A priori knowledge and the Kochen-Specker theorem

International Nuclear Information System (INIS)

Brunet, Olivier

2007-01-01

We introduce and formalize a notion of 'a priori knowledge' about a quantum system, and show some properties about this form of knowledge. Finally, we show that the Kochen-Specker theorem follows directly from this study

Random neural Q-learning for obstacle avoidance of a mobile robot in unknown environments

Directory of Open Access Journals (Sweden)

Jing Yang

2016-07-01

Full Text Available The article presents a random neural Q-learning strategy for the obstacle avoidance problem of an autonomous mobile robot in unknown environments. In the proposed strategy, two independent modules, namely, avoidance without considering the target and goal-seeking without considering obstacles, are first trained using the proposed random neural Q-learning algorithm to obtain their best control policies. Then, the two trained modules are combined based on a switching function to realize the obstacle avoidance in unknown environments. For the proposed random neural Q-learning algorithm, a single-hidden layer feedforward network is used to approximate the Q-function to estimate the Q-value. The parameters of the single-hidden layer feedforward network are modified using the recently proposed neural algorithm named the online sequential version of extreme learning machine, where the parameters of the hidden nodes are assigned randomly and the sample data can come one by one. However, different from the original online sequential version of extreme learning machine algorithm, the initial output weights are estimated subjected to quadratic inequality constraint to improve the convergence speed. Finally, the simulation results demonstrate that the proposed random neural Q-learning strategy can successfully solve the obstacle avoidance problem. Also, the higher learning efficiency and better generalization ability are achieved by the proposed random neural Q-learning algorithm compared with the Q-learning based on the back-propagation method.

Total Evidence, Uncertainty and A Priori Beliefs

NARCIS (Netherlands)

Bewersdorf, Benjamin; Felline, Laura; Ledda, Antonio; Paoli, Francesco; Rossanese, Emanuele

2016-01-01

Defining the rational belief state of an agent in terms of her initial or a priori belief state as well as her total evidence can help to address a number of important philosophical problems. In this paper, I discuss how this strategy can be applied to cases in which evidence is uncertain. I argue

Autonomous Underwater Navigation and Optical Mapping in Unknown Natural Environments

Directory of Open Access Journals (Sweden)

Juan David Hernández

2016-07-01

Full Text Available We present an approach for navigating in unknown environments while, simultaneously, gathering information for inspecting underwater structures using an autonomous underwater vehicle (AUV. To accomplish this, we first use our pipeline for mapping and planning collision-free paths online, which endows an AUV with the capability to autonomously acquire optical data in close proximity. With that information, we then propose a reconstruction pipeline to create a photo-realistic textured 3D model of the inspected area. These 3D models are also of particular interest to other fields of study in marine sciences, since they can serve as base maps for environmental monitoring, thus allowing change detection of biological communities and their environment over time. Finally, we evaluate our approach using the Sparus II, a torpedo-shaped AUV, conducting inspection missions in a challenging, real-world and natural scenario.

A Priori Regularity of Parabolic Partial Differential Equations

KAUST Repository

Berkemeier, Francisco

2018-01-01

In this thesis, we consider parabolic partial differential equations such as the heat equation, the Fokker-Planck equation, and the porous media equation. Our aim is to develop methods that provide a priori estimates for solutions with singular

Trajectory Planning of Mobile robot in Unstructured Environment for Multiple Objects

Directory of Open Access Journals (Sweden)

Muhammad Arshad

2012-01-01

Full Text Available In this paper we have presented a novel technique for the navigation and path formulation of wheeled mobile robot. In a given environment having obstacles, a path is generated from the given initial and final position of the robot. Based on the global knowledge of the environment a global path is formulated initially. This global path considers all the known obstacles in the environment and must avoid collision with these obstacles, i.e. the formulated path must be safe (collision free. For global path formulation strategic schemes have been employed using the a priori knowledge of the environment. The global path is fed to the robot. When unknown obstacles come in the path of the robot, it must deviate from the given global path and should generate a local path to avoid collision with the new unknown obstacle. By using sensors data the reactive schemes have been implemented for local path formulation. For local path formulation the path has been subdivided into intermediate steps known as sub goals. In the existing approaches known and unknown objects are considered separately. But in some of the practical applications known and unknown objects need to be considered simultaneously. This paper considers the problem of robot motion formulation in an environment having already known obstacles and unknown new moving objects. A Novel algorithm has been developed which incorporates local path planner, optimization and navigation modules. As unknown objects can appear in the environment randomly therefore uncertainty in the environment has been considered.

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

Science.gov (United States)

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.

Intention to use a fully automated car: attitudes and a priori acceptability

OpenAIRE

PAYRE, William; CESTAC, Julien; DELHOMME, Patricia

2014-01-01

If previous research studied acceptability of partially or highly automated driving, few of them focused on fully automated driving (FAD), including the ability to master longitudinal control, lateral control and maneuvers. The present study analyzes a priori acceptability, attitudes, personality traits and intention to use a fully automated vehicle. 421 French drivers (153 males, M= 40.2 years, age range 19-73) answered an online questionnaire. 68.1% of the sample a priori accepted FAD. P...

Kidnapping Detection and Recognition in Previous Unknown Environment

Directory of Open Access Journals (Sweden)

Yang Tian

2017-01-01

Full Text Available An unaware event referred to as kidnapping makes the estimation result of localization incorrect. In a previous unknown environment, incorrect localization result causes incorrect mapping result in Simultaneous Localization and Mapping (SLAM by kidnapping. In this situation, the explored area and unexplored area are divided to make the kidnapping recovery difficult. To provide sufficient information on kidnapping, a framework to judge whether kidnapping has occurred and to identify the type of kidnapping with filter-based SLAM is proposed. The framework is called double kidnapping detection and recognition (DKDR by performing two checks before and after the “update” process with different metrics in real time. To explain one of the principles of DKDR, we describe a property of filter-based SLAM that corrects the mapping result of the environment using the current observations after the “update” process. Two classical filter-based SLAM algorithms, Extend Kalman Filter (EKF SLAM and Particle Filter (PF SLAM, are modified to show that DKDR can be simply and widely applied in existing filter-based SLAM algorithms. Furthermore, a technique to determine the adapted thresholds of metrics in real time without previous data is presented. Both simulated and experimental results demonstrate the validity and accuracy of the proposed method.

Practical interior tomography with radial Hilbert filtering and a priori knowledge in a small round area.

Science.gov (United States)

Tang, Shaojie; Yang, Yi; Tang, Xiangyang

2012-01-01

Interior tomography problem can be solved using the so-called differentiated backprojection-projection onto convex sets (DBP-POCS) method, which requires a priori knowledge within a small area interior to the region of interest (ROI) to be imaged. In theory, the small area wherein the a priori knowledge is required can be in any shape, but most of the existing implementations carry out the Hilbert filtering either horizontally or vertically, leading to a vertical or horizontal strip that may be across a large area in the object. In this work, we implement a practical DBP-POCS method with radial Hilbert filtering and thus the small area with the a priori knowledge can be roughly round (e.g., a sinus or ventricles among other anatomic cavities in human or animal body). We also conduct an experimental evaluation to verify the performance of this practical implementation. We specifically re-derive the reconstruction formula in the DBP-POCS fashion with radial Hilbert filtering to assure that only a small round area with the a priori knowledge be needed (namely radial DBP-POCS method henceforth). The performance of the practical DBP-POCS method with radial Hilbert filtering and a priori knowledge in a small round area is evaluated with projection data of the standard and modified Shepp-Logan phantoms simulated by computer, followed by a verification using real projection data acquired by a computed tomography (CT) scanner. The preliminary performance study shows that, if a priori knowledge in a small round area is available, the radial DBP-POCS method can solve the interior tomography problem in a more practical way at high accuracy. In comparison to the implementations of DBP-POCS method demanding the a priori knowledge in horizontal or vertical strip, the radial DBP-POCS method requires the a priori knowledge within a small round area only. Such a relaxed requirement on the availability of a priori knowledge can be readily met in practice, because a variety of small

Mediterranean Diet and Cardiovascular Disease: A Critical Evaluation of A Priori Dietary Indexes

Science.gov (United States)

D’Alessandro, Annunziata; De Pergola, Giovanni

2015-01-01

The aim of this paper is to analyze the a priori dietary indexes used in the studies that have evaluated the role of the Mediterranean Diet in influencing the risk of developing cardiovascular disease. All the studies show that this dietary pattern protects against cardiovascular disease, but studies show quite different effects on specific conditions such as coronary heart disease or cerebrovascular disease. A priori dietary indexes used to measure dietary exposure imply quantitative and/or qualitative divergences from the traditional Mediterranean Diet of the early 1960s, and, therefore, it is very difficult to compare the results of different studies. Based on real cultural heritage and traditions, we believe that the a priori indexes used to evaluate adherence to the Mediterranean Diet should consider classifying whole grains and refined grains, olive oil and monounsaturated fats, and wine and alcohol differently. PMID:26389950

A concept for automated nanoscale atomic force microscope (AFM) measurements using a priori knowledge

International Nuclear Information System (INIS)

Recknagel, C; Rothe, H

2009-01-01

The nanometer coordinate measuring machine (NCMM) is developed for comparatively fast large area scans with high resolution. The system combines a metrological atomic force microscope (AFM) with a precise positioning system. The sample is moved under the probe system via the positioning system achieving a scan range of 25 × 25 × 5 mm 3 with a resolution of 0.1 nm. A concept for AFM measurements using a priori knowledge is implemented. The a priori knowledge is generated through measurements with a white light interferometer and the use of CAD data. Dimensional markup language is used as a transfer and target format for a priori knowledge and measurement data. Using the a priori knowledge and template matching algorithms combined with the optical microscope of the NCMM, the region of interest can automatically be identified. In the next step the automatic measurement of the part coordinate system and the measurement elements with the AFM sensor of the NCMM is done. The automatic measurement involves intelligent measurement strategies, which are adapted to specific geometries of the measurement feature to reduce measurement time and drift effects

Mediterranean Diet and Cardiovascular Disease: A Critical Evaluation of A Priori Dietary Indexes

Directory of Open Access Journals (Sweden)

Annunziata D'Alessandro

2015-09-01

Full Text Available The aim of this paper is to analyze the a priori dietary indexes used in the studies that have evaluated the role of the Mediterranean Diet in influencing the risk of developing cardiovascular disease. All the studies show that this dietary pattern protects against cardiovascular disease, but studies show quite different effects on specific conditions such as coronary heart disease or cerebrovascular disease. A priori dietary indexes used to measure dietary exposure imply quantitative and/or qualitative divergences from the traditional Mediterranean Diet of the early 1960s, and, therefore, it is very difficult to compare the results of different studies. Based on real cultural heritage and traditions, we believe that the a priori indexes used to evaluate adherence to the Mediterranean Diet should consider classifying whole grains and refined grains, olive oil and monounsaturated fats, and wine and alcohol differently.

The determination of an unknown boundary condition in a fractional diffusion equation

KAUST Repository

Rundell, William

2013-07-01

In this article we consider an inverse boundary problem, in which the unknown boundary function ∂u/∂v = f(u) is to be determined from overposed data in a time-fractional diffusion equation. Based upon the free space fundamental solution, we derive a representation for the solution f as a nonlinear Volterra integral equation of second kind with a weakly singular kernel. Uniqueness and reconstructibility by iteration is an immediate result of a priori assumption on f and applying the fixed point theorem. Numerical examples are presented to illustrate the validity and effectiveness of the proposed method. © 2013 Copyright Taylor and Francis Group, LLC.

Introduction of a priori information in the elastic linearized inversion of seismic data before stacking; Introduction d'informations a priori dans l'inversion linearisee elastique de donnees sismiques de surface avant sommation

Energy Technology Data Exchange (ETDEWEB)

Tonellot, Th.L.

2000-03-24

In this thesis, we propose a method which takes into account a priori information (geological, diagraphic and stratigraphic knowledge) in linearized pre-stack seismic data inversion. The approach is based on a formalism in which the a priori information is incorporated in an a priori model of elastic parameters - density, P and S impedances - and a model covariance operator which describes the uncertainties in the model. The first part of the thesis is dedicated to the study of this covariance operator and to the norm associated to its inverse. We have generalized the exponential covariance operator in order to describe the uncertainties in the a priori model elastic parameters and their correlations at each location. We give the analytical expression of the covariance operator inverse in 1-D, 2-D, and 3-D, and we discretized the associated norm with a finite element method. The second part is dedicated to synthetic and real examples. In a preliminary step, we have developed a pre-stack data well calibration method which allows the estimation of the source signal. The impact of different a priori information is then demonstrated on synthetic and real data. (author)

Conventional Principles in Science: On the foundations and development of the relativized a priori

Science.gov (United States)

Ivanova, Milena; Farr, Matt

2015-11-01

The present volume consists of a collection of papers originally presented at the conference Conventional Principles in Science, held at the University of Bristol, August 2011, which featured contributions on the history and contemporary development of the notion of 'relativized a priori' principles in science, from Henri Poincaré's conventionalism to Michael Friedman's contemporary defence of the relativized a priori. In Science and Hypothesis, Poincaré assessed the problematic epistemic status of Euclidean geometry and Newton's laws of motion, famously arguing that each has the status of 'convention' in that their justification is neither analytic nor empirical in nature. In The Theory of Relativity and A Priori Knowledge, Hans Reichenbach, in light of the general theory of relativity, proposed an updated notion of the Kantian synthetic a priori to account for the dynamic inter-theoretic status of geometry and other non-empirical physical principles. Reichenbach noted that one may reject the 'necessarily true' aspect of the synthetic a priori whilst preserving the feature of being constitutive of the object of knowledge. Such constitutive principles are theory-relative, as illustrated by the privileged role of non-Euclidean geometry in general relativity theory. This idea of relativized a priori principles in spacetime physics has been analysed and developed at great length in the modern literature in the work of Michael Friedman, in particular the roles played by the light postulate and the equivalence principle - in special and general relativity respectively - in defining the central terms of their respective theories and connecting the abstract mathematical formalism of the theories with their empirical content. The papers in this volume guide the reader through the historical development of conventional and constitutive principles in science, from the foundational work of Poincaré, Reichenbach and others, to contemporary issues and applications of the

Sensitivity of the OMI ozone profile retrieval (OMO3PR) to a priori assumptions

NARCIS (Netherlands)

Mielonen, T.; De Haan, J.F.; Veefkind, J.P.

2014-01-01

We have assessed the sensitivity of the operational OMI ozone profile retrieval (OMO3PR) algorithm to a number of a priori assumptions. We studied the effect of stray light correction, surface albedo assumptions and a priori ozone profiles on the retrieved ozone profile. Then, we studied how to

A Priori Knowledge and Heuristic Reasoning in Architectural Design.

Science.gov (United States)

Rowe, Peter G.

1982-01-01

It is proposed that the various classes of a priori knowledge incorporated in heuristic reasoning processes exert a strong influence over architectural design activity. Some design problems require exercise of some provisional set of rules, inference, or plausible strategy which requires heuristic reasoning. A case study illustrates this concept.…

Time-discrete higher order ALE formulations: a priori error analysis

KAUST Repository

Bonito, Andrea; Kyza, Irene; Nochetto, Ricardo H.

2013-01-01

We derive optimal a priori error estimates for discontinuous Galerkin (dG) time discrete schemes of any order applied to an advection-diffusion model defined on moving domains and written in the Arbitrary Lagrangian Eulerian (ALE) framework. Our

Razonamiento a priori y argumento ontológico en Antonio Rosmini

Directory of Open Access Journals (Sweden)

Juan F. Franck

2013-11-01

Full Text Available Rosmini’s criticism of the ontological argument finds its place between those of Aquinas and of Kant. With the former he shares the denial of the evidence of God’s essence quoad nos, and with the latter, his acknowledgment of the decisive character of the nucleus of the ontological argument for all other proofs of God’s existence. Such nucleus consists for Rosmini in the possibility of developing an a priori reasoning, different from the ontological one, be it in its Anselmian, Cartesian or Leibnizian form, which would justify the validity of the other proofs and the fascination exercised by the ontological argument. Key words: A Priori Reasoning, Ontological Argument, Antonio Rosmini.

Psicoanálisis y filosofía: el problema del a priori de la investigación en Heidegger y Winnicott Psychoanalysis and philosophy: the problem of a priori research in Heidegger and Winnicott

Directory of Open Access Journals (Sweden)

Julieta Bareiro

2011-12-01

Full Text Available El presente trabajo intenta presentar la relación entre saber psicoanalítico y filosofía a partir de un diálogo entre Winnicott y Heidegger. Para ello se llevará a cabo dos reconstrucciones argumentativas. En primer lugar, se expondrá el modo en que Heidegger determina el carácter a priori de su investigación. En segundo lugar, se hará un recorrido por la obra de Winnicott a fin de determinar cómo concibe el vínculo entre psicoanálisis y filosofía y, fundamentalmente, para establecer si hay lugar en su pensamiento para un a priori que permita trazar un vínculo con la filosofía.This paper aims to present the relationship between psychoanalytic knowledge and philosophy through to dialogue between Winnicott and Heidegger. This will take place two reconstructions argumentative. First, it exposed the way in which Heidegger determines the a priori character of their research. Secondly, it will go through to Winnicott´s work to determine how he conceives the relationship between psychoanalysis and philosophy and, crucially, to establish if a form in their thinking to a priori that allows a link with philosophy.

Incorporating a priori knowledge into initialized weights for neural classifier

NARCIS (Netherlands)

Chen, Zhe; Feng, T.J.; Feng, Tian-Jin; Houkes, Z.

2000-01-01

Artificial neural networks (ANN), especially, multilayer perceptrons (MLP) have been widely used in pattern recognition and classification. Nevertheless, how to incorporate a priori knowledge in the design of ANNs is still an open problem. The paper tries to give some insight on this topic

A Frequency Matching Method for Generation of a Priori Sample Models from Training Images

DEFF Research Database (Denmark)

Lange, Katrine; Cordua, Knud Skou; Frydendall, Jan

2011-01-01

This paper presents a Frequency Matching Method (FMM) for generation of a priori sample models based on training images and illustrates its use by an example. In geostatistics, training images are used to represent a priori knowledge or expectations of models, and the FMM can be used to generate...... new images that share the same multi-point statistics as a given training image. The FMM proceeds by iteratively updating voxel values of an image until the frequency of patterns in the image matches the frequency of patterns in the training image; making the resulting image statistically...... indistinguishable from the training image....

Elimination of hidden a priori information from remotely sensed profile data

Directory of Open Access Journals (Sweden)

T. von Clarmann

2007-01-01

Full Text Available Profiles of atmospheric state variables retrieved from remote measurements often contain a priori information which causes complication in the statistical use of data and in the comparison with other measured or modeled data. For such applications it often is desirable to remove the a priori information from the data product. If the retrieval involves an ill-posed inversion problem, formal removal of the a priori information requires resampling of the data on a coarser grid, which in some sense, however, is a prior constraint in itself. The fact that the trace of the averaging kernel matrix of a retrieval is equivalent to the number of degrees of freedom of the retrieval is used to define an appropriate information-centered representation of the data where each data point represents one degree of freedom. Since regridding implies further degradation of the data and thus causes additional loss of information, a re-regularization scheme has been developed which allows resampling without additional loss of information. For a typical ClONO2 profile retrieved from spectra as measured by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS, the constrained retrieval has 9.7 degrees of freedom. After application of the proposed transformation to a coarser information-centered altitude grid, there are exactly 9 degrees of freedom left, and the averaging kernel on the coarse grid is unity. Pure resampling on the information-centered grid without re-regularization would reduce the degrees of freedom to 7.1 (6.7 for a staircase (triangular representation scheme.

New a priori estimates for mean-field games with congestion

KAUST Repository

Evangelista, David; Gomes, Diogo A.

2016-01-01

We present recent developments in crowd dynamics models (e.g. pedestrian flow problems). Our formulation is given by a mean-field game (MFG) with congestion. We start by reviewing earlier models and results. Next, we develop our model. We establish new a priori estimates that give partial regularity of the solutions. Finally, we discuss numerical results.

New a priori estimates for mean-field games with congestion

KAUST Repository

Evangelista, David

2016-01-06

We present recent developments in crowd dynamics models (e.g. pedestrian flow problems). Our formulation is given by a mean-field game (MFG) with congestion. We start by reviewing earlier models and results. Next, we develop our model. We establish new a priori estimates that give partial regularity of the solutions. Finally, we discuss numerical results.

Full 3-D stratigraphic inversion with a priori information: a powerful way to optimize data integration

Energy Technology Data Exchange (ETDEWEB)

Grizon, L.; Leger, M.; Dequirez, P.Y.; Dumont, F.; Richard, V.

1998-12-31

Integration between seismic and geological data is crucial to ensure that a reservoir study is accurate and reliable. To reach this goal, there is used a post-stack stratigraphic inversion with a priori information. The global cost-function combines two types of constraints. One is relevant to seismic amplitudes, and the other to an a priori impedance model. This paper presents this flexible and interpretative inversion to determine acoustic impedances constrained by seismic data, log data and geologic information. 5 refs., 8 figs.

Why Even Mind? -- On The A Priori Value Of “Life”

Directory of Open Access Journals (Sweden)

Amien Kacou

2008-10-01

Full Text Available span style="font-size: 12pt; font-family: Arial"span style="font-weight: normal; font-size: 12pt; text-decoration: none"font face="Times New Roman"span style="font-size: 12pt; font-family: #39;Times New Roman#39;"This article presentsnbsp;an analysis of the matter of the ldquo;meaningrdquo; of life in terms of whether it should even be lived in the first place. It begins with an attempt at defining the question as an inquiry on the ema priori/em value of attention in general, and develops into an axiological reflection distantly inspired from Martin Heideggerrsquo;s notion of ldquo;care.rdquo; The main objective of the article is (1 to ldquo;answerrdquo; the question (or to proceed as if the question could be answered objectively by ldquo;playing alongrdquo; with its naiuml;ve logicmdash;that is, by finding a basis for comparing the good that can be found ema priori/em in life (mainly, pleasure with the good that can be found ema priori/em in death (mainly, the absence of painmdash;and, then, (2 to suggest why we have no good reason to feel dissatisfied with where this leaves us (i.e., possibly facing a certain specter of ethical foundationalism: the question of the ldquo;value of valuerdquo;. Its basic conclusion is, assuming we are committed to assigning value to life emin general/em, that we should be able to say that life is good emirrespective of /emany explanation for its existence./span/font/span/span

Monte Carlo full-waveform inversion of crosshole GPR data using multiple-point geostatistical a priori information

DEFF Research Database (Denmark)

Cordua, Knud Skou; Hansen, Thomas Mejer; Mosegaard, Klaus

2012-01-01

We present a general Monte Carlo full-waveform inversion strategy that integrates a priori information described by geostatistical algorithms with Bayesian inverse problem theory. The extended Metropolis algorithm can be used to sample the a posteriori probability density of highly nonlinear...... inverse problems, such as full-waveform inversion. Sequential Gibbs sampling is a method that allows efficient sampling of a priori probability densities described by geostatistical algorithms based on either two-point (e.g., Gaussian) or multiple-point statistics. We outline the theoretical framework......) Based on a posteriori realizations, complicated statistical questions can be answered, such as the probability of connectivity across a layer. (3) Complex a priori information can be included through geostatistical algorithms. These benefits, however, require more computing resources than traditional...

Plasma ascorbic acid, a priori diet quality score, and incident hypertension

NARCIS (Netherlands)

Buijsse, Brian; Jacobs, D.R.; Steffen, L.M.; Kromhout, Daan; Gross, M.D.

2015-01-01

Vitamin C may reduce risk of hypertension, either in itself or by marking a healthy diet pattern. We assessed whether plasma ascorbic acid and the a priori diet quality score relate to incident hypertension and whether they explain each other's predictive abilities. Data were from 2884 black and

On Evaluation of Recharge Model Uncertainty: a Priori and a Posteriori

International Nuclear Information System (INIS)

Ming Ye; Karl Pohlmann; Jenny Chapman; David Shafer

2006-01-01

Hydrologic environments are open and complex, rendering them prone to multiple interpretations and mathematical descriptions. Hydrologic analyses typically rely on a single conceptual-mathematical model, which ignores conceptual model uncertainty and may result in bias in predictions and under-estimation of predictive uncertainty. This study is to assess conceptual model uncertainty residing in five recharge models developed to date by different researchers based on different theories for Nevada and Death Valley area, CA. A recently developed statistical method, Maximum Likelihood Bayesian Model Averaging (MLBMA), is utilized for this analysis. In a Bayesian framework, the recharge model uncertainty is assessed, a priori, using expert judgments collected through an expert elicitation in the form of prior probabilities of the models. The uncertainty is then evaluated, a posteriori, by updating the prior probabilities to estimate posterior model probability. The updating is conducted through maximum likelihood inverse modeling by calibrating the Death Valley Regional Flow System (DVRFS) model corresponding to each recharge model against observations of head and flow. Calibration results of DVRFS for the five recharge models are used to estimate three information criteria (AIC, BIC, and KIC) used to rank and discriminate these models. Posterior probabilities of the five recharge models, evaluated using KIC, are used as weights to average head predictions, which gives posterior mean and variance. The posterior quantities incorporate both parametric and conceptual model uncertainties

Image reconstruction in electrostatic tomography using a priori knowledge from ECT

International Nuclear Information System (INIS)

Zhou Bin; Zhang Jianyong; Xu Chuanlong; Wang Shimin

2011-01-01

Research highlights: → A dual-mode sensor technique based on ECT and EST is proposed. → The interference of the charged particles to ECT can be eliminated. → A priori knowledge from ECT improves the inversion accuracy. - Abstract: In gas-solid two-phase flow, the charge distribution is a very important process parameter which is useful to the study of electrostatic adhesion. Electrostatic tomography (EST) is a relatively new non-intrusive technique which can be used to acquire charge distribution. However, due to limited measurements, the quality of image reconstruction is poor. In this paper, a dual-mode sensor technique based on electrical capacitance tomography (ECT) and EST is proposed. The theoretical analysis and the numerical simulation results reveal that the permittivity distribution obtained from ECT can provide a priori knowledge for the inversion calculation of EST, so that the accuracy of spatial sensitivity calculation in EST can be improved. This proposed technique is expected to be prospective in industrial applications and will also be beneficial to the research on the fluid dynamics of gas-solid two-phase flow.

Importance of A Priori Vertical Ozone Profiles for TEMPO Air Quality Retrievals

Science.gov (United States)

Johnson, M. S.; Sullivan, J. T.; Liu, X.; Zoogman, P.; Newchurch, M.; Kuang, S.; McGee, T. J.; Leblanc, T.

2017-12-01

Ozone (O3) is a toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address the limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product. TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME, GOME-2, and OMI. This algorithm is suggested to use a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB-Clim) O3 climatology). This study evaluates the TB-Clim dataset and model simulated O3 profiles, which could potentially serve as a priori O3 profile information in TEMPO retrievals, from near-real-time data assimilation model products (NASA GMAO's operational GEOS-5 FP model and reanalysis data from MERRA2) and a full chemical transport model (CTM), GEOS-Chem. In this study, vertical profile products are evaluated with surface (0-2 km) and tropospheric (0-10 km) TOLNet observations and the theoretical impact of individual a priori profile sources on the accuracy of TEMPO O3 retrievals in the troposphere and at the surface are presented. Results indicate that while the TB-Clim climatological dataset can replicate seasonally-averaged tropospheric O3 profiles, model-simulated profiles from a full CTM resulted in more accurate tropospheric and surface-level O3 retrievals from

A priori and a posteriori approaches in human reliability

International Nuclear Information System (INIS)

Griffon-Fouco, M.; Gagnolet, P.

1981-09-01

The French atomic energy commission (CEA) and the French supplier in electric power (EDF) have joint studies on human factors in nuclear safety. This paper deals with these studies which are a combination of two approaches: - An a posteriori approach so as to know the rate of human errors and their causes: an analysis of incident data banks and an analysis of human errors on simulator are presented. - An a priori approach so as to know the potential factors of human errors: an analysis of the control rooms design and an analysis of the writing of procedures are presented. The possibility to take into account these two approaches to prevent and quantify human errors is discussed

Profile reconstruction from neutron reflectivity data and a priori knowledge

International Nuclear Information System (INIS)

Leeb, H.

2008-01-01

The problem of incomplete and noisy information in profile reconstruction from neutron reflectometry data is considered. In particular methods of Bayesian statistics in combination with modelling or inverse scattering techniques are considered in order to properly include the required a priori knowledge to obtain quantitatively reliable estimates of the reconstructed profiles. Applying Bayes theorem the results of different experiments on the same sample can be consistently included in the profile reconstruction

LandScape: a simple method to aggregate p--Values and other stochastic variables without a priori grouping

DEFF Research Database (Denmark)

Wiuf, Carsten; Pallesen, Jonatan; Foldager, Leslie

2016-01-01

variables without assuming a priori defined groups. We provide different ways to evaluate the significance of the aggregated variables based on theoretical considerations and resampling techniques, and show that under certain assumptions the FWER is controlled in the strong sense. Validity of the method...... and the results might depend on the chosen criteria. Methods that summarize, or aggregate, test statistics or p-values, without relying on a priori criteria, are therefore desirable. We present a simple method to aggregate a sequence of stochastic variables, such as test statistics or p-values, into fewer...

Improving multiple-point-based a priori models for inverse problems by combining Sequential Simulation with the Frequency Matching Method

DEFF Research Database (Denmark)

Cordua, Knud Skou; Hansen, Thomas Mejer; Lange, Katrine

In order to move beyond simplified covariance based a priori models, which are typically used for inverse problems, more complex multiple-point-based a priori models have to be considered. By means of marginal probability distributions ‘learned’ from a training image, sequential simulation has...... proven to be an efficient way of obtaining multiple realizations that honor the same multiple-point statistics as the training image. The frequency matching method provides an alternative way of formulating multiple-point-based a priori models. In this strategy the pattern frequency distributions (i.......e. marginals) of the training image and a subsurface model are matched in order to obtain a solution with the same multiple-point statistics as the training image. Sequential Gibbs sampling is a simulation strategy that provides an efficient way of applying sequential simulation based algorithms as a priori...

Diffuse optical tomography with physiological and spatial a priori constraints

International Nuclear Information System (INIS)

Intes, Xavier; Maloux, Clemence; Guven, Murat; Yazici, Birzen; Chance, Britton

2004-01-01

Diffuse optical tomography is a typical inverse problem plagued by ill-condition. To overcome this drawback, regularization or constraining techniques are incorporated in the inverse formulation. In this work, we investigate the enhancement in recovering functional parameters by using physiological and spatial a priori constraints. More accurate recovery of the two main functional parameters that are the blood volume and the relative saturation is demonstrated through simulations by using our method compared to actual techniques. (note)

LMFBR safety criteria: cost-benefit considerations under the constraint of an a priori risk criterion

International Nuclear Information System (INIS)

Hartung, J.

1979-01-01

The role of cost-benefit considerations and a priori risk criteria as determinants of Core Disruptive Accident (CDA)-related safety criteria for large LMFBR's is explored with the aid of quantitative risk and probabilistic analysis methods. A methodology is described which allows a large number of design and siting alternatives to be traded off against each other with the goal of minimizing energy generation costs subject to the constraint of both an a priori risk criterion and a cost-benefit criterion. Application of this methodology to a specific LMFBR design project is described and the results are discussed. 5 refs

A hybrid search algorithm for swarm robots searching in an unknown environment.

Science.gov (United States)

Li, Shoutao; Li, Lina; Lee, Gordon; Zhang, Hao

2014-01-01

This paper proposes a novel method to improve the efficiency of a swarm of robots searching in an unknown environment. The approach focuses on the process of feeding and individual coordination characteristics inspired by the foraging behavior in nature. A predatory strategy was used for searching; hence, this hybrid approach integrated a random search technique with a dynamic particle swarm optimization (DPSO) search algorithm. If a search robot could not find any target information, it used a random search algorithm for a global search. If the robot found any target information in a region, the DPSO search algorithm was used for a local search. This particle swarm optimization search algorithm is dynamic as all the parameters in the algorithm are refreshed synchronously through a communication mechanism until the robots find the target position, after which, the robots fall back to a random searching mode. Thus, in this searching strategy, the robots alternated between two searching algorithms until the whole area was covered. During the searching process, the robots used a local communication mechanism to share map information and DPSO parameters to reduce the communication burden and overcome hardware limitations. If the search area is very large, search efficiency may be greatly reduced if only one robot searches an entire region given the limited resources available and time constraints. In this research we divided the entire search area into several subregions, selected a target utility function to determine which subregion should be initially searched and thereby reduced the residence time of the target to improve search efficiency.

Realism, functions, and the a priori: Ernst Cassirer's philosophy of science.

Science.gov (United States)

Heis, Jeremy

2014-12-01

This paper presents the main ideas of Cassirer's general philosophy of science, focusing on the two aspects of his thought that--in addition to being the most central ideas in his philosophy of science--have received the most attention from contemporary philosophers of science: his theory of the a priori aspects of physical theory, and his relation to scientific realism.

Geopositioning with a quadcopter: Extracted feature locations and predicted accuracy without a priori sensor attitude information

Science.gov (United States)

Dolloff, John; Hottel, Bryant; Edwards, David; Theiss, Henry; Braun, Aaron

2017-05-01

This paper presents an overview of the Full Motion Video-Geopositioning Test Bed (FMV-GTB) developed to investigate algorithm performance and issues related to the registration of motion imagery and subsequent extraction of feature locations along with predicted accuracy. A case study is included corresponding to a video taken from a quadcopter. Registration of the corresponding video frames is performed without the benefit of a priori sensor attitude (pointing) information. In particular, tie points are automatically measured between adjacent frames using standard optical flow matching techniques from computer vision, an a priori estimate of sensor attitude is then computed based on supplied GPS sensor positions contained in the video metadata and a photogrammetric/search-based structure from motion algorithm, and then a Weighted Least Squares adjustment of all a priori metadata across the frames is performed. Extraction of absolute 3D feature locations, including their predicted accuracy based on the principles of rigorous error propagation, is then performed using a subset of the registered frames. Results are compared to known locations (check points) over a test site. Throughout this entire process, no external control information (e.g. surveyed points) is used other than for evaluation of solution errors and corresponding accuracy.

Evaluating the effectiveness of a priori information on process measures in a virtual reality inspection task

Directory of Open Access Journals (Sweden)

Shannon Raye Bowling

2010-06-01

Full Text Available 72 1024x768 Normal 0 false false false Due to the nature of the complexity of the aircraft maintenance industry, much emphasis has been placed on improving aircraft inspection performance. One proven technique for improving inspection performance is the use of training. Several strategies have been implemented for training, one of which is giving feedforward information. The use of a priori (feedforward information is known to positively affect inspection performance (Ernst and Yovits, 1972; Long and Rourke, 1989; McKernan, 1989; Gramopadhye et al., 1997.  This information can consist of knowledge about defect characteristics (types, severity/criticality, and location and the probability of occurrence. Although several studies have been conducted that demonstrate the usefulness of feedforward as a training strategy, there are certain research issues that need to be addressed. This study evaluates the effects of feedforward information on process measures in a simulated 3-dimensional environment (aircraft cargo bay by the use of virtual reality.

Inverse identification of unknown finite-duration air pollutant release from a point source in urban environment

Science.gov (United States)

Kovalets, Ivan V.; Efthimiou, George C.; Andronopoulos, Spyros; Venetsanos, Alexander G.; Argyropoulos, Christos D.; Kakosimos, Konstantinos E.

2018-05-01

In this work, we present an inverse computational method for the identification of the location, start time, duration and quantity of emitted substance of an unknown air pollution source of finite time duration in an urban environment. We considered a problem of transient pollutant dispersion under stationary meteorological fields, which is a reasonable assumption for the assimilation of available concentration measurements within 1 h from the start of an incident. We optimized the calculation of the source-receptor function by developing a method which requires integrating as many backward adjoint equations as the available measurement stations. This resulted in high numerical efficiency of the method. The source parameters are computed by maximizing the correlation function of the simulated and observed concentrations. The method has been integrated into the CFD code ADREA-HF and it has been tested successfully by performing a series of source inversion runs using the data of 200 individual realizations of puff releases, previously generated in a wind tunnel experiment.

Approximate deconvolution model for the simulation of turbulent gas-solid flows: An a priori analysis

Science.gov (United States)

Schneiderbauer, Simon; Saeedipour, Mahdi

2018-02-01

Highly resolved two-fluid model (TFM) simulations of gas-solid flows in vertical periodic channels have been performed to study closures for the filtered drag force and the Reynolds-stress-like contribution stemming from the convective terms. An approximate deconvolution model (ADM) for the large-eddy simulation of turbulent gas-solid suspensions is detailed and subsequently used to reconstruct those unresolved contributions in an a priori manner. With such an approach, an approximation of the unfiltered solution is obtained by repeated filtering allowing the determination of the unclosed terms of the filtered equations directly. A priori filtering shows that predictions of the ADM model yield fairly good agreement with the fine grid TFM simulations for various filter sizes and different particle sizes. In particular, strong positive correlation (ρ > 0.98) is observed at intermediate filter sizes for all sub-grid terms. Additionally, our study reveals that the ADM results moderately depend on the choice of the filters, such as box and Gaussian filter, as well as the deconvolution order. The a priori test finally reveals that ADM is superior compared to isotropic functional closures proposed recently [S. Schneiderbauer, "A spatially-averaged two-fluid model for dense large-scale gas-solid flows," AIChE J. 63, 3544-3562 (2017)].

Evaluating A Priori Ozone Profile Information Used in TEMPO Tropospheric Ozone Retrievals

Science.gov (United States)

Johnson, Matthew S.; Sullivan, John T.; Liu, Xiong; Newchurch, Mike; Kuang, Shi; McGee, Thomas J.; Langford, Andrew O'Neil; Senff, Christoph J.; Leblanc, Thierry; Berkoff, Timothy;

Evaluating A Priori Ozone Profile Information Used in TEMPO Tropospheric Ozone Retrievals

Science.gov (United States)

Johnson, M. S.; Sullivan, J. T.; Liu, X.; Newchurch, M.; Kuang, S.; McGee, T. J.; Langford, A. O.; Senff, C. J.; Leblanc, T.; Berkoff, T.; Gronoff, G.; Chen, G.; Strawbridge, K. B.

2016-12-01

Ozone (O3) is a greenhouse gas and toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is primarily conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address these limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product. TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME, GOME-2, and OMI. This algorithm uses a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB) O3 climatology). It has been shown that satellite O3 retrievals are sensitive to a priori O3 profiles and covariance matrices. During this work we investigate the climatological data to be used in TEMPO algorithms (TB O3) and simulated data from the NASA GMAO Goddard Earth Observing System (GEOS-5) Forward Processing (FP) near-real-time (NRT) model products. These two data products will be evaluated with ground-based lidar data from the Tropospheric Ozone Lidar Network (TOLNet) at various locations of the US. This study evaluates the TB climatology, GEOS-5 climatology, and 3-hourly GEOS-5 data compared to lower tropospheric observations to demonstrate the accuracy of a priori information to potentially be used in TEMPO O3 algorithms. Here we present our initial analysis and the theoretical impact on TEMPO retrievals in the lower troposphere.

AUTONOMOUS UNMANNED HELICOPTER SYSTEM FOR REMOTE SENSING MISSIONS IN UNKNOWN ENVIRONMENTS

Directory of Open Access Journals (Sweden)

T. Merz

2012-09-01

Full Text Available This paper presents the design of an autonomous unmanned helicopter system for low-altitude remote sensing. The proposed concepts and methods are generic and not limited to a specific helicopter. The development was driven by the need for a dependable, modular, and affordable system with sufficient payload capacity suitable for both research and real-world deployment. The helicopter can be safely operated without a backup pilot in a contained area beyond visual range. This enables data collection in inaccessible or dangerous areas. Thanks to its terrain following and obstacle avoidance capability, the system does not require a priori information about terrain elevation and obstacles. Missions are specified in state diagrams and flight plans. We present performance characteristics of our system and show results of its deployment in real-world scenarios. We have successfully completed several dozen infrastructure inspection missions and crop monitoring missions facilitating plant phenomics studies.

The effect of a priori probability and complexity on decision making in a supervisory control task

NARCIS (Netherlands)

Kerstholt, J.H.; Passenier, P.O.; Houttuin, K.; Schuffel, H.

1996-01-01

In the present study we investigated how monitoring and fault management in a ship control task are affected by complexity and a priori probability of disturbances. Partici-pants were required to supervise four independent shipping subsystems and to adjust the subsystems whenever deviations

A Priori Regularity of Parabolic Partial Differential Equations

KAUST Repository

Berkemeier, Francisco

2018-05-13

In this thesis, we consider parabolic partial differential equations such as the heat equation, the Fokker-Planck equation, and the porous media equation. Our aim is to develop methods that provide a priori estimates for solutions with singular initial data. These estimates are obtained by understanding the time decay of norms of solutions. First, we derive regularity results for the heat equation by estimating the decay of Lebesgue norms. Then, we apply similar methods to the Fokker-Planck equation with suitable assumptions on the advection and diffusion. Finally, we conclude by extending our techniques to the porous media equation. The sharpness of our results is confirmed by examining known solutions of these equations. The main contribution of this thesis is the use of functional inequalities to express decay of norms as differential inequalities. These are then combined with ODE methods to deduce estimates for the norms of solutions and their derivatives.

Non-uniform Mutation Rates for Problems with Unknown Solution Lengths

DEFF Research Database (Denmark)

Cathabard, Stephan; Lehre, Per Kristian; Yao, Xin

2011-01-01

Many practical optimisation problems allow candidate solu- tions of varying lengths, and where the length of the opti- mal solution is thereby a priori unknown. We suggest that non-uniform mutation rates can be beneficial when solving such problems. In particular, we consider a mutation oper- ator...... that flips each bit with a probability that is inversely proportional to the bit position, rather than the bitstring length. The runtime of the (1+1) EA using this mutation operator is analysed rigorously on standard example func- tions. Furthermore, the behaviour of the new mutation op- erator...... distribution, and show that the new operator can yield exponentially faster runtimes for some parameters of this distribution. The experimental results show that the new mutation operator leads to dramatically shorter runtimes on a class of instances of the software engi- neering problem that is conjectured...

The Mediterranean Diet: its definition and evaluation of a priori dietary indexes in primary cardiovascular prevention.

Science.gov (United States)

D'Alessandro, Annunziata; De Pergola, Giovanni

2018-01-18

We have analysed the definition of Mediterranean Diet in 28 studies included in six meta-analyses evaluating the relation between the Mediterranean Diet and primary prevention of cardiovascular disease. Some typical food of this dietary pattern like whole cereals, olive oil and red wine were taken into account only in a few a priori indexes, and the dietary pattern defined as Mediterranean showed many differences among the studies and compared to traditional Mediterranean Diet of the early 1960s. Altogether, the analysed studies show a protective effect of the Mediterranean Diet against cardiovascular disease but present different effects against specific conditions as cerebrovascular disease and coronary heart disease. These different effects might depend on the definition of Mediterranean Diet and the indexes of the adhesion to the same one used. To compare the effects of the Mediterranean Diet against cardiovascular disease, coronary heart disease and stroke a univocal model of Mediterranean Diet should be established as a reference, and it might be represented by the Modern Mediterranean Diet Pyramid. The a priori index to evaluate the adhesion to Mediterranean Diet might be the Mediterranean-Style Dietary Pattern Score that has some advantages in comparison to the others a priori indexes.

Time-discrete higher order ALE formulations: a priori error analysis

KAUST Repository

Bonito, Andrea

2013-03-16

We derive optimal a priori error estimates for discontinuous Galerkin (dG) time discrete schemes of any order applied to an advection-diffusion model defined on moving domains and written in the Arbitrary Lagrangian Eulerian (ALE) framework. Our estimates hold without any restrictions on the time steps for dG with exact integration or Reynolds\\' quadrature. They involve a mild restriction on the time steps for the practical Runge-Kutta-Radau methods of any order. The key ingredients are the stability results shown earlier in Bonito et al. (Time-discrete higher order ALE formulations: stability, 2013) along with a novel ALE projection. Numerical experiments illustrate and complement our theoretical results. © 2013 Springer-Verlag Berlin Heidelberg.

Global a priori estimates for the inhomogeneous Landau equation with moderately soft potentials

Science.gov (United States)

Cameron, Stephen; Silvestre, Luis; Snelson, Stanley

2018-05-01

We establish a priori upper bounds for solutions to the spatially inhomogeneous Landau equation in the case of moderately soft potentials, with arbitrary initial data, under the assumption that mass, energy and entropy densities stay under control. Our pointwise estimates decay polynomially in the velocity variable. We also show that if the initial data satisfies a Gaussian upper bound, this bound is propagated for all positive times.

Considerations about expected a posteriori estimation in adaptive testing: adaptive a priori, adaptive correction for bias, and adaptive integration interval.

Science.gov (United States)

Raiche, Gilles; Blais, Jean-Guy

2009-01-01

In a computerized adaptive test, we would like to obtain an acceptable precision of the proficiency level estimate using an optimal number of items. Unfortunately, decreasing the number of items is accompanied by a certain degree of bias when the true proficiency level differs significantly from the a priori estimate. The authors suggest that it is possible to reduced the bias, and even the standard error of the estimate, by applying to each provisional estimation one or a combination of the following strategies: adaptive correction for bias proposed by Bock and Mislevy (1982), adaptive a priori estimate, and adaptive integration interval.

Robotic Services at Home: An Initialization System Based on Robots' Information and User Preferences in Unknown Environments

Directory of Open Access Journals (Sweden)

Nor Nur Safwati Mohd

2014-07-01

Full Text Available One important issue in robotic services is the construction of the robotic system in the actual environment. In other words, robots must perform environment sensing or have information on real objects, such as location and 3D dimensions, in order to live together with humans. It is crucial to have a mechanism to create an actual robotic system (intelligent space such that there is no initialization framework for the objects in the environment, or we have to perform SLAM and object recognition as well as mapping to generate a useful environmental database. In intelligent space research, normally the objects are attached to various sensors in order to extract the necessary information. However, that approach will highly depend on sensor accuracy and the robotic system will be burdened if there are too many sensors in an environment. Therefore, in this paper we present a system in which a robot can obtain information about an object and even create the furniture layout map for an unknown environment. Our approach is intended to improve home-based robotic services by taking into account the user or individual preferences for the Intelligent Space (IS. With this information, we can create an informational map of the home-based environment for the realization of robot assistance of humans in their daily activities at home, especially for disabled people. The result shows the system design and development in our approach by using model-based system engineering.

Comparative interpretations of renormalization inversion technique for reconstructing unknown emissions from measured atmospheric concentrations

Science.gov (United States)

Singh, Sarvesh Kumar; Kumar, Pramod; Rani, Raj; Turbelin, Grégory

2017-04-01

The study highlights a theoretical comparison and various interpretations of a recent inversion technique, called renormalization, developed for the reconstruction of unknown tracer emissions from their measured concentrations. The comparative interpretations are presented in relation to the other inversion techniques based on principle of regularization, Bayesian, minimum norm, maximum entropy on mean, and model resolution optimization. It is shown that the renormalization technique can be interpreted in a similar manner to other techniques, with a practical choice of a priori information and error statistics, while eliminating the need of additional constraints. The study shows that the proposed weight matrix and weighted Gram matrix offer a suitable deterministic choice to the background error and measurement covariance matrices, respectively, in the absence of statistical knowledge about background and measurement errors. The technique is advantageous since it (i) utilizes weights representing a priori information apparent to the monitoring network, (ii) avoids dependence on background source estimates, (iii) improves on alternative choices for the error statistics, (iv) overcomes the colocalization problem in a natural manner, and (v) provides an optimally resolved source reconstruction. A comparative illustration of source retrieval is made by using the real measurements from a continuous point release conducted in Fusion Field Trials, Dugway Proving Ground, Utah.

Verdad y apertura de mundo. El problema de los juicios sintéticos a priori tras el giro lingüístico

Directory of Open Access Journals (Sweden)

Cristina LAFONT

2009-11-01

Full Text Available RESUMEN: Este artículo analiza el impacto del giro lingüístico en la transformación de la concepción kantiana de los juicios sintéticos a priori. Se centra para ello en dos concepciones contemporáneas de los mismos, a saber, el a priori hermenéutico de Heidegger y el a priori contextual de Putnam, y saca a relucir expresamente tanto sus rasgos similares como sus importantes diferencias: mientras que la concepción heideggeriana mantiene el idealismo transcendental de Kant a través de la suposición hermenéutica de que el significado determina la referencia, la concepción de Putnam rompe por completo con la teoría kantiana de los juicios sintéticos a priori, según la cual éstos no pueden ser modificados por la sola experiencia, al tiempo que rechaza la suposición kantiana de que los juicios sintéticos a priori y aposteriori son dos clases permanentes de juicios. En contraste con Heidegger, Putnam es por eso capaz de mostrar que los juicios sintéticos apriori son modificables bajo condiciones especiales.ABSTRACT: This paper analyzes the impact of the linguistic turn in the transformation of the Kantian conception of the synthetic a priori. It focuses on two contemporary conceptions of the synthetic apriori, namely, Heidegger's hermeneutic apriori and Putnam's contextual apriori and shows their strikingly similar features as well as their important differences: whereas Heidegger's conception retains Kant's transcendental idealism via the hermeneutic assumption that meaning determines reference, Putnam's conception breaks entirely of Kant's conception fo synthetic a priori judgments, namely, that they cannot be revised by experience alone, while rejecting the Kantian assumption that synthetic apriori and aposteriori are permanent statuses of judgments. In contradistinction to Heidegger, Putnam is thus able to show that synthetic apriori judgments are revisable under special conditions.

Content analyses of a priori qualitative phantom limb pain descriptions and emerging categories in mid-southerners with limb loss.

Science.gov (United States)

Evans, Cecile B

2014-01-01

The purposes of this descriptive study were (a) to identify the relative frequencies of a priori categories of phantom limb pain (PLP) quality descriptors reported by Mid-Southerners with limb loss, (b) to analyze their descriptions for emerging categories of PLP, and (c) to identify the relative frequencies of the emerging categories. This cross-sectional descriptive verbal survey assessed PLP descriptors. A content analyses determined relative frequencies of a priori PLP descriptors as well as emerging categories that were identified. The most common a priori PLP quality descriptors reported by 52 amputees with PLP were intermittent, tingling/needles/numb, sharp, cramping, burning, and stabbing. The most common emerging categories reported were pain compared to illness/injury, electrical cyclical, and manipulated/positional. The detailed descriptions of PLP provide insight into the vivid experiences of PLP. Rehabilitation nurses can use this information with PLP assessment, patient teaching, and counseling. © 2013 Association of Rehabilitation Nurses.

Towards Improving Satellite Tropospheric NO2 Retrieval Products: Impacts of the spatial resolution and lighting NOx production from the a priori chemical transport model

Science.gov (United States)

Smeltzer, C. D.; Wang, Y.; Zhao, C.; Boersma, F.

2009-12-01

Polar orbiting satellite retrievals of tropospheric nitrogen dioxide (NO2) columns are important to a variety of scientific applications. These NO2 retrievals rely on a priori profiles from chemical transport models and radiative transfer models to derive the vertical columns (VCs) from slant columns measurements. In this work, we compare the retrieval results using a priori profiles from a global model (TM4) and a higher resolution regional model (REAM) at the OMI overpass hour of 1330 local time, implementing the Dutch OMI NO2 (DOMINO) retrieval. We also compare the retrieval results using a priori profiles from REAM model simulations with and without lightning NOx (NO + NO2) production. A priori model resolution and lightning NOx production are both found to have large impact on satellite retrievals by altering the satellite sensitivity to a particular observation by shifting the NO2 vertical distribution interpreted by the radiation model. The retrieved tropospheric NO2 VCs may increase by 25-100% in urban regions and be reduced by 50% in rural regions if the a priori profiles from REAM simulations are used during the retrievals instead of the profiles from TM4 simulations. The a priori profiles with lightning NOx may result in a 25-50% reduction of the retrieved tropospheric NO2 VCs compared to the a priori profiles without lightning. As first priority, a priori vertical NO2 profiles from a chemical transport model with a high resolution, which can better simulate urban-rural NO2 gradients in the boundary layer and make use of observation-based parameterizations of lightning NOx production, should be first implemented to obtain more accurate NO2 retrievals over the United States, where NOx source regions are spatially separated and lightning NOx production is significant. Then as consequence of a priori NO2 profile variabilities resulting from lightning and model resolution dynamics, geostationary satellite, daylight observations would further promote the next

Brezzi-Pitkaranta stabilization and a priori error analysis for the Stokes Control

Directory of Open Access Journals (Sweden)

Aytekin Cibik

2016-12-01

Full Text Available In this study, we consider a Brezzi-Pitkaranta stabilization scheme for the optimal control problem governed by stationary Stokes equation, using a P1-P1 interpolation for velocity and pressure. We express the stabilization as extra terms added to the discrete variational form of the problem.  We first prove the stability of the finite element discretization of the problem. Then, we derive a priori error bounds for each variable and present a numerical example to show the effectiveness of the stabilization clearly.

Contribution to restoration of degraded images by a space-variant system: use of an a priori model of the image

International Nuclear Information System (INIS)

Barakat, Valerie

1998-01-01

Imaging systems often present shift-variant point spread functions which are usually approximated by shift-invariant ones, in order to simplify the restoration problem. The aim of this thesis is to show that, if this shift-variant degradation is taken into account, it may increase strongly the quality of restoration. The imaging system is a pinhole, used to acquire images of high energy beams. Three restoration methods have been studied and compared: the Tikhonov-Miller regularization, the Markov-fields and the Maximum-Entropy methods. These methods are based on the incorporation of an a priori knowledge into the restoration process, to achieve stability of the solution. An improved restoration method is proposed: this approach is based on the Tikhonov-Miller regularization, combined with an a priori model of the solution. The idea of such a model is to express local characteristics to be reconstructed. The concept of parametric models described by a set of parameters (shape of the object, amplitude values,...) is used. A parametric optimization is used to find the optimal estimation of parameters close to the correct a priori information data of the expected solution. Several criteria have been proposed to measure the restoration quality. (author) [fr

Using A Priori Information to Improve Atmospheric Duct Estimation

Science.gov (United States)

Zhao, X.

2017-12-01

Knowledge of refractivity condition in the marine atmospheric boundary layer (MABL) is crucial for the prediction of radar and communication systems performance at frequencies above 1 GHz on low-altitude paths. Since early this century, the `refractivity from clutter (RFC)' technique has been proved to be an effective way to estimate the MABL refractivity structure. Refractivity model is very important for RFC techniques. If prior knowledge of the local refractivity information is available (e.g., from numerical weather prediction models, atmospheric soundings, etc.), more accurate parameterized refractivity model can be constructed by the statistical method, e.g. principal analysis, which in turn can be used to improve the quality of the local refractivity retrievals. This work extends the adjoint parabolic equation approach to range-varying atmospheric duct structure inversions, in which a linear empirical reduced-dimension refractivity model constructed from the a priori refractive information is used.

Tomographic inversion of time-domain resistivity and chargeability data for the investigation of landfills using a priori information.

Science.gov (United States)

De Donno, Giorgio; Cardarelli, Ettore

2017-01-01

In this paper, we present a new code for the modelling and inversion of resistivity and chargeability data using a priori information to improve the accuracy of the reconstructed model for landfill. When a priori information is available in the study area, we can insert them by means of inequality constraints on the whole model or on a single layer or assigning weighting factors for enhancing anomalies elongated in the horizontal or vertical directions. However, when we have to face a multilayered scenario with numerous resistive to conductive transitions (the case of controlled landfills), the effective thickness of the layers can be biased. The presented code includes a model-tuning scheme, which is applied after the inversion of field data, where the inversion of the synthetic data is performed based on an initial guess, and the absolute difference between the field and synthetic inverted models is minimized. The reliability of the proposed approach has been supported in two real-world examples; we were able to identify an unauthorized landfill and to reconstruct the geometrical and physical layout of an old waste dump. The combined analysis of the resistivity and chargeability (normalised) models help us to remove ambiguity due to the presence of the waste mass. Nevertheless, the presence of certain layers can remain hidden without using a priori information, as demonstrated by a comparison of the constrained inversion with a standard inversion. The robustness of the above-cited method (using a priori information in combination with model tuning) has been validated with the cross-section from the construction plans, where the reconstructed model is in agreement with the original design. Copyright © 2016 Elsevier Ltd. All rights reserved.

O Caráter a priori das Estruturas Necessárias ao Conhecimento, Construídas segundo a Epistemologia Genética

OpenAIRE

Marçal, Vicente Eduardo Ribeiro; Tassinari, Ricardo Pereira [UNESP

2014-01-01

In this paper we discuss the question of the a priori character of the necessary structures of knowledge according to Genetic Epistemology, focusing on the notion of space in particular. We establish some relations between Jean Piaget’s Genetic Epistemology and Immanuel Kant’s Critical Philosophy, discuss the notion of the a priori according to Kant in relation to the notion of space, and discuss the construction of the notion of space by the epistemic subject according to Genetic Epistemolog...

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

Science.gov (United States)

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.

Design of a DNA chip for detection of unknown genetically modified organisms (GMOs).

Science.gov (United States)

Nesvold, Håvard; Kristoffersen, Anja Bråthen; Holst-Jensen, Arne; Berdal, Knut G

2005-05-01

Unknown genetically modified organisms (GMOs) have not undergone a risk evaluation, and hence might pose a danger to health and environment. There are, today, no methods for detecting unknown GMOs. In this paper we propose a novel method intended as a first step in an approach for detecting unknown genetically modified (GM) material in a single plant. A model is designed where biological and combinatorial reduction rules are applied to a set of DNA chip probes containing all possible sequences of uniform length n, creating probes capable of detecting unknown GMOs. The model is theoretically tested for Arabidopsis thaliana Columbia, and the probabilities for detecting inserts and receiving false positives are assessed for various parameters for this organism. From a theoretical standpoint, the model looks very promising but should be tested further in the laboratory. The model and algorithms will be available upon request to the corresponding author.

A priori estimates of global solutions of superlinear parabolic systems

Directory of Open Access Journals (Sweden)

Julius Pacuta

2016-04-01

Full Text Available We consider the parabolic system $ u_{t}-\\Delta u = u^{r}v^{p}$, $v_{t}-\\Delta v = u^{q}v^{s}$ in $\\Omega\\times(0,\\infty$, complemented by the homogeneous Dirichlet boundary conditions and the initial conditions $(u,v(\\cdot,0 = (u_{0},v_{0}$ in $\\Omega$, where $\\Omega $ is a smooth bounded domain in $ \\mathbb{R}^{N} $ and $ u_{0},v_{0}\\in L^{\\infty}(\\Omega$ are nonnegative functions. We find conditions on $ p,q,r,s $ guaranteeing a priori estimates of nonnegative classical global solutions. More precisely every such solution is bounded by a constant depending on suitable norm of the initial data. Our proofs are based on bootstrap in weighted Lebesgue spaces, universal estimates of auxiliary functions and estimates of the Dirichlet heat kernel.

Driving a car with custom-designed fuzzy inferencing VLSI chips and boards

Science.gov (United States)

Pin, Francois G.; Watanabe, Yutaka

1993-01-01

Vehicle control in a-priori unknown, unpredictable, and dynamic environments requires many calculational and reasoning schemes to operate on the basis of very imprecise, incomplete, or unreliable data. For such systems, in which all the uncertainties can not be engineered away, approximate reasoning may provide an alternative to the complexity and computational requirements of conventional uncertainty analysis and propagation techniques. Two types of computer boards including custom-designed VLSI chips were developed to add a fuzzy inferencing capability to real-time control systems. All inferencing rules on a chip are processed in parallel, allowing execution of the entire rule base in about 30 microseconds, and therefore, making control of 'reflex-type' of motions envisionable. The use of these boards and the approach using superposition of elemental sensor-based behaviors for the development of qualitative reasoning schemes emulating human-like navigation in a-priori unknown environments are first discussed. Then how the human-like navigation scheme implemented on one of the qualitative inferencing boards was installed on a test-bed platform to investigate two control modes for driving a car in a-priori unknown environments on the basis of sparse and imprecise sensor data is described. In the first mode, the car navigates fully autonomously, while in the second mode, the system acts as a driver's aid providing the driver with linguistic (fuzzy) commands to turn left or right and speed up or slow down depending on the obstacles perceived by the sensors. Experiments with both modes of control are described in which the system uses only three acoustic range (sonar) sensor channels to perceive the environment. Simulation results as well as indoors and outdoors experiments are presented and discussed to illustrate the feasibility and robustness of autonomous navigation and/or safety enhancing driver's aid using the new fuzzy inferencing hardware system and some human

Sampling informative/complex a priori probability distributions using Gibbs sampling assisted by sequential simulation

DEFF Research Database (Denmark)

Hansen, Thomas Mejer; Mosegaard, Klaus; Cordua, Knud Skou

2010-01-01

Markov chain Monte Carlo methods such as the Gibbs sampler and the Metropolis algorithm can be used to sample the solutions to non-linear inverse problems. In principle these methods allow incorporation of arbitrarily complex a priori information, but current methods allow only relatively simple...... this algorithm with the Metropolis algorithm to obtain an efficient method for sampling posterior probability densities for nonlinear inverse problems....

Locally optimal control under unknown dynamics with learnt cost function: application to industrial robot positioning

Science.gov (United States)

Guérin, Joris; Gibaru, Olivier; Thiery, Stéphane; Nyiri, Eric

2017-01-01

Recent methods of Reinforcement Learning have enabled to solve difficult, high dimensional, robotic tasks under unknown dynamics using iterative Linear Quadratic Gaussian control theory. These algorithms are based on building a local time-varying linear model of the dynamics from data gathered through interaction with the environment. In such tasks, the cost function is often expressed directly in terms of the state and control variables so that it can be locally quadratized to run the algorithm. If the cost is expressed in terms of other variables, a model is required to compute the cost function from the variables manipulated. We propose a method to learn the cost function directly from the data, in the same way as for the dynamics. This way, the cost function can be defined in terms of any measurable quantity and thus can be chosen more appropriately for the task to be carried out. With our method, any sensor information can be used to design the cost function. We demonstrate the efficiency of this method through simulating, with the V-REP software, the learning of a Cartesian positioning task on several industrial robots with different characteristics. The robots are controlled in joint space and no model is provided a priori. Our results are compared with another model free technique, consisting in writing the cost function as a state variable.

Navigation through unknown and dynamic open spaces using topological notions

Science.gov (United States)

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.

Reconstruction of Consistent 3d CAD Models from Point Cloud Data Using a Priori CAD Models

Science.gov (United States)

Bey, A.; Chaine, R.; Marc, R.; Thibault, G.; Akkouche, S.

2011-09-01

We address the reconstruction of 3D CAD models from point cloud data acquired in industrial environments, using a pre-existing 3D model as an initial estimate of the scene to be processed. Indeed, this prior knowledge can be used to drive the reconstruction so as to generate an accurate 3D model matching the point cloud. We more particularly focus our work on the cylindrical parts of the 3D models. We propose to state the problem in a probabilistic framework: we have to search for the 3D model which maximizes some probability taking several constraints into account, such as the relevancy with respect to the point cloud and the a priori 3D model, and the consistency of the reconstructed model. The resulting optimization problem can then be handled using a stochastic exploration of the solution space, based on the random insertion of elements in the configuration under construction, coupled with a greedy management of the conflicts which efficiently improves the configuration at each step. We show that this approach provides reliable reconstructed 3D models by presenting some results on industrial data sets.

Population extinction under bursty reproduction in a time-modulated environment

Science.gov (United States)

Vilk, Ohad; Assaf, Michael

2018-06-01

In recent years nondemographic variability has been shown to greatly affect dynamics of stochastic populations. For example, nondemographic noise in the form of a bursty reproduction process with an a priori unknown burst size, or environmental variability in the form of time-varying reaction rates, have been separately found to dramatically impact the extinction risk of isolated populations. In this work we investigate the extinction risk of an isolated population under the combined influence of these two types of nondemographic variation. Using the so-called momentum-space Wentzel-Kramers-Brillouin (WKB) approach and accounting for the explicit time dependence in the reaction rates, we arrive at a set of time-dependent Hamilton equations. To this end, we evaluate the population's extinction risk by finding the instanton of the time-perturbed Hamiltonian numerically, whereas analytical expressions are presented in particular limits using various perturbation techniques. We focus on two classes of time-varying environments: periodically varying rates corresponding to seasonal effects and a sudden decrease in the birth rate corresponding to a catastrophe. All our theoretical results are tested against numerical Monte Carlo simulations with time-dependent rates and also against a numerical solution of the corresponding time-dependent Hamilton equations.

Use of a priori information in incomplete data x-ray CT imaging

International Nuclear Information System (INIS)

Eberhard, J.W.; Hedengren, K.H.

1988-01-01

A new technique for utilizing a priori information is presented which uses CAD electronic part models to make use of effectively all the information which is available in the blueprint of a selected industrial part. Significant improvements in x-ray image quality are demonstrated using the technique in the image enhancement of the model of an exhaust nozzle actuation ring for the F110 aircraft. Three approaches were evaluated: a projection data approach, an iterative reconstruction approach, and an image processing and analysis approach. Results for these approaches are included. X-ray CT images of the simulated part image reconstructed with several choices of available angular range are shown

Parameter transferability within homogeneous regions and comparisons with predictions from a priori parameters in the eastern United States

Science.gov (United States)

Chouaib, Wafa; Alila, Younes; Caldwell, Peter V.

2018-05-01

The need for predictions of flow time-series persists at ungauged catchments, motivating the research goals of our study. By means of the Sacramento model, this paper explores the use of parameter transfer within homogeneous regions of similar climate and flow characteristics and makes comparisons with predictions from a priori parameters. We assessed the performance using the Nash-Sutcliffe (NS), bias, mean monthly hydrograph and flow duration curve (FDC). The study was conducted on a large dataset of 73 catchments within the eastern US. Two approaches to the parameter transferability were developed and evaluated; (i) the within homogeneous region parameter transfer using one donor catchment specific to each region, (ii) the parameter transfer disregarding the geographical limits of homogeneous regions, where one donor catchment was common to all regions. Comparisons between both parameter transfers enabled to assess the gain in performance from the parameter regionalization and its respective constraints and limitations. The parameter transfer within homogeneous regions outperformed the a priori parameters and led to a decrease in bias and increase in efficiency reaching a median NS of 0.77 and a NS of 0.85 at individual catchments. The use of FDC revealed the effect of bias on the inaccuracy of prediction from parameter transfer. In one specific region, of mountainous and forested catchments, the prediction accuracy of the parameter transfer was less satisfactory and equivalent to a priori parameters. In this region, the parameter transfer from the outsider catchment provided the best performance; less-biased with smaller uncertainty in medium flow percentiles (40%-60%). The large disparity of energy conditions explained the lack of performance from parameter transfer in this region. Besides, the subsurface stormflow is predominant and there is a likelihood of lateral preferential flow, which according to its specific properties further explained the reduced

A program for the a priori evaluation of detection limits in instrumental neutron activation analysis using a SLOWPOKE II reactor

International Nuclear Information System (INIS)

Galinier, J.L.; Zikovsky, L.

1982-01-01

A program that permits the a priori calculation of detection limits in monoelemental matrices, adapted to instrumental neutron activation analysis using a SLOWPOKE II reactor, is described. A simplified model of the gamma spectra is proposed. Products of (n,p) and (n,α) reactions induced by the fast components of the neutron flux that accompanies the thermal flux at the level of internal irradiation sites in the reactor have been included in the list of interfering radionuclides. The program calculates in a systematic way the detection limits of 66 elements in an equal number of matrices using 153 intermediary radionuclides. Experimental checks carried out with silicon (for short lifetimes) and aluminum and magnesium (for intermediate lifetimes) show satisfactory agreement with the calculations. These results show in particular the importance of the contribution of the (n,p) and (n,α) reactions in the a priori evaluation of detection limits with a SLOWPOKE type reactor [fr

A priori tests of combustion models based on a CH{sub 4}/H{sub 2} Triple Flame

Energy Technology Data Exchange (ETDEWEB)

Dombard, J.; Naud, B.; Jimenez Sanchez, C.

2008-07-01

This document reproduces the final project of Jerome Dombard, presented on June 25, 2008, for the obtention of the Master degree MIMSE (Master Ingenierie Mathematique, Statistique et Economique) of Bordeaux University (Universite Bordeaux 1). We make an a priori study of FPI/FGM-type turbulent combustion models using a 2D DNS of a triple flame. A reduced chemical scheme of 16 species and 12 reactions is used (ARM1, proposed by J.-Y. Chen at Berkeley University). The fuel (CH4/H2 mixture) and oxidizer (air) correspond to the inlet composition of the Sydney bluff-body stabilised flame experiments (flames HM1-3). First, we compute 1D laminar premixed flames. The purpose of those calculations is twofold: 1. check the differences between different computer programs and different treatments of molecular diffusion, and 2. calibrate the 2D-DNS of the laminar triple flame (mainly decide on the grid resolution). Then, the solution of the 2D laminar triple flame is used to test a priori FPI/FGM tables. Finally, preliminary considerations on sub-grid scale modelling in the context of Large Eddy Simulation are made. (Author) 14 refs.

Fast grasping of unknown objects using principal component analysis

Science.gov (United States)

Lei, Qujiang; Chen, Guangming; Wisse, Martijn

2017-09-01

Fast grasping of unknown objects has crucial impact on the efficiency of robot manipulation especially subjected to unfamiliar environments. In order to accelerate grasping speed of unknown objects, principal component analysis is utilized to direct the grasping process. In particular, a single-view partial point cloud is constructed and grasp candidates are allocated along the principal axis. Force balance optimization is employed to analyze possible graspable areas. The obtained graspable area with the minimal resultant force is the best zone for the final grasping execution. It is shown that an unknown object can be more quickly grasped provided that the component analysis principle axis is determined using single-view partial point cloud. To cope with the grasp uncertainty, robot motion is assisted to obtain a new viewpoint. Virtual exploration and experimental tests are carried out to verify this fast gasping algorithm. Both simulation and experimental tests demonstrated excellent performances based on the results of grasping a series of unknown objects. To minimize the grasping uncertainty, the merits of the robot hardware with two 3D cameras can be utilized to suffice the partial point cloud. As a result of utilizing the robot hardware, the grasping reliance is highly enhanced. Therefore, this research demonstrates practical significance for increasing grasping speed and thus increasing robot efficiency under unpredictable environments.

Developing an A Priori Database for Passive Microwave Snow Water Retrievals Over Ocean

Science.gov (United States)

Yin, Mengtao; Liu, Guosheng

2017-12-01

A physically optimized a priori database is developed for Global Precipitation Measurement Microwave Imager (GMI) snow water retrievals over ocean. The initial snow water content profiles are derived from CloudSat Cloud Profiling Radar (CPR) measurements. A radiative transfer model in which the single-scattering properties of nonspherical snowflakes are based on the discrete dipole approximate results is employed to simulate brightness temperatures and their gradients. Snow water content profiles are then optimized through a one-dimensional variational (1D-Var) method. The standard deviations of the difference between observed and simulated brightness temperatures are in a similar magnitude to the observation errors defined for observation error covariance matrix after the 1D-Var optimization, indicating that this variational method is successful. This optimized database is applied in a Bayesian retrieval snow water algorithm. The retrieval results indicated that the 1D-Var approach has a positive impact on the GMI retrieved snow water content profiles by improving the physical consistency between snow water content profiles and observed brightness temperatures. Global distribution of snow water contents retrieved from the a priori database is compared with CloudSat CPR estimates. Results showed that the two estimates have a similar pattern of global distribution, and the difference of their global means is small. In addition, we investigate the impact of using physical parameters to subset the database on snow water retrievals. It is shown that using total precipitable water to subset the database with 1D-Var optimization is beneficial for snow water retrievals.

A Priori Analysis of a Compressible Flamelet Model using RANS Data for a Dual-Mode Scramjet Combustor

Science.gov (United States)

Quinlan, Jesse R.; Drozda, Tomasz G.; McDaniel, James C.; Lacaze, Guilhem; Oefelein, Joseph

2015-01-01

In an effort to make large eddy simulation of hydrocarbon-fueled scramjet combustors more computationally accessible using realistic chemical reaction mechanisms, a compressible flamelet/progress variable (FPV) model was proposed that extends current FPV model formulations to high-speed, compressible flows. Development of this model relied on observations garnered from an a priori analysis of the Reynolds-Averaged Navier-Stokes (RANS) data obtained for the Hypersonic International Flight Research and Experimentation (HI-FiRE) dual-mode scramjet combustor. The RANS data were obtained using a reduced chemical mechanism for the combustion of a JP-7 surrogate and were validated using avail- able experimental data. These RANS data were then post-processed to obtain, in an a priori fashion, the scalar fields corresponding to an FPV-based modeling approach. In the current work, in addition to the proposed compressible flamelet model, a standard incompressible FPV model was also considered. Several candidate progress variables were investigated for their ability to recover static temperature and major and minor product species. The effects of pressure and temperature on the tabulated progress variable source term were characterized, and model coupling terms embedded in the Reynolds- averaged Navier-Stokes equations were studied. Finally, results for the novel compressible flamelet/progress variable model were presented to demonstrate the improvement attained by modeling the effects of pressure and flamelet boundary conditions on the combustion.

A priori study of subgrid-scale features in turbulent Rayleigh-Bénard convection

Science.gov (United States)

Dabbagh, F.; Trias, F. X.; Gorobets, A.; Oliva, A.

2017-10-01

At the crossroad between flow topology analysis and turbulence modeling, a priori studies are a reliable tool to understand the underlying physics of the subgrid-scale (SGS) motions in turbulent flows. In this paper, properties of the SGS features in the framework of a large-eddy simulation are studied for a turbulent Rayleigh-Bénard convection (RBC). To do so, data from direct numerical simulation (DNS) of a turbulent air-filled RBC in a rectangular cavity of aspect ratio unity and π spanwise open-ended distance are used at two Rayleigh numbers R a ∈{1 08,1 010 } [Dabbagh et al., "On the evolution of flow topology in turbulent Rayleigh-Bénard convection," Phys. Fluids 28, 115105 (2016)]. First, DNS at Ra = 108 is used to assess the performance of eddy-viscosity models such as QR, Wall-Adapting Local Eddy-viscosity (WALE), and the recent S3PQR-models proposed by Trias et al. ["Building proper invariants for eddy-viscosity subgrid-scale models," Phys. Fluids 27, 065103 (2015)]. The outcomes imply that the eddy-viscosity modeling smoothes the coarse-grained viscous straining and retrieves fairly well the effect of the kinetic unfiltered scales in order to reproduce the coherent large scales. However, these models fail to approach the exact evolution of the SGS heat flux and are incapable to reproduce well the further dominant rotational enstrophy pertaining to the buoyant production. Afterwards, the key ingredients of eddy-viscosity, νt, and eddy-diffusivity, κt, are calculated a priori and revealed positive prevalent values to maintain a turbulent wind essentially driven by the mean buoyant force at the sidewalls. The topological analysis suggests that the effective turbulent diffusion paradigm and the hypothesis of a constant turbulent Prandtl number are only applicable in the large-scale strain-dominated areas in the bulk. It is shown that the bulk-dominated rotational structures of vortex-stretching (and its synchronous viscous dissipative structures) hold

Exploration of Unknown Spaces by People Who Are Blind Using a Multi-sensory Virtual Environment

Science.gov (United States)

Lahav, Orly; Mioduser, David

2004-01-01

The ability to explore unknown spaces independently, safely and efficiently is a combined product of motor, sensory, and cognitive skills. Normal exercise of this ability directly affects an individual?s quality of life. Mental mapping of spaces and of the possible paths for navigating these spaces is essential for the development of efficient…

Online Solution of Two-Player Zero-Sum Games for Continuous-Time Nonlinear Systems With Completely Unknown Dynamics.

Science.gov (United States)

Fu, Yue; Chai, Tianyou

2016-12-01

Regarding two-player zero-sum games of continuous-time nonlinear systems with completely unknown dynamics, this paper presents an online adaptive algorithm for learning the Nash equilibrium solution, i.e., the optimal policy pair. First, for known systems, the simultaneous policy updating algorithm (SPUA) is reviewed. A new analytical method to prove the convergence is presented. Then, based on the SPUA, without using a priori knowledge of any system dynamics, an online algorithm is proposed to simultaneously learn in real time either the minimal nonnegative solution of the Hamilton-Jacobi-Isaacs (HJI) equation or the generalized algebraic Riccati equation for linear systems as a special case, along with the optimal policy pair. The approximate solution to the HJI equation and the admissible policy pair is reexpressed by the approximation theorem. The unknown constants or weights of each are identified simultaneously by resorting to the recursive least square method. The convergence of the online algorithm to the optimal solutions is provided. A practical online algorithm is also developed. Simulation results illustrate the effectiveness of the proposed method.

Determining the depth of certain gravity sources without a priori specification of their structural index

Science.gov (United States)

Zhou, Shuai; Huang, Danian

2015-11-01

We have developed a new method for the interpretation of gravity tensor data based on the generalized Tilt-depth method. Cooper (2011, 2012) extended the magnetic Tilt-depth method to gravity data. We take the gradient-ratio method of Cooper (2011, 2012) and modify it so that the source type does not need to be specified a priori. We develop the new method by generalizing the Tilt-depth method for depth estimation for different types of source bodies. The new technique uses only the three vertical tensor components of the full gravity tensor data observed or calculated at different height plane to estimate the depth of the buried bodies without a priori specification of their structural index. For severely noise-corrupted data, our method utilizes different upward continuation height data, which can effectively reduce the influence of noise. Theoretical simulations of the gravity source model with and without noise illustrate the ability of the method to provide source depth information. Additionally, the simulations demonstrate that the new method is simple, computationally fast and accurate. Finally, we apply the method using the gravity data acquired over the Humble Salt Dome in the USA as an example. The results show a good correspondence to the previous drilling and seismic interpretation results.

A novel algorithm for fast grasping of unknown objects using C-shape configuration

Science.gov (United States)

Lei, Qujiang; Chen, Guangming; Meijer, Jonathan; Wisse, Martijn

2018-02-01

Increasing grasping efficiency is very important for the robots to grasp unknown objects especially subjected to unfamiliar environments. To achieve this, a new algorithm is proposed based on the C-shape configuration. Specifically, the geometric model of the used under-actuated gripper is approximated as a C-shape. To obtain an appropriate graspable position, this C-shape configuration is applied to fit geometric model of an unknown object. The geometric model of unknown object is constructed by using a single-view partial point cloud. To examine the algorithm using simulations, a comparison of the commonly used motion planners is made. The motion planner with the highest number of solved runs, lowest computing time and the shortest path length is chosen to execute grasps found by this grasping algorithm. The simulation results demonstrate that excellent grasping efficiency is achieved by adopting our algorithm. To validate this algorithm, experiment tests are carried out using a UR5 robot arm and an under-actuated gripper. The experimental results show that steady grasping actions are obtained. Hence, this research provides a novel algorithm for fast grasping of unknown objects.

A priori which-way information in quantum interference with unstable particles

International Nuclear Information System (INIS)

Krause, D.E.; Fischbach, E.; Rohrbach, Z.J.

2014-01-01

If an unstable particle used in a two-path interference experiment decays before reaching a detector, which-way information becomes available that reduces the detected interference fringe visibility V. Here we argue that even when an unstable particle does not decay while in the interferometer, a priori which-way information is still available in the form of path predictability P which depends on the particle's decay rate Γ. We further demonstrate that in a matter-wave Mach–Zehnder interferometer using an excited atom with an appropriately tuned cavity, P is related to V through the duality relation P 2 +V 2 =1. - Highlights: • Even undecayed unstable particles exhibit novel interference effects. • Interference is studied in a Mach–Zehnder interferometer with a cavity. • More which-way information is available when using unstable particles. • A relation between which-way information and interference is satisfied

Globally Stable Adaptive Backstepping Neural Network Control for Uncertain Strict-Feedback Systems With Tracking Accuracy Known a Priori.

Science.gov (United States)

Chen, Weisheng; Ge, Shuzhi Sam; Wu, Jian; Gong, Maoguo

2015-09-01

This paper addresses the problem of globally stable direct adaptive backstepping neural network (NN) tracking control design for a class of uncertain strict-feedback systems under the assumption that the accuracy of the ultimate tracking error is given a priori. In contrast to the classical adaptive backstepping NN control schemes, this paper analyzes the convergence of the tracking error using Barbalat's Lemma via some nonnegative functions rather than the positive-definite Lyapunov functions. Thus, the accuracy of the ultimate tracking error can be determined and adjusted accurately a priori, and the closed-loop system is guaranteed to be globally uniformly ultimately bounded. The main technical novelty is to construct three new n th-order continuously differentiable functions, which are used to design the control law, the virtual control variables, and the adaptive laws. Finally, two simulation examples are given to illustrate the effectiveness and advantages of the proposed control method.

Robot navigation in unknown terrains: Introductory survey of non-heuristic algorithms

Energy Technology Data Exchange (ETDEWEB)

Rao, N.S.V. [Oak Ridge National Lab., TN (US); Kareti, S.; Shi, Weimin [Old Dominion Univ., Norfolk, VA (US). Dept. of Computer Science; Iyengar, S.S. [Louisiana State Univ., Baton Rouge, LA (US). Dept. of Computer Science

1993-07-01

A formal framework for navigating a robot in a geometric terrain by an unknown set of obstacles is considered. Here the terrain model is not a priori known, but the robot is equipped with a sensor system (vision or touch) employed for the purpose of navigation. The focus is restricted to the non-heuristic algorithms which can be theoretically shown to be correct within a given framework of models for the robot, terrain and sensor system. These formulations, although abstract and simplified compared to real-life scenarios, provide foundations for practical systems by highlighting the underlying critical issues. First, the authors consider the algorithms that are shown to navigate correctly without much consideration given to the performance parameters such as distance traversed, etc. Second, they consider non-heuristic algorithms that guarantee bounds on the distance traversed or the ratio of the distance traversed to the shortest path length (computed if the terrain model is known). Then they consider the navigation of robots with very limited computational capabilities such as finite automata, etc.

Optimum path planning of mobile robot in unknown static and dynamic environments using Fuzzy-Wind Driven Optimization algorithm

Directory of Open Access Journals (Sweden)

Anish Pandey

2017-02-01

Full Text Available This article introduces a singleton type-1 fuzzy logic system (T1-SFLS controller and Fuzzy-WDO hybrid for the autonomous mobile robot navigation and collision avoidance in an unknown static and dynamic environment. The WDO (Wind Driven Optimization algorithm is used to optimize and tune the input/output membership function parameters of the fuzzy controller. The WDO algorithm is working based on the atmospheric motion of infinitesimal small air parcels navigates over an N-dimensional search domain. The performance of this proposed technique has compared through many computer simulations and real-time experiments by using Khepera-III mobile robot. As compared to the T1-SFLS controller the Fuzzy-WDO algorithm is found good agreement for mobile robot navigation.

Utilizing Q-Learning to allow a radar to choose its transmit frequency, adapting to its environment

CSIR Research Space (South Africa)

Wabeke, LO

2010-06-01

Full Text Available Recent research show that utilization of knowledge of the environment can allow a radar system to adapt its processing to improve its performance. Furthermore, a radar system that utilize both a-priori and measured knowledge in an adaptive close...

Rapid multi-wavelength optical assessment of circulating blood volume without a priori data

Science.gov (United States)

Loginova, Ekaterina V.; Zhidkova, Tatyana V.; Proskurnin, Mikhail A.; Zharov, Vladimir P.

2016-03-01

The measurement of circulating blood volume (CBV) is crucial in various medical conditions including surgery, iatrogenic problems, rapid fluid administration, transfusion of red blood cells, or trauma with extensive blood loss including battlefield injuries and other emergencies. Currently, available commercial techniques are invasive and time-consuming for trauma situations. Recently, we have proposed high-speed multi-wavelength photoacoustic/photothermal (PA/PT) flow cytometry for in vivo CBV assessment with multiple dyes as PA contrast agents (labels). As the first step, we have characterized the capability of this technique to monitor the clearance of three dyes (indocyanine green, methylene blue, and trypan blue) in an animal model. However, there are strong demands on improvements in PA/PT flow cytometry. As additional verification of our proof-of-concept of this technique, we performed optical photometric CBV measurements in vitro. Three label dyes—methylene blue, crystal violet and, partially, brilliant green—were selected for simultaneous photometric determination of the components of their two-dye mixtures in the circulating blood in vitro without any extra data (like hemoglobin absorption) known a priori. The tests of single dyes and their mixtures in a flow system simulating a blood transfusion system showed a negligible difference between the sensitivities of the determination of these dyes under batch and flow conditions. For individual dyes, the limits of detection of 3×10-6 M‒3×10-6 M in blood were achieved, which provided their continuous determination at a level of 10-5 M for the CBV assessment without a priori data on the matrix. The CBV assessment with errors no higher than 4% were obtained, and the possibility to apply the developed procedure for optical photometric (flow cytometry) with laser sources was shown.

Methods for improving limited field-of-view radiotherapy reconstructions using imperfect a priori images

International Nuclear Information System (INIS)

Ruchala, Kenneth J.; Olivera, Gustavo H.; Kapatoes, Jeffrey M.; Reckwerdt, Paul J.; Mackie, Thomas R.

2002-01-01

There are many benefits to having an online CT imaging system for radiotherapy, as it helps identify changes in the patient's position and anatomy between the time of planning and treatment. However, many current online CT systems suffer from a limited field-of-view (LFOV) in that collected data do not encompass the patient's complete cross section. Reconstruction of these data sets can quantitatively distort the image values and introduce artifacts. This work explores the use of planning CT data as a priori information for improving these reconstructions. Methods are presented to incorporate this data by aligning the LFOV with the planning images and then merging the data sets in sinogram space. One alignment option is explicit fusion, producing fusion-aligned reprojection (FAR) images. For cases where explicit fusion is not viable, FAR can be implemented using the implicit fusion of normal setup error, referred to as normal-error-aligned reprojection (NEAR). These methods are evaluated for multiday patient images showing both internal and skin-surface anatomical variation. The iterative use of NEAR and FAR is also investigated, as are applications of NEAR and FAR to dose calculations and the compensation of LFOV online MVCT images with kVCT planning images. Results indicate that NEAR and FAR can utilize planning CT data as imperfect a priori information to reduce artifacts and quantitatively improve images. These benefits can also increase the accuracy of dose calculations and be used for augmenting CT images (e.g., MVCT) acquired at different energies than the planning CT

Online reinforcement learning control for aerospace systems

NARCIS (Netherlands)

Zhou, Y.

2018-01-01

Reinforcement Learning (RL) methods are relatively new in the field of aerospace guidance, navigation, and control. This dissertation aims to exploit RL methods to improve the autonomy and online learning of aerospace systems with respect to the a priori unknown system and environment, dynamical

Priori mask guided image reconstruction (p-MGIR) for ultra-low dose cone-beam computed tomography

Science.gov (United States)

Park, Justin C.; Zhang, Hao; Chen, Yunmei; Fan, Qiyong; Kahler, Darren L.; Liu, Chihray; Lu, Bo

2015-11-01

Recently, the compressed sensing (CS) based iterative reconstruction method has received attention because of its ability to reconstruct cone beam computed tomography (CBCT) images with good quality using sparsely sampled or noisy projections, thus enabling dose reduction. However, some challenges remain. In particular, there is always a tradeoff between image resolution and noise/streak artifact reduction based on the amount of regularization weighting that is applied uniformly across the CBCT volume. The purpose of this study is to develop a novel low-dose CBCT reconstruction algorithm framework called priori mask guided image reconstruction (p-MGIR) that allows reconstruction of high-quality low-dose CBCT images while preserving the image resolution. In p-MGIR, the unknown CBCT volume was mathematically modeled as a combination of two regions: (1) where anatomical structures are complex, and (2) where intensities are relatively uniform. The priori mask, which is the key concept of the p-MGIR algorithm, was defined as the matrix that distinguishes between the two separate CBCT regions where the resolution needs to be preserved and where streak or noise needs to be suppressed. We then alternately updated each part of image by solving two sub-minimization problems iteratively, where one minimization was focused on preserving the edge information of the first part while the other concentrated on the removal of noise/artifacts from the latter part. To evaluate the performance of the p-MGIR algorithm, a numerical head-and-neck phantom, a Catphan 600 physical phantom, and a clinical head-and-neck cancer case were used for analysis. The results were compared with the standard Feldkamp-Davis-Kress as well as conventional CS-based algorithms. Examination of the p-MGIR algorithm showed that high-quality low-dose CBCT images can be reconstructed without compromising the image resolution. For both phantom and the patient cases, the p-MGIR is able to achieve a clinically

Almost half of the Danish general practitioners have negative a priori attitudes towards a mandatory accreditation programme

DEFF Research Database (Denmark)

Waldorff, Frans Boch; Nicolaisdottir, Dagny Ros; Kousgaard, Marius Brostrøm

2016-01-01

INTRODUCTION: The objective of this study was to analyse Danish general practitioners' (GPs) a priori attitudes and expectations towards a nationwide mandatory accreditation programme. METHODS: This study is based on a nationwide electronic survey comprising all Danish GPs (n = 3,403). RESULTS...... accreditation. FUNDING: The three Research Units for General Practice in Odense, Aarhus and Copenhagen initiated and funded this study. TRIAL REGISTRATION: The survey was recommended by the Danish Multipractice Committee (MPU 02-2015) and evaluated by the Danish Data Agency (2015-41-3684)....

A Priori User Acceptance and the Perceived Driving Pleasure in Semi-autonomous and Autonomous Vehicles

DEFF Research Database (Denmark)

Bjørner, Thomas

The aim of this minor pilot study is, from a sociological user perspective, to explore a priori user acceptance and the perceived driving pleasure in semi- autonomous and autonomous vehicles. The methods used were 13 in-depth interviews while having participants watch video examples within four...... different scenarios. After each scenario, two different numerical rating scales were used. There was a tendency toward positive attitudes regarding semi- autonomous driving systems, especially the use of a parking assistant and while driving in city traffic congestion. However, there were also major...

Reconstruction of signals with unknown spectra in information field theory with parameter uncertainty

International Nuclear Information System (INIS)

Ensslin, Torsten A.; Frommert, Mona

2011-01-01

The optimal reconstruction of cosmic metric perturbations and other signals requires knowledge of their power spectra and other parameters. If these are not known a priori, they have to be measured simultaneously from the same data used for the signal reconstruction. We formulate the general problem of signal inference in the presence of unknown parameters within the framework of information field theory. To solve this, we develop a generic parameter-uncertainty renormalized estimation (PURE) technique. As a concrete application, we address the problem of reconstructing Gaussian signals with unknown power-spectrum with five different approaches: (i) separate maximum-a-posteriori power-spectrum measurement and subsequent reconstruction, (ii) maximum-a-posteriori reconstruction with marginalized power-spectrum, (iii) maximizing the joint posterior of signal and spectrum, (iv) guessing the spectrum from the variance in the Wiener-filter map, and (v) renormalization flow analysis of the field-theoretical problem providing the PURE filter. In all cases, the reconstruction can be described or approximated as Wiener-filter operations with assumed signal spectra derived from the data according to the same recipe, but with differing coefficients. All of these filters, except the renormalized one, exhibit a perception threshold in case of a Jeffreys prior for the unknown spectrum. Data modes with variance below this threshold do not affect the signal reconstruction at all. Filter (iv) seems to be similar to the so-called Karhune-Loeve and Feldman-Kaiser-Peacock estimators for galaxy power spectra used in cosmology, which therefore should also exhibit a marginal perception threshold if correctly implemented. We present statistical performance tests and show that the PURE filter is superior to the others, especially if the post-Wiener-filter corrections are included or in case an additional scale-independent spectral smoothness prior can be adopted.

Analysis of Milk Production Traits in Early Lactation Using a Reaction Norm Model with Unknown Covariates

DEFF Research Database (Denmark)

Mahdi Shariati, Mohammad; Su, Guosheng; Madsen, Per

2007-01-01

The reaction norm model is becoming a popular approach to study genotype x environment interaction (GxE), especially when there is a continuum of environmental effects. These effects are typically unknown, and an approximation that is used in the literature is to replace them by the phenotypic...... means of each environment. It has been shown that this method results in poor inferences and that a more satisfactory alternative is to infer environmental effects jointly with the other parameters of the model. Such a reaction norm model with unknown covariates and heterogeneous residual variances...... across herds was fitted to milk, protein, and fat yield of first-lactation Danish Holstein cows to investigate the presence of GxE. Data included 188,502 first test-day records from 299 herds and 3,775 herd-years in a time period ranging from 1991 to 2003. Variance components and breeding values were...

Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming

Science.gov (United States)

Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai

2013-09-01

In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

Identification of parametric models with a priori knowledge of process properties

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Janiszowski Krzysztof B.

2016-12-01

Full Text Available An approach to estimation of a parametric discrete-time model of a process in the case of some a priori knowledge of the investigated process properties is presented. The knowledge of plant properties is introduced in the form of linear bounds, which can be determined for the coefficient vector of the parametric model studied. The approach yields special biased estimation of model coefficients that preserves demanded properties. A formula for estimation of the model coefficients is derived and combined with a recursive scheme determined for minimization of the sum of absolute model errors. The estimation problem of a model with known static gains of inputs is discussed and proper formulas are derived. This approach can overcome the non-identifiability problem which has been observed during estimation based on measurements recorded in industrial closed-loop control systems. The application of the proposed approach to estimation of a model for an industrial plant (a water injector into the steam flow in a power plant is presented and discussed.

Grasping Unknown Objects in an Early Cognitive Vision System

DEFF Research Database (Denmark)

Popovic, Mila

2011-01-01

Grasping of unknown objects presents an important and challenging part of robot manipulation. The growing area of service robotics depends upon the ability of robots to autonomously grasp and manipulate a wide range of objects in everyday environments. Simple, non task-specific grasps of unknown ...... and comparing vision-based grasping methods, and the creation of algorithms for bootstrapping a process of acquiring world understanding for artificial cognitive agents....... presents a system for robotic grasping of unknown objects us- ing stereo vision. Grasps are defined based on contour and surface information provided by the Early Cognitive Vision System, that organizes visual informa- tion into a biologically motivated hierarchical representation. The contributions...... of the thesis are: the extension of the Early Cognitive Vision representation with a new type of feature hierarchy in the texture domain, the definition and evaluation of contour based grasping methods, the definition and evaluation of surface based grasping methods, the definition of a benchmark for testing...

Factor analysis with a priori knowledge - application in dynamic cardiac SPECT

Energy Technology Data Exchange (ETDEWEB)

Sitek, A.; Di Bella, E.V.R.; Gullberg, G.T. [Medical Imaging Research Laboratory, Department of Radiology, University of Utah, CAMT, 729 Arapeen Drive, Salt Lake City, UT 84108-1218 (United States)

2000-09-01

Two factor analysis of dynamic structures (FADS) methods for the extraction of time-activity curves (TACs) from cardiac dynamic SPECT data sequences were investigated. One method was based on a least squares (LS) approach which was subject to positivity constraints. The other method was the well known apex-seeking (AS) method. A post-processing step utilizing a priori information was employed to correct for the non-uniqueness of the FADS solution. These methods were used to extract {sup 99m}Tc-teboroxime TACs from computer simulations and from experimental canine and patient studies. In computer simulations, the LS and AS methods, which are completely different algorithms, yielded very similar and accurate results after application of the correction for non-uniqueness. FADS-obtained blood curves correlated well with curves derived from region of interest (ROI) measurements in the experimental studies. The results indicate that the factor analysis techniques can be used for semi-automatic estimation of activity curves derived from cardiac dynamic SPECT images, and that they can be used for separation of physiologically different regions in dynamic cardiac SPECT studies. (author)

A Priori and a Posteriori Dietary Patterns during Pregnancy and Gestational Weight Gain: The Generation R Study

Directory of Open Access Journals (Sweden)

Myrte J. Tielemans

2015-11-01

Full Text Available Abnormal gestational weight gain (GWG is associated with adverse pregnancy outcomes. We examined whether dietary patterns are associated with GWG. Participants included 3374 pregnant women from a population-based cohort in the Netherlands. Dietary intake during pregnancy was assessed with food-frequency questionnaires. Three a posteriori-derived dietary patterns were identified using principal component analysis: a “Vegetable, oil and fish”, a “Nuts, high-fiber cereals and soy”, and a “Margarine, sugar and snacks” pattern. The a priori-defined dietary pattern was based on national dietary recommendations. Weight was repeatedly measured around 13, 20 and 30 weeks of pregnancy; pre-pregnancy and maximum weight were self-reported. Normal weight women with high adherence to the “Vegetable, oil and fish” pattern had higher early-pregnancy GWG than those with low adherence (43 g/week (95% CI 16; 69 for highest vs. lowest quartile (Q. Adherence to the “Margarine, sugar and snacks” pattern was associated with a higher prevalence of excessive GWG (OR 1.45 (95% CI 1.06; 1.99 Q4 vs. Q1. Normal weight women with higher scores on the “Nuts, high-fiber cereals and soy” pattern had more moderate GWG than women with lower scores (−0.01 (95% CI −0.02; −0.00 per SD. The a priori-defined pattern was not associated with GWG. To conclude, specific dietary patterns may play a role in early pregnancy but are not consistently associated with GWG.

A priori analysis: an application to the estimate of the uncertainty in course grades

Science.gov (United States)

Lippi, G. L.

2014-07-01

A priori analysis (APA) is discussed as a tool to assess the reliability of grades in standard curricular courses. This unusual, but striking, application is presented when teaching the section on the data treatment of a laboratory course to illustrate the characteristics of the APA and its potential for widespread use, beyond the traditional physics curriculum. The conditions necessary for this kind of analysis are discussed, the general framework is set out and a specific example is given to illustrate its various aspects. Students are often struck by this unusual application and are more apt to remember the APA. Instructors may also benefit from some of the gathered information, as discussed in the paper.

A priori analysis: an application to the estimate of the uncertainty in course grades

International Nuclear Information System (INIS)

Lippi, G L

2014-01-01

A priori analysis (APA) is discussed as a tool to assess the reliability of grades in standard curricular courses. This unusual, but striking, application is presented when teaching the section on the data treatment of a laboratory course to illustrate the characteristics of the APA and its potential for widespread use, beyond the traditional physics curriculum. The conditions necessary for this kind of analysis are discussed, the general framework is set out and a specific example is given to illustrate its various aspects. Students are often struck by this unusual application and are more apt to remember the APA. Instructors may also benefit from some of the gathered information, as discussed in the paper. (paper)

Practical Considerations about Expected A Posteriori Estimation in Adaptive Testing: Adaptive A Priori, Adaptive Correction for Bias, and Adaptive Integration Interval.

Science.gov (United States)

Raiche, Gilles; Blais, Jean-Guy

In a computerized adaptive test (CAT), it would be desirable to obtain an acceptable precision of the proficiency level estimate using an optimal number of items. Decreasing the number of items is accompanied, however, by a certain degree of bias when the true proficiency level differs significantly from the a priori estimate. G. Raiche (2000) has…

A contextual image segmentation system using a priori information for automatic data classification in nuclear physics

International Nuclear Information System (INIS)

Benkirane, A.; Auger, G.; Chbihi, A.; Bloyet, D.; Plagnol, E.

1994-01-01

This paper presents an original approach to solve an automatic data classification problem by means of image processing techniques. The classification is achieved using image segmentation techniques for extracting the meaningful classes. Two types of information are merged for this purpose: the information contained in experimental images and a priori information derived from underlying physics (and adapted to image segmentation problem). This data fusion is widely used at different stages of the segmentation process. This approach yields interesting results in terms of segmentation performances, even in very noisy cases. Satisfactory classification results are obtained in cases where more ''classical'' automatic data classification methods fail. (authors). 25 refs., 14 figs., 1 append

A contextual image segmentation system using a priori information for automatic data classification in nuclear physics

Energy Technology Data Exchange (ETDEWEB)

Benkirane, A; Auger, G; Chbihi, A [Grand Accelerateur National d` Ions Lourds (GANIL), 14 - Caen (France); Bloyet, D [Caen Univ., 14 (France); Plagnol, E [Paris-11 Univ., 91 - Orsay (France). Inst. de Physique Nucleaire

1994-12-31

This paper presents an original approach to solve an automatic data classification problem by means of image processing techniques. The classification is achieved using image segmentation techniques for extracting the meaningful classes. Two types of information are merged for this purpose: the information contained in experimental images and a priori information derived from underlying physics (and adapted to image segmentation problem). This data fusion is widely used at different stages of the segmentation process. This approach yields interesting results in terms of segmentation performances, even in very noisy cases. Satisfactory classification results are obtained in cases where more ``classical`` automatic data classification methods fail. (authors). 25 refs., 14 figs., 1 append.

Predicting thermal history a-priori for magnetic nanoparticle hyperthermia of internal carcinoma

Science.gov (United States)

Dhar, Purbarun; Sirisha Maganti, Lakshmi

2017-08-01

This article proposes a simplistic and realistic method where a direct analytical expression can be derived for the temperature field within a tumour during magnetic nanoparticle hyperthermia. The approximated analytical expression for thermal history within the tumour is derived based on the lumped capacitance approach and considers all therapy protocols and parameters. The present method is simplistic and provides an easy framework for estimating hyperthermia protocol parameters promptly. The model has been validated with respect to several experimental reports on animal models such as mice/rabbit/hamster and human clinical trials. It has been observed that the model is able to accurately estimate the thermal history within the carcinoma during the hyperthermia therapy. The present approach may find implications in a-priori estimation of the thermal history in internal tumours for optimizing magnetic hyperthermia treatment protocols with respect to the ablation time, tumour size, magnetic drug concentration, field strength, field frequency, nanoparticle material and size, tumour location, and so on.

SLAM algorithm applied to robotics assistance for navigation in unknown environments

Directory of Open Access Journals (Sweden)

Lobo Pereira Fernando

2010-02-01

Full Text Available Abstract Background The combination of robotic tools with assistance technology determines a slightly explored area of applications and advantages for disability or elder people in their daily tasks. Autonomous motorized wheelchair navigation inside an environment, behaviour based control of orthopaedic arms or user's preference learning from a friendly interface are some examples of this new field. In this paper, a Simultaneous Localization and Mapping (SLAM algorithm is implemented to allow the environmental learning by a mobile robot while its navigation is governed by electromyographic signals. The entire system is part autonomous and part user-decision dependent (semi-autonomous. The environmental learning executed by the SLAM algorithm and the low level behaviour-based reactions of the mobile robot are robotic autonomous tasks, whereas the mobile robot navigation inside an environment is commanded by a Muscle-Computer Interface (MCI. Methods In this paper, a sequential Extended Kalman Filter (EKF feature-based SLAM algorithm is implemented. The features correspond to lines and corners -concave and convex- of the environment. From the SLAM architecture, a global metric map of the environment is derived. The electromyographic signals that command the robot's movements can be adapted to the patient's disabilities. For mobile robot navigation purposes, five commands were obtained from the MCI: turn to the left, turn to the right, stop, start and exit. A kinematic controller to control the mobile robot was implemented. A low level behavior strategy was also implemented to avoid robot's collisions with the environment and moving agents. Results The entire system was tested in a population of seven volunteers: three elder, two below-elbow amputees and two young normally limbed patients. The experiments were performed within a closed low dynamic environment. Subjects took an average time of 35 minutes to navigate the environment and to learn how

Investigating industrial investigation: examining the impact of a priori knowledge and tunnel vision education.

Science.gov (United States)

Maclean, Carla L; Brimacombe, C A Elizabeth; Lindsay, D Stephen

2013-12-01

The current study addressed tunnel vision in industrial incident investigation by experimentally testing how a priori information and a human bias (generated via the fundamental attribution error or correspondence bias) affected participants' investigative behavior as well as the effectiveness of a debiasing intervention. Undergraduates and professional investigators engaged in a simulated industrial investigation exercise. We found that participants' judgments were biased by knowledge about the safety history of either a worker or piece of equipment and that a human bias was evident in participants' decision making. However, bias was successfully reduced with "tunnel vision education." Professional investigators demonstrated a greater sophistication in their investigative decision making compared to undergraduates. The similarities and differences between these two populations are discussed. (c) 2013 APA, all rights reserved

Musical Probabilities, Abductive Reasoning, and Brain Mechanisms: Extended Perspective of "A Priori" Listening to Music within the Creative Cognition Approach

Science.gov (United States)

Schmidt, Sebastian; Troge, Thomas A.; Lorrain, Denis

2013-01-01

A theory of listening to music is proposed. It suggests that, for listeners, the process of prediction is the starting point to experiencing music. This implies that perception of music starts through both a predisposed and an experience-based extrapolation into the future (this is labeled "a priori" listening). Indications for this…

Where am I? Creating spatial awareness in unmanned ground ...

Indian Academy of Sciences (India)

This paper presents a survey of Simultaneous Localization And Mapping (SLAM) algorithms for unmanned ground robots. SLAM is the process of creating a map of the environment, sometimes unknown a priori, while at the same time localizing the robot in the same map. The map could be one of different types i.e. metrical, ...

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

Science.gov (United States)

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.

Geography of resonances and Arnold diffusion in a priori unstable Hamiltonian systems

International Nuclear Information System (INIS)

Delshams, Amadeu; Huguet, Gemma

2009-01-01

In this paper we consider the case of a general C r+2 perturbation, for r large enough, of an a priori unstable Hamiltonian system of 2 + 1/2 degrees of freedom, and we provide explicit conditions on it, which turn out to be C 2 generic and are verifiable in concrete examples, which guarantee the existence of Arnold diffusion. This is a generalization of the result in Delshams et al (2006 Mem. Am. Math. Soc.) where the case of a perturbation with a finite number of harmonics in the angular variables was considered. The method of proof is based on a careful analysis of the geography of resonances created by a generic perturbation and it contains a deep quantitative description of the invariant objects generated by the resonances therein. The scattering map is used as an essential tool to construct transition chains of objects of different topology. The combination of quantitative expressions for both the geography of resonances and the scattering map provides, in a natural way, explicit computable conditions for instability

River routing at the continental scale: use of globally-available data and an a priori method of parameter estimation

Directory of Open Access Journals (Sweden)

P. Naden

1999-01-01

Full Text Available Two applications of a river routing model based on the observed river network and a linearised solution to the convective-diffusion equation are presented. One is an off-line application to part of the Amazon basin (catchment area 2.15 M km2 using river network data from the Digital Chart of the World and GCM-generated runoff at a grid resolution of 2.5 degrees latitude and 3.75 degrees longitude. The other application is to the Arkansas (409,000 km2 and Red River (125,500 km2 basins as an integrated component of a macro-scale hydrological model, driven by observed meteorology and operating on a 17 km grid. This second application makes use of the US EPA reach data to construct the river network. In both cases, a method of computing parameter values a priori has been applied and shows some success, although some interpretation is required to derive `correct' parameter values and further work is needed to develop guidelines for use of the method. The applications, however, do demonstrate the possibilities for applying the routing model at the continental scale, with globally-available data and a priori parameter estimation, and its value for validating GCM output against observed flows.

GNSS Precise Kinematic Positioning for Multiple Kinematic Stations Based on A Priori Distance Constraints

Science.gov (United States)

He, Kaifei; Xu, Tianhe; Förste, Christoph; Petrovic, Svetozar; Barthelmes, Franz; Jiang, Nan; Flechtner, Frank

2016-01-01

When applying the Global Navigation Satellite System (GNSS) for precise kinematic positioning in airborne and shipborne gravimetry, multiple GNSS receiving equipment is often fixed mounted on the kinematic platform carrying the gravimetry instrumentation. Thus, the distances among these GNSS antennas are known and invariant. This information can be used to improve the accuracy and reliability of the state estimates. For this purpose, the known distances between the antennas are applied as a priori constraints within the state parameters adjustment. These constraints are introduced in such a way that their accuracy is taken into account. To test this approach, GNSS data of a Baltic Sea shipborne gravimetric campaign have been used. The results of our study show that an application of distance constraints improves the accuracy of the GNSS kinematic positioning, for example, by about 4 mm for the radial component. PMID:27043580

Global identifiability of linear compartmental models--a computer algebra algorithm.

Science.gov (United States)

Audoly, S; D'Angiò, L; Saccomani, M P; Cobelli, C

1998-01-01

A priori global identifiability deals with the uniqueness of the solution for the unknown parameters of a model and is, thus, a prerequisite for parameter estimation of biological dynamic models. Global identifiability is however difficult to test, since it requires solving a system of algebraic nonlinear equations which increases both in nonlinearity degree and number of terms and unknowns with increasing model order. In this paper, a computer algebra tool, GLOBI (GLOBal Identifiability) is presented, which combines the topological transfer function method with the Buchberger algorithm, to test global identifiability of linear compartmental models. GLOBI allows for the automatic testing of a priori global identifiability of general structure compartmental models from general multi input-multi output experiments. Examples of usage of GLOBI to analyze a priori global identifiability of some complex biological compartmental models are provided.

Characteristic Investigation of Unfolded Neutron Spectra with Different Priori Information and Gamma Radiation Interference

International Nuclear Information System (INIS)

Kim, Bong Hwan

2006-01-01

Neutron field spectrometry using multi spheres such as Bonner Spheres (BS) has been almost essential in radiation protection dosimetry for a long time at workplace in spite of poor energy resolution because it is not asking the fine energy resolution but requiring easy operation and measurement performance over a wide range of energy interested. KAERI has developed and used extended BS system based on a LiI(Eu) scintillator as the representative neutron spectrometry system for workplace monitoring as well as for the quantification of neutron calibration fields such as those recommended by ISO 8529. Major topics in using BS are how close the unfolded spectra is the real one and to minimize the interference of gamma radiation in neutron/gamma mixed fields in case of active instrument such as a BS with a LiI(Eu) scintillator. The former is related with choosing a priori information when unfolding the measured data and the latter is depend on how to discriminate it in intense gamma radiation fields. Influence of a priori information in unfolding and effect of counting loss due to pile-up of signals for the KAERI BS system were investigated analyzing the spectral measurement results of Scattered Neutron Calibration Fields (SNCF)

Protecting unknown two-qubit entangled states by nesting Uhrig's dynamical decoupling sequences

International Nuclear Information System (INIS)

Mukhtar, Musawwadah; Soh, Wee Tee; Saw, Thuan Beng; Gong, Jiangbin

2010-01-01

Future quantum technologies rely heavily on good protection of quantum entanglement against environment-induced decoherence. A recent study showed that an extension of Uhrig's dynamical decoupling (UDD) sequence can (in theory) lock an arbitrary but known two-qubit entangled state to the Nth order using a sequence of N control pulses [Mukhtar et al., Phys. Rev. A 81, 012331 (2010)]. By nesting three layers of explicitly constructed UDD sequences, here we first consider the protection of unknown two-qubit states as superposition of two known basis states, without making assumptions of the system-environment coupling. It is found that the obtained decoherence suppression can be highly sensitive to the ordering of the three UDD layers and can be remarkably effective with the correct ordering. The detailed theoretical results are useful for general understanding of the nature of controlled quantum dynamics under nested UDD. As an extension of our three-layer UDD, it is finally pointed out that a completely unknown two-qubit state can be protected by nesting four layers of UDD sequences. This work indicates that when UDD is applicable (e.g., when the environment has a sharp frequency cutoff and when control pulses can be taken as instantaneous pulses), dynamical decoupling using nested UDD sequences is a powerful approach for entanglement protection.

Optimization of Decision-Making for Spatial Sampling in the North China Plain, Based on Remote-Sensing a Priori Knowledge

Science.gov (United States)

Feng, J.; Bai, L.; Liu, S.; Su, X.; Hu, H.

2012-07-01

In this paper, the MODIS remote sensing data, featured with low-cost, high-timely and moderate/low spatial resolutions, in the North China Plain (NCP) as a study region were firstly used to carry out mixed-pixel spectral decomposition to extract an useful regionalized indicator parameter (RIP) (i.e., an available ratio, that is, fraction/percentage, of winter wheat planting area in each pixel as a regionalized indicator variable (RIV) of spatial sampling) from the initial selected indicators. Then, the RIV values were spatially analyzed, and the spatial structure characteristics (i.e., spatial correlation and variation) of the NCP were achieved, which were further processed to obtain the scalefitting, valid a priori knowledge or information of spatial sampling. Subsequently, founded upon an idea of rationally integrating probability-based and model-based sampling techniques and effectively utilizing the obtained a priori knowledge or information, the spatial sampling models and design schemes and their optimization and optimal selection were developed, as is a scientific basis of improving and optimizing the existing spatial sampling schemes of large-scale cropland remote sensing monitoring. Additionally, by the adaptive analysis and decision strategy the optimal local spatial prediction and gridded system of extrapolation results were able to excellently implement an adaptive report pattern of spatial sampling in accordance with report-covering units in order to satisfy the actual needs of sampling surveys.

The determination of a neutron source position in an unknown homogeneous medium: The planar case

International Nuclear Information System (INIS)

Dubinski, S.; Talmor, A.; Presler, O.; Tshuva, A.; Yaar, I.; Orion, I.; Alfassi, Z.B.

2005-01-01

The possibility of localization of an unknown neutron source in various bulky homogeneous media (box) was studied. For the planar case, two 3 He detectors on the opposite faces of the box were used. A constant polypropylene shield around the box and detectors was used to eliminate the varying contribution from the environment to increase count rates of the detectors and to protect the experimentalist. It is shown that the location of a single small neutron emitting source in a large box can be found to a better than 7% by using two neutron detectors positioned on parallel faces of the box, coplanar with the source. The localization requires measurement of the count rate of both the unknown source and an extra source positioned on one of the faces of the box. The localization is based on the finding that the ratio of the count rates of the two detectors is an exponential function of the distance of the source from one of the detectors

Comparison of a priori versus provisional heparin therapy on radial artery occlusion after transradial coronary angiography and patent hemostasis (from the PHARAOH Study).

Science.gov (United States)

Pancholy, Samir B; Bertrand, Olivier F; Patel, Tejas

2012-07-15

Systemic anticoagulation decreases the risk of radial artery occlusion (RAO) after transradial catheterization and standard occlusive hemostasis. We compared the efficacy and safety of provisional heparin use only when the technique of patent hemostasis was not achievable to standard a priori heparin administration after radial sheath introduction. Patients referred for coronary angiography were randomized in 2 groups. In the a priori group, 200 patients received intravenous heparin (50 IU/kg) immediately after sheath insertion. In the provisional group, 200 patients did not receive heparin during the procedure. After sheath removal, hemostasis was obtained using a TR band (Terumo corporation, Tokyo, Japan) with a plethysmography-guided patent hemostasis technique. In the provisional group, no heparin was given if radial artery patency could be obtained and maintained. If radial patency was not achieved, a bolus of heparin (50 IU/kg) was given. Radial artery patency was evaluated at 24 hours (early RAO) and 30 days after the procedure (late RAO) by plethysmography. Patent hemostasis was obtained in 67% in the a priori group and 74% in the provisional group (p = 0.10). Incidence of RAO remained similar in the 2 groups at the early (7.5% vs 7.0%, p = 0.84) and late (4.5% vs 5.0%, p = 0.83) evaluations. Women, patients with diabetes, patients having not received heparin, and patients without radial artery patency during hemostasis had more RAO. By multivariate analysis, patent radial artery during hemostasis (odds ratio [OR] 0.03, 95% confidence interval [CI] 0.004 to 0.28, p = 0.002) and diabetes (OR 11, 95% CI 3 to 38,p patent hemostasis is maintained. Copyright © 2012 Elsevier Inc. All rights reserved.

Evaluation of a compliance device in a subgroup of adult patients receiving specific immunotherapy with grass allergen tablets (GRAZAX) in a randomized, open-label, controlled study: an a priori subgroup analysis.

NARCIS (Netherlands)

Jansen, A.P.H.; Andersen, K.F.; Bruning, H.

2009-01-01

OBJECTIVES: This a priori subgroup analysis was conducted to assess patients' experience with a compliance device for the administration of sublingual specific immunotherapy for grass pollen-induced rhinoconjunctivitis. METHODS: The present paper reports the results of a subgroup analysis of a

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

Science.gov (United States)

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

Statistical parameters as a means to a priori assess the accuracy of solar forecasting models

International Nuclear Information System (INIS)

Voyant, Cyril; Soubdhan, Ted; Lauret, Philippe; David, Mathieu; Muselli, Marc

2015-01-01

In this paper we propose to determinate and to test a set of 20 statistical parameters in order to estimate the short term predictability of the global horizontal irradiation time series and thereby to propose a new prospective tool indicating the expected error regardless the forecasting methods used. The mean absolute log return, which is a tool usually used in econometrics but never in global radiation prediction, proves to be a very good estimator. Some examples of the use of this tool are exposed, showing the interest of this statistical parameter in concrete cases of predictions or optimizations. This study gives a judgment for engineers and researchers on the installation or management of solar plants and could help in minimizing the energy crisis allowing to improve the renewable energy part of the energy mix. - Highlights: • Use of statistical parameter never used for the global radiation forecasting. • A priori index allowing to optimize easily and quickly a clear sky model. • New methodology allowing to quantify the prediction error regardless the predictor used. • The prediction error depends more on the location and the time series type than the machine Learning method used.

Designing towards the unknown

DEFF Research Database (Denmark)

Wilde, Danielle; Underwood, Jenny

2018-01-01

the research potential to far-ranging possibilities. In this article we unpack the motivations driving the PKI project. We present our mixed-methodology, which entangles textile crafts, design interactions and materiality to shape an embodied enquiry. Our research outcomes are procedural and methodological......New materials with new capabilities demand new ways of approaching design. Destabilising existing methods is crucial to develop new methods. Yet, radical destabilisation—where outcomes remain unknown long enough that new discoveries become possible—is not easy in technology design where complex......, to design towards unknown outcomes, using unknown materials. The impossibility of this task is proving as useful as it is disruptive. At its most potent, it is destabilising expectations, aesthetics and processes. Keeping the researchers, collaborators and participants in a state of unknowing, is opening...

Blind Identification of FIR Channels in the Presence of Unknown Noise

Directory of Open Access Journals (Sweden)

Kon Max Wong

2007-01-01

Full Text Available Blind channel identification techniques based on second-order statistics (SOS of the received data have been a topic of active research in recent years. Among the most popular is the subspace method (SS proposed by Moulines et al. (1995. It has good performance when the channel output is corrupted by white noise. However, when the channel noise is correlated and unknown as is often encountered in practice, the performance of the SS method degrades severely. In this paper, we address the problem of estimating FIR channels in the presence of arbitrarily correlated noise whose covariance matrix is unknown. We propose several algorithms according to the different available system resources: (1 when only one receiving antenna is available, by upsampling the output, we develop the maximum a posteriori (MAP algorithm for which a simple criterion is obtained and an efficient implementation algorithm is developed; (2 when two receiving antennae are available, by upsampling both the outputs and utilizing canonical correlation decomposition (CCD to obtain the subspaces, we present two algorithms (CCD-SS and CCD-ML to blindly estimate the channels. Our algorithms perform well in unknown noise environment and outperform existing methods proposed for similar scenarios.

Financial Development and Economic Growth: Known Knowns, Known Unknowns, and Unknown Unknowns

OpenAIRE

Ugo Panizza

2014-01-01

This paper summarizes the main findings of the literature on the relationship between financial and economic development (the known knowns), points to directions for future research (the known unknowns), and then speculates on the third Rumsfeldian category. The known knowns section organizes the empirical literature on finance and growth into three strands: (i) the traditional literature which established the link between finance and growth; (ii) the new literature which qualified some of th...

A review of a priori regression models for warfarin maintenance dose prediction.

Directory of Open Access Journals (Sweden)

Ben Francis

Full Text Available A number of a priori warfarin dosing algorithms, derived using linear regression methods, have been proposed. Although these dosing algorithms may have been validated using patients derived from the same centre, rarely have they been validated using a patient cohort recruited from another centre. In order to undertake external validation, two cohorts were utilised. One cohort formed by patients from a prospective trial and the second formed by patients in the control arm of the EU-PACT trial. Of these, 641 patients were identified as having attained stable dosing and formed the dataset used for validation. Predicted maintenance doses from six criterion fulfilling regression models were then compared to individual patient stable warfarin dose. Predictive ability was assessed with reference to several statistics including the R-square and mean absolute error. The six regression models explained different amounts of variability in the stable maintenance warfarin dose requirements of the patients in the two validation cohorts; adjusted R-squared values ranged from 24.2% to 68.6%. An overview of the summary statistics demonstrated that no one dosing algorithm could be considered optimal. The larger validation cohort from the prospective trial produced more consistent statistics across the six dosing algorithms. The study found that all the regression models performed worse in the validation cohort when compared to the derivation cohort. Further, there was little difference between regression models that contained pharmacogenetic coefficients and algorithms containing just non-pharmacogenetic coefficients. The inconsistency of results between the validation cohorts suggests that unaccounted population specific factors cause variability in dosing algorithm performance. Better methods for dosing that take into account inter- and intra-individual variability, at the initiation and maintenance phases of warfarin treatment, are needed.

A review of a priori regression models for warfarin maintenance dose prediction.

Science.gov (United States)

Francis, Ben; Lane, Steven; Pirmohamed, Munir; Jorgensen, Andrea

2014-01-01

A number of a priori warfarin dosing algorithms, derived using linear regression methods, have been proposed. Although these dosing algorithms may have been validated using patients derived from the same centre, rarely have they been validated using a patient cohort recruited from another centre. In order to undertake external validation, two cohorts were utilised. One cohort formed by patients from a prospective trial and the second formed by patients in the control arm of the EU-PACT trial. Of these, 641 patients were identified as having attained stable dosing and formed the dataset used for validation. Predicted maintenance doses from six criterion fulfilling regression models were then compared to individual patient stable warfarin dose. Predictive ability was assessed with reference to several statistics including the R-square and mean absolute error. The six regression models explained different amounts of variability in the stable maintenance warfarin dose requirements of the patients in the two validation cohorts; adjusted R-squared values ranged from 24.2% to 68.6%. An overview of the summary statistics demonstrated that no one dosing algorithm could be considered optimal. The larger validation cohort from the prospective trial produced more consistent statistics across the six dosing algorithms. The study found that all the regression models performed worse in the validation cohort when compared to the derivation cohort. Further, there was little difference between regression models that contained pharmacogenetic coefficients and algorithms containing just non-pharmacogenetic coefficients. The inconsistency of results between the validation cohorts suggests that unaccounted population specific factors cause variability in dosing algorithm performance. Better methods for dosing that take into account inter- and intra-individual variability, at the initiation and maintenance phases of warfarin treatment, are needed.

Zero Distribution of System with Unknown Random Variables Case Study: Avoiding Collision Path

Directory of Open Access Journals (Sweden)

Parman Setyamartana

2014-07-01

Full Text Available This paper presents the stochastic analysis of finding the feasible trajectories of robotics arm motion at obstacle surrounding. Unknown variables are coefficients of polynomials joint angle so that the collision-free motion is achieved. ãk is matrix consisting of these unknown feasible polynomial coefficients. The pattern of feasible polynomial in the obstacle environment shows as random. This paper proposes to model the pattern of this randomness values using random polynomial with unknown variables as coefficients. The behavior of the system will be obtained from zero distribution as the characteristic of such random polynomial. Results show that the pattern of random polynomial of avoiding collision can be constructed from zero distribution. Zero distribution is like building block of the system with obstacles as uncertainty factor. By scale factor k, which has range, the random coefficient pattern can be predicted.

How to know unknown fungi: the role of a herbarium.

Science.gov (United States)

Brock, Patrick M; Döring, Heidi; Bidartondo, Martin I

2009-01-01

The development of a universal approach to the identification of fungi from the environment is impeded by the limited number and narrow phylogenetic range of the named internal transcribed spacer DNA sequences available on GenBank. The goal here was to assess the potential impact of systematic DNA sequencing from a fungal herbarium collection. DNA sequences were generated from a diverse set of 279 specimens deposited at the fungal herbarium of the Royal Botanic Gardens at Kew (UK) and bioinformatic analyses were used to study their overlap with the public database. It is estimated that c. 70% of the herbarium taxonomic diversity is not yet represented in GenBank and that a further c. 10% of our sequences match solely to 'environmental samples' or fungi otherwise unidentified. Here it is shown that the unsampled diversity residing in fungal herbaria can substantially enlarge the coverage of GenBank's fully identified sequence pool to ameliorate the problem of environmental unknowns and to aid in the detection of truly novel fungi by molecular data.

Experiments in Competence Acquisition for Autonomous Mobile Robots

OpenAIRE

Nehmzow, Ulrich

1992-01-01

This thesis addresses the problem of intelligent control of autonomous mobile robots, particularly under circumstances unforeseen by the designer.As the range of applications for autonomous robots widens and increasingly includes operation in unknown environments (exploration) and tasks which are not clearly specifiable a priori (maintenance work), this question is becoming more and more important. It is argued that in order to achieve such flexibility in unforeseen situations it is necess...

Self-Organized Multi-Camera Network for a Fast and Easy Deployment of Ubiquitous Robots in Unknown Environments

Science.gov (United States)

Canedo-Rodriguez, Adrián; Iglesias, Roberto; Regueiro, Carlos V.; Alvarez-Santos, Victor; Pardo, Xose Manuel

2013-01-01

To bring cutting edge robotics from research centres to social environments, the robotics community must start providing affordable solutions: the costs must be reduced and the quality and usefulness of the robot services must be enhanced. Unfortunately, nowadays the deployment of robots and the adaptation of their services to new environments are tasks that usually require several days of expert work. With this in view, we present a multi-agent system made up of intelligent cameras and autonomous robots, which is easy and fast to deploy in different environments. The cameras will enhance the robot perceptions and allow them to react to situations that require their services. Additionally, the cameras will support the movement of the robots. This will enable our robots to navigate even when there are not maps available. The deployment of our system does not require expertise and can be done in a short period of time, since neither software nor hardware tuning is needed. Every system task is automatic, distributed and based on self-organization processes. Our system is scalable, robust, and flexible to the environment. We carried out several real world experiments, which show the good performance of our proposal. PMID:23271604

Self-organized multi-camera network for a fast and easy deployment of ubiquitous robots in unknown environments.

Science.gov (United States)

Canedo-Rodriguez, Adrián; Iglesias, Roberto; Regueiro, Carlos V; Alvarez-Santos, Victor; Pardo, Xose Manuel

2012-12-27

To bring cutting edge robotics from research centres to social environments, the robotics community must start providing affordable solutions: the costs must be reduced and the quality and usefulness of the robot services must be enhanced. Unfortunately, nowadays the deployment of robots and the adaptation of their services to new environments are tasks that usually require several days of expert work. With this in view, we present a multi-agent system made up of intelligent cameras and autonomous robots, which is easy and fast to deploy in different environments. The cameras will enhance the robot perceptions and allow them to react to situations that require their services. Additionally, the cameras will support the movement of the robots. This will enable our robots to navigate even when there are not maps available. The deployment of our system does not require expertise and can be done in a short period of time, since neither software nor hardware tuning is needed. Every system task is automatic, distributed and based on self-organization processes. Our system is scalable, robust, and flexible to the environment. We carried out several real world experiments, which show the good performance of our proposal.

On possible a-priori "imprinting" of General Relativity itself on the performed Lense-Thirring tests with LAGEOS satellites

Science.gov (United States)

Iorio, Lorenzo

2010-02-01

The impact of possible a-priori "imprinting" effects of general relativity itself on recent attempts to measure the general relativistic Lense-Thirring effect with the LAGEOS satellites orbiting the Earth and the terrestrial geopotential models from the dedicated mission GRACE is investigated. It is analytically shown that general relativity, not explicitly solved for in the GRACE-based models, may "imprint" their even zonal harmonic coefficients of low degrees J_l at a non-negligible level, given the present-day accuracy in recovering them. This translates into a bias of the LAGEOS-based relativistic tests as large as the Lense-Thirring effect itself. Further analyses should include general relativity itself in the GRACE data processing by explicitly solving for it.

Recension: Mao - The Unknown Story

DEFF Research Database (Denmark)

Clausen, Søren

2005-01-01

Anmeldelse - kritisk! - til Sveriges førende Kinatidsskrift af Jung Chang & Jon Halliday's sensationelle "Mao - the Unknown Story".......Anmeldelse - kritisk! - til Sveriges førende Kinatidsskrift af Jung Chang & Jon Halliday's sensationelle "Mao - the Unknown Story"....

Organizational Conditions for Dealing with The Unknown Unknown Illustrated by how a Dutch water management authority is preparing for climate change

NARCIS (Netherlands)

Termeer, Catrien J. A. M.; van den Brink, Margo A.

2013-01-01

The central question of this article is the extent to which organizations, governmental authorities in particular, are able to deal with the unknown unknown. Drawing on Weick's work on sensemaking, we introduce seven organizational conditions that can facilitate organizations to be reliable under

Impact of modellers' decisions on hydrological a priori predictions

Science.gov (United States)

Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.

2014-06-01

In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers - using the model of their choice - for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of

Organizational conditions for dealing with the unknown unknown : illustrated by how a Dutch water management authority is preparing for climate change

NARCIS (Netherlands)

Termeer, C.J.A.M.; Brink, van den M.A.

2013-01-01

The central question of this article is the extent to which organizations, governmental authorities in particular, are able to deal with the unknown unknown. Drawing on Weick’s work on sensemaking, we introduce seven organizational conditions that can facilitate organizations to be reliable under

Electrical impedance tomography imaging using a priori ultrasound data

Directory of Open Access Journals (Sweden)

Soleimani Manuchehr

2006-02-01

Full Text Available Abstract Background Different imaging systems (e.g. electrical, magnetic, and ultrasound rely on a wide variety of physical properties, and the datasets obtained from such systems provide only partial information about the unknown true state. One approach is to choose complementary imaging systems, and to combine the information to achieve a better representation. Methods This paper discusses the combination of ultrasound and electrical impedance tomography (EIT information. Ultrasound reflection signals are good at locating sharp acoustic density changes associated with the boundaries of objects. Some boundaries, however, may be indeterminable due to masking from intermediate boundaries or because they are outside the ultrasound beam. Conversely, the EIT data contains relatively low-quality information, but it includes the whole region enclosed by the electrodes. Results Results are shown from a narrowband level-set method applied to 2D and 3D EIT incorporating limited angle ultrasound time of flight data. Conclusion The EIT reconstruction is shown to be faster and more accurate using the additional edge information from both one and four transducer ultrasound systems.

Quantum circuits cannot control unknown operations

International Nuclear Information System (INIS)

Araújo, Mateus; Feix, Adrien; Costa, Fabio; Brukner, Časlav

2014-01-01

One of the essential building blocks of classical computer programs is the ‘if’ clause, which executes a subroutine depending on the value of a control variable. Similarly, several quantum algorithms rely on applying a unitary operation conditioned on the state of a control system. Here we show that this control cannot be performed by a quantum circuit if the unitary is completely unknown. The task remains impossible even if we allow the control to be done modulo a global phase. However, this no-go theorem does not prevent implementing quantum control of unknown unitaries in practice, as any physical implementation of an unknown unitary provides additional information that makes the control possible. We then argue that one should extend the quantum circuit formalism to capture this possibility in a straightforward way. This is done by allowing unknown unitaries to be applied to subspaces and not only to subsystems. (paper)

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

Science.gov (United States)

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.

A priori motion models for four-dimensional reconstruction in gated cardiac SPECT

International Nuclear Information System (INIS)

Lalush, D.S.; Tsui, B.M.W.; Cui, Lin

1996-01-01

We investigate the benefit of incorporating a priori assumptions about cardiac motion in a fully four-dimensional (4D) reconstruction algorithm for gated cardiac SPECT. Previous work has shown that non-motion-specific 4D Gibbs priors enforcing smoothing in time and space can control noise while preserving resolution. In this paper, we evaluate methods for incorporating known heart motion in the Gibbs prior model. The new model is derived by assigning motion vectors to each 4D voxel, defining the movement of that volume of activity into the neighboring time frames. Weights for the Gibbs cliques are computed based on these open-quotes most likelyclose quotes motion vectors. To evaluate, we employ the mathematical cardiac-torso (MCAT) phantom with a new dynamic heart model that simulates the beating and twisting motion of the heart. Sixteen realistically-simulated gated datasets were generated, with noise simulated to emulate a real Tl-201 gated SPECT study. Reconstructions were performed using several different reconstruction algorithms, all modeling nonuniform attenuation and three-dimensional detector response. These include ML-EM with 4D filtering, 4D MAP-EM without prior motion assumption, and 4D MAP-EM with prior motion assumptions. The prior motion assumptions included both the correct motion model and incorrect models. Results show that reconstructions using the 4D prior model can smooth noise and preserve time-domain resolution more effectively than 4D linear filters. We conclude that modeling of motion in 4D reconstruction algorithms can be a powerful tool for smoothing noise and preserving temporal resolution in gated cardiac studies

Known knowns, known unknowns and unknown unknowns in prokaryotic transposition.

Science.gov (United States)

Siguier, Patricia; Gourbeyre, Edith; Chandler, Michael

2017-08-01

Although the phenomenon of transposition has been known for over 60 years, its overarching importance in modifying and streamlining genomes took some time to recognize. In spite of a robust understanding of transposition of some TE, there remain a number of important TE groups with potential high genome impact and unknown transposition mechanisms and yet others, only recently identified by bioinformatics, yet to be formally confirmed as mobile. Here, we point to some areas of limited understanding concerning well established important TE groups with DDE Tpases, to address central gaps in our knowledge of characterised Tn with other types of Tpases and finally, to highlight new potentially mobile DNA species. It is not exhaustive. Examples have been chosen to provide encouragement in the continued exploration of the considerable prokaryotic mobilome especially in light of the current threat to public health posed by the spread of multiple Ab R . Copyright © 2017 Elsevier Ltd. All rights reserved.

Clostridium difficile: A healthcare-associated infection of unknown ...

African Journals Online (AJOL)

Clostridium difficile: A healthcare-associated infection of unknown significance in adults in sub-Saharan Africa. ... Abstract. Background: Clostridium difficile infection (CDI) causes a high burden of disease in high-resource healthcare systems, with significant morbidity, mortality, and financial implications. CDI is a ...

'Aussie normals': an a priori study to develop clinical chemistry reference intervals in a healthy Australian population.

Science.gov (United States)

Koerbin, G; Cavanaugh, J A; Potter, J M; Abhayaratna, W P; West, N P; Glasgow, N; Hawkins, C; Armbruster, D; Oakman, C; Hickman, P E

2015-02-01

Development of reference intervals is difficult, time consuming, expensive and beyond the scope of most laboratories. The Aussie Normals study is a direct a priori study to determine reference intervals in healthy Australian adults. All volunteers completed a health and lifestyle questionnaire and exclusion was based on conditions such as pregnancy, diabetes, renal or cardiovascular disease. Up to 91 biochemical analyses were undertaken on a variety of analytical platforms using serum samples collected from 1856 volunteers. We report on our findings for 40 of these analytes and two calculated parameters performed on the Abbott ARCHITECTci8200/ci16200 analysers. Not all samples were analysed for all assays due to volume requirements or assay/instrument availability. Results with elevated interference indices and those deemed unsuitable after clinical evaluation were removed from the database. Reference intervals were partitioned based on the method of Harris and Boyd into three scenarios, combined gender, males and females and age and gender. We have performed a detailed reference interval study on a healthy Australian population considering the effects of sex, age and body mass. These reference intervals may be adapted to other manufacturer's analytical methods using method transference.

Melanoma of unknown origin: a case series.

LENUS (Irish Health Repository)

Kelly, J

2010-12-01

The natural history of metastatic melanoma involving lymph nodes, in the absence of a known primary site (cutaneous, ocular or mucosal) has, to date, been poorly defined; and the optimal management of this rare subtype of disease is therefore unclear. Melanomas of unknown primary site (MUP) are estimated to comprise between 3.7 and 6% of all melanomas (Anbari et al. in Cancer 79:1861-1821, 1997).

Chinese Unknown Word Recognition for PCFG-LA Parsing

Directory of Open Access Journals (Sweden)

Qiuping Huang

2014-01-01

Full Text Available This paper investigates the recognition of unknown words in Chinese parsing. Two methods are proposed to handle this problem. One is the modification of a character-based model. We model the emission probability of an unknown word using the first and last characters in the word. It aims to reduce the POS tag ambiguities of unknown words to improve the parsing performance. In addition, a novel method, using graph-based semisupervised learning (SSL, is proposed to improve the syntax parsing of unknown words. Its goal is to discover additional lexical knowledge from a large amount of unlabeled data to help the syntax parsing. The method is mainly to propagate lexical emission probabilities to unknown words by building the similarity graphs over the words of labeled and unlabeled data. The derived distributions are incorporated into the parsing process. The proposed methods are effective in dealing with the unknown words to improve the parsing. Empirical results for Penn Chinese Treebank and TCT Treebank revealed its effectiveness.

Farmer knowledge and a priori risk analysis: pre-release evaluation of genetically modified Roundup Ready wheat across the Canadian prairies.

Science.gov (United States)

Mauro, Ian J; McLachlan, Stéphane M; Van Acker, Rene C

2009-09-01

The controversy over the world's first genetically modified (GM) wheat, Roundup Ready wheat (RRW), challenged the efficacy of 'science-based' risk assessment, largely because it excluded the public, particularly farmers, from meaningful input. Risk analysis, in contrast, is broader in orientation as it incorporates scientific data as well as socioeconomic, ethical, and legal concerns, and considers expert and lay input in decision-making. Local knowledge (LK) of farmers is experience-based and represents a rich and reliable source of information regarding the impacts associated with agricultural technology, thereby complementing the scientific data normally used in risk assessment. The overall goal of this study was to explore the role of farmer LK in the a priori risk analysis of RRW. In 2004, data were collected from farmers using mail surveys sent across the three prairie provinces (i.e., Manitoba, Saskatchewan, and Alberta) in western Canada. A stratified random sampling approach was used whereby four separate sampling districts were identified in regions where wheat was grown for each province. Rural post offices were randomly selected in each sampling district using Canada Post databases such that no one post office exceeded 80 farms and that each sampling district comprised 225-235 test farms (n = 11,040). In total, 1,814 people responded, representing an adjusted response rate for farmers of 33%. A subsequent telephone survey showed there was no non-response bias. The primary benefits associated with RRW were associated with weed control, whereas risks emphasized the importance of market harm, corporate control, agronomic problems, and the likelihood of contamination. Overall, risks were ranked much higher than benefits, and the great majority of farmers were highly critical of RRW commercialization. In total, 83.2% of respondents disagreed that RRW should have unconfined release into the environment. Risk was associated with distrust in government and

Comparative study and implementation of images re processing methods for the tomography by positrons emission: interest of taking into account a priori information; Etude comparative et implementation de methodes de reconstruction d`images pour la tomographie par emission de positons: interet de la prise en compte d`informations a priori

Energy Technology Data Exchange (ETDEWEB)

Bouchet, F.

1996-09-25

The tomography by positron emission has for aim to explore an organ by injection of a radiotracer and bidimensional representation with processing techniques. The most used in routine is the filtered retro projection that gives smoothed images. this work realizes a comparative study of new techniques. The methods of preservations of contours are studied here, the idea is to use NMR imaging as a priori information. Two techniques of images construction are viewed more particularly: the resolution by pseudo inverse and the Bayesian method. (N.C.).

Adaptive control of chaotic systems with stochastic time varying unknown parameters

Energy Technology Data Exchange (ETDEWEB)

Salarieh, Hassan [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: salarieh@mech.sharif.edu; Alasty, Aria [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: aalasti@sharif.edu

2008-10-15

In this paper based on the Lyapunov stability theorem, an adaptive control scheme is proposed for stabilizing the unstable periodic orbits (UPO) of chaotic systems. It is assumed that the chaotic system has some linearly dependent unknown parameters which are stochastically time varying. The stochastic parameters are modeled through the Weiner process derivative. To demonstrate the effectiveness of the proposed technique it has been applied to the Lorenz, Chen and Rossler dynamical systems, as some case studies. Simulation results indicate that the proposed adaptive controller has a high performance in stabilizing the UPO of chaotic systems in noisy environment.

Moving carbonation fronts in concrete: a moving-sharp-interface approach

NARCIS (Netherlands)

Muntean, A.; Böhm, M.; Kropp, J.

2011-01-01

We present a new modeling strategy for predicting the penetration of carbonation reaction fronts in concrete. The approach relies on the assumption that carbonation reaction concentrates macroscopically on an a priori unknown narrow strip (called reaction front) moving into concrete gradually

Analysing Trust Transitivity and The Effects of Unknown Dependence

Directory of Open Access Journals (Sweden)

Touhid Bhuiyan

2010-03-01

Full Text Available Trust can be used to improve online automated recommendation within a given domain. Trust transitivity is used to make it successful. But trust transitivity has different interpretations. Trust and trust transitivity; both are the human mental phenomenon and for this reason, there is no such thing as objective transitivity. Trust transitivity and trust fusion both are important elements in computational trust. This paper analyses the parameter dependence problem in trust transitivity and proposes some definitions considering the effects of base rate. In addition, it also proposes belief functions based on subjective logic to analyse trust transitivity of three specified cases with sensitive and insensitive based rate. Then it presents a quantitative analysis of the effects of unknown dependence problem in an interconnected network environment; such Internet.

A comparative study of amplitude calibrations for the East Asia VLBI Network: A priori and template spectrum methods

Science.gov (United States)

Cho, Ilje; Jung, Taehyun; Zhao, Guang-Yao; Akiyama, Kazunori; Sawada-Satoh, Satoko; Kino, Motoki; Byun, Do-Young; Sohn, Bong Won; Shibata, Katsunori M.; Hirota, Tomoya; Niinuma, Kotaro; Yonekura, Yoshinori; Fujisawa, Kenta; Oyama, Tomoaki

2017-12-01

We present the results of a comparative study of amplitude calibrations for the East Asia VLBI Network (EAVN) at 22 and 43 GHz using two different methods of an "a priori" and a "template spectrum", particularly on lower declination sources. Using observational data sets of early EAVN observations, we investigated the elevation-dependence of the gain values at seven stations of the KaVA (KVN and VERA Array) and three additional telescopes in Japan (Takahagi 32 m, Yamaguchi 32 m, and Nobeyama 45 m). By comparing the independently obtained gain values based on these two methods, we found that the gain values from each method were consistent within 10% at elevations higher than 10°. We also found that the total flux densities of two images produced from the different amplitude calibrations were in agreement within 10% at both 22 and 43 GHz. By using the template spectrum method, furthermore, the additional radio telescopes can participate in KaVA (i.e., EAVN), giving a notable sensitivity increase. Therefore, our results will constrain the detailed conditions in order to measure the VLBI amplitude reliably using EAVN, and discuss the potential of possible expansion to telescopes comprising EAVN.

Mobile assistant for unknown caller identification

OpenAIRE

Hribernik, Andraž

2012-01-01

The main motivation of this diploma thesis is a development of Android application, which helps user of application to find out who is the owner of unknown phone number. Data source for finding unknown phone number are free available web sources. Through the development of prototype, data from different web sources were integrated. Result of this integration is shown in Android application. Data integration includes access to semi-structured data on web portal of Phone Directory of Slovenia, ...

MoCha: Molecular Characterization of Unknown Pathways.

Science.gov (United States)

Lobo, Daniel; Hammelman, Jennifer; Levin, Michael

2016-04-01

Automated methods for the reverse-engineering of complex regulatory networks are paving the way for the inference of mechanistic comprehensive models directly from experimental data. These novel methods can infer not only the relations and parameters of the known molecules defined in their input datasets, but also unknown components and pathways identified as necessary by the automated algorithms. Identifying the molecular nature of these unknown components is a crucial step for making testable predictions and experimentally validating the models, yet no specific and efficient tools exist to aid in this process. To this end, we present here MoCha (Molecular Characterization), a tool optimized for the search of unknown proteins and their pathways from a given set of known interacting proteins. MoCha uses the comprehensive dataset of protein-protein interactions provided by the STRING database, which currently includes more than a billion interactions from over 2,000 organisms. MoCha is highly optimized, performing typical searches within seconds. We demonstrate the use of MoCha with the characterization of unknown components from reverse-engineered models from the literature. MoCha is useful for working on network models by hand or as a downstream step of a model inference engine workflow and represents a valuable and efficient tool for the characterization of unknown pathways using known data from thousands of organisms. MoCha and its source code are freely available online under the GPLv3 license.

An a priori analysis of how solar energy production will affect the balance of payment account in one developing Latin American country

Energy Technology Data Exchange (ETDEWEB)

Stavy, Michael [Chicago, Illinois (United States)

2000-07-01

This paper studies a model developing Latin American country (hypotheria) with a weak currency (the hypo is the monetary unit), a trade deficit (including being a net importer of fossil fuels) and a sensitive balance of payments situation. There is an a priori analysis of the effect of domestic solar energy production on Hypotheria's positive effect is the BoP Value of domestic solar energy. Many forms of solar energy are not cost competitive with fossil fuels. Because solar energy production does not emit greenhouse Value and the BoP Value of solar energy should be used to reduce the cost of solar energy projects in Hypotheria and to make the solar energy cost competitive with fossil fuels. [Spanish] Este articulo estudia un modelo de un pais Latinoamericano en desarrollo (Hypoteria) con moneda debil (el hypo es la unidad monetaria), un deficit comercial (incluyendo el ser un importador neto de combustibles fosiles) y un balance precario en la situacion de pagos. Existe un analisis a priori sobre el efecto de la produccion domestica de energia solar en un efecto positivo de Hypoteria que es el Valor de la Balanza de Pagos (BoP) de la energia solar domestica. Muchas formas de energia solar no son competitivas en costo con los combustibles fosiles debido a que la produccion de energia solar no emite un Valor de invernadero, y el Valor de la Balanza de Pagos, debe ser utilizado para reducir los costos de los proyectos de energia solar en Hypoteria y asi hacer el costo de la energia solar competitiva con los combustibles fosiles.

Optimization of biomathematical model predictions for cognitive performance impairment in individuals: accounting for unknown traits and uncertain states in homeostatic and circadian processes.

Science.gov (United States)

Van Dongen, Hans P A; Mott, Christopher G; Huang, Jen-Kuang; Mollicone, Daniel J; McKenzie, Frederic D; Dinges, David F

2007-09-01

Current biomathematical models of fatigue and performance do not accurately predict cognitive performance for individuals with a priori unknown degrees of trait vulnerability to sleep loss, do not predict performance reliably when initial conditions are uncertain, and do not yield statistically valid estimates of prediction accuracy. These limitations diminish their usefulness for predicting the performance of individuals in operational environments. To overcome these 3 limitations, a novel modeling approach was developed, based on the expansion of a statistical technique called Bayesian forecasting. The expanded Bayesian forecasting procedure was implemented in the two-process model of sleep regulation, which has been used to predict performance on the basis of the combination of a sleep homeostatic process and a circadian process. Employing the two-process model with the Bayesian forecasting procedure to predict performance for individual subjects in the face of unknown traits and uncertain states entailed subject-specific optimization of 3 trait parameters (homeostatic build-up rate, circadian amplitude, and basal performance level) and 2 initial state parameters (initial homeostatic state and circadian phase angle). Prior information about the distribution of the trait parameters in the population at large was extracted from psychomotor vigilance test (PVT) performance measurements in 10 subjects who had participated in a laboratory experiment with 88 h of total sleep deprivation. The PVT performance data of 3 additional subjects in this experiment were set aside beforehand for use in prospective computer simulations. The simulations involved updating the subject-specific model parameters every time the next performance measurement became available, and then predicting performance 24 h ahead. Comparison of the predictions to the subjects' actual data revealed that as more data became available for the individuals at hand, the performance predictions became

IN-cross Entropy Based MAGDM Strategy under Interval Neutrosophic Set Environment

Directory of Open Access Journals (Sweden)

Shyamal Dalapati

2017-12-01

Full Text Available Cross entropy measure is one of the best way to calculate the divergence of any variable from the priori one variable. We define a new cross entropy measure under interval neutrosophic set (INS environment, which we call IN-cross entropy measure and prove its basic properties. We also develop weighted IN-cross entropy measure and investigats its basic properties. Based on the weighted IN-cross entropy measure, we develop a novel strategy for multi attribute group decision making (MAGDM strategy under interval neutrosophic environment. The proposed multi attribute group decision making strategy is compared with the existing cross entropy measure based strategy in the literature under interval neutrosophic set environment. Finally, an illustrative example of multi attribute group decision making problem is solved to show the feasibility, validity and efficiency of the proposed MAGDM strategy.

Known Unknowns in Judgment and Choice

OpenAIRE

Walters, Daniel

2017-01-01

This dissertation investigates how people make inferences about missing information. Whereas most prior literature focuses on how people process known information, I show that the extent to which people make inferences about missing information impacts judgments and choices. Specifically, I investigate how (1) awareness of known unknowns affects overconfidence in judgment in Chapter 1, (2) beliefs about the knowability of unknowns impacts investment strategies in Chapter 2, and (3) inferences...

Numerical method of identification of an unknown source term in a heat equation

Directory of Open Access Journals (Sweden)

Fatullayev Afet Golayo?lu

2002-01-01

Full Text Available A numerical procedure for an inverse problem of identification of an unknown source in a heat equation is presented. Approach of proposed method is to approximate unknown function by polygons linear pieces which are determined consecutively from the solution of minimization problem based on the overspecified data. Numerical examples are presented.

Unknown foundation determination for scour.

Science.gov (United States)

2012-04-01

Unknown foundations affect about 9,000 bridges in Texas. For bridges over rivers, this creates a problem : regarding scour decisions as the calculated scour depth cannot be compared to the foundation depth, and a : very conservative costly approach m...

A sensitivity analysis approach to control of manipulators with unknown load

International Nuclear Information System (INIS)

Tzes, A.; Yurkovich, S.

1987-01-01

This paper presents a straightforward control strategy applied to an N-link manipulator holding an unknown load and driving its end effector along a prespecified trajectory. The control is constituted into two primary components. The non-adaptive component is derived from the inverse problem technique while the adaptive component is computed via the application of sensitivity analysis applied to the complete, centralized dynamic model of the manipulator. The result is a robust adaptive controller which tunes its parameters at specified time instants and can withstand all expected variations of the payload. The control synthesis is illustrated by simulations in a 2-link planar manipulator holding an unknown load

Determination of the origin of unknown irradiated nuclear fuel.

Science.gov (United States)

Nicolaou, G

2006-01-01

An isotopic fingerprinting method is presented to determine the origin of unknown nuclear material with forensic importance. Spent nuclear fuel of known origin has been considered as the 'unknown' nuclear material in order to demonstrate the method and verify its prediction capabilities. The method compares, using factor analysis, the measured U, Pu isotopic compositions of the 'unknown' material with U, Pu isotopic compositions simulating well known spent fuels from a range of commercial nuclear power stations. Then, the 'unknown' fuel has the same origin as the commercial fuel with which it exhibits the highest similarity in U, Pu compositions.

Determination of the origin of unknown irradiated nuclear fuel

International Nuclear Information System (INIS)

Nicolaou, G.

2006-01-01

An isotopic fingerprinting method is presented to determine the origin of unknown nuclear material with forensic importance. Spent nuclear fuel of known origin has been considered as the 'unknown' nuclear material in order to demonstrate the method and verify its prediction capabilities. The method compares, using factor analysis, the measured U, Pu isotopic compositions of the 'unknown' material with U, Pu isotopic compositions simulating well known spent fuels from a range of commercial nuclear power stations. Then, the 'unknown' fuel has the same origin as the commercial fuel with which it exhibits the highest similarity in U, Pu compositions

Optimal conclusive teleportation of a d-dimensional two-particle unknown quantum state

Institute of Scientific and Technical Information of China (English)

Yang Yu-Guang; Wen Qiao-Yan; Zhu Fu-Chen

2006-01-01

A conclusive teleportation protocol of a d-dimensional two-particle unknown quantum state using three ddimensional particles in an arbitrary pure state is proposed. A sender teleports the unknown state conclusively to a receiver by using the positive operator valued measure(POVM) and introducing an ancillary qudit to perform the generalized Bell basis measurement. We calculate the optimal teleportation fidelity. We also discuss and analyse the reason why the information on the teleported state is lost in the course of the protocol.

First attempt to assess the viability of bluefin tuna spawning events in offshore cages located in an a priori favourable larval habitat

Directory of Open Access Journals (Sweden)

Patricia Reglero

2013-10-01

Full Text Available Most of the Atlantic bluefin tuna caught by the purse-seine fleet in the Mediterranean Sea are transferred alive into transport cages and towed to coastal facilities where they are fattened. This major fishery is targeting aggregations of reproductive bluefin tuna that continue spawning within the transport cages. Our study is the first attempt to assess the viability of the spawning events within transport cages placed offshore in a priori favourable locations for larval survival. The study was conducted in June 2010 in the Balearic Sea, a main spawning area for bluefin tuna in the Mediterranean. The location of two transport cages, one with wild and one with captive tuna, coincide with the situation of the chlorophyll front using satellite imagery as a proxy for the salinity front between resident surface waters and those of recent Atlantic origin. The results showed that bluefin tuna eggs were spawned almost every day within the two cages but few or no larvae were found. The expected larval densities estimated after applying mortality curves to the daily egg densities observed in the cages were higher than the sampled larval densities. The trajectories of the eggs after hatching estimated from a particle tracking model based on observed geostrophic currents and a drifter deployed adjacent to the cage suggest that larvae were likely to be caught close to the cages within the sampling dates. Spawning events in captive tuna in transport cages may hatch into larvae though they may experience higher mortality rates than expected in natural populations. The causes of the larval mortality are further discussed in the text. Such studies should be repeated in other spawning areas in the Mediterranean if spawning in cages located offshore in areas favourable a priori for larval survival is likely to be considered a management measurement to minimize the impact of purse-seine fishing on tuna.

A priori estimation of accuracy and of the number of wells to be employed in limiting dilution assays

Directory of Open Access Journals (Sweden)

J.G. Chaui-Berlinck

2000-08-01

Full Text Available The use of limiting dilution assay (LDA for assessing the frequency of responders in a cell population is a method extensively used by immunologists. A series of studies addressing the statistical method of choice in an LDA have been published. However, none of these studies has addressed the point of how many wells should be employed in a given assay. The objective of this study was to demonstrate how a researcher can predict the number of wells that should be employed in order to obtain results with a given accuracy, and, therefore, to help in choosing a better experimental design to fulfill one's expectations. We present the rationale underlying the expected relative error computation based on simple binomial distributions. A series of simulated in machina experiments were performed to test the validity of the a priori computation of expected errors, thus confirming the predictions. The step-by-step procedure of the relative error estimation is given. We also discuss the constraints under which an LDA must be performed.

Function analysis of unknown genes

DEFF Research Database (Denmark)

Rogowska-Wrzesinska, A.

2002-01-01

  This thesis entitled "Function analysis of unknown genes" presents the use of proteome analysis for the characterisation of yeast (Saccharomyces cerevisiae) genes and their products (proteins especially those of unknown function). This study illustrates that proteome analysis can be used...... to describe different aspects of molecular biology of the cell, to study changes that occur in the cell due to overexpression or deletion of a gene and to identify various protein modifications. The biological questions and the results of the described studies show the diversity of the information that can...... genes and proteins. It reports the first global proteome database collecting 36 yeast single gene deletion mutants and selecting over 650 differences between analysed mutants and the wild type strain. The obtained results show that two-dimensional gel electrophoresis and mass spectrometry based proteome...

Visual identification and similarity measures used for on-line motion planning of autonomous robots in unknown environments

Science.gov (United States)

Martínez, Fredy; Martínez, Fernando; Jacinto, Edwar

2017-02-01

In this paper we propose an on-line motion planning strategy for autonomous robots in dynamic and locally observable environments. In this approach, we first visually identify geometric shapes in the environment by filtering images. Then, an ART-2 network is used to establish the similarity between patterns. The proposed algorithm allows that a robot establish its relative location in the environment, and define its navigation path based on images of the environment and its similarity to reference images. This is an efficient and minimalist method that uses the similarity of landmark view patterns to navigate to the desired destination. Laboratory tests on real prototypes demonstrate the performance of the algorithm.

Liability for Unknown Risks: A Law and Economics Perspective

NARCIS (Netherlands)

M.G. Faure (Michael); L.T. Visscher (Louis); F. Weber (Franziska)

2017-01-01

textabstractIn the law and economics literature liability is generally regarded as an instrument which provides potential tortfeasors with incentives for optimal care taking. The question, however, arises whether liability can still provide those incentives when risks are unknown. That is the

Psychosocial work environment among immigrant and Danish cleaners

DEFF Research Database (Denmark)

Olesen, Kasper; Carneiro, Isabella G; Jørgensen, Marie B

2012-01-01

Non-Western cleaners have been shown to have poorer health than their Danish colleagues. One reason could be a poorer psychosocial work environment. However, it is unknown if differences in self-reported psychosocial work environment exist between non-Western and Danish workers within the same so...

Running over unknown rough terrain with a one-legged planar robot

International Nuclear Information System (INIS)

Andrews, Ben; Miller, Bruce; Clark, Jonathan E; Schmitt, John

2011-01-01

The ability to traverse unknown, rough terrain is an advantage that legged locomoters have over their wheeled counterparts. However, due to the complexity of multi-legged systems, research in legged robotics has not yet been able to reproduce the agility found in the animal kingdom. In an effort to reduce the complexity of the problem, researchers have developed single-legged models to gain insight into the fundamental dynamics of legged running. Inspired by studies of animal locomotion, researchers have proposed numerous control strategies to achieve stable, one-legged running over unknown, rough terrain. One such control strategy incorporates energy variations into the system during the stance phase by changing the force-free leg length as a sinusoidal function of time. In this research, a one-legged planar robot capable of implementing this and other state-of-the-art control strategies was designed and built. Both simulated and experimental results were used to determine and compare the stability of the proposed controllers as the robot was subjected to unknown drop and raised step perturbations equal to 25% of the nominal leg length. This study illustrates the relative advantages of utilizing a minimal-sensing, active energy removal control scheme to stabilize running over rough terrain.

Advancement of vision-based SLAM from static to dynamic environments

CSIR Research Space (South Africa)

Pancham, A

2012-11-01

Full Text Available Simultaneous Localization And Mapping (SLAM) allows a mobile robot to construct a map of an unknown, static environment and simultaneously localize itself. Real world environments, however, have dynamic objects such as people, doors that open...

A Virtual Environment for People Who Are Blind - A Usability Study.

Science.gov (United States)

Lahav, O; Schloerb, D W; Kumar, S; Srinivasan, M A

2012-01-01

For most people who are blind, exploring an unknown environment can be unpleasant, uncomfortable, and unsafe. Over the past years, the use of virtual reality as a learning and rehabilitation tool for people with disabilities has been on the rise. This research is based on the hypothesis that the supply of appropriate perceptual and conceptual information through compensatory sensorial channels may assist people who are blind with anticipatory exploration. In this research we developed and tested the BlindAid system, which allows the user to explore a virtual environment. The two main goals of the research were: (a) evaluation of different modalities (haptic and audio) and navigation tools, and (b) evaluation of spatial cognitive mapping employed by people who are blind. Our research included four participants who are totally blind. The preliminary findings confirm that the system enabled participants to develop comprehensive cognitive maps by exploring the virtual environment.

A Stochastic Model of Plausibility in Live Virtual Constructive Environments

Science.gov (United States)

2017-09-14

from the model parameters that are inputs to the computer model ( mathematical model) but whose exact values are unknown to experimentalists and...Environments Jeremy R. Millar Follow this and additional works at: https://scholar.afit.edu/etd Part of the Computer Sciences Commons This Dissertation...25 3.3 Computing Plausibility Exceedance Probabilities . . . . . . . . . . . . . . . . . . . 28 IV

Numerical aspects of drift kinetic turbulence: Ill-posedness, regularization and a priori estimates of sub-grid-scale terms

KAUST Repository

Samtaney, Ravi

2012-01-01

We present a numerical method based on an Eulerian approach to solve the Vlasov-Poisson system for 4D drift kinetic turbulence. Our numerical approach uses a conservative formulation with high-order (fourth and higher) evaluation of the numerical fluxes coupled with a fourth-order accurate Poisson solver. The fluxes are computed using a low-dissipation high-order upwind differencing method or a tuned high-resolution finite difference method with no numerical dissipation. Numerical results are presented for the case of imposed ion temperature and density gradients. Different forms of controlled regularization to achieve a well-posed system are used to obtain convergent resolved simulations. The regularization of the equations is achieved by means of a simple collisional model, by inclusion of an ad-hoc hyperviscosity or artificial viscosity term or by implicit dissipation in upwind schemes. Comparisons between the various methods and regularizations are presented. We apply a filtering formalism to the Vlasov equation and derive sub-grid-scale (SGS) terms analogous to the Reynolds stress terms in hydrodynamic turbulence. We present a priori quantifications of these SGS terms in resolved simulations of drift-kinetic turbulence by applying a sharp filter. © 2012 IOP Publishing Ltd.

Numerical aspects of drift kinetic turbulence: ill-posedness, regularization and a priori estimates of sub-grid-scale terms

International Nuclear Information System (INIS)

Samtaney, Ravi

2012-01-01

We present a numerical method based on an Eulerian approach to solve the Vlasov-Poisson system for 4D drift kinetic turbulence. Our numerical approach uses a conservative formulation with high-order (fourth and higher) evaluation of the numerical fluxes coupled with a fourth-order accurate Poisson solver. The fluxes are computed using a low-dissipation high-order upwind differencing method or a tuned high-resolution finite difference method with no numerical dissipation. Numerical results are presented for the case of imposed ion temperature and density gradients. Different forms of controlled regularization to achieve a well-posed system are used to obtain convergent resolved simulations. The regularization of the equations is achieved by means of a simple collisional model, by inclusion of an ad-hoc hyperviscosity or artificial viscosity term or by implicit dissipation in upwind schemes. Comparisons between the various methods and regularizations are presented. We apply a filtering formalism to the Vlasov equation and derive sub-grid-scale (SGS) terms analogous to the Reynolds stress terms in hydrodynamic turbulence. We present a priori quantifications of these SGS terms in resolved simulations of drift-kinetic turbulence by applying a sharp filter.

Tomographic image via background subtraction using an x-ray projection image and a priori computed tomography

International Nuclear Information System (INIS)

Zhang Jin; Yi Byongyong; Lasio, Giovanni; Suntharalingam, Mohan; Yu, Cedric

2009-01-01

Kilovoltage x-ray projection images (kV images for brevity) are increasingly available in image guided radiotherapy (IGRT) for patient positioning. These images are two-dimensional (2D) projections of a three-dimensional (3D) object along the x-ray beam direction. Projecting a 3D object onto a plane may lead to ambiguities in the identification of anatomical structures and to poor contrast in kV images. Therefore, the use of kV images in IGRT is mainly limited to bony landmark alignments. This work proposes a novel subtraction technique that isolates a slice of interest (SOI) from a kV image with the assistance of a priori information from a previous CT scan. The method separates structural information within a preselected SOI by suppressing contributions to the unprocessed projection from out-of-SOI-plane structures. Up to a five-fold increase in the contrast-to-noise ratios (CNRs) was observed in selected regions of the isolated SOI, when compared to the original unprocessed kV image. The tomographic image via background subtraction (TIBS) technique aims to provide a quick snapshot of the slice of interest with greatly enhanced image contrast over conventional kV x-ray projections for fast and accurate image guidance of radiation therapy. With further refinements, TIBS could, in principle, provide real-time tumor localization using gantry-mounted x-ray imaging systems without the need for implanted markers.

<<Unknown>> earthquakes: a growing contribution to the Catalogue of Strong Italian Earthquakes

Directory of Open Access Journals (Sweden)

E. Guidoboni

2000-06-01

Full Text Available The particular structure of the research into historical seismology found in this catalogue has allowed a lot of information about unknown seismic events to be traced. This new contribution to seismologic knowledge mainly consists in: i the retrieval and organisation within a coherent framework of documentary evidence of earthquakes that took place between the Middle Ages and the sixteenth century; ii the improved knowledge of seismic events, even destructive events, which in the past had been "obscured" by large earthquakes; iii the identification of earthquakes in "silent" seismic areas. The complex elements to be taken into account when dealing with unknown seismic events have been outlined; much "new" information often falls into one of the following categories: simple chronological errors relative to other well-known events; descriptions of other natural phenomena, though defined in texts as "earthquakes" (landslides, hurricanes, tornadoes, etc.; unknown tremors belonging to known seismic periods; tremors that may be connected with events which have been catalogued under incorrect dates and with very approximate estimates of location and intensity. This proves that this was not a real seismic "silence" but a research vacuum.

Implementation of a Mobile Robot Platform Navigating in Dynamic Environment

Directory of Open Access Journals (Sweden)

Belaidi Hadjira

2017-01-01

Full Text Available Currently, problems of autonomous wheeled mobile robots in unknown environments are great challenge. Obstacle avoidance and path planning are the back bone of autonomous control as it makes robot able to reach its destination without collision. Dodging obstacles in dynamic and uncertain environment is the most complex part of obstacle avoidance and path planning tasks. This work deals with the implementation of an easy approach of static and dynamic obstacles avoidance. The robot starts by executing a free optimal path loaded into its controller; then, it uses its sensors to avoid the unexpected obstacles which may occur in that path during navigation.

Twelve previously unknown phage genera are ubiquitous in global oceans.

Science.gov (United States)

Holmfeldt, Karin; Solonenko, Natalie; Shah, Manesh; Corrier, Kristen; Riemann, Lasse; Verberkmoes, Nathan C; Sullivan, Matthew B

2013-07-30

Viruses are fundamental to ecosystems ranging from oceans to humans, yet our ability to study them is bottlenecked by the lack of ecologically relevant isolates, resulting in "unknowns" dominating culture-independent surveys. Here we present genomes from 31 phages infecting multiple strains of the aquatic bacterium Cellulophaga baltica (Bacteroidetes) to provide data for an underrepresented and environmentally abundant bacterial lineage. Comparative genomics delineated 12 phage groups that (i) each represent a new genus, and (ii) represent one novel and four well-known viral families. This diversity contrasts the few well-studied marine phage systems, but parallels the diversity of phages infecting human-associated bacteria. Although all 12 Cellulophaga phages represent new genera, the podoviruses and icosahedral, nontailed ssDNA phages were exceptional, with genomes up to twice as large as those previously observed for each phage type. Structural novelty was also substantial, requiring experimental phage proteomics to identify 83% of the structural proteins. The presence of uncommon nucleotide metabolism genes in four genera likely underscores the importance of scavenging nutrient-rich molecules as previously seen for phages in marine environments. Metagenomic recruitment analyses suggest that these particular Cellulophaga phages are rare and may represent a first glimpse into the phage side of the rare biosphere. However, these analyses also revealed that these phage genera are widespread, occurring in 94% of 137 investigated metagenomes. Together, this diverse and novel collection of phages identifies a small but ubiquitous fraction of unknown marine viral diversity and provides numerous environmentally relevant phage-host systems for experimental hypothesis testing.

[Security of hospital infusion practices: From an a priori risk analysis to an improvement action plan].

Science.gov (United States)

Pignard, J; Cosserant, S; Traore, O; Souweine, B; Sautou, V

2016-03-01

Infusion in care units, and all the more in intensive care units, is a complex process which can be the source of many risks for the patient. Under cover of an institutional approach for the improvement of the quality and safety of patient healthcare, a risk mapping infusion practices was performed. The analysis was focused on intravenous infusion situations in adults, the a priori risk assessment methodology was applied and a multidisciplinary work group established. Forty-three risks were identified for the infusion process (prescription, preparation and administration). The risks' assessment and the existing means of control showed that 48% of them would have a highly critical patient security impact. Recommendations were developed for 20 risks considered to be most critical, to limit their occurrence and severity, and improve their control level. An institutional action plan was developed and validated in the Drug and Sterile Medical Devices Commission. This mapping allowed the realization of an exhaustive inventory of potential risks associated with the infusion. At the end of this work, multidisciplinary groups were set up to work on different themes and regular quarterly meetings were established to follow the progress of various projects. Risk mapping will be performed in pediatric and oncology unit where the risks associated with the handling of toxic products is omnipresent. Copyright © 2015 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.

Protocol for counterfactually transporting an unknown qubit

Directory of Open Access Journals (Sweden)

Hatim eSalih

2016-01-01

Full Text Available Quantum teleportation circumvents the uncertainty principle using dual channels: a quantum one consisting of previously-shared entanglement, and a classical one, together allowing the disembodied transport of an unknown quantum state over distance. It has recently been shown that a classical bit can be counterfactually communicated between two parties in empty space, Alice and Bob. Here, by using our dual version of the chained quantum Zeno effect to achieve a counterfactual CNOT gate, we propose a protocol for transporting an unknown qubit counterfactually, that is without any physical particles travelling between Alice and Bob—no classical channel and no previously-shared entanglement.

A Size Exclusion Chromatography Laboratory with Unknowns for Introductory Students

Science.gov (United States)

McIntee, Edward J.; Graham, Kate J.; Colosky, Edward C.; Jakubowski, Henry V.

2015-01-01

Size exclusion chromatography is an important technique in the separation of biological and polymeric samples by molecular weight. While a number of laboratory experiments have been published that use this technique for the purification of large molecules, this is the first report of an experiment that focuses on purifying an unknown small…

Classification of Unknown Thermocouple Types Using Similarity Factor Measurement

Directory of Open Access Journals (Sweden)

Seshu K. DAMARLA

2011-01-01

Full Text Available In contrast to classification using PCA method, a new methodology is proposed for type identification of unknown thermocouple. The new methodology is based on calculating the degree of similarity between two multivariate datasets using two types of similarity factors. One similarity factor is based on principle component analysis and the angles between the principle component subspaces while the other is based on the Mahalanobis distance between the datasets. Datasets containing thermo-emfs against given temperature ranges are formed for each type of thermocouple (e.g. J, K, S, T, R, E, B and N type by experimentation are considered as reference datasets. Datasets corresponding to unknown type are captured. Similarity factor between the datasets one of which being the unknown type and the other being each known type are compared. When maximum similarity factor occurs, then the class of unknown type is allocated to that of known type.

Identification of dietary patterns associated with obesity in a nationally representative survey of Canadian adults: application of a priori, hybrid, and simplified dietary pattern techniques.

Science.gov (United States)

Jessri, Mahsa; Wolfinger, Russell D; Lou, Wendy Y; L'Abbé, Mary R

2017-03-01

Background: Analyzing the effects of dietary patterns is an important approach for examining the complex role of nutrition in the etiology of obesity and chronic diseases. Objectives: The objectives of this study were to characterize the dietary patterns of Canadians with the use of a priori, hybrid, and simplified dietary pattern techniques, and to compare the associations of these patterns with obesity risk in individuals with and without chronic diseases (unhealthy and healthy obesity). Design: Dietary recalls from 11,748 participants (≥18 y of age) in the cross-sectional, nationally representative Canadian Community Health Survey 2.2 were used. A priori dietary pattern was characterized with the use of the previously validated 2015 Dietary Guidelines for Americans Adherence Index (DGAI). Weighted partial least squares (hybrid method) was used to derive an energy-dense (ED), high-fat (HF), low-fiber density (LFD) dietary pattern with the use of 38 food groups. The associations of derived dietary patterns with disease outcomes were then tested with the use of multinomial logistic regression. Results: An ED, HF, and LFD dietary pattern had high positive loadings for fast foods, carbonated drinks, and refined grains, and high negative loadings for whole fruits and vegetables (≥|0.17|). Food groups with a high loading were summed to form a simplified dietary pattern score. Moving from the first (healthiest) to the fourth (least healthy) quartiles of the ED, HF, and LFD pattern and the simplified dietary pattern scores was associated with increasingly elevated ORs for unhealthy obesity, with individuals in quartile 4 having an OR of 2.57 (95% CI: 1.75, 3.76) and 2.73 (95% CI: 1.88, 3.98), respectively ( P -trend obesity ( P -trend dietary patterns with healthy obesity and unhealthy nonobesity were weaker, albeit significant. Conclusions: Consuming an ED, HF, and LFD dietary pattern and lack of adherence to the recommendations of the 2015 DGAI were associated with

The effect of viewing a virtual environment through a head-mounted display on balance.

Science.gov (United States)

Robert, Maxime T; Ballaz, Laurent; Lemay, Martin

2016-07-01

In the next few years, several head-mounted displays (HMD) will be publicly released making virtual reality more accessible. HMD are expected to be widely popular at home for gaming but also in clinical settings, notably for training and rehabilitation. HMD can be used in both seated and standing positions; however, presently, the impact of HMD on balance remains largely unknown. It is therefore crucial to examine the impact of viewing a virtual environment through a HMD on standing balance. To compare static and dynamic balance in a virtual environment perceived through a HMD and the physical environment. The visual representation of the virtual environment was based on filmed image of the physical environment and was therefore highly similar. This is an observational study in healthy adults. No significant difference was observed between the two environments for static balance. However, dynamic balance was more perturbed in the virtual environment when compared to that of the physical environment. HMD should be used with caution because of its detrimental impact on dynamic balance. Sensorimotor conflict possibly explains the impact of HMD on balance. Copyright © 2016 Elsevier B.V. All rights reserved.

Mobile-robot navigation with complete coverage of unstructured environments

OpenAIRE

García Armada, Elena; González de Santos, Pablo

2004-01-01

There are some mobile-robot applications that require the complete coverage of an unstructured environment. Examples are humanitarian de-mining and floor-cleaning tasks. A complete-coverage algorithm is then used, a path-planning technique that allows the robot to pass over all points in the environment, avoiding unknown obstacles. Different coverage algorithms exist, but they fail working in unstructured environments. This paper details a complete-coverage algorithm for unstructured environm...

Interactive local super-resolution reconstruction of whole-body MRI mouse data: A pilot study with applications to bone and kidney metastases

NARCIS (Netherlands)

O.M. Dzyubachyk (Oleh); A. Khmelinskii (Artem); E. Plenge (Esben); P. Kok (Peter); T.J.A. Snoeks (Thomas); D.H.J. Poot; C.W.G.M. Löwik (Clemens); C.P. Botha (Charl); W.J. Niessen (Wiro); L. van der Weerd; E. Meijering (Erik); B.P.F. Lelieveldt (Boudewijn)

2014-01-01

textabstractIn small animal imaging studies, when the locations of the micro-structures of interest are unknown a priori, there is a simultaneous need for full-body coverage and high resolution. In MRI, additional requirements to image contrast and acquisition time will often make it impossible to

Robust adaptive fuzzy neural tracking control for a class of unknown ...

Indian Academy of Sciences (India)

In this paper, an adaptive fuzzy neural controller (AFNC) for a class of unknown chaotic systems is ... The robust controller is used to guarantee the stability and to control the per- ..... From the above analysis we have the following theorem:.

Using 222Rn as a tracer of geophysical processes in underground environments

International Nuclear Information System (INIS)

Lacerda, T.; Anjos, R. M.; Valladares, D. L.; Rizzotto, M.; Velasco, H.; Rosas, J. P. de; Ayub, J. Juri; Silva, A. A. R. da; Yoshimura, E. M.

2014-01-01

Radon levels in two old mines in San Luis, Argentina, are reported and analyzed. These mines are today used for touristic visitation. Our goal was to assess the potential use of such radioactive noble gas as tracer of geological processes in underground environments. CR-39 nuclear track detectors were used during the winter and summer seasons. The findings show that the significant radon concentrations reported in this environment are subject to large seasonal modulations, due to the strong dependence of natural ventilation on the variations of outside temperature. The results also indicate that radon pattern distribution appear as a good method to localize unknown ducts, fissures or secondary tunnels in subterranean environments

Fever of unknown origin

International Nuclear Information System (INIS)

Misaki, Takashi; Matsui, Akira; Tanaka, Fumiko; Okuno, Yoshishige; Mitsumori, Michihide; Torizuka, Tatsurou; Dokoh, Shigeharu; Hayakawa, Katsumi; Shimbo, Shin-ichirou

1990-01-01

Gallium-67 scintigraphy is a commonly performed imaging modality in deteting pyrogenic lesions in cases of long-standing inexplainable fever. To re-evaluate the significance of gallium imaging in such cases, a retrospective review was made of 56 scans performed in febrile patients in whom sufficient clinical and laboratory findings were obtained. Gallium scans were true positive in 30 patients, false positive in 3, true negative in 19, and false negative in 4. In the group of true positive, local inflammatory lesions were detected in 23 patients with a final diagnosis of lung tuberculosis, urinary tract infection, and inflammatory joint disease. Abnormal gallium accumulation, as shown in the other 7 patients, provided clues to the diagnosis of generalized disorders, such as hematological malignancies (n=3), systemic autoimmune diseases (n=3), and severe infectious mononucleosis (n=one). In the group of false positive, gallium imaging revealed intestinal excretion of gallium in 2 patients and physiological pulmonary hilar accumulation in one. In the true negative group of 19 patients, fever of unknown origin was resolved spontaneously in 12 patients, and with antibiotics and corticosteroids in 2 and 5 patients, respectively. Four patients having false negative scans were finally diagnosed as having urinary tract infection (n=2), bacterial meningitis (n=one), and polyarteritis (n=one). Gallium imaging would remain the technique of choice in searching for origin of unknown fever. It may also be useful for early diagnosis of systemic disease, as well as focal inflammation. (N.K.)

HIV-related social intolerance and risky sexual behavior in a high HIV prevalence environment.

Science.gov (United States)

Delavande, Adeline; Sampaio, Mafalda; Sood, Neeraj

2014-06-01

Although most countries state that fighting social intolerance against persons with HIV is part of their national HIV strategy, the impact of reducing intolerance on risky sexual behavior is largely unknown. In this paper, we estimate the effect of social intolerance against HIV+ persons on risky sexual behavior in rural Malawi using data from roughly 2000 respondents from the 2004 and 2006 waves of the Malawi Longitudinal Study of Families and Health (MLSFH). The effect of social intolerance on risky behavior is a priori ambiguous. On the one hand, higher social intolerance or stigma can lead people to disassociate from the stigmatized group and hence promote risky behavior. On the other hand, intolerance can be viewed as a social tax on being HIV+ and thus higher intolerance may reduce risky behavior. We find that a decrease in social intolerance is associated with a decrease in risky behavior, including fewer partners and a lower likelihood of having extra-marital relations. This effect is mainly driven by the impact of social intolerance on men. Overall the results suggests that reducing social intolerance might not only benefit the HIV positive but might also forestall the spread of HIV. Copyright © 2014 Elsevier Ltd. All rights reserved.

Decentralized adaptive control of interconnected nonlinear systems with unknown control directions.

Science.gov (United States)

Huang, Jiangshuai; Wang, Qing-Guo

2018-03-01

In this paper, we propose a decentralized adaptive control scheme for a class of interconnected strict-feedback nonlinear systems without a priori knowledge of subsystems' control directions. To address this problem, a novel Nussbaum-type function is proposed and a key theorem is drawn which involves quantifying the interconnections of multiple Nussbaum-type functions of the subsystems with different control directions in a single inequality. Global stability of the closed-loop system and asymptotic stabilization of subsystems' output are proved and a simulation example is given to illustrate the effectiveness of the proposed control scheme. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Impact of nonlinearity on changing the a priori of trace gas profile estimates from the Tropospheric Emission Spectrometer (TES

Directory of Open Access Journals (Sweden)

S. S. Kulawik

2008-06-01

Full Text Available Non-linear maximum a posteriori (MAP estimates of atmospheric profiles from the Tropospheric Emission Spectrometer (TES contains a priori information that may vary geographically, which is a confounding factor in the analysis and physical interpretation of an ensemble of profiles. One mitigation strategy is to transform profile estimates to a common prior using a linear operation thereby facilitating the interpretation of profile variability. However, this operation is dependent on the assumption of not worse than moderate non-linearity near the solution of the non-linear estimate. The robustness of this assumption is tested by comparing atmospheric retrievals from the Tropospheric Emission Spectrometer processed with a uniform prior with those processed with a variable prior and converted to a uniform prior following the non-linear retrieval. Linearly converting the prior following a non-linear retrieval is shown to have a minor effect on the results as compared to a non-linear retrieval using a uniform prior when compared to the expected total error, with less than 10% of the change in the prior ending up as unbiased fluctuations in the profile estimate results.

N-grams Based Supervised Machine Learning Model for Mobile Agent Platform Protection against Unknown Malicious Mobile Agents

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Pallavi Bagga

2017-12-01

Full Text Available From many past years, the detection of unknown malicious mobile agents before they invade the Mobile Agent Platform has been the subject of much challenging activity. The ever-growing threat of malicious agents calls for techniques for automated malicious agent detection. In this context, the machine learning (ML methods are acknowledged more effective than the Signature-based and Behavior-based detection methods. Therefore, in this paper, the prime contribution has been made to detect the unknown malicious mobile agents based on n-gram features and supervised ML approach, which has not been done so far in the sphere of the Mobile Agents System (MAS security. To carry out the study, the n-grams ranging from 3 to 9 are extracted from a dataset containing 40 malicious and 40 non-malicious mobile agents. Subsequently, the classification is performed using different classifiers. A nested 5-fold cross validation scheme is employed in order to avoid the biasing in the selection of optimal parameters of classifier. The observations of extensive experiments demonstrate that the work done in this paper is suitable for the task of unknown malicious mobile agent detection in a Mobile Agent Environment, and also adds the ML in the interest list of researchers dealing with MAS security.

Lost in space: Onboard star identification using CCD star tracker data without an a priori attitude

Science.gov (United States)

Ketchum, Eleanor A.; Tolson, Robert H.

1993-01-01

There are many algorithms in use today which determine spacecraft attitude by identifying stars in the field of view of a star tracker. Some methods, which date from the early 1960's, compare the angular separation between observed stars with a small catalog. In the last 10 years, several methods have been developed which speed up the process and reduce the amount of memory needed, a key element to onboard attitude determination. However, each of these methods require some a priori knowledge of the spacecraft attitude. Although the Sun and magnetic field generally provide the necessary coarse attitude information, there are occasions when a spacecraft could get lost when it is not prudent to wait for sunlight. Also, the possibility of efficient attitude determination using only the highly accurate CCD star tracker could lead to fully autonomous spacecraft attitude determination. The need for redundant coarse sensors could thus be eliminated at substantial cost reduction. Some groups have extended their algorithms to implement a computation intense full sky scan. Some require large data bases. Both storage and speed are concerns for autonomous onboard systems. Neural network technology is even being explored by some as a possible solution, but because of the limited number of patterns that can be stored and large overhead, nothing concrete has resulted from these efforts. This paper presents an algorithm which, by descretizing the sky and filtering by visual magnitude of the brightness observed star, speeds up the lost in space star identification process while reducing the amount of necessary onboard computer storage compared to existing techniques.

Quantum jointly assisted cloning of an unknown three-dimensional equatorial state

Science.gov (United States)

Ma, Peng-Cheng; Chen, Gui-Bin; Li, Xiao-Wei; Zhan, You-Bang

2018-02-01

We present two schemes for perfectly cloning an unknown single-qutrit equatorial state with assistance from two and N state preparers, respectively. In the first scheme, the sender wishes to teleport an unknown single-qutrit equatorial state from two state preparers to a remote receiver, and then to create a perfect copy of the unknown state at her location. The scheme consists of two stages. The first stage of the scheme requires the usual teleportation. In the second stage, to help the sender realize the quantum cloning, two state preparers perform single-qutrit projective measurements on their own qutrits from the sender, then the sender can acquire a perfect copy of the unknown state. It is shown that, only if the two state preparers collaborate with each other, the sender can create a copy of the unknown state by means of some appropriate unitary operations. In the second scheme, we generalized the jointly assisted cloning in the first scheme to the case of N state prepares. In the present schemes, the total probability of success for assisted cloning of a perfect copy of the unknown state can reach 1.

A Numerical Approach to Solving an Inverse Heat Conduction Problem Using the Levenberg-Marquardt Algorithm

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Tao Min

2014-01-01

Full Text Available This paper is intended to provide a numerical algorithm involving the combined use of the Levenberg-Marquardt algorithm and the Galerkin finite element method for estimating the diffusion coefficient in an inverse heat conduction problem (IHCP. In the present study, the functional form of the diffusion coefficient is unknown a priori. The unknown diffusion coefficient is approximated by the polynomial form and the present numerical algorithm is employed to find the solution. Numerical experiments are presented to show the efficiency of the proposed method.

Building a RAPPOR with the Unknown: Privacy-Preserving Learning of Associations and Data Dictionaries

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Fanti Giulia

2016-07-01

Full Text Available Techniques based on randomized response enable the collection of potentially sensitive data from clients in a privacy-preserving manner with strong local differential privacy guarantees. A recent such technology, RAPPOR [12], enables estimation of the marginal frequencies of a set of strings via privacy-preserving crowdsourcing. However, this original estimation process relies on a known dictionary of possible strings; in practice, this dictionary can be extremely large and/or unknown. In this paper, we propose a novel decoding algorithm for the RAPPOR mechanism that enables the estimation of “unknown unknowns,” i.e., strings we do not know we should be estimating. To enable learning without explicit dictionary knowledge, we develop methodology for estimating the joint distribution of multiple variables collected with RAPPOR. Our contributions are not RAPPOR-specific, and can be generalized to other local differential privacy mechanisms for learning distributions of string-valued random variables.

Interactive local super-resolution reconstruction of whole-body MRI mouse data : A pilot study with applications to bone and kidney metastases

NARCIS (Netherlands)

Dzyubachyk, O.; Khmelinskii, A.; Plenge, E.; Kok, P.; Snoeks, T.J.; Poot, D.H.; Löwik, C.W.; Botha, C.P.; Niessen, W.J.; Van der Weerd, L.; Meijering, E.; Lelieveldt, B.P.F.

2014-01-01

In small animal imaging studies, when the locations of the micro-structures of interest are unknown a priori, there is a simultaneous need for full-body coverage and high resolution. In MRI, additional requirements to image contrast and acquisition time will often make it impossible to acquire such

Adaptability and phenotypic stability of common bean genotypes through Bayesian inference.

Science.gov (United States)

Corrêa, A M; Teodoro, P E; Gonçalves, M C; Barroso, L M A; Nascimento, M; Santos, A; Torres, F E

2016-04-27

This study used Bayesian inference to investigate the genotype x environment interaction in common bean grown in Mato Grosso do Sul State, and it also evaluated the efficiency of using informative and minimally informative a priori distributions. Six trials were conducted in randomized blocks, and the grain yield of 13 common bean genotypes was assessed. To represent the minimally informative a priori distributions, a probability distribution with high variance was used, and a meta-analysis concept was adopted to represent the informative a priori distributions. Bayes factors were used to conduct comparisons between the a priori distributions. The Bayesian inference was effective for the selection of upright common bean genotypes with high adaptability and phenotypic stability using the Eberhart and Russell method. Bayes factors indicated that the use of informative a priori distributions provided more accurate results than minimally informative a priori distributions. According to Bayesian inference, the EMGOPA-201, BAMBUÍ, CNF 4999, CNF 4129 A 54, and CNFv 8025 genotypes had specific adaptability to favorable environments, while the IAPAR 14 and IAC CARIOCA ETE genotypes had specific adaptability to unfavorable environments.

A Mobile Sensor Network System for Monitoring of Unfriendly Environments.

Science.gov (United States)

Song, Guangming; Zhou, Yaoxin; Ding, Fei; Song, Aiguo

2008-11-14

Observing microclimate changes is one of the most popular applications of wireless sensor networks. However, some target environments are often too dangerous or inaccessible to humans or large robots and there are many challenges for deploying and maintaining wireless sensor networks in those unfriendly environments. This paper presents a mobile sensor network system for solving this problem. The system architecture, the mobile node design, the basic behaviors and advanced network capabilities have been investigated respectively. A wheel-based robotic node architecture is proposed here that can add controlled mobility to wireless sensor networks. A testbed including some prototype nodes has also been created for validating the basic functions of the proposed mobile sensor network system. Motion performance tests have been done to get the positioning errors and power consumption model of the mobile nodes. Results of the autonomous deployment experiment show that the mobile nodes can be distributed evenly into the previously unknown environments. It provides powerful support for network deployment and maintenance and can ensure that the sensor network will work properly in unfriendly environments.

Phillips-Tikhonov regularization with a priori information for neutron emission tomographic reconstruction on Joint European Torus

Energy Technology Data Exchange (ETDEWEB)

Bielecki, J.; Scholz, M.; Drozdowicz, K. [Institute of Nuclear Physics, Polish Academy of Sciences, PL-31342 Krakow (Poland); Giacomelli, L. [CCFE, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); Istituto di Fisica del Plasma “P. Caldirola,” Milano (Italy); Kiptily, V.; Kempenaars, M. [CCFE, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); Conroy, S. [CCFE, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); Department of Physics and Astronomy, Uppsala University (Sweden); Craciunescu, T. [IAP, National Institute for Laser Plasma and Radiation Physics, Bucharest (Romania); Collaboration: EUROfusion Consortium, JET, Culham Science Centre, Abingdon OX14 3DB (United Kingdom)

2015-09-15

A method of tomographic reconstruction of the neutron emissivity in the poloidal cross section of the Joint European Torus (JET, Culham, UK) tokamak was developed. Due to very limited data set (two projection angles, 19 lines of sight only) provided by the neutron emission profile monitor (KN3 neutron camera), the reconstruction is an ill-posed inverse problem. The aim of this work consists in making a contribution to the development of reliable plasma tomography reconstruction methods that could be routinely used at JET tokamak. The proposed method is based on Phillips-Tikhonov regularization and incorporates a priori knowledge of the shape of normalized neutron emissivity profile. For the purpose of the optimal selection of the regularization parameters, the shape of normalized neutron emissivity profile is approximated by the shape of normalized electron density profile measured by LIDAR or high resolution Thomson scattering JET diagnostics. In contrast with some previously developed methods of ill-posed plasma tomography reconstruction problem, the developed algorithms do not include any post-processing of the obtained solution and the physical constrains on the solution are imposed during the regularization process. The accuracy of the method is at first evaluated by several tests with synthetic data based on various plasma neutron emissivity models (phantoms). Then, the method is applied to the neutron emissivity reconstruction for JET D plasma discharge #85100. It is demonstrated that this method shows good performance and reliability and it can be routinely used for plasma neutron emissivity reconstruction on JET.

Membranoproliferative glomerulonephritis in a carcinoma with unknown primary: An autopsy study

Directory of Open Access Journals (Sweden)

Gupta Kirti

2008-04-01

Full Text Available Kidney disease frequently complicates malignancy and its treatment. Although many solid and hematologic cancers may involve the renal parenchyma, clinical sequelae are usually not prominent. Published reports cite membranous nephropathy as the most common malignancy-associated glomerulopathy, occurring with many carcinomas and occasionally with leukemia and lymphoma followed by minimal change disease. Rarely membranoproliferative glomerulonephritis (MPGN has been reported in patients with malignancy. The mechanism by which malignancy induces disease remains unproved, but may involve deposition of tumor antigen in the subepithelial space with in situ immune complex formation and subsequent complement activation. Treatment of the underlying malignancy may lead to resolution of nephrotic syndrome, lending indirect support to this theory. We report a rare autopsy case of a patient with metastatic carcinoma (with unknown primary associated with MPGN. The association between MPGN and metastatic carcinoma with unknown primary is uncommon and has not been previously reported in the literature.

Characterizing unknown systematics in large scale structure surveys

International Nuclear Information System (INIS)

Agarwal, Nishant; Ho, Shirley; Myers, Adam D.; Seo, Hee-Jong; Ross, Ashley J.; Bahcall, Neta; Brinkmann, Jonathan; Eisenstein, Daniel J.; Muna, Demitri; Palanque-Delabrouille, Nathalie; Yèche, Christophe; Pâris, Isabelle; Petitjean, Patrick; Schneider, Donald P.; Streblyanska, Alina; Weaver, Benjamin A.

2014-01-01

Photometric large scale structure (LSS) surveys probe the largest volumes in the Universe, but are inevitably limited by systematic uncertainties. Imperfect photometric calibration leads to biases in our measurements of the density fields of LSS tracers such as galaxies and quasars, and as a result in cosmological parameter estimation. Earlier studies have proposed using cross-correlations between different redshift slices or cross-correlations between different surveys to reduce the effects of such systematics. In this paper we develop a method to characterize unknown systematics. We demonstrate that while we do not have sufficient information to correct for unknown systematics in the data, we can obtain an estimate of their magnitude. We define a parameter to estimate contamination from unknown systematics using cross-correlations between different redshift slices and propose discarding bins in the angular power spectrum that lie outside a certain contamination tolerance level. We show that this method improves estimates of the bias using simulated data and further apply it to photometric luminous red galaxies in the Sloan Digital Sky Survey as a case study

Characterizing unknown systematics in large scale structure surveys

Energy Technology Data Exchange (ETDEWEB)

Agarwal, Nishant; Ho, Shirley [McWilliams Center for Cosmology, Department of Physics, Carnegie Mellon University, Pittsburgh, PA 15213 (United States); Myers, Adam D. [Department of Physics and Astronomy, University of Wyoming, Laramie, WY 82071 (United States); Seo, Hee-Jong [Berkeley Center for Cosmological Physics, LBL and Department of Physics, University of California, Berkeley, CA 94720 (United States); Ross, Ashley J. [Institute of Cosmology and Gravitation, University of Portsmouth, Portsmouth, PO1 3FX (United Kingdom); Bahcall, Neta [Princeton University Observatory, Peyton Hall, Princeton, NJ 08544 (United States); Brinkmann, Jonathan [Apache Point Observatory, P.O. Box 59, Sunspot, NM 88349 (United States); Eisenstein, Daniel J. [Harvard-Smithsonian Center for Astrophysics, 60 Garden St., Cambridge, MA 02138 (United States); Muna, Demitri [Department of Astronomy, Ohio State University, Columbus, OH 43210 (United States); Palanque-Delabrouille, Nathalie; Yèche, Christophe [CEA, Centre de Saclay, Irfu/SPP, F-91191 Gif-sur-Yvette (France); Pâris, Isabelle [Departamento de Astronomía, Universidad de Chile, Casilla 36-D, Santiago (Chile); Petitjean, Patrick [Université Paris 6 et CNRS, Institut d' Astrophysique de Paris, 98bis blvd. Arago, 75014 Paris (France); Schneider, Donald P. [Department of Astronomy and Astrophysics, Pennsylvania State University, University Park, PA 16802 (United States); Streblyanska, Alina [Instituto de Astrofisica de Canarias (IAC), E-38200 La Laguna, Tenerife (Spain); Weaver, Benjamin A., E-mail: nishanta@andrew.cmu.edu [Center for Cosmology and Particle Physics, New York University, New York, NY 10003 (United States)

2014-04-01

Photometric large scale structure (LSS) surveys probe the largest volumes in the Universe, but are inevitably limited by systematic uncertainties. Imperfect photometric calibration leads to biases in our measurements of the density fields of LSS tracers such as galaxies and quasars, and as a result in cosmological parameter estimation. Earlier studies have proposed using cross-correlations between different redshift slices or cross-correlations between different surveys to reduce the effects of such systematics. In this paper we develop a method to characterize unknown systematics. We demonstrate that while we do not have sufficient information to correct for unknown systematics in the data, we can obtain an estimate of their magnitude. We define a parameter to estimate contamination from unknown systematics using cross-correlations between different redshift slices and propose discarding bins in the angular power spectrum that lie outside a certain contamination tolerance level. We show that this method improves estimates of the bias using simulated data and further apply it to photometric luminous red galaxies in the Sloan Digital Sky Survey as a case study.

Randomized clinical trials in orthodontics are rarely registered a priori and often published late or not at all.

Science.gov (United States)

Papageorgiou, Spyridon N; Antonoglou, Georgios N; Sándor, George K; Eliades, Theodore

2017-01-01

A priori registration of randomized clinical trials is crucial to the transparency and credibility of their findings. Aim of this study was to assess the frequency with which registered and completed randomized trials in orthodontics are published. We searched ClinicalTrials.gov and ISRCTN for registered randomized clinical trials in orthodontics that had been completed up to January 2017 and judged the publication status and date of registered trials using a systematic protocol. Statistical analysis included descriptive statistics, chi-square or Fisher exact tests, and Kaplan-Meier survival estimates. From the 266 orthodontic trials registered up to January 2017, 80 trials had been completed and included in the present study. Among these 80 included trials, the majority (76%) were registered retrospectively, while only 33 (41%) were published at the time. The median time from completion to publication was 20.1 months (interquartile range: 9.1 to 31.6 months), while survival analysis indicated that less than 10% of the trials were published after 5 years from their completion. Finally, 22 (28%) of completed trials remain unpublished even after 5 years from their completion. Publication rates of registered randomized trials in orthodontics remained low, even 5 years after their completion date.

Robust adaptive fuzzy neural tracking control for a class of unknown ...

Indian Academy of Sciences (India)

In this paper, an adaptive fuzzy neural controller (AFNC) for a class of unknown chaotic systems is proposed. The proposed AFNC is comprised of a fuzzy neural controller and a robust controller. The fuzzy neural controller including a fuzzy neural network identifier (FNNI) is the principal controller. The FNNI is used for ...

Enhancing the performance of model-based elastography by incorporating additional a priori information in the modulus image reconstruction process

International Nuclear Information System (INIS)

Doyley, Marvin M; Srinivasan, Seshadri; Dimidenko, Eugene; Soni, Nirmal; Ophir, Jonathan

2006-01-01

Model-based elastography is fraught with problems owing to the ill-posed nature of the inverse elasticity problem. To overcome this limitation, we have recently developed a novel inversion scheme that incorporates a priori information concerning the mechanical properties of the underlying tissue structures, and the variance incurred during displacement estimation in the modulus image reconstruction process. The information was procured by employing standard strain imaging methodology, and introduced in the reconstruction process through the generalized Tikhonov approach. In this paper, we report the results of experiments conducted on gelatin phantoms to evaluate the performance of modulus elastograms computed with the generalized Tikhonov (GTK) estimation criterion relative to those computed by employing the un-weighted least-squares estimation criterion, the weighted least-squares estimation criterion and the standard Tikhonov method (i.e., the generalized Tikhonov method with no modulus prior). The results indicate that modulus elastograms computed with the generalized Tikhonov approach had superior elastographic contrast discrimination and contrast recovery. In addition, image reconstruction was more resilient to structural decorrelation noise when additional constraints were imposed on the reconstruction process through the GTK method

Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer

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T. Youssef

2013-01-01

Full Text Available This paper presents an unknown input Proportional Multiple-Integral Observer (PIO for synchronization of chaotic systems based on Takagi-Sugeno (TS fuzzy chaotic models subject to unmeasurable decision variables and unknown input. In a secure communication configuration, this unknown input is regarded as a message encoded in the chaotic system and recovered by the proposed PIO. Both states and outputs of the fuzzy chaotic models are subject to polynomial unknown input with kth derivative zero. Using Lyapunov stability theory, sufficient design conditions for synchronization are proposed. The PIO gains matrices are obtained by resolving linear matrix inequalities (LMIs constraints. Simulation results show through two TS fuzzy chaotic models the validity of the proposed method.

FRAMEWORK FOR AD HOC NETWORK COMMUNICATION IN MULTI-ROBOT SYSTEMS

Directory of Open Access Journals (Sweden)

Khilda Slyusar

2016-11-01

Full Text Available Assume a team of mobile robots operating in environments where no communication infrastructure like routers or access points is available. The robots have to create a mobile ad hoc network, in that case, it provides communication on peer-to-peer basis. The paper gives an overview of existing solutions how to route messages in such ad hoc networks between robots that are not directly connected and introduces a design of a software framework for realization of such communication. Feasibility of the proposed framework is shown on the example of distributed multi-robot exploration of an a priori unknown environment. Testing of developed functionality in an exploration scenario is based on results of several experiments with various input conditions of the exploration process and various sizes of a team and is described herein.

An algorithm for finding biologically significant features in microarray data based on a priori manifold learning.

Directory of Open Access Journals (Sweden)

Zena M Hira

Full Text Available Microarray databases are a large source of genetic data, which, upon proper analysis, could enhance our understanding of biology and medicine. Many microarray experiments have been designed to investigate the genetic mechanisms of cancer, and analytical approaches have been applied in order to classify different types of cancer or distinguish between cancerous and non-cancerous tissue. However, microarrays are high-dimensional datasets with high levels of noise and this causes problems when using machine learning methods. A popular approach to this problem is to search for a set of features that will simplify the structure and to some degree remove the noise from the data. The most widely used approach to feature extraction is principal component analysis (PCA which assumes a multivariate Gaussian model of the data. More recently, non-linear methods have been investigated. Among these, manifold learning algorithms, for example Isomap, aim to project the data from a higher dimensional space onto a lower dimension one. We have proposed a priori manifold learning for finding a manifold in which a representative set of microarray data is fused with relevant data taken from the KEGG pathway database. Once the manifold has been constructed the raw microarray data is projected onto it and clustering and classification can take place. In contrast to earlier fusion based methods, the prior knowledge from the KEGG databases is not used in, and does not bias the classification process--it merely acts as an aid to find the best space in which to search the data. In our experiments we have found that using our new manifold method gives better classification results than using either PCA or conventional Isomap.

Using {sup 222}Rn as a tracer of geophysical processes in underground environments

Energy Technology Data Exchange (ETDEWEB)

Lacerda, T.; Anjos, R. M. [LARA - Laboratório de Radioecologia e Alterações Ambientais, Instituto de Física, Universidade Federal Fluminense, Av. Gal Milton Tavares de Souza, s/no, Gragoatá, 24210-346, Niterói, RJ (Brazil); Valladares, D. L.; Rizzotto, M.; Velasco, H.; Rosas, J. P. de; Ayub, J. Juri [GEA - Instituto de Matemática Aplicada San Luis (IMASL), Universidad Nacional de San Luis, CCT-San Luis CONICET, Ej. de los Andes 950, D5700HHW San Luis (Argentina); Silva, A. A. R. da; Yoshimura, E. M. [Instituto de Física, Universidade de São Paulo, P.O. Box 66318, 05314-970, São Paulo, SP (Brazil)

2014-11-11

Radon levels in two old mines in San Luis, Argentina, are reported and analyzed. These mines are today used for touristic visitation. Our goal was to assess the potential use of such radioactive noble gas as tracer of geological processes in underground environments. CR-39 nuclear track detectors were used during the winter and summer seasons. The findings show that the significant radon concentrations reported in this environment are subject to large seasonal modulations, due to the strong dependence of natural ventilation on the variations of outside temperature. The results also indicate that radon pattern distribution appear as a good method to localize unknown ducts, fissures or secondary tunnels in subterranean environments.

Robust Fault Detection for Switched Fuzzy Systems With Unknown Input.

Science.gov (United States)

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.

Detection of viral sequence fragments of HIV-1 subfamilies yet unknown

Directory of Open Access Journals (Sweden)

Stanke Mario

2011-04-01

Full Text Available Abstract Background Methods of determining whether or not any particular HIV-1 sequence stems - completely or in part - from some unknown HIV-1 subtype are important for the design of vaccines and molecular detection systems, as well as for epidemiological monitoring. Nevertheless, a single algorithm only, the Branching Index (BI, has been developed for this task so far. Moving along the genome of a query sequence in a sliding window, the BI computes a ratio quantifying how closely the query sequence clusters with a subtype clade. In its current version, however, the BI does not provide predicted boundaries of unknown fragments. Results We have developed Unknown Subtype Finder (USF, an algorithm based on a probabilistic model, which automatically determines which parts of an input sequence originate from a subtype yet unknown. The underlying model is based on a simple profile hidden Markov model (pHMM for each known subtype and an additional pHMM for an unknown subtype. The emission probabilities of the latter are estimated using the emission frequencies of the known subtypes by means of a (position-wise probabilistic model for the emergence of new subtypes. We have applied USF to SIV and HIV-1 sequences formerly classified as having emerged from an unknown subtype. Moreover, we have evaluated its performance on artificial HIV-1 recombinants and non-recombinant HIV-1 sequences. The results have been compared with the corresponding results of the BI. Conclusions Our results demonstrate that USF is suitable for detecting segments in HIV-1 sequences stemming from yet unknown subtypes. Comparing USF with the BI shows that our algorithm performs as good as the BI or better.

[Badminton--unknown sport].

Science.gov (United States)

Zekan-Petrinović, Lidija

2007-01-01

For a long time, badminton was considered to be only a slow and light game for children, a game that is played outdoors and is structurally undemanding.Today, it is not an unknown and unrecognised sport, especially after it was included into the Olympics Games in 1992. Badminton is one of the oldest sports in the world. It is suitable for all ages (for children and elderly equally), women and men and even handicapped persons. Beginners can start playing badminton matches early because the basics are learned quickly. As a recreational activity, badminton is very popular in Zagreb. In the last 10 years, a number of halls specialized for badminton or offering badminton as one of available sports activities have been opened in Zagreb. At present, there are over 70 professional playgrounds for training of top contestants but also for the citizens who can play recreational badminton.

Multi-Robot, Multi-Target Particle Swarm Optimization Search in Noisy Wireless Environments

Energy Technology Data Exchange (ETDEWEB)

Kurt Derr; Milos Manic

2009-05-01

Multiple small robots (swarms) can work together using Particle Swarm Optimization (PSO) to perform tasks that are difficult or impossible for a single robot to accomplish. The problem considered in this paper is exploration of an unknown environment with the goal of finding a target(s) at an unknown location(s) using multiple small mobile robots. This work demonstrates the use of a distributed PSO algorithm with a novel adaptive RSS weighting factor to guide robots for locating target(s) in high risk environments. The approach was developed and analyzed on multiple robot single and multiple target search. The approach was further enhanced by the multi-robot-multi-target search in noisy environments. The experimental results demonstrated how the availability of radio frequency signal can significantly affect robot search time to reach a target.

Adaptive control of Parkinson's state based on a nonlinear computational model with unknown parameters.

Science.gov (United States)

Su, Fei; Wang, Jiang; Deng, Bin; Wei, Xi-Le; Chen, Ying-Yuan; Liu, Chen; Li, Hui-Yan

2015-02-01

The objective here is to explore the use of adaptive input-output feedback linearization method to achieve an improved deep brain stimulation (DBS) algorithm for closed-loop control of Parkinson's state. The control law is based on a highly nonlinear computational model of Parkinson's disease (PD) with unknown parameters. The restoration of thalamic relay reliability is formulated as the desired outcome of the adaptive control methodology, and the DBS waveform is the control input. The control input is adjusted in real time according to estimates of unknown parameters as well as the feedback signal. Simulation results show that the proposed adaptive control algorithm succeeds in restoring the relay reliability of the thalamus, and at the same time achieves accurate estimation of unknown parameters. Our findings point to the potential value of adaptive control approach that could be used to regulate DBS waveform in more effective treatment of PD.

Bayesian source term determination with unknown covariance of measurements

Science.gov (United States)

Belal, Alkomiet; Tichý, Ondřej; Šmídl, Václav

2017-04-01

Determination of a source term of release of a hazardous material into the atmosphere is a very important task for emergency response. We are concerned with the problem of estimation of the source term in the conventional linear inverse problem, y = Mx, where the relationship between the vector of observations y is described using the source-receptor-sensitivity (SRS) matrix M and the unknown source term x. Since the system is typically ill-conditioned, the problem is recast as an optimization problem minR,B(y - Mx)TR-1(y - Mx) + xTB-1x. The first term minimizes the error of the measurements with covariance matrix R, and the second term is a regularization of the source term. There are different types of regularization arising for different choices of matrices R and B, for example, Tikhonov regularization assumes covariance matrix B as the identity matrix multiplied by scalar parameter. In this contribution, we adopt a Bayesian approach to make inference on the unknown source term x as well as unknown R and B. We assume prior on x to be a Gaussian with zero mean and unknown diagonal covariance matrix B. The covariance matrix of the likelihood R is also unknown. We consider two potential choices of the structure of the matrix R. First is the diagonal matrix and the second is a locally correlated structure using information on topology of the measuring network. Since the inference of the model is intractable, iterative variational Bayes algorithm is used for simultaneous estimation of all model parameters. The practical usefulness of our contribution is demonstrated on an application of the resulting algorithm to real data from the European Tracer Experiment (ETEX). This research is supported by EEA/Norwegian Financial Mechanism under project MSMT-28477/2014 Source-Term Determination of Radionuclide Releases by Inverse Atmospheric Dispersion Modelling (STRADI).

Celiac Disease Presenting as Fever of Unknown Origin

Directory of Open Access Journals (Sweden)

Megan J. Cooney

2013-01-01

Full Text Available Celiac disease (CD is a common autoimmune enteropathy that occurs, in affected individuals, with exposure to gluten in the diet and improves with removal of dietary gluten. Although CD is readily considered in patients with classical presentations of the disease, atypical manifestations may be the only presenting symptoms. We present a case of CD in a 16-year-old female presenting as fever of unknown origin, which has not been reported previously. The postulated mechanism for fever in CD and the importance of clinicians having a low threshold for considering CD in the differential diagnosis of fever of unknown origin and other enigmatic clinical presentations is discussed.

Multifocal, chronic osteomyelitis of unknown etiology

International Nuclear Information System (INIS)

Kozlowski, K.; Beluffi, G.; Feltham, C.; James, M.; Nespoli, L.; Tamaela, L.; Pavia Univ.; Municipal Hospital, Nelson; Medical School, Jakarta

1985-01-01

Four cases of multifocal osteomyelitis of unknown origin in childhood are reported. The variable clinical and radiographic appearances of the disease are illustrated and the diagnostic difficulties in the early stages of the disease are stressed. (orig.) [de

A priori assumptions about characters as a cause of incongruence between molecular and morphological hypotheses of primate interrelationships.

Science.gov (United States)

Tornow, Matthew A; Skelton, Randall R

2012-01-01

When molecules and morphology produce incongruent hypotheses of primate interrelationships, the data are typically viewed as incompatible, and molecular hypotheses are often considered to be better indicators of phylogenetic history. However, it has been demonstrated that the choice of which taxa to include in cladistic analysis as well as assumptions about character weighting, character state transformation order, and outgroup choice all influence hypotheses of relationships and may positively influence tree topology, so that relationships between extant taxa are consistent with those found using molecular data. Thus, the source of incongruence between morphological and molecular trees may lie not in the morphological data themselves but in assumptions surrounding the ways characters evolve and their impact on cladistic analysis. In this study, we investigate the role that assumptions about character polarity and transformation order play in creating incongruence between primate phylogenies based on morphological data and those supported by multiple lines of molecular data. By releasing constraints imposed on published morphological analyses of primates from disparate clades and subjecting those data to parsimony analysis, we test the hypothesis that incongruence between morphology and molecules results from inherent flaws in morphological data. To quantify the difference between incongruent trees, we introduce a new method called branch slide distance (BSD). BSD mitigates many of the limitations attributed to other tree comparison methods, thus allowing for a more accurate measure of topological similarity. We find that releasing a priori constraints on character behavior often produces trees that are consistent with molecular trees. Case studies are presented that illustrate how congruence between molecules and unconstrained morphological data may provide insight into issues of polarity, transformation order, homology, and homoplasy.

Quantum key distribution with an unknown and untrusted source

Science.gov (United States)

Zhao, Yi; Qi, Bing; Lo, Hoi-Kwong

2009-03-01

The security of a standard bi-directional ``plug & play'' quantum key distribution (QKD) system has been an open question for a long time. This is mainly because its source is equivalently controlled by an eavesdropper, which means the source is unknown and untrusted. Qualitative discussion on this subject has been made previously. In this paper, we present the first quantitative security analysis on a general class of QKD protocols whose sources are unknown and untrusted. The securities of standard BB84 protocol, weak+vacuum decoy state protocol, and one-decoy decoy state protocol, with unknown and untrusted sources are rigorously proved. We derive rigorous lower bounds to the secure key generation rates of the above three protocols. Our numerical simulation results show that QKD with an untrusted source gives a key generation rate that is close to that with a trusted source. Our work is published in [1]. [4pt] [1] Y. Zhao, B. Qi, and H.-K. Lo, Phys. Rev. A, 77:052327 (2008).

Séparation des ondes P et S à l'aide de la matrice spectrale avec informations à priori The Separation of P and S Waves Using the Spectral Matrix with a Priori Information

Directory of Open Access Journals (Sweden)

Mari J. L.

2006-11-01

Full Text Available Classiquement, la technique de filtrage utilisant la matrice spectrale proposée par Mermoz ne permet une séparation automatique des ondes au sens des indicatrices sismiques que dans certains cas particuliers, à savoir lorsque les ondes à séparer sont naturellement alignées sur les vecteurs propres de la matrice spectrale. Dans les autres cas, nous montrons que l'introduction d'information a priori sur la vitesse apparente de quelques ondes et une limitation de la durée temporelle de ces dernières permettent d'estimer leurs vecteurs d'ondes. L'utilisation de ces vecteurs et une technique de projection au sens des moindres carrés conduit à une extraction optimale de ces ondes, sans dégrader les autres ondes. La technique de filtrage proposée a été appliquée sur des données sismiques de type PSV (profil sismique vertical déporté. Le PSV a été enregistré dans un puits entre les cotes 1050 m et 1755 m; la source est déportée de 654 m par rapport à la tête de puits. L'outil utilisé est un géophone de puits à trois composantes. Le puits traverse une structure géologique complexe. Le traitement réalisé a mis en évidence des réflexions sismiques d'ondes de compression et de cisaillement, associées à des marqueurs fortement pentés (10 à 25°. Après estimation des champs de vitesse et des pendages à l'aide d'abaques, la migration en profondeur des horizons temps pointés a permis d'obtenir un modèle structural faillé. Detailed structural analysis can be achieved by using 3-component vertical seismic profiling method which gives structural information at several hundred meters from the wellhead. The use of an offset VSP on the Auzance structure has led to obtain a structural model composed by faulted dipping reflectors. This is due to the robust nature of the wave separation method which is based on the spectral matrix and uses an a priori information. This method preserves the true amplitude and the local apparent

Mapping of unknown industrial plant using ROS-based navigation mobile robot

Science.gov (United States)

Priyandoko, G.; Ming, T. Y.; Achmad, M. S. H.

2017-10-01

This research examines how humans work with teleoperated unmanned mobile robot inspection in industrial plant area resulting 2D/3D map for further critical evaluation. This experiment focuses on two parts, the way human-robot doing remote interactions using robust method and the way robot perceives the environment surround as a 2D/3D perspective map. ROS (robot operating system) as a tool was utilized in the development and implementation during the research which comes up with robust data communication method in the form of messages and topics. RGBD SLAM performs the visual mapping function to construct 2D/3D map using Kinect sensor. The results showed that the mobile robot-based teleoperated system are successful to extend human perspective in term of remote surveillance in large area of industrial plant. It was concluded that the proposed work is robust solution for large mapping within an unknown construction building.

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

Science.gov (United States)

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.

Hyperfamiliarity for unknown faces after left lateral temporo-occipital venous infarction: a double dissociation with prosopagnosia.

Science.gov (United States)

Vuilleumier, Patrik; Mohr, Christine; Valenza, Nathalie; Wetzel, Corinne; Landis, Theodor

2003-04-01

Right hemisphere dominance in face processing is well established and unilateral right inferior temporo-occipital damage can result in prosopagnosia. Here, we describe a 21-year-old right-handed woman with acute impairment in face recognition that selectively concerned unfamiliar faces, following a focal left lateral temporo-occipital venous infarct. She was severely impaired in discerning that unknown people seen in everyday life were unfamiliar, although she had no difficulty recognizing familiar people. Thus, she had no prosopagnosia, but abnormal 'hyperfamiliarity' for unknown faces. Her difficulty was not accompanied by delusions or deficits in discrimination, identification or memory for faces. Standard neuropsychological testing showed that her recognition of familiar faces was entirely normal. By contrast, her sense of personally knowing faces was severely impaired when unknown faces evoked weak signals of familiarity based on spurious cues, to the extent that she would misattribute fame to faces that were unknown but to which she had been incidentally exposed on a prior occasion. Priming experiments also revealed that, unlike normal subjects, she made familiarity judgements without accessing semantic identity representations. Moreover, in face recognition tests, she generally showed bias in that she relied more on right-hemisphere strategies to identify global traits and less on left-hemisphere processes compared with healthy subjects. This case provides novel evidence for a differential contribution of the two hemispheres to face recognition. Hyperfamiliarity for unknown faces might arise from an imbalance between reciprocal hemispheric functions in face recognition, with relative hypoactivation of left hemisphere processes but hyperactivation of right-hemisphere processes for retrieving stored associations about people, linking seen faces to representations of affective and personal relevance. Hence, abnormal bias in attributing some personal meaning to

Vaginal symptoms of unknown etiology - a study in dutch general-practice

NARCIS (Netherlands)

Dekker, Janny H.; Boeke, A. Joan P.; Janssens, J; van Eijk, J.Th.M.

Vaginal symptoms are frequently presented by women to general practitioners. In many cases, the aetiology of these symptoms remains unknown. This study focused on the factors associated with microbiologically unexplained vaginal symptoms, the course of symptoms and signs in these cases, and factors

Using 222Rn as a tracer of geodynamical processes in underground environments

International Nuclear Information System (INIS)

Valladares, D.L.; Silva, A.A.R. da; o, Gragoatá, 24210-340, Niterói, RJ (Brazil))" data-affiliation=" (Instituto de Física, Universidade Federal Fluminense, Av. Gal Milton Tavares de Souza, s/no, Gragoatá, 24210-340, Niterói, RJ (Brazil))" >Lacerda, T.; o, Gragoatá, 24210-340, Niterói, RJ (Brazil))" data-affiliation=" (Instituto de Física, Universidade Federal Fluminense, Av. Gal Milton Tavares de Souza, s/no, Gragoatá, 24210-340, Niterói, RJ (Brazil))" >Anjos, R.M.; Rizzotto, M.; Velasco, H.; Rosas, J.P. de; Tognelli, G.

2014-01-01

Radon levels in two old mines in San Luis, Argentina, were measured and analyzed, with the aim to assess the potential use of this radioactive noble gas as a tracer of geological processes in underground environments. La Carolina gold mine and Los Cóndores tungsten mine are today used as tourism mines. CR-39 nuclear track detectors were used for this purpose. Measurements were performed during both winter and summer seasons. The findings show that in these environments, significant radon concentrations are subject to large seasonal fluctuations, due to the strong dependence on natural ventilation with the outside temperature variations. For both mines, higher concentration values of 222 Rn were observed in summer than in winter; with an extreme ratio of 2.5 times between summer and winter seasons for Los Cóndores mine. The pattern of radon transport inside La Carolina mine revealed, contrary to what was believed, that this mine behaves as a system with two entrances located at different levels. However, this feature can only be observed in the winter season, when there is a marked difference between the inside and outside temperatures of the mine. In the case of Los Cóndores mine, the radon concentration pattern distribution is principally established by air current due to chimney-effect in summer and winter seasons. In both cases, the analyses of radon pattern distribution appear as a good method to trace air currents, and then localize unknown ducts, fissures or secondary tunnels in subterranean environments. - Highlights: • 222 Rn levels in two old mines in San Luis, Argentina • CR-39 nuclear track detectors were used for this purpose • higher concentration values of 222 Rn were observed in summer than in winter • radon pattern distribution appear as a good method to trace air currents • it localizes unknown ducts, fissures or secondary tunnels in subterranean environments

18F-FDG-PET/CT in fever of unknown origin

DEFF Research Database (Denmark)

Middelbo Buch-Olsen, Karen; Andersen, Rikke V; Hess, Søren

2014-01-01

OBJECTIVE: Fever of unknown origin continues to be a diagnostic challenge for clinicians. The aim of this study was to confirm whether (18)F-fluorodeoxyglucose ((18)F-FDG)-PET/computed tomography (CT) is a helpful tool in patients suffering from this condition. PATIENTS AND METHODS: Fifty......-seven patients with fever of unknown origin were examined with (18)F-FDG-PET/CT as part of their diagnostic workup at the clinicians' discretion. The medical records were read retrospectively to establish the final diagnosis and evaluate the degree to which PET/CT contributed to the diagnosis. RESULTS......-FDG-PET/CT is a useful tool in the investigation of fever of unknown origin; it can reduce patient inconvenience and possibly costs to society if used earlier in the diagnostic process....

Vibration control of an IVVS long-reach deployer using unknown visual features from inside the ITER vessel

International Nuclear Information System (INIS)

Dubus, G.; David, O.; Measson, Y.

2010-01-01

The In-Vessel Viewing System (IVVS) project assumes that a long reach deployer equipped with a probe penetrates the ITER chamber to perform periodic inspections. By giving the operator the capability and flexibility to examine unplanned targets, man-in-the-loop technology would be very helpful. But vibrations due to the high flexibility of the structure are probably the main problem in such a master-slave mode, which therefore needs the integration of a high level compensation scheme. However the ITER RH equipment will be confronted with strong electromagnetic interferences as well as a cumulated radiation dose up to several MGy. Short of costly developments, these constraints limit the use of dedicated electronics such as accelerometers or strain gauges. Our main idea is to control the vibrational behaviour of the flexible carrier without considering any extra sensor apart from its embedded probe. In this pre-study we propose to use the kind of rad-hardened viewing system already developed for the AIA demonstrator in order to feed an oscillation observer with visual information. The visual data are extracted from the environment without a priori knowledge of the examined scene. Our approach is quite open-ended and can be extended to other flexible systems. Moreover it has been designed to damp the oscillatory behaviour of the arm whatever its origins may be. As a consequence it should yield good performance when vibrations result from a critical trajectory imposed by the operator, from an interaction with the environment, or from internal dynamics of the carried process, e.g. the rotating prism of the IVVS 3D Inspection System. Experimental results validate the proposed strategy.

Vibration control of an IVVS long-reach deployer using unknown visual features from inside the ITER vessel

Energy Technology Data Exchange (ETDEWEB)

Dubus, G., E-mail: gregory.dubus@f4e.europa.e [Fusion for Energy, Remote Handling group, Josep Pla 2, Torres Diagonal Litoral B3, Barcelona E-08019 (Spain); David, O.; Measson, Y. [CEA LIST, Interactive Robotics Unit, 18 route du Panorama, BP6, Fontenay-aux-Roses F-92265 (France)

2010-12-15

The In-Vessel Viewing System (IVVS) project assumes that a long reach deployer equipped with a probe penetrates the ITER chamber to perform periodic inspections. By giving the operator the capability and flexibility to examine unplanned targets, man-in-the-loop technology would be very helpful. But vibrations due to the high flexibility of the structure are probably the main problem in such a master-slave mode, which therefore needs the integration of a high level compensation scheme. However the ITER RH equipment will be confronted with strong electromagnetic interferences as well as a cumulated radiation dose up to several MGy. Short of costly developments, these constraints limit the use of dedicated electronics such as accelerometers or strain gauges. Our main idea is to control the vibrational behaviour of the flexible carrier without considering any extra sensor apart from its embedded probe. In this pre-study we propose to use the kind of rad-hardened viewing system already developed for the AIA demonstrator in order to feed an oscillation observer with visual information. The visual data are extracted from the environment without a priori knowledge of the examined scene. Our approach is quite open-ended and can be extended to other flexible systems. Moreover it has been designed to damp the oscillatory behaviour of the arm whatever its origins may be. As a consequence it should yield good performance when vibrations result from a critical trajectory imposed by the operator, from an interaction with the environment, or from internal dynamics of the carried process, e.g. the rotating prism of the IVVS 3D Inspection System. Experimental results validate the proposed strategy.

Scheme for teleportation of unknown states of trapped ion

Institute of Scientific and Technical Information of China (English)

Chen Mei-Feng; Ma Song-She

2008-01-01

A scheme is presented for teleporting an unknown state in a trapped ion system.The scheme only requires a single laser beam.It allows the trap to be in any state with a few phonons,e.g.a thermal motion.Furthermore,it works in the regime,where the Rabi frequency of the laser is on the order of the trap frequency.Thus,the teleportation speed is greatly increased,which is important for decreasing the decoherence effect.This idea can also be used to teleport an unknown ionic entangled state.

Active fault tolerance control of a wind turbine system using an unknown input observer with an actuator fault

Directory of Open Access Journals (Sweden)

Li Shanzhi

2018-03-01

Full Text Available This paper proposes a fault tolerant control scheme based on an unknown input observer for a wind turbine system subject to an actuator fault and disturbance. Firstly, an unknown input observer for state estimation and fault detection using a linear parameter varying model is developed. By solving linear matrix inequalities (LMIs and linear matrix equalities (LMEs, the gains of the unknown input observer are obtained. The convergence of the unknown input observer is also analysed with Lyapunov theory. Secondly, using fault estimation, an active fault tolerant controller is applied to a wind turbine system. Finally, a simulation of a wind turbine benchmark with an actuator fault is tested for the proposed method. The simulation results indicate that the proposed FTC scheme is efficient.

Prevalence and Impact of Unknown Diabetes in the ICU.

Science.gov (United States)

Carpenter, David L; Gregg, Sara R; Xu, Kejun; Buchman, Timothy G; Coopersmith, Craig M

2015-12-01

Many patients with diabetes and their care providers are unaware of the presence of the disease. Dysglycemia encompassing hyperglycemia, hypoglycemia, and glucose variability is common in the ICU in patients with and without diabetes. The purpose of this study was to determine the impact of unknown diabetes on glycemic control in the ICU. Prospective observational study. Nine ICUs in an academic, tertiary hospital and a hybrid academic/community hospital. Hemoglobin A1c levels were ordered at all ICU admissions from March 1, 2011 to September 30, 2013. Electronic medical records were examined for a history of antihyperglycemic medications or International Classification of Diseases, 9th Edition diagnosis of diabetes. Patients were categorized as having unknown diabetes (hemoglobin A1c > 6.5%, without history of diabetes), no diabetes (hemoglobin A1c 6.5%, with documented history of diabetes). None. A total of 15,737 patients had an hemoglobin A1c and medical record evaluable for the history of diabetes, and 5,635 patients had diabetes diagnosed by either medical history or an elevated hemoglobin A1c in the ICU. Of these, 1,460 patients had unknown diabetes, accounting for 26.0% of all patients with diabetes. This represented 41.0% of patients with an hemoglobin A1c > 6.5% and 9.3% of all ICU patients. Compared with patients without diabetes, patients with unknown diabetes had a higher likelihood of requiring an insulin infusion (44.3% vs 29.3%; p 180 mg/dL; p < 0.0001) and hypoglycemia (8.9% vs 2.5%; blood glucose < 70 mg/dL; p < 0.0001), higher glycemic variability (55.6 vs 28.8, average of patient SD of glucose; p < 0.0001), and increased mortality (13.8% vs 11.4%; p = 0.01). Patients with unknown diabetes represent a significant percentage of ICU admissions. Measurement of hemoglobin A1c at admission can prospectively identify a population that are not known to have diabetes but have significant challenges in glycemic control in the ICU.

Circuit realization, chaos synchronization and estimation of parameters of a hyperchaotic system with unknown parameters

Directory of Open Access Journals (Sweden)

A. Elsonbaty

2014-10-01

Full Text Available In this article, the adaptive chaos synchronization technique is implemented by an electronic circuit and applied to the hyperchaotic system proposed by Chen et al. We consider the more realistic and practical case where all the parameters of the master system are unknowns. We propose and implement an electronic circuit that performs the estimation of the unknown parameters and the updating of the parameters of the slave system automatically, and hence it achieves the synchronization. To the best of our knowledge, this is the first attempt to implement a circuit that estimates the values of the unknown parameters of chaotic system and achieves synchronization. The proposed circuit has a variety of suitable real applications related to chaos encryption and cryptography. The outputs of the implemented circuits and numerical simulation results are shown to view the performance of the synchronized system and the proposed circuit.

Renal disease masquerading as pyrexia of unknown origin

Directory of Open Access Journals (Sweden)

D Korivi

2013-01-01

Full Text Available Pyrexia of unknown origin is a challenging clinical problem. Infections, malignancies, and connective tissue diseases form the major etiologies for this condition. We report a case of a 57-year-old diabetic male who presented with fever of unknown origin for several months. The course of investigations led to a kidney biopsy which clinched the cause of his fever as well as the underlying diagnosis. The light microscopy findings of expansile storiform fibrosis with a dense inflammatory infiltrate suggested the diagnosis which was confirmed by positive staining of Immunoglobulin G4, the dense lympho-plasmacytic infiltrate and elevated serum IgG4 concentrations. A course of steroids followed by mycophenolate mofetil as maintenance immunosuppression rendered the patient afebrile with improvement of renal function.

Intraabdominal abscessus of unknown etiology

Directory of Open Access Journals (Sweden)

Čolović Radoje

2012-01-01

Full Text Available Introduction. Intraabdominal abscesses are in 98-99% cases the result of secondary and only in 1-2% of primary peritonitis. They are easy and successfully diagnosed. Abdominal abscesses of unknown cause are extremely rare. Case Outline. The authors present a 68-year-old man, without significant data in past history, who suddenly developed epigastric pain, nausea, vomiting and leukocytosis which was treated with antibiotics resulting in the alleviation of complaints and reduction of white blood cells count. After five days ultrasonography showed incapsulated collection of dense fluid in the epigastrium confirmed by CT scan two days later. Upper endoscopy excluded ulcer and/or perforation of the stomach and duodenum. Under local anesthesia, through the upper part of the left rectal muscle, puncture followed by incision was done, and about 50 ml of dense pus was removed. Finger exploration of the cavity showed no foreign body within the cavity. Using drainage, the recovery was quick and uneventful. By preoperative and postoperative abdominal investigations no cause of the abscess was found. Two and a half years after surgery the patient remained symptom-free with normal clinical, laboratory and ultrasonographic findings. Conclusion. The authors presented an intraabdominal abscess of unknown cause that was successfully treated with antibiotics, percutaneous puncture and drainage under local anaesthesia. In spite of all diagnostic methods the cause of the abscess could not be found. Thus, such a possibility, although being rare, should be taken into account.

Adaptive Algorithm For Identification Of The Environment Parameters In Contact Tasks

Energy Technology Data Exchange (ETDEWEB)

Tuneski, Atanasko; Babunski, Darko [Faculty of Mechanical Engineering, ' St. Cyril and Methodius' University, Skopje (Macedonia, The Former Yugoslav Republic of)

2003-07-01

An adaptive algorithm for identification of the unknown parameters of the dynamic environment in contact tasks is proposed in this paper using the augmented least square estimation method. An approximate environment digital simulator for the continuous environment dynamics is derived, i.e. a discrete transfer function which has the approximately the same characteristics as the continuous environment dynamics is found. For solving this task a method named hold equivalence is used. The general model of the environment dynamics is given and the case when the environment dynamics is represented by second order models with parameter uncertainties is considered. (Author)

Adaptive Algorithm For Identification Of The Environment Parameters In Contact Tasks

International Nuclear Information System (INIS)

Tuneski, Atanasko; Babunski, Darko

2003-01-01

An adaptive algorithm for identification of the unknown parameters of the dynamic environment in contact tasks is proposed in this paper using the augmented least square estimation method. An approximate environment digital simulator for the continuous environment dynamics is derived, i.e. a discrete transfer function which has the approximately the same characteristics as the continuous environment dynamics is found. For solving this task a method named hold equivalence is used. The general model of the environment dynamics is given and the case when the environment dynamics is represented by second order models with parameter uncertainties is considered. (Author)

Confluence of genes, environment, development, and behavior in a post Genome-Wide Association Study world.

Science.gov (United States)

Vrieze, Scott I; Iacono, William G; McGue, Matt

2012-11-01

This article serves to outline a research paradigm to investigate main effects and interactions of genes, environment, and development on behavior and psychiatric illness. We provide a historical context for candidate gene studies and genome-wide association studies, including benefits, limitations, and expected payoffs. Using substance use and abuse as our driving example, we then turn to the importance of etiological psychological theory in guiding genetic, environmental, and developmental research, as well as the utility of refined phenotypic measures, such as endophenotypes, in the pursuit of etiological understanding and focused tests of genetic and environmental associations. Phenotypic measurement has received considerable attention in the history of psychology and is informed by psychometrics, whereas the environment remains relatively poorly measured and is often confounded with genetic effects (i.e., gene-environment correlation). Genetically informed designs, which are no longer limited to twin and adoption studies thanks to ever-cheaper genotyping, are required to understand environmental influences. Finally, we outline the vast amount of individual difference in structural genomic variation, most of which remains to be leveraged in genetic association tests. Although the genetic data can be massive and burdensome (tens of millions of variants per person), we argue that improved understanding of genomic structure and function will provide investigators with new tools to test specific a priori hypotheses derived from etiological psychological theory, much like current candidate gene research but with less confusion and more payoff than candidate gene research has to date.

Decentralised output feedback control of Markovian jump interconnected systems with unknown interconnections

Science.gov (United States)

Li, Li-Wei; Yang, Guang-Hong

2017-07-01

The problem of decentralised output feedback control is addressed for Markovian jump interconnected systems with unknown interconnections and general transition rates (TRs) allowed to be unknown or known with uncertainties. A class of decentralised dynamic output feedback controllers are constructed, and a cyclic-small-gain condition is exploited to dispose the unknown interconnections so that the resultant closed-loop system is stochastically stable and satisfies an H∞ performance. With slack matrices to cope with the nonlinearities incurred by unknown and uncertain TRs in control synthesis, a novel controller design condition is developed in linear matrix inequality formalism. Compared with the existing works, the proposed approach leads to less conservatism. Finally, two examples are used to illustrate the effectiveness of the new results.

From 'circumstances' to 'environment': Herbert Spencer and the origins of the idea of organism-environment interaction.

Science.gov (United States)

Pearce, Trevor

2010-09-01

The word 'environment' has a history. Before the mid-nineteenth century, the idea of a singular, abstract entity--the organism--interacting with another singular, abstract entity--the environment--was virtually unknown. In this paper I trace how the idea of a plurality of external conditions or circumstances was replaced by the idea of a singular environment. The central figure behind this shift, at least in Anglo-American intellectual life, was the philosopher Herbert Spencer. I examine Spencer's work from 1840 to 1855, demonstrating that he was exposed to a variety of discussions of the 'force of circumstances' in this period, and was decisively influenced by the ideas of Auguste Comte in the years preceding the publication of Principles of psychology (1855). It is this latter work that popularized the word 'environment' and the corresponding idea of organism--environment interaction--an idea with important metaphysical and methodological implications. Spencer introduced into the English-speaking world one of our most enduring dichotomies: organism and environment. Copyright © 2010 Elsevier Ltd. All rights reserved.

Iterative Selection of Unknown Weights in Direct Weight Optimization Identification

Directory of Open Access Journals (Sweden)

Xiao Xuan

2014-01-01

Full Text Available To the direct weight optimization identification of the nonlinear system, we add some linear terms about input sequences in the former linear affine function so as to approximate the nonlinear property. To choose the two classes of unknown weights in the more linear terms, this paper derives the detailed process on how to choose these unknown weights from theoretical analysis and engineering practice, respectively, and makes sure of their key roles between the unknown weights. From the theoretical analysis, the added unknown weights’ auxiliary role can be known in the whole process of approximating the nonlinear system. From the practical analysis, we learn how to transform one complex optimization problem to its corresponding common quadratic program problem. Then, the common quadratic program problem can be solved by the basic interior point method. Finally, the efficiency and possibility of the proposed strategies can be confirmed by the simulation results.

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

Science.gov (United States)

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.

A Brief Introduction on Mystery, the Unknown, Surprise

Directory of Open Access Journals (Sweden)

Sean Scanlan

2012-03-01

Full Text Available In this age of globalization, this age of so many ways to know—and so many ways to know things so quickly—it is both satisfying and deeply unnerving to come upon things and events that are really hard to understand, things and events so shocking or strange or mysterious, that they seem Unknown. Perhaps even unknowable. The first note of NANO Issue 2 focuses on an unsolved murder and reveals a mystery that is confounding, creepy, and yet oddly compelling. In “Karr’s Kill Cult: Virtual Cults and Pseudo-Killing in the Digital Age,” Jeremy Biles and Brian Collins explore the edges of where cyber-crime threatens to turn real—and vice versa. In the second note, Jennifer Ballengee compares Oedipus at Colonus with Don DeLillo’s Falling Man.

Previously unknown evolutionary groups dominate the ssDNA gokushoviruses in oxic and anoxic waters of a coastal marine environment

Directory of Open Access Journals (Sweden)

Jessica M. Labonté

2015-04-01

Full Text Available Metagenomic studies have revealed that ssDNA phages from the family Microviridae subfamily Gokushovirinae are widespread in aquatic ecosystems. It is hypothesized that gokushoviruses occupy specialized niches, resulting in differences among genotypes traversing water column gradients. Here, we use degenerate primers that amplify a fragment of the gene encoding the major capsid protein to examine the diversity of gokushoviruses in Saanich Inlet, a seasonally anoxic fjord on the coast of Vancouver Island, British Columbia. Amplicon sequencing of samples from the mixed oxic surface (10 m and deeper anoxic (200 m layers indicated a diverse assemblage of gokushoviruses, with greater richness at 10 m than 200 m. A comparison of amplicon sequences with sequences selected on the basis of RFLP patterns from eight surface samples collected over a one-year period revealed that gokushovirus diversity was higher in spring and summer during stratification, and lower in fall and winter after deep-water renewal, consistent with seasonal variability within gokushovirus populations. Phylogenetic analysis of clustered amplicons revealed at least five new phylogenetic clades of previously unknown sequences, with the most abundant group associated with viruses that infect SUP05, a ubiquitous and abundant member of marine oxygen minimum zones. Our results provide persuasive evidence that, while specific gokushovirus genotypes may have a narrow host range, hosts for gokushoviruses in Saanich Inlet consist of a wide range of bacterial taxa, including SUP05, a taxonomic clade of gamma proteobacterial sulfur oxidizers. Members of SUP05 are abundant in Saanich Inlet and involved in carbon, nitrogen, and sulfur cycling along the redoxline; thus, gokushoviruses are likely important mortality agents of these bacteria and have consequent influences on biogeochemical cycling in this system.

SEM-EDX analysis of an unknown "known" white powder found in a shipping container from Peru

Science.gov (United States)

Albright, Douglas C.

2009-05-01

In 2008, an unknown white powder was discovered spilled inside of a shipping container of whole kernel corn during an inspection by federal inspectors in the port of Baltimore, Maryland. The container was detained and quarantined while a sample of the powder was collected and sent to a federal laboratory where it was screened using chromatography for the presence of specific poisons and pesticides with negative results. Samples of the corn kernels and the white powder were forwarded to the Food and Drug Administration, Forensic Chemistry Center for further analysis. Stereoscopic Light Microscopy (SLM), Scanning Electron Microscopy/Energy Dispersive X-ray Spectrometry (SEM/EDX), and Polarized Light Microscopy/Infrared Spectroscopy (PLM-IR) were used in the analysis of the kernels and the unknown powder. Based on the unique particle analysis by SLM and SEM as well as the detection of the presence of aluminum and phosphorous by EDX, the unknown was determined to be consistent with reacted aluminum phosphide (AlP). While commonly known in the agricultural industry, aluminum phosphide is relatively unknown in the forensic community. A history of the use and acute toxicity of this compound along with some very unique SEM/EDX analysis characteristics of aluminum phosphide will be discussed.

A highly abundant bacteriophage discovered in the unknown sequences of human faecal metagenomes

NARCIS (Netherlands)

Dutilh, Bas E; Cassman, Noriko; McNair, Katelyn; Sanchez, Savannah E; Silva, Genivaldo G Z; Boling, Lance; Barr, Jeremy J; Speth, Daan R; Seguritan, Victor; Aziz, Ramy K; Felts, Ben; Dinsdale, Elizabeth A; Mokili, John L; Edwards, Robert A

2014-01-01

Metagenomics, or sequencing of the genetic material from a complete microbial community, is a promising tool to discover novel microbes and viruses. Viral metagenomes typically contain many unknown sequences. Here we describe the discovery of a previously unidentified bacteriophage present in the

Cancer of unknown primary origin: a case report

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Elisa De Carlo

2013-03-01

Full Text Available Carcinoma of unknown primary origin (CUP accounts for 2-10% of all malignancies. The apparent absence of the primary tumour, the development of early, uncommon systemic metastases and the resistance to therapy and poor prognosis are hallmarks of this heterogeneous clinical entity and are a challenge for physicians. The diagnostic workup of patients with CUP includes a large amount of histopathological examination, as well as the use of imaging techniques that often fail to identify the primary tumour. Therefore, the optimal workup and treatment for these patients remains to be determined. Molecular diagnostic tools, such as DNA microarray analysis, could help in the search for "lost" CUP origin and guide the further treatment approach. We report the case of a 66-year-old man, with mediastinal lymph nodes metastasis of carcinoma and neurological syndrome with diplopia and balance disorders, in which many exams have been performed without finding the primary tumour.

Tunable Collagen I Hydrogels for Engineered Physiological Tissue Micro-Environments

Science.gov (United States)

Antoine, Elizabeth E.; Vlachos, Pavlos P.; Rylander, Marissa N.

2015-01-01

Collagen I hydrogels are commonly used to mimic the extracellular matrix (ECM) for tissue engineering applications. However, the ability to design collagen I hydrogels similar to the properties of physiological tissues has been elusive. This is primarily due to the lack of quantitative correlations between multiple fabrication parameters and resulting material properties. This study aims to enable informed design and fabrication of collagen hydrogels in order to reliably and reproducibly mimic a variety of soft tissues. We developed empirical predictive models relating fabrication parameters with material and transport properties. These models were obtained through extensive experimental characterization of these properties, which include compression modulus, pore and fiber diameter, and diffusivity. Fabrication parameters were varied within biologically relevant ranges and included collagen concentration, polymerization pH, and polymerization temperature. The data obtained from this study elucidates previously unknown fabrication-property relationships, while the resulting equations facilitate informed a priori design of collagen hydrogels with prescribed properties. By enabling hydrogel fabrication by design, this study has the potential to greatly enhance the utility and relevance of collagen hydrogels in order to develop physiological tissue microenvironments for a wide range of tissue engineering applications. PMID:25822731

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

Science.gov (United States)

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.

Value of Bone marrow Examination in Pyrexia of unknown origin

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A Jha

2013-10-01

Full Text Available Background: Pyrexia of unknown origin is a common diagnostic dilemma. Series of diagnostic modalities are required to arrive at diagnosis. Bone marrow examination is one of the common tests implicated in the diagnosis in combination with other diagnostic modalities. Present study has attempted to explore the causes of pyrexia of unknown origin based on bone marrow morphological study. Materials and Methods: In a one year prospective study conducted at Manipal Teaching Hospital, Pokhara, Nepal; bone marrow aspiration and biopsy was performed and evaluated morphologically, in 57 patients fulfilling the criteria of classic pyrexia of unknown origin. Results: In 42% cases; specific diagnosis could be made and hematological neoplasm was the most common finding followed by megaloblastic anemia, hypoplastic anemia and one case each of hemophagocytosis, malaria and tuberculosis. Acute leukemia was the most frequently encountered hematological malignancy followed by multiple myeloma, chronic myeloid leukemia, essential thrombocythemia and myelodysplastic syndrome. Conclusion: Morphological examination of bone marrow has important role in diagnosis of pyrexia of unknown origin. However, yield of diagnosis can be increased if it is combined with other diagnostic modalities including radiological, microbiological and serological tests. DOI: http://dx.doi.org/10.3126/jpn.v3i6.8991 Journal of Pathology of Nepal (2013 Vol. 3, 447-451

Adaptive Incentive Controls for Stackelberg Games with Unknown Cost Functionals.

Science.gov (United States)

1984-01-01

APR EZT:: F I AN 73S e OsL:-: UNCLASSI?:-- Q4~.’~- .A.., 6, *~*i i~~*~~*.- U ADAPTIVE INCENTIVE CONTROLS FOR STACKELBERG GAMES WITH UNKNOWN COST...AD-A161 885 ADAPTIVE INCENTIVE CONTROLS FOR STACKELBERG GAMES WITH i/1 UNKNOWN COST FUNCTIONALSCU) ILLINOIS UNIV AT URBANA DECISION AND CONTROL LAB T...ORGANIZATION 6b. OFFICE SYMBOL 7.. NAME OF MONITORING ORGANIZATION CoriaeLcenef~pda~ Joint Services Electronics Program Laboratory, Univ. of Illinois N/A

Elimination of some unknown parameters and its effect on outlier detection

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Serif Hekimoglu

Full Text Available Outliers in observation set badly affect all the estimated unknown parameters and residuals, that is because outlier detection has a great importance for reliable estimation results. Tests for outliers (e.g. Baarda's and Pope's tests are frequently used to detect outliers in geodetic applications. In order to reduce the computational time, sometimes elimination of some unknown parameters, which are not of interest, is performed. In this case, although the estimated unknown parameters and residuals do not change, the cofactor matrix of the residuals and the redundancies of the observations change. In this study, the effects of the elimination of the unknown parameters on tests for outliers have been investigated. We have proved that the redundancies in initial functional model (IFM are smaller than the ones in reduced functional model (RFM where elimination is performed. To show this situation, a horizontal control network was simulated and then many experiences were performed. According to simulation results, tests for outlier in IFM are more reliable than the ones in RFM.

Neuroendocrine Merkel cell nodal carcinoma of unknown primary site: management and outcomes of a rare entity.

Science.gov (United States)

Kotteas, E A; Pavlidis, N

2015-04-01

Merkel cell nodal carcinoma of unknown primary (MCCUP) is a rare neuroendocrine tumour with distinct clinical and biological behaviour. We conducted a review of retrospective data extracted from 90 patients focusing on the management and outcome of this disease. We also compared life expectancy of these patients with the outcome of patients with known Merkel primaries and with neuroendocrine cancers of unidentifiable primary. There is a limited body of data for this type of malignancy, however, patients with Merkel cell nodal carcinoma of unknown primary site, seem to have better survival when treated aggressively than patients with cutaneous Merkel tumours of the same stage and equal survival with patients with low-grade neuroendocrine tumour of unknown origin. The lack of prospective trials, and the inadequate data, hamper the management of these tumours. Establishment of treatment guidelines is urgently needed. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A Multidisciplinary Investigation of a Polycythemia Vera Cancer Cluster of Unknown Origin

Science.gov (United States)

Seaman, Vincent; Dearwent, Steve M; Gable, Debra; Lewis, Brian; Metcalf, Susan; Orloff, Ken; Tierney, Bruce; Zhu, Jane; Logue, James; Marchetto, David; Ostroff, Stephen; Hoffman, Ronald; Xu, Mingjiang; Carey, David; Erlich, Porat; Gerhard, Glenn; Roda, Paul; Iannuzzo, Joseph; Lewis, Robert; Mellow, John; Mulvihill, Linda; Myles, Zachary; Wu, Manxia; Frank, Arthur; Gross-Davis, Carol Ann; Klotz, Judith; Lynch, Adam; Weissfeld, Joel; Weinberg, Rona; Cole, Henry

2010-01-01

Cancer cluster investigations rarely receive significant public health resource allocations due to numerous inherent challenges and the limited success of past efforts. In 2008, a cluster of polycythemia vera, a rare blood cancer with unknown etiology, was identified in northeast Pennsylvania. A multidisciplinary group of federal and state agencies, academic institutions, and local healthcare providers subsequently developed a multifaceted research portfolio designed to better understand the cause of the cluster. This research agenda represents a unique and important opportunity to demonstrate that cancer cluster investigations can produce desirable public health and scientific outcomes when necessary resources are available. PMID:20617023

A NEW METHOD OF CHANNEL FRICTION INVERSION BASED ON KALMAN FILTER WITH UNKNOWN PARAMETER VECTOR

Institute of Scientific and Technical Information of China (English)

CHENG Wei-ping; MAO Gen-hai; LIU Guo-hua

2005-01-01

Channel friction is an important parameter in hydraulic analysis.A channel friction parameter inversion method based on Kalman Filter with unknown parameter vector is proposed.Numerical simulations indicate that when the number of monitoring stations exceeds a critical value, the solution is hardly affected.In addition, Kalman Filter with unknown parameter vector is effective only at unsteady state.For the nonlinear equations, computations of sensitivity matrices are time-costly.Two simplified measures can reduce computing time, but not influence the results.One is to reduce sensitivity matrix analysis time, the other is to substitute for sensitivity matrix.

Adaptive observer for the joint estimation of parameters and input for a coupled wave PDE and infinite dimensional ODE system

KAUST Repository

Belkhatir, Zehor

2016-08-05

This paper deals with joint parameters and input estimation for coupled PDE-ODE system. The system consists of a damped wave equation and an infinite dimensional ODE. This model describes the spatiotemporal hemodynamic response in the brain and the objective is to characterize brain regions using functional Magnetic Resonance Imaging (fMRI) data. For this reason, we propose an adaptive estimator and prove the asymptotic convergence of the state, the unknown input and the unknown parameters. The proof is based on a Lyapunov approach combined with a priori identifiability assumptions. The performance of the proposed observer is illustrated through some simulation results.

Rendezvous with connectivity preservation for multi-robot systems with an unknown leader

Science.gov (United States)

Dong, Yi

2018-02-01

This paper studies the leader-following rendezvous problem with connectivity preservation for multi-agent systems composed of uncertain multi-robot systems subject to external disturbances and an unknown leader, both of which are generated by a so-called exosystem with parametric uncertainty. By combining internal model design, potential function technique and adaptive control, two distributed control strategies are proposed to maintain the connectivity of the communication network, to achieve the asymptotic tracking of all the followers to the output of the unknown leader system, as well as to reject unknown external disturbances. It is also worth to mention that the uncertain parameters in the multi-robot systems and exosystem are further allowed to belong to unknown and unbounded sets when applying the second fully distributed control law containing a dynamic gain inspired by high-gain adaptive control or self-tuning regulator.

Psychological profile: the problem of modeling the unknown criminal personality

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Г. М. Гетьман

2013-10-01

Full Text Available The article investigates the problem of modeling an unknown person in the preparation of criminal psychological profile. Some approaches to the concept of "psychological profile" and "psychological portrait", in particular the proposed delineation of these terms. We consider the system steps in the development of the psychological profile of an unknown perpetrator.

Multifocal chronic osteomyelitis of unknown etiology

International Nuclear Information System (INIS)

Kozlowski, K.; Masel, J.; Harbison, S.; Yu, J.; Royal Brisbane Children Hospital; Regional Hospital Bowral

1983-01-01

Five cases of chronic, inflammatory, multifocal bone lesions of unknown etiology are reported. Although bone biopsy confirmed osteomyelitis in each case in none of them were organisms found inspite of an extensive work up. Different clinical course of the disease reflects different aetiology in respective cases. These cases present changing aspects of osteomyelitis emerging since introduction of antibiotics. (orig.)

Designing towards the Unknown: Engaging with Material and Aesthetic Uncertainty

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Danielle Wilde

2017-12-01

Full Text Available New materials with new capabilities demand new ways of approaching design. Destabilising existing methods is crucial to develop new methods. Yet, radical destabilisation—where outcomes remain unknown long enough that new discoveries become possible—is not easy in technology design where complex interdisciplinary teams with time and resource constraints need to deliver concrete outcomes on schedule. The Poetic Kinaesthetic Interface project (PKI engages with this problematic directly. In PKI we use unfolding processes—informed by participatory, speculative and critical design—in emergent actions, to design towards unknown outcomes, using unknown materials. The impossibility of this task is proving as useful as it is disruptive. At its most potent, it is destabilising expectations, aesthetics and processes. Keeping the researchers, collaborators and participants in a state of unknowing, is opening the research potential to far-ranging possibilities. In this article we unpack the motivations driving the PKI project. We present our mixed-methodology, which entangles textile crafts, design interactions and materiality to shape an embodied enquiry. Our research outcomes are procedural and methodological. PKI brings together diverse human, non-human, known and unknown actors to discover where the emergent assemblages might lead. Our approach is re-invigorating—as it demands re-envisioning of—the design process.

Speeding up transmissions of unknown quantum information along Ising-type quantum channels

International Nuclear Information System (INIS)

Guo W J; Wei L F

2017-01-01

Quantum teleportation with entanglement channels and a series of two-qubit SWAP gates between the nearest-neighbor qubits are usually utilized to achieve the transfers of unknown quantum state from the sender to the distant receiver. In this paper, by simplifying the usual SWAP gates we propose an approach to speed up the transmissions of unknown quantum information, specifically including the single-qubit unknown state and two-qubit unknown entangled ones, by a series of entangling and disentangling operations between the remote qubits with distant interactions. The generic proposal is demonstrated specifically with experimentally-existing Ising-type quantum channels without transverse interaction; liquid NMR-molecules driven by global radio frequency electromagnetic pulses and capacitively-coupled Josephson circuits driven by local microwave pulses. The proposal should be particularly useful to set up the connections between the distant qubits in a chip of quantum computing. (paper)

Multidimensional procurement auctions with unknown weights

DEFF Research Database (Denmark)

Greve, Thomas

This paper studies the consequences of holding a procurement auction when the principal chooses not to show its preferences. My paper extends the procurement auction model of Che (1993) to a situation where both the principal and the agents have private information. Thus, unknown parameters of bo...... gives rise to an analysis of a principal that can not fully commit to the outcome induced by the scoring rule. Therefore, my result apply to contract theory and it’s problems with imperfect commitment....

Lod score curves for phase-unknown matings.

Science.gov (United States)

Hulbert-Shearon, T; Boehnke, M; Lange, K

1996-01-01

For a phase-unknown nuclear family, we show that the likelihood and lod score are unimodal, and we describe conditions under which the maximum occurs at recombination fraction theta = 0, theta = 1/2, and 0 < theta < 1/2. These simply stated necessary and sufficient conditions seem to have escaped the notice of previous statistical geneticists.

A powerful test for weak periodic signals with unknown light curve shape in sparse data

International Nuclear Information System (INIS)

Jager De, O.C.; Raubenheimer, B.C.; Swanepoel, J.W.H.

1989-01-01

A problem with most tests for periodicity is that they are powerful enough to detect only certain kinds of periodic shapes in the case of weak signals. This causes a selection effect with the identification of weak periodic signals. A new test for uniformity called the H-test is derived for which the probability distribution is an exponential function. This test is shown to have a very good power against most light curve shapes encountered in X- and γ-ray Astronomy and therefore makes the detection of sources with a larger variety of shapes possible. The use of the H-test is suggested if no a priori information about the light curve shape is available. It is also shown how the probability distribution of the test statistics changes when a periodicity search is conducted using very small steps in the period or frequency range. The flux sensitivity for various light curve shapes is also derived for a few tests and this flux is on average a minimum for the H-test

Chronic kidney disease of unknown etiology in Sri Lanka.

Science.gov (United States)

Rajapakse, Senaka; Shivanthan, Mitrakrishnan Chrishan; Selvarajah, Mathu

2016-07-01

In the last two decades, chronic kidney disease of unknown etiology (CKDu) has emerged as a significant contributor to the burden of chronic kidney disease (CKD) in rural Sri Lanka. It is characterized by the absence of identified causes for CKD. The prevalence of CKDu is 15.1-22.9% in some Sri Lankan districts, and previous research has found an association with farming occupations. A systematic literature review in Pubmed, Embase, Scopus, and Lilacs databases identified 46 eligible peer-reviewed articles and one conference abstract. Geographical mapping indicates a relationship between CKDu and agricultural irrigation water sources. Health mapping studies, human biological studies, and environment-based studies have explored possible causative agents. Most studies focused on likely causative agents related to agricultural practices, geographical distribution based on the prevalence and incidence of CKDu, and contaminants identified in drinking water. Nonetheless, the link between agrochemicals or heavy metals and CKDu remains to be established. No definitive cause for CKDu has been identified. Evidence to date suggests that the disease is related to one or more environmental agents, however pinpointing a definite cause for CKDu is challenging. It is plausible that CKDu is multifactorial. No specific guidelines or recommendations exist for treatment of CKDu, and standard management protocols for CKD apply. Changes in agricultural practices, provision of safe drinking water, and occupational safety precautions are recommended by the World Health Organization.

Identification of fractional-order systems with unknown initial values and structure

Energy Technology Data Exchange (ETDEWEB)

Du, Wei, E-mail: duwei0203@gmail.com [Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237 (China); Miao, Qingying, E-mail: qymiao@sjtu.edu.cn [School of Continuing Education, Shanghai Jiao Tong University, Shanghai 200030 (China); Tong, Le, E-mail: tongle0328@gmail.com [Faculty of Applied Science and Textiles, The Hong Kong Polytechnic University, Hong Kong (China); Tang, Yang [Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237 (China)

2017-06-21

In this paper, the identification problem of fractional-order chaotic systems is proposed and investigated via an evolutionary optimization approach. Different with other studies to date, this research focuses on the identification of fractional-order chaotic systems with not only unknown orders and parameters, but also unknown initial values and structure. A group of fractional-order chaotic systems, i.e., Lorenz, Lü, Chen, Rössler, Arneodo and Volta chaotic systems, are set as the system candidate pool. The identification problem of fractional-order chaotic systems in this research belongs to mixed integer nonlinear optimization in essence. A powerful evolutionary algorithm called composite differential evolution (CoDE) is introduced for the identification problem presented in this paper. Extensive experiments are carried out to show that the fractional-order chaotic systems with unknown initial values and structure can be successfully identified by means of CoDE. - Highlights: • Unknown initial values and structure are introduced in the identification of fractional-order chaotic systems; • Only a series of output is utilized in the identification of fractional-order chaotic systems; • CoDE is used for the identification problem and the results are satisfactory when compared with other DE variants.

Robust Control for the Segway with Unknown Control Coefficient and Model Uncertainties

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Byung Woo Kim

2016-06-01

Full Text Available The Segway, which is a popular vehicle nowadays, is an uncertain nonlinear system and has an unknown time-varying control coefficient. Thus, we should consider the unknown time-varying control coefficient and model uncertainties to design the controller. Motivated by this observation, we propose a robust control for the Segway with unknown control coefficient and model uncertainties. To deal with the time-varying unknown control coefficient, we employ the Nussbaum gain technique. We introduce an auxiliary variable to solve the underactuated problem. Due to the prescribed performance control technique, the proposed controller does not require the adaptive technique, neural network, and fuzzy logic to compensate the uncertainties. Therefore, it can be simple. From the Lyapunov stability theory, we prove that all signals in the closed-loop system are bounded. Finally, we provide the simulation results to demonstrate the effectiveness of the proposed control scheme.

M-MRAC Backstepping for Systems with Unknown Virtual Control Coefficients

Science.gov (United States)

Stepanyan, Vahram; Krishnakumar, Kalmanje

2015-01-01

The paper presents an over-parametrization free certainty equivalence state feedback backstepping adaptive control design method for systems of any relative degree with unmatched uncertainties and unknown virtual control coefficients. It uses a fast prediction model to estimate the unknown parameters, which is independent of the control design. It is shown that the system's input and output tracking errors can be systematically decreased by the proper choice of the design parameters. The benefits of the approach are demonstrated in numerical simulations.

System reliability prediction using data from non-identical environments

International Nuclear Information System (INIS)

Bergman, B.; Ringi, M.

1997-01-01

Since information changes one's mind and probability assessments reflect one's degree of beliefs, a reliability prediction model should enclose all relevant information. Almost always ignored in existing reliability models is the dependence on component life lengths, induced by a common but unknown environment. Furthermore, existing models seldom permit learning from components' performance in similar systems, under the knowledge of non-identical operating environments. In an earlier paper by the present authors the first type of aspects were taken into account and in this paper that model is generalised so that failure data generated from several similar systems in non-identical environments may be used for the prediction of any similar system in its specific environment

Splenectomy as a treatment for adults with relapsed hemophagocytic lymphohistiocytosis of unknown cause.

Science.gov (United States)

Jing-Shi, Wang; Yi-Ni, Wang; Lin, Wu; Zhao, Wang

2015-05-01

Our aim was to evaluate the clinical value of splenectomy as a treatment for relapsed hemophagocytic lymphohistiocytosis (HLH) of unknown cause in adults. We retrospectively reviewed the clinical data from medical records of 19 adults with relapsed HLH of unknown cause treated with splenectomy in our institution from June 2007 to March 2014. To rule out possible underlying diseases, including infection, autoimmune disease, neoplasms, and primary HLH, the patients had undergone examinations including F18 fluoro-2-deoxyglucose positron emission tomography/computed tomography, HLH-associated gene defects, and lymph node biopsies. Twelve patients (63.2%) achieved partial responses (PR), whereas seven patients (36.8%) had no response (NR) prior to splenectomy. Infection and hemorrhage were the main complications of splenectomy. Eighteen cases were evaluable after follow-up. Seven cases with histopathologic diagnoses of lymphoma had received chemotherapy, four of whom had achieved complete responses (CR), one PR, and two NR. Maintenance treatment was ceased 2 or 3 months after splenectomy in the other 11 cases, five of whom had CR, four PR, and two NR. Eleven of 18 cases (61.1%) survived with a median follow-up of 25 months (range 3-79 months) for survivors. Twelve- and 36-month progression-free survival rates were 48 and 24%, respectively; 12- and 36-month overall survival rates were 57 and 25%, respectively. Median survival time was 22 months. Our results indicate splenectomy may be an effective means of diagnosis and treatment of relapsed HLH of unknown cause. Further study is required to establish the mechanism and value of splenectomy in this disease.

Severe scratcher-reaction: an unknown health hazard?

Directory of Open Access Journals (Sweden)

Carsten Sauer Mikkelsen

2015-03-01

Full Text Available Tattoos are well known to cause skin problems and the number of reported adverse reactions after tattooing has increased. Illegally imported tattoo ink is unrestrained and can contain unknown ingredients and contamination thereby posing a serious health hazard. We present a case illustrating the risk of pronounced phototoxic allergic reaction and other severe complications after using home kit tattoo ink.

InSourcerer: a high-throughput method to search for unknown metabolite modifications by mass spectrometry.

Science.gov (United States)

Mrzic, Aida; Lermyte, Frederik; Vu, Trung Nghia; Valkenborg, Dirk; Laukens, Kris

2017-09-15

Using mass spectrometry, the analysis of known metabolite structures has become feasible in a systematic high-throughput fashion. Nevertheless, the identification of previously unknown structures remains challenging, partially because many unidentified variants originate from known molecules that underwent unexpected modifications. Here, we present a method for the discovery of unknown metabolite modifications and conjugate metabolite isoforms in a high-throughput fashion. The method is based on user-controlled in-source fragmentation which is used to induce loss of weakly bound modifications. This is followed by the comparison of product ions from in-source fragmentation and collision-induced dissociation (CID). Diagonal MS 2 -MS 3 matching allows the detection of unknown metabolite modifications, as well as substructure similarities. As the method relies heavily on the advantages of in-source fragmentation and its ability to 'magically' elucidate unknown modification, we have named it inSourcerer as a portmanteau of in-source and sorcerer. The method was evaluated using a set of 15 different cytokinin standards. Product ions from in-source fragmentation and CID were compared. Hierarchical clustering revealed that good matches are due to the presence of common substructures. Plant leaf extract, spiked with a mix of all 15 standards, was used to demonstrate the method's ability to detect these standards in a complex mixture, as well as confidently identify compounds already present in the plant material. Here we present a method that incorporates a classic liquid chromatography/mass spectrometry (LC/MS) workflow with fragmentation models and computational algorithms. The assumptions upon which the concept of the method was built were shown to be valid and the method showed that in-source fragmentation can be used to pinpoint structural similarities and indicate the occurrence of a modification. Copyright © 2017 John Wiley & Sons, Ltd.

Previously unknown species of Aspergillus.

Science.gov (United States)

Gautier, M; Normand, A-C; Ranque, S

2016-08-01

The use of multi-locus DNA sequence analysis has led to the description of previously unknown 'cryptic' Aspergillus species, whereas classical morphology-based identification of Aspergillus remains limited to the section or species-complex level. The current literature highlights two main features concerning these 'cryptic' Aspergillus species. First, the prevalence of such species in clinical samples is relatively high compared with emergent filamentous fungal taxa such as Mucorales, Scedosporium or Fusarium. Second, it is clearly important to identify these species in the clinical laboratory because of the high frequency of antifungal drug-resistant isolates of such Aspergillus species. Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently been shown to enable the identification of filamentous fungi with an accuracy similar to that of DNA sequence-based methods. As MALDI-TOF MS is well suited to the routine clinical laboratory workflow, it facilitates the identification of these 'cryptic' Aspergillus species at the routine mycology bench. The rapid establishment of enhanced filamentous fungi identification facilities will lead to a better understanding of the epidemiology and clinical importance of these emerging Aspergillus species. Based on routine MALDI-TOF MS-based identification results, we provide original insights into the key interpretation issues of a positive Aspergillus culture from a clinical sample. Which ubiquitous species that are frequently isolated from air samples are rarely involved in human invasive disease? Can both the species and the type of biological sample indicate Aspergillus carriage, colonization or infection in a patient? Highly accurate routine filamentous fungi identification is central to enhance the understanding of these previously unknown Aspergillus species, with a vital impact on further improved patient care. Copyright © 2016 European Society of Clinical Microbiology and

A 'range test' for determining scatterers with unknown physical properties

Science.gov (United States)

Potthast, Roland; Sylvester, John; Kusiak, Steven

2003-06-01

We describe a new scheme for determining the convex scattering support of an unknown scatterer when the physical properties of the scatterers are not known. The convex scattering support is a subset of the scatterer and provides information about its location and estimates for its shape. For convex polygonal scatterers the scattering support coincides with the scatterer and we obtain full shape reconstructions. The method will be formulated for the reconstruction of the scatterers from the far field pattern for one or a few incident waves. The method is non-iterative in nature and belongs to the type of recently derived generalized sampling schemes such as the 'no response test' of Luke-Potthast. The range test operates by testing whether it is possible to analytically continue a far field to the exterior of any test domain Omegatest. By intersecting the convex hulls of various test domains we can produce a minimal convex set, the convex scattering support of which must be contained in the convex hull of the support of any scatterer which produces that far field. The convex scattering support is calculated by testing the range of special integral operators for a sampling set of test domains. The numerical results can be used as an approximation for the support of the unknown scatterer. We prove convergence and regularity of the scheme and show numerical examples for sound-soft, sound-hard and medium scatterers. We can apply the range test to non-convex scatterers as well. We can conclude that an Omegatest which passes the range test has a non-empty intersection with the infinity-support (the complement of the unbounded component of the complement of the support) of the true scatterer, but cannot find a minimal set which must be contained therein.

Mobile Sensor Networks for Inspection Tasks in Harsh Industrial Environments

NARCIS (Netherlands)

Mulder, Jacob; Wang, Xinyu; Ferwerda, Franke; Cao, Ming

Recent advances in sensor technology have enabled the fast development of mobile sensor networks operating in various unknown and sometimes hazardous environments. In this paper, we introduce one integrative approach to design, analyze and test distributed control algorithms to coordinate a network

Structure-From for Calibration of a Vehicle Camera System with Non-Overlapping Fields-Of in AN Urban Environment

Science.gov (United States)

Hanel, A.; Stilla, U.

2017-05-01

Vehicle environment cameras observing traffic participants in the area around a car and interior cameras observing the car driver are important data sources for driver intention recognition algorithms. To combine information from both camera groups, a camera system calibration can be performed. Typically, there is no overlapping field-of-view between environment and interior cameras. Often no marked reference points are available in environments, which are a large enough to cover a car for the system calibration. In this contribution, a calibration method for a vehicle camera system with non-overlapping camera groups in an urban environment is described. A-priori images of an urban calibration environment taken with an external camera are processed with the structure-frommotion method to obtain an environment point cloud. Images of the vehicle interior, taken also with an external camera, are processed to obtain an interior point cloud. Both point clouds are tied to each other with images of both image sets showing the same real-world objects. The point clouds are transformed into a self-defined vehicle coordinate system describing the vehicle movement. On demand, videos can be recorded with the vehicle cameras in a calibration drive. Poses of vehicle environment cameras and interior cameras are estimated separately using ground control points from the respective point cloud. All poses of a vehicle camera estimated for different video frames are optimized in a bundle adjustment. In an experiment, a point cloud is created from images of an underground car park, as well as a point cloud of the interior of a Volkswagen test car is created. Videos of two environment and one interior cameras are recorded. Results show, that the vehicle camera poses are estimated successfully especially when the car is not moving. Position standard deviations in the centimeter range can be achieved for all vehicle cameras. Relative distances between the vehicle cameras deviate between

Observações aos prolegômenos da teoria kantiana dos juízos jurídicos a priori em Rechtslehre

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Fábio César Scherer

2010-12-01

Full Text Available In this article the kantian Rechtslehre is interpreted as a critical juridical doctrine, understandable under the critical project – started in Kritik der reinen Vernunft and adapted to the practical field in Kritik der praktischen Vernunft. In particular, it is aimed to highlight, besides the apriority, the systematic character and the search for the completeness of the juridical principles, the use of the solubility of problems theory of the reasoning in general in the prolegomenon of Rechtslehre. The study of this preliminary part is justified in presenting the supreme division of the system according to principals, where it is derived a division of the law doctrine, which determines the object (Gegenstand and, therefore, the field of this particular science and the discussion of the research procedure. Such a priori frame of the Law doctrine is the basis of the following Kantian theory of private law and public law. In a bigger picture, this article can be understood as a renouncement to the idea that the Kantian Rechtslehre does not follow the requirements of the critical philosophy – created by Hermann Cohen (Ethik des reinen Willens, 1904 and detailed by Christian Ritter (Der Rechtsgedanke Kants nach den frühen Quellen, 1971.

Row Reduced Echelon Form for Solving Fully Fuzzy System with Unknown Coefficients

Directory of Open Access Journals (Sweden)

Ghassan Malkawi

2014-08-01

Full Text Available This study proposes a new method for finding a feasible fuzzy solution in positive Fully Fuzzy Linear System (FFLS, where the coefficients are unknown. The fully fuzzy system is transferred to linear system in order to obtain the solution using row reduced echelon form, thereafter; the crisp solution is restricted in obtaining the positive fuzzy solution. The fuzzy solution of FFLS is included crisp intervals, to assign alternative values of unknown entries of fuzzy numbers. To illustrate the proposed method, numerical examples are solved, where the entries of coefficients are unknown in right or left hand side, to demonstrate the contributions in this study.

Atmospheric turbulence profiling with unknown power spectral density

Science.gov (United States)

Helin, Tapio; Kindermann, Stefan; Lehtonen, Jonatan; Ramlau, Ronny

2018-04-01

Adaptive optics (AO) is a technology in modern ground-based optical telescopes to compensate for the wavefront distortions caused by atmospheric turbulence. One method that allows to retrieve information about the atmosphere from telescope data is so-called SLODAR, where the atmospheric turbulence profile is estimated based on correlation data of Shack-Hartmann wavefront measurements. This approach relies on a layered Kolmogorov turbulence model. In this article, we propose a novel extension of the SLODAR concept by including a general non-Kolmogorov turbulence layer close to the ground with an unknown power spectral density. We prove that the joint estimation problem of the turbulence profile above ground simultaneously with the unknown power spectral density at the ground is ill-posed and propose three numerical reconstruction methods. We demonstrate by numerical simulations that our methods lead to substantial improvements in the turbulence profile reconstruction compared to the standard SLODAR-type approach. Also, our methods can accurately locate local perturbations in non-Kolmogorov power spectral densities.

Discrete-time online learning control for a class of unknown nonaffine nonlinear systems using reinforcement learning.

Science.gov (United States)

Yang, Xiong; Liu, Derong; Wang, Ding; Wei, Qinglai

2014-07-01

In this paper, a reinforcement-learning-based direct adaptive control is developed to deliver a desired tracking performance for a class of discrete-time (DT) nonlinear systems with unknown bounded disturbances. We investigate multi-input-multi-output unknown nonaffine nonlinear DT systems and employ two neural networks (NNs). By using Implicit Function Theorem, an action NN is used to generate the control signal and it is also designed to cancel the nonlinearity of unknown DT systems, for purpose of utilizing feedback linearization methods. On the other hand, a critic NN is applied to estimate the cost function, which satisfies the recursive equations derived from heuristic dynamic programming. The weights of both the action NN and the critic NN are directly updated online instead of offline training. By utilizing Lyapunov's direct method, the closed-loop tracking errors and the NN estimated weights are demonstrated to be uniformly ultimately bounded. Two numerical examples are provided to show the effectiveness of the present approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

Vision-based autonomous grasping of unknown piled objects

International Nuclear Information System (INIS)

Johnson, R.K.

1994-01-01

Computer vision techniques have been used to develop a vision-based grasping capability for autonomously picking and placing unknown piled objects. This work is currently being applied to the problem of hazardous waste sorting in support of the Department of Energy's Mixed Waste Operations Program

Non-predictor control of a class of feedforward nonlinear systems with unknown time-varying delays

Science.gov (United States)

Koo, Min-Sung; Choi, Ho-Lim

2016-08-01

This paper generalises the several recent results on the control of feedforward time-delay nonlinear systems. First, in view of system formulation, there are unknown time-varying delays in both states and main control input. Also, the considered nonlinear system has extended feedforward nonlinearities. Second, in view of control solution, our proposed controller is a non-predictor feedback controller whereas smith-predictor type controllers are used in the several existing results. Moreover, our controller does not need any information on the unknown delays except their upper bounds. Thus, our result has certain merits in both system formulation and control solution perspective. The analysis and example are given for clear illustration.

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

Science.gov (United States)

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

48 CFR 52.222-49 - Service Contract Act-Place of Performance Unknown.

Science.gov (United States)

2010-10-01

... 48 Federal Acquisition Regulations System 2 2010-10-01 2010-10-01 false Service Contract Act-Place... Provisions and Clauses 52.222-49 Service Contract Act—Place of Performance Unknown. As prescribed in 22.1006(f), insert the following clause: Service Contract Act—Place of Performance Unknown (MAY 1989) (a...

The Effect of Known-and-Unknown Word Combinations on Intentional Vocabulary Learning

Science.gov (United States)

Kasahara, Kiwamu

2011-01-01

The purpose of this study is to examine whether learning a known-and-unknown word combination is superior in terms of retention and retrieval of meaning to learning a single unknown word. The term "combination" in this study means a two-word collocation of a familiar word and a word that is new to the participants. Following the results of…

STUDY OF SPECTRUM OF PYREXIA OF UNKNOWN ORIGIN PATIENTS IN A TERTIARY CARE HOSPITAL IN COASTAL ANDHRA PRADESH

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Suryaprakasa Rao Salla

2017-09-01

Full Text Available BACKGROUND Pyrexia of Unknown Origin (PUO/Fever of Unknown Origin (FUO was defined in 1961 by Petersdorf RG and Beeson PB2 as the following- A temperature greater than 38.3°C (101°F on several occasions; more than 3 weeks' duration of illness; and failure to reach a diagnosis despite 1 week of inpatient investigation. The aim of the study is to study the spectrum of cases of Pyrexia of Unknown Origin (PUO/Fever of Unknown Origin (FUO in a tertiary care hospital in coastal Andhra Pradesh. MATERIALS AND METHODS All patients with PUO admitted under the Department of General Medicine in the NRI Institute of Medical Sciences (Anil Neerukonda Hospital Sangivalasa, Visakhapatnam, during the period from 1st September, 2016, to 31st August, 2017, and who fulfil inclusion and exclusion criteria of classic PUO defined by Durrack and AC street1 were selected for the study. RESULTS The present study included 34 patients with pyrexia of unknown origin in which the patients’ age ranged from 15 years to 77 years. Most of the cases, 41.2% were in the age group 21 to 40 years and 35.3% in the age group 41 to 60 yrs. This indicates PUO is common in middle age group in our study. CONCLUSION Noninfectious causes like collagen vascular disease and neoplasms are becoming important differential diagnosis. But, in India, infections like tuberculosis, enteric fever are still the most common cause of FUO.

Distribution Agnostic Structured Sparsity Recovery: Algorithms and Applications

KAUST Repository

Masood, Mudassir

2015-01-01

about the data. While Bayesian approaches have their advantages, these methods must have access to a priori statistics. Usually, these statistics are unknown and are often difficult or even impossible to predict. An effective workaround is to assume a

Neurological Autoantibody Prevalence in Epilepsy of Unknown Etiology.

Science.gov (United States)

Dubey, Divyanshu; Alqallaf, Abdulradha; Hays, Ryan; Freeman, Matthew; Chen, Kevin; Ding, Kan; Agostini, Mark; Vernino, Steven

2017-04-01

Autoimmune epilepsy is an underrecognized condition, and its true incidence is unknown. Identifying patients with an underlying autoimmune origin is critical because these patients' condition may remain refractory to conventional antiseizure medications but may respond to immunotherapy. To determine the prevalence of neurological autoantibodies (Abs) among adult patients with epilepsy of unknown etiology. Consecutive patients presenting to neurology services with new-onset epilepsy or established epilepsy of unknown etiology were identified. Serum samples were tested for autoimmune encephalitis Abs as well as thyroperoxidase (TPO) and glutamic acid decarboxylase 65 (GAD65) Abs. An antibody prevalence in epilepsy (APE) score based on clinical characteristics was assigned prospectively. Data were collected from June 1, 2015, to June 1, 2016. Presence of neurological Abs. A score based on clinical characteristics was assigned to estimate the probability of seropositivity prior to antibody test results. Good seizure outcome was estimated on the basis of significant reduction of seizure frequency at the first follow-up or seizure freedom. Of the 127 patients (68 males and 59 females) enrolled in the study, 15 were subsequently excluded after identification of an alternative diagnosis. Serum Abs suggesting a potential autoimmune etiology were detected in 39 (34.8%) cases. More than 1 Ab was detected in 7 patients (6.3%): 3 (2.7%) had TPO-Ab and voltage-gated potassium channel complex (VGKCc) Ab, 2 (1.8%) had GAD65-Ab and VGKCc-Ab, 1 had TPO-Ab and GAD65-Ab, and 1 had anti-Hu Ab and GAD65-Ab. Thirty-two patients (28.6%) had a single Ab marker. Among 112 patients included in the study, 15 (13.4%) had TPO-Ab, 14 (12.5%) had GAD65-Ab, 12 (10.7%) had VGKCc (4 of whom were positive for leucine-rich glioma-inactivated protein 1 [LGI1] Ab), and 4 (3.6%) had N-methyl-D-aspartate receptor (NMDAR) Ab. Even after excluding TPO-Ab and low-titer GAD65-Ab, Abs strongly suggesting an

Using {sup 222}Rn as a tracer of geodynamical processes in underground environments

Energy Technology Data Exchange (ETDEWEB)

Valladares, D.L. [GEA, Instituto de Matemática Aplicada San Luis (IMASL), Universidad Nacional de San Luis, Consejo Nacional de Investigaciones Científicas y Técnicas, Ej. de los Andes 950, D5700HHW San Luis (Argentina); Silva, A.A.R. da [Instituto de Física, Universidade de São Paulo, P.O.Box 66318, 05314-970, São Paulo, SP (Brazil); Serviço Especializado em Engenharia de Segurança e Medicina do Trabalho, Departamento de Saúde, Universidade de São Paulo, Rua da Reitoria, 109, 05508-900, São Paulo, SP (Brazil); Lacerda, T. [Instituto de Física, Universidade Federal Fluminense, Av. Gal Milton Tavares de Souza, s/n" o, Gragoatá, 24210-340, Niterói, RJ (Brazil); Anjos, R.M., E-mail: meigikos@if.uff.br [Instituto de Física, Universidade Federal Fluminense, Av. Gal Milton Tavares de Souza, s/n" o, Gragoatá, 24210-340, Niterói, RJ (Brazil); Rizzotto, M.; Velasco, H.; Rosas, J.P. de [GEA, Instituto de Matemática Aplicada San Luis (IMASL), Universidad Nacional de San Luis, Consejo Nacional de Investigaciones Científicas y Técnicas, Ej. de los Andes 950, D5700HHW San Luis (Argentina); Tognelli, G. [Departamento de Geología, Universidad Nacional de San Luis, Ej. de los Andes 950, D5700HHW San Luis (Argentina); and others

2014-01-01

Radon levels in two old mines in San Luis, Argentina, were measured and analyzed, with the aim to assess the potential use of this radioactive noble gas as a tracer of geological processes in underground environments. La Carolina gold mine and Los Cóndores tungsten mine are today used as tourism mines. CR-39 nuclear track detectors were used for this purpose. Measurements were performed during both winter and summer seasons. The findings show that in these environments, significant radon concentrations are subject to large seasonal fluctuations, due to the strong dependence on natural ventilation with the outside temperature variations. For both mines, higher concentration values of {sup 222}Rn were observed in summer than in winter; with an extreme ratio of 2.5 times between summer and winter seasons for Los Cóndores mine. The pattern of radon transport inside La Carolina mine revealed, contrary to what was believed, that this mine behaves as a system with two entrances located at different levels. However, this feature can only be observed in the winter season, when there is a marked difference between the inside and outside temperatures of the mine. In the case of Los Cóndores mine, the radon concentration pattern distribution is principally established by air current due to chimney-effect in summer and winter seasons. In both cases, the analyses of radon pattern distribution appear as a good method to trace air currents, and then localize unknown ducts, fissures or secondary tunnels in subterranean environments. - Highlights: • {sup 222}Rn levels in two old mines in San Luis, Argentina • CR-39 nuclear track detectors were used for this purpose • higher concentration values of {sup 222}Rn were observed in summer than in winter • radon pattern distribution appear as a good method to trace air currents • it localizes unknown ducts, fissures or secondary tunnels in subterranean environments.

A Nonlinear Unit Root Test in the Presence of an Unknown Break

OpenAIRE

Popp, Stephan

2008-01-01

The Perron test is the most commonly applied procedure to test for a unit root in the presence of a structural break of unknown timing in the trend function. Deriving the Perron-type test regression from an unobserved component model, it is shown that the test regression in fact is nonlinear in coefficient. Taking account of the nonlinearity leads to a test with properties that are exclusively assigned to Schmidt-Phillips LM-type unit root tests.

Local digital control of power electronic converters in a dc microgrid based on a-priori derivation of switching surfaces

Science.gov (United States)

Banerjee, Bibaswan

In power electronic basedmicrogrids, the computational requirements needed to implement an optimized online control strategy can be prohibitive. The work presented in this dissertation proposes a generalized method of derivation of geometric manifolds in a dc microgrid that is based on the a-priori computation of the optimal reactions and trajectories for classes of events in a dc microgrid. The proposed states are the stored energies in all the energy storage elements of the dc microgrid and power flowing into them. It is anticipated that calculating a large enough set of dissimilar transient scenarios will also span many scenarios not specifically used to develop the surface. These geometric manifolds will then be used as reference surfaces in any type of controller, such as a sliding mode hysteretic controller. The presence of switched power converters in microgrids involve different control actions for different system events. The control of the switch states of the converters is essential for steady state and transient operations. A digital memory look-up based controller that uses a hysteretic sliding mode control strategy is an effective technique to generate the proper switch states for the converters. An example dcmicrogrid with three dc-dc boost converters and resistive loads is considered for this work. The geometric manifolds are successfully generated for transient events, such as step changes in the loads and the sources. The surfaces corresponding to a specific case of step change in the loads are then used as reference surfaces in an EEPROM for experimentally validating the control strategy. The required switch states corresponding to this specific transient scenario are programmed in the EEPROM as a memory table. This controls the switching of the dc-dc boost converters and drives the system states to the reference manifold. In this work, it is shown that this strategy effectively controls the system for a transient condition such as step changes

Fault diagnosis of an intelligent hydraulic pump based on a nonlinear unknown input observer

Directory of Open Access Journals (Sweden)

Zhonghai MA

2018-02-01

Full Text Available Hydraulic piston pumps are commonly used in aircraft. In order to improve the viability of aircraft and energy efficiency, intelligent variable pressure pump systems have been used in aircraft hydraulic systems more and more widely. Efficient fault diagnosis plays an important role in improving the reliability and performance of hydraulic systems. In this paper, a fault diagnosis method of an intelligent hydraulic pump system (IHPS based on a nonlinear unknown input observer (NUIO is proposed. Different from factors of a full-order Luenberger-type unknown input observer, nonlinear factors of the IHPS are considered in the NUIO. Firstly, a new type of intelligent pump is presented, the mathematical model of which is established to describe the IHPS. Taking into account the real-time requirements of the IHPS and the special structure of the pump, the mechanism of the intelligent pump and failure modes are analyzed and two typical failure modes are obtained. Furthermore, a NUIO of the IHPS is performed based on the output pressure and swashplate angle signals. With the residual error signals produced by the NUIO, online intelligent pump failure occurring in real-time can be detected. Lastly, through analysis and simulation, it is confirmed that this diagnostic method could accurately diagnose and isolate those typical failure modes of the nonlinear IHPS. The method proposed in this paper is of great significance in improving the reliability of the IHPS. Keywords: Fault diagnosis, Hydraulic piston pump, Model-based, Nonlinear unknown input observer (NUIO, Residual error

On the Implications of A Priori Constraints in Transdimensional Bayesian Inversion for Continental Lithospheric Layering

Science.gov (United States)

Roy, C.; Romanowicz, B. A.

2017-12-01

Monte Carlo methods are powerful approaches to solve nonlinear problems and are becoming very popular in Earth sciences. One reason being that, at first glance, no constraints or explicit regularization of model parameters are required. At second glance, one might realize that regularization is done through a prior. The choice of this prior, however, is subjective, and with its choice, unintended or undesired extra information can be injected into the problem. The principal criticism of Bayesian methods is that the prior can be "tuned" in order to get the expected solution. Consequently, detractors of the Bayesian method could easily argue that the solution is influenced by the form of the prior distribution, which choice is subjective. Hence, models obtained with Monte Carlo methods are still highly debated. Here we investigate the influence of a priori constraints (i.e., fixed crustal discontinuities) on the posterior probability distributions of estimated parameters, that is, vertical polarized shear velocity VSV and radial anisotropy ξ, in a transdimensional Bayesian inversion for continental lithospheric structure. We follow upon the work of Calò et al. (2016), who jointly inverted converted phases (P to S) without deconvolution and surface wave dispersion data, to obtain 1-D radial anisotropic shear wave velocity profiles in the North American craton. We aim at verifying whether the strong lithospheric layering found in the stable part of the craton is robust with respect to artifacts that might be caused by the methodology used. We test the hypothesis that the observed midlithospheric discontinuities result from (1) fixed crustal discontinuities in the reference model and (2) a fixed Vp/Vs ratio. The synthetic tests on two Earth models show that a fixed Vp/Vs ratio does not introduce artificial layering, even if the assumed value is slightly wrong. This is an important finding for real data inversion where the true value is not always available or accurate

Gravity, strings and particles a journey into the unknown

CERN Document Server

Gasperini, Maurizio

2014-01-01

New fundamental forces of Nature? New forms of "dark'' energy? Signals from epochs preceding the Big Bang? Is our space-time unique? Only a joint study of the three topics examined in this book – gravity, strings and particles – may provide answers to these questions. Such a study may also provide the key to solving one of the most fascinating mysteries of modern science, namely: Besides time and the three spatial dimensions, how many other dimensions exist in our universe? The book is primarily addressed to readers who do not necessarily have a specific background in physics but are nevertheless interested in discovering the originality and the possible implications of some of the amazing ideas in modern theoretical physics. The emphasis is on conveying ideas rather than explaining formulas, focusing not on what is known but -- mainly -- on what is still unknown. Many parts of the book are devoted to fundamental theoretical models and results which are potentially highly relevant for a deeper understand...

Potentials of ionizing radiation in reducing hazards to man and environment

Energy Technology Data Exchange (ETDEWEB)

Mullie, W C; Van Laerhoven, M J.A.M.; Kroes, R

1991-07-01

The main goal of the title study was to compare a relevant number of conventional processes and technologies for a range of uses with the application of ionizing radiation technology. Special emphasis is given to the hazardous effects of contemporary processes and chemicals on man and environment and to the potential role of the radiation processing technology, gamma irradiation in particular, in reducing these hazards. Based on their quantities and on (eco)toxicological criteria, four fields of application were identified a priori as potentially of interest for radiation processing. These fields of application are food preservation, sterilization and sanitization of pharmaceuticals and cosmetics, waste water and drinking water disinfection, and disinfection of sewage sludge and infectious hospital waste. Other fields of application as mentioned above are discussed in a more general matter. 12 figs., 31 tabs., 4 apps., refs.

Optimising measurement of health-related characteristics of the built environment: Comparing data collected by foot-based street audits, virtual street audits and routine secondary data sources.

Science.gov (United States)

Pliakas, Triantafyllos; Hawkesworth, Sophie; Silverwood, Richard J; Nanchahal, Kiran; Grundy, Chris; Armstrong, Ben; Casas, Juan Pablo; Morris, Richard W; Wilkinson, Paul; Lock, Karen

2017-01-01

The role of the neighbourhood environment in influencing health behaviours continues to be an important topic in public health research and policy. Foot-based street audits, virtual street audits and secondary data sources are widespread data collection methods used to objectively measure the built environment in environment-health association studies. We compared these three methods using data collected in a nationally representative epidemiological study in 17 British towns to inform future development of research tools. There was good agreement between foot-based and virtual audit tools. Foot based audits were superior for fine detail features. Secondary data sources measured very different aspects of the local environment that could be used to derive a range of environmental measures if validated properly. Future built environment research should design studies a priori using multiple approaches and varied data sources in order to best capture features that operate on different health behaviours at varying spatial scales. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

A novel KFCM based fault diagnosis method for unknown faults in satellite reaction wheels.

Science.gov (United States)

Hu, Di; Sarosh, Ali; Dong, Yun-Feng

2012-03-01

Reaction wheels are one of the most critical components of the satellite attitude control system, therefore correct diagnosis of their faults is quintessential for efficient operation of these spacecraft. The known faults in any of the subsystems are often diagnosed by supervised learning algorithms, however, this method fails to work correctly when a new or unknown fault occurs. In such cases an unsupervised learning algorithm becomes essential for obtaining the correct diagnosis. Kernel Fuzzy C-Means (KFCM) is one of the unsupervised algorithms, although it has its own limitations; however in this paper a novel method has been proposed for conditioning of KFCM method (C-KFCM) so that it can be effectively used for fault diagnosis of both known and unknown faults as in satellite reaction wheels. The C-KFCM approach involves determination of exact class centers from the data of known faults, in this way discrete number of fault classes are determined at the start. Similarity parameters are derived and determined for each of the fault data point. Thereafter depending on the similarity threshold each data point is issued with a class label. The high similarity points fall into one of the 'known-fault' classes while the low similarity points are labeled as 'unknown-faults'. Simulation results show that as compared to the supervised algorithm such as neural network, the C-KFCM method can effectively cluster historical fault data (as in reaction wheels) and diagnose the faults to an accuracy of more than 91%. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

High frequency sonar variability in littoral environments: Irregular particles and bubbles

Science.gov (United States)

Richards, Simon D.; Leighton, Timothy G.; White, Paul R.

2002-11-01

Littoral environments may be characterized by high concentrations of suspended particles. Such suspensions contribute to attenuation through visco-inertial absorption and scattering and may therefore be partially responsible for the observed variability in high frequency sonar performance in littoral environments. Microbubbles which are prevalent in littoral waters also contribute to volume attenuation through radiation, viscous and thermal damping and cause dispersion. The attenuation due to a polydisperse suspension of particles with depth-dependent concentration has been included in a sonar model. The effects of a depth-dependent, polydisperse population of microbubbles on attenuation, sound speed and volume reverberation are also included. Marine suspensions are characterized by nonspherical particles, often plate-like clay particles. Measurements of absorption in dilute suspensions of nonspherical particles have shown disagreement with predictions of spherical particle models. These measurements have been reanalyzed using three techniques for particle sizing: laser diffraction, gravitational sedimentation, and centrifugal sedimentation, highlighting the difficulty of characterizing polydisperse suspensions of irregular particles. The measurements have been compared with predictions of a model for suspensions of oblate spheroids. Excellent agreement is obtained between this model and the measurements for kaolin particles, without requiring any a priori knowledge of the measurements.

Inverse estimation for the unknown frost geometry on the external wall of a forced-convection pipe

International Nuclear Information System (INIS)

Chen, W.-L.; Yang, Y.-C.

2009-01-01

In this study, a conjugate gradient method based inverse algorithm is applied to estimate the unknown frost-layer boundary profile on the external wall of a pipe system using temperature measurements. It is assumed that no prior information is available on the functional form of the unknown profile; hence the procedure is classified as the function estimation in inverse calculation. The temperature data obtained from the direct problem are used to simulate the temperature measurements. The accuracy of the inverse analysis is examined by using simulated exact and inexact temperature measurements. Results show that an excellent estimation on boundary profile can be obtained for the test case considered in this study.

Boundary conditions for free surface inlet and outlet problems

KAUST Repository

Taroni, M.; Breward, C. J. W.; Howell, P. D.; Oliver, J. M.

2012-01-01

We investigate and compare the boundary conditions that are to be applied to free-surface problems involving inlet and outlets of Newtonian fluid, typically found in coating processes. The flux of fluid is a priori known at an inlet, but unknown

High Precision Fast Projective Synchronization for Chaotic Systems with Unknown Parameters

Science.gov (United States)

Nian, Fuzhong; Wang, Xingyuan; Lin, Da; Niu, Yujun

2013-08-01

A high precision fast projective synchronization method for chaotic systems with unknown parameters was proposed by introducing optimal matrix. Numerical simulations indicate that the precision be improved about three orders compared with other common methods under the same condition of software and hardware. Moreover, when average error is less than 10-3, the synchronization speed is 6500 times than common methods, the iteration needs only 4 times. The unknown parameters also were identified rapidly. The theoretical analysis and proof also were given.

Quantifying road dust resuspension in urban environment by Multilinear Engine: A comparison with PMF2

Science.gov (United States)

Amato, F.; Pandolfi, M.; Escrig, A.; Querol, X.; Alastuey, A.; Pey, J.; Perez, N.; Hopke, P. K.

Atmospheric PM pollution from traffic comprises not only direct emissions but also non-exhaust emissions because resuspension of road dust that can produce high human exposure to heavy metals, metalloids, and mineral matter. A key task for establishing mitigation or preventive measures is estimating the contribution of road dust resuspension to the atmospheric PM mixture. Several source apportionment studies, applying receptor modeling at urban background sites, have shown the difficulty in identifying a road dust source separately from other mineral sources or vehicular exhausts. The Multilinear Engine (ME-2) is a computer program that can solve the Positive Matrix Factorization (PMF) problem. ME-2 uses a programming language permitting the solution to be guided toward some possible targets that can be derived from a priori knowledge of sources (chemical profile, ratios, etc.). This feature makes it especially suitable for source apportionment studies where partial knowledge of the sources is available. In the present study ME-2 was applied to data from an urban background site of Barcelona (Spain) to quantify the contribution of road dust resuspension to PM 10 and PM 2.5 concentrations. Given that recently the emission profile of local resuspended road dust was obtained (Amato, F., Pandolfi, M., Viana, M., Querol, X., Alastuey, A., Moreno, T., 2009. Spatial and chemical patterns of PM 10 in road dust deposited in urban environment. Atmospheric Environment 43 (9), 1650-1659), such a priori information was introduced in the model as auxiliary terms of the object function to be minimized by the implementation of the so-called "pulling equations". ME-2 permitted to enhance the basic PMF solution (obtained by PMF2) identifying, beside the seven sources of PMF2, the road dust source which accounted for 6.9 μg m -3 (17%) in PM 10, 2.2 μg m -3 (8%) of PM 2.5 and 0.3 μg m -3 (2%) of PM 1. This reveals that resuspension was responsible of the 37%, 15% and 3% of total

Taming the unknown a history of algebra from antiquity to the early twentieth century

CERN Document Server

Katz, Victor J

2014-01-01

What is algebra? For some, it is an abstract language of x's and y's. For mathematics majors and professional mathematicians, it is a world of axiomatically defined constructs like groups, rings, and fields. Taming the Unknown considers how these two seemingly different types of algebra evolved and how they relate. Victor Katz and Karen Parshall explore the history of algebra, from its roots in the ancient civilizations of Egypt, Mesopotamia, Greece, China, and India, through its development in the medieval Islamic world and medieval and early modern Europe, to its modern form in the early twentieth century. Defining algebra originally as a collection of techniques for determining unknowns, the authors trace the development of these techniques from geometric beginnings in ancient Egypt and Mesopotamia and classical Greece. They show how similar problems were tackled in Alexandrian Greece, in China, and in India, then look at how medieval Islamic scholars shifted to an algorithmic stage, which was further dev...

Content-Based Multimedia Retrieval in the Presence of Unknown User Preferences

DEFF Research Database (Denmark)

Beecks, Christian; Assent, Ira; Seidl, Thomas

2011-01-01

Content-based multimedia retrieval requires an appropriate similarity model which reflects user preferences. When these preferences are unknown or when the structure of the data collection is unclear, retrieving the most preferable objects the user has in mind is challenging, as the notion...... address the problem of content-based multimedia retrieval in the presence of unknown user preferences. Our idea consists in performing content-based retrieval by considering all possibilities in a family of similarity models simultaneously. To this end, we propose a novel content-based retrieval approach...

Unknown quantum states: The quantum de Finetti representation

International Nuclear Information System (INIS)

Caves, Carlton M.; Fuchs, Christopher A.; Schack, Ruediger

2002-01-01

We present an elementary proof of the quantum de Finetti representation theorem, a quantum analog of de Finetti's classical theorem on exchangeable probability assignments. This contrasts with the original proof of Hudson and Moody [Z. Wahrschein. verw. Geb. 33, 343 (1976)], which relies on advanced mathematics and does not share the same potential for generalization. The classical de Finetti theorem provides an operational definition of the concept of an unknown probability in Bayesian probability theory, where probabilities are taken to be degrees of belief instead of objective states of nature. The quantum de Finetti theorem, in a closely analogous fashion, deals with exchangeable density-operator assignments and provides an operational definition of the concept of an ''unknown quantum state'' in quantum-state tomography. This result is especially important for information-based interpretations of quantum mechanics, where quantum states, like probabilities, are taken to be states of knowledge rather than states of nature. We further demonstrate that the theorem fails for real Hilbert spaces and discuss the significance of this point

A Lightweight Intelligent Virtual Cinematography System for Machinima Production

Science.gov (United States)

2007-01-01

portmanteau of machine and cinema , machinima refers to the innovation of leveraging video game technology to greatly ease the creation of computer...selecting camera angles to capture the action of an a priori unknown script as aesthetically appropriate cinema . There are a number of challenges therein...Proc. of the 4th International Conf. on Autonomous Agents. Young, R.M. and Riedl, M.O. 2003. Towards an Architecture for Intelligent Control of Narrative in Interactive Virtual Worlds. In Proc. of IUI 2003.

Teleportation of Unknown Superpositions of Collective Atomic Coherent States

Institute of Scientific and Technical Information of China (English)

ZHENG ShiBiao

2001-01-01

We propose a scheme to teleport an unknown superposition of two atomic coherent states with different phases. Our scheme is based on resonant and dispersive atom-field interaction. Our scheme provides a possibility of teleporting macroscopic superposition states of many atoms first time.``

Inferring Drosophila gap gene regulatory network: Pattern analysis of simulated gene expression profiles and stability analysis

NARCIS (Netherlands)

Fomekong-Nanfack, Y.; Postma, M.; Kaandorp, J.A.

2009-01-01

Background: Inference of gene regulatory networks (GRNs) requires accurate data, a method to simulate the expression patterns and an efficient optimization algorithm to estimate the unknown parameters. Using this approach it is possible to obtain alternative circuits without making any a priori

Human-Robot Teams for Unknown and Uncertain Environments

Science.gov (United States)

Fong, Terry

2015-01-01

Man-robot interaction is the study of interactions between humans and robots. It is often referred as HRI by researchers. Human-robot interaction is a multidisciplinary field with contributions from human-computer interaction, artificial intelligence.

Bilateral teleoperation control to improve transparency in stiff environment with time delay

Directory of Open Access Journals (Sweden)

M. Azadegan

2014-09-01

Full Text Available This paper proposes a new bilateral control scheme to ensure both transparency and robust stability under unknown constant time delay in stiff environment. Furthermore, this method guaranties suitable performance and robust stability when transition occurs between soft and stiff environments. This framework is composed of an adaptive sliding mode controller and an adaptive impedance controller, where online estimation of the environment impedance is performed, and then used as the desired impedance at the master side. Numerical simulations are provided to verify the theoretical results under different conditions, such as constant and time-varying delay, obstructed environment and transitioning between soft and stiff environment. Afterwards, comparison with a recent work is addressed.

A priori Considerations When Conducting High-Throughput Amplicon-Based Sequence Analysis

Directory of Open Access Journals (Sweden)

Aditi Sengupta

2016-03-01

Full Text Available Amplicon-based sequencing strategies that include 16S rRNA and functional genes, alongside “meta-omics” analyses of communities of microorganisms, have allowed researchers to pose questions and find answers to “who” is present in the environment and “what” they are doing. Next-generation sequencing approaches that aid microbial ecology studies of agricultural systems are fast gaining popularity among agronomy, crop, soil, and environmental science researchers. Given the rapid development of these high-throughput sequencing techniques, researchers with no prior experience will desire information about the best practices that can be used before actually starting high-throughput amplicon-based sequence analyses. We have outlined items that need to be carefully considered in experimental design, sampling, basic bioinformatics, sequencing of mock communities and negative controls, acquisition of metadata, and in standardization of reaction conditions as per experimental requirements. Not all considerations mentioned here may pertain to a particular study. The overall goal is to inform researchers about considerations that must be taken into account when conducting high-throughput microbial DNA sequencing and sequences analysis.

Learning Unknown Structure in CRFs via Adaptive Gradient Projection Method

Directory of Open Access Journals (Sweden)

Wei Xue

2016-08-01

Full Text Available We study the problem of fitting probabilistic graphical models to the given data when the structure is not known. More specifically, we focus on learning unknown structure in conditional random fields, especially learning both the structure and parameters of a conditional random field model simultaneously. To do this, we first formulate the learning problem as a convex minimization problem by adding an l_2-regularization to the node parameters and a group l_1-regularization to the edge parameters, and then a gradient-based projection method is proposed to solve it which combines an adaptive stepsize selection strategy with a nonmonotone line search. Extensive simulation experiments are presented to show the performance of our approach in solving unknown structure learning problems.

Adaptive Tracking and Obstacle Avoidance Control for Mobile Robots with Unknown Sliding

Directory of Open Access Journals (Sweden)

Mingyue Cui

2012-11-01

Full Text Available An adaptive control approach is proposed for trajectory tracking and obstacle avoidance for mobile robots with consideration given to unknown sliding. A kinematic model of mobile robots is established in this paper, in which both longitudinal and lateral sliding are considered and processed as three time-varying parameters. A sliding model observer is introduced to estimate the sliding parameters online. A stable tracking control law for this nonholonomic system is proposed to compensate the unknown sliding effect. From Lyapunov-stability analysis, it is proved, regardless of unknown sliding, that tracking errors of the controlled closed-loop system are asymptotically stable, the tracking errors converge to zero outside the obstacle detection region and obstacle avoidance is guaranteed inside the obstacle detection region. The efficiency and robustness of the proposed control system are verified by simulation results.

Keratosis of unknown significance and leukoplakia: a preliminary study.

Science.gov (United States)

Woo, Sook-Bin; Grammer, Rebecca L; Lerman, Mark A

2014-12-01

The objectives were to (1) determine the frequency of specific diagnoses in a series of white lesions, and (2) describe the nature of keratotic lesions that are neither reactive nor dysplastic. White lesions were analyzed and diagnosed as reactive keratoses, dysplastic/malignant, or keratoses of unknown significance (KUS). Of the 1251 specimens that were evaluated, 703 met criteria for inclusion, and approximately 75% were reactive, 10% dysplastic/malignant, and 14% KUS. Excluding reactive keratoses, 43% were dysplastic/malignant and 57% were KUS. Reactive keratoses were the most common white lesions followed by lichen planus. Dysplastic/malignant lesions constituted almost 50% of all true leukoplakias. KUS constituted the remaining cases and do not show typical reactive histopathology as well as clear dysplasia. They may represent evolving or devolving reactive keratoses but may also represent the very earliest dysplasia phenotype. Clinical findings may be helpful in differentiating the two. Copyright © 2014 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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.

Streamlined structure elucidation of an unknown compound in a pigment formulation.

Science.gov (United States)

Yüce, Imanuel; Morlock, Gertrud E

2016-10-21

A fast and reliable quality control is important for ink manufacturers to ensure a constant production grade of mixtures and chemical formulations, and unknown components attract their attention. Structure elucidating techniques seem time-consuming in combination with column-based methods, but especially the low solubility of pigment formulations is challenging the analysis. In contrast, layer chromatography is more tolerant with regard to pigment particles. One PLC plate for NMR and FTIR analyses and one HPTLC plate for recording of high resolution mass spectra, MS/MS spectra and for gathering information on polarity and spectral properties were needed to characterize a structure, exemplarily shown for an unknown component in pigment Red 57:1 to be 3-hydroxy-2-naphtoic acid. A preparative layer chromatography (PLC) workflow was developed that used an Automated Multiple Development 2 (AMD 2) system. The 0.5-mm PLC plate could still be operated in the AMD 2 system and allowed a smooth switch from the analytical to the preparative gradient separation. Through automated gradient development and the resulting focusing of bands, the sharpness of the PLC bands was improved. For NMR, the necessary high load of the target compound on the PLC plate was achieved via a selective solvent extraction that discriminated the polar sample matrix and thus increased the application volume of the extract that could maximally be applied without overloading. By doing so, the yield for NMR analysis was improved by a factor of 9. The effectivity gain through a simple, but thoroughly chosen extraction solvent is often overlooked, and for educational purpose, it was clearly illustrated and demonstrated by an extended solvent screening. Thus, PLC using an automated gradient development after a selective extraction was proven to be a new powerful combination for structural elucidation by NMR. Copyright © 2016 Elsevier B.V. All rights reserved.

High-order sliding mode observer for fractional commensurate linear systems with unknown input

KAUST Repository

Belkhatir, Zehor; Laleg-Kirati, Taous-Meriem

2017-01-01

In this paper, a high-order sliding mode observer (HOSMO) is proposed for the joint estimation of the pseudo-state and the unknown input of fractional commensurate linear systems with single unknown input and a single output. The convergence of the proposed observer is proved using a Lyapunov-based approach. In addition, an enhanced variant of the proposed fractional-HOSMO is introduced to avoid the peaking phenomenon and thus to improve the estimation results in the transient phase. Simulation results are provided to illustrate the performance of the proposed fractional observer in both noise-free and noisy cases. The effect of the observer’s gains on the estimated pseudo-state and unknown input is also discussed.

High-order sliding mode observer for fractional commensurate linear systems with unknown input

KAUST Repository

Belkhatir, Zehor

2017-05-20

In this paper, a high-order sliding mode observer (HOSMO) is proposed for the joint estimation of the pseudo-state and the unknown input of fractional commensurate linear systems with single unknown input and a single output. The convergence of the proposed observer is proved using a Lyapunov-based approach. In addition, an enhanced variant of the proposed fractional-HOSMO is introduced to avoid the peaking phenomenon and thus to improve the estimation results in the transient phase. Simulation results are provided to illustrate the performance of the proposed fractional observer in both noise-free and noisy cases. The effect of the observer’s gains on the estimated pseudo-state and unknown input is also discussed.

Estimation of the false discovery proportion with unknown dependence.

Science.gov (United States)

Fan, Jianqing; Han, Xu

2017-09-01

Large-scale multiple testing with correlated test statistics arises frequently in many scientific research. Incorporating correlation information in approximating false discovery proportion has attracted increasing attention in recent years. When the covariance matrix of test statistics is known, Fan, Han & Gu (2012) provided an accurate approximation of False Discovery Proportion (FDP) under arbitrary dependence structure and some sparsity assumption. However, the covariance matrix is often unknown in many applications and such dependence information has to be estimated before approximating FDP. The estimation accuracy can greatly affect FDP approximation. In the current paper, we aim to theoretically study the impact of unknown dependence on the testing procedure and establish a general framework such that FDP can be well approximated. The impacts of unknown dependence on approximating FDP are in the following two major aspects: through estimating eigenvalues/eigenvectors and through estimating marginal variances. To address the challenges in these two aspects, we firstly develop general requirements on estimates of eigenvalues and eigenvectors for a good approximation of FDP. We then give conditions on the structures of covariance matrices that satisfy such requirements. Such dependence structures include banded/sparse covariance matrices and (conditional) sparse precision matrices. Within this framework, we also consider a special example to illustrate our method where data are sampled from an approximate factor model, which encompasses most practical situations. We provide a good approximation of FDP via exploiting this specific dependence structure. The results are further generalized to the situation where the multivariate normality assumption is relaxed. Our results are demonstrated by simulation studies and some real data applications.

Unknown input observer based detection of sensor faults in a wind turbine

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Stoustrup, Jakob

2010-01-01

In this paper an unknown input observer is designed to detect three different sensor fault scenarios in a specified bench mark model for fault detection and accommodation of wind turbines. In this paper a subset of faults is dealt with, it are faults in the rotor and generator speed sensors as well...... as a converter sensor fault. The proposed scheme detects the speed sensor faults in question within the specified requirements given in the bench mark model, while the converter fault is detected but not within the required time to detect....

Identification of CJC-1295, a growth-hormone-releasing peptide, in an unknown pharmaceutical preparation.

Science.gov (United States)

Henninge, John; Pepaj, Milaim; Hullstein, Ingunn; Hemmersbach, Peter

2010-01-01

Several peptide drugs are being manufactured illicitly, and in some cases they are being made available to the public before entering or completing clinical trials. At the request of Norwegian police and customs authorities, unknown pharmaceutical preparations suspected to contain peptide drugs are regularly subjected to analysis. In 2009, an unknown pharmaceutical preparation was submitted for analysis by liquid chromatography-high resolution tandem mass spectrometry (LC-HRMS/MS). The preparation was found to contain a 29 amino acid peptide with a C-terminal amide function. Based on the interpretation of mass spectrometric data, an amino acid sequence was proposed. The sequence is consistent with a peptide currently marketed under the name CJC-1295. CJC-1295 is a releasing factor for growth hormone and is therefore considered a Prohibited Substance under Section S2 of the WADA Prohibited List. This substance has potential performance-enhancing effects, it is readily available, and there is reason to believe that it is being used within the bodybuilding community. Copyright © 2010 John Wiley & Sons, Ltd.

Extensive screening for primary tumor is redundant in melanoma of unknown primary

DEFF Research Database (Denmark)

Tos, Tina; Klyver, Helle; Drzewiecki, Krzysztof T

2011-01-01

For decades, patients in our institution with metastastic melanoma of unknown primary have been subjected to extensive examinations in search of the primary tumor. This retrospective study questions the results, and thus the feasibility of these examinations. Of 103 patients diagnosed with unknow......, for patients referred with metastastic melanoma of unknown primary, we recommend that a detailed history is obtained, and a standard physical examination performed, in addition to a histopathological review and CT/PET for staging....

The unknown-unknowns: Revealing the hidden insights in massive biomedical data using combined artificial intelligence and knowledge networks

Directory of Open Access Journals (Sweden)

Chris Yoo

2017-12-01

Full Text Available Genomic data is estimated to be doubling every seven months with over 2 trillion bases from whole genome sequence studies deposited in Genbank in just the last 15 years alone. Recent advances in compute and storage have enabled the use of artificial intelligence techniques in areas such as feature recognition in digital pathology and chemical synthesis for drug development. To apply A.I. productively to multidimensional data such as cellular processes and their dysregulation, the data must be transformed into a structured format, using prior knowledge to create contextual relationships and hierarchies upon which computational analysis can be performed. Here we present the organization of complex data into hypergraphs that facilitate the application of A.I. We provide an example use case of a hypergraph containing hundreds of biological data values and the results of several classes of A.I. algorithms applied in a popular compute cloud. While multiple, biologically insightful correlations between disease states, behavior, and molecular features were identified, the insights of scientific import were revealed only when exploration of the data included visualization of subgraphs of represented knowledge. The results suggest that while machine learning can identify known correlations and suggest testable ones, the greater probability of discovering unexpected relationships between seemingly independent variables (unknown-unknowns requires a context-aware system – hypergraphs that impart biological meaning in nodes and edges. We discuss the implications of a combined hypergraph-A.I. analysis approach to multidimensional data and the pre-processing requirements for such a system.

Determinants of use and non-use of a web-based communication system in cerebral palsy care: evaluating the association between professionals' system use and their a priori expectancies and background

Directory of Open Access Journals (Sweden)

van Harten Wim H

2011-06-01

Full Text Available Abstract Background Previously we described parents' and professionals' experiences with a web-based communication system in a 6-month pilot in three Dutch cerebral palsy care settings. We found that half of the participating professionals had not used the system, and of those who had used the system one third had used it only once. The present study aimed to evaluate whether professionals' system use was associated with their a priori expectancies and background. Methods Professionals who had not used the system (n = 54 were compared with professionals who had used the system more than once (n = 46 on the basis of their questionnaire responses before the pilot, their affiliation and the number of patients which they represented in the study. The questionnaire items comprised professionals' expectancies regarding the system's performance and ease of use, as well as the expected time availability and integration into daily care practice. Results Overall, users had higher a priori expectancies than non-users. System use was associated with expected ease of use (p = .046 and time availability (p = .005: 50% of the users (vs. 31% of the non-users expected that the system would be easy to use and 93% of the users (vs. 72% of the non-users expected that they would be able to reserve a time slot each week for responding to submitted questions. With respect to professionals' affiliation, system use was associated with professionals' institution (p = .003 and discipline (p = .001, with more (para- medical professionals among users (93% vs. 63% among non-users, and more education professionals among non-users (37% vs. 7% among users. In addition, users represented more patients (mean 2, range 1-8 than non-users (mean 1.1, range 1-2 (p = .000. Conclusions Professionals' system use was associated with expected ease of use and time availability, professionals' affiliation and the number of represented patients, while no association was found with expected

Quadrotor Control in the Presence of Unknown Mass Properties

Science.gov (United States)

Duivenvoorden, Rikky Ricardo Petrus Rufino

Quadrotor UAVs are popular due to their mechanical simplicity, as well as their capability to hover and vertically take-off and land. As applications diversify, quadrotors are increasingly required to operate under unknown mass properties, for example as a multirole sensor platform or for package delivery operations. The work presented here consists of the derivation of a generalized quadrotor dynamic model without the typical simplifying assumptions on the first and second moments of mass. The maximum payload capacity of a quadrotor in hover, and the observability of the unknown mass properties are discussed. A brief introduction of L1 adaptive control is provided, and three different L 1 adaptive controllers were designed for the Parrot AR.Drone quadrotor. Their tracking and disturbance rejection performance was compared to the baseline nonlinear controller in experiments. Finally, the results of the combination of L1 adaptive control with iterative learning control are presented, showing high performance trajectory tracking under uncertainty.

Intrathecal immunoglobulin synthesis in patients with symptomatic epilepsy and epilepsy of unknown etiology ('cryptogenic').

Science.gov (United States)

Fauser, S; Soellner, C; Bien, C G; Tumani, H

2017-09-01

To compare the frequency of intrathecal immunoglobulin (Ig) synthesis in patients with symptomatic epilepsy and epilepsy of unknown etiology ('cryptogenic'). Patients with epileptic (n = 301) and non-epileptic (n = 10) seizures were retrospectively screened for autochthonous intrathecal Ig synthesis and oligoclonal bands (OCBs) in the cerebrospinal fluid. Intrathecal IgG/OCBs were detected in 8% of patients with epilepsies of unknown etiology, 5% of patients with first seizures of unknown cause and 0-4% of patients with epilepsy due to brain tumors, cerebrovascular disease or other etiologies. Intrathecal IgG/OCBs were not seen in patients with psychogenic seizures. Identical OCBs in serum and cerebrospinal fluid were more common in all patient groups (10-40% depending on underlying etiology). Intrathecal IgG synthesis/OCBs were observed slightly more frequently in patients with 'cryptogenic' epilepsy and with first seizures of unknown etiology than in other patient groups. However, this remained an infrequent finding and thus we could not confirm humoral immunity as a leading disease mechanism in patients with epilepsy in general or with unknown etiology in particular. © 2017 EAN.

Multiple analysis of an unknown optical multilayer coating

International Nuclear Information System (INIS)

Dobrowolski, J.A.; Ho, F.C.; Waldorf, A.

1985-01-01

Results are given of the analysis at five different laboratories of an unknown optical multilayer coating. In all, eleven different analytical and laboratory techniques were applied to the problem. The multilayer nominally consisted of three dielectric and two metallic layers. It was demonstrated convincingly that with present day techniques it is possible to determine the basic structure of such a coating

F-18-FDG PET/CT in inflammation of unknown origin : a cost-effectiveness pilot-study

NARCIS (Netherlands)

Balink, H.; Tan, S. S.; Veeger, N. J. G. M.; Holleman, F.; van Eck-Smit, B. L. F.; Bennink, R. J.; Verberne, H. J.

Purpose Patients with increased inflammatory parameters, nonspecific signs and symptoms without fever and without a diagnosis after a variety of diagnostic procedures are a diagnostic dilemma and are referred to as having inflammation of unknown origin (IUO). The objective of this pilot study was to

Community-acquired purulent meningitis of unknown etiology. A continuing problem.

Science.gov (United States)

Geiseler, P J; Nelson, K E; Levin, S

1981-12-01

The clinical features and hospital course of 132 patients with purulent meningitis of unknown etiology (PMU) were compared with those of 1,032 patients with proven bacterial meningitis; all patients were admitted to a major referral center for meningitis treatment between 1954 and 1976. Most patients had no major underlying illnesses. Patients with PMU were more frequently older, "pretreated" with antibiotics, had longer duration of symptoms, evidenced less marked alterations of mental status, and died later in the hospitalization; however, the mortality and frequency of neurologic complications were similar to those in patients with bacterial meningitis. Patients with PMU who also had hemorrhagic rashes had fewer neurologic complications and none died; these patients comprised a distinct group in terms of better prognosis. New methods for rapid diagnosis of bacterial meningitis have only partially resolved the diagnostic dilemma of PMU.

Marked improvement of vulvovaginitis of unknown origin in a pediatric patient--case report.

Science.gov (United States)

Check, J H; Cohen, R

2014-01-01

To present a novel therapy for pediatric vulvovaginitis. An eight-year-old girl with persistent severe vulvovaginitis of unknown origin also complained of unexplained weight gain and sudden academic difficulties. She was treated with dextroamphetamine sulfate. She not only showed very quick and excellent relief from her vulvovaginitis but she also lost weight and improved her mentality. Sympathomimetic amine therapy may benefit pediatric vulvovaginitis when an infectious cause cannot be ascertained.

Carcinoma of Unknown Primary Treatment (PDQ®)—Patient Version

Science.gov (United States)

Carcinoma of unknown primary (CUP), treatment can include surgery, radiation therapy, chemotherapy, or hormone therapy. Get detailed information about the diagnosis and treatment of CUP in this expert-reviewed summary.

Bottom-up learning of hierarchical models in a class of deterministic POMDP environments

Directory of Open Access Journals (Sweden)

Itoh Hideaki

2015-09-01

Full Text Available The theory of partially observable Markov decision processes (POMDPs is a useful tool for developing various intelligent agents, and learning hierarchical POMDP models is one of the key approaches for building such agents when the environments of the agents are unknown and large. To learn hierarchical models, bottom-up learning methods in which learning takes place in a layer-by-layer manner from the lowest to the highest layer are already extensively used in some research fields such as hidden Markov models and neural networks. However, little attention has been paid to bottom-up approaches for learning POMDP models. In this paper, we present a novel bottom-up learning algorithm for hierarchical POMDP models and prove that, by using this algorithm, a perfect model (i.e., a model that can perfectly predict future observations can be learned at least in a class of deterministic POMDP environments

Spacecraft Internal Acoustic Environment Modeling

Science.gov (United States)

Chu, SShao-sheng R.; Allen, Christopher S.

2009-01-01

Acoustic modeling can be used to identify key noise sources, determine/analyze sub-allocated requirements, keep track of the accumulation of minor noise sources, and to predict vehicle noise levels at various stages in vehicle development, first with estimates of noise sources, later with experimental data. In FY09, the physical mockup developed in FY08, with interior geometric shape similar to Orion CM (Crew Module) IML (Interior Mode Line), was used to validate SEA (Statistical Energy Analysis) acoustic model development with realistic ventilation fan sources. The sound power levels of these sources were unknown a priori, as opposed to previous studies that RSS (Reference Sound Source) with known sound power level was used. The modeling results were evaluated based on comparisons to measurements of sound pressure levels over a wide frequency range, including the frequency range where SEA gives good results. Sound intensity measurement was performed over a rectangular-shaped grid system enclosing the ventilation fan source. Sound intensities were measured at the top, front, back, right, and left surfaces of the and system. Sound intensity at the bottom surface was not measured, but sound blocking material was placed tinder the bottom surface to reflect most of the incident sound energy back to the remaining measured surfaces. Integrating measured sound intensities over measured surfaces renders estimated sound power of the source. The reverberation time T6o of the mockup interior had been modified to match reverberation levels of ISS US Lab interior for speech frequency bands, i.e., 0.5k, 1k, 2k, 4 kHz, by attaching appropriately sized Thinsulate sound absorption material to the interior wall of the mockup. Sound absorption of Thinsulate was modeled in three methods: Sabine equation with measured mockup interior reverberation time T60, layup model based on past impedance tube testing, and layup model plus air absorption correction. The evaluation/validation was

Teleportation of an Unknown Atomic State via Adiabatic Passage

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

We propose a scheme for teleporting an unknown atomic state via adiabatic passage. Taking advantage of adiabatic passage, the atom has no probability of being excited and thus the atomic spontaneous emission is suppressed.We also show that the fidelity can reach 1 under certain condition.

Os nanomateriais e a questão ambiental Nanomaterials and the environment

Directory of Open Access Journals (Sweden)

Matheus P. Paschoalino

2010-01-01

Full Text Available The increasing use of nanomaterials in several products in different areas such as electronics, cosmetics, food and drugs has attracted the attention of the scientific community due to unknown properties of these materials, such as the life cycle and the interaction with receptor organisms once they reach the environment. In this context, the present work shows an updated scenario of nanomaterials applications, characterization methods and toxicity evaluation, also addressing important aspects related to the development and application of nanotechnology under the environmental point of view.

[Focal myositis: An unknown disease].

Science.gov (United States)

Gallay, L; Streichenberger, N; Benveniste, O; Allenbach, Y

2017-10-01

Focal myositis are inflammatory muscle diseases of unknown origin. At the opposite from the other idiopathic inflammatory myopathies, they are restricted to a single muscle or to a muscle group. They are not associated with extramuscular manifestations, and they have a good prognosis without any treatment. They are characterized by a localized swelling affecting mostly lower limbs. The pseudo-tumor can be painful, but is not associated with a muscle weakness. Creatine kinase level is normal. Muscle MRI shows an inflammation restricted to a muscle or a muscle group. Muscle biopsy and pathological analysis remain necessary for the diagnosis, showing inflammatory infiltrates composed by macrophages and lymphocytes without any specific distribution within the muscle. Focal overexpression of HLA-1 by the muscle fibers is frequently observed. The muscle biopsy permits to rule out differential diagnosis such a malignancy (sarcoma). Spontaneous remission occurs within weeks or months after the first symptoms, relapse is unusual. Copyright © 2017. Published by Elsevier SAS.

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

Science.gov (United States)

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.

A Gyrocompass for Maritime Applications Based Upon Multivariable Control Theory

Directory of Open Access Journals (Sweden)

Olav Egeland

1984-10-01

Full Text Available A gyrocompass is designed using multivariable control theory. The compass can be implemented with an inertial platform or as a strap-down system. Measurement noise caused by vessel acceleration is modeled and feedforward is taken from vessel speed. Though the model is of order 9, it has only three unknown parameters of which one can be chosen a priori. Parameter estimation is discussed. For simulation of the compass, a non-linear surface vessel model with 6 degrees of freedom and wave excitation is used.

Discrimination of source reactor type by multivariate statistical analysis of uranium and plutonium isotopic concentrations in unknown irradiated nuclear fuel material.

Science.gov (United States)

Robel, Martin; Kristo, Michael J

2008-11-01

The problem of identifying the provenance of unknown nuclear material in the environment by multivariate statistical analysis of its uranium and/or plutonium isotopic composition is considered. Such material can be introduced into the environment as a result of nuclear accidents, inadvertent processing losses, illegal dumping of waste, or deliberate trafficking in nuclear materials. Various combinations of reactor type and fuel composition were analyzed using Principal Components Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLSDA) of the concentrations of nine U and Pu isotopes in fuel as a function of burnup. Real-world variation in the concentrations of (234)U and (236)U in the fresh (unirradiated) fuel was incorporated. The U and Pu were also analyzed separately, with results that suggest that, even after reprocessing or environmental fractionation, Pu isotopes can be used to determine both the source reactor type and the initial fuel composition with good discrimination.

A Movement-Assisted Deployment of Collaborating Autonomous Sensors for Indoor and Outdoor Environment Monitoring.

Science.gov (United States)

Niewiadomska-Szynkiewicz, Ewa; Sikora, Andrzej; Marks, Michał

2016-09-14

Using mobile robots or unmanned vehicles to assist optimal wireless sensors deployment in a working space can significantly enhance the capability to investigate unknown environments. This paper addresses the issues of the application of numerical optimization and computer simulation techniques to on-line calculation of a wireless sensor network topology for monitoring and tracking purposes. We focus on the design of a self-organizing and collaborative mobile network that enables a continuous data transmission to the data sink (base station) and automatically adapts its behavior to changes in the environment to achieve a common goal. The pre-defined and self-configuring approaches to the mobile-based deployment of sensors are compared and discussed. A family of novel algorithms for the optimal placement of mobile wireless devices for permanent monitoring of indoor and outdoor dynamic environments is described. They employ a network connectivity-maintaining mobility model utilizing the concept of the virtual potential function for calculating the motion trajectories of platforms carrying sensors. Their quality and utility have been justified through simulation experiments and are discussed in the final part of the paper.

Metastasis to neck from unknown primary tumor

International Nuclear Information System (INIS)

Jose, B.; Bosch, A.; Caldwell, W.L.; Frias, Z.

1979-01-01

The records of 54 consecutive patients who were irradiated for metastatic disease in the neck from an unknown primary tumor were reviewed. The overall survival results are comparable to those of other reported series. Patients with high or posterior cervical lymph node involvement were irradiated with fields including the nasopharynx and oropharynx. Patients with high neck nodes had a better survival rate than those with low neck nodes. The size of the neck tumors and the local control after treatment also have prognostic significance. (Auth.)

MUSIC-type imaging of small perfectly conducting cracks with an unknown frequency

International Nuclear Information System (INIS)

Park, Won-Kwang

2015-01-01

MUltiple SIgnal Classification (MUSIC) is a famous non-iterative detection algorithm in inverse scattering problems. However, when the applied frequency is unknown, inaccurate locations are identified via MUSIC. This fact has been confirmed through numerical simulations. However, the reason behind this phenomenon has not been investigated theoretically. Motivated by this fact, we identify the structure of MUSIC-type imaging functionals with unknown frequency, by establishing a relationship with Bessel functions of order zero of the first kind. Through this, we can explain why inaccurate results appear. (paper)

MUSIC-type imaging of small perfectly conducting cracks with an unknown frequency

Science.gov (United States)

Park, Won-Kwang

2015-09-01

MUltiple SIgnal Classification (MUSIC) is a famous non-iterative detection algorithm in inverse scattering problems. However, when the applied frequency is unknown, inaccurate locations are identified via MUSIC. This fact has been confirmed through numerical simulations. However, the reason behind this phenomenon has not been investigated theoretically. Motivated by this fact, we identify the structure of MUSIC-type imaging functionals with unknown frequency, by establishing a relationship with Bessel functions of order zero of the first kind. Through this, we can explain why inaccurate results appear.

Structure Determination of Unknown Organic Liquids Using NMR and IR Spectroscopy: A General Chemistry Laboratory

Science.gov (United States)

Pavel, John T.; Hyde, Erin C.; Bruch, Martha D.

2012-01-01

This experiment introduced general chemistry students to the basic concepts of organic structures and to the power of spectroscopic methods for structure determination. Students employed a combination of IR and NMR spectroscopy to perform de novo structure determination of unknown alcohols, without being provided with a list of possible…

Spectroscopic gamma camera for use in high dose environments

Energy Technology Data Exchange (ETDEWEB)

Ueno, Yuichiro, E-mail: yuichiro.ueno.bv@hitachi.com [Research and Development Group, Hitachi, Ltd., Hitachi-shi, Ibaraki-ken 319-1221 (Japan); Takahashi, Isao; Ishitsu, Takafumi; Tadokoro, Takahiro; Okada, Koichi; Nagumo, Yasushi [Research and Development Group, Hitachi, Ltd., Hitachi-shi, Ibaraki-ken 319-1221 (Japan); Fujishima, Yasutake; Kometani, Yutaka [Hitachi Works, Hitachi-GE Nuclear Energy, Ltd., Hitachi-shi, Ibaraki-ken (Japan); Suzuki, Yasuhiko [Measuring Systems Engineering Dept., Hitachi Aloka Medical, Ltd., Ome-shi, Tokyo (Japan); Umegaki, Kikuo [Faculty of Engineering, Hokkaido University, Sapporo-shi, Hokkaido (Japan)

2016-06-21

We developed a pinhole gamma camera to measure distributions of radioactive material contaminants and to identify radionuclides in extraordinarily high dose regions (1000 mSv/h). The developed gamma camera is characterized by: (1) tolerance for high dose rate environments; (2) high spatial and spectral resolution for identifying unknown contaminating sources; and (3) good usability for being carried on a robot and remotely controlled. These are achieved by using a compact pixelated detector module with CdTe semiconductors, efficient shielding, and a fine resolution pinhole collimator. The gamma camera weighs less than 100 kg, and its field of view is an 8 m square in the case of a distance of 10 m and its image is divided into 256 (16×16) pixels. From the laboratory test, we found the energy resolution at the 662 keV photopeak was 2.3% FWHM, which is enough to identify the radionuclides. We found that the count rate per background dose rate was 220 cps h/mSv and the maximum count rate was 300 kcps, so the maximum dose rate of the environment where the gamma camera can be operated was calculated as 1400 mSv/h. We investigated the reactor building of Unit 1 at the Fukushima Dai-ichi Nuclear Power Plant using the gamma camera and could identify the unknown contaminating source in the dose rate environment that was as high as 659 mSv/h.

Magnetic resonance appearance of monoclonal gammopathies of unknown significance and multiple myeloma. The GRI Study Group.

Science.gov (United States)

Bellaïche, L; Laredo, J D; Lioté, F; Koeger, A C; Hamze, B; Ziza, J M; Pertuiset, E; Bardin, T; Tubiana, J M

1997-11-01

A prospective multicenter study. To evaluate the use of magnetic resonance imaging, in the differentiation between monoclonal gammopathies of unknown significance and multiple myeloma. Although multiple myeloma has been studied extensively with magnetic resonance imaging, to the authors' knowledge, no study has evaluated the clinical interest of magnetic resonance imaging in the differentiation between monoclonal gammopathies of unknown significance and multiple myeloma. The magnetic resonance examinations of the thoracolumbar spine in 24 patients with newly diagnosed monoclonal gammopathies of unknown significance were compared with those performed in 44 patients with newly diagnosed nontreated multiple myeloma. All findings on magnetic resonance examination performed in patients with monoclonal gammopathies of unknown significance were normal, whereas findings on 38 (86%) of the 44 magnetic resonance examinations performed in patients with multiple myeloma were abnormal. Magnetic resonance imaging can be considered as an additional diagnostic tool in differentiating between monoclonal gammopathies of unknown significance and multiple myeloma, which may be helpful when routine criteria are not sufficient. An abnormal finding on magnetic resonance examination in a patient with monoclonal gammopathies of unknown significance should suggest the diagnosis of multiple myeloma after other causes of marrow signal abnormalities are excluded. Magnetic resonance imaging also may be proposed in the long-term follow-up of monoclonal gammopathies of unknown significance when a new biologic or clinical event suggests the diagnosis of malignant monoclonal gammopathy.

Three-dimensional cinematography with control object of unknown shape.

Science.gov (United States)

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.

Carcinomatous Meningitis from Unknown Primary Carcinoma

Directory of Open Access Journals (Sweden)

L. Favier

2009-10-01

Full Text Available Carcinomatous meningitis (CM occurs in 3 to 8% of cancer patients. Patients present with a focal symptom, and multifocal signs are often found following neurological examination. The gold standard for diagnosis remains the demonstration of carcinomatous cells in the cerebrospinal fluid on cytopathological examination. Despite the poor prognosis, palliative treatment could improve quality of life and, in some cases, overall survival. We report on a patient who presented with vertigo, tinnitus and left-sided hearing loss followed by progressive diffuse facial nerve paralysis. Lumbar cerebrospinal fluid confirmed the diagnosis of CM. However, no primary tumor was discovered, even after multiple invasive investigations. This is the first reported case in the English-language medical literature of CM resulting from a carcinoma of unknown primary origin.

Does social environment influence learning ability in a family-living lizard?

Science.gov (United States)

Riley, Julia L; Noble, Daniel W A; Byrne, Richard W; Whiting, Martin J

2017-05-01

Early developmental environment can have profound effects on individual physiology, behaviour, and learning. In birds and mammals, social isolation during development is known to negatively affect learning ability; yet in other taxa, like reptiles, the effect of social isolation during development on learning ability is unknown. We investigated how social environment affects learning ability in the family-living tree skink (Egernia striolata). We hypothesized that early social environment shapes cognitive development in skinks and predicted that skinks raised in social isolation would have reduced learning ability compared to skinks raised socially. Offspring were separated at birth into two rearing treatments: (1) raised alone or (2) in a pair. After 1 year, we quantified spatial learning ability of skinks in these rearing treatments (N = 14 solitary, 14 social). We found no effect of rearing treatment on learning ability. The number of skinks to successfully learn the task, the number of trials taken to learn the task, the latency to perform the task, and the number of errors in each trial did not differ between isolated and socially reared skinks. Our results were unexpected, yet the facultative nature of this species' social system may result in a reduced effect of social isolation on behaviour when compared to species with obligate sociality. Overall, our findings do not provide evidence that social environment affects development of spatial learning ability in this family-living lizard.

Antibiotics in the aquatic environments: A review of the European scenario.

Science.gov (United States)

Carvalho, Isabel T; Santos, Lúcia

2016-09-01

The discovery of antibiotics is considered one of the most significant scientific achievements of the 20th century, revolutionizing both human and veterinary medicine. However, antibiotics have been recently recognized as an emerging class of environmental contaminants since they have been massively administrated in humans and animals and persist in the environment through a complex vicious cycle of transformation and bioaccumulation. The diffusion of antibiotics in the environment, particularly in natural water systems, contributes to the development and global dissemination of antibiotic resistance. This phenomenon is one of the most important challenges to the health care sector in the 21st century. As a result, studies on the occurrence, fate, and effects of antibiotics in European aqueous environments have increased in the last years. Nevertheless, their potential aquatic ecotoxicity and human toxicity via environmental exposure routes remain unknown. Consequently, antibiotics are not regulated through the current European environmental water quality standards, which requires evidence concerning their widespread environmental contamination and intrinsic hazard. In this context, this literature review summarizes the state of knowledge on the occurrence of antibiotics in the different aqueous environmental systems across the Europe, as reported since 2000. Relating this subject to antibiotic consumption and their dynamic behavior in the environment, the acquired insights provide an improved understanding on aquatic pollution by antibiotics to outline the European scenario. Moreover, it addresses challenges, prospects for future research, and typical topics to stimulate discussion. Copyright © 2016 Elsevier Ltd. All rights reserved.

Difference equation approach to two-thermocouple sensor characterization in constant velocity flow environments

International Nuclear Information System (INIS)

Hung, P.C.; Irwin, G.; Kee, R.; McLoone, S.

2005-01-01

Thermocouples are one of the most popular devices for temperature measurement due to their robustness, ease of manufacture and installation, and low cost. However, when used in certain harsh environments, for example, in combustion systems and engine exhausts, large wire diameters are required, and consequently the measurement bandwidth is reduced. This article discusses a software compensation technique to address the loss of high frequency fluctuations based on measurements from two thermocouples. In particular, a difference equation (DE) approach is proposed and compared with existing methods both in simulation and on experimental test rig data with constant flow velocity. It is found that the DE algorithm, combined with the use of generalized total least squares for parameter identification, provides better performance in terms of time constant estimation without any a priori assumption on the time constant ratios of the thermocouples

Automated pathway and reaction prediction facilitates in silico identification of unknown metabolites in human cohort studies.

Science.gov (United States)

Quell, Jan D; Römisch-Margl, Werner; Colombo, Marco; Krumsiek, Jan; Evans, Anne M; Mohney, Robert; Salomaa, Veikko; de Faire, Ulf; Groop, Leif C; Agakov, Felix; Looker, Helen C; McKeigue, Paul; Colhoun, Helen M; Kastenmüller, Gabi

2017-12-15

Identification of metabolites in non-targeted metabolomics continues to be a bottleneck in metabolomics studies in large human cohorts. Unidentified metabolites frequently emerge in the results of association studies linking metabolite levels to, for example, clinical phenotypes. For further analyses these unknown metabolites must be identified. Current approaches utilize chemical information, such as spectral details and fragmentation characteristics to determine components of unknown metabolites. Here, we propose a systems biology model exploiting the internal correlation structure of metabolite levels in combination with existing biochemical and genetic information to characterize properties of unknown molecules. Levels of 758 metabolites (439 known, 319 unknown) in human blood samples of 2279 subjects were measured using a non-targeted metabolomics platform (LC-MS and GC-MS). We reconstructed the structure of biochemical pathways that are imprinted in these metabolomics data by building an empirical network model based on 1040 significant partial correlations between metabolites. We further added associations of these metabolites to 134 genes from genome-wide association studies as well as reactions and functional relations to genes from the public database Recon 2 to the network model. From the local neighborhood in the network, we were able to predict the pathway annotation of 180 unknown metabolites. Furthermore, we classified 100 pairs of known and unknown and 45 pairs of unknown metabolites to 21 types of reactions based on their mass differences. As a proof of concept, we then looked further into the special case of predicted dehydrogenation reactions leading us to the selection of 39 candidate molecules for 5 unknown metabolites. Finally, we could verify 2 of those candidates by applying LC-MS analyses of commercially available candidate substances. The formerly unknown metabolites X-13891 and X-13069 were shown to be 2-dodecendioic acid and 9

Method for signal conditioning and data acquisition system, based on variable amplification and feedback technique

Energy Technology Data Exchange (ETDEWEB)

Conti, Livio, E-mail: livio.conti@uninettunouniversity.net [Facoltà di Ingegneria, Università Telematica Internazionale Uninettuno, Corso Vittorio Emanuele II 39, 00186 Rome, Italy INFN Sezione Roma Tor Vergata, Via della Ricerca Scientifica 1, 00133 Rome (Italy); Sgrigna, Vittorio [Dipartimento di Matematica e Fisica, Università Roma Tre, 84 Via della Vasca Navale, I-00146 Rome (Italy); Zilpimiani, David [National Institute of Geophysics, Georgian Academy of Sciences, 1 M. Alexidze St., 009 Tbilisi, Georgia (United States); Assante, Dario [Facoltà di Ingegneria, Università Telematica Internazionale Uninettuno, Corso Vittorio Emanuele II 39, 00186 Rome, Italy INFN Sezione Roma Tor Vergata, Via della Ricerca Scientifica 1, 00133 Rome (Italy)

2014-08-21

An original method of signal conditioning and adaptive amplification is proposed for data acquisition systems of analog signals, conceived to obtain a high resolution spectrum of any input signal. The procedure is based on a feedback scheme of the signal amplification with aim at maximizing the dynamic range and resolution of the data acquisition system. The paper describes the signal conditioning, digitization, and data processing procedures applied to an a priori unknown signal in order to enucleate its amplitude and frequency content for applications in different environments: on the ground, in space, or in the laboratory. An electronic board of the conditioning module has also been constructed and described. In the paper are also discussed the main fields of application and advantages of the method with respect to those known today.

Method for signal conditioning and data acquisition system, based on variable amplification and feedback technique

International Nuclear Information System (INIS)

Conti, Livio; Sgrigna, Vittorio; Zilpimiani, David; Assante, Dario

2014-01-01

An original method of signal conditioning and adaptive amplification is proposed for data acquisition systems of analog signals, conceived to obtain a high resolution spectrum of any input signal. The procedure is based on a feedback scheme of the signal amplification with aim at maximizing the dynamic range and resolution of the data acquisition system. The paper describes the signal conditioning, digitization, and data processing procedures applied to an a priori unknown signal in order to enucleate its amplitude and frequency content for applications in different environments: on the ground, in space, or in the laboratory. An electronic board of the conditioning module has also been constructed and described. In the paper are also discussed the main fields of application and advantages of the method with respect to those known today

Slowly switching between environments facilitates reverse evolution in small populations

Science.gov (United States)

Tan, Longzhi; Gore, Jeff

2011-03-01

The rate at which a physical process occurs usually changes the behavior of a system. In thermodynamics, the reversibility of a process generally increases when it occurs at an infinitely slow rate. In biological evolution, adaptations to a new environment may be reversed by evolution in the ancestral environment. Such fluctuating environments are ubiquitous in nature, although how the rate of switching affects reverse evolution is unknown. Here we use a computational approach to quantify evolutionary reversibility as a function of the rate of switching between two environments. For small population sizes, which travel on landscapes as random walkers, we find that both genotypic and phenotypic reverse evolution increase at slow switching rates. However, slow switching of environments decreases evolutionary reversibility for a greedy walker, corresponding to large populations (extensive clonal interference). We conclude that the impact of the switching rate for biological evolution is more complicated than other common physical processes, and that a quantitative approach may yield significant insight into reverse evolution.

Marine nitrous oxide emissions: An unknown liability for the international water sector

International Nuclear Information System (INIS)

Short, Michael D.; Peters, Gregory M.; Peirson, William L.; Ashbolt, Nicholas J.

2013-01-01

Highlights: • IPCC methodology for indirect marine nitrous oxide (N 2 O) emissions does not exist. • The water sector has an unknown N 2 O emissions liability from marine sewage disposal. • We model global sewage-nitrogen (N) emissions to coastal oceans during 1970–2050. • Emission factors for marine N 2 O will enable water sector N 2 O emissions accounting. • Industry benefits will include future revenue streams and better N emissions policy. -- Abstract: Reliable estimates of anthropogenic greenhouse gas (GHG) emissions are essential for setting effective climate policy at both the sector and national level. Current IPCC Guidelines for calculating nitrous oxide (N 2 O) emissions from sewage management are both highly uncertain and incomplete; a major methodological gap relates to the calculation of indirect N 2 O emissions from sewage disposed to marine environments. Here we apply a novel approach to estimate past and future global sewage-nitrogen emissions to coastal oceans and the potential marine N 2 O emissions linked to this nitrogen source. Then, by estimating the future cost associated with this largely uncharacterized emission source, we demonstrate the industry significance of developing a methodology for estimating N 2 O emissions from marine receiving environments. The capacity to accurately estimate, monitor and report GHG emissions has important consequences for informing future policy decisions regarding both mitigation and adaptation. A robust N 2 O emissions estimation methodology for sewage-nitrogen disposed to coastal oceans will allow the international water sector to more accurately and comprehensively inventory its N 2 O emissions. This will in turn allow for proper accounting of related future emissions liabilities while also enabling the sector to capitalize on any future economic returns linked to this source – providing much-needed capital to support the sector's future infrastructure and climate change adaptation challenges

A case of hemophagocytic lymphohistiocytosis presenting as pyrexia of unknown origin

Directory of Open Access Journals (Sweden)

Indira Madhavan

2015-01-01

Full Text Available Hemophagocytic lymphohistiocytosis (HLH is a potentially fatal hyper inflammatory condition, which occurs as either primary (genetic or secondary (acquired due to impaired or absent function of natural killer cells and cytotoxic cells. Common secondary causes include viral and bacterial infections, autoimmune diseases, and hematological malignancies. Extensive phagocytosis of blood cells by histiocytes in bone marrow, spleen, liver and lymphnodes result in peripheral blood cytopenias, hepatosplenomegaly, and lymphadenopathy. We evaluated a case of pyrexia of unknown origin and found out that he fulfilled the criteria for diagnosing HLH. He was started on immunochemotherapy with etoposide, cyclosporine and steroids, but he succumbed to illness within 2 weeks of treatment. High index of suspicion is needed to diagnose HLH and prompt treatment on diagnosis can be lifesaving.

Approximate and Conditional Teleportation of an Unknown Atomic-Entangled State Without Bell-State Measurement

Institute of Scientific and Technical Information of China (English)

CHEN Chang-Yong; LI Shao-Hua

2007-01-01

A scheme for approximately and conditionally teleporting an unknown atomic-entangled state in cavity QED is proposed.It is the novel extension of the scheme of [Phys.Rev.A 69 (2004) 064302],where the state to be teleported is an unknown atomic state and where only a time point of system evolution and the corresponding fidelity implementing the teleportation are given.In fact,there exists multi-time points and the corresponding fidclities,which are shown in this paper and then are used to realize the approximate and conditional teleportation of the unknown atomic-entangled state.Naturally,our scheme does not involve the Bell-state measurement or an additional atom,which is required in the Bell-state measurement,only requiring one single-mode cavity.The scheme may be generalized to not only the teleportation of the cavity-mode-entangled-state by means of a single atom but also the teleportation of the unknown trapped-ion-entangled-state in a linear ion trap and the teleportation of the multi-atomic entangled states included in generalized GHZ states.

Optimal critic learning for robot control in time-varying environments.

Science.gov (United States)

Wang, Chen; Li, Yanan; Ge, Shuzhi Sam; Lee, Tong Heng

2015-10-01

In this paper, optimal critic learning is developed for robot control in a time-varying environment. The unknown environment is described as a linear system with time-varying parameters, and impedance control is employed for the interaction control. Desired impedance parameters are obtained in the sense of an optimal realization of the composite of trajectory tracking and force regulation. Q -function-based critic learning is developed to determine the optimal impedance parameters without the knowledge of the system dynamics. The simulation results are presented and compared with existing methods, and the efficacy of the proposed method is verified.

Adding memory processing behaviors to the fuzzy behaviorist-based navigation of mobile robots

Energy Technology Data Exchange (ETDEWEB)

Pin, F.G.; Bender, S.R.

1996-05-01

Most fuzzy logic-based reasoning schemes developed for robot control are fully reactive, i.e., the reasoning modules consist of fuzzy rule bases that represent direct mappings from the stimuli provided by the perception systems to the responses implemented by the motion controllers. Due to their totally reactive nature, such reasoning systems can encounter problems such as infinite loops and limit cycles. In this paper, we proposed an approach to remedy these problems by adding a memory and memory-related behaviors to basic reactive systems. Three major types of memory behaviors are addressed: memory creation, memory management, and memory utilization. These are first presented, and examples of their implementation for the recognition of limit cycles during the navigation of an autonomous robot in a priori unknown environments are then discussed.

Autonomous construction using scarce resources in unknown environments - Ingredients for an intelligent robotic interaction with the physical world

OpenAIRE

Magnenat, Stéphane; Philippsen, Roland; Mondada, Francesco

2012-01-01

The goal of creating machines that autonomously perform useful work in a safe, robust and intelligent manner continues to motivate robotics research. Achieving this autonomy requires capabilities for understanding the environment, physically interacting with it, predicting the outcomes of actions and reasoning with this knowledge. Such intelligent physical interaction was at the centre of early robotic investigations and remains an open topic. In this paper, we build on the fruit of decades ...

Avoidance of Affect Mediates the Effect of Invalidating Childhood Environments on Borderline Personality Symptomatology in a Non-Clinical Sample

Science.gov (United States)

Sturrock, Bonnie A.; Francis, Andrew; Carr, Steven

2009-01-01

The aim of this study was to test the Linehan (1993) proposal regarding associations between invalidating childhood environments, distress tolerance (e.g., avoidance of affect), and borderline personality disorder (BPD) symptoms. The sample consisted of 141 non-clinical participants (51 men, 89 women, one gender unknown), ranging in age from 18 to…

Using systematic and comparative GC/MS and GC/FID data to identify the source of an unknown oil on contaminated birds

International Nuclear Information System (INIS)

Wang, Z.; Fingas, M.; Landriault, M.; Sigouin, L.; Feng, Y.

1996-01-01

A method to identify and differentiate spilled oil and petroleum products was developed. In January 1996, four birds covered with an unknown oil were found near Larchipel-de-Mingan National Park in Quebec. Environment Canada wanted to know if the oil came from a leak in a barge which was grounded on Anticosti Island. To do so, it was necessary to determine the nature of the oil, the type of petroleum hydrocarbons, the age, the weathering and degradation extent of the spilled oil, and changes in oil character since the occurrence of any possible spill. The analytical approach to determine the source of the unknown oil was described. The analysis of individual aliphatic, aromatic, and biomarker hydrocarbons were made with the use of gas chromatography/mass spectroscopy (GC/MS), and gas chromatography/flame ionization detector (GC/FID). Pattern recognition plot analysis was also used in determining the source of the oil. It was concluded that the residual oil on the birds was not from the suspected barge oil, and was most probably old, highly weathered, somewhat biodegraded bunker type oil. 23 refs., 5 tabs., 7 figs

Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances

Science.gov (United States)

Yang, Xinxin; Ge, Shuzhi Sam; He, Wei

2018-04-01

In this paper, both the closed-form dynamics and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances are developed. The dynamic model of the system is described with assumed modes approach and Lagrangian method. The flexible manipulators are represented as Euler-Bernoulli beams. Based on singular perturbation technique, the displacements/joint angles and flexible modes are modelled as slow and fast variables, respectively. A sliding mode control is designed for trajectories tracking of the slow subsystem under unknown but bounded disturbances, and an adaptive sliding mode control is derived for slow subsystem under unknown slowly time-varying disturbances. An optimal linear quadratic regulator method is proposed for the fast subsystem to damp out the vibrations of the flexible manipulators. Theoretical analysis validates the stability of the proposed composite controller. Numerical simulation results demonstrate the performance of the closed-loop flexible space robot system.

The origin of anomalous transport in porous media - is it possible to make a priori predictions?

Science.gov (United States)

Bijeljic, Branko; Blunt, Martin

2013-04-01

at approximately the average flow speed; in the carbonate with the widest velocity distribution the stagnant concentration peak is persistent, while the emergence of a smaller secondary mobile peak is observed, leading to a highly anomalous behavior. This defines different generic nature of non-Fickian transport in the three media and quantifies the effect of pore structure on transport. Moreover, the propagators obtained by the model are in a very good agreement with the propagators measured on beadpack, Bentheimer sandstone and Portland carbonate cores in nuclear magnetic resonance experiments. These findings demonstrate that it is possible to make a priori predictions of anomalous transport in porous media. The importance of these findings for transport in complex carbonate rock micro-CT images is discussed, classifying them in terms of degree of anomalous transport that can have an impact at the field scale. Extensions to reactive transport will be discussed.

Work group I: Measures of the food and physical activity environment: instruments.

Science.gov (United States)

Saelens, Brian E; Glanz, Karen

2009-04-01

A work group was convened to identify the core challenges, content gaps, and corresponding possible solutions for improving food- and physical activity-environment instrumentation. Identified challenges included instrument proliferation, the scaling or grain of instruments and appropriate aggregation to the neighborhood or community level, and unknown sensitivity to change of most instruments. Solutions for addressing these challenges included establishing an interactive and real-time instrument repository, developing and enforcing high standards for instrument reporting, increasing community-researcher collaborations, and implementing surveillance of food and physical activity environment. Solid instrumentation will accelerate a better understanding of food- and physical activity-environment effects on eating and physical activity behaviors.

RBF neural network based H∞ synchronization for unknown chaotic ...

Indian Academy of Sciences (India)

, 172 ... the effect of disturbance to an H∞ norm constraint. It is shown that ... unknown chaotic systems; linear matrix inequality (LMI); learning law. 1. Introduction .... (9) is RBFNN H∞ synchronized if the synchronization error e(t) satisfies. ∫ ∞.

Metastatic meningioma presenting as cancer of unknown primary

Directory of Open Access Journals (Sweden)

Vinay Gupta

2013-12-01

Full Text Available We describe a case of anaplastic meningioma presenting in an extracranial osseous location, initially diagnosed as cancer of unknown primary. Although anaplastic meningioma comprise 3% of all meningiomas, this subtype is more likely to be associated with metastases. The increased degree of dedifferentiation in anaplastic meningioma makes diagnosis difficult, especially if characteristic imaging findings of meningioma are not identified. Adequate tissue for diagnostic purposes and appropriate imaging studies may help in establishing a definitive diagnosis.

Distributed autonomous mapping of indoor environments

Science.gov (United States)

Rogers, J.; Paluri, M.; Cunningham, A.; Christensen, H. I.; Michael, N.; Kumar, V.; Ma, J.; Matthies, L.

2011-06-01

This paper describes the results of a Joint Experiment performed on behalf of the MAST CTA. The system developed for the Joint Experiment makes use of three robots which work together to explore and map an unknown environment. Each of the robots used in this experiment is equipped with a laser scanner for measuring walls and a camera for locating doorways. Information from both of these types of structures is concurrently incorporated into each robot's local map using a graph based SLAM technique. A Distributed-Data-Fusion algorithm is used to efficiently combine local maps from each robot into a shared global map. Each robot computes a compressed local feature map and transmits it to neighboring robots, which allows each robot to merge its map with the maps of its neighbors. Each robot caches the compressed maps from its neighbors, allowing it to maintain a coherent map with a common frame of reference. The robots utilize an exploration strategy to efficiently cover the unknown environment which allows collaboration on an unreliable communications channel. As each new branching point is discovered by a robot, it broadcasts the information about where this point is along with the robot's path from a known landmark to the other robots. When the next robot reaches a dead-end, new branching points are allocated by auction. In the event of communication interruption, the robot which observed the branching point will eventually explore it; therefore, the exploration is complete in the face of communication failure.

Acquisition of a space representation by a naive agent from sensorimotor invariance and proprioceptive compensation

Directory of Open Access Journals (Sweden)

Gurvan Le Clec’H

2016-11-01

Full Text Available In this article, we present a simple agent which learns an internal representation of space without a priori knowledge of its environment, body, or sensors. The learned environment is seen as an internal space representation. This representation is isomorphic to the group of transformations applied to the environment. The model solves certain theoretical and practical issues encountered in previous work in sensorimotor contingency theory. Considering the mathematical description of the internal representation, analysis of its properties and simulations, we prove that this internal representation is equivalent to knowledge of space.

Accounting for unknown foster dams in the genetic evaluation of embryo transfer progeny.

Science.gov (United States)

Suárez, M J; Munilla, S; Cantet, R J C

2015-02-01

Animals born by embryo transfer (ET) are usually not included in the genetic evaluation of beef cattle for preweaning growth if the recipient dam is unknown. This is primarily to avoid potential bias in the estimation of the unknown age of dam. We present a method that allows including records of calves with unknown age of dam. Assumptions are as follows: (i) foster cows belong to the same breed being evaluated, (ii) there is no correlation between the breeding value (BV) of the calf and the maternal BV of the recipient cow, and (iii) cows of all ages are used as recipients. We examine the issue of bias for the fixed level of unknown age of dam (AOD) and propose an estimator of the effect based on classical measurement error theory (MEM) and a Bayesian approach. Using stochastic simulation under random mating or selection, the MEM estimating equations were compared with BLUP in two situations as follows: (i) full information (FI); (ii) missing AOD information on some dams. Predictions of breeding value (PBV) from the FI situation had the smallest empirical average bias followed by PBV obtained without taking measurement error into account. In turn, MEM displayed the highest bias, although the differences were small. On the other hand, MEM showed the smallest MSEP, for either random mating or selection, followed by FI, whereas ignoring measurement error produced the largest MSEP. As a consequence from the smallest MSEP with a relatively small bias, empirical accuracies of PBV were larger for MEM than those for full information, which in turn showed larger accuracies than the situation ignoring measurement error. It is concluded that MEM equations are a useful alternative for analysing weaning weight data when recipient cows are unknown, as it mitigates the effects of bias in AOD by decreasing MSEP. © 2014 Blackwell Verlag GmbH.

Sliding Mode Observer-Based Current Sensor Fault Reconstruction and Unknown Load Disturbance Estimation for PMSM Driven System.

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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.

Neurological autoantibodies in drug-resistant epilepsy of unknown cause.

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Tecellioglu, Mehmet; Kamisli, Ozden; Kamisli, Suat; Yucel, Fatma Ebru; Ozcan, Cemal

2018-03-09

Autoimmune epilepsy is a rarely diagnosed condition. Recognition of the underlying autoimmune condition is important, as these patients can be resistant to antiepileptic drugs. To determine the autoimmune and oncological antibodies in adult drug-resistant epilepsy of unknown cause and identify the clinical, radiological, and EEG findings associated with these antibodies according to data in the literature. Eighty-two patients with drug-resistant epilepsy of unknown cause were prospectively identified. Clinical features were recorded. The levels of anti-voltage-gated potassium channel complex (anti-VGKCc), anti-thyroid peroxidase (anti-TPO), anti-nuclear antibody (ANA), anti-glutamic acid decarboxylase (anti-GAD), anti-phospholipid IgG and IgM, anti-cardiolipin IgG and IgM, and onconeural antibodies were determined. Serum antibody positivity suggesting the potential role of autoimmunity in the aetiology was present in 17 patients with resistant epilepsy (22.0%). Multiple antibodies were found in two patients (2.6%). One of these patients (1.3%) had anti-VGKCc and ANA, whereas another (1.3%) had anti-VGKCc and anti-TPO. A single antibody was present in 15 patients (19.5%). Of the 77 patients finally included in the study, 4 had anti-TPO (5.2%), 1 had anti-GAD (1.3%), 4 had anti-VGKCc (5.2%) 8 had ANA (10.3%), and 2 had onconeural antibodies (2.6%) (1 patient had anti-Yo and 1 had anti-MA2/TA). The other antibodies investigated were not detected. EEG abnormality (focal), focal seizure incidence, and frequent seizures were more common in antibody-positive patients. Autoimmune factors may be aetiologically relevant in patients with drug-resistant epilepsy of unknown cause, especially if focal seizures are present together with focal EEG abnormality and frequent seizures.

Semi-Supervised Clustering for High-Dimensional and Sparse Features

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Yan, Su

2010-01-01

Clustering is one of the most common data mining tasks, used frequently for data organization and analysis in various application domains. Traditional machine learning approaches to clustering are fully automated and unsupervised where class labels are unknown a priori. In real application domains, however, some "weak" form of side…

Roughened glass slides and a spectrophotometer for the detection of the wavelength-dependent refractive index of transparent liquids.

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Niskanen, Ilpo; Räty, Jukka; Myllylä, Risto; Sutinen, Veijo; Matsuda, Kiyofumi; Homma, Kazuhiro; Silfsten, Pertti; Peiponen, Kai-Erik

2012-07-01

We describe a method to determine the wavelength-dependent refractive index of liquids by measurement of light transmittance with a spectrophotometer. The method is based on using roughened glass slides with different a priori known refractive indices and immersing the slides into the transparent liquid with unknown refractive index. Using the dispersion data on the glass material it is possible to find the index match between the liquid and the glass slide, and hence the refractive index of the liquid.

Auditory Brainstem Response Wave Amplitude Characteristics as a Diagnostic Tool in Children with Speech Delay with Unknown Causes

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Susan Abadi

2016-09-01

Full Text Available Speech delay with an unknown cause is a problem among children. This diagnosis is the last differential diagnosis after observing normal findings in routine hearing tests. The present study was undertaken to determine whether auditory brainstem responses to click stimuli are different between normally developing children and children suffering from delayed speech with unknown causes. In this cross-sectional study, we compared click auditory brainstem responses between 261 children who were clinically diagnosed with delayed speech with unknown causes based on normal routine auditory test findings and neurological examinations and had >12 months of speech delay (case group and 261 age- and sex-matched normally developing children (control group. Our results indicated that the case group exhibited significantly higher wave amplitude responses to click stimuli (waves I, III, and V than did the control group (P=0.001. These amplitudes were significantly reduced after 1 year (P=0.001; however, they were still significantly higher than those of the control group (P=0.001. The significant differences were seen regardless of the age and the sex of the participants. There were no statistically significant differences between the 2 groups considering the latency of waves I, III, and V. In conclusion, the higher amplitudes of waves I, III, and V, which were observed in the auditory brainstem responses to click stimuli among the patients with speech delay with unknown causes, might be used as a diagnostic tool to track patients’ improvement after treatment.

Hatching asynchrony aggravates inbreeding depression in a songbird (Serinus canaria): an inbreeding-environment interaction.

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de Boer, Raïssa A; Eens, Marcel; Fransen, Erik; Müller, Wendt

2015-04-01

Understanding how the intensity of inbreeding depression is influenced by stressful environmental conditions is an important area of enquiry in various fields of biology. In birds, environmental stress during early development is often related to hatching asynchrony; differences in age, and thus size, impose a gradient in conditions ranging from benign (first hatched chick) to harsh (last hatched chick). Here, we compared the effect of hatching order on growth rate in inbred (parents are full siblings) and outbred (parents are unrelated) canary chicks (Serinus canaria). We found that inbreeding depression was more severe under more stressful conditions, being most evident in later hatched chicks. Thus, consideration of inbreeding-environment interactions is of vital importance for our understanding of the biological significance of inbreeding depression and hatching asynchrony. The latter is particularly relevant given that hatching asynchrony is a widespread phenomenon, occurring in many bird species. The exact causes of the observed inbreeding-environment interaction are as yet unknown, but may be related to a decrease in maternal investment in egg contents with laying position (i.e. prehatching environment), or to performance of the chicks during sibling competition and/or their resilience to food shortage (i.e. posthatching environment). © 2015 The Author(s).

TOURISM PROMOTION FOR UNKNOWN AREAS IN ROMANIA

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Fotache Lacramioara

2013-12-01

Full Text Available The paper is an effort to unknown areas identity affirmation, through collaborative development of advertising mix, with an emphasis on virtual platforms as admissible solution for increasing visibility. Based upon comparative effective analysis of categories of communication particularities, it is suggested a positioning strategic solution, via virtual advertising platform as unique, integrated, complex and very attractive tourism product promotion, fitted for the internal and international tourism circuit. The active promotion of the specified territorial identity will launch a brand with an impact among tourists by using marketing techniques and innovating technical means and prioritizing tourism as a principal vector of local and regional development.

Unknown facets of Well-Known Scientists Series - Part II

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V S Dixit

2016-01-01

Full Text Available 1st in the series of articles on “Unknown Facets of well-known Scientists” was about Sir Frederick Grant Banting, co-discoverer of Insulin, who also researched in Aviation and Diving Medicines, results of which brought extraordinary benefits for Flight crew during the World War II. The article was published in the previous issue of the Journal Unknown facets could be celebrated attributes, talents or otherwise, but it is necessary that we get to know fully about the “great mind". THIS ARTICLE IS ABOUT DR WERNER THEODOR OTTO FORSSMANN, A CARDIOLOGIST, WHO BECAME A UROLOGIST! Does the name Dr Forssmann ring a bell? He shared the 1956 Nobel Prize in Physiology or Medicine with “Andre Cournand and Dickinson Richards". The trio was awarded for their “discoveries concerning heart catheterization and pathological changes in the circulatory system". Dr Forssmann was nominated for performing an experiment in which he introduced a catheter into a vein of his arm, further passing it onward into his heart It was risky. This was in the year 1929. Subject of this article is the self-experimentation he carried out and what happened later.

Stability of Nonlinear Systems with Unknown Time-varying Feedback Delay

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Chunodkar, Apurva A.; Akella, Maruthi R.

2013-12-01

This paper considers the problem of stabilizing a class of nonlinear systems with unknown bounded delayed feedback wherein the time-varying delay is 1) piecewise constant 2) continuous with a bounded rate. We also consider application of these results to the stabilization of rigid-body attitude dynamics. In the first case, the time-delay in feedback is modeled specifically as a switch among an arbitrarily large set of unknown constant values with a known strict upper bound. The feedback is a linear function of the delayed states. In the case of linear systems with switched delay feedback, a new sufficiency condition for average dwell time result is presented using a complete type Lyapunov-Krasovskii (L-K) functional approach. Further, the corresponding switched system with nonlinear perturbations is proven to be exponentially stable inside a well characterized region of attraction for an appropriately chosen average dwell time. In the second case, the concept of the complete type L-K functional is extended to a class of nonlinear time-delay systems with unknown time-varying time-delay. This extension ensures stability robustness to time-delay in the control design for all values of time-delay less than the known upper bound. Model-transformation is used in order to partition the nonlinear system into a nominal linear part that is exponentially stable with a bounded perturbation. We obtain sufficient conditions which ensure exponential stability inside a region of attraction estimate. A constructive method to evaluate the sufficient conditions is presented together with comparison with the corresponding constant and piecewise constant delay. Numerical simulations are performed to illustrate the theoretical results of this paper.

Solving differential equations with unknown constitutive relations as recurrent neural networks

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Hagge, Tobias J.; Stinis, Panagiotis; Yeung, Enoch H.; Tartakovsky, Alexandre M.

2017-12-08

We solve a system of ordinary differential equations with an unknown functional form of a sink (reaction rate) term. We assume that the measurements (time series) of state variables are partially available, and use a recurrent neural network to “learn” the reaction rate from this data. This is achieved by including discretized ordinary differential equations as part of a recurrent neural network training problem. We extend TensorFlow’s recurrent neural network architecture to create a simple but scalable and effective solver for the unknown functions, and apply it to a fedbatch bioreactor simulation problem. Use of techniques from recent deep learning literature enables training of functions with behavior manifesting over thousands of time steps. Our networks are structurally similar to recurrent neural networks, but differ in purpose, and require modified training strategies.

Adresse inconnue / Address unknown / Suchwiin Bulmyeong

OpenAIRE

Serge Gruzinski

2005-01-01

Tous les films asiatiques parlent de métissage, même ceux qui se présentent comme de vastes fresques historiques perdues dans le temps. Les emprunts aux traditions hollywoodiennes et européennes n'ont cessé d'enrichir une cinématographie aussi ancienne que celle du monde occidental. Dans Adresse inconnue (Address unknown) le cinéaste coréen Kim Ki-duk explore l'expérience du métissage et le corps du métis à la frontière entre Corée du Nord et Corée du sud. Fils d'un GI américain et noir et d'...

Regularity in an environment produces an internal torque pattern for biped balance control.

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Ito, Satoshi; Kawasaki, Haruhisa

2005-04-01

In this paper, we present a control method for achieving biped static balance under unknown periodic external forces whose periods are only known. In order to maintain static balance adaptively in an uncertain environment, it is essential to have information on the ground reaction forces. However, when the biped is exposed to a steady environment that provides an external force periodically, uncertain factors on the regularity with respect to a steady environment are gradually clarified using learning process, and finally a torque pattern for balancing motion is acquired. Consequently, static balance is maintained without feedback from ground reaction forces and achieved in a feedforward manner.