly period and therefore help to obtain a good orbit determination solution after the anomaly. Orbit Determination Toolbox (ODTBX) is modified to adapt this technique in order to verify the performance of this interpolation approach. Spacecraft anomaly cases are based on either single or multiple low or high thrust maneuvers and the unknown thrust accelerations are recovered and compared with the true thrust acceleration. The advantage of this approach is to easily append TFCs and its dynamics to the pre-built ODTBX, which enables us to blend post-anomaly tracking data to improve the performance of the interpolation representation in the absence of detailed information about a maneuver. It allows us to improve space situational awareness in the areas of uncertainty propagation, anomaly characterization and track correlation.

A modified NARMAX model-based self-tuner with fault tolerance for unknown nonlinear stochastic hybrid systems with an input-output direct feed-through term.

PubMed

Tsai, Jason S-H; Hsu, Wen-Teng; Lin, Long-Guei; Guo, Shu-Mei; Tann, Joseph W

2014-01-01

A modified nonlinear autoregressive moving average with exogenous inputs (NARMAX) model-based state-space self-tuner with fault tolerance is proposed in this paper for the unknown nonlinear stochastic hybrid system with a direct transmission matrix from input to output. Through the off-line observer/Kalman filter identification method, one has a good initial guess of modified NARMAX model to reduce the on-line system identification process time. Then, based on the modified NARMAX-based system identification, a corresponding adaptive digital control scheme is presented for the unknown continuous-time nonlinear system, with an input-output direct transmission term, which also has measurement and system noises and inaccessible system states. Besides, an effective state space self-turner with fault tolerance scheme is presented for the unknown multivariable stochastic system. A quantitative criterion is suggested by comparing the innovation process error estimated by the Kalman filter estimation algorithm, so that a weighting matrix resetting technique by adjusting and resetting the covariance matrices of parameter estimate obtained by the Kalman filter estimation algorithm is utilized to achieve the parameter estimation for faulty system recovery. Consequently, the proposed method can effectively cope with partially abrupt and/or gradual system faults and input failures by the fault detection. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Bayesian learning

NASA Technical Reports Server (NTRS)

Denning, Peter J.

1989-01-01

In 1983 and 1984, the Infrared Astronomical Satellite (IRAS) detected 5,425 stellar objects and measured their infrared spectra. In 1987 a program called AUTOCLASS used Bayesian inference methods to discover the classes present in these data and determine the most probable class of each object, revealing unknown phenomena in astronomy. AUTOCLASS has rekindled the old debate on the suitability of Bayesian methods, which are computationally intensive, interpret probabilities as plausibility measures rather than frequencies, and appear to depend on a subjective assessment of the probability of a hypothesis before the data were collected. Modern statistical methods have, however, recently been shown to also depend on subjective elements. These debates bring into question the whole tradition of scientific objectivity and offer scientists a new way to take responsibility for their findings and conclusions.

Feasibility of performing space surveillance tasks with a proposed space-based optical architecture

NASA Astrophysics Data System (ADS)

Flohrer, Tim; Krag, Holger; Klinkrad, Heiner; Schildknecht, Thomas

Under ESA contract an industrial consortium including Aboa Space Research Oy (ASRO), the Astronomical Institute of the University of Bern (AIUB), and the Dutch National Aerospace Laboratory (NLR), proposed the observation concept, developed a suitable sensor architecture, and assessed the performance of a space-based optical (SBO) telescope in 2005. The goal of the SBO instrumentation was to analyse how the existing knowledge gap in the space debris population in the millimetre and centimetre regime may be closed by means of a passive op-tical instrument. SBO was requested to provide statistical information on the space debris population, in terms of number of objects and size distribution. The SBO was considered to be a cost-efficient instrumentation of 20 cm aperture and 6 deg field-of-view with flexible integration requirements. It should be possible to integrate the SBO easily as a secondary payload on satellites launched into low-Earth orbits (LEO), or into geostationary orbit (GEO). Thus the selected mission concept only allowed for fix-mounted telescopes, and the pointing direction could be requested freely. It was shown in the performance analysis that the statistical information on small-sized space debris can only be collected if the observation ranges are comparatively small. Two of the most promising concepts were to observe objects in LEO from a sensor placed into a sun-synchronous LEO, while objects in GEO should be observed from a GEO satellite. Since 2007 ESA focuses space surveillance and tracking activities in the Space Situational Awareness (SSA) preparatory program. Ground-based radars and optical telescopes are stud-ied for the build-up and to maintenance of a catalogue of objects. In this paper we analyse how the SBO architecture could contribute to the space surveillance tasks survey and tracking. We assume that the SBO instrumentation is placed into a circular sun-synchronous orbit at 800 km altitude. We discuss the observation conditions of objects at higher altitude, such as GEO and Medium-Earth Orbits (MEO). Of particular interest are the radiometric performance from which we derive the detectable object diameters, the coverage of a reference population, and the covered arc lengths of individual objects. The latter is of particular interest for the simu-lation of the orbit determination, correlation, and cataloguing. Assuming realistic noise levels known from the SBO design we simulate first orbit determination of unknown objects (surveys) and orbit improvements (tracking) for sample objects. We use a simulation environment that comprises the ESA Program for Radar and Optical Observation Forecasting (PROOF) in the version 2005 and AIUB's program system CelMech. ESA's MASTER-2005 serves as reference population for all analyses.

Thermal Imaging with Novel Infrared Focal Plane Arrays and Quantitative Analysis of Thermal Imagery

NASA Technical Reports Server (NTRS)

Gunapala, S. D.; Rafol, S. B.; Bandara, S. V.; Liu, J. K.; Mumolo, J. M.; Soibel, A.; Ting, D. Z.; Tidrow, Meimei

2012-01-01

We have developed a single long-wavelength infrared (LWIR) quantum well infrared photodetector (QWIP) camera for thermography. This camera has been used to measure the temperature profile of patients. A pixel coregistered simultaneously reading mid-wavelength infrared (MWIR)/LWIR dual-band QWIP camera was developed to improve the accuracy of temperature measurements especially with objects with unknown emissivity. Even the dualband measurement can provide inaccurate results due to the fact that emissivity is a function of wavelength. Thus we have been developing a four-band QWIP camera for accurate temperature measurement of remote object.

383. F.A.N., Delineator Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

383. F.A.N., Delineator Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF PUBLIC WORKS; SAN FRANCISCO - OAKLAND BAY BRIDGE; WEST BAY CROSSING; TOWERS; TYPICAL BASE DETAILS; DRG. NO. 29 - San Francisco Oakland Bay Bridge, Spanning San Francisco Bay, San Francisco, San Francisco County, CA

Performance and robustness of optimal fractional fuzzy PID controllers for pitch control of a wind turbine using chaotic optimization algorithms.

PubMed

Asgharnia, Amirhossein; Shahnazi, Reza; Jamali, Ali

2018-05-11

The most studied controller for pitch control of wind turbines is proportional-integral-derivative (PID) controller. However, due to uncertainties in wind turbine modeling and wind speed profiles, the need for more effective controllers is inevitable. On the other hand, the parameters of PID controller usually are unknown and should be selected by the designer which is neither a straightforward task nor optimal. To cope with these drawbacks, in this paper, two advanced controllers called fuzzy PID (FPID) and fractional-order fuzzy PID (FOFPID) are proposed to improve the pitch control performance. Meanwhile, to find the parameters of the controllers the chaotic evolutionary optimization methods are used. Using evolutionary optimization methods not only gives us the unknown parameters of the controllers but also guarantees the optimality based on the chosen objective function. To improve the performance of the evolutionary algorithms chaotic maps are used. All the optimization procedures are applied to the 2-mass model of 5-MW wind turbine model. The proposed optimal controllers are validated using simulator FAST developed by NREL. Simulation results demonstrate that the FOFPID controller can reach to better performance and robustness while guaranteeing fewer fatigue damages in different wind speeds in comparison to FPID, fractional-order PID (FOPID) and gain-scheduling PID (GSPID) controllers. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive neural control for a class of nonlinear time-varying delay systems with unknown hysteresis.

PubMed

Liu, Zhi; Lai, Guanyu; Zhang, Yun; Chen, Xin; Chen, Chun Lung Philip

2014-12-01

This paper investigates the fusion of unknown direction hysteresis model with adaptive neural control techniques in face of time-delayed continuous time nonlinear systems without strict-feedback form. Compared with previous works on the hysteresis phenomenon, the direction of the modified Bouc-Wen hysteresis model investigated in the literature is unknown. To reduce the computation burden in adaptation mechanism, an optimized adaptation method is successfully applied to the control design. Based on the Lyapunov-Krasovskii method, two neural-network-based adaptive control algorithms are constructed to guarantee that all the system states and adaptive parameters remain bounded, and the tracking error converges to an adjustable neighborhood of the origin. In final, some numerical examples are provided to validate the effectiveness of the proposed control methods.

Reconstruction of phonon relaxation times from systems featuring interfaces with unknown properties

NASA Astrophysics Data System (ADS)

Forghani, Mojtaba; Hadjiconstantinou, Nicolas G.

2018-05-01

We present a method for reconstructing the phonon relaxation-time function τω=τ (ω ) (including polarization) and associated phonon free-path distribution from thermal spectroscopy data for systems featuring interfaces with unknown properties. Our method does not rely on the effective thermal-conductivity approximation or a particular physical model of the interface behavior. The reconstruction is formulated as an optimization problem in which the relaxation times are determined as functions of frequency by minimizing the discrepancy between the experimentally measured temperature profiles and solutions of the Boltzmann transport equation for the same system. Interface properties such as transmissivities are included as unknowns in the optimization; however, because for the thermal spectroscopy problems considered here the reconstruction is not very sensitive to the interface properties, the transmissivities are only approximately reconstructed and can be considered as byproducts of the calculation whose primary objective is the accurate determination of the relaxation times. The proposed method is validated using synthetic experimental data obtained from Monte Carlo solutions of the Boltzmann transport equation. The method is shown to remain robust in the presence of uncertainty (noise) in the measurement.

Sliding Mode Observer-Based Current Sensor Fault Reconstruction and Unknown Load Disturbance Estimation for PMSM Driven System

PubMed Central

Li, Xiangfei; Lin, Yuliang

2017-01-01

This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for a permanent magnet synchronous motor (PMSM)-driven system. First, the original PMSM system is transformed into two subsystems; the first subsystem has unknown system load disturbances, which are unrelated to sensor faults, and the second subsystem has sensor faults, but is free from unknown load disturbances. Introducing a new state variable, the augmented subsystem that has sensor faults can be transformed into having actuator faults. Second, two sliding mode observers (SMOs) are designed: the unknown load disturbance is estimated by the first SMO in the subsystem, which has unknown load disturbance, and the sensor faults can be reconstructed using the second SMO in the augmented subsystem, which has sensor faults. The gains of the proposed SMOs and their stability analysis are developed via the solution of linear matrix inequality (LMI). Finally, the effectiveness of the proposed scheme was verified by simulations and experiments. The results demonstrate that the proposed scheme can reconstruct current sensor faults and estimate unknown load disturbance for the PMSM-driven system. PMID:29211017

Object Recognition in Flight: How Do Bees Distinguish between 3D Shapes?

PubMed Central

Werner, Annette; Stürzl, Wolfgang; Zanker, Johannes

2016-01-01

Honeybees (Apis mellifera) discriminate multiple object features such as colour, pattern and 2D shape, but it remains unknown whether and how bees recover three-dimensional shape. Here we show that bees can recognize objects by their three-dimensional form, whereby they employ an active strategy to uncover the depth profiles. We trained individual, free flying honeybees to collect sugar water from small three-dimensional objects made of styrofoam (sphere, cylinder, cuboids) or folded paper (convex, concave, planar) and found that bees can easily discriminate between these stimuli. We also tested possible strategies employed by the bees to uncover the depth profiles. For the card stimuli, we excluded overall shape and pictorial features (shading, texture gradients) as cues for discrimination. Lacking sufficient stereo vision, bees are known to use speed gradients in optic flow to detect edges; could the bees apply this strategy also to recover the fine details of a surface depth profile? Analysing the bees’ flight tracks in front of the stimuli revealed specific combinations of flight maneuvers (lateral translations in combination with yaw rotations), which are particularly suitable to extract depth cues from motion parallax. We modelled the generated optic flow and found characteristic patterns of angular displacement corresponding to the depth profiles of our stimuli: optic flow patterns from pure translations successfully recovered depth relations from the magnitude of angular displacements, additional rotation provided robust depth information based on the direction of the displacements; thus, the bees flight maneuvers may reflect an optimized visuo-motor strategy to extract depth structure from motion signals. The robustness and simplicity of this strategy offers an efficient solution for 3D-object-recognition without stereo vision, and could be employed by other flying insects, or mobile robots. PMID:26886006

Object Recognition in Flight: How Do Bees Distinguish between 3D Shapes?

PubMed

Werner, Annette; Stürzl, Wolfgang; Zanker, Johannes

2016-01-01

Honeybees (Apis mellifera) discriminate multiple object features such as colour, pattern and 2D shape, but it remains unknown whether and how bees recover three-dimensional shape. Here we show that bees can recognize objects by their three-dimensional form, whereby they employ an active strategy to uncover the depth profiles. We trained individual, free flying honeybees to collect sugar water from small three-dimensional objects made of styrofoam (sphere, cylinder, cuboids) or folded paper (convex, concave, planar) and found that bees can easily discriminate between these stimuli. We also tested possible strategies employed by the bees to uncover the depth profiles. For the card stimuli, we excluded overall shape and pictorial features (shading, texture gradients) as cues for discrimination. Lacking sufficient stereo vision, bees are known to use speed gradients in optic flow to detect edges; could the bees apply this strategy also to recover the fine details of a surface depth profile? Analysing the bees' flight tracks in front of the stimuli revealed specific combinations of flight maneuvers (lateral translations in combination with yaw rotations), which are particularly suitable to extract depth cues from motion parallax. We modelled the generated optic flow and found characteristic patterns of angular displacement corresponding to the depth profiles of our stimuli: optic flow patterns from pure translations successfully recovered depth relations from the magnitude of angular displacements, additional rotation provided robust depth information based on the direction of the displacements; thus, the bees flight maneuvers may reflect an optimized visuo-motor strategy to extract depth structure from motion signals. The robustness and simplicity of this strategy offers an efficient solution for 3D-object-recognition without stereo vision, and could be employed by other flying insects, or mobile robots.

Image system for three dimensional, 360{degree}, time sequence surface mapping of moving objects

DOEpatents

Lu, S.Y.

1998-12-22

A three-dimensional motion camera system comprises a light projector placed between two synchronous video cameras all focused on an object-of-interest. The light projector shines a sharp pattern of vertical lines (Ronchi ruling) on the object-of-interest that appear to be bent differently to each camera by virtue of the surface shape of the object-of-interest and the relative geometry of the cameras, light projector and object-of-interest. Each video frame is captured in a computer memory and analyzed. Since the relative geometry is known and the system pre-calibrated, the unknown three-dimensional shape of the object-of-interest can be solved for by matching the intersections of the projected light lines with orthogonal epipolar lines corresponding to horizontal rows in the video camera frames. A surface reconstruction is made and displayed on a monitor screen. For 360{degree} all around coverage of the object-of-interest, two additional sets of light projectors and corresponding cameras are distributed about 120{degree} apart from one another. 20 figs.

Numerical model of two-dimensional heterogeneous combustion in porous media under natural convection or forced filtration

NASA Astrophysics Data System (ADS)

Lutsenko, Nickolay A.

2018-03-01

A novel mathematical model and original numerical method for investigating the two-dimensional waves of heterogeneous combustion in porous media are proposed and described in detail. The mathematical model is constructed within the framework of the model of interacting interpenetrating continua and includes equations of state, continuity, momentum conservation and energy for solid and gas phases. Combustion, considered in the paper, is due to the exothermic reaction between fuel in the porous solid medium and oxidiser contained in the gas flowing through the porous object. The original numerical method is based on a combination of explicit and implicit finite-difference schemes. A distinctive feature of the proposed model is that the gas velocity at the open boundaries (inlet and outlet) of the porous object is unknown and has to be found from the solution of the problem, i.e. the flow rate of the gas regulates itself. This approach allows processes to be modelled not only under forced filtration, but also under free convection, when there is no forced gas input in porous objects, which is typical for many natural or anthropogenic disasters (burning of peatlands, coal dumps, landfills, grain elevators). Some two-dimensional time-dependent problems of heterogeneous combustion in porous objects have been solved using the proposed numerical method. It is shown that two-dimensional waves of heterogeneous combustion in porous media can propagate in two modes with different characteristics, as in the case of one-dimensional combustion, but the combustion front can move in a complex manner, and gas dynamics within the porous objects can be complicated. When natural convection takes place, self-sustaining combustion waves can go through the all parts of the object regardless of where an ignition zone was located, so the all combustible material in each part of the object is burned out, in contrast to forced filtration.

Assessing disease severity: accuracy and reliability of rater estimates in relation to number of diagrams in a standard area diagram set

USDA-ARS?s Scientific Manuscript database

Error in rater estimates of plant disease severity occur, and standard area diagrams (SADs) help improve accuracy and reliability. The effects of diagram number in a SAD set on accuracy and reliability is unknown. The objective of this study was to compare estimates of pecan scab severity made witho...

19. Photocopy of photograph. VIEW OF WORKER MANIPULATING SMALL GLASS ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

19. Photocopy of photograph. VIEW OF WORKER MANIPULATING SMALL GLASS OBJECTS IN THE HOT BAY WITH MANIPULATOR ARMS AT WORK STATION E-2. Photographer unknown, ca. 1969, original photograph and negative on file at the Remote Sensing Laboratory, Department of Energy, Nevada Operations Office. - Nevada Test Site, Engine Maintenance Assembly & Disassembly Facility, Area 25, Jackass Flats, Mercury, Nye County, NV

Contribution of stumps to carbon and nitrogen pools in southern Appalachian hardwood forests

Treesearch

Eric B. Sucre; Thomas R. Fox

2008-01-01

Decomposing stumps are prevalent in managed forest ecosystems although the impact of these microsites on nutrient retention and cycling is relatively unknown. In this study, stumps were defined as the aboveground and belowground (i.e., root system) left over from previous harvests. The objective of this study was to quantify the total soil volume occupied by stumps and...

Exploring Individual Trajectories of Social Communicative Development in Toddlers at Risk for Autism Spectrum Disorders

ERIC Educational Resources Information Center

Dereu, Mieke; Roeyers, Herbert; Raymaekers, Ruth; Warreyn, Petra

2012-01-01

Whilst impairments in joint attention, imitation, and pretend play are well documented in children with autism spectrum disorder (ASD), the developmental trajectories of these symptoms remain unknown. The main objective was to explore these trajectories in a sample of children at risk for ASD between the ages of 2 and 4 years. After screening…

Dissociation between Small and Large Numerosities in Newborn Infants

ERIC Educational Resources Information Center

Coubart, Aurélie; Izard, Véronique; Spelke, Elizabeth S.; Marie, Julien; Streri, Arlette

2014-01-01

In the first year of life, infants possess two cognitive systems encoding numerical information: one for processing the numerosity of sets of 4 or more items, and the second for tracking up to 3 objects in parallel. While a previous study showed the former system to be already present a few hours after birth, it is unknown whether the latter…

The contribution of beverages to intakes of energy and MyPlate components by current, former, and never smokers in the United States

USDA-ARS?s Scientific Manuscript database

Though beverage intake patterns have been shown to differ by smoking status, it is unknown whether the contributions of beverages to intakes of energy and MyPlate components also differ. The objective of this study was to compare beverage intakes and contributions of energy and MyPlate components by...

Childhood Gender Nonconformity, Bullying Victimization, and Depressive Symptoms across Adolescence and Early Adulthood: An 11-Year Longitudinal Study

ERIC Educational Resources Information Center

Roberts, Andrea L.; Rosario, Margaret; Slopen, Natalie; Calzo, Jerel P.; Austin, S. Bryn

2013-01-01

Objective: Childhood gender nonconformity has been associated with increased risk of caregiver abuse and bullying victimization outside the home, but it is unknown whether as a consequence children who are nonconforming are at higher risk of depressive symptoms. Method: Using data from a large national cohort (N = 10,655), we examined differences…

Consumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians

USDA-ARS?s Scientific Manuscript database

BACKGROUND: Recent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown. OBJECTIVE: We investigated the associations of mea...

Evaluation of the ruminal bacterial diversity of cattle fed diets containing citrus pulp pellets (CPP) using bacterial tag-encoded FLX amplicon pyrosequencing (bTEFAP)

USDA-ARS?s Scientific Manuscript database

The rumen microbial ecosystem has been extensively studied, but remains a mystery from a quantitative perspective. Dietary components and changes cause shifts in the ruminal microflora that can affect animal health and productivity, but the majority of these changes remain unknown. The objective of ...

Personnel Dose Assessment during Active Interrogation

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

Miller, Thomas Martin; Akkurt, Hatice; Patton, Bruce W

A leading candidate in the detection of special nuclear material (SNM) is active interrogation (AI). Unlike passive interrogation, AI uses a source to enhance or create a detectable signal from SNM (usually fission), particularly in shielded scenarios or scenarios where the SNM has a low activity. The use of AI thus makes the detection of SNM easier or, in some scenarios, even enables previously impossible detection. During the development of AI sources, significant effort is put into determining the source strength required to detect SNM in specific scenarios. Usually during this process, but not always, an evaluation of personnel dosemore » is also completed. In this instance personnel dose could involve any of the following: (1) personnel performing the AI; (2) unknown stowaways who are inside the object being interrogated; or (3) in clandestine interrogations, personnel who are known to be inside the object being interrogated but are unaware of the interrogation. In most instances, dose to anyone found smuggling SNM will be a secondary issue. However, for the organizations performing the AI, legal if not moral considerations should make dose to the personnel performing the AI, unknown stowaways, or innocent bystanders in clandestine interrogations a serious concern.« less

Functional cross‐hemispheric shift between object‐place paired associate memory and spatial memory in the human hippocampus

PubMed Central

Lee, Choong‐Hee; Ryu, Jungwon; Lee, Sang‐Hun; Kim, Hakjin

2016-01-01

ABSTRACT The hippocampus plays critical roles in both object‐based event memory and spatial navigation, but it is largely unknown whether the left and right hippocampi play functionally equivalent roles in these cognitive domains. To examine the hemispheric symmetry of human hippocampal functions, we used an fMRI scanner to measure BOLD activity while subjects performed tasks requiring both object‐based event memory and spatial navigation in a virtual environment. Specifically, the subjects were required to form object‐place paired associate memory after visiting four buildings containing discrete objects in a virtual plus maze. The four buildings were visually identical, and the subjects used distal visual cues (i.e., scenes) to differentiate the buildings. During testing, the subjects were required to identify one of the buildings when cued with a previously associated object, and when shifted to a random place, the subject was expected to navigate to the previously chosen building. We observed that the BOLD activity foci changed from the left hippocampus to the right hippocampus as task demand changed from identifying a previously seen object (object‐cueing period) to searching for its paired‐associate place (object‐cued place recognition period). Furthermore, the efficient retrieval of object‐place paired associate memory (object‐cued place recognition period) was correlated with the BOLD response of the left hippocampus, whereas the efficient retrieval of relatively pure spatial memory (spatial memory period) was correlated with the right hippocampal BOLD response. These findings suggest that the left and right hippocampi in humans might process qualitatively different information for remembering episodic events in space. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc. PMID:27009679

Summary of evidence-based guideline: Complementary and alternative medicine in multiple sclerosis

PubMed Central

Yadav, Vijayshree; Bever, Christopher; Bowen, James; Bowling, Allen; Weinstock-Guttman, Bianca; Cameron, Michelle; Bourdette, Dennis; Gronseth, Gary S.; Narayanaswami, Pushpa

2014-01-01

Objective: To develop evidence-based recommendations for complementary and alternative medicine (CAM) in multiple sclerosis (MS). Methods: We searched the literature (1970–March 2011; March 2011−September 2013 MEDLINE search), classified articles, and linked recommendations to evidence. Results and recommendations: Clinicians might offer oral cannabis extract for spasticity symptoms and pain (excluding central neuropathic pain) (Level A). Clinicians might offer tetrahydrocannabinol for spasticity symptoms and pain (excluding central neuropathic pain) (Level B). Clinicians should counsel patients that these agents are probably ineffective for objective spasticity (short-term)/tremor (Level B) and possibly effective for spasticity and pain (long-term) (Level C). Clinicians might offer Sativex oromucosal cannabinoid spray (nabiximols) for spasticity symptoms, pain, and urinary frequency (Level B). Clinicians should counsel patients that these agents are probably ineffective for objective spasticity/urinary incontinence (Level B). Clinicians might choose not to offer these agents for tremor (Level C). Clinicians might counsel patients that magnetic therapy is probably effective for fatigue and probably ineffective for depression (Level B); fish oil is probably ineffective for relapses, disability, fatigue, MRI lesions, and quality of life (QOL) (Level B); ginkgo biloba is ineffective for cognition (Level A) and possibly effective for fatigue (Level C); reflexology is possibly effective for paresthesia (Level C); Cari Loder regimen is possibly ineffective for disability, symptoms, depression, and fatigue (Level C); and bee sting therapy is possibly ineffective for relapses, disability, fatigue, lesion burden/volume, and health-related QOL (Level C). Cannabinoids may cause adverse effects. Clinicians should exercise caution regarding standardized vs nonstandardized cannabis extracts and overall CAM quality control/nonregulation. Safety/efficacy of other CAM/CAM interaction with MS disease-modifying therapies is unknown. PMID:24663230

Detecting unresolved binary stars in Euclid VIS images

NASA Astrophysics Data System (ADS)

Kuntzer, T.; Courbin, F.

2017-10-01

Measuring a weak gravitational lensing signal to the level required by the next generation of space-based surveys demands exquisite reconstruction of the point-spread function (PSF). However, unresolved binary stars can significantly distort the PSF shape. In an effort to mitigate this bias, we aim at detecting unresolved binaries in realistic Euclid stellar populations. We tested methods in numerical experiments where (I) the PSF shape is known to Euclid requirements across the field of view; and (II) the PSF shape is unknown. We drew simulated catalogues of PSF shapes for this proof-of-concept paper. Following the Euclid survey plan, the objects were observed four times. We propose three methods to detect unresolved binary stars. The detection is based on the systematic and correlated biases between exposures of the same object. One method is a simple correlation analysis, while the two others use supervised machine-learning algorithms (random forest and artificial neural network). In both experiments, we demonstrate the ability of our methods to detect unresolved binary stars in simulated catalogues. The performance depends on the level of prior knowledge of the PSF shape and the shape measurement errors. Good detection performances are observed in both experiments. Full complexity, in terms of the images and the survey design, is not included, but key aspects of a more mature pipeline are discussed. Finding unresolved binaries in objects used for PSF reconstruction increases the quality of the PSF determination at arbitrary positions. We show, using different approaches, that we are able to detect at least binary stars that are most damaging for the PSF reconstruction process. The code corresponding to the algorithms used in this work and all scripts to reproduce the results are publicly available from a GitHub repository accessible via http://lastro.epfl.ch/software

Stimulation of PPC Affects the Mapping between Motion and Force Signals for Stiffness Perception But Not Motion Control

PubMed Central

Mawase, Firas; Karniel, Amir; Donchin, Opher; Rothwell, John; Nisky, Ilana; Davare, Marco

2016-01-01

How motion and sensory inputs are combined to assess an object's stiffness is still unknown. Here, we provide evidence for the existence of a stiffness estimator in the human posterior parietal cortex (PPC). We showed previously that delaying force feedback with respect to motion when interacting with an object caused participants to underestimate its stiffness. We found that applying theta-burst transcranial magnetic stimulation (TMS) over the PPC, but not the dorsal premotor cortex, enhances this effect without affecting movement control. We explain this enhancement as an additional lag in force signals. This is the first causal evidence that the PPC is not only involved in motion control, but also has an important role in perception that is disassociated from action. We provide a computational model suggesting that the PPC integrates position and force signals for perception of stiffness and that TMS alters the synchronization between the two signals causing lasting consequences on perceptual behavior. SIGNIFICANCE STATEMENT When selecting an object such as a ripe fruit or sofa, we need to assess the object's stiffness. Because we lack dedicated stiffness sensors, we rely on an as yet unknown mechanism that generates stiffness percepts by combining position and force signals. Here, we found that the posterior parietal cortex (PPC) contributes to combining position and force signals for stiffness estimation. This finding challenges the classical view about the role of the PPC in regulating position signals only for motion control because we highlight a key role of the PPC in perception that is disassociated from action. Altogether this sheds light on brain mechanisms underlying the interaction between action and perception and may help in the development of better teleoperation systems and rehabilitation of patients with sensory impairments. PMID:27733607

Stimulation of PPC Affects the Mapping between Motion and Force Signals for Stiffness Perception But Not Motion Control.

PubMed

Leib, Raz; Mawase, Firas; Karniel, Amir; Donchin, Opher; Rothwell, John; Nisky, Ilana; Davare, Marco

2016-10-12

How motion and sensory inputs are combined to assess an object's stiffness is still unknown. Here, we provide evidence for the existence of a stiffness estimator in the human posterior parietal cortex (PPC). We showed previously that delaying force feedback with respect to motion when interacting with an object caused participants to underestimate its stiffness. We found that applying theta-burst transcranial magnetic stimulation (TMS) over the PPC, but not the dorsal premotor cortex, enhances this effect without affecting movement control. We explain this enhancement as an additional lag in force signals. This is the first causal evidence that the PPC is not only involved in motion control, but also has an important role in perception that is disassociated from action. We provide a computational model suggesting that the PPC integrates position and force signals for perception of stiffness and that TMS alters the synchronization between the two signals causing lasting consequences on perceptual behavior. When selecting an object such as a ripe fruit or sofa, we need to assess the object's stiffness. Because we lack dedicated stiffness sensors, we rely on an as yet unknown mechanism that generates stiffness percepts by combining position and force signals. Here, we found that the posterior parietal cortex (PPC) contributes to combining position and force signals for stiffness estimation. This finding challenges the classical view about the role of the PPC in regulating position signals only for motion control because we highlight a key role of the PPC in perception that is disassociated from action. Altogether this sheds light on brain mechanisms underlying the interaction between action and perception and may help in the development of better teleoperation systems and rehabilitation of patients with sensory impairments. Copyright © 2016 Leib et al.

Method for genetic identification of unknown organisms

DOEpatents

Colston, Jr., Billy W.; Fitch, Joseph P.; Hindson, Benjamin J.; Carter, Chance J.; Beer, Neil Reginald

2016-08-23

A method of rapid, genome and proteome based identification of unknown pathogenic or non-pathogenic organisms in a complex sample. The entire sample is analyzed by creating millions of emulsion encapsulated microdroplets, each containing a single pathogenic or non-pathogenic organism sized particle and appropriate reagents for amplification. Following amplification, the amplified product is analyzed.

Object Segmentation Methods for Online Model Acquisition to Guide Robotic Grasping

NASA Astrophysics Data System (ADS)

Ignakov, Dmitri

A vision system is an integral component of many autonomous robots. It enables the robot to perform essential tasks such as mapping, localization, or path planning. A vision system also assists with guiding the robot's grasping and manipulation tasks. As an increased demand is placed on service robots to operate in uncontrolled environments, advanced vision systems must be created that can function effectively in visually complex and cluttered settings. This thesis presents the development of segmentation algorithms to assist in online model acquisition for guiding robotic manipulation tasks. Specifically, the focus is placed on localizing door handles to assist in robotic door opening, and on acquiring partial object models to guide robotic grasping. First, a method for localizing a door handle of unknown geometry based on a proposed 3D segmentation method is presented. Following segmentation, localization is performed by fitting a simple box model to the segmented handle. The proposed method functions without requiring assumptions about the appearance of the handle or the door, and without a geometric model of the handle. Next, an object segmentation algorithm is developed, which combines multiple appearance (intensity and texture) and geometric (depth and curvature) cues. The algorithm is able to segment objects without utilizing any a priori appearance or geometric information in visually complex and cluttered environments. The segmentation method is based on the Conditional Random Fields (CRF) framework, and the graph cuts energy minimization technique. A simple and efficient method for initializing the proposed algorithm which overcomes graph cuts' reliance on user interaction is also developed. Finally, an improved segmentation algorithm is developed which incorporates a distance metric learning (DML) step as a means of weighing various appearance and geometric segmentation cues, allowing the method to better adapt to the available data. The improved method also models the distribution of 3D points in space as a distribution of algebraic distances from an ellipsoid fitted to the object, improving the method's ability to predict which points are likely to belong to the object or the background. Experimental validation of all methods is performed. Each method is evaluated in a realistic setting, utilizing scenarios of various complexities. Experimental results have demonstrated the effectiveness of the handle localization method, and the object segmentation methods.

A Mobile Anchor Assisted Localization Algorithm Based on Regular Hexagon in Wireless Sensor Networks

PubMed Central

Rodrigues, Joel J. P. C.

2014-01-01

Localization is one of the key technologies in wireless sensor networks (WSNs), since it provides fundamental support for many location-aware protocols and applications. Constraints of cost and power consumption make it infeasible to equip each sensor node in the network with a global position system (GPS) unit, especially for large-scale WSNs. A promising method to localize unknown nodes is to use several mobile anchors which are equipped with GPS units moving among unknown nodes and periodically broadcasting their current locations to help nearby unknown nodes with localization. This paper proposes a mobile anchor assisted localization algorithm based on regular hexagon (MAALRH) in two-dimensional WSNs, which can cover the whole monitoring area with a boundary compensation method. Unknown nodes calculate their positions by using trilateration. We compare the MAALRH with HILBERT, CIRCLES, and S-CURVES algorithms in terms of localization ratio, localization accuracy, and path length. Simulations show that the MAALRH can achieve high localization ratio and localization accuracy when the communication range is not smaller than the trajectory resolution. PMID:25133212

Approximation-Based Adaptive Neural Tracking Control of Nonlinear MIMO Unknown Time-Varying Delay Systems With Full State Constraints.

PubMed

Li, Da-Peng; Li, Dong-Juan; Liu, Yan-Jun; Tong, Shaocheng; Chen, C L Philip

2017-10-01

This paper deals with the tracking control problem for a class of nonlinear multiple input multiple output unknown time-varying delay systems with full state constraints. To overcome the challenges which cause by the appearances of the unknown time-varying delays and full-state constraints simultaneously in the systems, an adaptive control method is presented for such systems for the first time. The appropriate Lyapunov-Krasovskii functions and a separation technique are employed to eliminate the effect of unknown time-varying delays. The barrier Lyapunov functions are employed to prevent the violation of the full state constraints. The singular problems are dealt with by introducing the signal function. Finally, it is proven that the proposed method can both guarantee the good tracking performance of the systems output, all states are remained in the constrained interval and all the closed-loop signals are bounded in the design process based on choosing appropriate design parameters. The practicability of the proposed control technique is demonstrated by a simulation study in this paper.

Identification and properties of host galaxies of RCR radio sources

NASA Astrophysics Data System (ADS)

Zhelenkova, O. P.; Soboleva, N. S.; Majorova, E. K.; Temirova, A. V.

2013-01-01

FIRST and NVSS radio maps are used to cross identify the radio sources of the RCR catalog, which is based on observational data obtained in several runs of the "Cold" survey, with the SDSS and DPOSS digital optical sky surveys and the 2MASS, LAS UKIDSS, and WISE infrared surveys. Digital images in various filters and the coadded gri-band SDSS images, red and infrared DPOSS images, JHK-band UKIDSS images, and JHK-band 2MASS images are analyzed for the sources with no optical candidates found in the above catalogs. Our choice of optical candidates was based on the data on the structure of the radio source, its photometry, and spectroscopy (where available). We found reliable identifications for 86% of the radio sources; possible counterparts for 8% of the sources, and failed to find any optical counterparts for 6% of the sources because their host objects proved to be fainter than the limiting magnitude of the corresponding surveys. A little over half of all the identifications proved to be galaxies; about one quarter were quasars, and the types of the remaining objects were difficult to determine because of their faintness. A relation between the luminosity and the radioloudness index was derived and used to estimate the 1.4 and 3.94 GHz luminosities for the sources with unknown redshifts. We found 3% and 60% of all the RCR radio sources to be FRI-type objects ( L ≲ 1024 W/Hz at 1.4 GHz) and powerful FRII-type galaxies ( L ≳ 1026.5 W/Hz), respectively, whereas the rest are sources including objects of the FRI, FRII, and mixed FRI-FRII types. Unlike quasars, galaxies show a trend of decreasing luminosity with decreasing flux density. Note that identification would be quite problematic without the software and resources of the virtual observatory.

Grasping with a soft glove: intrinsic impedance control in pneumatic actuators

PubMed Central

2017-01-01

The interaction of a robotic manipulator with unknown soft objects represents a significant challenge for traditional robotic platforms because of the difficulty in controlling the grasping force between a soft object and a stiff manipulator. Soft robotic actuators inspired by elephant trunks, octopus limbs and muscular hydrostats are suggestive of ways to overcome this fundamental difficulty. In particular, the large intrinsic compliance of soft manipulators such as ‘pneu-nets’—pneumatically actuated elastomeric structures—makes them ideal for applications that require interactions with an uncertain mechanical and geometrical environment. Using a simple theoretical model, we show how the geometric and material nonlinearities inherent in the passive mechanical response of such devices can be used to grasp soft objects using force control, and stiff objects using position control, without any need for active sensing or feedback control. Our study is suggestive of a general principle for designing actuators with autonomous intrinsic impedance control. PMID:28250097

Distance estimation and collision prediction for on-line robotic motion planning

NASA Technical Reports Server (NTRS)

Kyriakopoulos, K. J.; Saridis, G. N.

1991-01-01

An efficient method for computing the minimum distance and predicting collisions between moving objects is presented. This problem has been incorporated in the framework of an in-line motion planning algorithm to satisfy collision avoidance between a robot and moving objects modeled as convex polyhedra. In the beginning the deterministic problem, where the information about the objects is assumed to be certain is examined. If instead of the Euclidean norm, L(sub 1) or L(sub infinity) norms are used to represent distance, the problem becomes a linear programming problem. The stochastic problem is formulated, where the uncertainty is induced by sensing and the unknown dynamics of the moving obstacles. Two problems are considered: (1) filtering of the minimum distance between the robot and the moving object, at the present time; and (2) prediction of the minimum distance in the future, in order to predict possible collisions with the moving obstacles and estimate the collision time.

Uncertainty analysis in fault tree models with dependent basic events.

PubMed

Pedroni, Nicola; Zio, Enrico

2013-06-01

In general, two types of dependence need to be considered when estimating the probability of the top event (TE) of a fault tree (FT): "objective" dependence between the (random) occurrences of different basic events (BEs) in the FT and "state-of-knowledge" (epistemic) dependence between estimates of the epistemically uncertain probabilities of some BEs of the FT model. In this article, we study the effects on the TE probability of objective and epistemic dependences. The well-known Frèchet bounds and the distribution envelope determination (DEnv) method are used to model all kinds of (possibly unknown) objective and epistemic dependences, respectively. For exemplification, the analyses are carried out on a FT with six BEs. Results show that both types of dependence significantly affect the TE probability; however, the effects of epistemic dependence are likely to be overwhelmed by those of objective dependence (if present). © 2012 Society for Risk Analysis.

E-health and health care behaviour of parents of young children: a qualitative study

PubMed Central

van der Gugten, Anne C.; de Leeuw, Rob J. R. J.; Verheij, Theo J.M.; van der Ent, Cornelis K.; Kars, Marijke C.

2016-01-01

Objective Internet plays a huge role in providing information about health care problems. However, it is unknown how parents use and perceive the internet as a source of information and how this influences health care utilisation when it comes to common complaints in infants. The objective was to evaluate the perception parents have on the role of internet in providing health care information on common symptoms in infants and its effects on health care utilisation. Design A qualitative design was chosen. Setting and subjects Parents were recruited from a population-based birth-cohort and selected purposefully. Main outcome measures Semi-structured interviews were used to receive information of parentsʼ ideas. Thematic coding and constant comparison were used for interview transcript analysis. Results Ten parents were interviewed. Parents felt anxious and responsible when their child displayed common symptoms, and appeared to be in need of information. They tried to obtain information from relatives, but more so from the internet, because of its accessibility. Nevertheless, information found on the internet had several limitations, evoked new doubts and insecurity and although parents compared information from multiple sources, only the physician was able to take away the insecurity. The internet did not interfere in the decision to consult the physician. Conclusions Parents need information about their childrenʼs symptoms and the internet is a major resource. However, only physicians could take away their symptom-related doubts and insecurities and internet information did not play a role in parental decision making. Information gathered online may complement the information from physicians, rather than replace it. Key pointsInternet plays an increasing role in providing health care information but it is unknown how this influences health care utilisation.Our study suggests that:Parents need information about their children’s symptoms and the internet is a major resource.However, only physicians could take away their symptom-related doubts and insecurities.Internet information did not play a role in parental decision making. PMID:27063729

Motor unit number index (MUNIX) derivation from the relationship between the area and power of surface electromyogram: a computer simulation and clinical study

NASA Astrophysics Data System (ADS)

Miralles, Francesc

2018-06-01

Objective. The motor unit number index (MUNIX) is a technique based on the surface electromyogram (sEMG) that is gaining acceptance as a method for monitoring motor neuron loss, because it is reliable and produces less discomfort than other electrodiagnostic techniques having the same intended purpose. MUNIX assumes that the relationship between the area of sEMG obtained at increasing levels of muscle activation and the values of a variable called ‘ideal case motor unit count’ (ICMUC), defined as the product of the ratio between area and power of the compound muscle action potential (CMAP) by that of the sEMG, is described by a decreasing power function. Nevertheless, the reason for this comportment is unknown. The objective of this work is to investigate if the definition of MUNIX could derive from more basic properties of the sEMG. Approach. The CMAP and sEMG epochs obtained at different levels of muscle activation from (1) the abductor pollicis brevis (APB) muscle of persons with and without a carpal tunnel syndrome (CTS) and (2) from a computer model of sEMG generation previously published were analysed. Main results. MUNIX reflects the power relationship existing between the area and power of a sEMG. The exponent of this function was smaller in patients with motor CTS than in the rest of the subjects. The analysis of the relationship between the area and power of a sEMG could aid in distinguishing a MUNIX reduction due to a motoneuron loss from that due to a loss of muscle fibre. Significance. MUNIX is derived from the relationship between the area and power of a sEMG. This relationship changes when there is a loss of motor units (MUs), which partially explains the diagnostic sensibility of MUNIX. Although the reasons for this change are unknown, it could reflect an increase in the proportion of MUs of great amplitude.

Dynamic motion planning of 3D human locomotion using gradient-based optimization.

PubMed

Kim, Hyung Joo; Wang, Qian; Rahmatalla, Salam; Swan, Colby C; Arora, Jasbir S; Abdel-Malek, Karim; Assouline, Jose G

2008-06-01

Since humans can walk with an infinite variety of postures and limb movements, there is no unique solution to the modeling problem to predict human gait motions. Accordingly, we test herein the hypothesis that the redundancy of human walking mechanisms makes solving for human joint profiles and force time histories an indeterminate problem best solved by inverse dynamics and optimization methods. A new optimization-based human-modeling framework is thus described for predicting three-dimensional human gait motions on level and inclined planes. The basic unknowns in the framework are the joint motion time histories of a 25-degree-of-freedom human model and its six global degrees of freedom. The joint motion histories are calculated by minimizing an objective function such as deviation of the trunk from upright posture that relates to the human model's performance. A variety of important constraints are imposed on the optimization problem, including (1) satisfaction of dynamic equilibrium equations by requiring the model's zero moment point (ZMP) to lie within the instantaneous geometrical base of support, (2) foot collision avoidance, (3) limits on ground-foot friction, and (4) vanishing yawing moment. Analytical forms of objective and constraint functions are presented and discussed for the proposed human-modeling framework in which the resulting optimization problems are solved using gradient-based mathematical programming techniques. When the framework is applied to the modeling of bipedal locomotion on level and inclined planes, acyclic human walking motions that are smooth and realistic as opposed to less natural robotic motions are obtained. The aspects of the modeling framework requiring further investigation and refinement, as well as potential applications of the framework in biomechanics, are discussed.

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities.

PubMed

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.