Tridimensional pose estimation of a person head

International Nuclear Information System (INIS)

Perez Berenguer, Elisa; Soria, Carlos; Nasisi, Oscar; Mut, Vicente

2007-01-01

In this work, we present a method for estimating 3-D motion parameters; this method provides an alternative way for 3D head pose estimation from image sequence in the current computer vision literature. This method is robust over extended sequences and large head motions and accurately extracts the orientation angles of head from a single view. Experimental results show that this tracking system works well for development a human-computer interface for people that possess severe motor incapacity

Teach it Yourself - Fast Modeling of Industrial Objects for 6D Pose Estimation

DEFF Research Database (Denmark)

Sølund, Thomas; Rajeeth Savarimuthu, Thiusius; Glent Buch, Anders

2015-01-01

In this paper, we present a vision system that allows a human to create new 3D models of novel industrial parts by placing the part in two different positions in the scene. The two shot modeling framework generates models with a precision that allows the model to be used for 6D pose estimation wi....... In addition, the models are applied in a pose estimation application, evaluated with 37 different scenes with 61 unique object poses. The pose estimation results show a mean translation error on 4.97 mm and a mean rotation error on 3.38 degrees....

Perturbation-Based Regularization for Signal Estimation in Linear Discrete Ill-posed Problems

KAUST Repository

Suliman, Mohamed Abdalla Elhag; Ballal, Tarig; Al-Naffouri, Tareq Y.

2016-01-01

Estimating the values of unknown parameters from corrupted measured data faces a lot of challenges in ill-posed problems. In such problems, many fundamental estimation methods fail to provide a meaningful stabilized solution. In this work, we propose a new regularization approach and a new regularization parameter selection approach for linear least-squares discrete ill-posed problems. The proposed approach is based on enhancing the singular-value structure of the ill-posed model matrix to acquire a better solution. Unlike many other regularization algorithms that seek to minimize the estimated data error, the proposed approach is developed to minimize the mean-squared error of the estimator which is the objective in many typical estimation scenarios. The performance of the proposed approach is demonstrated by applying it to a large set of real-world discrete ill-posed problems. Simulation results demonstrate that the proposed approach outperforms a set of benchmark regularization methods in most cases. In addition, the approach also enjoys the lowest runtime and offers the highest level of robustness amongst all the tested benchmark regularization methods.

Perturbation-Based Regularization for Signal Estimation in Linear Discrete Ill-posed Problems

KAUST Repository

Suliman, Mohamed Abdalla Elhag

2016-11-29

Estimating the values of unknown parameters from corrupted measured data faces a lot of challenges in ill-posed problems. In such problems, many fundamental estimation methods fail to provide a meaningful stabilized solution. In this work, we propose a new regularization approach and a new regularization parameter selection approach for linear least-squares discrete ill-posed problems. The proposed approach is based on enhancing the singular-value structure of the ill-posed model matrix to acquire a better solution. Unlike many other regularization algorithms that seek to minimize the estimated data error, the proposed approach is developed to minimize the mean-squared error of the estimator which is the objective in many typical estimation scenarios. The performance of the proposed approach is demonstrated by applying it to a large set of real-world discrete ill-posed problems. Simulation results demonstrate that the proposed approach outperforms a set of benchmark regularization methods in most cases. In addition, the approach also enjoys the lowest runtime and offers the highest level of robustness amongst all the tested benchmark regularization methods.

A multi-camera system for real-time pose estimation

Science.gov (United States)

Savakis, Andreas; Erhard, Matthew; Schimmel, James; Hnatow, Justin

2007-04-01

This paper presents a multi-camera system that performs face detection and pose estimation in real-time and may be used for intelligent computing within a visual sensor network for surveillance or human-computer interaction. The system consists of a Scene View Camera (SVC), which operates at a fixed zoom level, and an Object View Camera (OVC), which continuously adjusts its zoom level to match objects of interest. The SVC is set to survey the whole filed of view. Once a region has been identified by the SVC as a potential object of interest, e.g. a face, the OVC zooms in to locate specific features. In this system, face candidate regions are selected based on skin color and face detection is accomplished using a Support Vector Machine classifier. The locations of the eyes and mouth are detected inside the face region using neural network feature detectors. Pose estimation is performed based on a geometrical model, where the head is modeled as a spherical object that rotates upon the vertical axis. The triangle formed by the mouth and eyes defines a vertical plane that intersects the head sphere. By projecting the eyes-mouth triangle onto a two dimensional viewing plane, equations were obtained that describe the change in its angles as the yaw pose angle increases. These equations are then combined and used for efficient pose estimation. The system achieves real-time performance for live video input. Testing results assessing system performance are presented for both still images and video.

Pose Estimation of Interacting People using Pictorial Structures

DEFF Research Database (Denmark)

Fihl, Preben; Moeslund, Thomas B.

2010-01-01

Pose estimation of people have had great progress in recent years but so far research has dealt with single persons. In this paper we address some of the challenges that arise when doing pose estimation of interacting people. We build on the pictorial structures framework and make important...... contributions by combining color-based appearance and edge information using a measure of the local quality of the appearance feature. In this way we not only combine the two types of features but dynamically find the optimal weighting of them. We further enable the method to handle occlusions by searching...... a foreground mask for possible occluded body parts and then applying extra strong kinematic constraints to find the true occluded body parts. The effect of applying our two contributions are show through both qualitative and quantitative tests and show a clear improvement on the ability to correctly localize...

Coupled multiview autoencoders with locality sensitivity for three-dimensional human pose estimation

Science.gov (United States)

Yu, Jialin; Sun, Jifeng; Luo, Shasha; Duan, Bichao

2017-09-01

Estimating three-dimensional (3D) human poses from a single camera is usually implemented by searching pose candidates with image descriptors. Existing methods usually suppose that the mapping from feature space to pose space is linear, but in fact, their mapping relationship is highly nonlinear, which heavily degrades the performance of 3D pose estimation. We propose a method to recover 3D pose from a silhouette image. It is based on the multiview feature embedding (MFE) and the locality-sensitive autoencoders (LSAEs). On the one hand, we first depict the manifold regularized sparse low-rank approximation for MFE and then the input image is characterized by a fused feature descriptor. On the other hand, both the fused feature and its corresponding 3D pose are separately encoded by LSAEs. A two-layer back-propagation neural network is trained by parameter fine-tuning and then used to map the encoded 2D features to encoded 3D poses. Our LSAE ensures a good preservation of the local topology of data points. Experimental results demonstrate the effectiveness of our proposed method.

Monocular-Based 6-Degree of Freedom Pose Estimation Technology for Robotic Intelligent Grasping Systems

Directory of Open Access Journals (Sweden)

Tao Liu

2017-02-01

Full Text Available Industrial robots are expected to undertake ever more advanced tasks in the modern manufacturing industry, such as intelligent grasping, in which robots should be capable of recognizing the position and orientation of a part before grasping it. In this paper, a monocular-based 6-degree of freedom (DOF pose estimation technology to enable robots to grasp large-size parts at informal poses is proposed. A camera was mounted on the robot end-flange and oriented to measure several featured points on the part before the robot moved to grasp it. In order to estimate the part pose, a nonlinear optimization model based on the camera object space collinearity error in different poses is established, and the initial iteration value is estimated with the differential transformation. Measuring poses of the camera are optimized based on uncertainty analysis. Also, the principle of the robotic intelligent grasping system was developed, with which the robot could adjust its pose to grasp the part. In experimental tests, the part poses estimated with the method described in this paper were compared with those produced by a laser tracker, and results show the RMS angle and position error are about 0.0228° and 0.4603 mm. Robotic intelligent grasping tests were also successfully performed in the experiments.

Gaussian particle filter based pose and motion estimation

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

Determination of relative three-dimensional (3D) position, orientation, and relative motion between two reference frames is an important problem in robotic guidance, manipulation, and assembly as well as in other fields such as photogrammetry.A solution to pose and motion estimation problem that uses two-dimensional (2D) intensity images from a single camera is desirable for real-time applications. The difficulty in performing this measurement is that the process of projecting 3D object features to 2D images is a nonlinear transformation. In this paper, the 3D transformation is modeled as a nonlinear stochastic system with the state estimation providing six degrees-of-freedom motion and position values, using line features in image plane as measuring inputs and dual quaternion to represent both rotation and translation in a unified notation. A filtering method called the Gaussian particle filter (GPF) based on the particle filtering concept is presented for 3D pose and motion estimation of a moving target from monocular image sequences. The method has been implemented with simulated data, and simulation results are provided along with comparisons to the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) to show the relative advantages of the GPF. Simulation results showed that GPF is a superior alternative to EKF and UKF.

Combining Front Vehicle Detection with 3D Pose Estimation for a Better Driver Assistance

Directory of Open Access Journals (Sweden)

Yu Peng

2012-09-01

Full Text Available Driver assistant systems enhance traffic safety and efficiency. The accurate 3D pose of a front vehicle can help a driver to make the right decision on the road. We propose a novel real-time system to estimate the 3D pose of the front vehicle. This system consists of two parallel threads: vehicle rear tracking and mapping. The vehicle rear is first identified in the video captured by an onboard camera, after license plate localization and foreground extraction. The 3D pose estimation technique is then employed with respect to the extracted vehicle rear. Most current 3D pose estimation techniques need prior models or a stereo initialization with user cooperation. It is extremely difficult to obtain prior models due to the varying appearance of vehicles' rears. Moreover, it is unsafe to ask for drivers' cooperation when a vehicle is running. In our system, two initial keyframes for stereo algorithms are automatically extracted by vehicle rear detection and tracking. Map points are defined as a collection of point features extracted from the vehicle's rear with their 3D information. These map points are inferences that relate the 2D features detected in following vehicles' rears with the 3D world. The relative 3D pose of the onboard camera to the front vehicle rear is then estimated through matching the map points with point features detected on the front vehicle rear. We demonstrate the capabilities of our system by testing on real-time and synthesized videos. In order to make the experimental analysis visible, we demonstrated an estimated 3D pose through augmented reality, which needs accurate and real-time 3D pose estimation.

The investigation and implementation of real-time face pose and direction estimation on mobile computing devices

Science.gov (United States)

Fu, Deqian; Gao, Lisheng; Jhang, Seong Tae

2012-04-01

The mobile computing device has many limitations, such as relative small user interface and slow computing speed. Usually, augmented reality requires face pose estimation can be used as a HCI and entertainment tool. As far as the realtime implementation of head pose estimation on relatively resource limited mobile platforms is concerned, it is required to face different constraints while leaving enough face pose estimation accuracy. The proposed face pose estimation method met this objective. Experimental results running on a testing Android mobile device delivered satisfactory performing results in the real-time and accurately.

A new benchmark for pose estimation with ground truth from virtual reality

DEFF Research Database (Denmark)

Schlette, Christian; Buch, Anders Glent; Aksoy, Eren Erdal

2014-01-01

The development of programming paradigms for industrial assembly currently gets fresh impetus from approaches in human demonstration and programming-by-demonstration. Major low- and mid-level prerequisites for machine vision and learning in these intelligent robotic applications are pose estimation......, stereo reconstruction and action recognition. As a basis for the machine vision and learning involved, pose estimation is used for deriving object positions and orientations and thus target frames for robot execution. Our contribution introduces and applies a novel benchmark for typical multi...

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

Science.gov (United States)

Zhu, Aichun; Wang, Tian; Snoussi, Hichem

2018-03-01

This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

Directory of Open Access Journals (Sweden)

Aichun Zhu

2018-03-01

Full Text Available This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN. Firstly, a Relative Mixture Deformable Model (RMDM is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Full Body Pose Estimation During Occlusion using Multiple Cameras

DEFF Research Database (Denmark)

Fihl, Preben; Cosar, Serhan

people is a very challenging problem for methods based on pictorials structure as for any other monocular pose estimation method. In this report we present work on a multi-view approach based on pictorial structures that integrate low level information from multiple calibrated cameras to improve the 2D...

Head Pose Estimation on Top of Haar-Like Face Detection: A Study Using the Kinect Sensor

Directory of Open Access Journals (Sweden)

Anwar Saeed

2015-08-01

Full Text Available Head pose estimation is a crucial initial task for human face analysis, which is employed in several computer vision systems, such as: facial expression recognition, head gesture recognition, yawn detection, etc. In this work, we propose a frame-based approach to estimate the head pose on top of the Viola and Jones (VJ Haar-like face detector. Several appearance and depth-based feature types are employed for the pose estimation, where comparisons between them in terms of accuracy and speed are presented. It is clearly shown through this work that using the depth data, we improve the accuracy of the head pose estimation. Additionally, we can spot positive detections, faces in profile views detected by the frontal model, that are wrongly cropped due to background disturbances. We introduce a new depth-based feature descriptor that provides competitive estimation results with a lower computation time. Evaluation on a benchmark Kinect database shows that the histogram of oriented gradients and the developed depth-based features are more distinctive for the head pose estimation, where they compare favorably to the current state-of-the-art approaches. Using a concatenation of the aforementioned feature types, we achieved a head pose estimation with average errors not exceeding 5:1; 4:6; 4:2 for pitch, yaw and roll angles, respectively.

Robotic-surgical instrument wrist pose estimation.

Science.gov (United States)

Fabel, Stephan; Baek, Kyungim; Berkelman, Peter

2010-01-01

The Compact Lightweight Surgery Robot from the University of Hawaii includes two teleoperated instruments and one endoscope manipulator which act in accord to perform assisted interventional medicine. The relative positions and orientations of the robotic instruments and endoscope must be known to the teleoperation system so that the directions of the instrument motions can be controlled to correspond closely to the directions of the motions of the master manipulators, as seen by the the endoscope and displayed to the surgeon. If the manipulator bases are mounted in known locations and all manipulator joint variables are known, then the necessary coordinate transformations between the master and slave manipulators can be easily computed. The versatility and ease of use of the system can be increased, however, by allowing the endoscope or instrument manipulator bases to be moved to arbitrary positions and orientations without reinitializing each manipulator or remeasuring their relative positions. The aim of this work is to find the pose of the instrument end effectors using the video image from the endoscope camera. The P3P pose estimation algorithm is used with a Levenberg-Marquardt optimization to ensure convergence. The correct transformations between the master and slave coordinate frames can then be calculated and updated when the bases of the endoscope or instrument manipulators are moved to new, unknown, positions at any time before or during surgical procedures.

The relative pose estimation of aircraft based on contour model

Science.gov (United States)

Fu, Tai; Sun, Xiangyi

2017-02-01

This paper proposes a relative pose estimation approach based on object contour model. The first step is to obtain a two-dimensional (2D) projection of three-dimensional (3D)-model-based target, which will be divided into 40 forms by clustering and LDA analysis. Then we proceed by extracting the target contour in each image and computing their Pseudo-Zernike Moments (PZM), thus a model library is constructed in an offline mode. Next, we spot a projection contour that resembles the target silhouette most in the present image from the model library with reference of PZM; then similarity transformation parameters are generated as the shape context is applied to match the silhouette sampling location, from which the identification parameters of target can be further derived. Identification parameters are converted to relative pose parameters, in the premise that these values are the initial result calculated via iterative refinement algorithm, as the relative pose parameter is in the neighborhood of actual ones. At last, Distance Image Iterative Least Squares (DI-ILS) is employed to acquire the ultimate relative pose parameters.

Robust Pose Estimation using the SwissRanger SR-3000 Camera

DEFF Research Database (Denmark)

Gudmundsson, Sigurjon Arni; Larsen, Rasmus; Ersbøll, Bjarne Kjær

2007-01-01

In this paper a robust method is presented to classify and estimate an objects pose from a real time range image and a low dimensional model. The model is made from a range image training set which is reduced dimensionally by a nonlinear manifold learning method named Local Linear Embedding (LLE)......). New range images are then projected to this model giving the low dimensional coordinates of the object pose in an efficient manner. The range images are acquired by a state of the art SwissRanger SR-3000 camera making the projection process work in real-time....

Relative Pose Estimation and Accuracy Verification of Spherical Panoramic Image

Directory of Open Access Journals (Sweden)

XIE Donghai

2017-11-01

Full Text Available This paper improves the method of the traditional 5-point relative pose estimation algorithm, and proposes a relative pose estimation algorithm which is suitable for spherical panoramic images. The algorithm firstly computes the essential matrix, then decomposes the essential matrix to obtain the rotation matrix and the translation vector using SVD, and finally the reconstructed three-dimensional points are used to eliminate the error solution. The innovation of the algorithm lies the derivation of panorama epipolar formula and the use of the spherical distance from the point to the epipolar plane as the error term for the spherical panorama co-planarity function. The simulation experiment shows that when the random noise of the image feature points is within the range of pixel, the error of the three Euler angles is about 0.1°, and the error between the relative translational displacement and the simulated value is about 1.5°. The result of the experiment using the data obtained by the vehicle panorama camera and the POS shows that:the error of the roll angle and pitch angle can be within 0.2°, the error of the heading angle can be within 0.4°, and the error between the relative translational displacement and the POS can be within 2°. The result of our relative pose estimation algorithm is used to generate the spherical panoramic epipolar images, then we extract the key points between the spherical panoramic images and calculate the errors in the column direction. The result shows that the errors is less than 1 pixel.

A New Pose Estimation Algorithm Using a Perspective-Ray-Based Scaled Orthographic Projection with Iteration.

Directory of Open Access Journals (Sweden)

Pengfei Sun

Full Text Available Pose estimation aims at measuring the position and orientation of a calibrated camera using known image features. The pinhole model is the dominant camera model in this field. However, the imaging precision of this model is not accurate enough for an advanced pose estimation algorithm. In this paper, a new camera model, called incident ray tracking model, is introduced. More importantly, an advanced pose estimation algorithm based on the perspective ray in the new camera model, is proposed. The perspective ray, determined by two positioning points, is an abstract mathematical equivalent of the incident ray. In the proposed pose estimation algorithm, called perspective-ray-based scaled orthographic projection with iteration (PRSOI, an approximate ray-based projection is calculated by a linear system and refined by iteration. Experiments on the PRSOI have been conducted, and the results demonstrate that it is of high accuracy in the six degrees of freedom (DOF motion. And it outperforms three other state-of-the-art algorithms in terms of accuracy during the contrast experiment.

The Pose Estimation of Mobile Robot Based on Improved Point Cloud Registration

Directory of Open Access Journals (Sweden)

Yanzi Miao

2016-03-01

Full Text Available Due to GPS restrictions, an inertial sensor is usually used to estimate the location of indoor mobile robots. However, it is difficult to achieve high-accuracy localization and control by inertial sensors alone. In this paper, a new method is proposed to estimate an indoor mobile robot pose with six degrees of freedom based on an improved 3D-Normal Distributions Transform algorithm (3D-NDT. First, point cloud data are captured by a Kinect sensor and segmented according to the distance to the robot. After the segmentation, the input point cloud data are processed by the Approximate Voxel Grid Filter algorithm in different sized voxel grids. Second, the initial registration and precise registration are performed respectively according to the distance to the sensor. The most distant point cloud data use the 3D-Normal Distributions Transform algorithm (3D-NDT with large-sized voxel grids for initial registration, based on the transformation matrix from the odometry method. The closest point cloud data use the 3D-NDT algorithm with small-sized voxel grids for precise registration. After the registrations above, a final transformation matrix is obtained and coordinated. Based on this transformation matrix, the pose estimation problem of the indoor mobile robot is solved. Test results show that this method can obtain accurate robot pose estimation and has better robustness.

Estimation de pose omnidirectionnelle dans un contexte de réalité augmentée

OpenAIRE

Poirier, Stéphane

2012-01-01

Estimer la pose de la caméra est un défi fondamental en réalité augmentée et permet la superposition d’un modèle à la réalité. Estimer précisément la pose est souvent critique en ingénierie d’infrastructures. Les images omnidirectionnelles ont un champ de vision supérieur aux images planaires communément utilisées en RA. Cette propriété peut bénéficier à l’estimation de la pose. Or, aucun travail ne présente de résultats montrant clairement un gain de précision. Notre objectif est de quantifi...

An Improved Method of Pose Estimation for Lighthouse Base Station Extension.

Science.gov (United States)

Yang, Yi; Weng, Dongdong; Li, Dong; Xun, Hang

2017-10-22

In 2015, HTC and Valve launched a virtual reality headset empowered with Lighthouse, the cutting-edge space positioning technology. Although Lighthouse is superior in terms of accuracy, latency and refresh rate, its algorithms do not support base station expansion, and is flawed concerning occlusion in moving targets, that is, it is unable to calculate their poses with a small set of sensors, resulting in the loss of optical tracking data. In view of these problems, this paper proposes an improved pose estimation algorithm for cases where occlusion is involved. Our algorithm calculates the pose of a given object with a unified dataset comprising of inputs from sensors recognized by all base stations, as long as three or more sensors detect a signal in total, no matter from which base station. To verify our algorithm, HTC official base stations and autonomous developed receivers are used for prototyping. The experiment result shows that our pose calculation algorithm can achieve precise positioning when a few sensors detect the signal.

A combined vision-inertial fusion approach for 6-DoF object pose estimation

Science.gov (United States)

Li, Juan; Bernardos, Ana M.; Tarrío, Paula; Casar, José R.

2015-02-01

The estimation of the 3D position and orientation of moving objects (`pose' estimation) is a critical process for many applications in robotics, computer vision or mobile services. Although major research efforts have been carried out to design accurate, fast and robust indoor pose estimation systems, it remains as an open challenge to provide a low-cost, easy to deploy and reliable solution. Addressing this issue, this paper describes a hybrid approach for 6 degrees of freedom (6-DoF) pose estimation that fuses acceleration data and stereo vision to overcome the respective weaknesses of single technology approaches. The system relies on COTS technologies (standard webcams, accelerometers) and printable colored markers. It uses a set of infrastructure cameras, located to have the object to be tracked visible most of the operation time; the target object has to include an embedded accelerometer and be tagged with a fiducial marker. This simple marker has been designed for easy detection and segmentation and it may be adapted to different service scenarios (in shape and colors). Experimental results show that the proposed system provides high accuracy, while satisfactorily dealing with the real-time constraints.

Improving head and body pose estimation through semi-supervised manifold alignment

KAUST Repository

Heili, Alexandre

2014-10-27

In this paper, we explore the use of a semi-supervised manifold alignment method for domain adaptation in the context of human body and head pose estimation in videos. We build upon an existing state-of-the-art system that leverages on external labelled datasets for the body and head features, and on the unlabelled test data with weak velocity labels to do a coupled estimation of the body and head pose. While this previous approach showed promising results, the learning of the underlying manifold structure of the features in the train and target data and the need to align them were not explored despite the fact that the pose features between two datasets may vary according to the scene, e.g. due to different camera point of view or perspective. In this paper, we propose to use a semi-supervised manifold alignment method to bring the train and target samples closer within the resulting embedded space. To this end, we consider an adaptation set from the target data and rely on (weak) labels, given for example by the velocity direction whenever they are reliable. These labels, along with the training labels are used to bias the manifold distance within each manifold and to establish correspondences for alignment.

Attribute And-Or Grammar for Joint Parsing of Human Pose, Parts and Attributes.

Science.gov (United States)

Park, Seyoung; Nie, Xiaohan; Zhu, Song-Chun

2017-07-25

This paper presents an attribute and-or grammar (A-AOG) model for jointly inferring human body pose and human attributes in a parse graph with attributes augmented to nodes in the hierarchical representation. In contrast to other popular methods in the current literature that train separate classifiers for poses and individual attributes, our method explicitly represents the decomposition and articulation of body parts, and account for the correlations between poses and attributes. The A-AOG model is an amalgamation of three traditional grammar formulations: (i)Phrase structure grammar representing the hierarchical decomposition of the human body from whole to parts; (ii)Dependency grammar modeling the geometric articulation by a kinematic graph of the body pose; and (iii)Attribute grammar accounting for the compatibility relations between different parts in the hierarchy so that their appearances follow a consistent style. The parse graph outputs human detection, pose estimation, and attribute prediction simultaneously, which are intuitive and interpretable. We conduct experiments on two tasks on two datasets, and experimental results demonstrate the advantage of joint modeling in comparison with computing poses and attributes independently. Furthermore, our model obtains better performance over existing methods for both pose estimation and attribute prediction tasks.

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

Science.gov (United States)

Frikha, Rawia; Ejbali, Ridha; Zaied, Mourad

2017-09-01

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

Towards real-time body pose estimation for presenters in meeting environments

NARCIS (Netherlands)

Poppe, Ronald Walter; Heylen, Dirk K.J.; Nijholt, Antinus; Poel, Mannes

2005-01-01

This paper describes a computer vision-based approach to body pose estimation. The algorithm can be executed in real-time and processes low resolution, monocular image sequences. A silhouette is extracted and matched against a projection of a 16 DOF human body model. In addition, skin color is used

Input-output model for MACCS nuclear accident impacts estimation¹

Energy Technology Data Exchange (ETDEWEB)

Outkin, Alexander V. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bixler, Nathan E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vargas, Vanessa N [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-01-27

Since the original economic model for MACCS was developed, better quality economic data (as well as the tools to gather and process it) and better computational capabilities have become available. The update of the economic impacts component of the MACCS legacy model will provide improved estimates of business disruptions through the use of Input-Output based economic impact estimation. This paper presents an updated MACCS model, bases on Input-Output methodology, in which economic impacts are calculated using the Regional Economic Accounting analysis tool (REAcct) created at Sandia National Laboratories. This new GDP-based model allows quick and consistent estimation of gross domestic product (GDP) losses due to nuclear power plant accidents. This paper outlines the steps taken to combine the REAcct Input-Output-based model with the MACCS code, describes the GDP loss calculation, and discusses the parameters and modeling assumptions necessary for the estimation of long-term effects of nuclear power plant accidents.

Drogue pose estimation for unmanned aerial vehicle autonomous aerial refueling system based on infrared vision sensor

Science.gov (United States)

Chen, Shanjun; Duan, Haibin; Deng, Yimin; Li, Cong; Zhao, Guozhi; Xu, Yan

2017-12-01

Autonomous aerial refueling is a significant technology that can significantly extend the endurance of unmanned aerial vehicles. A reliable method that can accurately estimate the position and attitude of the probe relative to the drogue is the key to such a capability. A drogue pose estimation method based on infrared vision sensor is introduced with the general goal of yielding an accurate and reliable drogue state estimate. First, by employing direct least squares ellipse fitting and convex hull in OpenCV, a feature point matching and interference point elimination method is proposed. In addition, considering the conditions that some infrared LEDs are damaged or occluded, a missing point estimation method based on perspective transformation and affine transformation is designed. Finally, an accurate and robust pose estimation algorithm improved by the runner-root algorithm is proposed. The feasibility of the designed visual measurement system is demonstrated by flight test, and the results indicate that our proposed method enables precise and reliable pose estimation of the probe relative to the drogue, even in some poor conditions.

Structural Estimation of the Output Gap: A Bayesian DSGE Approach for the U.S. Economy

OpenAIRE

Yasuo Hirose; Saori Naganuma

2007-01-01

We estimate the output gap that is consistent with a fully specified DSGE model. Given the structural parameters estimated using Bayesian methods, we estimate the output gap that is defined as a deviation of output from its flexible-price equilibrium. Our output gap illustrates the U.S. business cycles well, compared with other estimates. We find that the main source of the output gap movements is the demand shocks, but that the productivity shocks contributed to the stable output gap in the ...

Joint Angle and Frequency Estimation Using Multiple-Delay Output Based on ESPRIT

Science.gov (United States)

Xudong, Wang

2010-12-01

This paper presents a novel ESPRIT algorithm-based joint angle and frequency estimation using multiple-delay output (MDJAFE). The algorithm can estimate the joint angles and frequencies, since the use of multiple output makes the estimation accuracy greatly improved when compared with a conventional algorithm. The useful behavior of the proposed algorithm is verified by simulations.

Automated pose estimation of objects using multiple ID devices for handling and maintenance task in nuclear fusion reactor

International Nuclear Information System (INIS)

Umetani, Tomohiro; Morioka, Jun-ichi; Tamura, Yuichi; Inoue, Kenji; Arai, Tatsuo; Mae, Yasusi

2011-01-01

This paper describes a method for the automated estimation of three-dimensional pose (position and orientation) of objects by autonomous robots, using multiple identification (ID) devices. Our goal is to estimate the object pose for assembly or maintenance tasks in a real nuclear fusion reactor system, with autonomous robots cooperating in a virtual assembly system. The method estimates the three-dimensional pose for autonomous robots. This paper discusses a method of motion generation for ID acquisition using the sensory data acquired by the measurement system attached to the robots and from the environment. Experimental results show the feasibility of the proposed method. (author)

NUI framework based on real-time head pose estimation and hand gesture recognition

Directory of Open Access Journals (Sweden)

Kim Hyunduk

2016-01-01

Full Text Available The natural user interface (NUI is used for the natural motion interface without using device or tool such as mice, keyboards, pens and markers. In this paper, we develop natural user interface framework based on two recognition module. First module is real-time head pose estimation module using random forests and second module is hand gesture recognition module, named Hand gesture Key Emulation Toolkit (HandGKET. Using the head pose estimation module, we can know where the user is looking and what the user’s focus of attention is. Moreover, using the hand gesture recognition module, we can also control the computer using the user’s hand gesture without mouse and keyboard. In proposed framework, the user’s head direction and hand gesture are mapped into mouse and keyboard event, respectively.

Head pose estimation from a 2D face image using 3D face morphing with depth parameters.

Science.gov (United States)

Kong, Seong G; Mbouna, Ralph Oyini

2015-06-01

This paper presents estimation of head pose angles from a single 2D face image using a 3D face model morphed from a reference face model. A reference model refers to a 3D face of a person of the same ethnicity and gender as the query subject. The proposed scheme minimizes the disparity between the two sets of prominent facial features on the query face image and the corresponding points on the 3D face model to estimate the head pose angles. The 3D face model used is morphed from a reference model to be more specific to the query face in terms of the depth error at the feature points. The morphing process produces a 3D face model more specific to the query image when multiple 2D face images of the query subject are available for training. The proposed morphing process is computationally efficient since the depth of a 3D face model is adjusted by a scalar depth parameter at feature points. Optimal depth parameters are found by minimizing the disparity between the 2D features of the query face image and the corresponding features on the morphed 3D model projected onto 2D space. The proposed head pose estimation technique was evaluated on two benchmarking databases: 1) the USF Human-ID database for depth estimation and 2) the Pointing'04 database for head pose estimation. Experiment results demonstrate that head pose estimation errors in nodding and shaking angles are as low as 7.93° and 4.65° on average for a single 2D input face image.

Multi-view 3D human pose estimation combining single-frame recovery, temporal integration and model adaptation

NARCIS (Netherlands)

Hofmann, K.M.; Gavrilla, D.M.

2009-01-01

We present a system for the estimation of unconstrained 3D human upper body movement from multiple cameras. Its main novelty lies in the integration of three components: single frame pose recovery, temporal integration and model adaptation. Single frame pose recovery consists of a hypothesis

Using Online Modelled Spatial Constraints for Pose Estimation in an Industrial Setting

DEFF Research Database (Denmark)

Meyer, Kenneth Korsgaard; Wolniakowski, Adam; Hagelskjær, Frederik

2017-01-01

We introduce a vision system that is able to on-line learn spatial constraints to improve pose estimation in terms of correct recognition as well as computational speed. By making use of a simulated industrial robot system performing various pick and place tasks, we show the effect of model...

3D head pose estimation and tracking using particle filtering and ICP algorithm

KAUST Repository

Ben Ghorbel, Mahdi; Baklouti, Malek; Couvet, Serge

2010-01-01

This paper addresses the issue of 3D head pose estimation and tracking. Existing approaches generally need huge database, training procedure, manual initialization or use face feature extraction manually extracted. We propose a framework for estimating the 3D head pose in its fine level and tracking it continuously across multiple Degrees of Freedom (DOF) based on ICP and particle filtering. We propose to approach the problem, using 3D computational techniques, by aligning a face model to the 3D dense estimation computed by a stereo vision method, and propose a particle filter algorithm to refine and track the posteriori estimate of the position of the face. This work comes with two contributions: the first concerns the alignment part where we propose an extended ICP algorithm using an anisotropic scale transformation. The second contribution concerns the tracking part. We propose the use of the particle filtering algorithm and propose to constrain the search space using ICP algorithm in the propagation step. The results show that the system is able to fit and track the head properly, and keeps accurate the results on new individuals without a manual adaptation or training. © Springer-Verlag Berlin Heidelberg 2010.

Voxel-based registration of simulated and real patient CBCT data for accurate dental implant pose estimation

Science.gov (United States)

Moreira, António H. J.; Queirós, Sandro; Morais, Pedro; Rodrigues, Nuno F.; Correia, André Ricardo; Fernandes, Valter; Pinho, A. C. M.; Fonseca, Jaime C.; Vilaça, João. L.

2015-03-01

The success of dental implant-supported prosthesis is directly linked to the accuracy obtained during implant's pose estimation (position and orientation). Although traditional impression techniques and recent digital acquisition methods are acceptably accurate, a simultaneously fast, accurate and operator-independent methodology is still lacking. Hereto, an image-based framework is proposed to estimate the patient-specific implant's pose using cone-beam computed tomography (CBCT) and prior knowledge of implanted model. The pose estimation is accomplished in a threestep approach: (1) a region-of-interest is extracted from the CBCT data using 2 operator-defined points at the implant's main axis; (2) a simulated CBCT volume of the known implanted model is generated through Feldkamp-Davis-Kress reconstruction and coarsely aligned to the defined axis; and (3) a voxel-based rigid registration is performed to optimally align both patient and simulated CBCT data, extracting the implant's pose from the optimal transformation. Three experiments were performed to evaluate the framework: (1) an in silico study using 48 implants distributed through 12 tridimensional synthetic mandibular models; (2) an in vitro study using an artificial mandible with 2 dental implants acquired with an i-CAT system; and (3) two clinical case studies. The results shown positional errors of 67+/-34μm and 108μm, and angular misfits of 0.15+/-0.08° and 1.4°, for experiment 1 and 2, respectively. Moreover, in experiment 3, visual assessment of clinical data results shown a coherent alignment of the reference implant. Overall, a novel image-based framework for implants' pose estimation from CBCT data was proposed, showing accurate results in agreement with dental prosthesis modelling requirements.

Utilizing Semantic Interpretation of Junctions for 3D-2D Pose Estimation

DEFF Research Database (Denmark)

Pilz, Florian; Yan, Shi; Grest, Daniel

2007-01-01

In this paper we investigate the quality of 3D-2D pose estimates using hand labeled line and point correspondences. We select point correspondences from junctions in the image, allowing to construct a meaningful interpretation about how the junction is formed, as proposed in e.g. [1], [2], [3]. W...

Robustness of Input features from Noisy Silhouettes in Human Pose Estimation

DEFF Research Database (Denmark)

Gong, Wenjuan; Fihl, Preben; Gonzàlez, Jordi

2014-01-01

. In this paper, we explore this problem. First, We compare performances of several image features widely used for human pose estimation and explore their performances against each other and select one with best performance. Second, iterative closest point algorithm is introduced for a new quantitative...... of silhouette samples of different noise levels and compare with the selected feature on a public dataset: Human Eva dataset....

Estimation of G-renewal process parameters as an ill-posed inverse problem

International Nuclear Information System (INIS)

Krivtsov, V.; Yevkin, O.

2013-01-01

Statistical estimation of G-renewal process parameters is an important estimation problem, which has been considered by many authors. We view this problem from the standpoint of a mathematically ill-posed, inverse problem (the solution is not unique and/or is sensitive to statistical error) and propose a regularization approach specifically suited to the G-renewal process. Regardless of the estimation method, the respective objective function usually involves parameters of the underlying life-time distribution and simultaneously the restoration parameter. In this paper, we propose to regularize the problem by decoupling the estimation of the aforementioned parameters. Using a simulation study, we show that the resulting estimation/extrapolation accuracy of the proposed method is considerably higher than that of the existing methods

Regularization parameter selection methods for ill-posed Poisson maximum likelihood estimation

International Nuclear Information System (INIS)

Bardsley, Johnathan M; Goldes, John

2009-01-01

In image processing applications, image intensity is often measured via the counting of incident photons emitted by the object of interest. In such cases, image data noise is accurately modeled by a Poisson distribution. This motivates the use of Poisson maximum likelihood estimation for image reconstruction. However, when the underlying model equation is ill-posed, regularization is needed. Regularized Poisson likelihood estimation has been studied extensively by the authors, though a problem of high importance remains: the choice of the regularization parameter. We will present three statistically motivated methods for choosing the regularization parameter, and numerical examples will be presented to illustrate their effectiveness

6-DOF Pose Estimation of a Robotic Navigation Aid by Tracking Visual and Geometric Features.

Science.gov (United States)

Ye, Cang; Hong, Soonhac; Tamjidi, Amirhossein

2015-10-01

This paper presents a 6-DOF Pose Estimation (PE) method for a Robotic Navigation Aid (RNA) for the visually impaired. The RNA uses a single 3D camera for PE and object detection. The proposed method processes the camera's intensity and range data to estimates the camera's egomotion that is then used by an Extended Kalman Filter (EKF) as the motion model to track a set of visual features for PE. A RANSAC process is employed in the EKF to identify inliers from the visual feature correspondences between two image frames. Only the inliers are used to update the EKF's state. The EKF integrates the egomotion into the camera's pose in the world coordinate system. To retain the EKF's consistency, the distance between the camera and the floor plane (extracted from the range data) is used by the EKF as the observation of the camera's z coordinate. Experimental results demonstrate that the proposed method results in accurate pose estimates for positioning the RNA in indoor environments. Based on the PE method, a wayfinding system is developed for localization of the RNA in a home environment. The system uses the estimated pose and the floorplan to locate the RNA user in the home environment and announces the points of interest and navigational commands to the user through a speech interface. This work was motivated by the limitations of the existing navigation technology for the visually impaired. Most of the existing methods use a point/line measurement sensor for indoor object detection. Therefore, they lack capability in detecting 3D objects and positioning a blind traveler. Stereovision has been used in recent research. However, it cannot provide reliable depth data for object detection. Also, it tends to produce a lower localization accuracy because its depth measurement error quadratically increases with the true distance. This paper suggests a new approach for navigating a blind traveler. The method uses a single 3D time-of-flight camera for both 6-DOF PE and 3D object

3D pose estimation and motion analysis of the articulated human hand-forearm limb in an industrial production environment

Science.gov (United States)

Hahn, Markus; Barrois, Björn; Krüger, Lars; Wöhler, Christian; Sagerer, Gerhard; Kummert, Franz

2010-09-01

This study introduces an approach to model-based 3D pose estimation and instantaneous motion analysis of the human hand-forearm limb in the application context of safe human-robot interaction. 3D pose estimation is performed using two approaches: The Multiocular Contracting Curve Density (MOCCD) algorithm is a top-down technique based on pixel statistics around a contour model projected into the images from several cameras. The Iterative Closest Point (ICP) algorithm is a bottom-up approach which uses a motion-attributed 3D point cloud to estimate the object pose. Due to their orthogonal properties, a fusion of these algorithms is shown to be favorable. The fusion is performed by a weighted combination of the extracted pose parameters in an iterative manner. The analysis of object motion is based on the pose estimation result and the motion-attributed 3D points belonging to the hand-forearm limb using an extended constraint-line approach which does not rely on any temporal filtering. A further refinement is obtained using the Shape Flow algorithm, a temporal extension of the MOCCD approach, which estimates the temporal pose derivative based on the current and the two preceding images, corresponding to temporal filtering with a short response time of two or at most three frames. Combining the results of the two motion estimation stages provides information about the instantaneous motion properties of the object. Experimental investigations are performed on real-world image sequences displaying several test persons performing different working actions typically occurring in an industrial production scenario. In all example scenes, the background is cluttered, and the test persons wear various kinds of clothes. For evaluation, independently obtained ground truth data are used. [Figure not available: see fulltext.

Surgical fiducial segmentation and tracking for pose estimation based on ultrasound B-mode images.

Science.gov (United States)

Lei Chen; Kuo, Nathanael; Aalamifar, Fereshteh; Narrow, David; Coon, Devin; Prince, Jerry; Boctor, Emad M

2016-08-01

Doppler ultrasound is a non-invasive diagnostic tool for the quantitative measurement of blood flow. However, given that it provides velocity data that is dependent on the location and angle of measurement, repeat measurements to detect problems over time may require an expert to return to the same location. We therefore developed an image-guidance system based on ultrasound B-mode images that enables an inexperienced user to position the ultrasound probe at the same site repeatedly in order to acquire a comparable time series of Doppler readings. The system utilizes a bioresorbable fiducial and complementing software composed of the fiducial detection, key points tracking, probe pose estimation, and graphical user interface (GUI) modules. The fiducial is an echogenic marker that is implanted at the surgical site and can be detected and tracked during ultrasound B-mode screening. The key points on the marker can next be used to determine the pose of the ultrasound probe with respect to the marker. The 3D representation of the probe with its position and orientation are then displayed in the GUI for the user guidance. The fiducial detection has been tested on the data sets collected from three animal studies. The pose estimation algorithm was validated by five data sets collected by a UR5 robot. We tested the system on a plastisol phantom and showed that it can detect and track the fiducial marker while displaying the probe pose in real-time.

Marker detection evaluation by phantom and cadaver experiments for C-arm pose estimation pattern

Science.gov (United States)

Steger, Teena; Hoßbach, Martin; Wesarg, Stefan

2013-03-01

C-arm fluoroscopy is used for guidance during several clinical exams, e.g. in bronchoscopy to locate the bronchoscope inside the airways. Unfortunately, these images provide only 2D information. However, if the C-arm pose is known, it can be used to overlay the intrainterventional fluoroscopy images with 3D visualizations of airways, acquired from preinterventional CT images. Thus, the physician's view is enhanced and localization of the instrument at the correct position inside the bronchial tree is facilitated. We present a novel method for C-arm pose estimation introducing a marker-based pattern, which is placed on the patient table. The steel markers form a pattern, allowing to deduce the C-arm pose by use of the projective invariant cross-ratio. Simulations show that the C-arm pose estimation is reliable and accurate for translations inside an imaging area of 30 cm x 50 cm and rotations up to 30°. Mean error values are 0.33 mm in 3D space and 0.48 px in the 2D imaging plane. First tests on C-arm images resulted in similarly compelling accuracy values and high reliability in an imaging area of 30 cm x 42.5 cm. Even in the presence of interfering structures, tested both with anatomy phantoms and a turkey cadaver, high success rates over 90% and fully satisfying execution times below 4 sec for 1024 px × 1024 px images could be achieved.

Methods of RVD object pose estimation and experiments

Science.gov (United States)

Shang, Yang; He, Yan; Wang, Weihua; Yu, Qifeng

2007-11-01

Methods of measuring a RVD (rendezvous and docking) cooperative object's pose from monocular and binocular images respectively are presented. The methods solve the initial values first and optimize the object pose parameters by bundle adjustment. In the disturbance-rejecting binocular method, chosen measurement system parameters of one camera's exterior parameters are modified simultaneously. The methods need three or more cooperative target points to measure the object's pose accurately. Experimental data show that the methods converge quickly and stably, provide accurate results and do not need accurate initial values. Even when the chosen measurement system parameters are subjected to some amount of disturbance, the binocular method manages to provide fairly accurate results.

Estimation of continuous multi-DOF finger joint kinematics from surface EMG using a multi-output Gaussian Process.

Science.gov (United States)

Ngeo, Jimson; Tamei, Tomoya; Shibata, Tomohiro

2014-01-01

Surface electromyographic (EMG) signals have often been used in estimating upper and lower limb dynamics and kinematics for the purpose of controlling robotic devices such as robot prosthesis and finger exoskeletons. However, in estimating multiple and a high number of degrees-of-freedom (DOF) kinematics from EMG, output DOFs are usually estimated independently. In this study, we estimate finger joint kinematics from EMG signals using a multi-output convolved Gaussian Process (Multi-output Full GP) that considers dependencies between outputs. We show that estimation of finger joints from muscle activation inputs can be improved by using a regression model that considers inherent coupling or correlation within the hand and finger joints. We also provide a comparison of estimation performance between different regression methods, such as Artificial Neural Networks (ANN) which is used by many of the related studies. We show that using a multi-output GP gives improved estimation compared to multi-output ANN and even dedicated or independent regression models.

Probabilistic Mapping of Human Visual Attention from Head Pose Estimation

Directory of Open Access Journals (Sweden)

Andrea Veronese

2017-10-01

Full Text Available Effective interaction between a human and a robot requires the bidirectional perception and interpretation of actions and behavior. While actions can be identified as a directly observable activity, this might not be sufficient to deduce actions in a scene. For example, orienting our face toward a book might suggest the action toward “reading.” For a human observer, this deduction requires the direction of gaze, the object identified as a book and the intersection between gaze and book. With this in mind, we aim to estimate and map human visual attention as directed to a scene, and assess how this relates to the detection of objects and their related actions. In particular, we consider human head pose as measurement to infer the attention of a human engaged in a task and study which prior knowledge should be included in such a detection system. In a user study, we show the successful detection of attention to objects in a typical office task scenario (i.e., reading, working with a computer, studying an object. Our system requires a single external RGB camera for head pose measurements and a pre-recorded 3D point cloud of the environment.

Camera-pose estimation via projective Newton optimization on the manifold.

Science.gov (United States)

Sarkis, Michel; Diepold, Klaus

2012-04-01

Determining the pose of a moving camera is an important task in computer vision. In this paper, we derive a projective Newton algorithm on the manifold to refine the pose estimate of a camera. The main idea is to benefit from the fact that the 3-D rigid motion is described by the special Euclidean group, which is a Riemannian manifold. The latter is equipped with a tangent space defined by the corresponding Lie algebra. This enables us to compute the optimization direction, i.e., the gradient and the Hessian, at each iteration of the projective Newton scheme on the tangent space of the manifold. Then, the motion is updated by projecting back the variables on the manifold itself. We also derive another version of the algorithm that employs homeomorphic parameterization to the special Euclidean group. We test the algorithm on several simulated and real image data sets. Compared with the standard Newton minimization scheme, we are now able to obtain the full numerical formula of the Hessian with a 60% decrease in computational complexity. Compared with Levenberg-Marquardt, the results obtained are more accurate while having a rather similar complexity.

Segmentation, classification, and pose estimation of military vehicles in low resolution laser radar images

Science.gov (United States)

Neulist, Joerg; Armbruster, Walter

2005-05-01

Model-based object recognition in range imagery typically involves matching the image data to the expected model data for each feasible model and pose hypothesis. Since the matching procedure is computationally expensive, the key to efficient object recognition is the reduction of the set of feasible hypotheses. This is particularly important for military vehicles, which may consist of several large moving parts such as the hull, turret, and gun of a tank, and hence require an eight or higher dimensional pose space to be searched. The presented paper outlines techniques for reducing the set of feasible hypotheses based on an estimation of target dimensions and orientation. Furthermore, the presence of a turret and a main gun and their orientations are determined. The vehicle parts dimensions as well as their error estimates restrict the number of model hypotheses whereas the position and orientation estimates and their error bounds reduce the number of pose hypotheses needing to be verified. The techniques are applied to several hundred laser radar images of eight different military vehicles with various part classifications and orientations. On-target resolution in azimuth, elevation and range is about 30 cm. The range images contain up to 20% dropouts due to atmospheric absorption. Additionally some target retro-reflectors produce outliers due to signal crosstalk. The presented algorithms are extremely robust with respect to these and other error sources. The hypothesis space for hull orientation is reduced to about 5 degrees as is the error for turret rotation and gun elevation, provided the main gun is visible.

Exemplar-based human action pose correction.

Science.gov (United States)

Shen, Wei; Deng, Ke; Bai, Xiang; Leyvand, Tommer; Guo, Baining; Tu, Zhuowen

2014-07-01

The launch of Xbox Kinect has built a very successful computer vision product and made a big impact on the gaming industry. This sheds lights onto a wide variety of potential applications related to action recognition. The accurate estimation of human poses from the depth image is universally a critical step. However, existing pose estimation systems exhibit failures when facing severe occlusion. In this paper, we propose an exemplar-based method to learn to correct the initially estimated poses. We learn an inhomogeneous systematic bias by leveraging the exemplar information within a specific human action domain. Furthermore, as an extension, we learn a conditional model by incorporation of pose tags to further increase the accuracy of pose correction. In the experiments, significant improvements on both joint-based skeleton correction and tag prediction are observed over the contemporary approaches, including what is delivered by the current Kinect system. Our experiments for the facial landmark correction also illustrate that our algorithm can improve the accuracy of other detection/estimation systems.

Simulation-Based Optimization of Camera Placement in the Context of Industrial Pose Estimation

DEFF Research Database (Denmark)

Jørgensen, Troels Bo; Iversen, Thorbjørn Mosekjær; Lindvig, Anders Prier

2018-01-01

In this paper, we optimize the placement of a camera in simulation in order to achieve a high success rate for a pose estimation problem. This is achieved by simulating 2D images from a stereo camera in a virtual scene. The stereo images are then used to generate 3D point clouds based on two diff...

Neuro-fuzzy model for estimating race and gender from geometric distances of human face across pose

Science.gov (United States)

Nanaa, K.; Rahman, M. N. A.; Rizon, M.; Mohamad, F. S.; Mamat, M.

2018-03-01

Classifying human face based on race and gender is a vital process in face recognition. It contributes to an index database and eases 3D synthesis of the human face. Identifying race and gender based on intrinsic factor is problematic, which is more fitting to utilizing nonlinear model for estimating process. In this paper, we aim to estimate race and gender in varied head pose. For this purpose, we collect dataset from PICS and CAS-PEAL databases, detect the landmarks and rotate them to the frontal pose. After geometric distances are calculated, all of distance values will be normalized. Implementation is carried out by using Neural Network Model and Fuzzy Logic Model. These models are combined by using Adaptive Neuro-Fuzzy Model. The experimental results showed that the optimization of address fuzzy membership. Model gives a better assessment rate and found that estimating race contributing to a more accurate gender assessment.

Estimation of Individual Cylinder Air-Fuel Ratio in Gasoline Engine with Output Delay

Directory of Open Access Journals (Sweden)

Changhui Wang

2016-01-01

Full Text Available The estimation of the individual cylinder air-fuel ratio (AFR with a single universal exhaust gas oxygen (UEGO sensor installed in the exhaust pipe is an important issue for the cylinder-to-cylinder AFR balancing control, which can provide high-quality torque generation and reduce emissions in multicylinder engine. In this paper, the system dynamic for the gas in exhaust pipe including the gas mixing, gas transport, and sensor dynamics is described as an output delay system, and a new method using the output delay system observer is developed to estimate the individual cylinder AFR. With the AFR at confluence point augmented as a system state, an observer for the augmented discrete system with output delay is designed to estimate the AFR at confluence point. Using the gas mixing model, a method with the designed observer to estimate the individual cylinder AFR is presented. The validity of the proposed method is verified by the simulation results from a spark ignition gasoline engine from engine software enDYNA by Tesis.

An investigation into multi-dimensional prediction models to estimate the pose error of a quadcopter in a CSP plant setting

Science.gov (United States)

Lock, Jacobus C.; Smit, Willie J.; Treurnicht, Johann

2016-05-01

The Solar Thermal Energy Research Group (STERG) is investigating ways to make heliostats cheaper to reduce the total cost of a concentrating solar power (CSP) plant. One avenue of research is to use unmanned aerial vehicles (UAVs) to automate and assist with the heliostat calibration process. To do this, the pose estimation error of each UAV must be determined and integrated into a calibration procedure. A computer vision (CV) system is used to measure the pose of a quadcopter UAV. However, this CV system contains considerable measurement errors. Since this is a high-dimensional problem, a sophisticated prediction model must be used to estimate the measurement error of the CV system for any given pose measurement vector. This paper attempts to train and validate such a model with the aim of using it to determine the pose error of a quadcopter in a CSP plant setting.

An Inertial and Optical Sensor Fusion Approach for Six Degree-of-Freedom Pose Estimation

Science.gov (United States)

He, Changyu; Kazanzides, Peter; Sen, Hasan Tutkun; Kim, Sungmin; Liu, Yue

2015-01-01

Optical tracking provides relatively high accuracy over a large workspace but requires line-of-sight between the camera and the markers, which may be difficult to maintain in actual applications. In contrast, inertial sensing does not require line-of-sight but is subject to drift, which may cause large cumulative errors, especially during the measurement of position. To handle cases where some or all of the markers are occluded, this paper proposes an inertial and optical sensor fusion approach in which the bias of the inertial sensors is estimated when the optical tracker provides full six degree-of-freedom (6-DOF) pose information. As long as the position of at least one marker can be tracked by the optical system, the 3-DOF position can be combined with the orientation estimated from the inertial measurements to recover the full 6-DOF pose information. When all the markers are occluded, the position tracking relies on the inertial sensors that are bias-corrected by the optical tracking system. Experiments are performed with an augmented reality head-mounted display (ARHMD) that integrates an optical tracking system (OTS) and inertial measurement unit (IMU). Experimental results show that under partial occlusion conditions, the root mean square errors (RMSE) of orientation and position are 0.04° and 0.134 mm, and under total occlusion conditions for 1 s, the orientation and position RMSE are 0.022° and 0.22 mm, respectively. Thus, the proposed sensor fusion approach can provide reliable 6-DOF pose under long-term partial occlusion and short-term total occlusion conditions. PMID:26184191

Extended 3D Line Segments from RGB-D Data for Pose Estimation

DEFF Research Database (Denmark)

Buch, Anders Glent; Jessen, Jeppe Barsøe; Kraft, Dirk

2013-01-01

We propose a method for the extraction of complete and rich symbolic line segments in 3D based on RGB-D data. Edges are detected by combining cues from the RGB image and the aligned depth map. 3D line segments are then reconstructed by back-projecting 2D line segments and intersecting this with l...... this with local surface patches computed from the 3D point cloud. Different edge types are classified using the new enriched representation and the potential of this representation for the task of pose estimation is demonstrated....

Estimation of the Maximum Output Power of Double-Clad Photonic Crystal Fiber Laser

International Nuclear Information System (INIS)

Chen Yue-E; Wang Yong; Qu Xi-Long

2012-01-01

Compared with traditional optical fiber lasers, double-clad photonic crystal fiber (PCF) lasers have larger surface-area-to-volume ratios. With an increase of output power, thermal effects may severely restrict output power and deteriorate beam quality of fiber lasers. We utilize the heat-conduction equations to estimate the maximum output power of a double-clad PCF laser under natural-convection, air-cooling, and water-cooling conditions in terms of a certain surface-volume heat ratio of the PCF. The thermal effects hence define an upper power limit of double-clad PCF lasers when scaling output power. (fundamental areas of phenomenology(including applications))

Dynamic Estimation on Output Elasticity of Highway Capital Stock in China

Science.gov (United States)

Li, W. J.; Zuo, Q. L.; Bai, Y. F.

2017-12-01

By using the Perpetual Inventory Method to calculate the capital stock of highway in China from 1988 to 2016, the paper builds the State Space Model based on Translog Production Function, according to the Ridge Regression and Kalman Filter Method, the dynamic estimation results of output elasticity are measured continuously and analyzed. The conclusions show that: Firstly, China’s growth speed on highway industry capital stock are divided into three stages which are respectively from 1988 to 2000, from 2001 to 2009 and from 2010 to 2016, during which shows steady growth, between which reflect rapid growth; Secondly, the output elasticity of highway capital stock, being between 0.154 and 0.248, is slightly larger than the output elasticity of human input factor, lower than the output elasticity of the technical level, shows positive effect on transport economy and rises steadily, but the output efficiency is low on the whole; Thirdly, around the year of 2010, the scale pay on highway industry begins to highlight the characteristic of increase.

A Comparison of Iterative 2D-3D Pose Estimation Methods for Real-Time Applications

DEFF Research Database (Denmark)

Grest, Daniel; Krüger, Volker; Petersen, Thomas

2009-01-01

This work compares iterative 2D-3D Pose Estimation methods for use in real-time applications. The compared methods are available for public as C++ code. One method is part of the openCV library, namely POSIT. Because POSIT is not applicable for planar 3Dpoint congurations, we include the planar P...

Estimation of international output-energy relation. Effects of alternative output measures

International Nuclear Information System (INIS)

Shrestha, R.M.

2000-01-01

This paper analyzes the output-energy relationship with alternative measures of output and energy. Our analysis rejects the hypothesis of non-diminishing returns to energy consumption when GDP at purchasing power parities is used as the output measure unlike the case with GNP at market exchange rates. This finding also holds when energy input includes the usage of both commercial and traditional fuels. 13 refs

Dynamic Output Feedback Robust MPC with Input Saturation Based on Zonotopic Set-Membership Estimation

Directory of Open Access Journals (Sweden)

Xubin Ping

2016-01-01

Full Text Available For quasi-linear parameter varying (quasi-LPV systems with bounded disturbance, a synthesis approach of dynamic output feedback robust model predictive control (OFRMPC with the consideration of input saturation is investigated. The saturated dynamic output feedback controller is represented by a convex hull involving the actual dynamic output controller and an introduced auxiliary controller. By taking both the actual output feedback controller and the auxiliary controller with a parameter-dependent form, the main optimization problem can be formulated as convex optimization. The consideration of input saturation in the main optimization problem reduces the conservatism of dynamic output feedback controller design. The estimation error set and bounded disturbance are represented by zonotopes and refreshed by zonotopic set-membership estimation. Compared with the previous results, the proposed algorithm can not only guarantee the recursive feasibility of the optimization problem, but also improve the control performance at the cost of higher computational burden. A nonlinear continuous stirred tank reactor (CSTR example is given to illustrate the effectiveness of the approach.

Human Pose Estimation and Activity Recognition from Multi-View Videos

DEFF Research Database (Denmark)

Holte, Michael Boelstoft; Tran, Cuong; Trivedi, Mohan

2012-01-01

approaches which have been proposed to comply with these requirements. We report a comparison of the most promising methods for multi-view human action recognition using two publicly available datasets: the INRIA Xmas Motion Acquisition Sequences (IXMAS) Multi-View Human Action Dataset, and the i3DPost Multi......–computer interaction (HCI), assisted living, gesture-based interactive games, intelligent driver assistance systems, movies, 3D TV and animation, physical therapy, autonomous mental development, smart environments, sport motion analysis, video surveillance, and video annotation. Next, we review and categorize recent......-View Human Action and Interaction Dataset. To compare the proposed methods, we give a qualitative assessment of methods which cannot be compared quantitatively, and analyze some prominent 3D pose estimation techniques for application, where not only the performed action needs to be identified but a more...

Comparison of different methods for gender estimation from face image of various poses

Science.gov (United States)

Ishii, Yohei; Hongo, Hitoshi; Niwa, Yoshinori; Yamamoto, Kazuhiko

2003-04-01

Recently, gender estimation from face images has been studied for frontal facial images. However, it is difficult to obtain such facial images constantly in the case of application systems for security, surveillance and marketing research. In order to build such systems, a method is required to estimate gender from the image of various facial poses. In this paper, three different classifiers are compared in appearance-based gender estimation, which use four directional features (FDF). The classifiers are linear discriminant analysis (LDA), Support Vector Machines (SVMs) and Sparse Network of Winnows (SNoW). Face images used for experiments were obtained from 35 viewpoints. The direction of viewpoints varied +/-45 degrees horizontally, +/-30 degrees vertically at 15 degree intervals respectively. Although LDA showed the best performance for frontal facial images, SVM with Gaussian kernel was found the best performance (86.0%) for the facial images of 35 viewpoints. It is considered that SVM with Gaussian kernel is robust to changes in viewpoint when estimating gender from these results. Furthermore, the estimation rate was quite close to the average estimation rate at 35 viewpoints respectively. It is supposed that the methods are reasonable to estimate gender within the range of experimented viewpoints by learning face images from multiple directions by one class.

Head Pose Estimation from Passive Stereo Images

DEFF Research Database (Denmark)

Breitenstein, Michael D.; Jensen, Jeppe; Høilund, Carsten

2009-01-01

function. Our algorithm incorporates 2D and 3D cues to make the system robust to low-quality range images acquired by passive stereo systems. It handles large pose variations (of ±90 ° yaw and ±45 ° pitch rotation) and facial variations due to expressions or accessories. For a maximally allowed error of 30...

Long-term energy output estimation for photovoltaic energy systems using synthetic solar irradiation data

International Nuclear Information System (INIS)

Celik, A.N.

2003-01-01

A general methodology is presented to estimate the monthly average daily energy output from photovoltaic energy systems. Energy output is estimated from synthetically generated solar radiation data. The synthetic solar radiation data are generated based on the cumulative frequency distribution of the daily clearness index, given as a function of the monthly clearness index. Two sets of synthetic solar irradiation data are generated: 3- and 4-day months. In the 3-day month, each month is represented by 3 days and in the 4-day month, by 4 days. The 3- and 4-day solar irradiation data are synthetically generated for each month and the corresponding energy outputs are calculated. A total of 8-year long measured hourly solar irradiation data, from five different locations in the world, is used to validate the new model. The monthly energy output values calculated from the synthetic solar irradiation data are compared to those calculated from the measured hour-by-hour data. It is shown that when the measured solar radiation data do not exist for a particular location or reduced data set is advantageous, the energy output from photovoltaic converters could be correctly calculated

Soft tissue navigation for laparoscopic prostatectomy: evaluation of camera pose estimation for enhanced visualization

Science.gov (United States)

Baumhauer, M.; Simpfendörfer, T.; Schwarz, R.; Seitel, M.; Müller-Stich, B. P.; Gutt, C. N.; Rassweiler, J.; Meinzer, H.-P.; Wolf, I.

2007-03-01

We introduce a novel navigation system to support minimally invasive prostate surgery. The system utilizes transrectal ultrasonography (TRUS) and needle-shaped navigation aids to visualize hidden structures via Augmented Reality. During the intervention, the navigation aids are segmented once from a 3D TRUS dataset and subsequently tracked by the endoscope camera. Camera Pose Estimation methods directly determine position and orientation of the camera in relation to the navigation aids. Accordingly, our system does not require any external tracking device for registration of endoscope camera and ultrasonography probe. In addition to a preoperative planning step in which the navigation targets are defined, the procedure consists of two main steps which are carried out during the intervention: First, the preoperatively prepared planning data is registered with an intraoperatively acquired 3D TRUS dataset and the segmented navigation aids. Second, the navigation aids are continuously tracked by the endoscope camera. The camera's pose can thereby be derived and relevant medical structures can be superimposed on the video image. This paper focuses on the latter step. We have implemented several promising real-time algorithms and incorporated them into the Open Source Toolkit MITK (www.mitk.org). Furthermore, we have evaluated them for minimally invasive surgery (MIS) navigation scenarios. For this purpose, a virtual evaluation environment has been developed, which allows for the simulation of navigation targets and navigation aids, including their measurement errors. Besides evaluating the accuracy of the computed pose, we have analyzed the impact of an inaccurate pose and the resulting displacement of navigation targets in Augmented Reality.

Face pose tracking using the four-point algorithm

Science.gov (United States)

Fung, Ho Yin; Wong, Kin Hong; Yu, Ying Kin; Tsui, Kwan Pang; Kam, Ho Chuen

2017-06-01

In this paper, we have developed an algorithm to track the pose of a human face robustly and efficiently. Face pose estimation is very useful in many applications such as building virtual reality systems and creating an alternative input method for the disabled. Firstly, we have modified a face detection toolbox called DLib for the detection of a face in front of a camera. The detected face features are passed to a pose estimation method, known as the four-point algorithm, for pose computation. The theory applied and the technical problems encountered during system development are discussed in the paper. It is demonstrated that the system is able to track the pose of a face in real time using a consumer grade laptop computer.

On the generalization of linear least mean squares estimation to quantum systems with non-commutative outputs

Energy Technology Data Exchange (ETDEWEB)

Amini, Nina H. [Stanford University, Edward L. Ginzton Laboratory, Stanford, CA (United States); CNRS, Laboratoire des Signaux et Systemes (L2S) CentraleSupelec, Gif-sur-Yvette (France); Miao, Zibo; Pan, Yu; James, Matthew R. [Australian National University, ARC Centre for Quantum Computation and Communication Technology, Research School of Engineering, Canberra, ACT (Australia); Mabuchi, Hideo [Stanford University, Edward L. Ginzton Laboratory, Stanford, CA (United States)

2015-12-15

The purpose of this paper is to study the problem of generalizing the Belavkin-Kalman filter to the case where the classical measurement signal is replaced by a fully quantum non-commutative output signal. We formulate a least mean squares estimation problem that involves a non-commutative system as the filter processing the non-commutative output signal. We solve this estimation problem within the framework of non-commutative probability. Also, we find the necessary and sufficient conditions which make these non-commutative estimators physically realizable. These conditions are restrictive in practice. (orig.)

Enhancing e-waste estimates: Improving data quality by multivariate Input–Output Analysis

Energy Technology Data Exchange (ETDEWEB)

Wang, Feng, E-mail: fwang@unu.edu [Institute for Sustainability and Peace, United Nations University, Hermann-Ehler-Str. 10, 53113 Bonn (Germany); Design for Sustainability Lab, Faculty of Industrial Design Engineering, Delft University of Technology, Landbergstraat 15, 2628CE Delft (Netherlands); Huisman, Jaco [Institute for Sustainability and Peace, United Nations University, Hermann-Ehler-Str. 10, 53113 Bonn (Germany); Design for Sustainability Lab, Faculty of Industrial Design Engineering, Delft University of Technology, Landbergstraat 15, 2628CE Delft (Netherlands); Stevels, Ab [Design for Sustainability Lab, Faculty of Industrial Design Engineering, Delft University of Technology, Landbergstraat 15, 2628CE Delft (Netherlands); Baldé, Cornelis Peter [Institute for Sustainability and Peace, United Nations University, Hermann-Ehler-Str. 10, 53113 Bonn (Germany); Statistics Netherlands, Henri Faasdreef 312, 2492 JP Den Haag (Netherlands)

2013-11-15

Highlights: • A multivariate Input–Output Analysis method for e-waste estimates is proposed. • Applying multivariate analysis to consolidate data can enhance e-waste estimates. • We examine the influence of model selection and data quality on e-waste estimates. • Datasets of all e-waste related variables in a Dutch case study have been provided. • Accurate modeling of time-variant lifespan distributions is critical for estimate. - Abstract: Waste electrical and electronic equipment (or e-waste) is one of the fastest growing waste streams, which encompasses a wide and increasing spectrum of products. Accurate estimation of e-waste generation is difficult, mainly due to lack of high quality data referred to market and socio-economic dynamics. This paper addresses how to enhance e-waste estimates by providing techniques to increase data quality. An advanced, flexible and multivariate Input–Output Analysis (IOA) method is proposed. It links all three pillars in IOA (product sales, stock and lifespan profiles) to construct mathematical relationships between various data points. By applying this method, the data consolidation steps can generate more accurate time-series datasets from available data pool. This can consequently increase the reliability of e-waste estimates compared to the approach without data processing. A case study in the Netherlands is used to apply the advanced IOA model. As a result, for the first time ever, complete datasets of all three variables for estimating all types of e-waste have been obtained. The result of this study also demonstrates significant disparity between various estimation models, arising from the use of data under different conditions. It shows the importance of applying multivariate approach and multiple sources to improve data quality for modelling, specifically using appropriate time-varying lifespan parameters. Following the case study, a roadmap with a procedural guideline is provided to enhance e

Enhancing e-waste estimates: Improving data quality by multivariate Input–Output Analysis

International Nuclear Information System (INIS)

Wang, Feng; Huisman, Jaco; Stevels, Ab; Baldé, Cornelis Peter

2013-01-01

Highlights: • A multivariate Input–Output Analysis method for e-waste estimates is proposed. • Applying multivariate analysis to consolidate data can enhance e-waste estimates. • We examine the influence of model selection and data quality on e-waste estimates. • Datasets of all e-waste related variables in a Dutch case study have been provided. • Accurate modeling of time-variant lifespan distributions is critical for estimate. - Abstract: Waste electrical and electronic equipment (or e-waste) is one of the fastest growing waste streams, which encompasses a wide and increasing spectrum of products. Accurate estimation of e-waste generation is difficult, mainly due to lack of high quality data referred to market and socio-economic dynamics. This paper addresses how to enhance e-waste estimates by providing techniques to increase data quality. An advanced, flexible and multivariate Input–Output Analysis (IOA) method is proposed. It links all three pillars in IOA (product sales, stock and lifespan profiles) to construct mathematical relationships between various data points. By applying this method, the data consolidation steps can generate more accurate time-series datasets from available data pool. This can consequently increase the reliability of e-waste estimates compared to the approach without data processing. A case study in the Netherlands is used to apply the advanced IOA model. As a result, for the first time ever, complete datasets of all three variables for estimating all types of e-waste have been obtained. The result of this study also demonstrates significant disparity between various estimation models, arising from the use of data under different conditions. It shows the importance of applying multivariate approach and multiple sources to improve data quality for modelling, specifically using appropriate time-varying lifespan parameters. Following the case study, a roadmap with a procedural guideline is provided to enhance e

Cardiac output estimation using pulmonary mechanics in mechanically ventilated patients

Directory of Open Access Journals (Sweden)

Hann Christopher E

2010-11-01

Full Text Available Abstract The application of positive end expiratory pressure (PEEP in mechanically ventilated (MV patients with acute respiratory distress syndrome (ARDS decreases cardiac output (CO. Accurate measurement of CO is highly invasive and is not ideal for all MV critically ill patients. However, the link between the PEEP used in MV, and CO provides an opportunity to assess CO via MV therapy and other existing measurements, creating a CO measure without further invasiveness. This paper examines combining models of diffusion resistance and lung mechanics, to help predict CO changes due to PEEP. The CO estimator uses an initial measurement of pulmonary shunt, and estimations of shunt changes due to PEEP to predict CO at different levels of PEEP. Inputs to the cardiac model are the PV loops from the ventilator, as well as the oxygen saturation values using known respiratory inspired oxygen content. The outputs are estimates of pulmonary shunt and CO changes due to changes in applied PEEP. Data from two published studies are used to assess and initially validate this model. The model shows the effect on oxygenation due to decreased CO and decreased shunt, resulting from increased PEEP. It concludes that there is a trade off on oxygenation parameters. More clinically importantly, the model also examines how the rate of CO drop with increased PEEP can be used as a method to determine optimal PEEP, which may be used to optimise MV therapy with respect to the gas exchange achieved, as well as accounting for the impact on the cardiovascular system and its management.

Stereovision-based pose and inertia estimation of unknown and uncooperative space objects

Science.gov (United States)

Pesce, Vincenzo; Lavagna, Michèle; Bevilacqua, Riccardo

2017-01-01

Autonomous close proximity operations are an arduous and attractive problem in space mission design. In particular, the estimation of pose, motion and inertia properties of an uncooperative object is a challenging task because of the lack of available a priori information. This paper develops a novel method to estimate the relative position, velocity, angular velocity, attitude and the ratios of the components of the inertia matrix of an uncooperative space object using only stereo-vision measurements. The classical Extended Kalman Filter (EKF) and an Iterated Extended Kalman Filter (IEKF) are used and compared for the estimation procedure. In addition, in order to compute the inertia properties, the ratios of the inertia components are added to the state and a pseudo-measurement equation is considered in the observation model. The relative simplicity of the proposed algorithm could be suitable for an online implementation for real applications. The developed algorithm is validated by numerical simulations in MATLAB using different initial conditions and uncertainty levels. The goal of the simulations is to verify the accuracy and robustness of the proposed estimation algorithm. The obtained results show satisfactory convergence of estimation errors for all the considered quantities. The obtained results, in several simulations, shows some improvements with respect to similar works, which deal with the same problem, present in literature. In addition, a video processing procedure is presented to reconstruct the geometrical properties of a body using cameras. This inertia reconstruction algorithm has been experimentally validated at the ADAMUS (ADvanced Autonomous MUltiple Spacecraft) Lab at the University of Florida. In the future, this different method could be integrated to the inertia ratios estimator to have a complete tool for mass properties recognition.

Estimating changes in cardiac output using an implanted hemodynamic monitor in heart failure patients

DEFF Research Database (Denmark)

Ståhlberg, Marcus; Damgaard, Morten; Ersgård, David

2010-01-01

OBJECTIVES: The aim of this study was to evaluate an algorithm that estimates changes in cardiac output (CO) from right ventricular (RV) pressure waveforms derived from an implantable hemodynamic monitor (IHM) in heart failure patients. DESIGN: Twelve heart failure patients (NYHA II-III, EF 32......%) with an implantable hemodynamic monitor (Chronicle) were included in this study. Changes in cardiac output were provoked by body position change at rest (left lateral supine, horizontal supine, sitting, and standing) and a steady state bicycle exercise at 20 watts. Estimated CO derived from the IHM (CO...... was -0.39 L/min (11%). Limits of agreement were +/-1.56 L/min and relative error was 21%. CONCLUSIONS: A simple algorithm based on RV pressure wave form characteristics derived from an IHM can be used to estimate changes in CO in heart failure patients. These findings encourage further research aiming...

Estimation of monthly wind power outputs of WECS with limited record period using artificial neural networks

International Nuclear Information System (INIS)

Tu, Yi-Long; Chang, Tsang-Jung; Chen, Cheng-Lung; Chang, Yu-Jung

2012-01-01

Highlights: ► ANN with short record training data is used to estimate power outputs in an existing station. ► The suitable numbers/parameters of input neurons for ANN are presented. ► Current wind speeds and previous power outputs are the most important input neurons. ► Choosing suitable input parameters is more important than choosing multiple parameters. - Abstract: For the brand new wind power industry, online recordings of wind power data are always in a relatively limited period. The aim of the study is to investigate the suitable numbers/parameters of input neurons for artificial neural networks under a short record of measured data. Measured wind speeds, wind directions (yaw angles) and power outputs with 10-min resolution at an existing wind power station, located at Jhongtun, Taiwan, are integrated to form three types of input neuron numbers and sixteen cases of input neurons. The first-10 days of each month in 2006 are used for data training to simulate the following 20-day power generation of the same month. The performance of various input neuron cases is evaluated. The simulated results show that using the first 10-day training data with adequate input neurons can estimate energy outputs well except the weak wind regime (May, June, and July). Among the input neuron parameters used, current wind speeds V(t) and previous power outputs P(t − 1) are the most important. Individually using one of them into input neurons can only provide satisfactory estimation. However, simultaneously using these two parameters into input neurons can give the best estimation. Thus, choosing suitable input parameters is more important than choosing multiple parameters.

Vision-Based Pose Estimation for Robot-Mediated Hand Telerehabilitation

Directory of Open Access Journals (Sweden)

Giuseppe Airò Farulla

2016-02-01

Full Text Available Vision-based Pose Estimation (VPE represents a non-invasive solution to allow a smooth and natural interaction between a human user and a robotic system, without requiring complex calibration procedures. Moreover, VPE interfaces are gaining momentum as they are highly intuitive, such that they can be used from untrained personnel (e.g., a generic caregiver even in delicate tasks as rehabilitation exercises. In this paper, we present a novel master–slave setup for hand telerehabilitation with an intuitive and simple interface for remote control of a wearable hand exoskeleton, named HX. While performing rehabilitative exercises, the master unit evaluates the 3D position of a human operator’s hand joints in real-time using only a RGB-D camera, and commands remotely the slave exoskeleton. Within the slave unit, the exoskeleton replicates hand movements and an external grip sensor records interaction forces, that are fed back to the operator-therapist, allowing a direct real-time assessment of the rehabilitative task. Experimental data collected with an operator and six volunteers are provided to show the feasibility of the proposed system and its performances. The results demonstrate that, leveraging on our system, the operator was able to directly control volunteers’ hands movements.

Estimation of hospital efficiency--do different definitions and casemix measures for hospital output affect the results?

Science.gov (United States)

Vitikainen, Kirsi; Street, Andrew; Linna, Miika

2009-02-01

Hospital efficiency has been the subject of numerous health economics studies, but there is little evidence on how the chosen output and casemix measures affect the efficiency results. The aim of this study is to examine the robustness of efficiency results due to these factors. Comparison is made between activities and episode output measures, and two different output grouping systems (Classic and FullDRG). Non-parametric data envelopment analysis is used as an analysis technique. The data consist of all public acute care hospitals in Finland in 2005 (n=40). Efficiency estimates were not found to be highly sensitive to the choice between episode and activity descriptions of output, but more so to the choice of DRG grouping system. Estimates are most sensitive to scale assumptions, with evidence of decreasing returns to scale in larger hospitals. Episode measures are generally to be preferred to activity measures because these better capture the patient pathway, while FullDRGs are preferred to Classic DRGs particularly because of the better description of outpatient output in the former grouping system. Attention should be paid to reducing the extent of scale inefficiency in Finland.

Reachable set estimation for Takagi-Sugeno fuzzy systems against unknown output delays with application to tracking control of AUVs.

Science.gov (United States)

Zhong, Zhixiong; Zhu, Yanzheng; Ahn, Choon Ki

2018-03-20

In this paper, we address the problem of reachable set estimation for continuous-time Takagi-Sugeno (T-S) fuzzy systems subject to unknown output delays. Based on the reachable set concept, a new controller design method is also discussed for such systems. An effective method is developed to attenuate the negative impact from the unknown output delays, which likely degrade the performance/stability of systems. First, an augmented fuzzy observer is proposed to capacitate a synchronous estimation for the system state and the disturbance term owing to the unknown output delays, which ensures that the reachable set of the estimation error is limited via the intersection operation of ellipsoids. Then, a compensation technique is employed to eliminate the influence on the system performance stemmed from the unknown output delays. Finally, the effectiveness and correctness of the obtained theories are verified by the tracking control of autonomous underwater vehicles. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Temporal subtraction of chest radiographs compensating pose differences

Science.gov (United States)

von Berg, Jens; Dworzak, Jalda; Klinder, Tobias; Manke, Dirk; Kreth, Adrian; Lamecker, Hans; Zachow, Stefan; Lorenz, Cristian

2011-03-01

Temporal subtraction techniques using 2D image registration improve the detectability of interval changes from chest radiographs. Although such methods are well known for some time they are not widely used in radiologic practice. The reason is the occurrence of strong pose differences between two acquisitions with a time interval of months to years in between. Such strong perspective differences occur in a reasonable number of cases. They cannot be compensated by available image registration methods and thus mask interval changes to be undetectable. In this paper a method is proposed to estimate a 3D pose difference by the adaptation of a 3D rib cage model to both projections. The difference between both is then compensated for, thus producing a subtraction image with virtually no change in pose. The method generally assumes that no 3D image data is available from the patient. The accuracy of pose estimation is validated with chest phantom images acquired under controlled geometric conditions. A subtle interval change simulated by a piece of plastic foam attached to the phantom becomes visible in subtraction images generated with this technique even at strong angular pose differences like an anterior-posterior inclination of 13 degrees.

Single-frame 3D human pose recovery from multiple views

NARCIS (Netherlands)

Hofmann, M.; Gavrila, D.M.

2009-01-01

We present a system for the estimation of unconstrained 3D human upper body pose from multi-camera single-frame views. Pose recovery starts with a shape detection stage where candidate poses are generated based on hierarchical exemplar matching in the individual camera views. The hierarchy used in

Locating binding poses in protein-ligand systems using reconnaissance metadynamics

Science.gov (United States)

Söderhjelm, Pär; Tribello, Gareth A.; Parrinello, Michele

2012-01-01

A molecular dynamics-based protocol is proposed for finding and scoring protein-ligand binding poses. This protocol uses the recently developed reconnaissance metadynamics method, which employs a self-learning algorithm to construct a bias that pushes the system away from the kinetic traps where it would otherwise remain. The exploration of phase space with this algorithm is shown to be roughly six to eight times faster than unbiased molecular dynamics and is only limited by the time taken to diffuse about the surface of the protein. We apply this method to the well-studied trypsin–benzamidine system and show that we are able to refind all the poses obtained from a reference EADock blind docking calculation. These poses can be scored based on the length of time the system remains trapped in the pose. Alternatively, one can perform dimensionality reduction on the output trajectory and obtain a map of phase space that can be used in more expensive free-energy calculations. PMID:22440749

Driver head pose tracking with thermal camera

Science.gov (United States)

Bole, S.; Fournier, C.; Lavergne, C.; Druart, G.; Lépine, T.

2016-09-01

Head pose can be seen as a coarse estimation of gaze direction. In automotive industry, knowledge about gaze direction could optimize Human-Machine Interface (HMI) and Advanced Driver Assistance Systems (ADAS). Pose estimation systems are often based on camera when applications have to be contactless. In this paper, we explore uncooled thermal imagery (8-14μm) for its intrinsic night vision capabilities and for its invariance versus lighting variations. Two methods are implemented and compared, both are aided by a 3D model of the head. The 3D model, mapped with thermal texture, allows to synthesize a base of 2D projected models, differently oriented and labeled in yaw and pitch. The first method is based on keypoints. Keypoints of models are matched with those of the query image. These sets of matchings, aided with the 3D shape of the model, allow to estimate 3D pose. The second method is a global appearance approach. Among all 2D models of the base, algorithm searches the one which is the closest to the query image thanks to a weighted least squares difference.

Baseline Face Detection, Head Pose Estimation, and Coarse Direction Detection for Facial Data in the SHRP2 Naturalistic Driving Study

Energy Technology Data Exchange (ETDEWEB)

Paone, Jeffrey R [ORNL; Bolme, David S [ORNL; Ferrell, Regina Kay [ORNL; Aykac, Deniz [ORNL; Karnowski, Thomas Paul [ORNL

2015-01-01

Keeping a driver focused on the road is one of the most critical steps in insuring the safe operation of a vehicle. The Strategic Highway Research Program 2 (SHRP2) has over 3,100 recorded videos of volunteer drivers during a period of 2 years. This extensive naturalistic driving study (NDS) contains over one million hours of video and associated data that could aid safety researchers in understanding where the driver s attention is focused. Manual analysis of this data is infeasible, therefore efforts are underway to develop automated feature extraction algorithms to process and characterize the data. The real-world nature, volume, and acquisition conditions are unmatched in the transportation community, but there are also challenges because the data has relatively low resolution, high compression rates, and differing illumination conditions. A smaller dataset, the head pose validation study, is available which used the same recording equipment as SHRP2 but is more easily accessible with less privacy constraints. In this work we report initial head pose accuracy using commercial and open source face pose estimation algorithms on the head pose validation data set.

6DoF object pose measurement by a monocular manifold-based pattern recognition technique

International Nuclear Information System (INIS)

Kouskouridas, Rigas; Charalampous, Konstantinos; Gasteratos, Antonios

2012-01-01

In this paper, a novel solution to the compound problem of object recognition and 3D pose estimation is presented. An accurate measurement of the geometrical configuration of a recognized target, relative to a known coordinate system, is of fundamental importance and constitutes a prerequisite for several applications such as robot grasping or obstacle avoidance. The proposed method lays its foundations on the following assumptions: (a) the same object captured under varying viewpoints and perspectives represents data that could be projected onto a well-established and highly distinguishable subspace; (b) totally different objects observed under the same viewpoints and perspectives share identical 3D pose that can be sufficiently modeled to produce a generalized model. Toward this end, we propose an advanced architecture that allows both recognizing patterns and providing efficient solution for 6DoF pose estimation. We employ a manifold modeling architecture that is grounded on a part-based representation of an object, which in turn, is accomplished via an unsupervised clustering of the extracted visual cues. The main contributions of the proposed framework are: (a) the proposed part-based architecture requires minimum supervision, compared to other contemporary solutions, whilst extracting new features encapsulating both appearance and geometrical attributes of the objects; (b) contrary to related projects that extract high-dimensional data, thus, increasing the complexity of the system, the proposed manifold modeling approach makes use of low dimensionality input vectors; (c) the formulation of a novel input–output space mapping that outperforms the existing dimensionality reduction schemes. Experimental results justify our theoretical claims and demonstrate the superiority of our method comparing to other related contemporary projects. (paper)

Hand Pose Estimation by Fusion of Inertial and Magnetic Sensing Aided by a Permanent Magnet.

Science.gov (United States)

Kortier, Henk G; Antonsson, Jacob; Schepers, H Martin; Gustafsson, Fredrik; Veltink, Peter H

2015-09-01

Tracking human body motions using inertial sensors has become a well-accepted method in ambulatory applications since the subject is not confined to a lab-bounded volume. However, a major drawback is the inability to estimate relative body positions over time because inertial sensor information only allows position tracking through strapdown integration, but does not provide any information about relative positions. In addition, strapdown integration inherently results in drift of the estimated position over time. We propose a novel method in which a permanent magnet combined with 3-D magnetometers and 3-D inertial sensors are used to estimate the global trunk orientation and relative pose of the hand with respect to the trunk. An Extended Kalman Filter is presented to fuse estimates obtained from inertial sensors with magnetic updates such that the position and orientation between the human hand and trunk as well as the global trunk orientation can be estimated robustly. This has been demonstrated in multiple experiments in which various hand tasks were performed. The most complex task in which simultaneous movements of both trunk and hand were performed resulted in an average rms position difference with an optical reference system of 19.7±2.2 mm whereas the relative trunk-hand and global trunk orientation error was 2.3±0.9 and 8.6±8.7 deg respectively.

Empirical investigation on using wind speed volatility to estimate the operation probability and power output of wind turbines

International Nuclear Information System (INIS)

Liu, Heping; Shi, Jing; Qu, Xiuli

2013-01-01

Highlights: ► Ten-minute wind speed and power generation data of an offshore wind turbine are used. ► An ARMA–GARCH-M model is built to simultaneously forecast wind speed mean and volatility. ► The operation probability and expected power output of the wind turbine are predicted. ► The integrated approach produces more accurate wind power forecasting than other conventional methods. - Abstract: In this paper, we introduce a quantitative methodology that performs the interval estimation of wind speed, calculates the operation probability of wind turbine, and forecasts the wind power output. The technological advantage of this methodology stems from the empowered capability of mean and volatility forecasting of wind speed. Based on the real wind speed and corresponding wind power output data from an offshore wind turbine, this methodology is applied to build an ARMA–GARCH-M model for wind speed forecasting, and then to compute the operation probability and the expected power output of the wind turbine. The results show that the developed methodology is effective, the obtained interval estimation of wind speed is reliable, and the forecasted operation probability and expected wind power output of the wind turbine are accurate

Recovering the 3d Pose and Shape of Vehicles from Stereo Images

Science.gov (United States)

Coenen, M.; Rottensteiner, F.; Heipke, C.

2018-05-01

The precise reconstruction and pose estimation of vehicles plays an important role, e.g. for autonomous driving. We tackle this problem on the basis of street level stereo images obtained from a moving vehicle. Starting from initial vehicle detections, we use a deformable vehicle shape prior learned from CAD vehicle data to fully reconstruct the vehicles in 3D and to recover their 3D pose and shape. To fit a deformable vehicle model to each detection by inferring the optimal parameters for pose and shape, we define an energy function leveraging reconstructed 3D data, image information, the vehicle model and derived scene knowledge. To minimise the energy function, we apply a robust model fitting procedure based on iterative Monte Carlo model particle sampling. We evaluate our approach using the object detection and orientation estimation benchmark of the KITTI dataset (Geiger et al., 2012). Our approach can deal with very coarse pose initialisations and we achieve encouraging results with up to 82 % correct pose estimations. Moreover, we are able to deliver very precise orientation estimation results with an average absolute error smaller than 4°.

Dose estimate by personal music players based on weighted output voltage

DEFF Research Database (Denmark)

Hammershøi, Dorte; Ordoñez Pizarro, Rodrigo Eduardo; Christensen, Anders Tornvig

2015-01-01

The exposure by personal music players may in future be displayed to users, as described in the current draft of EN 50332-3. The suggested procedure includes a weighting of the electrical output voltages of the music player, and does not include the significance of the earphone sensitivity. It does...... not include the weighting principles necessary for sound sources close to the ears either, which constitutes an inverse head-related transfer function for the free- or diffuse field. The purpose of the present study is to assess the uncertainties in the dose estimate determined this way. Measurements for 20...

Pose estimation and tracking of non-cooperative rocket bodies using Time-of-Flight cameras

Science.gov (United States)

Gómez Martínez, Harvey; Giorgi, Gabriele; Eissfeller, Bernd

2017-10-01

This paper presents a methodology for estimating the position and orientation of a rocket body in orbit - the target - undergoing a roto-translational motion, with respect to a chaser spacecraft, whose task is to match the target dynamics for a safe rendezvous. During the rendezvous maneuver the chaser employs a Time-of-Flight camera that acquires a point cloud of 3D coordinates mapping the sensed target surface. Once the system identifies the target, it initializes the chaser-to-target relative position and orientation. After initialization, a tracking procedure enables the system to sense the evolution of the target's pose between frames. The proposed algorithm is evaluated using simulated point clouds, generated with a CAD model of the Cosmos-3M upper stage and the PMD CamCube 3.0 camera specifications.

Meta Analysis for Benefits Transfer – Toward Value Estimates for Some Outputs of Multifunctional Agriculture

OpenAIRE

Randall, Alan; Kidder, Ayuna; Chen, Ding-Rong

2008-01-01

As a contribution to valuing the outputs of multifunctional agriculture, we report three new meta analyses estimating value functions for agricultural conservation program impacts on water quality, wetlands, and upland habitat and open space. As is often the case in valuation, where methods have yet to be standardized, the data sets are relatively small and noisy. With a clear objective of benefits transfer, we seek robust parameter estimates for key RHS variables, even at the cost of some lo...

Web-based Visualisation of Head Pose and Facial Expressions Changes:

DEFF Research Database (Denmark)

Kalliatakis, Grigorios; Vidakis, Nikolaos; Triantafyllidis, Georgios

2016-01-01

Despite significant recent advances in the field of head pose estimation and facial expression recognition, raising the cognitive level when analysing human activity presents serious challenges to current concepts. Motivated by the need of generating comprehensible visual representations from...... and accurately estimate head pose changes in unconstrained environment. In order to complete the secondary process of recognising four universal dominant facial expressions (happiness, anger, sadness and surprise), emotion recognition via facial expressions (ERFE) was adopted. After that, a lightweight data...

Multispectral embedding-based deep neural network for three-dimensional human pose recovery

Science.gov (United States)

Yu, Jialin; Sun, Jifeng

2018-01-01

Monocular image-based three-dimensional (3-D) human pose recovery aims to retrieve 3-D poses using the corresponding two-dimensional image features. Therefore, the pose recovery performance highly depends on the image representations. We propose a multispectral embedding-based deep neural network (MSEDNN) to automatically obtain the most discriminative features from multiple deep convolutional neural networks and then embed their penultimate fully connected layers into a low-dimensional manifold. This compact manifold can explore not only the optimum output from multiple deep networks but also the complementary properties of them. Furthermore, the distribution of each hierarchy discriminative manifold is sufficiently smooth so that the training process of our MSEDNN can be effectively implemented only using few labeled data. Our proposed network contains a body joint detector and a human pose regressor that are jointly trained. Extensive experiments conducted on four databases show that our proposed MSEDNN can achieve the best recovery performance compared with the state-of-the-art methods.

Estimating the basilar-membrane input-output function in normal-hearing and hearing-impaired listeners

DEFF Research Database (Denmark)

Jepsen, Morten Løve; Dau, Torsten

To partly characterize the function of cochlear processing in humans, the basilar membrane (BM) input-output function can be estimated. In recent studies, forward masking has been used to estimate BM compression. If an on-frequency masker is processed compressively, while an off-frequency masker...... is transformed more linearly, the ratio between the slopes of growth of masking (GOM) functions provides an estimate of BM compression at the signal frequency. In this study, this paradigm is extended to also estimate the knee-point of the I/O-function between linear rocessing at low levels and compressive...... processing at medium levels. If a signal can be masked by a low-level on-frequency masker such that signal and masker fall in the linear region of the I/O-function, then a steeper GOM function is expected. The knee-point can then be estimated in the input level region where the GOM changes significantly...

Pose Self-Calibration of Stereo Vision Systems for Autonomous Vehicle Applications.

Science.gov (United States)

Musleh, Basam; Martín, David; Armingol, José María; de la Escalera, Arturo

2016-09-14

Nowadays, intelligent systems applied to vehicles have grown very rapidly; their goal is not only the improvement of safety, but also making autonomous driving possible. Many of these intelligent systems are based on making use of computer vision in order to know the environment and act accordingly. It is of great importance to be able to estimate the pose of the vision system because the measurement matching between the perception system (pixels) and the vehicle environment (meters) depends on the relative position between the perception system and the environment. A new method of camera pose estimation for stereo systems is presented in this paper, whose main contribution regarding the state of the art on the subject is the estimation of the pitch angle without being affected by the roll angle. The validation of the self-calibration method is accomplished by comparing it with relevant methods of camera pose estimation, where a synthetic sequence is used in order to measure the continuous error with a ground truth. This validation is enriched by the experimental results of the method in real traffic environments.

Pose Self-Calibration of Stereo Vision Systems for Autonomous Vehicle Applications

Science.gov (United States)

Musleh, Basam; Martín, David; Armingol, José María; de la Escalera, Arturo

2016-01-01

Nowadays, intelligent systems applied to vehicles have grown very rapidly; their goal is not only the improvement of safety, but also making autonomous driving possible. Many of these intelligent systems are based on making use of computer vision in order to know the environment and act accordingly. It is of great importance to be able to estimate the pose of the vision system because the measurement matching between the perception system (pixels) and the vehicle environment (meters) depends on the relative position between the perception system and the environment. A new method of camera pose estimation for stereo systems is presented in this paper, whose main contribution regarding the state of the art on the subject is the estimation of the pitch angle without being affected by the roll angle. The validation of the self-calibration method is accomplished by comparing it with relevant methods of camera pose estimation, where a synthetic sequence is used in order to measure the continuous error with a ground truth. This validation is enriched by the experimental results of the method in real traffic environments. PMID:27649178

Adjustment of regional climate model output for modeling the climatic mass balance of all glaciers on Svalbard.

NARCIS (Netherlands)

Möller, M.; Obleitner, F.; Reijmer, C.H.; Pohjola, V.A.; Glowacki, P.; Kohler, J.

2016-01-01

Large-scale modeling of glacier mass balance relies often on the output from regional climate models (RCMs). However, the limited accuracy and spatial resolution of RCM output pose limitations on mass balance simulations at subregional or local scales. Moreover, RCM output is still rarely available

Improving head and body pose estimation through semi-supervised manifold alignment

KAUST Repository

Heili, Alexandre; Varadarajan, Jagannadan; Ghanem, Bernard; Ahuja, Narendra; Odobez, Jean-Marc

2014-01-01

structure of the features in the train and target data and the need to align them were not explored despite the fact that the pose features between two datasets may vary according to the scene, e.g. due to different camera point of view or perspective

Improved ESPRIT Method for Joint Direction-of-Arrival and Frequency Estimation Using Multiple-Delay Output

Directory of Open Access Journals (Sweden)

Wang Xudong

2012-01-01

Full Text Available An automatic pairing joint direction-of-arrival (DOA and frequency estimation is presented to overcome the unsatisfactory performances of estimation of signal parameter via rotational invariance techniques- (ESPRIT- like algorithm of Wang (2010, which requires an additional pairing. By using multiple-delay output of a uniform linear antenna arrays (ULA, the proposed algorithm can estimate joint angles and frequencies with an improved ESPRIT. Compared with Wang’s ESPRIT algorithm, the angle estimation performance of the proposed algorithm is greatly improved. The frequency estimation performance of the proposed algorithm is same with that of Wang’s ESPRIT algorithm. Furthermore, the proposed algorithm can obtain automatic pairing DOA and frequency parameters, and it has a comparative computational complexity in contrast to Wang’s ESPRIT algorithm. By the way, this proposed algorithm can also work well for nonuniform linear arrays. The useful behavior of this proposed algorithm is verified by simulations.

Pose-invariant face recognition using Markov random fields.

Science.gov (United States)

Ho, Huy Tho; Chellappa, Rama

2013-04-01

One of the key challenges for current face recognition techniques is how to handle pose variations between the probe and gallery face images. In this paper, we present a method for reconstructing the virtual frontal view from a given nonfrontal face image using Markov random fields (MRFs) and an efficient variant of the belief propagation algorithm. In the proposed approach, the input face image is divided into a grid of overlapping patches, and a globally optimal set of local warps is estimated to synthesize the patches at the frontal view. A set of possible warps for each patch is obtained by aligning it with images from a training database of frontal faces. The alignments are performed efficiently in the Fourier domain using an extension of the Lucas-Kanade algorithm that can handle illumination variations. The problem of finding the optimal warps is then formulated as a discrete labeling problem using an MRF. The reconstructed frontal face image can then be used with any face recognition technique. The two main advantages of our method are that it does not require manually selected facial landmarks or head pose estimation. In order to improve the performance of our pose normalization method in face recognition, we also present an algorithm for classifying whether a given face image is at a frontal or nonfrontal pose. Experimental results on different datasets are presented to demonstrate the effectiveness of the proposed approach.

Problem Posing

OpenAIRE

Šilhavá, Marie

2009-01-01

This diploma thesis concentrates on problem posing from the students' point of view. Problem posing can be either seen as a teaching method which can be used in the class, or it can be used as a tool for researchers or teachers to assess the level of students' understanding of the topic. In my research, I compare three classes, one mathematics specialist class and two generalist classes, in their ability of problem posing. As an assessment tool it seemed that mathemathics specialists were abl...

Pose Self-Calibration of Stereo Vision Systems for Autonomous Vehicle Applications

Directory of Open Access Journals (Sweden)

Basam Musleh

2016-09-01

Full Text Available Nowadays, intelligent systems applied to vehicles have grown very rapidly; their goal is not only the improvement of safety, but also making autonomous driving possible. Many of these intelligent systems are based on making use of computer vision in order to know the environment and act accordingly. It is of great importance to be able to estimate the pose of the vision system because the measurement matching between the perception system (pixels and the vehicle environment (meters depends on the relative position between the perception system and the environment. A new method of camera pose estimation for stereo systems is presented in this paper, whose main contribution regarding the state of the art on the subject is the estimation of the pitch angle without being affected by the roll angle. The validation of the self-calibration method is accomplished by comparing it with relevant methods of camera pose estimation, where a synthetic sequence is used in order to measure the continuous error with a ground truth. This validation is enriched by the experimental results of the method in real traffic environments.

Pose-Invariant Face Recognition via RGB-D Images.

Science.gov (United States)

Sang, Gaoli; Li, Jing; Zhao, Qijun

2016-01-01

Three-dimensional (3D) face models can intrinsically handle large pose face recognition problem. In this paper, we propose a novel pose-invariant face recognition method via RGB-D images. By employing depth, our method is able to handle self-occlusion and deformation, both of which are challenging problems in two-dimensional (2D) face recognition. Texture images in the gallery can be rendered to the same view as the probe via depth. Meanwhile, depth is also used for similarity measure via frontalization and symmetric filling. Finally, both texture and depth contribute to the final identity estimation. Experiments on Bosphorus, CurtinFaces, Eurecom, and Kiwi databases demonstrate that the additional depth information has improved the performance of face recognition with large pose variations and under even more challenging conditions.

Output gap uncertainty and real-time monetary policy

Directory of Open Access Journals (Sweden)

Francesco Grigoli

2015-12-01

Full Text Available Output gap estimates are subject to a wide range of uncertainty owing principally to the difficulty in distinguishing between cycle and trend in real time. We show that country desks tend to overestimate economic slack, especially during recessions, and that uncertainty in initial output gap estimates persists several years. Only a small share of output gap revisions is predictable based on output dynamics, data quality, and policy frameworks. We also show that for a group of Latin American inflation targeters the prescriptions from monetary policy rules are subject to large changes due to revised output gap estimates. These explain a sizable proportion of the deviation of inflation from target, suggesting this information is not accounted for in real-time policy decisions.

Two new formulae for estimating the output of x-ray units

International Nuclear Information System (INIS)

Kumar, Pratik; Kaul, Rashmi; Rehani, M.M.; Sethi, Bhawna; Berry, M.

1996-01-01

The radiation output from different x-ray machines varies considerably. For a given kVp and mAs, this variation results from voltage waveform from the generator, tube-age and filtration. In routine practices, no exposure meter is fitted in the controls of x-ray machines. The most appropriate way to know entrance skin exposure (ESE) to the patient is by using the standard formulae. But, as yet, no one has evaluated the different formulae available in the literature, for their validity when applied to different machines. In the present study, we have first measured the ESE for seven x-ray machines and then estimated the % error between experimental and calculated values with five formulae and nomogram available in literature. Since all these formulae gave errors exceeding ±35% of the actual value, we have evolved two new formulae and developed appropriate computer programs. These two formulae are able to provide an estimate of ESE within a mean % error of -3.9±14.5 and 0.7±19.4 respectively, for seven x-ray machines included in the study. (author). 15 refs., 3 tabs

Dynamic Output Feedback Robust Model Predictive Control via Zonotopic Set-Membership Estimation for Constrained Quasi-LPV Systems

Directory of Open Access Journals (Sweden)

Xubin Ping

2015-01-01

Full Text Available For the quasi-linear parameter varying (quasi-LPV system with bounded disturbance, a synthesis approach of dynamic output feedback robust model predictive control (OFRMPC is investigated. The estimation error set is represented by a zonotope and refreshed by the zonotopic set-membership estimation method. By properly refreshing the estimation error set online, the bounds of true state at the next sampling time can be obtained. Furthermore, the feasibility of the main optimization problem at the next sampling time can be determined at the current time. A numerical example is given to illustrate the effectiveness of the approach.

Uncertainty of solute flux estimation in ungauged small streams: potential implications for input-output nutrient mass balances at stream reach scale

Directory of Open Access Journals (Sweden)

A. Butturini

2005-01-01

Full Text Available Input-output mass balances within stream reaches provide in situ estimates of stream nutrient retention/release under a wide spectrum of hydrological conditions. Providing good estimates of the mass balances for nutrients depends on precise hydrological monitoring and good chemical characterisation of stream water at the input and output ends of the stream reach. There is a need to optimise the hydrological monitoring and the frequencies of water sampling to yield precise annual mass balances, so as to avoid undue cost - high resolution monitoring and subsequent chemical analysis can be labour intensive and costly. In this paper, simulation exercises were performed using a data set created to represent the instantaneous discharge and solute dynamics at the input and output ends of a model stream reach during a one year period. At the output end, stream discharge and water chemistry were monitored continuously, while the input end was assumed to be ungauged; water sampling frequency was changed arbitrarily. Instantaneous discharge at the ungauged sampling point was estimated with an empirical power model linking the discharge to the catchment area (Hooper, 1986. The model thus substitutes for the additional gauge station. Simulations showed that 10 days was the longest chemical sampling interval which could provide reach annual mass balances of acceptable precision. Presently, the relationship between discharge and catchment area is usually assumed to be linear but simulations indicate that small departures from the linearity of this relationship could cause dramatic changes in the mass balance estimations.

Body-part templates for recovery of 2D human poses under occlusion

NARCIS (Netherlands)

Poppe, Ronald Walter; Poel, Mannes; Perales, F.J.; Fisher, R.B.

2008-01-01

Detection of humans and estimation of their 2D poses from a single image are challenging tasks. This is especially true when part of the observation is occluded. However, given a limited class of movements, poses can be recovered given the visible body-parts. To this end, we propose a novel template

ESPRIT-like algorithm for computational-efficient angle estimation in bistatic multiple-input multiple-output radar

Science.gov (United States)

Gong, Jian; Lou, Shuntian; Guo, Yiduo

2016-04-01

An estimation of signal parameters via a rotational invariance techniques-like (ESPRIT-like) algorithm is proposed to estimate the direction of arrival and direction of departure for bistatic multiple-input multiple-output (MIMO) radar. The properties of a noncircular signal and Euler's formula are first exploited to establish a real-valued bistatic MIMO radar array data, which is composed of sine and cosine data. Then the receiving/transmitting selective matrices are constructed to obtain the receiving/transmitting rotational invariance factors. Since the rotational invariance factor is a cosine function, symmetrical mirror angle ambiguity may occur. Finally, a maximum likelihood function is used to avoid the estimation ambiguities. Compared with the existing ESPRIT, the proposed algorithm can save about 75% of computational load owing to the real-valued ESPRIT algorithm. Simulation results confirm the effectiveness of the ESPRIT-like algorithm.

Output-feedback control of combined sewer networks through receding horizon control with moving horizon estimation

OpenAIRE

Joseph-Duran, Bernat; Ocampo-Martinez, Carlos; Cembrano, Gabriela

2015-01-01

An output-feedback control strategy for pollution mitigation in combined sewer networks is presented. The proposed strategy provides means to apply model-based predictive control to large-scale sewer networks, in-spite of the lack of measurements at most of the network sewers. In previous works, the authors presented a hybrid linear control-oriented model for sewer networks together with the formulation of Optimal Control Problems (OCP) and State Estimation Problems (SEP). By iteratively solv...

Pose Estimation using a Hierarchical 3D Representation of Contours and Surfaces

DEFF Research Database (Denmark)

Buch, Anders Glent; Kraft, Dirk; Kämäräinen, Joni-Kristian

2013-01-01

We present a system for detecting the pose of rigid objects using texture and contour information. From a stereo image view of a scene, a sparse hierarchical scene representation is reconstructed using an early cognitive vision system. We define an object model in terms of a simple context...

Pose Estimation with a Kinect for Ergonomic Studies: Evaluation of the Accuracy Using a Virtual Mannequin

Directory of Open Access Journals (Sweden)

Pierre Plantard

2015-01-01

Full Text Available Analyzing human poses with a Kinect is a promising method to evaluate potentials risks of musculoskeletal disorders at workstations. In ecological situations, complex 3D poses and constraints imposed by the environment make it difficult to obtain reliable kinematic information. Thus, being able to predict the potential accuracy of the measurement for such complex 3D poses and sensor placements is challenging in classical experimental setups. To tackle this problem, we propose a new evaluation method based on a virtual mannequin. In this study, we apply this method to the evaluation of joint positions (shoulder, elbow, and wrist, joint angles (shoulder and elbow, and the corresponding RULA (a popular ergonomics assessment grid upper-limb score for a large set of poses and sensor placements. Thanks to this evaluation method, more than 500,000 configurations have been automatically tested, which would be almost impossible to evaluate with classical protocols. The results show that the kinematic information obtained by the Kinect software is generally accurate enough to fill in ergonomic assessment grids. However inaccuracy strongly increases for some specific poses and sensor positions. Using this evaluation method enabled us to report configurations that could lead to these high inaccuracies. As a supplementary material, we provide a software tool to help designers to evaluate the expected accuracy of this sensor for a set of upper-limb configurations. Results obtained with the virtual mannequin are in accordance with those obtained from a real subject for a limited set of poses and sensor placements.

Comparison On Matching Methods Used In Pose Tracking For 3D Shape Representation

Directory of Open Access Journals (Sweden)

Khin Kyu Kyu Win

2017-01-01

Full Text Available In this work three different algorithms such as Brute Force Delaunay Triangulation and k-d Tree are analyzed on matching comparison for 3D shape representation. It is intended for developing the pose tracking of moving objects in video surveillance. To determine 3D pose of moving objects some tracking system may require full 3D pose estimation of arbitrarily shaped objects in real time. In order to perform 3D pose estimation in real time each step in the tracking algorithm must be computationally efficient. This paper presents method comparison for the computationally efficient registration of 3D shapes including free-form surfaces. Matching of free-form surfaces are carried out by using geometric point matching algorithm ICP. Several aspects of the ICP algorithm are investigated and analyzed by using specified surface setup. The surface setup processed in this system is represented by simple geometric primitive dealing with objects of free-from shape. Considered representations are a cloud of points.

Fluctuations of the SNR at the output of the MVDR with Regularized Tyler Estimators

KAUST Repository

Elkhalil, Khalil

2016-12-27

This paper analyzes the statistical properties of the signal-to-noise ratio (SNR) at the output of the Capon\\'s minimum variance distortionless response (MVDR) beamformers when operating over impulsive noises. Particularly, we consider the supervised case in which the receiver employs the regularized Tyler estimator in order to estimate the covariance matrix of the interference-plus-noise process using n observations of size N×1N×1. The choice for the regularized Tylor estimator (RTE) is motivated by its resilience to the presence of outliers and its regularization parameter that guarantees a good conditioning of the covariance estimate. Of particular interest in this paper is the derivation of the second order statistics of the SINR. To achieve this goal, we consider two different approaches. The first one is based on considering the classical regime, referred to as the n-large regime, in which N is assumed to be fixed while n grows to infinity. The second approach is built upon recent results developped within the framework of random matrix theory and assumes that N and n grow large together. Numerical results are provided in order to compare between the accuracies of each regime under different settings.

Improved GRACE regional mass balance estimates of the Greenland ice sheet cross-validated with the input-output method

NARCIS (Netherlands)

Xu, Zheng; Schrama, Ernst J. O.; van der Wal, Wouter; van den Broeke, Michiel; Enderlin, Ellyn M.

2016-01-01

In this study, we use satellite gravimetry data from the Gravity Recovery and Climate Experiment (GRACE) to estimate regional mass change of the Greenland ice sheet (GrIS) and neighboring glaciated regions using a least squares inversion approach. We also consider results from the input–output

Improved GRACE regional mass balance estimates of the Greenland ice sheet cross-validated with the input–output method

NARCIS (Netherlands)

Xu, Z.; Schrama, E.J.O.; van der Wal, W.; van den Broeke, MR; Enderlin, EM

2016-01-01

In this study, we use satellite gravimetry data from the Gravity Recovery and Climate Experiment (GRACE) to estimate regional mass change of the Greenland ice sheet (GrIS) and neighboring glaciated regions using a least squares inversion approach. We also consider results from the input–output

Yoga Poses Increase Subjective Energy and State Self-Esteem in Comparison to 'Power Poses'.

Science.gov (United States)

Golec de Zavala, Agnieszka; Lantos, Dorottya; Bowden, Deborah

2017-01-01

Research on beneficial consequences of yoga focuses on the effects of yogic breathing and meditation. Less is known about the psychological effects of performing yoga postures. The present study investigated the effects of yoga poses on subjective sense of energy and self-esteem. The effects of yoga postures were compared to the effects of 'power poses,' which arguably increase the sense of power and self-confidence due to their association with interpersonal dominance (Carney et al., 2010). The study tested the novel prediction that yoga poses, which are not associated with interpersonal dominance but increase bodily energy, would increase the subjective feeling of energy and therefore increase self-esteem compared to 'high power' and 'low power' poses. A two factorial, between participants design was employed. Participants performed either two standing yoga poses with open front of the body ( n = 19), two standing yoga poses with covered front of the body ( n = 22), two expansive, high power poses ( n = 21), or two constrictive, low power poses ( n = 20) for 1-min each. The results showed that yoga poses in comparison to 'power poses' increased self-esteem. This effect was mediated by an increased subjective sense of energy and was observed when baseline trait self-esteem was controlled for. These results suggest that the effects of performing open, expansive body postures may be driven by processes other than the poses' association with interpersonal power and dominance. This study demonstrates that positive effects of yoga practice can occur after performing yoga poses for only 2 min.

Multi-Task Convolutional Neural Network for Pose-Invariant Face Recognition

Science.gov (United States)

Yin, Xi; Liu, Xiaoming

2018-02-01

This paper explores multi-task learning (MTL) for face recognition. We answer the questions of how and why MTL can improve the face recognition performance. First, we propose a multi-task Convolutional Neural Network (CNN) for face recognition where identity classification is the main task and pose, illumination, and expression estimations are the side tasks. Second, we develop a dynamic-weighting scheme to automatically assign the loss weight to each side task, which is a crucial problem in MTL. Third, we propose a pose-directed multi-task CNN by grouping different poses to learn pose-specific identity features, simultaneously across all poses. Last but not least, we propose an energy-based weight analysis method to explore how CNN-based MTL works. We observe that the side tasks serve as regularizations to disentangle the variations from the learnt identity features. Extensive experiments on the entire Multi-PIE dataset demonstrate the effectiveness of the proposed approach. To the best of our knowledge, this is the first work using all data in Multi-PIE for face recognition. Our approach is also applicable to in-the-wild datasets for pose-invariant face recognition and achieves comparable or better performance than state of the art on LFW, CFP, and IJB-A datasets.

Boneless Pose Editing and Animation

DEFF Research Database (Denmark)

Bærentzen, Jakob Andreas; Hansen, Kristian Evers; Erleben, Kenny

2007-01-01

In this paper, we propose a pose editing and animation method for triangulated surfaces based on a user controlled partitioning of the model into deformable parts and rigid parts which are denoted handles. In our pose editing system, the user can sculpt a set of poses simply by transforming...... the handles for each pose. Using Laplacian editing, the deformable parts are deformed to match the handles. In our animation system the user can constrain one or several handles in order to define a new pose. New poses are interpolated from the examples poses, by solving a small non-linear optimization...... problem in order to obtain the interpolation weights. While the system can be used simply for building poses, it is also an animation system. The user can specify a path for a given constraint and the model is animated correspondingly....

Investigating time-efficiency of forward masking paradigms for estimating basilar membrane input-output characteristics

DEFF Research Database (Denmark)

Fereczkowski, Michal; Jepsen, Morten Løve; Dau, Torsten

2017-01-01

-output (I/O) function have been proposed. However, such measures are very time consuming. The present study investigated possible modifications of the temporal masking curve (TMC) paradigm to improve time and measurement efficiency. In experiment 1, estimates of knee point (KP) and compression ratio (CR......”, was tested. In contrast to the standard TMC paradigm, the maker level was kept fixed and the “gap threshold” was obtained, such that the masker just masks a low-level (12 dB sensation level) signal. It is argued that this modification allows for better control of the tested stimulus level range, which...

Feature and Pose Constrained Visual Aided Inertial Navigation for Computationally Constrained Aerial Vehicles

Science.gov (United States)

Williams, Brian; Hudson, Nicolas; Tweddle, Brent; Brockers, Roland; Matthies, Larry

2011-01-01

A Feature and Pose Constrained Extended Kalman Filter (FPC-EKF) is developed for highly dynamic computationally constrained micro aerial vehicles. Vehicle localization is achieved using only a low performance inertial measurement unit and a single camera. The FPC-EKF framework augments the vehicle's state with both previous vehicle poses and critical environmental features, including vertical edges. This filter framework efficiently incorporates measurements from hundreds of opportunistic visual features to constrain the motion estimate, while allowing navigating and sustained tracking with respect to a few persistent features. In addition, vertical features in the environment are opportunistically used to provide global attitude references. Accurate pose estimation is demonstrated on a sequence including fast traversing, where visual features enter and exit the field-of-view quickly, as well as hover and ingress maneuvers where drift free navigation is achieved with respect to the environment.

IMU-based Real-time Pose Measurement system for Anterior Pelvic Plane in Total Hip Replacement Surgeries.

Science.gov (United States)

Zhe Cao; Shaojie Su; Hao Tang; Yixin Zhou; Zhihua Wang; Hong Chen

2017-07-01

With the aging of population, the number of Total Hip Replacement Surgeries (THR) increased year by year. In THR, inaccurate position of the implanted prosthesis may lead to the failure of the operation. In order to reduce the failure rate and acquire the real-time pose of Anterior Pelvic Plane (APP), we propose a measurement system in this paper. The measurement system includes two parts: Initial Pose Measurement Instrument (IPMI) and Real-time Pose Measurement Instrument (RPMI). IPMI is used to acquire the initial pose of the APP, and RPMI is used to estimate the real-time pose of the APP. Both are composed of an Inertial Measurement Unit (IMU) and magnetometer sensors. To estimate the attitude of the measurement system, the Extended Kalman Filter (EKF) is adopted in this paper. The real-time pose of the APP could be acquired together with the algorithm designed in the paper. The experiment results show that the Root Mean Square Error (RMSE) is within 1.6 degrees, which meets the requirement of THR operations.

ONKALO POSE experiment. Phase 3: execution and monitoring

International Nuclear Information System (INIS)

Valli, J.; Hakala, M.; Wanne, T.; Kantia, P.; Siren, T.

2014-01-01

In-depth knowledge of the in situ stress state at the Olkiluoto site is critical for stability assessment both prior to and after deposition of spent nuclear fuel in order to understand and avoid potential damage to the rock at the site. Posiva's Olkiluoto Spalling Experiment (POSE) was designed specifically for this purpose with three primary goals: establish the in situ spalling/damage strength of Olkiluoto migmatitic gneiss, establish the state of in situ stress at the -345 m depth level and act as a Prediction-Outcome (P-O) exercise. Phases 1 and 2 of POSE are outlined in WR 2012-60. The objectives of the third phase of the POSE experiment are the same as the original objectives outlined above. This report outlines the execution and results of the third phase of the POSE experiment. The third phase of the experiment involved internally heating the third experimental hole (ONK-EH3) of the POSE niche in order to cause a symmetrical thermal stress increase around the hole due to the thermal expansion of rock. This thermomechanically induced stress increase, coupled with the estimated existing in situ stress state, should cause the maximum principal stress around the hole to exceed the predicted spalling strength of the rock around the hole. ONK-EH3 is located almost completely in pegmatitic granite. Four fractures near the top of the hole were mapped after boring ONK-EH3, and a tensile failure located at the contact between mica-rich gneiss and pegmatitic granite was observed 18 months after boring, prior to the experiment. Based on predictive calculations and the estimated in situ state of stress, the maximum principal stress magnitude should reach ca. 100 MPa when the temperature was just below 100 deg C after 12 weeks of heating. There were problems with the heater control unit at the beginning of the experiment, after which heating proceeded according to plan. The crack damage threshold of pegmatitic granite has been determined to be 85 ±17 MPa at Olkiluoto

Influence of the level of fit of a density probability function to wind-speed data on the WECS mean power output estimation

International Nuclear Information System (INIS)

Carta, Jose A.; Ramirez, Penelope; Velazquez, Sergio

2008-01-01

Static methods which are based on statistical techniques to estimate the mean power output of a WECS (wind energy conversion system) have been widely employed in the scientific literature related to wind energy. In the static method which we use in this paper, for a given wind regime probability distribution function and a known WECS power curve, the mean power output of a WECS is obtained by resolving the integral, usually using numerical evaluation techniques, of the product of these two functions. In this paper an analysis is made of the influence of the level of fit between an empirical probability density function of a sample of wind speeds and the probability density function of the adjusted theoretical model on the relative error ε made in the estimation of the mean annual power output of a WECS. The mean power output calculated through the use of a quasi-dynamic or chronological method, that is to say using time-series of wind speed data and the power versus wind speed characteristic of the wind turbine, serves as the reference. The suitability of the distributions is judged from the adjusted R 2 statistic (R a 2 ). Hourly mean wind speeds recorded at 16 weather stations located in the Canarian Archipelago, an extensive catalogue of wind-speed probability models and two wind turbines of 330 and 800 kW rated power are used in this paper. Among the general conclusions obtained, the following can be pointed out: (a) that the R a 2 statistic might be useful as an initial gross indicator of the relative error made in the mean annual power output estimation of a WECS when a probabilistic method is employed; (b) the relative errors tend to decrease, in accordance with a trend line defined by a second-order polynomial, as R a 2 increases

Effects of Measurement Error on the Output Gap in Japan

OpenAIRE

Koichiro Kamada; Kazuto Masuda

2000-01-01

Potential output is the largest amount of products that can be produced by fully utilizing available labor and capital stock; the output gap is defined as the discrepancy between actual and potential output. If data on production factors contain measurement errors, total factor productivity (TFP) cannot be estimated accurately from the Solow residual(i.e., the portion of output that is not attributable to labor and capital inputs). This may give rise to distortions in the estimation of potent...

A review of cooperative and uncooperative spacecraft pose determination techniques for close-proximity operations

Science.gov (United States)

Opromolla, Roberto; Fasano, Giancarmine; Rufino, Giancarlo; Grassi, Michele

2017-08-01

The capability of an active spacecraft to accurately estimate its relative position and attitude (pose) with respect to an active/inactive, artificial/natural space object (target) orbiting in close-proximity is required to carry out various activities like formation flying, on-orbit servicing, active debris removal, and space exploration. According to the specific mission scenario, the pose determination task involves both theoretical and technological challenges related to the search for the most suitable algorithmic solution and sensor architecture, respectively. As regards the latter aspect, electro-optical sensors represent the best option as their use is compatible with mass and power limitation of micro and small satellites, and their measurements can be processed to estimate all the pose parameters. Overall, the degree of complexity of the challenges related to pose determination largely varies depending on the nature of the targets, which may be actively/passively cooperative, uncooperative but known, or uncooperative and unknown space objects. In this respect, while cooperative pose determination has been successfully demonstrated in orbit, the uncooperative case is still under study by universities, research centers, space agencies and private companies. However, in both the cases, the demand for space applications involving relative navigation maneuvers, also in close-proximity, for which pose determination capabilities are mandatory, is significantly increasing. In this framework, a review of state-of-the-art techniques and algorithms developed in the last decades for cooperative and uncooperative pose determination by processing data provided by electro-optical sensors is herein presented. Specifically, their main advantages and drawbacks in terms of achieved performance, computational complexity, and sensitivity to variability of pose and target geometry, are highlighted.

The art of problem posing

CERN Document Server

Brown, Stephen I

1990-01-01

Updated and expanded, this second edition satisfies the same philosophical objective as the first -- to show the importance of problem posing. Although interest in mathematical problem solving increased during the past decade, problem posing remained relatively ignored. The Art of Problem Posing draws attention to this equally important act and is the innovator in the field. Special features include: * an exploration ofthe logical relationship between problem posing and problem solving * a special chapter devoted to teaching problem posing as a separate course * sketches, drawings, diagrams, and cartoons that illustrate the schemes proposed * a special section on writing in mathematics.

Estimation of the 24-h urinary protein excretion based on the estimated urinary creatinine output.

Science.gov (United States)

Ubukata, Masamitsu; Takei, Takashi; Nitta, Kosaku

2016-06-01

The urinary protein/creatinine ratio [Up/Ucr (g/gCr)] has been used in the clinical management of patients with chronic kidney disease (CKD). However, a discrepancy is often noted between the Up/Ucr and 24-h urinary protein excretion [24hUp (g/day)] in patients with extremes of muscle mass. We examined devised a method for precise estimation of the 24-h urinary protein excretion (E-24hUp) based on estimation of 24-h urinary creatinine output (E-24hCr). Three parameters, spot Up/Ucr, 24hUP and E-24hUp (=Up/Ucr × E-24hCr), were determined in 116 adult patients with CKD. The correlations among the groups were analyzed. There was a significant correlation between the Up/Ucr and 24hUp (p high urinary protein group (>3.5 g/day). There was a significant correlation between the Up/Ucr and 24hUp in the low (p = 0.04) and high urinary protein (p = 0.01) groups, whereas the correlation coefficient was lower in the intermediate urinary protein (p = 0.07) group. Thus, we found a significant correlation between 24hUp and E-24hUp in the study population overall (p high urinary protein group (p < 0.001). We conclude that a poor correlation exists between the Up/Ucr and 24hUp in patients with intermediate urinary protein excretion levels. The recommended parameter for monitoring proteinuria in such patients may be the E-24hUp, which is calculated using the E-24hCr.

Direction-of-arrival estimation for co-located multiple-input multiple-output radar using structural sparsity Bayesian learning

International Nuclear Information System (INIS)

Wen Fang-Qing; Zhang Gong; Ben De

2015-01-01

This paper addresses the direction of arrival (DOA) estimation problem for the co-located multiple-input multiple-output (MIMO) radar with random arrays. The spatially distributed sparsity of the targets in the background makes compressive sensing (CS) desirable for DOA estimation. A spatial CS framework is presented, which links the DOA estimation problem to support recovery from a known over-complete dictionary. A modified statistical model is developed to accurately represent the intra-block correlation of the received signal. A structural sparsity Bayesian learning algorithm is proposed for the sparse recovery problem. The proposed algorithm, which exploits intra-signal correlation, is capable being applied to limited data support and low signal-to-noise ratio (SNR) scene. Furthermore, the proposed algorithm has less computation load compared to the classical Bayesian algorithm. Simulation results show that the proposed algorithm has a more accurate DOA estimation than the traditional multiple signal classification (MUSIC) algorithm and other CS recovery algorithms. (paper)

A comprehensive estimation of the economic effects of meteorological services based on the input-output method.

Science.gov (United States)

Wu, Xianhua; Wei, Guo; Yang, Lingjuan; Guo, Ji; Lu, Huaguo; Chen, Yunfeng; Sun, Jian

2014-01-01

Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete) economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency) in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27-1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30-1 : 51). Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries.

A Comprehensive Estimation of the Economic Effects of Meteorological Services Based on the Input-Output Method

Science.gov (United States)

Wu, Xianhua; Yang, Lingjuan; Guo, Ji; Lu, Huaguo; Chen, Yunfeng; Sun, Jian

2014-01-01

Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete) economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency) in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27–1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30–1 : 51). Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries. PMID:24578666

SVPWM Technique with Varying DC-Link Voltage for Common Mode Voltage Reduction in a Matrix Converter and Analytical Estimation of its Output Voltage Distortion

Science.gov (United States)

Padhee, Varsha

Common Mode Voltage (CMV) in any power converter has been the major contributor to premature motor failures, bearing deterioration, shaft voltage build up and electromagnetic interference. Intelligent control methods like Space Vector Pulse Width Modulation (SVPWM) techniques provide immense potential and flexibility to reduce CMV, thereby targeting all the afore mentioned problems. Other solutions like passive filters, shielded cables and EMI filters add to the volume and cost metrics of the entire system. Smart SVPWM techniques therefore, come with a very important advantage of being an economical solution. This thesis discusses a modified space vector technique applied to an Indirect Matrix Converter (IMC) which results in the reduction of common mode voltages and other advanced features. The conventional indirect space vector pulse-width modulation (SVPWM) method of controlling matrix converters involves the usage of two adjacent active vectors and one zero vector for both rectifying and inverting stages of the converter. By suitable selection of space vectors, the rectifying stage of the matrix converter can generate different levels of virtual DC-link voltage. This capability can be exploited for operation of the converter in different ranges of modulation indices for varying machine speeds. This results in lower common mode voltage and improves the harmonic spectrum of the output voltage, without increasing the number of switching transitions as compared to conventional modulation. To summarize it can be said that the responsibility of formulating output voltages with a particular magnitude and frequency has been transferred solely to the rectifying stage of the IMC. Estimation of degree of distortion in the three phase output voltage is another facet discussed in this thesis. An understanding of the SVPWM technique and the switching sequence of the space vectors in detail gives the potential to estimate the RMS value of the switched output voltage of any

Improved GRACE regional mass balance estimates of the Greenland Ice Sheet cross-validated with the input-output method (discussion paper)

NARCIS (Netherlands)

Xu, Z.; Schrama, E.J.O.; Van der Wal, W.; Van den Broeke, M.; Enderlin, E.M.

2015-01-01

In this study, we use satellite gravimetry data from the Gravity Recovery and Climate Experiment (GRACE) to estimate regional mass changes of the Greenland ice sheet (GrIS) and neighbouring glaciated regions using a least-squares inversion approach. We also consider results from the input-output

Integral-equation based methods for parameter estimation in output pulses of radiation detectors: Application in nuclear medicine and spectroscopy

Science.gov (United States)

Mohammadian-Behbahani, Mohammad-Reza; Saramad, Shahyar

2018-04-01

Model based analysis methods are relatively new approaches for processing the output data of radiation detectors in nuclear medicine imaging and spectroscopy. A class of such methods requires fast algorithms for fitting pulse models to experimental data. In order to apply integral-equation based methods for processing the preamplifier output pulses, this article proposes a fast and simple method for estimating the parameters of the well-known bi-exponential pulse model by solving an integral equation. The proposed method needs samples from only three points of the recorded pulse as well as its first and second order integrals. After optimizing the sampling points, the estimation results were calculated and compared with two traditional integration-based methods. Different noise levels (signal-to-noise ratios from 10 to 3000) were simulated for testing the functionality of the proposed method, then it was applied to a set of experimental pulses. Finally, the effect of quantization noise was assessed by studying different sampling rates. Promising results by the proposed method endorse it for future real-time applications.

Influence of the level of fit of a density probability function to wind-speed data on the WECS mean power output estimation

Energy Technology Data Exchange (ETDEWEB)

Carta, Jose A. [Department of Mechanical Engineering, University of Las Palmas de Gran Canaria, Campus de Tafira s/n, 35017 Las Palmas de Gran Canaria, Canary Islands (Spain); Ramirez, Penelope; Velazquez, Sergio [Department of Renewable Energies, Technological Institute of the Canary Islands, Pozo Izquierdo Beach s/n, 35119 Santa Lucia, Gran Canaria, Canary Islands (Spain)

2008-10-15

Static methods which are based on statistical techniques to estimate the mean power output of a WECS (wind energy conversion system) have been widely employed in the scientific literature related to wind energy. In the static method which we use in this paper, for a given wind regime probability distribution function and a known WECS power curve, the mean power output of a WECS is obtained by resolving the integral, usually using numerical evaluation techniques, of the product of these two functions. In this paper an analysis is made of the influence of the level of fit between an empirical probability density function of a sample of wind speeds and the probability density function of the adjusted theoretical model on the relative error {epsilon} made in the estimation of the mean annual power output of a WECS. The mean power output calculated through the use of a quasi-dynamic or chronological method, that is to say using time-series of wind speed data and the power versus wind speed characteristic of the wind turbine, serves as the reference. The suitability of the distributions is judged from the adjusted R{sup 2} statistic (R{sub a}{sup 2}). Hourly mean wind speeds recorded at 16 weather stations located in the Canarian Archipelago, an extensive catalogue of wind-speed probability models and two wind turbines of 330 and 800 kW rated power are used in this paper. Among the general conclusions obtained, the following can be pointed out: (a) that the R{sub a}{sup 2} statistic might be useful as an initial gross indicator of the relative error made in the mean annual power output estimation of a WECS when a probabilistic method is employed; (b) the relative errors tend to decrease, in accordance with a trend line defined by a second-order polynomial, as R{sub a}{sup 2} increases. (author)

Application of structured support vector machine backpropagation to a convolutional neural network for human pose estimation.

Science.gov (United States)

Witoonchart, Peerajak; Chongstitvatana, Prabhas

2017-08-01

In this study, for the first time, we show how to formulate a structured support vector machine (SSVM) as two layers in a convolutional neural network, where the top layer is a loss augmented inference layer and the bottom layer is the normal convolutional layer. We show that a deformable part model can be learned with the proposed structured SVM neural network by backpropagating the error of the deformable part model to the convolutional neural network. The forward propagation calculates the loss augmented inference and the backpropagation calculates the gradient from the loss augmented inference layer to the convolutional layer. Thus, we obtain a new type of convolutional neural network called an Structured SVM convolutional neural network, which we applied to the human pose estimation problem. This new neural network can be used as the final layers in deep learning. Our method jointly learns the structural model parameters and the appearance model parameters. We implemented our method as a new layer in the existing Caffe library. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Monte Carlo study on multiple output stochastic frontiers

DEFF Research Database (Denmark)

Henningsen, Geraldine; Henningsen, Arne; Jensen, Uwe

2015-01-01

, dividing all other output quantities by the selected outputquantity, and using these ratios as regressors (OD). Another approach is the stochasticray production frontier (SR), which transforms the output quantities into their Euclideandistance as the dependent variable and their polar coordinates...... of the approaches is clearly superior. However, considerable differences are found between the estimates at single replications. Taking average efficiencies from both approaches gives clearly better efficiency estimates than taking just the OD or the SR. In the case of zero values in the output quantities, the SR...

Pose Space Surface Manipulation

Directory of Open Access Journals (Sweden)

Yusuke Yoshiyasu

2012-01-01

Full Text Available Example-based mesh deformation techniques produce natural and realistic shapes by learning the space of deformations from examples. However, skeleton-based methods cannot manipulate a global mesh structure naturally, whereas the mesh-based approaches based on a translational control do not allow the user to edit a local mesh structure intuitively. This paper presents an example-driven mesh editing framework that achieves both global and local pose manipulations. The proposed system is built with a surface deformation method based on a two-step linear optimization technique and achieves direct manipulations of a model surface using translational and rotational controls. With the translational control, the user can create a model in natural poses easily. The rotational control can adjust the local pose intuitively by bending and twisting. We encode example deformations with a rotation-invariant mesh representation which handles large rotations in examples. To incorporate example deformations, we infer a pose from the handle translations/rotations and perform pose space interpolation, thereby avoiding involved nonlinear optimization. With the two-step linear approach combined with the proposed multiresolution deformation method, we can edit models at interactive rates without losing important deformation effects such as muscle bulging.

Use of Bayesian networks classifiers for long-term mean wind turbine energy output estimation at a potential wind energy conversion site

Energy Technology Data Exchange (ETDEWEB)

Carta, Jose A. [Department of Mechanical Engineering, University of Las Palmas de Gran Canaria, Campus de Tafira s/n, 35017 Las Palmas de Gran Canaria, Canary Islands (Spain); Velazquez, Sergio [Department of Electronics and Automatics Engineering, University of Las Palmas de Gran Canaria, Campus de Tafira s/n, 35017 Las Palmas de Gran Canaria, Canary Islands (Spain); Matias, J.M. [Department of Statistics, University of Vigo, Lagoas Marcosende, 36200 Vigo (Spain)

2011-02-15

Due to the interannual variability of wind speed a feasibility analysis for the installation of a Wind Energy Conversion System at a particular site requires estimation of the long-term mean wind turbine energy output. A method is proposed in this paper which, based on probabilistic Bayesian networks (BNs), enables estimation of the long-term mean wind speed histogram for a site where few measurements of the wind resource are available. For this purpose, the proposed method allows the use of multiple reference stations with a long history of wind speed and wind direction measurements. That is to say, the model that is proposed in this paper is able to involve and make use of regional information about the wind resource. With the estimated long-term wind speed histogram and the power curve of a wind turbine it is possible to use the method of bins to determine the long-term mean energy output for that wind turbine. The intelligent system employed, the knowledgebase of which is a joint probability function of all the model variables, uses efficient calculation techniques for conditional probabilities to perform the reasoning. This enables automatic model learning and inference to be performed efficiently based on the available evidence. The proposed model is applied in this paper to wind speeds and wind directions recorded at four weather stations located in the Canary Islands (Spain). Ten years of mean hourly wind speed and direction data are available for these stations. One of the conclusions reached is that the BN with three reference stations gave fewer errors between the real and estimated long-term mean wind turbine energy output than when using two measure-correlate-predict algorithms which were evaluated and which use a linear regression between the candidate station and one reference station. (author)

Use of Bayesian networks classifiers for long-term mean wind turbine energy output estimation at a potential wind energy conversion site

International Nuclear Information System (INIS)

Carta, Jose A.; Velazquez, Sergio; Matias, J.M.

2011-01-01

Due to the interannual variability of wind speed a feasibility analysis for the installation of a Wind Energy Conversion System at a particular site requires estimation of the long-term mean wind turbine energy output. A method is proposed in this paper which, based on probabilistic Bayesian networks (BNs), enables estimation of the long-term mean wind speed histogram for a site where few measurements of the wind resource are available. For this purpose, the proposed method allows the use of multiple reference stations with a long history of wind speed and wind direction measurements. That is to say, the model that is proposed in this paper is able to involve and make use of regional information about the wind resource. With the estimated long-term wind speed histogram and the power curve of a wind turbine it is possible to use the method of bins to determine the long-term mean energy output for that wind turbine. The intelligent system employed, the knowledgebase of which is a joint probability function of all the model variables, uses efficient calculation techniques for conditional probabilities to perform the reasoning. This enables automatic model learning and inference to be performed efficiently based on the available evidence. The proposed model is applied in this paper to wind speeds and wind directions recorded at four weather stations located in the Canary Islands (Spain). Ten years of mean hourly wind speed and direction data are available for these stations. One of the conclusions reached is that the BN with three reference stations gave fewer errors between the real and estimated long-term mean wind turbine energy output than when using two measure-correlate-predict algorithms which were evaluated and which use a linear regression between the candidate station and one reference station.

Association of HeartMate II left ventricular assist device flow estimate with thermodilution cardiac output.

Science.gov (United States)

Hasin, Tal; Huebner, Marianne; Li, Zhuo; Brown, Daniel; Stulak, John M; Boilson, Barry A; Joyce, Lyle; Pereira, Naveen L; Kushwaha, Sudhir S; Park, Soon J

2014-01-01

Cardiac output (CO) assessment is important in treating patients with heart failure. Durable left ventricular assist devices (LVADs) provide essentially all CO. In currently used LVADs, estimated device flow is generated by a computerized algorithm. However, LVAD flow estimate may be inaccurate in tracking true CO. We correlated LVAD (HeartMate II) flow with thermodilution CO during postoperative care (day 2-10 after implant) in 81 patients (5,616 paired measurements). Left ventricular assist device flow and CO correlated with a low correlation coefficient (r = 0.42). Left ventricular assist device readings were lower than CO measurements by approximately 0.36 L/min, trending for larger difference with higher values. Left ventricular assist device flow measurements showed less temporal variability compared with CO. Grouping for simultaneous measured blood pressure (BP device flow generally trends with measured CO, but large variability exists, hence flow measures should not be assumed to equal with CO. Clinicians should take into account variables such as high CO, BP, and opening of the aortic valve when interpreting LVAD flow readout. Direct flow sensors incorporated in the LVAD system may allow for better estimation.

Output-feedback control of combined sewer networks through receding horizon control with moving horizon estimation

Science.gov (United States)

Joseph-Duran, Bernat; Ocampo-Martinez, Carlos; Cembrano, Gabriela

2015-10-01

An output-feedback control strategy for pollution mitigation in combined sewer networks is presented. The proposed strategy provides means to apply model-based predictive control to large-scale sewer networks, in-spite of the lack of measurements at most of the network sewers. In previous works, the authors presented a hybrid linear control-oriented model for sewer networks together with the formulation of Optimal Control Problems (OCP) and State Estimation Problems (SEP). By iteratively solving these problems, preliminary Receding Horizon Control with Moving Horizon Estimation (RHC/MHE) results, based on flow measurements, were also obtained. In this work, the RHC/MHE algorithm has been extended to take into account both flow and water level measurements and the resulting control loop has been extensively simulated to assess the system performance according different measurement availability scenarios and rain events. All simulations have been carried out using a detailed physically based model of a real case-study network as virtual reality.

Extended Kalman filter-based methods for pose estimation using visual, inertial and magnetic sensors: comparative analysis and performance evaluation.

Science.gov (United States)

Ligorio, Gabriele; Sabatini, Angelo Maria

2013-02-04

In this paper measurements from a monocular vision system are fused with inertial/magnetic measurements from an Inertial Measurement Unit (IMU) rigidly connected to the camera. Two Extended Kalman filters (EKFs) were developed to estimate the pose of the IMU/camera sensor moving relative to a rigid scene (ego-motion), based on a set of fiducials. The two filters were identical as for the state equation and the measurement equations of the inertial/magnetic sensors. The DLT-based EKF exploited visual estimates of the ego-motion using a variant of the Direct Linear Transformation (DLT) method; the error-driven EKF exploited pseudo-measurements based on the projection errors from measured two-dimensional point features to the corresponding three-dimensional fiducials. The two filters were off-line analyzed in different experimental conditions and compared to a purely IMU-based EKF used for estimating the orientation of the IMU/camera sensor. The DLT-based EKF was more accurate than the error-driven EKF, less robust against loss of visual features, and equivalent in terms of computational complexity. Orientation root mean square errors (RMSEs) of 1° (1.5°), and position RMSEs of 3.5 mm (10 mm) were achieved in our experiments by the DLT-based EKF (error-driven EKF); by contrast, orientation RMSEs of 1.6° were achieved by the purely IMU-based EKF.

Money and Output: A Test of Reverse Causation.

OpenAIRE

Coleman, Wilbur John, II

1996-01-01

This paper attempts to explain the correlation between money and output at various leads and lags with a model in which money is largely neutral and endogenously responds to output. Money is endogenous because both monetary policy and deposit creation are endogenous. Parameters are selected according to the simulated moments estimation technique. While the estimated model succeeds along some dimensions in matching properties of postwar U.S. data, its failure to match key patterns of lead-lag ...

A Comprehensive Estimation of the Economic Effects of Meteorological Services Based on the Input-Output Method

Directory of Open Access Journals (Sweden)

Xianhua Wu

2014-01-01

Full Text Available Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27–1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30–1 : 51. Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries.

Explaining output volatility: The case of taxation

DEFF Research Database (Denmark)

Posch, Olaf

the second moment of output growth rates without (long-run) effects on the first moment. Taking the model to the data, we exploit observed heterogeneity patterns to estimate effects of tax rates on macro volatility using panel estimation, explicitly modeling the unobserved variance process. We find a strong......This paper studies the effects of taxation on output volatility in OECD countries to shed light on the sources of observed heterogeneity over time and across countries. To this end, we derive tax effects on macro aggregates in a stochastic neoclassical model. As a result, taxes are shown to affect...... positive effects....

A use-side procedure for estimating trade margins in input-output analysis

Directory of Open Access Journals (Sweden)

Marisa Asensio Pardo

2005-01-01

Full Text Available According to the National Accounting Systems proposed by United Nations (1993 and Eurostat (1996, use and make (or supply matrices should be measured before goods and services are conveyed to the markets (basic values. Actually, the make table is defined in basic values (excluding trade and transport margins and net commodity taxes whereas the use table is in purchasers’ values (including them. In particular, this paper shows how trade margins can be removed from the use table with the purpose of constructing an input-output table. The proposed approach is based on the use-side procedure from the ESA-95 Input-Output Manual (Eurostat, 2002 and is also being applied to the forthcoming 2000 Andalusian Input-Output Framework.

Pengenalan Pose Tangan Menggunakan HuMoment

Directory of Open Access Journals (Sweden)

Dina Budhi Utami

2017-02-01

Full Text Available Computer vision yang didasarkan pada pengenalan bentuk memiliki banyak potensi dalam interaksi manusia dan komputer. Pose tangan dapat dijadikan simbol interaksi manusia dengan komputer seperti halnya pada penggunaan berbagai pose tangan pada bahasa isyarat. Berbagai pose tangan dapat digunakan untuk menggantikan fungsi mouse, untuk mengendalikan robot, dan sebagainya. Penelitian ini difokuskan pada pembangunan sistem pengenalan pose tangan menggunakan HuMoment. Proses pengenalan pose tangan dimulai dengan melakukan segmentasi citra masukan untuk menghasilkan citra ROI (Region of Interest yaitu area telapak tangan. Selanjutnya dilakukan proses deteksi tepi. Kemudian dilakukan ekstraksi nilai HuMoment. Nilai HuMoment dikuantisasikan ke dalam bukukode yang dihasilkan dari proses pelatihan menggunakan K-Means. Proses kuantisasi dilakukan dengan menghitung nilai Euclidean Distance terkecil antara nilai HuMomment citra masukan dan bukukode. Berdasarkan hasil penelitian, nilai akurasi sistem dalam mengenali pose tangan adalah 88.57%.

A Monte Carlo Study on Multiple Output Stochastic Frontiers

DEFF Research Database (Denmark)

Henningsen, Géraldine; Henningsen, Arne; Jensen, Uwe

, dividing all other output quantities by the selected output quantity, and using these ratios as regressors (OD). Another approach is the stochastic ray production frontier (SR) which transforms the output quantities into their Euclidean distance as the dependent variable and their polar coordinates......In the estimation of multiple output technologies in a primal approach, the main question is how to handle the multiple outputs. Often an output distance function is used, where the classical approach is to exploit its homogeneity property by selecting one output quantity as the dependent variable...... of both specifications for the case of a Translog output distance function with respect to different common statistical problems as well as problems arising as a consequence of zero values in the output quantities. Although, our results partly show clear reactions to statistical misspecifications...

Output-Only Modal Parameter Recursive Estimation of Time-Varying Structures via a Kernel Ridge Regression FS-TARMA Approach

Directory of Open Access Journals (Sweden)

Zhi-Sai Ma

2017-01-01

Full Text Available Modal parameter estimation plays an important role in vibration-based damage detection and is worth more attention and investigation, as changes in modal parameters are usually being used as damage indicators. This paper focuses on the problem of output-only modal parameter recursive estimation of time-varying structures based upon parameterized representations of the time-dependent autoregressive moving average (TARMA. A kernel ridge regression functional series TARMA (FS-TARMA recursive identification scheme is proposed and subsequently employed for the modal parameter estimation of a numerical three-degree-of-freedom time-varying structural system and a laboratory time-varying structure consisting of a simply supported beam and a moving mass sliding on it. The proposed method is comparatively assessed against an existing recursive pseudolinear regression FS-TARMA approach via Monte Carlo experiments and shown to be capable of accurately tracking the time-varying dynamics in a recursive manner.

Global Sensitivity Analysis for multivariate output using Polynomial Chaos Expansion

International Nuclear Information System (INIS)

Garcia-Cabrejo, Oscar; Valocchi, Albert

2014-01-01

Many mathematical and computational models used in engineering produce multivariate output that shows some degree of correlation. However, conventional approaches to Global Sensitivity Analysis (GSA) assume that the output variable is scalar. These approaches are applied on each output variable leading to a large number of sensitivity indices that shows a high degree of redundancy making the interpretation of the results difficult. Two approaches have been proposed for GSA in the case of multivariate output: output decomposition approach [9] and covariance decomposition approach [14] but they are computationally intensive for most practical problems. In this paper, Polynomial Chaos Expansion (PCE) is used for an efficient GSA with multivariate output. The results indicate that PCE allows efficient estimation of the covariance matrix and GSA on the coefficients in the approach defined by Campbell et al. [9], and the development of analytical expressions for the multivariate sensitivity indices defined by Gamboa et al. [14]. - Highlights: • PCE increases computational efficiency in 2 approaches of GSA of multivariate output. • Efficient estimation of covariance matrix of output from coefficients of PCE. • Efficient GSA on coefficients of orthogonal decomposition of the output using PCE. • Analytical expressions of multivariate sensitivity indices from coefficients of PCE

Hardware in the Loop Performance Assessment of LIDAR-Based Spacecraft Pose Determination.

Science.gov (United States)

Opromolla, Roberto; Fasano, Giancarmine; Rufino, Giancarlo; Grassi, Michele

2017-09-24

In this paper an original, easy to reproduce, semi-analytic calibration approach is developed for hardware-in-the-loop performance assessment of pose determination algorithms processing point cloud data, collected by imaging a non-cooperative target with LIDARs. The laboratory setup includes a scanning LIDAR, a monocular camera, a scaled-replica of a satellite-like target, and a set of calibration tools. The point clouds are processed by uncooperative model-based algorithms to estimate the target relative position and attitude with respect to the LIDAR. Target images, acquired by a monocular camera operated simultaneously with the LIDAR, are processed applying standard solutions to the Perspective- n -Points problem to get high-accuracy pose estimates which can be used as a benchmark to evaluate the accuracy attained by the LIDAR-based techniques. To this aim, a precise knowledge of the extrinsic relative calibration between the camera and the LIDAR is essential, and it is obtained by implementing an original calibration approach which does not need ad-hoc homologous targets (e.g., retro-reflectors) easily recognizable by the two sensors. The pose determination techniques investigated by this work are of interest to space applications involving close-proximity maneuvers between non-cooperative platforms, e.g., on-orbit servicing and active debris removal.

Measuring nuclear power plant output by neutrino detection

International Nuclear Information System (INIS)

Korovkin, V.A.; Kodanev, S.A.; Panashchenko, N.S.; Sokolov, D.A.; Solov'yanov, O.M.; Tverdovskii, N.D.; Yarichin, A.D.; Ketov, S.N.; Kopeikin, V.I.; Machulin, I.N.; Mikaelyan, L.A.; Sinev, V.V.

1989-01-01

Neutrino emission from a reactor is inseparably linked with the fission process of heavy nuclei: each fission contributes a specific amount to the overall power output and gives rise to neutrinos which are emitted by the fission fragments created. Using a detector to record the neutrino flux gives a curve for the number of nuclei undergoing fission and the reactor power output. The question of whether it is practically possible to make use of neutrino emission from reactors was first posed in the mid-70s in connection with preparations for neutrino research at the Roven nuclear power plant (RAES) and in 1986 at an IAEA symposium on the topic of guarantees. Since 1982, research has been carried on at RAES on the fundamental properties and interactions of neutrinos. Based on this research and in parallel with it, in 1983 specialists from the Kurchatov Nuclear Power Institute and RAES jointly conducted an experiment which demonstrated in principle the possibility of remotely measuring reactor power output using the neutrino emission. This experiment had extremely limited statistics and is of interest today as the first demonstration of practical usage of neutrino emission from a reactor. At present the statistics for detecting neutrino events have increased tenfold and experience in lengthy measurements has been accumulated. This allows better analysis for the possibilities of the method. This paper reviews neutrino detection, theoretical bases of the method, determining the fission scale values for converting a number of neutrinos into power output, and measuring the power output

Output Feedback Tracking Control of an Underactuated Quad-Rotor UAV

National Research Council Canada - National Science Library

Lee, DongBin; Burg, Timothy; Xian, Bin; Dawson, Darren

2006-01-01

...) using output feedback (OFB). Specifically, an observer is designed to estimate the velocities and an output feedback controller is designed for a nonlinear UAV system in which only position and angles are measurable...

Inverse Free Iterative Methods for Nonlinear Ill-Posed Operator Equations

Directory of Open Access Journals (Sweden)

Ioannis K. Argyros

2014-01-01

ill-posed operator equation F(x=y. The proposed method is a modified form of Tikhonov gradient (TIGRA method considered by Ramlau (2003. The regularization parameter is chosen according to the balancing principle considered by Pereverzev and Schock (2005. The error estimate is derived under a general source condition and is of optimal order. Some numerical examples involving integral equations are also given in this paper.

Problem posing reflections and applications

CERN Document Server

Brown, Stephen I

2014-01-01

As a result of the editors' collaborative teaching at Harvard in the late 1960s, they produced a ground-breaking work -- The Art Of Problem Posing -- which related problem posing strategies to the already popular activity of problem solving. It took the concept of problem posing and created strategies for engaging in that activity as a central theme in mathematics education. Based in part upon that work and also upon a number of articles by its authors, other members of the mathematics education community began to apply and expand upon their ideas. This collection of thirty readings is a tes

Output Feedback Distributed Containment Control for High-Order Nonlinear Multiagent Systems.

Science.gov (United States)

Li, Yafeng; Hua, Changchun; Wu, Shuangshuang; Guan, Xinping

2017-01-31

In this paper, we study the problem of output feedback distributed containment control for a class of high-order nonlinear multiagent systems under a fixed undirected graph and a fixed directed graph, respectively. Only the output signals of the systems can be measured. The novel reduced order dynamic gain observer is constructed to estimate the unmeasured state variables of the system with the less conservative condition on nonlinear terms than traditional Lipschitz one. Via the backstepping method, output feedback distributed nonlinear controllers for the followers are designed. By means of the novel first virtual controllers, we separate the estimated state variables of different agents from each other. Consequently, the designed controllers show independence on the estimated state variables of neighbors except outputs information, and the dynamics of each agent can be greatly different, which make the design method have a wider class of applications. Finally, a numerical simulation is presented to illustrate the effectiveness of the proposed method.

Gas geochemistry and preliminary CO2 output estimation from the island of Kos (Greece)

Science.gov (United States)

D'Alessandro, Walter; Daskalopoulou, Kyriaki; Calabrese, Sergio; Longo, Manfredi; Kyriakopoulos, Konstantinos; Gagliano, Antonina Lisa

2017-04-01

Several gas samples have been collected from natural gas manifestations at the island of Kos. Most of them are found underwater along the southern coast of the island. On land two anomalous degassing areas have been recognized. These are characterised by lack of vegetation and after long dry periods by the presence of sulfate salts efflorescences. Almost all the gases are CO2-dominated (CO2 ranging from 88 to 99%) with minor amounts of N2 (up to 7%) and CH4 (up to 2.6%). Only the on-land manifestations have also significant contents of H2 (up to 0.2%) and H2S (up to 0.3%). Only one underwater manifestation is N2-dominated (61-99%) with CH4 (0.6-11%) and low CO2 (0.1-26%). The isotopic composition of He shows values ranging from 0.84 to 6.72 R/RA indicating a sometimes strong mantle contribution with the highest values measured in two of the most strongly degassing areas (Paradise Beach and Volcania). C-isotopic composition of CO2 is in the range from -3.6 to 0.6 ‰ vs V-PDB with most of the values around -1‰ indicating a mixed mantle - limestones origin. Isotopic composition of CH4, ranging from -21.5 to 2.8‰ for C and from -143 to 36‰ for H, points to a geothermal origin with sometimes evident secondary oxidation processes. CO2-flux measurements showed values up to about 10,000 g/m2/day in the areas of Volcania and Kokkino Nero and up to about 50,000 g/m2/day at Paradise beach. Preliminary CO2 output estimations gave values of 8.8 and 4 tons/day for the first two areas respectively and of 2.7 tons/day for the latter. The total output of the island (15.5 tons/day) should be considered a minimum estimation because of the incomplete coverage of the area and is comparable to the other active volcanic/geothermal systems of Greece (Nisyros, Nea Kameni and Methana).

Adaptive nonlinear robust relative pose control of spacecraft autonomous rendezvous and proximity operations.

Science.gov (United States)

Sun, Liang; Huo, Wei; Jiao, Zongxia

2017-03-01

This paper studies relative pose control for a rigid spacecraft with parametric uncertainties approaching to an unknown tumbling target in disturbed space environment. State feedback controllers for relative translation and relative rotation are designed in an adaptive nonlinear robust control framework. The element-wise and norm-wise adaptive laws are utilized to compensate the parametric uncertainties of chaser and target spacecraft, respectively. External disturbances acting on two spacecraft are treated as a lumped and bounded perturbation input for system. To achieve the prescribed disturbance attenuation performance index, feedback gains of controllers are designed by solving linear matrix inequality problems so that lumped disturbance attenuation with respect to the controlled output is ensured in the L 2 -gain sense. Moreover, in the absence of lumped disturbance input, asymptotical convergence of relative pose are proved by using the Lyapunov method. Numerical simulations are performed to show that position tracking and attitude synchronization are accomplished in spite of the presence of couplings and uncertainties. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Financial Development and Output Growth: A Panel Study for Asian Countries

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Sangjoon Jun

2012-03-01

Full Text Available This paper investigates the relationship between financial markets and output growth for a panel of 27 Asian countries over 1960-2009. It utilizes the recently-developed panel cointegration techniques to test and estimate the long-run equilibrium relationship between real GDP and financial development proxies. Real GDP and financial development variables are found to have unit roots and to be cointegrated, based on various panel unit root tests and panel cointegration tests. We find that there is a statistically significant positive bi-directional cointegrating relationship between financial development and output growth by three distinct methods of panel cointegration estimation. Empirical findings suggest that financial market development promotes output growth and in turn output growth stimulates further financial development.

Modeling the power output of piezoelectric energy harvesters

KAUST Repository

Al Ahmad, Mahmoud

2011-04-30

Design of experiments and multiphysics analyses were used to develop a parametric model for a d 33-based cantilever. The analysis revealed that the most significant parameters influencing the resonant frequency are the supporting layer thickness, piezoelectric layer thickness, and cantilever length. On the other hand, the most important factors affecting the charge output arethe piezoelectric thickness and the interdigitated electrode dimensions. The accuracy of the developed model was confirmed and showed less than 1% estimation error compared with a commercial simulation package. To estimate the power delivered to a load, the electric current output from the piezoelectric generator was calculated. A circuit model was built and used to estimate the power delivered to a load, which compared favorably to experimentally published power data on actual cantilevers of similar dimensions. © 2011 TMS.

Modeling the power output of piezoelectric energy harvesters

KAUST Repository

Al Ahmad, Mahmoud; Alshareef, Husam N.

2011-01-01

Design of experiments and multiphysics analyses were used to develop a parametric model for a d 33-based cantilever. The analysis revealed that the most significant parameters influencing the resonant frequency are the supporting layer thickness, piezoelectric layer thickness, and cantilever length. On the other hand, the most important factors affecting the charge output arethe piezoelectric thickness and the interdigitated electrode dimensions. The accuracy of the developed model was confirmed and showed less than 1% estimation error compared with a commercial simulation package. To estimate the power delivered to a load, the electric current output from the piezoelectric generator was calculated. A circuit model was built and used to estimate the power delivered to a load, which compared favorably to experimentally published power data on actual cantilevers of similar dimensions. © 2011 TMS.

Web-based visualisation of head pose and facial expressions changes: monitoring human activity using depth data

OpenAIRE

Kalliatakis, Grigorios; Vidakis, Nikolaos; Triantafyllidis, Georgios

2017-01-01

Despite significant recent advances in the field of head pose estimation and facial expression recognition, raising the cognitive level when analysing human activity presents serious challenges to current concepts. Motivated by the need of generating comprehensible visual representations from different sets of data, we introduce a system capable of monitoring human activity through head pose and facial expression changes, utilising an affordable 3D sensing technology (Microsoft Kinect sensor)...

Output Error Method for Tiltrotor Unstable in Hover

Directory of Open Access Journals (Sweden)

Lichota Piotr

2017-03-01

Full Text Available This article investigates unstable tiltrotor in hover system identification from flight test data. The aircraft dynamics was described by a linear model defined in Body-Fixed-Coordinate System. Output Error Method was selected in order to obtain stability and control derivatives in lateral motion. For estimating model parameters both time and frequency domain formulations were applied. To improve the system identification performed in the time domain, a stabilization matrix was included for evaluating the states. In the end, estimates obtained from various Output Error Method formulations were compared in terms of parameters accuracy and time histories. Evaluations were performed in MATLAB R2009b environment.

Relationship between cardiac output and effective renal plasma flow in patients with cardiac disease

Energy Technology Data Exchange (ETDEWEB)

McGriffin, D; Tauxe, W N; Lewis, C; Karp, R; Mantle, J

1984-12-01

The relationship between effective renal plasma flow (ERPF) and cardiac output was examined in 46 patients (22 with congestive heart failure and 24 following cardiac surgical procedures) by simultaneously measuring the global ERPF by the single-injection method and cardiac output by the thermodilution method. Of the patients in the heart-failure group, 21 also had pulmonary artery end diastolic pressure (PAEDP) recorded at the same time. ERPF and cardiac output were found to be related by the regression equations: cardiac output = 2.08 + 0.0065 ERPF (r, 080), with a SE of estimate of 0.81 l/min. ERPF and PAEDP were related by the regression equation: PAEDP = 42.02 - 0.0675 ERPF (r, 0.86), with a SE of estimate of 5.5 mm Hg. ERPF may be a useful noninvasive method of estimating cardiac output if it is known that no intrinsic kidney disease is present, and if the error of 0.81 l/min (1 SE of estimate) is within the range of clinical usefulness. The error is principally attributable to the determination of cardiac output by the thermodilution method.

Problems in Modelling Charge Output Accelerometers

Directory of Open Access Journals (Sweden)

Tomczyk Krzysztof

2016-12-01

Full Text Available The paper presents major issues associated with the problem of modelling change output accelerometers. The presented solutions are based on the weighted least squares (WLS method using transformation of the complex frequency response of the sensors. The main assumptions of the WLS method and a mathematical model of charge output accelerometers are presented in first two sections of this paper. In the next sections applying the WLS method to estimation of the accelerometer model parameters is discussed and the associated uncertainties are determined. Finally, the results of modelling a PCB357B73 charge output accelerometer are analysed in the last section of this paper. All calculations were executed using the MathCad software program. The main stages of these calculations are presented in Appendices A−E.

Handheld pose tracking using vision-inertial sensors with occlusion handling

Science.gov (United States)

Li, Juan; Slembrouck, Maarten; Deboeverie, Francis; Bernardos, Ana M.; Besada, Juan A.; Veelaert, Peter; Aghajan, Hamid; Casar, José R.; Philips, Wilfried

2016-07-01

Tracking of a handheld device's three-dimensional (3-D) position and orientation is fundamental to various application domains, including augmented reality (AR), virtual reality, and interaction in smart spaces. Existing systems still offer limited performance in terms of accuracy, robustness, computational cost, and ease of deployment. We present a low-cost, accurate, and robust system for handheld pose tracking using fused vision and inertial data. The integration of measurements from embedded accelerometers reduces the number of unknown parameters in the six-degree-of-freedom pose calculation. The proposed system requires two light-emitting diode (LED) markers to be attached to the device, which are tracked by external cameras through a robust algorithm against illumination changes. Three data fusion methods have been proposed, including the triangulation-based stereo-vision system, constraint-based stereo-vision system with occlusion handling, and triangulation-based multivision system. Real-time demonstrations of the proposed system applied to AR and 3-D gaming are also included. The accuracy assessment of the proposed system is carried out by comparing with the data generated by the state-of-the-art commercial motion tracking system OptiTrack. Experimental results show that the proposed system has achieved high accuracy of few centimeters in position estimation and few degrees in orientation estimation.

Multi-task pose-invariant face recognition.

Science.gov (United States)

Ding, Changxing; Xu, Chang; Tao, Dacheng

2015-03-01

Face images captured in unconstrained environments usually contain significant pose variation, which dramatically degrades the performance of algorithms designed to recognize frontal faces. This paper proposes a novel face identification framework capable of handling the full range of pose variations within ±90° of yaw. The proposed framework first transforms the original pose-invariant face recognition problem into a partial frontal face recognition problem. A robust patch-based face representation scheme is then developed to represent the synthesized partial frontal faces. For each patch, a transformation dictionary is learnt under the proposed multi-task learning scheme. The transformation dictionary transforms the features of different poses into a discriminative subspace. Finally, face matching is performed at patch level rather than at the holistic level. Extensive and systematic experimentation on FERET, CMU-PIE, and Multi-PIE databases shows that the proposed method consistently outperforms single-task-based baselines as well as state-of-the-art methods for the pose problem. We further extend the proposed algorithm for the unconstrained face verification problem and achieve top-level performance on the challenging LFW data set.

Estimation of Potential GDP and output Gap. Comparative Perspective

Directory of Open Access Journals (Sweden)

Dorin Măntescu

2014-08-01

Full Text Available The purpose of the analysis is to assess the impact of the crisis on the potential output and output gaps, to study their evolution by using a comparative approach for a sample of EU countries that were in majority included recently in financial assistance and macroeconomic adjustment programmes. The potential GDP growth rates calculated using the Cobb Douglas production function and Hodrick-Prescott methodology, decelerated substantially across the board in the countries studied once the international economic and financial crisis hit, recording even negative rates of growth in Cyprus, Greece, Portugal, Italy and Spain. In addition to the specific factors that characterise each country, there is a series of common features that will affect the developments of the potential GDP on a long-term basis, such as the increase of global risk aversion correlated with the reduction of the banking exposures, the slow economic recovery in the EU, and last but not least the incoming ageing process, which will exert an additional negative impact on the growth potential of the EU member states. The article makes a series of economic policy recommendations to promote key measures aiming to increase the flexibility of the goods, services, and labour markets, to improve the prioritisation of public expenditures especially capital spending, and to improve the management of the public assets including real estate and public buildings by promoting a mix of measures including privatisation, monetisation and a wider involvement of the private sector in their management.

Pose Estimation of a Mobile Robot Based on Fusion of IMU Data and Vision Data Using an Extended Kalman Filter.

Science.gov (United States)

Alatise, Mary B; Hancke, Gerhard P

2017-09-21

Using a single sensor to determine the pose estimation of a device cannot give accurate results. This paper presents a fusion of an inertial sensor of six degrees of freedom (6-DoF) which comprises the 3-axis of an accelerometer and the 3-axis of a gyroscope, and a vision to determine a low-cost and accurate position for an autonomous mobile robot. For vision, a monocular vision-based object detection algorithm speeded-up robust feature (SURF) and random sample consensus (RANSAC) algorithms were integrated and used to recognize a sample object in several images taken. As against the conventional method that depend on point-tracking, RANSAC uses an iterative method to estimate the parameters of a mathematical model from a set of captured data which contains outliers. With SURF and RANSAC, improved accuracy is certain; this is because of their ability to find interest points (features) under different viewing conditions using a Hessain matrix. This approach is proposed because of its simple implementation, low cost, and improved accuracy. With an extended Kalman filter (EKF), data from inertial sensors and a camera were fused to estimate the position and orientation of the mobile robot. All these sensors were mounted on the mobile robot to obtain an accurate localization. An indoor experiment was carried out to validate and evaluate the performance. Experimental results show that the proposed method is fast in computation, reliable and robust, and can be considered for practical applications. The performance of the experiments was verified by the ground truth data and root mean square errors (RMSEs).

Satellite markers: a simple method for ground truth car pose on stereo video

Science.gov (United States)

Gil, Gustavo; Savino, Giovanni; Piantini, Simone; Pierini, Marco

2018-04-01

Artificial prediction of future location of other cars in the context of advanced safety systems is a must. The remote estimation of car pose and particularly its heading angle is key to predict its future location. Stereo vision systems allow to get the 3D information of a scene. Ground truth in this specific context is associated with referential information about the depth, shape and orientation of the objects present in the traffic scene. Creating 3D ground truth is a measurement and data fusion task associated with the combination of different kinds of sensors. The novelty of this paper is the method to generate ground truth car pose only from video data. When the method is applied to stereo video, it also provides the extrinsic camera parameters for each camera at frame level which are key to quantify the performance of a stereo vision system when it is moving because the system is subjected to undesired vibrations and/or leaning. We developed a video post-processing technique which employs a common camera calibration tool for the 3D ground truth generation. In our case study, we focus in accurate car heading angle estimation of a moving car under realistic imagery. As outcomes, our satellite marker method provides accurate car pose at frame level, and the instantaneous spatial orientation for each camera at frame level.

Students’ Creativity: Problem Posing in Structured Situation

Science.gov (United States)

Amalina, I. K.; Amirudin, M.; Budiarto, M. T.

2018-01-01

This is a qualitative research concerning on students’ creativity on problem posing task. The study aimed at describing the students’ creative thinking ability to pose the mathematics problem in structured situations with varied condition of given problems. In order to find out the students’ creative thinking ability, an analysis of mathematics problem posing test based on fluency, novelty, and flexibility and interview was applied for categorizing students’ responses on that task. The data analysis used the quality of problem posing and categorized in 4 level of creativity. The results revealed from 29 secondary students grade 8, a student in CTL (Creative Thinking Level) 1 met the fluency. A student in CTL 2 met the novelty, while a student in CTL 3 met both fluency and novelty and no one in CTL 4. These results are affected by students’ mathematical experience. The findings of this study highlight that student’s problem posing creativity are dependent on their experience in mathematics learning and from the point of view of which students start to pose problem.

Estimation of Truck Trips on Large-Scale Irrigation Project: A Combinatory Input-Output Commodity-Based Approach

Directory of Open Access Journals (Sweden)

Ackchai Sirikijpanichkul

2015-01-01

Full Text Available For the agricultural-based countries, the requirement on transportation infrastructure should not only be limited to accommodate general traffic but also the transportation of crop and agricultural products during the harvest seasons. Most of the past researches focus on the development of truck trip estimation techniques for urban, statewide, or nationwide freight movement but neglect the importance of rural freight movement which contributes to pavement deterioration on rural roads especially during harvest seasons. Recently, the Thai Government initiated a plan to construct a network of reservoirs within the northeastern region, aiming at improving existing irrigation system particularly in the areas where a more effective irrigation system is needed. It is expected to bring in new opportunities on expanding the cultivation areas, increasing the economy of scale and enlarging the extent market of area. As a consequence, its effects on truck trip generation needed to be investigated to assure the service quality of related transportation infrastructure. This paper proposes a combinatory input-output commodity-based approach to estimate truck trips on rural highway infrastructure network. The large-scale irrigation project for the northeastern of Thailand is demonstrated as a case study.

Direction-of-arrival estimation for co-located multiple-input multiple-output radar using structural sparsity Bayesian learning

Science.gov (United States)

Wen, Fang-Qing; Zhang, Gong; Ben, De

2015-11-01

This paper addresses the direction of arrival (DOA) estimation problem for the co-located multiple-input multiple-output (MIMO) radar with random arrays. The spatially distributed sparsity of the targets in the background makes compressive sensing (CS) desirable for DOA estimation. A spatial CS framework is presented, which links the DOA estimation problem to support recovery from a known over-complete dictionary. A modified statistical model is developed to accurately represent the intra-block correlation of the received signal. A structural sparsity Bayesian learning algorithm is proposed for the sparse recovery problem. The proposed algorithm, which exploits intra-signal correlation, is capable being applied to limited data support and low signal-to-noise ratio (SNR) scene. Furthermore, the proposed algorithm has less computation load compared to the classical Bayesian algorithm. Simulation results show that the proposed algorithm has a more accurate DOA estimation than the traditional multiple signal classification (MUSIC) algorithm and other CS recovery algorithms. Project supported by the National Natural Science Foundation of China (Grant Nos. 61071163, 61271327, and 61471191), the Funding for Outstanding Doctoral Dissertation in Nanjing University of Aeronautics and Astronautics, China (Grant No. BCXJ14-08), the Funding of Innovation Program for Graduate Education of Jiangsu Province, China (Grant No. KYLX 0277), the Fundamental Research Funds for the Central Universities, China (Grant No. 3082015NP2015504), and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PADA), China.

Output, renewable energy consumption and trade in Africa

International Nuclear Information System (INIS)

Ben Aïssa, Mohamed Safouane; Ben Jebli, Mehdi; Ben Youssef, Slim

2014-01-01

We use panel cointegration techniques to examine the relationship between renewable energy consumption, trade and output in a sample of 11 African countries covering the period 1980–2008. The results from panel error correction model reveal that there is evidence of a bidirectional causality between output and exports and between output and imports in both the short and long-run. However, in the short-run, there is no evidence of causality between output and renewable energy consumption and between trade (exports or imports) and renewable energy consumption. Also, in the long-run, there is no causality running from output or trade to renewable energy. In the long-run, our estimations show that renewable energy consumption and trade have a statistically significant and positive impact on output. Our energy policy recommendations are that national authorities should design appropriate fiscal incentives to encourage the use of renewable energies, create more regional economic integration for renewable energy technologies, and encourage trade openness because of its positive impact on technology transfer and on output. - Highlights: • We examine the relationship between renewable energy consumption, trade and output in African countries. • There is a bidirectional causality between output and trade in both the short and long-run. • In the short-run, there is no causality between renewable energy consumption and trade or output. • In the long-run, renewable energy consumption and trade have a statistically significant positive impact on output. • African authorities should encourage trade openness because of its positive impact on technology transfer and on output

Pilot Study: Estimation of Stroke Volume and Cardiac Output from Pulse Wave Velocity.

Directory of Open Access Journals (Sweden)

Yurie Obata

Full Text Available Transesophageal echocardiography (TEE is increasingly replacing thermodilution pulmonary artery catheters to assess hemodynamics in patients at high risk for cardiovascular morbidity. However, one of the drawbacks of TEE compared to pulmonary artery catheters is the inability to measure real time stroke volume (SV and cardiac output (CO continuously. The aim of the present proof of concept study was to validate a novel method of SV estimation, based on pulse wave velocity (PWV in patients undergoing cardiac surgery.This is a retrospective observational study. We measured pulse transit time by superimposing the radial arterial waveform onto the continuous wave Doppler waveform of the left ventricular outflow tract, and calculated SV (SVPWV using the transformed Bramwell-Hill equation. The SV measured by TEE (SVTEE was used as a reference.A total of 190 paired SV were measured from 28 patients. A strong correlation was observed between SVPWV and SVTEE with the coefficient of determination (R2 of 0.71. A mean difference between the two (bias was 3.70 ml with the limits of agreement ranging from -20.33 to 27.73 ml and a percentage error of 27.4% based on a Bland-Altman analysis. The concordance rate of two methods was 85.0% based on a four-quadrant plot. The angular concordance rate was 85.9% with radial limits of agreement (the radial sector that contained 95% of the data points of ± 41.5 degrees based on a polar plot.PWV based SV estimation yields reasonable agreement with SV measured by TEE. Further studies are required to assess its utility in different clinical situations.

Assessing exposure risks for aquatic organisms posed by Tamiflu use under seasonal influenza and pandemic conditions

International Nuclear Information System (INIS)

Chen, Wei-Yu; Lin, Chia-Jung; Liao, Chung-Min

2014-01-01

Environmental pollution by anti-influenza drugs is increasingly recognized as a threat to aquatic environments. However, little is known about empirical data on risk effects posed by environmentally relevant concentrations of anti-influenza drug based on recently published ecotoxicological researches in Taiwan. Here we linked ecotoxicology models with an epidemiological scheme to assess exposure risks of aquatic organisms and environmental hazards posed by antiviral oseltamivir (Tamiflu) use in Taiwan. Built on published bioassays, we used probabilistic risk assessment model to estimate potential threats of environmentally relevant hazards on algae, daphnid, and zerbrafish. We found that Tamiflu use was unlikely to pose a significant chronic environmental risk to daphnia and zebrafish during seasonal influenza. However, the chronic environmental risk posed by Tamiflu use during pandemic was alarming. We conclude that no significant risk to algal growth was found during seasonal influenza and high pandemic Tamiflu use. -- Highlights: • Environmentally relevant concentrations of anti-influenza drug have ecotoxicologically important effects. • Tamiflu is unlikely to pose a significant chronic environmental risk during seasonal influenza. • Chronic environmental risk posed by Tamiflu during pandemic is alarming. • Tertiary process in sewage treatment plants is crucial in mitigating Tamiflu exposure risk. -- A probabilistic framework can be used for assessing exposure risks posed by environmentally relevant concentrations of anti-influenza drug in aquatic ecosystems

Numerical methods for the design of large-scale nonlinear discrete ill-posed inverse problems

International Nuclear Information System (INIS)

Haber, E; Horesh, L; Tenorio, L

2010-01-01

Design of experiments for discrete ill-posed problems is a relatively new area of research. While there has been some limited work concerning the linear case, little has been done to study design criteria and numerical methods for ill-posed nonlinear problems. We present an algorithmic framework for nonlinear experimental design with an efficient numerical implementation. The data are modeled as indirect, noisy observations of the model collected via a set of plausible experiments. An inversion estimate based on these data is obtained by a weighted Tikhonov regularization whose weights control the contribution of the different experiments to the data misfit term. These weights are selected by minimization of an empirical estimate of the Bayes risk that is penalized to promote sparsity. This formulation entails a bilevel optimization problem that is solved using a simple descent method. We demonstrate the viability of our design with a problem in electromagnetic imaging based on direct current resistivity and magnetotelluric data

Macrobend optical sensing for pose measurement in soft robot arms

International Nuclear Information System (INIS)

Sareh, Sina; Noh, Yohan; Liu, Hongbin; Althoefer, Kaspar; Li, Min; Ranzani, Tommaso

2015-01-01

This paper introduces a pose-sensing system for soft robot arms integrating a set of macrobend stretch sensors. The macrobend sensory design in this study consists of optical fibres and is based on the notion that bending an optical fibre modulates the intensity of the light transmitted through the fibre. This sensing method is capable of measuring bending, elongation and compression in soft continuum robots and is also applicable to wearable sensing technologies, e.g. pose sensing in the wrist joint of a human hand. In our arrangement, applied to a cylindrical soft robot arm, the optical fibres for macrobend sensing originate from the base, extend to the tip of the arm, and then loop back to the base. The connectors that link the fibres to the necessary opto-electronics are all placed at the base of the arm, resulting in a simplified overall design. The ability of this custom macrobend stretch sensor to flexibly adapt its configuration allows preserving the inherent softness and compliance of the robot which it is installed on. The macrobend sensing system is immune to electrical noise and magnetic fields, is safe (because no electricity is needed at the sensing site), and is suitable for modular implementation in multi-link soft continuum robotic arms. The measurable light outputs of the proposed stretch sensor vary due to bend-induced light attenuation (macrobend loss), which is a function of the fibre bend radius as well as the number of repeated turns. The experimental study conducted as part of this research revealed that the chosen bend radius has a far greater impact on the measured light intensity values than the number of turns (if greater than five). Taking into account that the bend radius is the only significantly influencing design parameter, the macrobend stretch sensors were developed to create a practical solution to the pose sensing in soft continuum robot arms. Henceforward, the proposed sensing design was benchmarked against an electromagnetic

Pose Planning for the Feed Support System of FAST

Directory of Open Access Journals (Sweden)

Rui Yao

2014-01-01

Full Text Available A six-cable driven parallel manipulator and an A-B rotator in the feed support system of the Five-hundred-meter Aperture Spherical radio Telescope (FAST are adopted for realizing the position and pose of nine feeds. The six-cable driven parallel manipulator is a flexible mechanism, which may not be stably controlled due to a small cable tension. The A-B rotator is a rigid mechanism, and its stability and accuracy can be improved by small pose angle. Based on the different characteristics, a pose planning function is presented. The optimization target of the pose planning function is to get the smallest pose angle of the A-B rotator, and the constraint condition can reflect the controllability of the six-cable driven parallel manipulator. Then, the pose planning realization process of the feed support system is proposed. Based on the pose planning method, optimized pose angles of the feed support system for the nine feeds are obtained, which suggests that the pose angle of the six-cable driven parallel manipulator changes from 0° to 14° and the pose angle of the A-B rotator changes from 0° to 26.4°.

2D Methods for pose invariant face recognition

CSIR Research Space (South Africa)

Mokoena, Ntabiseng

2016-12-01

Full Text Available The ability to recognise face images under random pose is a task that is done effortlessly by human beings. However, for a computer system, recognising face images under varying poses still remains an open research area. Face recognition across pose...

Analyzing Gait Using a Time-of-Flight Camera

DEFF Research Database (Denmark)

Jensen, Rasmus Ramsbøl; Paulsen, Rasmus Reinhold; Larsen, Rasmus

2009-01-01

An algorithm is created, which performs human gait analysis using spatial data and amplitude images from a Time-of-flight camera. For each frame in a sequence the camera supplies cartesian coordinates in space for every pixel. By using an articulated model the subject pose is estimated in the depth...... map in each frame. The pose estimation is based on likelihood, contrast in the amplitude image, smoothness and a shape prior used to solve a Markov random field. Based on the pose estimates, and the prior that movement is locally smooth, a sequential model is created, and a gait analysis is done...... on this model. The output data are: Speed, Cadence (steps per minute), Step length, Stride length (stride being two consecutive steps also known as a gait cycle), and Range of motion (angles of joints). The created system produces good output data of the described output parameters and requires no user...

The non-invasive and continuous estimation of cardiac output using a photoplethysmogram and electrocardiogram during incremental exercise

International Nuclear Information System (INIS)

Wang, L; Poon, C C Y; Zhang, Y T

2010-01-01

Cardiac output (CO) monitoring is not only essential for critically ill patients in the hospital, but also for patients at home and those undergoing cardiopulmonary exercise testing. However, CO is difficult to monitor during daily activities and exercise. In this paper, we aim at developing a novel CO estimation method that can be used under these challenging conditions. The tube model was utilized to derive a CO index, namely the pulse time reflection ratio (PTRR) from an electrocardiogram and photoplethysmogram. After calibration, the PTRR can be used to estimate beat-to-beat CO. The proposed method was verified against CO measured by impedance cardiography on 19 healthy subjects in an incremental intensity exercise test. Results showed that there were strong correlations (r) between the PTRR and reference CO in 18 subjects (mean r: 0.88, n = 245 trials). Two calibration approaches reported in the literature were applied to the proposed method and the corresponding bias ± precisions of estimation errors were 0 ± 1.89 L min −1 and −0.22 ± 2.12 L min −1 , respectively. The percent errors were 21.94% and 24.90%, smaller than the clinical acceptance limit (30%). To conclude, after calibration, this method can be used to monitor CO on healthy subjects during incremental intensity exercise

Influence of heart motion on cardiac output estimation by means of electrical impedance tomography: a case study

International Nuclear Information System (INIS)

Proença, Martin; Braun, Fabian; Rapin, Michael; Solà, Josep; Lemay, Mathieu; Adler, Andy; Grychtol, Bartłomiej; Bohm, Stephan H; Thiran, Jean-Philippe

2015-01-01

Electrical impedance tomography (EIT) is a non-invasive imaging technique that can measure cardiac-related intra-thoracic impedance changes. EIT-based cardiac output estimation relies on the assumption that the amplitude of the impedance change in the ventricular region is representative of stroke volume (SV). However, other factors such as heart motion can significantly affect this ventricular impedance change. In the present case study, a magnetic resonance imaging-based dynamic bio-impedance model fitting the morphology of a single male subject was built. Simulations were performed to evaluate the contribution of heart motion and its influence on EIT-based SV estimation. Myocardial deformation was found to be the main contributor to the ventricular impedance change (56%). However, motion-induced impedance changes showed a strong correlation (r = 0.978) with left ventricular volume. We explained this by the quasi-incompressibility of blood and myocardium. As a result, EIT achieved excellent accuracy in estimating a wide range of simulated SV values (error distribution of 0.57 ± 2.19 ml (1.02 ± 2.62%) and correlation of r = 0.996 after a two-point calibration was applied to convert impedance values to millilitres). As the model was based on one single subject, the strong correlation found between motion-induced changes and ventricular volume remains to be verified in larger datasets. (paper)

The nucleolus is well-posed

Science.gov (United States)

Fragnelli, Vito; Patrone, Fioravante; Torre, Anna

2006-02-01

The lexicographic order is not representable by a real-valued function, contrary to many other orders or preorders. So, standard tools and results for well-posed minimum problems cannot be used. We prove that under suitable hypotheses it is however possible to guarantee the well-posedness of a lexicographic minimum over a compact or convex set. This result allows us to prove that some game theoretical solution concepts, based on lexicographic order are well-posed: in particular, this is true for the nucleolus.

Solving ill-posed control problems by stabilized finite element methods: an alternative to Tikhonov regularization

Science.gov (United States)

Burman, Erik; Hansbo, Peter; Larson, Mats G.

2018-03-01

Tikhonov regularization is one of the most commonly used methods for the regularization of ill-posed problems. In the setting of finite element solutions of elliptic partial differential control problems, Tikhonov regularization amounts to adding suitably weighted least squares terms of the control variable, or derivatives thereof, to the Lagrangian determining the optimality system. In this note we show that the stabilization methods for discretely ill-posed problems developed in the setting of convection-dominated convection-diffusion problems, can be highly suitable for stabilizing optimal control problems, and that Tikhonov regularization will lead to less accurate discrete solutions. We consider some inverse problems for Poisson’s equation as an illustration and derive new error estimates both for the reconstruction of the solution from the measured data and reconstruction of the source term from the measured data. These estimates include both the effect of the discretization error and error in the measurements.

Output Feedback M-MRAC Backstepping With Aerospace Applications

Science.gov (United States)

Stepanyan, Vahram; Krishnakumar, Kalmanje Sriniva

2014-01-01

The paper presents a certainty equivalence output feedback backstepping adaptive control design method for the systems of any relative degree with unmatched uncertainties without over-parametrization. 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 approach is applied to aerospace control problems and tested in numerical simulations.

Output-only modal parameter estimator of linear time-varying structural systems based on vector TAR model and least squares support vector machine

Science.gov (United States)

Zhou, Si-Da; Ma, Yuan-Chen; Liu, Li; Kang, Jie; Ma, Zhi-Sai; Yu, Lei

2018-01-01

Identification of time-varying modal parameters contributes to the structural health monitoring, fault detection, vibration control, etc. of the operational time-varying structural systems. However, it is a challenging task because there is not more information for the identification of the time-varying systems than that of the time-invariant systems. This paper presents a vector time-dependent autoregressive model and least squares support vector machine based modal parameter estimator for linear time-varying structural systems in case of output-only measurements. To reduce the computational cost, a Wendland's compactly supported radial basis function is used to achieve the sparsity of the Gram matrix. A Gamma-test-based non-parametric approach of selecting the regularization factor is adapted for the proposed estimator to replace the time-consuming n-fold cross validation. A series of numerical examples have illustrated the advantages of the proposed modal parameter estimator on the suppression of the overestimate and the short data. A laboratory experiment has further validated the proposed estimator.

Multi-person localization and orientation estimation in volumetric scene reconstructions

NARCIS (Netherlands)

Liem, M.C.

2014-01-01

Accurate localization of persons and estimation of their pose are important topics in current-day computer vision research. As part of the pose estimation, estimating the body orientation of a person (i.e. rotation around torso major axis) conveys important information about the person's current

In-the-wild facial expression recognition in extreme poses

Science.gov (United States)

Yang, Fei; Zhang, Qian; Zheng, Chi; Qiu, Guoping

2018-04-01

In the computer research area, facial expression recognition is a hot research problem. Recent years, the research has moved from the lab environment to in-the-wild circumstances. It is challenging, especially under extreme poses. But current expression detection systems are trying to avoid the pose effects and gain the general applicable ability. In this work, we solve the problem in the opposite approach. We consider the head poses and detect the expressions within special head poses. Our work includes two parts: detect the head pose and group it into one pre-defined head pose class; do facial expression recognize within each pose class. Our experiments show that the recognition results with pose class grouping are much better than that of direct recognition without considering poses. We combine the hand-crafted features, SIFT, LBP and geometric feature, with deep learning feature as the representation of the expressions. The handcrafted features are added into the deep learning framework along with the high level deep learning features. As a comparison, we implement SVM and random forest to as the prediction models. To train and test our methodology, we labeled the face dataset with 6 basic expressions.

Modeling uncertainties in workforce disruptions from influenza pandemics using dynamic input-output analysis.

Science.gov (United States)

El Haimar, Amine; Santos, Joost R

2014-03-01

Influenza pandemic is a serious disaster that can pose significant disruptions to the workforce and associated economic sectors. This article examines the impact of influenza pandemic on workforce availability within an interdependent set of economic sectors. We introduce a simulation model based on the dynamic input-output model to capture the propagation of pandemic consequences through the National Capital Region (NCR). The analysis conducted in this article is based on the 2009 H1N1 pandemic data. Two metrics were used to assess the impacts of the influenza pandemic on the economic sectors: (i) inoperability, which measures the percentage gap between the as-planned output and the actual output of a sector, and (ii) economic loss, which quantifies the associated monetary value of the degraded output. The inoperability and economic loss metrics generate two different rankings of the critical economic sectors. Results show that most of the critical sectors in terms of inoperability are sectors that are related to hospitals and health-care providers. On the other hand, most of the sectors that are critically ranked in terms of economic loss are sectors with significant total production outputs in the NCR such as federal government agencies. Therefore, policy recommendations relating to potential mitigation and recovery strategies should take into account the balance between the inoperability and economic loss metrics. © 2013 Society for Risk Analysis.

Forecasting the Romanian sectoral economy using the input-output method

Directory of Open Access Journals (Sweden)

Liliana DUGULEANĂ

2017-07-01

Full Text Available The purpose of this paper is to forecast the sectoral output in 2013 based on the input-output structure of Romanian economy in 2010. Considering that the economic linkage mechanisms do not easily change during certain time periods, the forecasting is possible, even if not in the sequence of the time passing. Using the technical matrix of the sectoral structure described for year 2010 and some known indicators of the economic sectors, as the value added for each sector in 2013, the sectoral output is projected for 2013. The Romanian GDP in 2013 is estimated based on the input-output model. From a managerial perspective, this study is useful to forecast the sectoral output and to understand the sectoral behaviour, based on the input-output analysis of the value added, the compensation for employees and the final demand, which were considered here.

Skill Levels of Prospective Physics Teachers on Problem Posing

Science.gov (United States)

Cildir, Sema; Sezen, Nazan

2011-01-01

Problem posing is one of the topics which the educators thoroughly accentuate. Problem posing skill is defined as an introvert activity of a student's learning. In this study, skill levels of prospective physics teachers on problem posing were determined and their views on problem posing were evaluated. To this end, prospective teachers were given…

A Layered Approach for Robust Spatial Virtual Human Pose Reconstruction Using a Still Image

Directory of Open Access Journals (Sweden)

Chengyu Guo

2016-02-01

Full Text Available Pedestrian detection and human pose estimation are instructive for reconstructing a three-dimensional scenario and for robot navigation, particularly when large amounts of vision data are captured using various data-recording techniques. Using an unrestricted capture scheme, which produces occlusions or breezing, the information describing each part of a human body and the relationship between each part or even different pedestrians must be present in a still image. Using this framework, a multi-layered, spatial, virtual, human pose reconstruction framework is presented in this study to recover any deficient information in planar images. In this framework, a hierarchical parts-based deep model is used to detect body parts by using the available restricted information in a still image and is then combined with spatial Markov random fields to re-estimate the accurate joint positions in the deep network. Then, the planar estimation results are mapped onto a virtual three-dimensional space using multiple constraints to recover any deficient spatial information. The proposed approach can be viewed as a general pre-processing method to guide the generation of continuous, three-dimensional motion data. The experiment results of this study are used to describe the effectiveness and usability of the proposed approach.

Local Feature Learning for Face Recognition under Varying Poses

DEFF Research Database (Denmark)

Duan, Xiaodong; Tan, Zheng-Hua

2015-01-01

In this paper, we present a local feature learning method for face recognition to deal with varying poses. As opposed to the commonly used approaches of recovering frontal face images from profile views, the proposed method extracts the subject related part from a local feature by removing the pose...... related part in it on the basis of a pose feature. The method has a closed-form solution, hence being time efficient. For performance evaluation, cross pose face recognition experiments are conducted on two public face recognition databases FERET and FEI. The proposed method shows a significant...... recognition improvement under varying poses over general local feature approaches and outperforms or is comparable with related state-of-the-art pose invariant face recognition approaches. Copyright ©2015 by IEEE....

A Monte Carlo Study on Multiple Output Stochastic Frontiers: Comparison of Two Approaches

DEFF Research Database (Denmark)

Henningsen, Geraldine; Henningsen, Arne; Jensen, Uwe

, dividing all other output quantities by the selected output quantity, and using these ratios as regressors (OD). Another approach is the stochastic ray production frontier (SR) which transforms the output quantities into their Euclidean distance as the dependent variable and their polar coordinates......In the estimation of multiple output technologies in a primal approach, the main question is how to handle the multiple outputs. Often an output distance function is used, where the classical approach is to exploit its homogeneity property by selecting one output quantity as the dependent variable...... of both specifications for the case of a Translog output distance function with respect to different common statistical problems as well as problems arising as a consequence of zero values in the output quantities. Although, our results partly show clear reactions to statistical misspecifications...

To Strike a Pose: No Stereotype Backlash for Power Posing Women

Directory of Open Access Journals (Sweden)

Miriam Rennung

2016-09-01

Full Text Available Power posing, the adoption of open and powerful postures, has effects that parallel those of actual social power. This study explored the social evaluation of adopting powerful versus powerless body postures in men and women regarding perceived warmth, competence, and the likelihood of eliciting admiration, envy, pity, and contempt. Previous findings suggest that the display of power by women may have side effects due to gender stereotyping, namely reduced warmth ratings and negative emotional reactions. An experiment (N = 2,473 asked participants to rate pictures of men and women who adopted high-power or low-power body postures. High-power posers were rated higher on competence, admiration, envy, and contempt compared to low-power posers, whereas the opposite was true for pity. There was no impact of power posing on perceived warmth. Contrary to expectations, the poser’s gender did not moderate any of the effects. These findings suggest that nonverbal displays of power do influence fundamental dimensions of social perception and their accompanying emotional reactions but result in comparably positive and negative evaluations for both genders.

Penalized linear regression for discrete ill-posed problems: A hybrid least-squares and mean-squared error approach

KAUST Repository

Suliman, Mohamed Abdalla Elhag

2016-12-19

This paper proposes a new approach to find the regularization parameter for linear least-squares discrete ill-posed problems. In the proposed approach, an artificial perturbation matrix with a bounded norm is forced into the discrete ill-posed model matrix. This perturbation is introduced to enhance the singular-value (SV) structure of the matrix and hence to provide a better solution. The proposed approach is derived to select the regularization parameter in a way that minimizes the mean-squared error (MSE) of the estimator. Numerical results demonstrate that the proposed approach outperforms a set of benchmark methods in most cases when applied to different scenarios of discrete ill-posed problems. Jointly, the proposed approach enjoys the lowest run-time and offers the highest level of robustness amongst all the tested methods.

Multiple regression approach to predict turbine-generator output for Chinshan nuclear power plant

International Nuclear Information System (INIS)

Chan, Yea-Kuang; Tsai, Yu-Ching

2017-01-01

The objective of this study is to develop a turbine cycle model using the multiple regression approach to estimate the turbine-generator output for the Chinshan Nuclear Power Plant (NPP). The plant operating data was verified using a linear regression model with a corresponding 95% confidence interval for the operating data. In this study, the key parameters were selected as inputs for the multiple regression based turbine cycle model. The proposed model was used to estimate the turbine-generator output. The effectiveness of the proposed turbine cycle model was demonstrated by using plant operating data obtained from the Chinshan NPP Unit 2. The results show that this multiple regression based turbine cycle model can be used to accurately estimate the turbine-generator output. In addition, this study also provides an alternative approach with simple and easy features to evaluate the thermal performance for nuclear power plants.

Multiple regression approach to predict turbine-generator output for Chinshan nuclear power plant

Energy Technology Data Exchange (ETDEWEB)

Chan, Yea-Kuang; Tsai, Yu-Ching [Institute of Nuclear Energy Research, Taoyuan City, Taiwan (China). Nuclear Engineering Division

2017-03-15

The objective of this study is to develop a turbine cycle model using the multiple regression approach to estimate the turbine-generator output for the Chinshan Nuclear Power Plant (NPP). The plant operating data was verified using a linear regression model with a corresponding 95% confidence interval for the operating data. In this study, the key parameters were selected as inputs for the multiple regression based turbine cycle model. The proposed model was used to estimate the turbine-generator output. The effectiveness of the proposed turbine cycle model was demonstrated by using plant operating data obtained from the Chinshan NPP Unit 2. The results show that this multiple regression based turbine cycle model can be used to accurately estimate the turbine-generator output. In addition, this study also provides an alternative approach with simple and easy features to evaluate the thermal performance for nuclear power plants.

University Students' Problem Posing Abilities and Attitudes towards Mathematics.

Science.gov (United States)

Grundmeier, Todd A.

2002-01-01

Explores the problem posing abilities and attitudes towards mathematics of students in a university pre-calculus class and a university mathematical proof class. Reports a significant difference in numeric posing versus non-numeric posing ability in both classes. (Author/MM)

Students’ Mathematical Creative Thinking through Problem Posing Learning

Science.gov (United States)

Ulfah, U.; Prabawanto, S.; Jupri, A.

2017-09-01

The research aims to investigate the differences in enhancement of students’ mathematical creative thinking ability of those who received problem posing approach assisted by manipulative media and students who received problem posing approach without manipulative media. This study was a quasi experimental research with non-equivalent control group design. Population of this research was third-grade students of a primary school in Bandung city in 2016/2017 academic year. Sample of this research was two classes as experiment class and control class. The instrument used is a test of mathematical creative thinking ability. Based on the results of the research, it is known that the enhancement of the students’ mathematical creative thinking ability of those who received problem posing approach with manipulative media aid is higher than the ability of those who received problem posing approach without manipulative media aid. Students who get learning problem posing learning accustomed in arranging mathematical sentence become matter of story so it can facilitate students to comprehend about story

Money, Output and Price Level in Nigeria: A Test of the Monetary ...

African Journals Online (AJOL)

This paper presents and tests a model to determine either or both how anticipated or unanticipated money affects real output and inflation in Nigeria. The Barro two –step estimation procedure was explored. Also, the effects of devaluation and business cycles in the industrialized countries on output fluctuation in Nigeria ...

Nonlinear output feedback control of underwater vehicle propellers using feedback form estimated axial flow velocity

DEFF Research Database (Denmark)

Fossen, T. I.; Blanke, Mogens

2000-01-01

Accurate propeller shaft speed controllers can be designed by using nonlinear control theory and feedback from the axial water velocity in the propeller disc. In this paper, an output feedback controller is derived, reconstructing the axial flow velocity from vehicle speed measurements, using...... a three-state model of propeller shaft speed, forward (surge) speed of the vehicle, and the axial flow velocity. Lyapunov stability theory is used to prove that a nonlinear observer combined with an output feedback integral controller provide exponential stability. The output feedback controller...... compensates for variations in thrust due to time variations in advance speed. This is a major problem when applying conventional vehicle-propeller control systems, The proposed controller is simulated for an underwater vehicle equipped with a single propeller. The simulations demonstrate that the axial water...

Manifolds for pose tracking from monocular video

Science.gov (United States)

Basu, Saurav; Poulin, Joshua; Acton, Scott T.

2015-03-01

We formulate a simple human-pose tracking theory from monocular video based on the fundamental relationship between changes in pose and image motion vectors. We investigate the natural embedding of the low-dimensional body pose space into a high-dimensional space of body configurations that behaves locally in a linear manner. The embedded manifold facilitates the decomposition of the image motion vectors into basis motion vector fields of the tangent space to the manifold. This approach benefits from the style invariance of image motion flow vectors, and experiments to validate the fundamental theory show reasonable accuracy (within 4.9 deg of the ground truth).

Estimation of PV output power in moving and rocking hybrid energy marine ships

International Nuclear Information System (INIS)

Liu, Hongda; Zhang, Qing; Qi, Xiaoxia; Han, Yang; Lu, Fang

2017-01-01

Highlights: •A mathematical model for characterizing the ship PV output power is developed. •The impacts of the sea condition and ship type on the PV output power are analyzed. •The hybrid energy storage system is used to stabilize the PV fluctuation powers. •A SC configuration method based on maximum half period is applied. -- Abstract: In recent years, the application of solar energy and energy storage to ship power systems has shown promise as a method for both reducing annual carbon and nitrogen oxide emissions and improving ship energy efficiency in the maritime shipping industry. When a ship navigates at sea, it encounters a constant rocking motion that is affected by both the surrounding sea conditions and the ship’s navigation parameters. This motion increases the uncertainty involved in using solar energy and accelerates the aging of the ship’s energy storage battery to some extent. In this study, a universal mathematical model is established for the power generation by photovoltaic (PV) modules in which both the sea conditions and the ship’s integrated motion, including its basic movement along with the motion caused by rocking, are taken into account. Based on this model, the fluctuation characteristics of a ship’s PV output power are studied and determined using three different simulation scenarios. A binary energy storage scheme based on a decoupled PV output power is proposed in order to both stabilize the small-period PV power fluctuations and slow the aging of the actual battery caused by rocking. In addition, a super-capacitor (SC) configuration is constructed based on a maximum half cycle. Finally, the optimal energy storage capacities for this green ship are compared under both rocking and moving motion. In the case of rocking motion, the SCs are able to achieve an approximately 24.8–35.0% reduction in battery replacement. A shipping route between Shanghai, China and Sydney, Australia is considered to validate the practicality

Data Envelopment Analysis with Fixed Inputs, Undesirable Outputs and Negative Data

Directory of Open Access Journals (Sweden)

F. Seyed Esmaeili

2017-03-01

Full Text Available In Data Envelopment Analysis (DEA, different models have been measured to evaluate the performance of decision making units with multiple inputs and outputs. Revised model of Slack-based measures known as MBSM of collective models family has been introduced by Sharp et al. Slack-based measure has been introduced by Ton. In this study, a model is proposed that is able to estimate the efficiency when a number of outputs of decision making units are undesirable, inputs are fixed and some of outputs and inputs are negative. So that, level of undesirable output is reduced at the constant level of inputs in the evaluation unit and by conserving the efficiency.

The lighter side of advertising: investigating posing and lighting biases.

Science.gov (United States)

Thomas, Nicole A; Burkitt, Jennifer A; Patrick, Regan E; Elias, Lorin J

2008-11-01

People tend to display the left cheek when posing for a portrait; however, this effect does not appear to generalise to advertising. The amount of body visible in the image and the sex of the poser might also contribute to the posing bias. Portraits also exhibit lateral lighting biases, with most images being lit from the left. This effect might also be present in advertisements. A total of 2801 full-page advertisements were sampled and coded for posing direction, lighting direction, sex of model, and amount of body showing. Images of females showed an overall leftward posing bias, but the biases in males depended on the amount of body visible. Males demonstrated rightward posing biases for head-only images. Overall, images tended to be lit from the top left corner. The two factors of posing and lighting biases appear to influence one another. Leftward-lit images had more leftward poses than rightward, while the opposite occurred for rightward-lit images. Collectively, these results demonstrate that the posing biases in advertisements are dependent on the amount of body showing in the image, and that biases in lighting direction interact with these posing biases.

Novelty Detection for Interactive Pose Recognition by a Social Robot

Directory of Open Access Journals (Sweden)

Victor Gonzalez-Pacheco

2015-04-01

Full Text Available Active robot learners take an active role in their own learning by making queries to their human teachers when they receive new data. However, not every received input is useful for the robot, and asking for non-informative inputs or asking too many questions might worsen the user's perception of the robot. We present a novelty detection system that enables a robot to ask labels for new stimuli only when they seem both novel and interesting. Our system separates the decision process into two steps: first, it discriminates novel from known stimuli, and second, it estimates if these stimuli are likely to happen again. Our approach uses the notion of curiosity, which controls the eagerness with which the robot asks questions to the user. We evaluate our approach in the domain of pose learning by training our robot with a set of pointing poses able to detect up to 84%, 79%, and 78% of the observed novelties in three different experiments. Our approach enables robots to keep learning continuously, even after training is finished. The introduction of the curiosity parameter allows tuning, for the conditions in which the robot should want to learn more.

Robust facial landmark detection based on initializing multiple poses

Directory of Open Access Journals (Sweden)

Xin Chai

2016-10-01

Full Text Available For robot systems, robust facial landmark detection is the first and critical step for face-based human identification and facial expression recognition. In recent years, the cascaded-regression-based method has achieved excellent performance in facial landmark detection. Nevertheless, it still has certain weakness, such as high sensitivity to the initialization. To address this problem, regression based on multiple initializations is established in a unified model; face shapes are then estimated independently according to these initializations. With a ranking strategy, the best estimate is selected as the final output. Moreover, a face shape model based on restricted Boltzmann machines is built as a constraint to improve the robustness of ranking. Experiments on three challenging datasets demonstrate the effectiveness of the proposed facial landmark detection method against state-of-the-art methods.

Coupled bias-variance tradeoff for cross-pose face recognition.

Science.gov (United States)

Li, Annan; Shan, Shiguang; Gao, Wen

2012-01-01

Subspace-based face representation can be looked as a regression problem. From this viewpoint, we first revisited the problem of recognizing faces across pose differences, which is a bottleneck in face recognition. Then, we propose a new approach for cross-pose face recognition using a regressor with a coupled bias-variance tradeoff. We found that striking a coupled balance between bias and variance in regression for different poses could improve the regressor-based cross-pose face representation, i.e., the regressor can be more stable against a pose difference. With the basic idea, ridge regression and lasso regression are explored. Experimental results on CMU PIE, the FERET, and the Multi-PIE face databases show that the proposed bias-variance tradeoff can achieve considerable reinforcement in recognition performance.

Animated pose templates for modeling and detecting human actions.

Science.gov (United States)

Yao, Benjamin Z; Nie, Bruce X; Liu, Zicheng; Zhu, Song-Chun

2014-03-01

This paper presents animated pose templates (APTs) for detecting short-term, long-term, and contextual actions from cluttered scenes in videos. Each pose template consists of two components: 1) a shape template with deformable parts represented in an And-node whose appearances are represented by the Histogram of Oriented Gradient (HOG) features, and 2) a motion template specifying the motion of the parts by the Histogram of Optical-Flows (HOF) features. A shape template may have more than one motion template represented by an Or-node. Therefore, each action is defined as a mixture (Or-node) of pose templates in an And-Or tree structure. While this pose template is suitable for detecting short-term action snippets in two to five frames, we extend it in two ways: 1) For long-term actions, we animate the pose templates by adding temporal constraints in a Hidden Markov Model (HMM), and 2) for contextual actions, we treat contextual objects as additional parts of the pose templates and add constraints that encode spatial correlations between parts. To train the model, we manually annotate part locations on several keyframes of each video and cluster them into pose templates using EM. This leaves the unknown parameters for our learning algorithm in two groups: 1) latent variables for the unannotated frames including pose-IDs and part locations, 2) model parameters shared by all training samples such as weights for HOG and HOF features, canonical part locations of each pose, coefficients penalizing pose-transition and part-deformation. To learn these parameters, we introduce a semi-supervised structural SVM algorithm that iterates between two steps: 1) learning (updating) model parameters using labeled data by solving a structural SVM optimization, and 2) imputing missing variables (i.e., detecting actions on unlabeled frames) with parameters learned from the previous step and progressively accepting high-score frames as newly labeled examples. This algorithm belongs to a

Industrial output restriction and the Kyoto protocol. An input-output approach with application to Canada

International Nuclear Information System (INIS)

Lixon, Benoit; Thomassin, Paul J.; Hamaide, Bertrand

2008-01-01

The objective of this paper is to assess the economic impacts of reducing greenhouse gas emissions by decreasing industrial output in Canada to a level that will meet the target set out in the Kyoto Protocol. The study uses an ecological-economic Input-Output model combining economic components valued in monetary terms with ecologic components - GHG emissions - expressed in physical terms. Economic and greenhouse gas emissions data for Canada are computed in the same sectoral disaggregation. Three policy scenarios are considered: the first one uses the direct emission coefficients to allocate the reduction in industrial output, while the other two use the direct plus indirect emission coefficients. In the first two scenarios, the reduction in industrial sector output is allocated uniformly across sectors while it is allocated to the 12 largest emitting industries in the last one. The estimated impacts indicate that the results vary with the different allocation methods. The third policy scenario, allocation to the 12 largest emitting sectors, is the most cost effective of the three as the impacts of the Kyoto Protocol reduces Gross Domestic Product by 3.1% compared to 24% and 8.1% in the first two scenarios. Computed economic costs should be considered as upper-bounds because the model assumes immediate adjustment to the Kyoto Protocol and because flexibility mechanisms are not incorporated. The resulting upper-bound impact of the third scenario may seem to contradict those who claim that the Kyoto Protocol would place an unbearable burden on the Canadian economy. (author)

Formulas in inverse and ill-posed problems

CERN Document Server

Anikonov, Yu E

1997-01-01

The Inverse and Ill-Posed Problems Series is a series of monographs publishing postgraduate level information on inverse and ill-posed problems for an international readership of professional scientists and researchers. The series aims to publish works which involve both theory and applications in, e.g., physics, medicine, geophysics, acoustics, electrodynamics, tomography, and ecology.

Effect of material constants on power output in piezoelectric vibration-based generators.

Science.gov (United States)

Takeda, Hiroaki; Mihara, Kensuke; Yoshimura, Tomohiro; Hoshina, Takuya; Tsurumi, Takaaki

2011-09-01

A possible power output estimation based on material constants in piezoelectric vibration-based generators is proposed. A modified equivalent circuit model of the generator was built and was validated by the measurement results in the generator fabricated using potassium sodium niobate-based and lead zirconate titanate (PZT) ceramics. Subsequently, generators with the same structure using other PZT-based and bismuth-layered structure ferroelectrics ceramics were fabricated and tested. The power outputs of these generators were expressed as a linear functions of the term composed of electromechanical coupling coefficients k(sys)(2) and mechanical quality factors Q*(m) of the generator. The relationship between device constants (k(sys)(2) and Q*(m)) and material constants (k(31)(2) and Q(m)) was clarified. Estimation of the power output using material constants is demonstrated and the appropriate piezoelectric material for the generator is suggested.

Transfer between Pose and Illumination Training in Face Recognition

Science.gov (United States)

Liu, Chang Hong; Bhuiyan, Md. Al-Amin; Ward, James; Sui, Jie

2009-01-01

The relationship between pose and illumination learning in face recognition was examined in a yes-no recognition paradigm. The authors assessed whether pose training can transfer to a new illumination or vice versa. Results show that an extensive level of pose training through a face-name association task was able to generalize to a new…

Enhanced DEA model with undesirable output and interval data for rice growing farmers performance assessment

Energy Technology Data Exchange (ETDEWEB)

Khan, Sahubar Ali Mohd. Nadhar, E-mail: sahubar@uum.edu.my; Ramli, Razamin, E-mail: razamin@uum.edu.my; Baten, M. D. Azizul, E-mail: baten-math@yahoo.com [School of Quantitative Sciences, UUM College of Arts and Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah (Malaysia)

2015-12-11

Agricultural production process typically produces two types of outputs which are economic desirable as well as environmentally undesirable outputs (such as greenhouse gas emission, nitrate leaching, effects to human and organisms and water pollution). In efficiency analysis, this undesirable outputs cannot be ignored and need to be included in order to obtain the actual estimation of firms efficiency. Additionally, climatic factors as well as data uncertainty can significantly affect the efficiency analysis. There are a number of approaches that has been proposed in DEA literature to account for undesirable outputs. Many researchers has pointed that directional distance function (DDF) approach is the best as it allows for simultaneous increase in desirable outputs and reduction of undesirable outputs. Additionally, it has been found that interval data approach is the most suitable to account for data uncertainty as it is much simpler to model and need less information regarding its distribution and membership function. In this paper, an enhanced DEA model based on DDF approach that considers undesirable outputs as well as climatic factors and interval data is proposed. This model will be used to determine the efficiency of rice farmers who produces undesirable outputs and operates under uncertainty. It is hoped that the proposed model will provide a better estimate of rice farmers’ efficiency.

Enhanced DEA model with undesirable output and interval data for rice growing farmers performance assessment

International Nuclear Information System (INIS)

Khan, Sahubar Ali Mohd. Nadhar; Ramli, Razamin; Baten, M. D. Azizul

2015-01-01

Agricultural production process typically produces two types of outputs which are economic desirable as well as environmentally undesirable outputs (such as greenhouse gas emission, nitrate leaching, effects to human and organisms and water pollution). In efficiency analysis, this undesirable outputs cannot be ignored and need to be included in order to obtain the actual estimation of firms efficiency. Additionally, climatic factors as well as data uncertainty can significantly affect the efficiency analysis. There are a number of approaches that has been proposed in DEA literature to account for undesirable outputs. Many researchers has pointed that directional distance function (DDF) approach is the best as it allows for simultaneous increase in desirable outputs and reduction of undesirable outputs. Additionally, it has been found that interval data approach is the most suitable to account for data uncertainty as it is much simpler to model and need less information regarding its distribution and membership function. In this paper, an enhanced DEA model based on DDF approach that considers undesirable outputs as well as climatic factors and interval data is proposed. This model will be used to determine the efficiency of rice farmers who produces undesirable outputs and operates under uncertainty. It is hoped that the proposed model will provide a better estimate of rice farmers’ efficiency

Enhanced DEA model with undesirable output and interval data for rice growing farmers performance assessment

Science.gov (United States)

Khan, Sahubar Ali Mohd. Nadhar; Ramli, Razamin; Baten, M. D. Azizul

2015-12-01

Agricultural production process typically produces two types of outputs which are economic desirable as well as environmentally undesirable outputs (such as greenhouse gas emission, nitrate leaching, effects to human and organisms and water pollution). In efficiency analysis, this undesirable outputs cannot be ignored and need to be included in order to obtain the actual estimation of firms efficiency. Additionally, climatic factors as well as data uncertainty can significantly affect the efficiency analysis. There are a number of approaches that has been proposed in DEA literature to account for undesirable outputs. Many researchers has pointed that directional distance function (DDF) approach is the best as it allows for simultaneous increase in desirable outputs and reduction of undesirable outputs. Additionally, it has been found that interval data approach is the most suitable to account for data uncertainty as it is much simpler to model and need less information regarding its distribution and membership function. In this paper, an enhanced DEA model based on DDF approach that considers undesirable outputs as well as climatic factors and interval data is proposed. This model will be used to determine the efficiency of rice farmers who produces undesirable outputs and operates under uncertainty. It is hoped that the proposed model will provide a better estimate of rice farmers' efficiency.

Output feedback control of a quadrotor UAV using neural networks.

Science.gov (United States)

Dierks, Travis; Jagannathan, Sarangapani

2010-01-01

In this paper, a new nonlinear controller for a quadrotor unmanned aerial vehicle (UAV) is proposed using neural networks (NNs) and output feedback. The assumption on the availability of UAV dynamics is not always practical, especially in an outdoor environment. Therefore, in this work, an NN is introduced to learn the complete dynamics of the UAV online, including uncertain nonlinear terms like aerodynamic friction and blade flapping. Although a quadrotor UAV is underactuated, a novel NN virtual control input scheme is proposed which allows all six degrees of freedom (DOF) of the UAV to be controlled using only four control inputs. Furthermore, an NN observer is introduced to estimate the translational and angular velocities of the UAV, and an output feedback control law is developed in which only the position and the attitude of the UAV are considered measurable. It is shown using Lyapunov theory that the position, orientation, and velocity tracking errors, the virtual control and observer estimation errors, and the NN weight estimation errors for each NN are all semiglobally uniformly ultimately bounded (SGUUB) in the presence of bounded disturbances and NN functional reconstruction errors while simultaneously relaxing the separation principle. The effectiveness of proposed output feedback control scheme is then demonstrated in the presence of unknown nonlinear dynamics and disturbances, and simulation results are included to demonstrate the theoretical conjecture.

The output least-squares approach to estimating Lamé moduli

Science.gov (United States)

Gockenbach, Mark S.

2007-12-01

The Lamé moduli of a heterogeneous, isotropic, planar membrane can be estimated by observing the displacement of the membrane under a known edge traction, and choosing estimates of the moduli that best predict the observed displacement under a finite-element simulation. This algorithm converges to the exact moduli given pointwise measurements of the displacement on an increasingly fine mesh. The error estimates that prove this convergence also show the instability of the inverse problem.

Non-standard and improperly posed problems

CERN Document Server

Straughan, Brian; Ames, William F

1997-01-01

Written by two international experts in the field, this book is the first unified survey of the advances made in the last 15 years on key non-standard and improperly posed problems for partial differential equations.This reference for mathematicians, scientists, and engineers provides an overview of the methodology typically used to study improperly posed problems. It focuses on structural stability--the continuous dependence of solutions on the initial conditions and the modeling equations--and on problems for which data are only prescribed on part of the boundary.The book addresses continuou

Quaternion-based adaptive output feedback attitude control of spacecraft using Chebyshev neural networks.

Science.gov (United States)

Zou, An-Min; Dev Kumar, Krishna; Hou, Zeng-Guang

2010-09-01

This paper investigates the problem of output feedback attitude control of an uncertain spacecraft. Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe the spacecraft attitude for global representation without singularities. The nonlinear reduced-order observer is used to estimate the derivative of the spacecraft output, and the CNN is introduced to further improve the control performance through approximating the spacecraft attitude motion. The implementation of the basis functions of the CNN used in the proposed controllers depends only on the desired signals, and the smooth robust compensator using the hyperbolic tangent function is employed to counteract the CNN approximation errors and external disturbances. The adaptive NN controller-II can efficiently avoid the over-estimation problem (i.e., the bound of the CNNs output is much larger than that of the approximated unknown function, and hence, the control input may be very large) existing in the adaptive NN controller-I. Both adaptive output feedback controllers using CNN can guarantee that all signals in the resulting closed-loop system are uniformly ultimately bounded. For performance comparisons, the standard adaptive controller using the linear parameterization of spacecraft attitude motion is also developed. Simulation studies are presented to show the advantages of the proposed CNN-based output feedback approach over the standard adaptive output feedback approach.

Method of orthogonally splitting imaging pose measurement

Science.gov (United States)

Zhao, Na; Sun, Changku; Wang, Peng; Yang, Qian; Liu, Xintong

2018-01-01

In order to meet the aviation's and machinery manufacturing's pose measurement need of high precision, fast speed and wide measurement range, and to resolve the contradiction between measurement range and resolution of vision sensor, this paper proposes an orthogonally splitting imaging pose measurement method. This paper designs and realizes an orthogonally splitting imaging vision sensor and establishes a pose measurement system. The vision sensor consists of one imaging lens, a beam splitter prism, cylindrical lenses and dual linear CCD. Dual linear CCD respectively acquire one dimensional image coordinate data of the target point, and two data can restore the two dimensional image coordinates of the target point. According to the characteristics of imaging system, this paper establishes the nonlinear distortion model to correct distortion. Based on cross ratio invariability, polynomial equation is established and solved by the least square fitting method. After completing distortion correction, this paper establishes the measurement mathematical model of vision sensor, and determines intrinsic parameters to calibrate. An array of feature points for calibration is built by placing a planar target in any different positions for a few times. An terative optimization method is presented to solve the parameters of model. The experimental results show that the field angle is 52 °, the focus distance is 27.40 mm, image resolution is 5185×5117 pixels, displacement measurement error is less than 0.1mm, and rotation angle measurement error is less than 0.15°. The method of orthogonally splitting imaging pose measurement can satisfy the pose measurement requirement of high precision, fast speed and wide measurement range.

Discriminating Projections for Estimating Face Age in Wild Images

Energy Technology Data Exchange (ETDEWEB)

Tokola, Ryan A [ORNL; Bolme, David S [ORNL; Ricanek, Karl [ORNL; Barstow, Del R [ORNL; Boehnen, Chris Bensing [ORNL

2014-01-01

We introduce a novel approach to estimating the age of a human from a single uncontrolled image. Current face age estimation algorithms work well in highly controlled images, and some are robust to changes in illumination, but it is usually assumed that images are close to frontal. This bias is clearly seen in the datasets that are commonly used to evaluate age estimation, which either entirely or mostly consist of frontal images. Using pose-specific projections, our algorithm maps image features into a pose-insensitive latent space that is discriminative with respect to age. Age estimation is then performed using a multi-class SVM. We show that our approach outperforms other published results on the Images of Groups dataset, which is the only age-related dataset with a non-trivial number of off-axis face images, and that we are competitive with recent age estimation algorithms on the mostly-frontal FG-NET dataset. We also experimentally demonstrate that our feature projections introduce insensitivity to pose.

Lavrentiev regularization method for nonlinear ill-posed problems

International Nuclear Information System (INIS)

Kinh, Nguyen Van

2002-10-01

In this paper we shall be concerned with Lavientiev regularization method to reconstruct solutions x 0 of non ill-posed problems F(x)=y o , where instead of y 0 noisy data y δ is an element of X with absolut(y δ -y 0 ) ≤ δ are given and F:X→X is an accretive nonlinear operator from a real reflexive Banach space X into itself. In this regularization method solutions x α δ are obtained by solving the singularly perturbed nonlinear operator equation F(x)+α(x-x*)=y δ with some initial guess x*. Assuming certain conditions concerning the operator F and the smoothness of the element x*-x 0 we derive stability estimates which show that the accuracy of the regularized solutions is order optimal provided that the regularization parameter α has been chosen properly. (author)

Adaptive Neural Output Feedback Control for Uncertain Robot Manipulators with Input Saturation

Directory of Open Access Journals (Sweden)

Rong Mei

2017-01-01

Full Text Available This paper presents an adaptive neural output feedback control scheme for uncertain robot manipulators with input saturation using the radial basis function neural network (RBFNN and disturbance observer. First, the RBFNN is used to approximate the system uncertainty, and the unknown approximation error of the RBFNN and the time-varying unknown external disturbance of robot manipulators are integrated as a compounded disturbance. Then, the state observer and the disturbance observer are proposed to estimate the unmeasured system state and the unknown compounded disturbance based on RBFNN. At the same time, the adaptation technique is employed to tackle the control input saturation problem. Utilizing the estimate outputs of the RBFNN, the state observer, and the disturbance observer, the adaptive neural output feedback control scheme is developed for robot manipulators using the backstepping technique. The convergence of all closed-loop signals is rigorously proved via Lyapunov analysis and the asymptotically convergent tracking error is obtained under the integrated effect of the system uncertainty, the unmeasured system state, the unknown external disturbance, and the input saturation. Finally, numerical simulation results are presented to illustrate the effectiveness of the proposed adaptive neural output feedback control scheme for uncertain robot manipulators.

The value of risk: measuring the service output of U.S. commercial banks

OpenAIRE

Basu, Susanto; Inklaar, Robert; Wang, J. Christina

2011-01-01

Rather than charging direct fees, banks often charge implicitly for their services via interest spreads. As a result, much of bank output has to be estimated indirectly. In contrast to current statistical practice, dynamic optimizing models of banks argue that compensation for bearing systematic risk is not part of bank output. We apply these models and find that between 1997 and 2007, in the U.S. National Accounts, on average, bank output is overestimated by 21 percent and GDP is overestimat...

Parameter and State Estimator for State Space Models

Directory of Open Access Journals (Sweden)

Ruifeng Ding

2014-01-01

Full Text Available This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.

Contactless and pose invariant biometric identification using hand surface.

Science.gov (United States)

Kanhangad, Vivek; Kumar, Ajay; Zhang, David

2011-05-01

This paper presents a novel approach for hand matching that achieves significantly improved performance even in the presence of large hand pose variations. The proposed method utilizes a 3-D digitizer to simultaneously acquire intensity and range images of the user's hand presented to the system in an arbitrary pose. The approach involves determination of the orientation of the hand in 3-D space followed by pose normalization of the acquired 3-D and 2-D hand images. Multimodal (2-D as well as 3-D) palmprint and hand geometry features, which are simultaneously extracted from the user's pose normalized textured 3-D hand, are used for matching. Individual matching scores are then combined using a new dynamic fusion strategy. Our experimental results on the database of 114 subjects with significant pose variations yielded encouraging results. Consistent (across various hand features considered) performance improvement achieved with the pose correction demonstrates the usefulness of the proposed approach for hand based biometric systems with unconstrained and contact-free imaging. The experimental results also suggest that the dynamic fusion approach employed in this work helps to achieve performance improvement of 60% (in terms of EER) over the case when matching scores are combined using the weighted sum rule.

Output power distributions of mobile radio base stations based on network measurements

International Nuclear Information System (INIS)

Colombi, D; Thors, B; Persson, T; Törnevik, C; Wirén, N; Larsson, L-E

2013-01-01

In this work output power distributions of mobile radio base stations have been analyzed for 2G and 3G telecommunication systems. The approach is based on measurements in selected networks using performance surveillance tools part of the network Operational Support System (OSS). For the 3G network considered, direct measurements of output power levels were possible, while for the 2G networks, output power levels were estimated from measurements of traffic volumes. Both voice and data services were included in the investigation. Measurements were conducted for large geographical areas, to ensure good overall statistics, as well as for smaller areas to investigate the impact of different environments. For high traffic hours, the 90th percentile of the averaged output power was found to be below 65% and 45% of the available output power for the 2G and 3G systems, respectively.

Output power distributions of mobile radio base stations based on network measurements

Science.gov (United States)

Colombi, D.; Thors, B.; Persson, T.; Wirén, N.; Larsson, L.-E.; Törnevik, C.

2013-04-01

In this work output power distributions of mobile radio base stations have been analyzed for 2G and 3G telecommunication systems. The approach is based on measurements in selected networks using performance surveillance tools part of the network Operational Support System (OSS). For the 3G network considered, direct measurements of output power levels were possible, while for the 2G networks, output power levels were estimated from measurements of traffic volumes. Both voice and data services were included in the investigation. Measurements were conducted for large geographical areas, to ensure good overall statistics, as well as for smaller areas to investigate the impact of different environments. For high traffic hours, the 90th percentile of the averaged output power was found to be below 65% and 45% of the available output power for the 2G and 3G systems, respectively.

Global sensitivity analysis for models with spatially dependent outputs

International Nuclear Information System (INIS)

Iooss, B.; Marrel, A.; Jullien, M.; Laurent, B.

2011-01-01

The global sensitivity analysis of a complex numerical model often calls for the estimation of variance-based importance measures, named Sobol' indices. Meta-model-based techniques have been developed in order to replace the CPU time-expensive computer code with an inexpensive mathematical function, which predicts the computer code output. The common meta-model-based sensitivity analysis methods are well suited for computer codes with scalar outputs. However, in the environmental domain, as in many areas of application, the numerical model outputs are often spatial maps, which may also vary with time. In this paper, we introduce an innovative method to obtain a spatial map of Sobol' indices with a minimal number of numerical model computations. It is based upon the functional decomposition of the spatial output onto a wavelet basis and the meta-modeling of the wavelet coefficients by the Gaussian process. An analytical example is presented to clarify the various steps of our methodology. This technique is then applied to a real hydrogeological case: for each model input variable, a spatial map of Sobol' indices is thus obtained. (authors)

Rhythmic Extended Kalman Filter for Gait Rehabilitation Motion Estimation and Segmentation.

Science.gov (United States)

Joukov, Vladimir; Bonnet, Vincent; Karg, Michelle; Venture, Gentiane; Kulic, Dana

2018-02-01

This paper proposes a method to enable the use of non-intrusive, small, wearable, and wireless sensors to estimate the pose of the lower body during gait and other periodic motions and to extract objective performance measures useful for physiotherapy. The Rhythmic Extended Kalman Filter (Rhythmic-EKF) algorithm is developed to estimate the pose, learn an individualized model of periodic movement over time, and use the learned model to improve pose estimation. The proposed approach learns a canonical dynamical system model of the movement during online observation, which is used to accurately model the acceleration during pose estimation. The canonical dynamical system models the motion as a periodic signal. The estimated phase and frequency of the motion also allow the proposed approach to segment the motion into repetitions and extract useful features, such as gait symmetry, step length, and mean joint movement and variance. The algorithm is shown to outperform the extended Kalman filter in simulation, on healthy participant data, and stroke patient data. For the healthy participant marching dataset, the Rhythmic-EKF improves joint acceleration and velocity estimates over regular EKF by 40% and 37%, respectively, estimates joint angles with 2.4° root mean squared error, and segments the motion into repetitions with 96% accuracy.

Turkish Primary School Teachers' Opinions about Problem Posing

Science.gov (United States)

Kilic, Cigdem

2013-01-01

Problem posing is one of the most important topics in a mathematics education. Through problem posing, students gain mathematical abilities and concepts and teachers can evaluate their students and arrange adequate learning environments. The aim of the present study is to investigate Turkish primary school teachers' opinions about problem posing…

Standard diffusive systems are well-posed linear systems

NARCIS (Netherlands)

Matignon, Denis; Zwart, Heiko J.

2004-01-01

The class of well-posed linear systems as introduced by Salamon has become a well-understood class of systems, see e.g. the work of Weiss and the book of Staffans. Many partial partial differential equations with boundary control and point observation can be formulated as a well-posed linear system.

Studies on the power output of a MADEAE-30 operating on complex terrain. Annual Energy Production estimation and Multivariable analysis. A case of multi-stall effect

International Nuclear Information System (INIS)

Cuerva, A.

1996-01-01

The main need of the EWTS-II Sub-project IV group is to have a suitable data-base which allows it to reach proper conclusions on the characteristics of power performance of wind turbines in complex terrain. With this aim, this document presents an analysis on the power output of the MADE AE-30 Wind turbine operating at Tarifa (also data from flat terrain are enclosed as a reference). An application of the bin method and AEP estimation for energy production method. In the two last issues a directional analysis and an study for two different turbulence intensity ranges are enclosed. Finally the STEPWISE multirregression method is applied on the measurements to identify the stored parameters that have influence on the power output. A brief description of multi stall effect is enclosed. (Author) 7 refs

Specification and Aggregation Errors in Environmentally Extended Input-Output Models

NARCIS (Netherlands)

Bouwmeester, Maaike C.; Oosterhaven, Jan

This article considers the specification and aggregation errors that arise from estimating embodied emissions and embodied water use with environmentally extended national input-output (IO) models, instead of with an environmentally extended international IO model. Model specification errors result

Posing Problems to Understand Children's Learning of Fractions

Science.gov (United States)

Cheng, Lu Pien

2013-01-01

In this study, ways in which problem posing activities aid our understanding of children's learning of addition of unlike fractions and product of proper fractions was examined. In particular, how a simple problem posing activity helps teachers take a second, deeper look at children's understanding of fraction concepts will be discussed. The…

The impact of monetary policy on output and inflation in India: A frequency domain analysis

Directory of Open Access Journals (Sweden)

Salunkhe Bhavesh

2017-01-01

Full Text Available In the recent past, several attempts by the RBI to control inflation through tight monetary policy have ended up slowing the growth process, thereby provoking prolonged discussion among academics and policymakers about the efficacy of monetary policy in India. Against this backdrop, the present study attempts to estimate the causal relationship between monetary policy and its final objectives; i.e., growth, and controlling inflation in India. The methodological tool used is testing for Granger Causality in the frequency domain as developed by Lemmens et al. (2008, and monetary policy has been proxied by the weighted average call money rate. In view of the fact that output gap is one of the determinants of future inflation, an attempt has also been made to study the causal relationship between output gap and inflation. The results of empirical estimation show a bi-directional causality between policy rate and inflation and between policy rate and output, which implies that the monetary authorities in India were equally concerned about inflation and output growth when determining policy. Furthermore, any attempt to control inflation affects output with the same or even greater magnitude than inflation, thereby damaging the growth process. The relationship between output gap and inflation was found to be positive, as reported in earlier studies for India. Furthermore, the output gap causes inflation only in the short-tomediumrun.

Pose and Motion Estimation Using Dual Quaternion-Based Extended Kalman Filtering

Energy Technology Data Exchange (ETDEWEB)

Goddard, J.S.; Abidi, M.A.

1998-06-01

A solution to the remote three-dimensional (3-D) measurement problem is presented for a dynamic system given a sequence of two-dimensional (2-D) intensity images of a moving object. The 3-D transformation is modeled as a nonlinear stochastic system with the state estimate providing the six-degree-of-freedom motion and position values as well as structure. The stochastic model uses the iterated extended Kalman filter (IEKF) as a nonlinear estimator and a screw representation of the 3-D transformation based on dual quaternions. Dual quaternions, whose elements are dual numbers, provide a means to represent both rotation and translation in a unified notation. Linear object features, represented as dual vectors, are transformed using the dual quaternion transformation and are then projected to linear features in the image plane. The method has been implemented and tested with both simulated and actual experimental data. Simulation results are provided, along with comparisons to a point-based IEKF method using rotation and translation, to show the relative advantages of this method. Experimental results from testing using a camera mounted on the end effector of a robot arm are also given.

Unit 16 - Output

OpenAIRE

Unit 16, CC in GIS; Star, Jeffrey L.

1990-01-01

This unit discusses issues related to GIS output, including the different types of output possible and the hardware for producing each. It describes text, graphic and digital data that can be generated by a GIS as well as line printers, dot matrix printers/plotters, pen plotters, optical scanners and cathode ray tubes (CRTs) as technologies for generating the output.

Control and automatic alignment of the output mode cleaner of GEO 600

Energy Technology Data Exchange (ETDEWEB)

Prijatelj, M; Grote, H; Degallaix, J; Hewitson, M; Affeldt, C; Leong, J; Lueck, H; Strain, K A; Wittel, H; Willke, B; Danzmann, K [Max-Planck-Institut fuer Gravitationsphysik (Albert-Einstein-Institut) and Leibniz Universitaet Hannover, Callinstr. 38, 30167 Hannover (Germany); Hild, S; Freise, A, E-mail: mirko.prijatelj@aei.mpg.d [School of Physics and Astronomy, University of Birmingham, Edgbaston, Birmingham, B15 2TT (United Kingdom)

2010-05-01

The implementation of a mode cleaner at the output port of the GEO 600 gravitational wave detector will be part of the upcoming transition from GEO 600 to GEO-HF. Part of the transition will be the move from a heterodyne readout to a DC readout scheme. DC readout performance will be limited by higher order optical modes and control sidebands present at the output port. For optimum performance of DC readout an output mode cleaner (OMC) will clean the output beam of these contributions. Inclusion of an OMC will introduce new noise sources whose magnitudes needed to be estimated and for which new control systems will be needed. In this article we set requirements on the performance of these control systems and investigate the simulated performance of different designs.

State estimation for a hexapod robot

CSIR Research Space (South Africa)

Lubbe, Estelle

2015-09-01

Full Text Available This paper introduces a state estimation methodology for a hexapod robot that makes use of proprioceptive sensors and a kinematic model of the robot. The methodology focuses on providing reliable full pose state estimation for a commercially...

Creativity of Field-dependent and Field-independent Students in Posing Mathematical Problems

Science.gov (United States)

Azlina, N.; Amin, S. M.; Lukito, A.

2018-01-01

This study aims at describing the creativity of elementary school students with different cognitive styles in mathematical problem-posing. The posed problems were assessed based on three components of creativity, namely fluency, flexibility, and novelty. The free-type problem posing was used in this study. This study is a descriptive research with qualitative approach. Data collections were conducted through written task and task-based interviews. The subjects were two elementary students. One of them is Field Dependent (FD) and the other is Field Independent (FI) which were measured by GEFT (Group Embedded Figures Test). Further, the data were analyzed based on creativity components. The results show thatFD student’s posed problems have fulfilled the two components of creativity namely fluency, in which the subject posed at least 3 mathematical problems, and flexibility, in whichthe subject posed problems with at least 3 different categories/ideas. Meanwhile,FI student’s posed problems have fulfilled all three components of creativity, namely fluency, in which thesubject posed at least 3 mathematical problems, flexibility, in which thesubject posed problems with at least 3 different categories/ideas, and novelty, in which the subject posed problems that are purely the result of her own ideas and different from problems they have known.

Baixa dosagem de óxido de cromo para estimativa da produção fecal em bovinos Low level of chromium oxide to estimate faecal output in cattle

Directory of Open Access Journals (Sweden)

Henrique Mendonça Nunes Ribeiro Filho

2008-12-01

Full Text Available Foi avaliado o uso de baixa dosagem de óxido de cromo (Cr2O3 incorporado em um alimento concentrado para estimativa da produção fecal (PF em bovinos. Para tanto, foram conduzidos quatro ensaios de digestibilidade in vivo utilizando quatro novilhos com peso vivo médio de 214±31kg, recebendo ad libitum no cocho azevém anual (Lolium multiflorum Lam. cortado verde. Aproximadamente 200g de ração contendo 5g kg-1 do indicador foi fornecida diariamente durante 12 dias, sendo feito a coleta de dados e amostras nos últimos cinco dias de cada período. A PF foi medida com o uso de sacolas de coleção total ou estimada com base na concentração do indicador em amostras fecais coletadas duas vezes ao dia (8 e 16h ou a intervalos de duas horas entre 8 e 22h. A concentração média de cromo nas amostras coletadas às 8 e 16h (445mg kg-1 foi semelhante à média geral de todos os horários (447mg kg-1. O grau de recuperação fecal (GR do indicador aumentou linearmente, de aproximadamente 40% para em torno de 80%, com o aumento da concentração fecal de cromo até esta última atingir um valor em torno de 250mg kg-1 de MO. Quando a concentração de cromo nas fezes foi superior a este valor o GR se manteve relativamente constante, em média 76%. A produção fecal foi superestimada pelo indicador em até 35% quando não corrigido para o GR. Quando corrigido para a recuperação fecal, as estimativas de produção fecal de MO estimadas foram similares às observadas. A excreção fecal de bovinos alimentados com azevém pode ser acuradamente estimada com o uso de baixa dosagem de óxido de cromo incorporado em uma ração peletizada concomitante à coleta de duas amostragens diárias de fezes.The aim of this research was to evaluate the use of a low level of chromium oxide (Cr2O3 incorporated into the concentrate ration to estimate faecal output (FO in cattle. Four in vivo digestibility essays were conducted using four steers with live weights of

Studies on the power output of a MADE AE-30 operating on complex terrain. Annual Energy Production estimation and Multivariable analysis. A case of multi-stall effect

Energy Technology Data Exchange (ETDEWEB)

Cuerva, A.

1996-12-01

The main need of the EWTS-II Sub-project IV group is to have a suitable data-base which allows it to reach proper conclusions on the characteristics of power performance of wind turbines in complex terrain. With this aim, this document presents an analysis on the power output of the MADE AE-30 Wind turbine operating at Tarifa (also data from flat terrain are enclosed as a reference). An application of the bin method and AEP estimation for energy production method, in the two last issues a directional analysis and an study for two different turbulence intensity ranges are enclosed. Finally the Stepwise multirregression method is applied on the measurements to identify the stored parameters that have influence on the power output. A brief description of multi stall effect is enclosed. (Author)

Is supergravity well-posed?

International Nuclear Information System (INIS)

Isenberg, J.; Bao, D.; Yasskin, P.B.

1983-01-01

One rather fundamental question concerning supergravity remains unresolved: Is supergravity a well-posed field theory? That is, does a set of certain (Cauchy) data specified on some initial spacelike surface determine a unique, causally propagating spacetime solution of the supergravity field equations (at least in some finite neighborhood of the initial surface)? In this paper, the authors give a very brief report on work directed towards answering this question. (Auth.)

Output synchronization control of ship replenishment operations: theory and experiments

NARCIS (Netherlands)

Kyrkjebø, E.; Pettersen, K.Y.; Wondergem, M.; Nijmeijer, H.

2007-01-01

A leader–follower synchronization output feedback control scheme is presented for the ship replenishment problem where only positions are measured. No mathematical model of the leader ship is required, and the control scheme relies on nonlinear observers to estimate velocity and acceleration of all

Spontaneous and posed facial expression in Parkinson's disease.

Science.gov (United States)

Smith, M C; Smith, M K; Ellgring, H

1996-09-01

Spontaneous and posed emotional facial expressions in individuals with Parkinson's disease (PD, n = 12) were compared with those of healthy age-matched controls (n = 12). The intensity and amount of facial expression in PD patients were expected to be reduced for spontaneous but not posed expressions. Emotional stimuli were video clips selected from films, 2-5 min in duration, designed to elicit feelings of happiness, sadness, fear, disgust, or anger. Facial movements were coded using Ekman and Friesen's (1978) Facial Action Coding System (FACS). In addition, participants rated their emotional experience on 9-point Likert scales. The PD group showed significantly less overall facial reactivity than did controls when viewing the films. The predicted Group X Condition (spontaneous vs. posed) interaction effect on smile intensity was found when PD participants with more severe disease were compared with those with milder disease and with controls. In contrast, ratings of emotional experience were similar for both groups. Depression was positively associated with emotion rating but not with measures of facial activity. Spontaneous facial expression appears to be selectively affected in PD, whereas posed expression and emotional experience remain relatively intact.

Prescribed Performance Fuzzy Adaptive Output-Feedback Control for Nonlinear Stochastic Systems

Directory of Open Access Journals (Sweden)

Lili Zhang

2014-01-01

Full Text Available A prescribed performance fuzzy adaptive output-feedback control approach is proposed for a class of single-input and single-output nonlinear stochastic systems with unmeasured states. Fuzzy logic systems are used to identify the unknown nonlinear system, and a fuzzy state observer is designed for estimating the unmeasured states. Based on the backstepping recursive design technique and the predefined performance technique, a new fuzzy adaptive output-feedback control method is developed. It is shown that all the signals of the resulting closed-loop system are bounded in probability and the tracking error remains an adjustable neighborhood of the origin with the prescribed performance bounds. A simulation example is provided to show the effectiveness of the proposed approach.

PENDUGAAN ELASTISITAS PENAWARAN OUTPUT DAN PERMINTAAN INPUT USAHATANI JAGUNG

Directory of Open Access Journals (Sweden)

Adang Agustian

2012-12-01

Full Text Available This study aims to determine the effect of changes in output and input prices, corn research expenditures and road infrastructure on output supply and input demand for corn in the Province of East Java and West Java. The data that are analyzed are those of structure of costs of corn farming in the Province of East Java and West Java in 1985-2009. Estimation model employed is the method of Seemingly Unrelated Regression. The results showed that the output supply of corn both in the province of East Java and West Java are elastic to its price changes, however it is inelastic to the price changes of: seed, urea, TSP and labor. Input demand of seed, urea, TSP and labor area inelastic to their price changes. Policy implications of this research is efforts to increase the supply of corn can be carried out by increasing its price, expenditures of corn research, and road infrastructure.

Input-output supervisor

International Nuclear Information System (INIS)

Dupuy, R.

1970-01-01

The input-output supervisor is the program which monitors the flow of informations between core storage and peripheral equipments of a computer. This work is composed of three parts: 1 - Study of a generalized input-output supervisor. With sample modifications it looks like most of input-output supervisors which are running now on computers. 2 - Application of this theory on a magnetic drum. 3 - Hardware requirement for time-sharing. (author) [fr

Quantitative Analysis Method of Output Loss due to Restriction for Grid-connected PV Systems

Science.gov (United States)

Ueda, Yuzuru; Oozeki, Takashi; Kurokawa, Kosuke; Itou, Takamitsu; Kitamura, Kiyoyuki; Miyamoto, Yusuke; Yokota, Masaharu; Sugihara, Hiroyuki

Voltage of power distribution line will be increased due to reverse power flow from grid-connected PV systems. In the case of high density grid connection, amount of voltage increasing will be higher than the stand-alone grid connection system. To prevent the over voltage of power distribution line, PV system's output will be restricted if the voltage of power distribution line is close to the upper limit of the control range. Because of this interaction, amount of output loss will be larger in high density case. This research developed a quantitative analysis method for PV systems output and losses to clarify the behavior of grid connected PV systems. All the measured data are classified into the loss factors using 1 minute average of 1 second data instead of typical 1 hour average. Operation point on the I-V curve is estimated to quantify the loss due to the output restriction using module temperature, array output voltage, array output current and solar irradiance. As a result, loss due to output restriction is successfully quantified and behavior of output restriction is clarified.

On output measurements via radiation pressure

DEFF Research Database (Denmark)

Leeman, S.; Healey, A.J.; Forsberg, F.

1990-01-01

It is shown, by simple physical argument, that measurements of intensity with a radiation pressure balance should not agree with those based on calorimetric techniques. The conclusion is ultimately a consequence of the circumstance that radiation pressure measurements relate to wave momentum, while...... calorimetric methods relate to wave energy. Measurements with some typical ultrasound fields are performed with a novel type of hydrophone, and these allow an estimate to be made of the magnitude of the discrepancy to be expected between the two types of output measurement in a typical case....

Perspective projection for variance pose face recognition from camera calibration

Science.gov (United States)

Fakhir, M. M.; Woo, W. L.; Chambers, J. A.; Dlay, S. S.

2016-04-01

Variance pose is an important research topic in face recognition. The alteration of distance parameters across variance pose face features is a challenging. We provide a solution for this problem using perspective projection for variance pose face recognition. Our method infers intrinsic camera parameters of the image which enable the projection of the image plane into 3D. After this, face box tracking and centre of eyes detection can be identified using our novel technique to verify the virtual face feature measurements. The coordinate system of the perspective projection for face tracking allows the holistic dimensions for the face to be fixed in different orientations. The training of frontal images and the rest of the poses on FERET database determine the distance from the centre of eyes to the corner of box face. The recognition system compares the gallery of images against different poses. The system initially utilises information on position of both eyes then focuses principally on closest eye in order to gather data with greater reliability. Differentiation between the distances and position of the right and left eyes is a unique feature of our work with our algorithm outperforming other state of the art algorithms thus enabling stable measurement in variance pose for each individual.

Post processing of protein-compound docking for fragment-based drug discovery (FBDD): in-silico structure-based drug screening and ligand-binding pose prediction.

Science.gov (United States)

Fukunishi, Yoshifumi

2010-01-01

For fragment-based drug development, both hit (active) compound prediction and docking-pose (protein-ligand complex structure) prediction of the hit compound are important, since chemical modification (fragment linking, fragment evolution) subsequent to the hit discovery must be performed based on the protein-ligand complex structure. However, the naïve protein-compound docking calculation shows poor accuracy in terms of docking-pose prediction. Thus, post-processing of the protein-compound docking is necessary. Recently, several methods for the post-processing of protein-compound docking have been proposed. In FBDD, the compounds are smaller than those for conventional drug screening. This makes it difficult to perform the protein-compound docking calculation. A method to avoid this problem has been reported. Protein-ligand binding free energy estimation is useful to reduce the procedures involved in the chemical modification of the hit fragment. Several prediction methods have been proposed for high-accuracy estimation of protein-ligand binding free energy. This paper summarizes the various computational methods proposed for docking-pose prediction and their usefulness in FBDD.

Output power fluctuations due to different weights of macro particles used in particle-in-cell simulations of Cerenkov devices

International Nuclear Information System (INIS)

Bao, Rong; Li, Yongdong; Liu, Chunliang; Wang, Hongguang

2016-01-01

The output power fluctuations caused by weights of macro particles used in particle-in-cell (PIC) simulations of a backward wave oscillator and a travelling wave tube are statistically analyzed. It is found that the velocities of electrons passed a specific slow-wave structure form a specific electron velocity distribution. The electron velocity distribution obtained in PIC simulation with a relative small weight of macro particles is considered as an initial distribution. By analyzing this initial distribution with a statistical method, the estimations of the output power fluctuations caused by different weights of macro particles are obtained. The statistical method is verified by comparing the estimations with the simulation results. The fluctuations become stronger with increasing weight of macro particles, which can also be determined reversely from estimations of the output power fluctuations. With the weights of macro particles optimized by the statistical method, the output power fluctuations in PIC simulations are relatively small and acceptable.

Compressive power spectrum sensing for vibration-based output-only system identification of structural systems in the presence of noise

Science.gov (United States)

Tau Siesakul, Bamrung; Gkoktsi, Kyriaki; Giaralis, Agathoklis

2015-05-01

Motivated by the need to reduce monetary and energy consumption costs of wireless sensor networks in undertaking output-only/operational modal analysis of engineering structures, this paper considers a multi-coset analog-toinformation converter for structural system identification from acceleration response signals of white noise excited linear damped structures sampled at sub-Nyquist rates. The underlying natural frequencies, peak gains in the frequency domain, and critical damping ratios of the vibrating structures are estimated directly from the sub-Nyquist measurements and, therefore, the computationally demanding signal reconstruction step is by-passed. This is accomplished by first employing a power spectrum blind sampling (PSBS) technique for multi-band wide sense stationary stochastic processes in conjunction with deterministic non-uniform multi-coset sampling patterns derived from solving a weighted least square optimization problem. Next, modal properties are derived by the standard frequency domain peak picking algorithm. Special attention is focused on assessing the potential of the adopted PSBS technique, which poses no sparsity requirements to the sensed signals, to derive accurate estimates of modal structural system properties from noisy sub- Nyquist measurements. To this aim, sub-Nyquist sampled acceleration response signals corrupted by various levels of additive white noise pertaining to a benchmark space truss structure with closely spaced natural frequencies are obtained within an efficient Monte Carlo simulation-based framework. Accurate estimates of natural frequencies and reasonable estimates of local peak spectral ordinates and critical damping ratios are derived from measurements sampled at about 70% below the Nyquist rate and for SNR as low as 0db demonstrating that the adopted approach enjoys noise immunity.

DEREGULATION, FINANCIAL CRISIS, AND BANK EFFICIENCY IN TAIWAN: AN ESTIMATION OF UNDESIRABLE OUTPUTS

OpenAIRE

Liao, Chang-Sheng

2018-01-01

Purpose- This study investigates the undesirable impacts of outputson bank efficiency and contributes to the literature by assessing howregulation policies and other events impact bank efficiency in Taiwan inregards to deregulation, financial crisis, and financial reform from 1993 to2011. Methodology- In order to effectively deal with both undesirableand desirable outputs, this study follows Seiford and Zhu (2002), who recommendusing the standard data envelopment analysis model to measure per...

Iterative Estimation in Turbo Equalization Process

Directory of Open Access Journals (Sweden)

MORGOS Lucian

2014-05-01

Full Text Available This paper presents the iterative estimation in turbo equalization process. Turbo equalization is the process of reception in which equalization and decoding are done together, not as separate processes. For the equalizer to work properly, it must receive before equalization accurate information about the value of the channel impulse response. This estimation of channel impulse response is done by transmission of a training sequence known at reception. Knowing both the transmitted and received sequence, it can be calculated estimated value of the estimated the channel impulse response using one of the well-known estimation algorithms. The estimated value can be also iterative recalculated based on the sequence data available at the output of the channel and estimated sequence data coming from turbo equalizer output, thereby refining the obtained results.

Investigation on the integral output power model of a large-scale wind farm

Institute of Scientific and Technical Information of China (English)

BAO Nengsheng; MA Xiuqian; NI Weidou

2007-01-01

The integral output power model of a large-scale wind farm is needed when estimating the wind farm's output over a period of time in the future.The actual wind speed power model and calculation method of a wind farm made up of many wind turbine units are discussed.After analyzing the incoming wind flow characteristics and their energy distributions,and after considering the multi-effects among the wind turbine units and certain assumptions,the incoming wind flow model of multi-units is built.The calculation algorithms and steps of the integral output power model of a large-scale wind farm are provided.Finally,an actual power output of the wind farm is calculated and analyzed by using the practical measurement wind speed data.The characteristics of a large-scale wind farm are also discussed.

Assessing the risk posed by natural hazards to infrastructures

Science.gov (United States)

Eidsvig, Unni Marie K.; Kristensen, Krister; Vidar Vangelsten, Bjørn

2017-03-01

This paper proposes a model for assessing the risk posed by natural hazards to infrastructures, with a focus on the indirect losses and loss of stability for the population relying on the infrastructure. The model prescribes a three-level analysis with increasing level of detail, moving from qualitative to quantitative analysis. The focus is on a methodology for semi-quantitative analyses to be performed at the second level. The purpose of this type of analysis is to perform a screening of the scenarios of natural hazards threatening the infrastructures, identifying the most critical scenarios and investigating the need for further analyses (third level). The proposed semi-quantitative methodology considers the frequency of the natural hazard, different aspects of vulnerability, including the physical vulnerability of the infrastructure itself, and the societal dependency on the infrastructure. An indicator-based approach is applied, ranking the indicators on a relative scale according to pre-defined ranking criteria. The proposed indicators, which characterise conditions that influence the probability of an infrastructure malfunctioning caused by a natural event, are defined as (1) robustness and buffer capacity, (2) level of protection, (3) quality/level of maintenance and renewal, (4) adaptability and quality of operational procedures and (5) transparency/complexity/degree of coupling. Further indicators describe conditions influencing the socio-economic consequences of the infrastructure malfunctioning, such as (1) redundancy and/or substitution, (2) cascading effects and dependencies, (3) preparedness and (4) early warning, emergency response and measures. The aggregated risk estimate is a combination of the semi-quantitative vulnerability indicators, as well as quantitative estimates of the frequency of the natural hazard, the potential duration of the infrastructure malfunctioning (e.g. depending on the required restoration effort) and the number of users of

A Multi-Sensor Fusion MAV State Estimation from Long-Range Stereo, IMU, GPS and Barometric Sensors.

Science.gov (United States)

Song, Yu; Nuske, Stephen; Scherer, Sebastian

2016-12-22

State estimation is the most critical capability for MAV (Micro-Aerial Vehicle) localization, autonomous obstacle avoidance, robust flight control and 3D environmental mapping. There are three main challenges for MAV state estimation: (1) it can deal with aggressive 6 DOF (Degree Of Freedom) motion; (2) it should be robust to intermittent GPS (Global Positioning System) (even GPS-denied) situations; (3) it should work well both for low- and high-altitude flight. In this paper, we present a state estimation technique by fusing long-range stereo visual odometry, GPS, barometric and IMU (Inertial Measurement Unit) measurements. The new estimation system has two main parts, a stochastic cloning EKF (Extended Kalman Filter) estimator that loosely fuses both absolute state measurements (GPS, barometer) and the relative state measurements (IMU, visual odometry), and is derived and discussed in detail. A long-range stereo visual odometry is proposed for high-altitude MAV odometry calculation by using both multi-view stereo triangulation and a multi-view stereo inverse depth filter. The odometry takes the EKF information (IMU integral) for robust camera pose tracking and image feature matching, and the stereo odometry output serves as the relative measurements for the update of the state estimation. Experimental results on a benchmark dataset and our real flight dataset show the effectiveness of the proposed state estimation system, especially for the aggressive, intermittent GPS and high-altitude MAV flight.

Wind power error estimation in resource assessments.

Directory of Open Access Journals (Sweden)

Osvaldo Rodríguez

Full Text Available Estimating the power output is one of the elements that determine the techno-economic feasibility of a renewable project. At present, there is a need to develop reliable methods that achieve this goal, thereby contributing to wind power penetration. In this study, we propose a method for wind power error estimation based on the wind speed measurement error, probability density function, and wind turbine power curves. This method uses the actual wind speed data without prior statistical treatment based on 28 wind turbine power curves, which were fitted by Lagrange's method, to calculate the estimate wind power output and the corresponding error propagation. We found that wind speed percentage errors of 10% were propagated into the power output estimates, thereby yielding an error of 5%. The proposed error propagation complements the traditional power resource assessments. The wind power estimation error also allows us to estimate intervals for the power production leveled cost or the investment time return. The implementation of this method increases the reliability of techno-economic resource assessment studies.

Wind power error estimation in resource assessments.

Science.gov (United States)

Rodríguez, Osvaldo; Del Río, Jesús A; Jaramillo, Oscar A; Martínez, Manuel

2015-01-01

Estimating the power output is one of the elements that determine the techno-economic feasibility of a renewable project. At present, there is a need to develop reliable methods that achieve this goal, thereby contributing to wind power penetration. In this study, we propose a method for wind power error estimation based on the wind speed measurement error, probability density function, and wind turbine power curves. This method uses the actual wind speed data without prior statistical treatment based on 28 wind turbine power curves, which were fitted by Lagrange's method, to calculate the estimate wind power output and the corresponding error propagation. We found that wind speed percentage errors of 10% were propagated into the power output estimates, thereby yielding an error of 5%. The proposed error propagation complements the traditional power resource assessments. The wind power estimation error also allows us to estimate intervals for the power production leveled cost or the investment time return. The implementation of this method increases the reliability of techno-economic resource assessment studies.

Bank output measurement in the euro area : A modified approach

NARCIS (Netherlands)

Colangelo, A.; Inklaar, R.

Banks do not charge explicit fees for many of the services they provide, bundling the service payment with the offered interest rates. This output therefore has to be imputed using estimates of the opportunity cost of funds. We argue that rather than using the single short-term, low-risk interest

Output hardcopy devices

CERN Document Server

Durbeck, Robert

1988-01-01

Output Hardcopy Devices provides a technical summary of computer output hardcopy devices such as plotters, computer output printers, and CRT generated hardcopy. Important related technical areas such as papers, ribbons and inks, color techniques, controllers, and character fonts are also covered. Emphasis is on techniques primarily associated with printing, as well as the plotting capabilities of printing devices that can be effectively used for computer graphics in addition to their various printing functions. Comprised of 19 chapters, this volume begins with an introduction to vector and ras

Determining the confidence levels of sensor outputs using neural networks

Energy Technology Data Exchange (ETDEWEB)

Broten, G S; Wood, H C [Saskatchewan Univ., Saskatoon, SK (Canada). Dept. of Electrical Engineering

1996-12-31

This paper describes an approach for determining the confidence level of a sensor output using multi-sensor arrays, sensor fusion and artificial neural networks. The authors have shown in previous work that sensor fusion and artificial neural networks can be used to learn the relationships between the outputs of an array of simulated partially selective sensors and the individual analyte concentrations in a mixture of analyses. Other researchers have shown that an array of partially selective sensors can be used to determine the individual gas concentrations in a gaseous mixture. The research reported in this paper shows that it is possible to extract confidence level information from an array of partially selective sensors using artificial neural networks. The confidence level of a sensor output is defined as a numeric value, ranging from 0% to 100%, that indicates the confidence associated with a output of a given sensor. A three layer back-propagation neural network was trained on a subset of the sensor confidence level space, and was tested for its ability to generalize, where the confidence level space is defined as all possible deviations from the correct sensor output. A learning rate of 0.1 was used and no momentum terms were used in the neural network. This research has shown that an artificial neural network can accurately estimate the confidence level of individual sensors in an array of partially selective sensors. This research has also shown that the neural network`s ability to determine the confidence level is influenced by the complexity of the sensor`s response and that the neural network is able to estimate the confidence levels even if more than one sensor is in error. The fundamentals behind this research could be applied to other configurations besides arrays of partially selective sensors, such as an array of sensors separated spatially. An example of such a configuration could be an array of temperature sensors in a tank that is not in

Determining the confidence levels of sensor outputs using neural networks

International Nuclear Information System (INIS)

Broten, G.S.; Wood, H.C.

1995-01-01

This paper describes an approach for determining the confidence level of a sensor output using multi-sensor arrays, sensor fusion and artificial neural networks. The authors have shown in previous work that sensor fusion and artificial neural networks can be used to learn the relationships between the outputs of an array of simulated partially selective sensors and the individual analyte concentrations in a mixture of analyses. Other researchers have shown that an array of partially selective sensors can be used to determine the individual gas concentrations in a gaseous mixture. The research reported in this paper shows that it is possible to extract confidence level information from an array of partially selective sensors using artificial neural networks. The confidence level of a sensor output is defined as a numeric value, ranging from 0% to 100%, that indicates the confidence associated with a output of a given sensor. A three layer back-propagation neural network was trained on a subset of the sensor confidence level space, and was tested for its ability to generalize, where the confidence level space is defined as all possible deviations from the correct sensor output. A learning rate of 0.1 was used and no momentum terms were used in the neural network. This research has shown that an artificial neural network can accurately estimate the confidence level of individual sensors in an array of partially selective sensors. This research has also shown that the neural network's ability to determine the confidence level is influenced by the complexity of the sensor's response and that the neural network is able to estimate the confidence levels even if more than one sensor is in error. The fundamentals behind this research could be applied to other configurations besides arrays of partially selective sensors, such as an array of sensors separated spatially. An example of such a configuration could be an array of temperature sensors in a tank that is not in

A Support System for the Electric Appliance Control Using Pose Recognition

Science.gov (United States)

Kawano, Takuya; Yamamoto, Kazuhiko; Kato, Kunihito; Hongo, Hitoshi

In this paper, we propose an electric appliance control support system for aged and bedridden people using pose recognition. We proposed a pose recognition system that distinguishes between seven poses of the user on the bed. First, the face and arm regions of the user are detected by using the skin color. Our system focuses a recognition region surrounding the face region. Next, the higher order local autocorrelation features within the region are extracted. The linear discriminant analysis creates the coefficient matrix that can optimally distinguish among training data from the seven poses. Our algorithm can recognize the seven poses even if the subject wears different clothes and slightly shifts or slants on the bed. From the experimental results, our system achieved an accuracy rate of over 99 %. Then, we show that it possibles to construct one of a user-friendly system.

Flexible Polyhedral Surfaces with Two Flat Poses

Directory of Open Access Journals (Sweden)

Hellmuth Stachel

2015-05-01

Full Text Available We present three types of polyhedral surfaces, which are continuously flexible and have not only an initial pose, where all faces are coplanar, but pass during their self-motion through another pose with coplanar faces (“flat pose”. These surfaces are examples of so-called rigid origami, since we only admit exact flexions, i.e., each face remains rigid during the motion; only the dihedral angles vary. We analyze the geometry behind Miura-ori and address Kokotsakis’ example of a flexible tessellation with the particular case of a cyclic quadrangle. Finally, we recall Bricard’s octahedra of Type 3 and their relation to strophoids.

Applying physical input-output tables of energy to estimate the energy ecological footprint (EEF) of Galicia (NW Spain)

International Nuclear Information System (INIS)

Carballo Penela, Adolfo; Sebastian Villasante, Carlos

2008-01-01

Nowadays, the achievement of sustainable development constitutes an important constraint in the design of energy policies, being necessary the development of reliable indicators to obtain helpful information about the use of energy resources. The ecological footprint (EF) provides a referential framework for the analysis of human demand for bioproductivity, including energy issues. In this article, the theoretical bases of the footprint analysis are described by applying input-output tables of energy to estimate the Galician energy ecological footprint (EEF). It is concluded that the location of highly polluting industries in Galicia makes the Galician EEF quite higher than more developed regions of Spain. The relevance of the outer component of the Galician EEF is also studied. First, available information seems to indicate that the energy incorporated to the trading of manufactured goods would notably increase the Galician consumption of energy. On the other hand, the inclusion of electricity trade in the EEF analysis, including an adjustment, following the same philosophy as with manufactured goods is proposed. This adjustment would substantially reduce the Galician EEF, as the exported electricity widely exceeds the imported one

Constancy of radiation output during diagnostic X-ray exposures

International Nuclear Information System (INIS)

Ardran, G.M.; Crooks, H.E.; Birch, R.

1978-01-01

Variation in X-ray output and quality during a diagnostic exposure can be undesirable and may result in unnecessary dose to the patient. When significant build-up or decay periods are present errors will arise if factors obtained under steady-state conditions are employed to estimate the exposure. These parameters must be taken into account when calibrating X-ray generators. A variable speed spinning film device and a spectrometry system have been used to measure the variations under fluoroscopic and radiographic conditions for a number of generators. Variations in output due to filament heating, voltage supply and rectification, cable capacity and target pitting have been demonstrated. At low fluoroscopic currents, large surges and long decays have been observed; the significance of these effects is considered. (author)

Simulation of the output power of copper bromide lasers by the MARS method

International Nuclear Information System (INIS)

Iliev, I P; Voynikova, D S; Gocheva-Ilieva, S G

2012-01-01

The dependence of the output power of CuBr lasers (operating at wavelengths of 510.6 and 578.2 nm) on ten input physical parameters has been statistically analysed based on a large amount of experimental data accumulated for these lasers. Regression models have been built using the flexible nonparametric method of multivariate adaptive regression splines (MARS) to describe both linear and nonlinear local dependences. These models cover more than 97% initial data with an error comparable with the experimental error; they are applied to estimate and predict the output powers of both existing and future lasers. The advantage of the models constructed for estimating laser parameters over the standard parametric methods of multivariate factor and regression analysis is demonstrated.

Model output statistics applied to wind power prediction

Energy Technology Data Exchange (ETDEWEB)

Joensen, A; Giebel, G; Landberg, L [Risoe National Lab., Roskilde (Denmark); Madsen, H; Nielsen, H A [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)

1999-03-01

Being able to predict the output of a wind farm online for a day or two in advance has significant advantages for utilities, such as better possibility to schedule fossil fuelled power plants and a better position on electricity spot markets. In this paper prediction methods based on Numerical Weather Prediction (NWP) models are considered. The spatial resolution used in NWP models implies that these predictions are not valid locally at a specific wind farm. Furthermore, due to the non-stationary nature and complexity of the processes in the atmosphere, and occasional changes of NWP models, the deviation between the predicted and the measured wind will be time dependent. If observational data is available, and if the deviation between the predictions and the observations exhibits systematic behavior, this should be corrected for; if statistical methods are used, this approaches is usually referred to as MOS (Model Output Statistics). The influence of atmospheric turbulence intensity, topography, prediction horizon length and auto-correlation of wind speed and power is considered, and to take the time-variations into account, adaptive estimation methods are applied. Three estimation techniques are considered and compared, Extended Kalman Filtering, recursive least squares and a new modified recursive least squares algorithm. (au) EU-JOULE-3. 11 refs.

Delay signatures in the chaotic intensity output of a quantum dot ...

Indian Academy of Sciences (India)

journal of. May 2016 physics pp. 1021–1030. Delay signatures in the chaotic intensity output ... Research in complex systems require quantitative predictions of their dynamics, even ... used methods for estimating delay in complex dynamics are autocorrelation function ..... Authors thank BRNS for its financial support.

Review of the Risks Posed to Drinking Water by Man-Made Nanoparticels

DEFF Research Database (Denmark)

Tiede, K.; Westerhoff, P.; Hansen, Steffen Foss

an estimate of the amount of exposure to a range of ENPs from drinking water as well as a relative qualitative risk of exposure to ENPs from drinking water compared to other routes. A range of metal, metal oxide and organic-based ENPs were identified that have the potential to contaminate drinking waters...... drinking waters. In order to address these concerns, the U.K. Drinking Water Inspectorate (DWI) has published a "Review of the risks posed to drinking water by man-made nanoparticles"(DWI 70/2/246). The study, which was funded by the Department for Food and Rural Affairs (Defra), was undertaken by the Food...... (such as ENPs that are produced in large quantities or are used in a free form) were identified and categorised. The classification was based on a categorisation framework to aid exposure assessment of nanomaterials in consumer products. A conservative approach was then used to estimate worst case...

From Static Output Feedback to Structured Robust Static Output Feedback: A Survey

OpenAIRE

Sadabadi , Mahdieh ,; Peaucelle , Dimitri

2016-01-01

This paper reviews the vast literature on static output feedback design for linear time-invariant systems including classical results and recent developments. In particular, we focus on static output feedback synthesis with performance specifications, structured static output feedback, and robustness. The paper provides a comprehensive review on existing design approaches including iterative linear matrix inequalities heuristics, linear matrix inequalities with rank constraints, methods with ...

Inverse and Ill-posed Problems Theory and Applications

CERN Document Server

Kabanikhin, S I

2011-01-01

The text demonstrates the methods for proving the existence (if et all) and finding of inverse and ill-posed problems solutions in linear algebra, integral and operator equations, integral geometry, spectral inverse problems, and inverse scattering problems. It is given comprehensive background material for linear ill-posed problems and for coefficient inverse problems for hyperbolic, parabolic, and elliptic equations. A lot of examples for inverse problems from physics, geophysics, biology, medicine, and other areas of application of mathematics are included.

Pose and Shape Reconstruction of a Noncooperative Spacecraft Using Camera and Range Measurements

Directory of Open Access Journals (Sweden)

Renato Volpe

2017-01-01

Full Text Available Recent interest in on-orbit proximity operations has pushed towards the development of autonomous GNC strategies. In this sense, optical navigation enables a wide variety of possibilities as it can provide information not only about the kinematic state but also about the shape of the observed object. Various mission architectures have been either tested in space or studied on Earth. The present study deals with on-orbit relative pose and shape estimation with the use of a monocular camera and a distance sensor. The goal is to develop a filter which estimates an observed satellite’s relative position, velocity, attitude, and angular velocity, along with its shape, with the measurements obtained by a camera and a distance sensor mounted on board a chaser which is on a relative trajectory around the target. The filter’s efficiency is proved with a simulation on a virtual target object. The results of the simulation, even though relevant to a simplified scenario, show that the estimation process is successful and can be considered a promising strategy for a correct and safe docking maneuver.

Trajectory Planning with Pose Feedback for a Dual-Arm Space Robot

Directory of Open Access Journals (Sweden)

Yicheng Liu

2016-01-01

Full Text Available In order to obtain high precision path tracking for a dual-arm space robot, a trajectory planning method with pose feedback is proposed to be introduced into the design process in this paper. Firstly, pose error kinematic models are derived from the related kinematics and desired pose command for the end-effector and the base, respectively. On this basis, trajectory planning with pose feedback is proposed from a control perspective. Theoretical analyses show that the proposed trajectory planning algorithm can guarantee that pose error converges to zero exponentially for both the end-effector and the base when the robot is out of singular configuration. Compared with the existing algorithms, the proposed algorithm can lead to higher precision path tracking for the end-effector. Furthermore, the algorithm renders the system good anti-interference property for the base. Simulation results demonstrate the effectiveness of the proposed trajectory planning algorithm.

Estimated Impact of the American Recovery and Reinvestment Act on Employment and Economic Output from October 2011 Through December 2011

Science.gov (United States)

2012-02-01

used to finance 11. Changes in the output gap affect unemployment gradually over several quarters. Initially, part of a rise in output shows up as...discussion of the long-run effects of other debt- financed policies for boosting output and employment, see statement of Douglas W. Elmendorf, Director...DECEMBER 2011 CBO 6. See Eric M. Leeper, "Monetary Science, Fiscal Alchemy " (paper presented at the Federal Reserve Bank of Kansas City symposium

Fault-tolerant cooperative output regulation for multi-vehicle systems with sensor faults

Science.gov (United States)

Qin, Liguo; He, Xiao; Zhou, D. H.

2017-10-01

This paper presents a unified framework of fault diagnosis and fault-tolerant cooperative output regulation (FTCOR) for a linear discrete-time multi-vehicle system with sensor faults. The FTCOR control law is designed through three steps. A cooperative output regulation (COR) controller is designed based on the internal mode principle when there are no sensor faults. A sufficient condition on the existence of the COR controller is given based on the discrete-time algebraic Riccati equation (DARE). Then, a decentralised fault diagnosis scheme is designed to cope with sensor faults occurring in followers. A residual generator is developed to detect sensor faults of each follower, and a bank of fault-matching estimators are proposed to isolate and estimate sensor faults of each follower. Unlike the current distributed fault diagnosis for multi-vehicle systems, the presented decentralised fault diagnosis scheme in each vehicle reduces the communication and computation load by only using the information of the vehicle. By combing the sensor fault estimation and the COR control law, an FTCOR controller is proposed. Finally, the simulation results demonstrate the effectiveness of the FTCOR controller.

Determining the Performances of Pre-Service Primary School Teachers in Problem Posing Situations

Science.gov (United States)

Kilic, Cigdem

2013-01-01

This study examined the problem posing strategies of pre-service primary school teachers in different problem posing situations (PPSs) and analysed the issues they encounter while posing problems. A problem posing task consisting of six PPSs (two free, two structured, and two semi-structured situations) was delivered to 40 participants.…

Apo E isoforms, insulin output and plasma lipid levels in essential hypertension.

Science.gov (United States)

Dembińska-Kieć, A; Kawecka-Jaszcz, K; Kwaśniak, M; Guevara, I; Pankiewicz, J; Malczewska-Malec, M; Iwanejko, J; Hartwich, J; Zdzienicka, A; Stochmal, A; Leszczyńska-Gołabek, I

1998-02-01

The association between apo E isoforms and insulin output during the oral glucose test (OGTT) in 60 non-diabetic, non-obese patients with essential hypertension and in control subjects (non-obese, non-diabetic normotensive subjects) was estimated. According to low or high insulin output during OGTT, the subjects were divided into the following groups: normotensive subjects with low (NLI) and high (NHI) and hypertensive subjects with low (HLI) and high (HHI) insulin output. The apo E 4/2 phenotype was detected in 32% of hypertensive subjects but not in control subjects. The frequency of apo E 3/2 phenotype in hypertensive subjects was 5% and in normotensive subjects 15%. An increased frequency of phenotype apo E 4/3 was noticed both in HHI (46%) and in NHI (50%) compared with HLI (22%) and NLI (17%) groups. The results suggest that the determination of phenotypes apo E and insulin output may contribute to an early detection of individuals at high risk of hypertension development.

Estimation of Fano factor in inorganic scintillators

Energy Technology Data Exchange (ETDEWEB)

Bora, Vaibhav, E-mail: bora.vaibhav@gmail.com [Center for Gamma-Ray Imaging, Department of Medical Imaging, University of Arizona and College of Optical Sciences, University of Arizona, Tucson, AZ 85724 (United States); Barrett, Harrison H., E-mail: barrett@radiology.arizona.edu [Center for Gamma-Ray Imaging, Department of Medical Imaging, University of Arizona and College of Optical Sciences, University of Arizona, Tucson, AZ 85724 (United States); Fastje, David, E-mail: dfastje@gmail.com [Center for Gamma-Ray Imaging, Department of Medical Imaging, University of Arizona and College of Optical Sciences, University of Arizona, Tucson, AZ 85724 (United States); Clarkson, Eric, E-mail: clarkson@radiology.arizona.edu [Center for Gamma-Ray Imaging, Department of Medical Imaging, University of Arizona and College of Optical Sciences, University of Arizona, Tucson, AZ 85724 (United States); Furenlid, Lars, E-mail: furen@radiology.arizona.edu [Center for Gamma-Ray Imaging, Department of Medical Imaging, University of Arizona and College of Optical Sciences, University of Arizona, Tucson, AZ 85724 (United States); Bousselham, Abdelkader, E-mail: abousselham@qf.org.qa [Qatar Foundation, QEERI, P.O. Box 5825, Doha (Qatar); Shah, Kanai S., E-mail: kanaishah@yahoo.com [Radiation Monitoring Devices, Inc., Watertown, MA 02472 (United States); Glodo, Jarek, E-mail: jglodo@rmdinc.com [Radiation Monitoring Devices, Inc., Watertown, MA 02472 (United States)

2016-01-01

The Fano factor of an integer-valued random variable is defined as the ratio of its variance to its mean. Correlation between the outputs of two photomultiplier tubes on opposite faces of a scintillation crystal was used to estimate the Fano factor of photoelectrons and scintillation photons. Correlations between the integrals of the detector outputs were used to estimate the photoelectron and photon Fano factor for YAP:Ce, SrI{sub 2}:Eu and CsI:Na scintillator crystals. At 662 keV, SrI{sub 2}:Eu was found to be sub-Poisson, while CsI:Na and YAP:Ce were found to be super-Poisson. An experiment setup inspired from the Hanbury Brown and Twiss experiment was used to measure the correlations as a function of time between the outputs of two photomultiplier tubes looking at the same scintillation event. A model of the scintillation and the detection processes was used to generate simulated detector outputs as a function of time for different values of Fano factor. The simulated outputs from the model for different Fano factors was compared to the experimentally measured detector outputs to estimate the Fano factor of the scintillation photons for YAP:Ce, LaBr{sub 3}:Ce scintillator crystals. At 662 keV, LaBr{sub 3}:Ce was found to be sub-Poisson, while YAP:Ce was found to be close to Poisson.

Tooth display and lip position during spontaneous and posed smiling in adults.

Science.gov (United States)

Van Der Geld, Pieter; Oosterveld, Paul; Berge, Stefaan J; Kuijpers-Jagtman, Anne M

2008-08-01

To analyze differences in tooth display, lip-line height, and smile width between the posed smiling record, traditionally produced for orthodontic diagnosis, and the spontaneous (Duchenne) smile of joy. The faces of 122 male participants were each filmed during spontaneous and posed smiling. Spontaneous smiles were elicited through the participants watching a comical movie. Maxillary and mandibular lip-line heights, tooth display, and smile width were measured using a digital videographic method for smile analysis. Paired sample t-tests were used to compare measurements of posed and spontaneous smiling. Maxillary lip-line heights during spontaneous smiling were significantly higher than during posed smiling. Compared to spontaneous smiling, tooth display in the (pre)molar area during posed smiling decreased by up to 30%, along with a significant reduction of smile width. During posed smiling, also mandibular lip-line heights changed and the teeth were more covered by the lower lip than during spontaneous smiling. Reduced lip-line heights, tooth display, and smile width on a posed smiling record can have implications for the diagnostics of lip-line height, smile arc, buccal corridors, and plane of occlusion. Spontaneous smiling records next to posed smiling records are therefore recommended for diagnostic purposes. Because of the dynamic nature of spontaneous smiling, it is proposed to switch to dynamic video recording of the smile.

Energy output estimation for a small wind turbine positioned on a rooftop in the urban environment with and without a duct

Energy Technology Data Exchange (ETDEWEB)

Beller, C.

2011-05-15

Nowadays, wind turbines in general, but also urban wind turbines attained acceptance to a certain extend. Conceptual designs and some examples in reality exist, where small-scale wind turbines have been implemented close to buildings or even integrated in the building structure. This work is aiming to estimate how much energy a wind turbine could produce in the built environment, depending on its integration and configuration. On the basis of measurements taken on the rooftop of H.C. Orsted Institut in Copenhagen, which is located in an urban area, a comparison of fictive free standing turbines with ducted turbines of the same type was carried out. First, a prevailing wind energy direction was detected with rough mean velocity and frequency calculations. Next, a duct was aligned with the direction, where the highest energy potential was found. Further calculations were conducted with more detailed wind velocity distributions, depending on the wind direction sectors. The duct's wind velocity amplification capability was set to 14%, while a total opening angle of 30. was assumed to be accessible from both sides. With the simplifying assumptions and the uncertainties at the location of measurement, the free standing turbines had an energy potential of 300kWh/m2/a for the horizontal axis wind turbine (HAWT) and for the vertical axis wind turbine (VAWT) 180kWh/m2/a. For the ducted turbines an energy output of 180kWh/m2/a was found for the HAWT configuration, while the VAWT configuration reached an output of 110kWh/m2/a. The available wind had an energy potential of 730kWh/m2/a. Evaluating these results it seems a free standing turbine is preferable, when only considering the power output, whereas the ducted version comprises properties, which are important considering the requirements needed in the inhabited area such as safety and noise issues. (Author)

Compensating Pose Uncertainties through Appropriate Gripper Finger Cutouts

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Wolniakowski Adam

2018-03-01

Full Text Available The gripper finger design is a recurring problem in many robotic grasping platforms used in industry. The task of switching the gripper configuration to accommodate for a new batch of objects typically requires engineering expertise, and is a lengthy and costly iterative trial-and-error process. One of the open challenges is the need for the gripper to compensate for uncertainties inherent to the workcell, e.g. due to errors in calibration, inaccurate pose estimation from the vision system, or object deformation. In this paper, we present an analysis of gripper uncertainty compensating capabilities in a sample industrial object grasping scenario for a finger that was designed using an automated simulation-based geometry optimization method (Wolniakowski et al., 2013, 2015. We test the developed gripper with a set of grasps subjected to structured perturbation in a simulation environment and in the real-world setting. We provide a comparison of the data obtained by using both of these approaches. We argue that the strong correspondence observed in results validates the use of dynamic simulation for the gripper finger design and optimization.

Estimation of the contribution of exports to the provincial economy: an analysis based on China's multi-regional input-output tables.

Science.gov (United States)

Wu, Sanmang; Li, Shantong; Lei, Yalin

2016-01-01

This paper developed an estimation model for the contribution of exports to a country's regional economy based on the Chenery-Moses model and conducted an empirical analysis using China's multi-regional input-output tables for 1997, 2002, and 2007. The results indicated that China's national exports make significantly different contributions to the provincial economy in various regions, with the greatest contribution being observed in the eastern region and the smallest in the central region. The provinces are also subjected to significantly different export spillover effects. The boosting effect for the eastern provinces is primarily generated from local exports, whereas the western provinces primarily benefit from the export spillover effect from the eastern provinces. The eastern provinces, such as Guangdong, Zhejiang, Jiangsu, and Shanghai, are the primary sources of export spillover effects, and Guangdong is the largest source of export spillover effects for almost all of the provinces in China.

Air Pollution and 'Dirty' Industries. How and Why Does the Composition of Manufacturing Output Change with Economic Development?

International Nuclear Information System (INIS)

Cole, M.A.

2000-01-01

This paper examines the impact on air pollution of changes in the composition of manufacturing output in developed and developing countries. Pollution emissions from manufacturing output are estimated in a manner which holds constant the effect of technology and regulations allowing the impact of compositional changes alone on pollution to be estimated. The paper has three main findings; (1) the inverted-U estimated between per capita income and the pollution intensity of GDP arises due to both the composition of manufacturing becoming cleaner and the share of manufacturing output in GDP falling. Compositional changes alone are not responsible for the inverted-U between per capita income and per capita emissions; (2) changes to the composition of manufacturing output are consistent with the pollution haven hypothesis, however there is clear evidence that rising per capita incomes are associated with a failing income elasticity of demand for 'dirty' products. This fact may explain the compositional changes that occur with development; (3) in addition to the income elasticity effect, the analysis suggests that land prices and to a lesser extent the prices of labour and capital, determine the proportion of dirty industry within a country's manufacturing sector. 27 refs

GDP Growth, Potential Output, and Output Gaps in Mexico

OpenAIRE

Ebrima A Faal

2005-01-01

This paper analyzes the sources of Mexico's economic growth since the 1960s and compares various decompositions of historical growth into its trend and cyclical components. The role of the implied output gaps in the inflationary process is then assessed. Looking ahead, the paper presents medium-term paths for GDP based on alternative assumptions for productivity growth rates. The results indicate that the most important factor underlying the slowdown in output growth was a decline in trend to...

A hybrid method for forecasting the energy output of photovoltaic systems

International Nuclear Information System (INIS)

Ramsami, Pamela; Oree, Vishwamitra

2015-01-01

Highlights: • We propose a novel hybrid technique for predicting the daily PV energy output. • Multiple linear regression, FFNN and GRNN artificial neural networks are used. • Stepwise regression is used to select the most relevant meteorological parameters. • SR-FFNN reduces the average dispersion and overall bias in prediction errors. • Accuracy metrics of hybrid models are better than those of single-stage models. - Abstract: The intermittent nature of solar energy poses many challenges to renewable energy system operators in terms of operational planning and scheduling. Predicting the output of photovoltaic systems is therefore essential for managing the operation and assessing the economic performance of power systems. This paper presents a new technique for forecasting the 24-h ahead stochastic energy output of photovoltaic systems based on the daily weather forecasts. A comparison of the performances of the hybrid technique with conventional linear regression and artificial neural network models has also been reported. Initially, three single-stage models were designed, namely the generalized regression neural network, feedforward neural network and multiple linear regression. Subsequently, a hybrid-modeling approach was adopted by applying stepwise regression to select input variables of greater importance. These variables were then fed to the single-stage models resulting in three hybrid models. They were then validated by comparing the forecasts of the models with measured dataset from an operational photovoltaic system. The accuracy of the each model was evaluated based on the correlation coefficient, mean absolute error, mean bias error and root mean square error values. Simulation results revealed that the hybrid models perform better than their corresponding single-stage models. Stepwise regression-feedforward neural network hybrid model outperformed the other models with root mean square error, mean absolute error, mean bias error and

LOAD THAT MAXIMIZES POWER OUTPUT IN COUNTERMOVEMENT JUMP

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Pedro Jimenez-Reyes

2016-02-01

Full Text Available ABSTRACT Introduction: One of the main problems faced by strength and conditioning coaches is the issue of how to objectively quantify and monitor the actual training load undertaken by athletes in order to maximize performance. It is well known that performance of explosive sports activities is largely determined by mechanical power. Objective: This study analysed the height at which maximal power output is generated and the corresponding load with which is achieved in a group of male-trained track and field athletes in the test of countermovement jump (CMJ with extra loads (CMJEL. Methods: Fifty national level male athletes in sprinting and jumping performed a CMJ test with increasing loads up to a height of 16 cm. The relative load that maximized the mechanical power output (Pmax was determined using a force platform and lineal encoder synchronization and estimating the power by peak power, average power and flight time in CMJ. Results: The load at which the power output no longer existed was at a height of 19.9 ± 2.35, referring to a 99.1 ± 1% of the maximum power output. The load that maximizes power output in all cases has been the load with which an athlete jump a height of approximately 20 cm. Conclusion: These results highlight the importance of considering the height achieved in CMJ with extra load instead of power because maximum power is always attained with the same height. We advise for the preferential use of the height achieved in CMJEL test, since it seems to be a valid indicative of an individual's actual neuromuscular potential providing a valid information for coaches and trainers when assessing the performance status of our athletes and to quantify and monitor training loads, measuring only the height of the jump in the exercise of CMJEL.

Method for estimation of the output electric power of PV module with considering environmental factors. Method for estimation of output using I-V curves; Kankyo inshi wo koryoshita taiyo denchi module no shutsuryoku keisanho. I-V tokusei curve ni yoru keisan

Energy Technology Data Exchange (ETDEWEB)

Yamagami, Y; Tani, T [Science University of Tokyo, Tokyo (Japan)

1996-10-27

Based on the basic quality equation of photovoltaic (PV) cell, a quality equation of PV module has been constructed by considering the spectral distribution of solar radiation and its intensity. A calculation method has been also proposed for determining the output from current-voltage (I-V) curves. Effectiveness of this method was examined by comparing calculated results and observed results. Amorphous Si (a-Si) and polycrystal Si PV modules were examined. By considering the environmental factors, differences of the annual output between the calculated and observed values were reduced from 2.50% to 0.95% for the a-Si PV module, and from 2.52% to 1.24% for the polycrystal Si PV module, which resulted in the reduction more than 50%. For the a-Si PV module, the environmental factor most greatly affecting the annual output was the spectral distribution of solar radiation, which was 3.86 times as large as the cell temperature, and 1.04 times as large as the intensity of solar radiation. For the polycrystal PV module, the environmental factor most greatly affecting the annual output was the cell temperature, which was 7.05 times as large as the spectral distribution of solar radiation, and 1.74 times as large as the intensity of solar radiation. 6 refs., 4 figs., 1 tab.

Audiovisual Head Orientation Estimation with Particle Filtering in Multisensor Scenarios

Directory of Open Access Journals (Sweden)

Javier Hernando

2007-07-01

Full Text Available This article presents a multimodal approach to head pose estimation of individuals in environments equipped with multiple cameras and microphones, such as SmartRooms or automatic video conferencing. Determining the individuals head orientation is the basis for many forms of more sophisticated interactions between humans and technical devices and can also be used for automatic sensor selection (camera, microphone in communications or video surveillance systems. The use of particle filters as a unified framework for the estimation of the head orientation for both monomodal and multimodal cases is proposed. In video, we estimate head orientation from color information by exploiting spatial redundancy among cameras. Audio information is processed to estimate the direction of the voice produced by a speaker making use of the directivity characteristics of the head radiation pattern. Furthermore, two different particle filter multimodal information fusion schemes for combining the audio and video streams are analyzed in terms of accuracy and robustness. In the first one, fusion is performed at a decision level by combining each monomodal head pose estimation, while the second one uses a joint estimation system combining information at data level. Experimental results conducted over the CLEAR 2006 evaluation database are reported and the comparison of the proposed multimodal head pose estimation algorithms with the reference monomodal approaches proves the effectiveness of the proposed approach.

Mathematical Thinking and Creativity through Mathematical Problem Posing and Solving

Directory of Open Access Journals (Sweden)

María F. Ayllón

2016-04-01

Full Text Available This work shows the relationship between the development of mathematical thinking and creativity with mathematical problem posing and solving. Creativity and mathematics are disciplines that do not usually appear together. Both concepts constitute complex processes sharing elements, such as fluency (number of ideas, flexibility (range of ideas, novelty (unique idea and elaboration (idea development. These factors contribute, among others, to the fact that schoolchildren are competent in mathematics. The problem solving and posing are a very powerful evaluation tool that shows the mathematical reasoning and creative level of a person. Creativity is part of the mathematics education and is a necessary ingredient to perform mathematical assignments. This contribution presents some important research works about problem posing and solving related to the development of mathematical knowledge and creativity. To that end, it is based on various beliefs reflected in the literature with respect to notions of creativity, problem solving and posing.

A Grasp-Pose Generation Method Based on Gaussian Mixture Models

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Wenjia Wu

2015-11-01

Full Text Available A Gaussian Mixture Model (GMM-based grasp-pose generation method is proposed in this paper. Through offline training, the GMM is set up and used to depict the distribution of the robot's reachable orientations. By dividing the robot's workspace into small 3D voxels and training the GMM for each voxel, a look-up table covering all the workspace is built with the x, y and z positions as the index and the GMM as the entry. Through the definition of Task Space Regions (TSR, an object's feasible grasp poses are expressed as a continuous region. With the GMM, grasp poses can be preferentially sampled from regions with high reachability probabilities in the online grasp-planning stage. The GMM can also be used as a preliminary judgement of a grasp pose's reachability. Experiments on both a simulated and a real robot show the superiority of our method over the existing method.

Modelling and Prediction of Photovoltaic Power Output Using Artificial Neural Networks

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Aminmohammad Saberian

2014-01-01

Full Text Available This paper presents a solar power modelling method using artificial neural networks (ANNs. Two neural network structures, namely, general regression neural network (GRNN feedforward back propagation (FFBP, have been used to model a photovoltaic panel output power and approximate the generated power. Both neural networks have four inputs and one output. The inputs are maximum temperature, minimum temperature, mean temperature, and irradiance; the output is the power. The data used in this paper started from January 1, 2006, until December 31, 2010. The five years of data were split into two parts: 2006–2008 and 2009-2010; the first part was used for training and the second part was used for testing the neural networks. A mathematical equation is used to estimate the generated power. At the end, both of these networks have shown good modelling performance; however, FFBP has shown a better performance comparing with GRNN.

Parametric estimation of the Duffing system by using a modified gradient algorithm

International Nuclear Information System (INIS)

Aguilar-Ibanez, Carlos; Sanchez Herrera, Jorge; Garrido-Moctezuma, Ruben

2008-01-01

The Letter presents a strategy for recovering the unknown parameters of the Duffing oscillator using a measurable output signal. The suggested approach employs the construction of an integral parametrization of one auxiliary output. It is calculated by measuring the difference between the output and its respective delay output. First we estimate the auxiliary output, followed by the application of a modified gradient algorithm, then we adjust the gains of the proposed linear estimator, until this error converges to zero. The convergence of the proposed scheme is shown using Lyapunov method

Investigation of Problem-Solving and Problem-Posing Abilities of Seventh-Grade Students

Science.gov (United States)

Arikan, Elif Esra; Ünal, Hasan

2015-01-01

This study aims to examine the effect of multiple problem-solving skills on the problem-posing abilities of gifted and non-gifted students and to assess whether the possession of such skills can predict giftedness or affect problem-posing abilities. Participants' metaphorical images of problem posing were also explored. Participants were 20 gifted…

Preparatory power posing affects nonverbal presence and job interview performance.

Science.gov (United States)

Cuddy, Amy J C; Wilmuth, Caroline A; Yap, Andy J; Carney, Dana R

2015-07-01

The authors tested whether engaging in expansive (vs. contractive) "power poses" before a stressful job interview--preparatory power posing--would enhance performance during the interview. Participants adopted high-power (i.e., expansive, open) poses or low-power (i.e., contractive, closed) poses, and then prepared and delivered a speech to 2 evaluators as part of a mock job interview. All interview speeches were videotaped and coded for overall performance and hireability and for 2 potential mediators: verbal content (e.g., structure, content) and nonverbal presence (e.g., captivating, enthusiastic). As predicted, those who prepared for the job interview with high- (vs. low-) power poses performed better and were more likely to be chosen for hire; this relation was mediated by nonverbal presence, but not by verbal content. Although previous research has focused on how a nonverbal behavior that is enacted during interactions and observed by perceivers affects how those perceivers evaluate and respond to the actor, this experiment focused on how a nonverbal behavior that is enacted before the interaction and unobserved by perceivers affects the actor's performance, which, in turn, affects how perceivers evaluate and respond to the actor. This experiment reveals a theoretically novel and practically informative result that demonstrates the causal relation between preparatory nonverbal behavior and subsequent performance and outcomes. (c) 2015 APA, all rights reserved).

Consistently Showing Your Best Side? Intra-individual Consistency in #Selfie Pose Orientation

Science.gov (United States)

Lindell, Annukka K.

2017-01-01

Painted and photographic portraits of others show an asymmetric bias: people favor their left cheek. Both experimental and database studies confirm that the left cheek bias extends to selfies. To date all such selfie studies have been cross-sectional; whether individual selfie-takers tend to consistently favor the same pose orientation, or switch between multiple poses, remains to be determined. The present study thus examined intra-individual consistency in selfie pose orientations. Two hundred selfie-taking participants (100 male and 100 female) were identified by searching #selfie on Instagram. The most recent 10 single-subject selfies for the each of the participants were selected and coded for type of selfie (normal; mirror) and pose orientation (left, midline, right), resulting in a sample of 2000 selfies. Results indicated that selfie-takers do tend to consistently adopt a preferred pose orientation (α = 0.72), with more participants showing an overall left cheek bias (41%) than would be expected by chance (overall right cheek bias = 31.5%; overall midline bias = 19.5%; no overall bias = 8%). Logistic regression modellng, controlling for the repeated measure of participant identity, indicated that sex did not affect pose orientation. However, selfie type proved a significant predictor when comparing left and right cheek poses, with a stronger left cheek bias for mirror than normal selfies. Overall, these novel findings indicate that selfie-takers show intra-individual consistency in pose orientation, and in addition, replicate the previously reported left cheek bias for selfies and other types of portrait, confirming that the left cheek bias also presents within individuals’ selfie corpora. PMID:28270790

Multiscale analysis for ill-posed problems with semi-discrete Tikhonov regularization

International Nuclear Information System (INIS)

Zhong, Min; Lu, Shuai; Cheng, Jin

2012-01-01

Using compactly supported radial basis functions of varying radii, Wendland has shown how a multiscale analysis can be applied to the approximation of Sobolev functions on a bounded domain, when the available data are discrete and noisy. Here, we examine the application of this analysis to the solution of linear moderately ill-posed problems using semi-discrete Tikhonov–Phillips regularization. As in Wendland’s work, the actual multiscale approximation is constructed by a sequence of residual corrections, where different support radii are employed to accommodate different scales. The convergence of the algorithm for noise-free data is given. Based on the Morozov discrepancy principle, a posteriori parameter choice rule and error estimates for the noisy data are derived. Two numerical examples are presented to illustrate the appropriateness of the proposed method. (paper)

Greedy solution of ill-posed problems: error bounds and exact inversion

International Nuclear Information System (INIS)

Denis, L; Lorenz, D A; Trede, D

2009-01-01

The orthogonal matching pursuit (OMP) is a greedy algorithm to solve sparse approximation problems. Sufficient conditions for exact recovery are known with and without noise. In this paper we investigate the applicability of the OMP for the solution of ill-posed inverse problems in general, and in particular for two deconvolution examples from mass spectrometry and digital holography, respectively. In sparse approximation problems one often has to deal with the problem of redundancy of a dictionary, i.e. the atoms are not linearly independent. However, one expects them to be approximatively orthogonal and this is quantified by the so-called incoherence. This idea cannot be transferred to ill-posed inverse problems since here the atoms are typically far from orthogonal. The ill-posedness of the operator probably causes the correlation of two distinct atoms to become huge, i.e. that two atoms look much alike. Therefore, one needs conditions which take the structure of the problem into account and work without the concept of coherence. In this paper we develop results for the exact recovery of the support of noisy signals. In the two examples, mass spectrometry and digital holography, we show that our results lead to practically relevant estimates such that one may check a priori if the experimental setup guarantees exact deconvolution with OMP. Especially in the example from digital holography, our analysis may be regarded as a first step to calculate the resolution power of droplet holography

Light output measurements and computational models of microcolumnar CsI scintillators for x-ray imaging

Energy Technology Data Exchange (ETDEWEB)

Nillius, Peter, E-mail: nillius@mi.physics.kth.se; Klamra, Wlodek; Danielsson, Mats [Royal Institute of Technology (KTH), Stockholm SE-100 44 (Sweden); Sibczynski, Pawel [National Centre for Nuclear Research, Otwock 05-400 (Poland); Sharma, Diksha; Badano, Aldo [Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, FDA, Silver Spring, Maryland 20993 (United States)

2015-02-15

Purpose: The authors report on measurements of light output and spatial resolution of microcolumnar CsI:Tl scintillator detectors for x-ray imaging. In addition, the authors discuss the results of simulations aimed at analyzing the results of synchrotron and sealed-source exposures with respect to the contributions of light transport to the total light output. Methods: The authors measured light output from a 490-μm CsI:Tl scintillator screen using two setups. First, the authors used a photomultiplier tube (PMT) to measure the response of the scintillator to sealed-source exposures. Second, the authors performed imaging experiments with a 27-keV monoenergetic synchrotron beam and a slit to calculate the total signal generated in terms of optical photons per keV. The results of both methods are compared to simulations obtained with hybridMANTIS, a coupled x-ray, electron, and optical photon Monte Carlo transport package. The authors report line response (LR) and light output for a range of linear absorption coefficients and describe a model that fits at the same time the light output and the blur measurements. Comparing the experimental results with the simulations, the authors obtained an estimate of the absorption coefficient for the model that provides good agreement with the experimentally measured LR. Finally, the authors report light output simulation results and their dependence on scintillator thickness and reflectivity of the backing surface. Results: The slit images from the synchrotron were analyzed to obtain a total light output of 48 keV{sup −1} while measurements using the fast PMT instrument setup and sealed-sources reported a light output of 28 keV{sup −1}. The authors attribute the difference in light output estimates between the two methods to the difference in time constants between the camera and PMT measurements. Simulation structures were designed to match the light output measured with the camera while providing good agreement with the

Early-Transition Output Decline Revisited

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Crt Kostevc

2016-05-01

Full Text Available In this paper we revisit the issue of aggregate output decline that took place in the early transition period. We propose an alternative explanation of output decline that is applicable to Central- and Eastern-European countries. In the first part of the paper we develop a simple dynamic general equilibrium model that builds on work by Gomulka and Lane (2001. In particular, we consider price liberalization, interpreted as elimination of distortionary taxation, as a trigger of the output decline. We show that price liberalization in interaction with heterogeneous adjustment costs and non-employment benefits lead to aggregate output decline and surge in wage inequality. While these patterns are consistent with actual dynamics in CEE countries, this model cannot generate output decline in all sectors. Instead sectors that were initially taxed even exhibit output growth. Thus, in the second part we consider an alternative general equilibrium model with only one production sector and two types of labor and distortion in a form of wage compression during the socialist era. The trigger for labor mobility and consequently output decline is wage liberalization. Assuming heterogeneity of workers in terms of adjustment costs and non-employment benefits can explain output decline in all industries.

Cultural adaptations to the differential threats posed by hot versus cold climates.

Science.gov (United States)

Murray, Damian R

2013-10-01

Hot and cold climates have posed differential threats to human survival throughout history. Cold temperatures can pose direct threats to survival in themselves, whereas hot temperatures may pose threats indirectly through higher prevalence of infectious disease. These differential threats yield convergent predictions for the relationship between more demanding climates and freedom of expression, but divergent predictions for freedom from discrimination.

Conceiving Human Interaction by Visualising Depth Data of Head Pose Changes and Emotion Recognition via Facial Expressions

Directory of Open Access Journals (Sweden)

Grigorios Kalliatakis

2017-07-01

Full Text Available Affective computing in general and human activity and intention analysis in particular comprise a rapidly-growing field of research. Head pose and emotion changes present serious challenges when applied to player’s training and ludology experience in serious games, or analysis of customer satisfaction regarding broadcast and web services, or monitoring a driver’s attention. Given the increasing prominence and utility of depth sensors, it is now feasible to perform large-scale collection of three-dimensional (3D data for subsequent analysis. Discriminative random regression forests were selected in order to rapidly and accurately estimate head pose changes in an unconstrained environment. In order to complete the secondary process of recognising four universal dominant facial expressions (happiness, anger, sadness and surprise, emotion recognition via facial expressions (ERFE was adopted. After that, a lightweight data exchange format (JavaScript Object Notation (JSON is employed, in order to manipulate the data extracted from the two aforementioned settings. Motivated by the need to generate comprehensible visual representations from different sets of data, in this paper, we introduce a system capable of monitoring human activity through head pose and emotion changes, utilising an affordable 3D sensing technology (Microsoft Kinect sensor.

Problem Posing with Realistic Mathematics Education Approach in Geometry Learning

Science.gov (United States)

Mahendra, R.; Slamet, I.; Budiyono

2017-09-01

One of the difficulties of students in the learning of geometry is on the subject of plane that requires students to understand the abstract matter. The aim of this research is to determine the effect of Problem Posing learning model with Realistic Mathematics Education Approach in geometry learning. This quasi experimental research was conducted in one of the junior high schools in Karanganyar, Indonesia. The sample was taken using stratified cluster random sampling technique. The results of this research indicate that the model of Problem Posing learning with Realistic Mathematics Education Approach can improve students’ conceptual understanding significantly in geometry learning especially on plane topics. It is because students on the application of Problem Posing with Realistic Mathematics Education Approach are become to be active in constructing their knowledge, proposing, and problem solving in realistic, so it easier for students to understand concepts and solve the problems. Therefore, the model of Problem Posing learning with Realistic Mathematics Education Approach is appropriately applied in mathematics learning especially on geometry material. Furthermore, the impact can improve student achievement.

Squeezeposenet: Image Based Pose Regression with Small Convolutional Neural Networks for Real Time Uas Navigation

Science.gov (United States)

Müller, M. S.; Urban, S.; Jutzi, B.

2017-08-01

The number of unmanned aerial vehicles (UAVs) is increasing since low-cost airborne systems are available for a wide range of users. The outdoor navigation of such vehicles is mostly based on global navigation satellite system (GNSS) methods to gain the vehicles trajectory. The drawback of satellite-based navigation are failures caused by occlusions and multi-path interferences. Beside this, local image-based solutions like Simultaneous Localization and Mapping (SLAM) and Visual Odometry (VO) can e.g. be used to support the GNSS solution by closing trajectory gaps but are computationally expensive. However, if the trajectory estimation is interrupted or not available a re-localization is mandatory. In this paper we will provide a novel method for a GNSS-free and fast image-based pose regression in a known area by utilizing a small convolutional neural network (CNN). With on-board processing in mind, we employ a lightweight CNN called SqueezeNet and use transfer learning to adapt the network to pose regression. Our experiments show promising results for GNSS-free and fast localization.

Investigation of solar photovoltaic module power output by various models

International Nuclear Information System (INIS)

Jakhrani, A.Q.; Othman, A.K.; Rigit, A.R.H.; Baini, R.

2012-01-01

This paper aims to investigate the power output of a solar photovoltaic module by various models and to formulate a suitable model for predicting the performance of solar photovoltaic modules. The model was used to correct the configurations of solar photovoltaic systems for sustainable power supply. Different types of models namely the efficiency, power, fill factor and current-voltage characteristic curve models have been reviewed. It was found that the examined models predicted a 40% yield of the rated power in cloudy weather conditions and up to 80% in clear skies. The models performed well in terms of electrical efficiency in cloudy days if the influence of low irradiance were incorporated. Both analytical and numerical methods were employed in the formulation of improved model which gave +- 2% error when compared with the rated power output of solar photovoltaic module. The proposed model is more practical in terms of number of variables used and acceptable performance in humid atmospheres. Therefore, it could be useful for the estimation of power output of the solar photovoltaic systems in Sarawak region. (author)

Pose and Solve Varignon Converse Problems

Science.gov (United States)

Contreras, José N.

2014-01-01

The activity of posing and solving problems can enrich learners' mathematical experiences because it fosters a spirit of inquisitiveness, cultivates their mathematical curiosity, and deepens their views of what it means to do mathematics. To achieve these goals, a mathematical problem needs to be at the appropriate level of difficulty,…

Socio-economic effects of a HYSOL CSP plant located in different countries: An input output analysis

NARCIS (Netherlands)

Corona, B.; López, A.; San Miguel, G.

2016-01-01

The aim of this paper is to estimate the socioeconomic effects associated with the production of electricity by a CSP plant with HYSOL configuration, using Input Output Analysis. These effects have been estimated in terms of production of Goods and Services (G&S), multiplier effect, value added,

Does the central bank directly respond to output and 
inflation uncertainties in Turkey?

Directory of Open Access Journals (Sweden)

Pelin Öge Güney

2016-06-01

Full Text Available This paper investigates the role of inflation and output uncertainties on monetary policy rules in Turkey for the period 2002:01–2014:02. In the literature it is suggested that uncertainty is a key element in monetary policy, hence empirical models of monetary policy should regard to uncertainty. In this study, we estimate a forward-looking monetary reaction function of the Central Bank of the Republic of Turkey (CBRT. In addition to inflation and output gap variables, our reaction function also includes both the inflation and output growth uncertainties. Our results suggest that the Central Bank of the Republic of Turkey (CBRT concerns with mainly price stability and significantly responds to inflation and growth uncertainties.

Nonlinear observer output-feedback MPC treatment scheduling for HIV

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Zurakowski Ryan

2011-05-01

Full Text Available Abstract Background Mathematical models of the immune response to the Human Immunodeficiency Virus demonstrate the potential for dynamic schedules of Highly Active Anti-Retroviral Therapy to enhance Cytotoxic Lymphocyte-mediated control of HIV infection. Methods In previous work we have developed a model predictive control (MPC based method for determining optimal treatment interruption schedules for this purpose. In this paper, we introduce a nonlinear observer for the HIV-immune response system and an integrated output-feedback MPC approach for implementing the treatment interruption scheduling algorithm using the easily available viral load measurements. We use Monte-Carlo approaches to test robustness of the algorithm. Results The nonlinear observer shows robust state tracking while preserving state positivity both for continuous and discrete measurements. The integrated output-feedback MPC algorithm stabilizes the desired steady-state. Monte-Carlo testing shows significant robustness to modeling error, with 90% success rates in stabilizing the desired steady-state with 15% variance from nominal on all model parameters. Conclusions The possibility of enhancing immune responsiveness to HIV through dynamic scheduling of treatment is exciting. Output-feedback Model Predictive Control is uniquely well-suited to solutions of these types of problems. The unique constraints of state positivity and very slow sampling are addressable by using a special-purpose nonlinear state estimator, as described in this paper. This shows the possibility of using output-feedback MPC-based algorithms for this purpose.

Immediate changes in estimated cardiac output and vascular resistance after 60Co exposure in monkeys: implication for performance decrement

International Nuclear Information System (INIS)

Bruner, A.

1977-01-01

Aortic blood flow velocity, blood pressure, and heart rate were recorded in 12 unanesthetized, nonperforming monkeys during exposure to 1000 rad 60 Co at 129--164 rad/min. The first postradiation changes were seen within 3--4 min of the exposure's start and included tachycardia, a transient hypotension secondary to a loss in peripheral resistance, and a brief increase followed by a decrease to subnormal levels in cardiac output. The lowest cardiac output occurred between 10 and 20 min postexposure while blood pressure and peripheral resistance were recovering. It was proposed that the concurrent combination of low cardiac output, low blood pressure, and supranormal peripheral resistance might sufficiently attenuate cerebral perfusion temporarily to account for the transient behavioral decrements often seen during this time. Histamine release was postulated as responsible for this vascular shock syndrome

Enhanced performance CCD output amplifier

Science.gov (United States)

Dunham, Mark E.; Morley, David W.

1996-01-01

A low-noise FET amplifier is connected to amplify output charge from a che coupled device (CCD). The FET has its gate connected to the CCD in common source configuration for receiving the output charge signal from the CCD and output an intermediate signal at a drain of the FET. An intermediate amplifier is connected to the drain of the FET for receiving the intermediate signal and outputting a low-noise signal functionally related to the output charge signal from the CCD. The amplifier is preferably connected as a virtual ground to the FET drain. The inherent shunt capacitance of the FET is selected to be at least equal to the sum of the remaining capacitances.

Parameter Estimation of Damped Compound Pendulum Using Bat Algorithm

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Saad Mohd Sazli

2016-01-01

Full Text Available In this study, the parameter identification of the damped compound pendulum system is proposed using one of the most promising nature inspired algorithms which is Bat Algorithm (BA. The procedure used to achieve the parameter identification of the experimental system consists of input-output data collection, ARX model order selection and parameter estimation using bat algorithm (BA method. PRBS signal is used as an input signal to regulate the motor speed. Whereas, the output signal is taken from position sensor. Both, input and output data is used to estimate the parameter of the autoregressive with exogenous input (ARX model. The performance of the model is validated using mean squares error (MSE between the actual and predicted output responses of the models. Finally, comparative study is conducted between BA and the conventional estimation method (i.e. Least Square. Based on the results obtained, MSE produce from Bat Algorithm (BA is outperformed the Least Square (LS method.

A Channelization-Based DOA Estimation Method for Wideband Signals

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Rui Guo

2016-07-01

Full Text Available In this paper, we propose a novel direction of arrival (DOA estimation method for wideband signals with sensor arrays. The proposed method splits the wideband array output into multiple frequency sub-channels and estimates the signal parameters using a digital channelization receiver. Based on the output sub-channels, a channelization-based incoherent signal subspace method (Channelization-ISM and a channelization-based test of orthogonality of projected subspaces method (Channelization-TOPS are proposed. Channelization-ISM applies narrowband signal subspace methods on each sub-channel independently. Then the arithmetic mean or geometric mean of the estimated DOAs from each sub-channel gives the final result. Channelization-TOPS measures the orthogonality between the signal and the noise subspaces of the output sub-channels to estimate DOAs. The proposed channelization-based method isolates signals in different bandwidths reasonably and improves the output SNR. It outperforms the conventional ISM and TOPS methods on estimation accuracy and dynamic range, especially in real environments. Besides, the parallel processing architecture makes it easy to implement on hardware. A wideband digital array radar (DAR using direct wideband radio frequency (RF digitization is presented. Experiments carried out in a microwave anechoic chamber with the wideband DAR are presented to demonstrate the performance. The results verify the effectiveness of the proposed method.

Input-output linearizing tracking control of induction machine with the included magnetic saturation

DEFF Research Database (Denmark)

Dolinar, Drago; Ljusev, Petar; Stumberger, Gorazd

2003-01-01

The tracking control design of an induction motor, based on input-output linearisation with magnetic saturation included is addressed. The magnetic saturation is represented by a nonlinear magnetising curve for the iron core and is used in the control, the observer of the state variables......, and in the load torque estimator. An input-output linearising control is used to achieve better tracking performances. It is based on the mixed 'stator current - rotor flux linkage' induction motor model with magnetic saturation considered in the stationary reference frame. Experimental results show...... that the proposed input-output linearising tracking control with saturation included behaves considerably better than the one without saturation, and that it introduces smaller position and speed errors, and better motor stiffness on account of the increased computational complexity....

Turbulent Output-Based Anisotropic Adaptation

Science.gov (United States)

Park, Michael A.; Carlson, Jan-Renee

2010-01-01

Controlling discretization error is a remaining challenge for computational fluid dynamics simulation. Grid adaptation is applied to reduce estimated discretization error in drag or pressure integral output functions. To enable application to high O(10(exp 7)) Reynolds number turbulent flows, a hybrid approach is utilized that freezes the near-wall boundary layer grids and adapts the grid away from the no slip boundaries. The hybrid approach is not applicable to problems with under resolved initial boundary layer grids, but is a powerful technique for problems with important off-body anisotropic features. Supersonic nozzle plume, turbulent flat plate, and shock-boundary layer interaction examples are presented with comparisons to experimental measurements of pressure and velocity. Adapted grids are produced that resolve off-body features in locations that are not known a priori.

Categorization of questions posed before and after inquiry-based learning

Directory of Open Access Journals (Sweden)

Sandra Milena García González

2014-07-01

Full Text Available Posing research questions is the central ability of the scientific thought. This article examines the ability of sixth grade children to pose researchable questions before and after a three months’ work on a didactic sequence based on the inquiry school model. According to their purpose, the questions asked by children, after reading a text, were classified into researchable questions -susceptible to be empirically explored-, questions about a cause, and questions on a piece of data. The results show that the amount and the type of questions the students were able to pose during the intervention changed, from most of questions on data or information, to most of researchable questions, subsequently, the importance of designing teaching approaches to foster this ability was proved.

Application of Firefly Algorithm for Parameter Estimation of Damped Compound Pendulum

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Saad Mohd Sazli

2016-01-01

Full Text Available This paper presents an investigation into the parameter estimation of the damped compound pendulum using Firefly algorithm method. In estimating the damped compound pendulum, the system necessarily needs a good model. Therefore, the aim of the work described in this paper is to obtain a dynamic model of the damped compound pendulum. By considering a discrete time form for the system, an autoregressive with exogenous input (ARX model structures was selected. In order to collect input-output data from the experiment, the PRBS signal is used to be input signal to regulate the motor speed. Where, the output signal is taken from position sensor. Firefly algorithm (FA algorithm is used to estimate the model parameters based on model 2nd orders. The model validation was done by comparing the measured output against the predicted output in terms of the closeness of both outputs via mean square error (MSE value. The performance of FA is measured in terms of mean square error (MSE.

Automatic generation of statistical pose and shape models for articulated joints.

Science.gov (United States)

Xin Chen; Graham, Jim; Hutchinson, Charles; Muir, Lindsay

2014-02-01

Statistical analysis of motion patterns of body joints is potentially useful for detecting and quantifying pathologies. However, building a statistical motion model across different subjects remains a challenging task, especially for a complex joint like the wrist. We present a novel framework for simultaneous registration and segmentation of multiple 3-D (CT or MR) volumes of different subjects at various articulated positions. The framework starts with a pose model generated from 3-D volumes captured at different articulated positions of a single subject (template). This initial pose model is used to register the template volume to image volumes from new subjects. During this process, the Grow-Cut algorithm is used in an iterative refinement of the segmentation of the bone along with the pose parameters. As each new subject is registered and segmented, the pose model is updated, improving the accuracy of successive registrations. We applied the algorithm to CT images of the wrist from 25 subjects, each at five different wrist positions and demonstrated that it performed robustly and accurately. More importantly, the resulting segmentations allowed a statistical pose model of the carpal bones to be generated automatically without interaction. The evaluation results show that our proposed framework achieved accurate registration with an average mean target registration error of 0.34 ±0.27 mm. The automatic segmentation results also show high consistency with the ground truth obtained semi-automatically. Furthermore, we demonstrated the capability of the resulting statistical pose and shape models by using them to generate a measurement tool for scaphoid-lunate dissociation diagnosis, which achieved 90% sensitivity and specificity.

Governmentally amplified output volatility

Science.gov (United States)

Funashima, Yoshito

2016-11-01

Predominant government behavior is decomposed by frequency into several periodic components: updating cycles of infrastructure, Kuznets cycles, fiscal policy over business cycles, and election cycles. Little is known, however, about the theoretical impact of such cyclical behavior in public finance on output fluctuations. Based on a standard neoclassical growth model, this study intends to examine the frequency at which public investment cycles are relevant to output fluctuations. We find an inverted U-shaped relationship between output volatility and length of cycle in public investment. This implies that periodic behavior in public investment at a certain frequency range can cause aggravated output resonance. Moreover, we present an empirical analysis to test the theoretical implication, using the U.S. data in the period from 1968 to 2015. The empirical results suggest that such resonance phenomena change from low to high frequency.

Fast Kalman Filtering for Relative Spacecraft Position and Attitude Estimation for the Raven ISS Hosted Payload

Science.gov (United States)

Galante, Joseph M.; Van Eepoel, John; D'Souza, Chris; Patrick, Bryan

2016-01-01

The Raven ISS Hosted Payload will feature several pose measurement sensors on a pan/tilt gimbal which will be used to autonomously track resupply vehicles as they approach and depart the International Space Station. This paper discusses the derivation of a Relative Navigation Filter (RNF) to fuse measurements from the different pose measurement sensors to produce relative position and attitude estimates. The RNF relies on relative translation and orientation kinematics and careful pose sensor modeling to eliminate dependence on orbital position information and associated orbital dynamics models. The filter state is augmented with sensor biases to provide a mechanism for the filter to estimate and mitigate the offset between the measurements from different pose sensors

Efficient Output Solution for Nonlinear Stochastic Optimal Control Problem with Model-Reality Differences

Directory of Open Access Journals (Sweden)

Sie Long Kek

2015-01-01

Full Text Available A computational approach is proposed for solving the discrete time nonlinear stochastic optimal control problem. Our aim is to obtain the optimal output solution of the original optimal control problem through solving the simplified model-based optimal control problem iteratively. In our approach, the adjusted parameters are introduced into the model used such that the differences between the real system and the model used can be computed. Particularly, system optimization and parameter estimation are integrated interactively. On the other hand, the output is measured from the real plant and is fed back into the parameter estimation problem to establish a matching scheme. During the calculation procedure, the iterative solution is updated in order to approximate the true optimal solution of the original optimal control problem despite model-reality differences. For illustration, a wastewater treatment problem is studied and the results show the efficiency of the approach proposed.

Single leg balancing in ballet: effects of shoe conditions and poses.

Science.gov (United States)

Lobo da Costa, Paula H; Azevedo Nora, Fernanda G S; Vieira, Marcus Fraga; Bosch, Kerstin; Rosenbaum, Dieter

2013-03-01

The purpose of this study was to describe the effects of lower limb positioning and shoe conditions on stability levels of selected single leg ballet poses performed in demi-pointe position. Fourteen female non-professional ballet dancers (mean age of 18.4±2.8 years and mean body mass index of 21.5±2.8kg/m(2)) who had practiced ballet for at least seven years, without any musculoskeletal impairment volunteered to participate in this study. A capacitive pressure platform allowed for the assessment of center of pressure variables related to the execution of three single leg ballet poses in demi pointé position: attitude devant, attitude derriére, and attitude a la second. Peak pressures, contact areas, COP oscillation areas, anterior-posterior and medio-lateral COP oscillations and velocities were compared between two shoe conditions (barefoot versus slippers) and among the different poses. Barefoot performances produced more stable poses with significantly higher plantar contact areas, smaller COP oscillation areas and smaller anterior-posterior COP oscillations. COP oscillation areas, anterior-posterior COP oscillations and medio-lateral COP velocities indicated that attitude a la second is the least challenging and attitude derriére the most challenging pose. Copyright © 2012 Elsevier B.V. All rights reserved.

Determination of Krebs cycle metabolic carbon exchange in vivo and its use to estimate the individual contributions of gluconeogenesis and glycogenolysis to overall glucose output in man

International Nuclear Information System (INIS)

Consoli, A.; Kennedy, F.; Miles, J.; Gerich, J.

1987-01-01

Current isotopic approaches underestimate gluconeogenesis in vivo because of Krebs cycle carbon exchange and the inability to measure intramitochondrial precursor specific activity. We therefore applied a new isotopic approach that theoretically overcomes these limitations and permits quantification of Krebs cycle carbon exchange and the individual contributions of gluconeogenesis and glycogenolysis to overall glucose outputex. [6-3H]Glucose was infused to measure overall glucose output; [2-14C]acetate was infused to trace phosphoenolpyruvate gluconeogenesis and to calculate Krebs cycle carbon exchange as proposed by Katz. Plasma [14C]3-OH-butyrate specific activity was used to estimate intramitochondrial acetyl coenzyme A (CoA) specific activity, and finally the ratio between plasma glucose 14C-specific activity and the calculated intracellular phosphoenolpyruvate 14C-specific activity was used to determine the relative contributions of gluconeogenesis and glycogenolysis to overall glucose output. Using this approach, acetyl CoA was found to enter the Krebs cycle at twice (postabsorptive subjects) and three times (2 1/2-d fasted subjects) the rate of pyruvate, respectively. Gluconeogenesis in postabsorptive subjects (3.36 +/- 0.20 mumol/kg per min) accounted for 28 +/- 2% of overall glucose output and increased twofold in subjects fasted for 2 1/2-d (P less than 0.01), accounting for greater than 97% of overall glucose output. Glycogenolysis in postabsorptive subjects averaged 8.96 +/- 0.40 mumol/kg per min and decreased to 0.34 +/- 0.08 mumol/kg per min (P less than 0.01) after a 2 1/2-d fast. Since these results agree well with previously reported values for gluconeogenesis and glycogenolysis based on determinations of splanchnic substrate balance and glycogen content of serial liver biopsies

Retrieval of LAI and leaf chlorophyll content from remote sensing data by agronomy mechanism knowledge to solve the ill-posed inverse problem

Science.gov (United States)

Li, Zhenhai; Nie, Chenwei; Yang, Guijun; Xu, Xingang; Jin, Xiuliang; Gu, Xiaohe

2014-10-01

Leaf area index (LAI) and LCC, as the two most important crop growth variables, are major considerations in management decisions, agricultural planning and policy making. Estimation of canopy biophysical variables from remote sensing data was investigated using a radiative transfer model. However, the ill-posed problem is unavoidable for the unique solution of the inverse problem and the uncertainty of measurements and model assumptions. This study focused on the use of agronomy mechanism knowledge to restrict and remove the ill-posed inversion results. For this purpose, the inversion results obtained using the PROSAIL model alone (NAMK) and linked with agronomic mechanism knowledge (AMK) were compared. The results showed that AMK did not significantly improve the accuracy of LAI inversion. LAI was estimated with high accuracy, and there was no significant improvement after considering AMK. The validation results of the determination coefficient (R2) and the corresponding root mean square error (RMSE) between measured LAI and estimated LAI were 0.635 and 1.022 for NAMK, and 0.637 and 0.999 for AMK, respectively. LCC estimation was significantly improved with agronomy mechanism knowledge; the R2 and RMSE values were 0.377 and 14.495 μg cm-2 for NAMK, and 0.503 and 10.661 μg cm-2 for AMK, respectively. Results of the comparison demonstrated the need for agronomy mechanism knowledge in radiative transfer model inversion.

Application of Shape Similarity in Pose Selection and Virtual Screening in CSARdock2014 Exercise.

Science.gov (United States)

Kumar, Ashutosh; Zhang, Kam Y J

2016-06-27

To evaluate the applicability of shape similarity in docking-based pose selection and virtual screening, we participated in the CSARdock2014 benchmark exercise for identifying the correct docking pose of inhibitors targeting factor XA, spleen tyrosine kinase, and tRNA methyltransferase. This exercise provides a valuable opportunity for researchers to test their docking programs, methods, and protocols in a blind testing environment. In the CSARdock2014 benchmark exercise, we have implemented an approach that uses ligand 3D shape similarity to facilitate docking-based pose selection and virtual screening. We showed here that ligand 3D shape similarity between bound poses could be used to identify the native-like pose from an ensemble of docking-generated poses. Our method correctly identified the native pose as the top-ranking pose for 73% of test cases in a blind testing environment. Moreover, the pose selection results also revealed an excellent correlation between ligand 3D shape similarity scores and RMSD to X-ray crystal structure ligand. In the virtual screening exercise, the average RMSD for our pose prediction was found to be 1.02 Å, and it was one of the top performances achieved in CSARdock2014 benchmark exercise. Furthermore, the inclusion of shape similarity improved virtual screening performance of docking-based scoring and ranking. The coefficient of determination (r(2)) between experimental activities and docking scores for 276 spleen tyrosine kinase inhibitors was found to be 0.365 but reached 0.614 when the ligand 3D shape similarity was included.

The Value of Risk : Measuring the Service Output of U.S. Commercial Banks

NARCIS (Netherlands)

Basu, Susanto; Inklaar, Robert; Wang, J. Christina

2008-01-01

Rather than charging direct fees, banks often charge implicitly for their services via interest spreads. As a result, much of bank output has to be estimated indirectly. In contrast to current statistical practice, dynamic optimizing models of banks argue that compensation for bearing systematic

Dynamic Output Feedback Based Active Decentralized Fault-Tolerant Control for Reconfigurable Manipulator with Concurrent Failures

Directory of Open Access Journals (Sweden)

Yuanchun Li

2015-01-01

Full Text Available The goal of this paper is to describe an active decentralized fault-tolerant control (ADFTC strategy based on dynamic output feedback for reconfigurable manipulators with concurrent actuator and sensor failures. Consider each joint module of the reconfigurable manipulator as a subsystem, and treat the fault as the unknown input of the subsystem. Firstly, by virtue of linear matrix inequality (LMI technique, the decentralized proportional-integral observer (DPIO is designed to estimate and compensate the sensor fault online; hereafter, the compensated system model could be derived. Then, the actuator fault is estimated similarly by another DPIO using LMI as well, and the sufficient condition of the existence of H∞ fault-tolerant controller in the dynamic output feedback is presented for the compensated system model. Furthermore, the dynamic output feedback controller is presented based on the estimation of actuator fault to realize active fault-tolerant control. Finally, two 3-DOF reconfigurable manipulators with different configurations are employed to verify the effectiveness of the proposed scheme in simulation. The main advantages of the proposed scheme lie in that it can handle the concurrent faults act on the actuator and sensor on the same joint module, as well as there is no requirement of fault detection and isolation process; moreover, it is more feasible to the modularity of the reconfigurable manipulator.

Output Feedback-Based Boundary Control of Uncertain Coupled Semilinear Parabolic PDE Using Neurodynamic Programming.

Science.gov (United States)

Talaei, Behzad; Jagannathan, Sarangapani; Singler, John

2018-04-01

In this paper, neurodynamic programming-based output feedback boundary control of distributed parameter systems governed by uncertain coupled semilinear parabolic partial differential equations (PDEs) under Neumann or Dirichlet boundary control conditions is introduced. First, Hamilton-Jacobi-Bellman (HJB) equation is formulated in the original PDE domain and the optimal control policy is derived using the value functional as the solution of the HJB equation. Subsequently, a novel observer is developed to estimate the system states given the uncertain nonlinearity in PDE dynamics and measured outputs. Consequently, the suboptimal boundary control policy is obtained by forward-in-time estimation of the value functional using a neural network (NN)-based online approximator and estimated state vector obtained from the NN observer. Novel adaptive tuning laws in continuous time are proposed for learning the value functional online to satisfy the HJB equation along system trajectories while ensuring the closed-loop stability. Local uniformly ultimate boundedness of the closed-loop system is verified by using Lyapunov theory. The performance of the proposed controller is verified via simulation on an unstable coupled diffusion reaction process.

Output variability caused by random seeds in a multi-agent transport simulation model

DEFF Research Database (Denmark)

Paulsen, Mads; Rasmussen, Thomas Kjær; Nielsen, Otto Anker

2018-01-01

Dynamic transport simulators are intended to support decision makers in transport-related issues, and as such it is valuable that the random variability of their outputs is as small as possible. In this study we analyse the output variability caused by random seeds of a multi-agent transport...... simulator (MATSim) when applied to a case study of Santiago de Chile. Results based on 100 different random seeds shows that the relative accuracies of estimated link loads tend to increase with link load, but that relative errors of up to 10 % do occur even for links with large volumes. Although...

Energy Output Estimation for a Small Wind Turbine Positioned on a Rooftop in the Urban Environment with and without a Duct

DEFF Research Database (Denmark)

Beller, Christina

, the free standing turbines had an energy potential of 300kWh/m2/a for the horizontal axis wind turbine (HAWT) and for the vertical axis wind turbine (VAWT) 180kWh/m2/a. For the ducted turbines an energy output of 180kWh/m2/a was found for the HAWT configuration, while the VAWT configuration reached......Nowadays, wind turbines in general, but also urban wind turbines attained acceptance to a certain extend. Conceptual designs and some examples in reality exist, where small-scale wind turbines have been implemented close to buildings or even integrated in the building structure. This work is aiming...... to estimate how much energy a wind turbine could produce in the built environment, depending on its integration and configuration. On the basis of measurements taken on the rooftop of H.C. Ørsted Institut in Copenhagen, which is located in an urban area, a comparison of fictive free standing turbines...

Enhancing students’ mathematical problem posing skill through writing in performance tasks strategy

Science.gov (United States)

Kadir; Adelina, R.; Fatma, M.

2018-01-01

Many researchers have studied the Writing in Performance Task (WiPT) strategy in learning, but only a few paid attention on its relation to the problem-posing skill in mathematics. The problem-posing skill in mathematics covers problem reformulation, reconstruction, and imitation. The purpose of the present study was to examine the effect of WiPT strategy on students’ mathematical problem-posing skill. The research was conducted at a Public Junior Secondary School in Tangerang Selatan. It used a quasi-experimental method with randomized control group post-test. The samples were 64 students consists of 32 students of the experiment group and 32 students of the control. A cluster random sampling technique was used for sampling. The research data were obtained by testing. The research shows that the problem-posing skill of students taught by WiPT strategy is higher than students taught by a conventional strategy. The research concludes that the WiPT strategy is more effective in enhancing the students’ mathematical problem-posing skill compared to the conventional strategy.

An Improved Mathematical Model for Computing Power Output of Solar Photovoltaic Modules

Directory of Open Access Journals (Sweden)

Abdul Qayoom Jakhrani

2014-01-01

Full Text Available It is difficult to determine the input parameters values for equivalent circuit models of photovoltaic modules through analytical methods. Thus, the previous researchers preferred to use numerical methods. Since, the numerical methods are time consuming and need long term time series data which is not available in most developing countries, an improved mathematical model was formulated by combination of analytical and numerical methods to overcome the limitations of existing methods. The values of required model input parameters were computed analytically. The expression for output current of photovoltaic module was determined explicitly by Lambert W function and voltage was determined numerically by Newton-Raphson method. Moreover, the algebraic equations were derived for the shape factor which involves the ideality factor and the series resistance of a single diode photovoltaic module power output model. The formulated model results were validated with rated power output of a photovoltaic module provided by manufacturers using local meteorological data, which gave ±2% error. It was found that the proposed model is more practical in terms of precise estimations of photovoltaic module power output for any required location and number of variables used.

The value of risk : measuring the service output of U.S. commercial banks

NARCIS (Netherlands)

Basu, Susanto; Inklaar, Robert; Wang, J. Christina

Banks often charge implicitly for their services via interest spreads, instead of explicit fees. Much of bank output thus has to be estimated indirectly. In contrast to current statistical practice, dynamic optimizing models of banks argue that compensation for bearing systematic risk is not part of

Characteristics of crosstalk in the reproduced output of a newly developed multi-channel MR head

International Nuclear Information System (INIS)

Machida, K.; Hayashi, N.; Yoneda, Y.; Numazawa, J.; Kohro, M.; Tanabe, T.

2001-01-01

We prepared the multi-channel magnetoresistive head with a simple structural design and it has the advantages of high-density recording and ultra-high transfer rate. Characteristics of crosstalk in the reproduced output of our head have been estimated by a micromagnetic calculation using the Landau-Lifshitz-Gilbert (LLG) equation, while the specimen head was fabricated and evaluated. As a result, by applying a magnetic field of 40 Oe only between adjacent channels, the crosstalk was much decreased without reducing the reproduced output

Optical neural network system for pose determination of spinning satellites

Science.gov (United States)

Lee, Andrew; Casasent, David

1990-01-01

An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.

Econometric model of the petroleum industry. [Determining crude supply and outputs/prices of refinery products

Energy Technology Data Exchange (ETDEWEB)

Rice, P [Oak Ridge National Lab., TN; Smith, V K

1977-11-01

This paper describes a forty-two nonlinear equation model of the U.S. petroleum industry estimated over the period 1946 to 1973. The model specifies refinery outputs and prices as being simultaneously determined by market forces while the domestic output of crude oil is determined in a block-recursive segment of the model. The simultaneous behavioral equations are estimated with nonlinear two-stage least-squares adjusted to reflect the implications of autocorrelation for those equations where it appears to be a problem. A multi-period sample simulation, together with forecasts for 1974 and 1975 are used to evaluate the model's performance. Finally, it is used to forecast to 1985 under two scenarios and compared with the Federal Energy Administration's forecast for the same period. 2 figures, 8 tables, 38 references.

Teachers Implementing Mathematical Problem Posing in the Classroom: Challenges and Strategies

Science.gov (United States)

Leung, Shuk-kwan S.

2013-01-01

This paper reports a study about how a teacher educator shared knowledge with teachers when they worked together to implement mathematical problem posing (MPP) in the classroom. It includes feasible methods for getting practitioners to use research-based tasks aligned to the curriculum in order to encourage children to pose mathematical problems.…

Estimation of Valve Stiction Using Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

S. Sivagamasundari

2011-06-01

Full Text Available This paper presents a procedure for quantifying valve stiction in control loops based on particle swarm optimization. Measurements of the Process Variable (PV and Controller Output (OP are used to estimate the parameters of a Hammerstein system, consisting of connection of a non linear control valve stiction model and a linear process model. The parameters of the Hammerstein model are estimated using particle swarm optimization, from the input-output data by minimizing the error between the true model output and the identified model output. Using particle swarm optimization, Hammerstein models with known nonlinear structure and unknown parameters can be identified. A cost-effective optimization technique is adopted to find the best valve stiction models representing a more realistic valve behavior in the oscillating loop. Simulation and practical laboratory control system results are included, which demonstrates the effectiveness and robustness of the identification scheme.

Geophysical excitation of LOD/UT1 estimated from the output of the global circulation models of the atmosphere - ERA-40 reanalysis and of the ocean - OMCT

Science.gov (United States)

Korbacz, A.; Brzeziński, A.; Thomas, M.

2008-04-01

We use new estimates of the global atmospheric and oceanic angular momenta (AAM, OAM) to study the influence on LOD/UT1. The AAM series was calculated from the output fields of the atmospheric general circulation model ERA-40 reanalysis. The OAM series is an outcome of global ocean model OMCT simulation driven by global fields of the atmospheric parameters from the ERA- 40 reanalysis. The excitation data cover the period between 1963 and 2001. Our calculations concern atmospheric and oceanic effects in LOD/UT1 over the periods between 20 days and decades. Results are compared to those derived from the alternative AAM/OAM data sets.

Model output: fact or artefact?

Science.gov (United States)

Melsen, Lieke

2015-04-01

As a third-year PhD-student, I relatively recently entered the wonderful world of scientific Hydrology. A science that has many pillars that directly impact society, for example with the prediction of hydrological extremes (both floods and drought), climate change, applications in agriculture, nature conservation, drinking water supply, etcetera. Despite its demonstrable societal relevance, hydrology is often seen as a science between two stools. Like Klemeš (1986) stated: "By their academic background, hydrologists are foresters, geographers, electrical engineers, geologists, system analysts, physicists, mathematicians, botanists, and most often civil engineers." Sometimes it seems that the engineering genes are still present in current hydrological sciences, and this results in pragmatic rather than scientific approaches for some of the current problems and challenges we have in hydrology. Here, I refer to the uncertainty in hydrological modelling that is often neglected. For over thirty years, uncertainty in hydrological models has been extensively discussed and studied. But it is not difficult to find peer-reviewed articles in which it is implicitly assumed that model simulations represent the truth rather than a conceptualization of reality. For instance in trend studies, where data is extrapolated 100 years ahead. Of course one can use different forcing datasets to estimate the uncertainty of the input data, but how to prevent that the output is not a model artefact, caused by the model structure? Or how about impact studies, e.g. of a dam impacting river flow. Measurements are often available for the period after dam construction, so models are used to simulate river flow before dam construction. Both are compared in order to qualify the effect of the dam. But on what basis can we tell that the model tells us the truth? Model validation is common nowadays, but validation only (comparing observations with model output) is not sufficient to assume that a

Consistent Estimation of Pricing Kernels from Noisy Price Data

OpenAIRE

Vladislav Kargin

2003-01-01

If pricing kernels are assumed non-negative then the inverse problem of finding the pricing kernel is well-posed. The constrained least squares method provides a consistent estimate of the pricing kernel. When the data are limited, a new method is suggested: relaxed maximization of the relative entropy. This estimator is also consistent. Keywords: $\\epsilon$-entropy, non-parametric estimation, pricing kernel, inverse problems.

Predicting Power Output of Upper Body using the OMNI-RES Scale

Directory of Open Access Journals (Sweden)

Bautista Iker J.

2014-12-01

Full Text Available The main aim of this study was to determine the optimal training zone for maximum power output. This was to be achieved through estimating mean bar velocity of the concentric phase of a bench press using a prediction equation. The values for the prediction equation would be obtained using OMNI-RES scale values of different loads of the bench press exercise. Sixty males ( voluntarily participated in the study and were tested using an incremental protocol on a Smith machine to determine one repetition maximum (1RM in the bench press exercise. A linear regression analysis produced a strong correlation (r = -0.94 between rating of perceived exertion (RPE and mean bar velocity (Velmean. The Pearson correlation analysis between real power output (PotReal and estimated power (PotEst showed a strong correlation coefficient of r = 0.77, significant at a level of p = 0.01. Therefore, the OMNI-RES scale can be used to predict Velmean in the bench press exercise to control the intensity of the exercise. The positive relationship between PotReal and PotEst allowed for the identification of a maximum power-training zone.

Energy and output dynamics in Bangladesh

International Nuclear Information System (INIS)

Paul, Biru Paksha; Uddin, Gazi Salah

2011-01-01

The relationship between energy consumption and output is still ambiguous in the existing literature. The economy of Bangladesh, having spectacular output growth and rising energy demand as well as energy efficiency in recent decades, can be an ideal case for examining energy-output dynamics. We find that while fluctuations in energy consumption do not affect output fluctuations, movements in output inversely affect movements in energy use. The results of Granger causality tests in this respect are consistent with those of innovative accounting that includes variance decompositions and impulse responses. Autoregressive distributed lag models also suggest a role of output in Bangladesh's energy use. Hence, the findings of this study have policy implications for other developing nations where measures for energy conservation and efficiency can be relevant in policymaking.

Reactor core performance estimating device

International Nuclear Information System (INIS)

Tanabe, Akira; Yamamoto, Toru; Shinpuku, Kimihiro; Chuzen, Takuji; Nishide, Fusayo.

1995-01-01

The present invention can autonomously simplify a neural net model thereby enabling to conveniently estimate various amounts which represents reactor core performances by a simple calculation in a short period of time. Namely, a reactor core performance estimation device comprises a nerve circuit net which divides the reactor core into a large number of spacial regions, and receives various physical amounts for each region as input signals for input nerve cells and outputs estimation values of each amount representing the reactor core performances as output signals of output nerve cells. In this case, the nerve circuit net (1) has a structure of extended multi-layered model having direct coupling from an upper stream layer to each of downstream layers, (2) has a forgetting constant q in a corrected equation for a joined load value ω using an inverse error propagation method, (3) learns various amounts representing reactor core performances determined using the physical models as teacher signals, (4) determines the joined load value ω decreased as '0' when it is to less than a predetermined value upon learning described above, and (5) eliminates elements of the nerve circuit net having all of the joined load value decreased to 0. As a result, the neural net model comprises an autonomously simplifying means. (I.S.)

Teaching Human Poses Interactively to a Social Robot

Science.gov (United States)

Gonzalez-Pacheco, Victor; Malfaz, Maria; Fernandez, Fernando; Salichs, Miguel A.

2013-01-01

The main activity of social robots is to interact with people. In order to do that, the robot must be able to understand what the user is saying or doing. Typically, this capability consists of pre-programmed behaviors or is acquired through controlled learning processes, which are executed before the social interaction begins. This paper presents a software architecture that enables a robot to learn poses in a similar way as people do. That is, hearing its teacher's explanations and acquiring new knowledge in real time. The architecture leans on two main components: an RGB-D (Red-, Green-, Blue- Depth) -based visual system, which gathers the user examples, and an Automatic Speech Recognition (ASR) system, which processes the speech describing those examples. The robot is able to naturally learn the poses the teacher is showing to it by maintaining a natural interaction with the teacher. We evaluate our system with 24 users who teach the robot a predetermined set of poses. The experimental results show that, with a few training examples, the system reaches high accuracy and robustness. This method shows how to combine data from the visual and auditory systems for the acquisition of new knowledge in a natural manner. Such a natural way of training enables robots to learn from users, even if they are not experts in robotics. PMID:24048336

Teaching Human Poses Interactively to a Social Robot

Directory of Open Access Journals (Sweden)

Miguel A. Salichs

2013-09-01

Full Text Available The main activity of social robots is to interact with people. In order to do that, the robot must be able to understand what the user is saying or doing. Typically, this capability consists of pre-programmed behaviors or is acquired through controlled learning processes, which are executed before the social interaction begins. This paper presents a software architecture that enables a robot to learn poses in a similar way as people do. That is, hearing its teacher’s explanations and acquiring new knowledge in real time. The architecture leans on two main components: an RGB-D (Red-, Green-, Blue- Depth -based visual system, which gathers the user examples, and an Automatic Speech Recognition (ASR system, which processes the speech describing those examples. The robot is able to naturally learn the poses the teacher is showing to it by maintaining a natural interaction with the teacher. We evaluate our system with 24 users who teach the robot a predetermined set of poses. The experimental results show that, with a few training examples, the system reaches high accuracy and robustness. This method shows how to combine data from the visual and auditory systems for the acquisition of new knowledge in a natural manner. Such a natural way of training enables robots to learn from users, even if they are not experts in robotics.

An Investigation of Eighth Grade Students' Problem Posing Skills (Turkey Sample)

Science.gov (United States)

Arikan, Elif Esra; Ünal, Hasan

2015-01-01

To pose a problem refers to the creative activity for mathematics education. The purpose of the study was to explore the eighth grade students' problem posing ability. Three learning domains such as requiring four operations, fractions and geometry were chosen for this reason. There were two classes which were coded as class A and class B. Class A…

Analyzing Pre-Service Primary Teachers' Fraction Knowledge Structures through Problem Posing

Science.gov (United States)

Kilic, Cigdem

2015-01-01

In this study it was aimed to determine pre-service primary teachers' knowledge structures of fraction through problem posing activities. A total of 90 pre-service primary teachers participated in this study. A problem posing test consisting of two questions was used and the participants were asked to generate as many as problems based on the…

Using physics-based pose predictions and free energy perturbation calculations to predict binding poses and relative binding affinities for FXR ligands in the D3R Grand Challenge 2

Science.gov (United States)

Athanasiou, Christina; Vasilakaki, Sofia; Dellis, Dimitris; Cournia, Zoe

2018-01-01

Computer-aided drug design has become an integral part of drug discovery and development in the pharmaceutical and biotechnology industry, and is nowadays extensively used in the lead identification and lead optimization phases. The drug design data resource (D3R) organizes challenges against blinded experimental data to prospectively test computational methodologies as an opportunity for improved methods and algorithms to emerge. We participated in Grand Challenge 2 to predict the crystallographic poses of 36 Farnesoid X Receptor (FXR)-bound ligands and the relative binding affinities for two designated subsets of 18 and 15 FXR-bound ligands. Here, we present our methodology for pose and affinity predictions and its evaluation after the release of the experimental data. For predicting the crystallographic poses, we used docking and physics-based pose prediction methods guided by the binding poses of native ligands. For FXR ligands with known chemotypes in the PDB, we accurately predicted their binding modes, while for those with unknown chemotypes the predictions were more challenging. Our group ranked #1st (based on the median RMSD) out of 46 groups, which submitted complete entries for the binding pose prediction challenge. For the relative binding affinity prediction challenge, we performed free energy perturbation (FEP) calculations coupled with molecular dynamics (MD) simulations. FEP/MD calculations displayed a high success rate in identifying compounds with better or worse binding affinity than the reference (parent) compound. Our studies suggest that when ligands with chemical precedent are available in the literature, binding pose predictions using docking and physics-based methods are reliable; however, predictions are challenging for ligands with completely unknown chemotypes. We also show that FEP/MD calculations hold predictive value and can nowadays be used in a high throughput mode in a lead optimization project provided that crystal structures of

Improving attitudes toward mathematics learning with problem posing in class VIII

Science.gov (United States)

Vionita, Alfha; Purboningsih, Dyah

2017-08-01

This research is classroom action research which is collaborated to improve student's behavior toward math and mathematics learning at class VIII by using problem posing approach. The subject of research is all of students grade VIIIA which consist of 32 students. This research has been held on two period, first period is about 3 times meeting, and second period is about 4 times meeting. The instrument of this research is implementation of learning observation's guidance by using problem posing approach. Cycle test has been used to measure cognitive competence, and questionnaire to measure the students' behavior in mathematics learning process. The result of research shows the students' behavior has been improving after using problem posing approach. It is showed by the behavior's criteria of students that has increasing result from the average in first period to high in second period. Furthermore, the percentage of test result is also improve from 68,75% in first period to 78,13% in second period. On the other hand, the implementation of learning observation by using problem posing approach has also improving and it is showed by the average percentage of teacher's achievement in first period is 89,2% and student's achievement 85,8%. These results get increase in second period for both teacher and students' achievement which are 94,4% and 91,11%. As a result, students' behavior toward math learning process in class VIII has been improving by using problem posing approach.

Output and substitution elasticities of energy and implications for renewable energy expansion in the ECOWAS region

International Nuclear Information System (INIS)

Wesseh, Presley K.; Lin, Boqiang

2016-01-01

This study estimates output and substitution elasticities of renewable energy and nonrenewable energy for the Economic Community of West African States (ECOWAS) and discusses implications for expanding the former. The results show that nonrenewable energy promises greater benefits for ECOWAS economic transition, with output elasticities averaging between 0.052–0.579 and −0.055 to 0.223 for nonrenewable energy and renewable energy respectively. Overall estimated technological progress is low (−0.5% to 2.6%); the bulk coming from input efficiency. Substitution elasticities (0.02–0.94) suggest potential for switching towards renewable energy. Notwithstanding, scale, economics and sitting problems inherent in renewable power generation challenge the opportunities for energy substitution. A sustainable policy solution, therefore, appears to be one favoring scaled and efficient electricity generation from fossil energy in the short-run with a gradual switch towards renewable power in the long-run. In general, the applied model provides insights that energy efficiency enhances sustainable growth by propelling technological advancement especially when technical change is scale-biased and factor-augmenting. The study also provides insights that impacts of exogenous shocks to inputs are temporary, and hence, do not jeopardize efforts aimed at scaling output through increased and efficient use of labor, capital and energy; especially nonrenewable energy. - Highlights: • Output and substitution elasticities of energy are estimated for the ECOWAS region. • Nonrenewable energy promises greater opportunities for economic growth. • Technical progress is low and driven mainly by the efficiency of inputs. • Energy efficiency drives technological innovation. • Potential of switching towards renewable energy is high but suffers feasibility gaps.

Cardiac output measurement

Directory of Open Access Journals (Sweden)

Andreja Möller Petrun

2014-02-01

Full Text Available In recent years, developments in the measuring of cardiac output and other haemodynamic variables are focused on the so-called minimally invasive methods. The aim of these methods is to simplify the management of high-risk and haemodynamically unstable patients. Due to the need of invasive approach and the possibility of serious complications the use of pulmonary artery catheter has decreased. This article describes the methods for measuring cardiac output, which are based on volume measurement (Fick method, indicator dilution method, pulse wave analysis, Doppler effect, and electrical bioimpedance.

The Extended-Window Channel Estimator for Iterative Channel-and-Symbol Estimation

Directory of Open Access Journals (Sweden)

Barry John R

2005-01-01

Full Text Available The application of the expectation-maximization (EM algorithm to channel estimation results in a well-known iterative channel-and-symbol estimator (ICSE. The EM-ICSE iterates between a symbol estimator based on the forward-backward recursion (BCJR equalizer and a channel estimator, and may provide approximate maximum-likelihood blind or semiblind channel estimates. Nevertheless, the EM-ICSE has high complexity, and it is prone to misconvergence. In this paper, we propose the extended-window (EW estimator, a novel channel estimator for ICSE that can be used with any soft-output symbol estimator. Therefore, the symbol estimator may be chosen according to performance or complexity specifications. We show that the EW-ICSE, an ICSE that uses the EW estimator and the BCJR equalizer, is less complex and less susceptible to misconvergence than the EM-ICSE. Simulation results reveal that the EW-ICSE may converge faster than the EM-ICSE.

Exploring the relationship between agricultural electricity consumption and output: New evidence from Turkish regional data

International Nuclear Information System (INIS)

Dogan, Eyup; Sebri, Maamar; Turkekul, Berna

2016-01-01

This study investigates the relationship between agricultural electricity consumption and agricultural output for a panel of 12 regions of Turkey for the period 1995–2013. In order to reveal the possible heterogeneity between regions, empirical analyses are conducted for the whole panel data and two sub-groups within the panel data; namely, coastal regions and non-coastal regions. The results from several panel unit root tests indicate that electricity consumption and output are stationary process at their levels for overall panel and the two specific groups. By using the OLS with regional fixed effects, this study finds that coefficient estimate of electricity consumption on output is statistically significant and positive for overall regions, coastal regions and non-coastal regions. In addition, the results from the Dumitrescu-Hurlin Granger causality test show that there is unidirectional causality running from agricultural output to electricity consumption for non-coastal regions, and there is bidirectional causality between agricultural electricity consumption and output for overall panel and coastal regions. Findings and policy implications are further discussed. - Highlights: •This study uses the recently developed Dumitrescu-Hurlin Granger causality test. •There is unidirectional causality running from agricultural output to electricity consumption for non-coastal regions. •Bidirectional causality runs between the analyzed variables for coastal regions. •Electricity consumption increases agricultural output.

Cloud computing approaches for prediction of ligand binding poses and pathways.

Science.gov (United States)

Lawrenz, Morgan; Shukla, Diwakar; Pande, Vijay S

2015-01-22

We describe an innovative protocol for ab initio prediction of ligand crystallographic binding poses and highly effective analysis of large datasets generated for protein-ligand dynamics. We include a procedure for setup and performance of distributed molecular dynamics simulations on cloud computing architectures, a model for efficient analysis of simulation data, and a metric for evaluation of model convergence. We give accurate binding pose predictions for five ligands ranging in affinity from 7 nM to > 200 μM for the immunophilin protein FKBP12, for expedited results in cases where experimental structures are difficult to produce. Our approach goes beyond single, low energy ligand poses to give quantitative kinetic information that can inform protein engineering and ligand design.

Yoga Poses Increase Subjective Energy and State Self-Esteem in Comparison to ‘Power Poses’

Directory of Open Access Journals (Sweden)

Agnieszka Golec de Zavala

2017-05-01

Full Text Available Research on beneficial consequences of yoga focuses on the effects of yogic breathing and meditation. Less is known about the psychological effects of performing yoga postures. The present study investigated the effects of yoga poses on subjective sense of energy and self-esteem. The effects of yoga postures were compared to the effects of ‘power poses,’ which arguably increase the sense of power and self-confidence due to their association with interpersonal dominance (Carney et al., 2010. The study tested the novel prediction that yoga poses, which are not associated with interpersonal dominance but increase bodily energy, would increase the subjective feeling of energy and therefore increase self-esteem compared to ‘high power’ and ‘low power’ poses. A two factorial, between participants design was employed. Participants performed either two standing yoga poses with open front of the body (n = 19, two standing yoga poses with covered front of the body (n = 22, two expansive, high power poses (n = 21, or two constrictive, low power poses (n = 20 for 1-min each. The results showed that yoga poses in comparison to ‘power poses’ increased self-esteem. This effect was mediated by an increased subjective sense of energy and was observed when baseline trait self-esteem was controlled for. These results suggest that the effects of performing open, expansive body postures may be driven by processes other than the poses’ association with interpersonal power and dominance. This study demonstrates that positive effects of yoga practice can occur after performing yoga poses for only 2 min.

Probabilistic Output Analysis by Program Manipulation

DEFF Research Database (Denmark)

Rosendahl, Mads; Kirkeby, Maja Hanne

2015-01-01

The aim of a probabilistic output analysis is to derive a probability distribution of possible output values for a program from a probability distribution of its input. We present a method for performing static output analysis, based on program transformation techniques. It generates a probability...

Estimation of wave directional spreading in shallow water

Digital Repository Service at National Institute of Oceanography (India)

SanilKumar, V.; Deo, M.C.; Anand, N.M.; Chandramohan, P.

loads on offshore structures, long- term estimation of waves and estimation of sediment transport. According to the principle of superposition of linear waves, the sea state is com- posed of a large number of individual wave components, each having a..., who were involved in the data collection programme. NIO Contribution number 2569. References Benoit, M., 1992. Practical comparative performance survey of methods used for estimating directional wave spectra from heave–pitch–roll data. Proceedings...

Fluctuations of the SNR at the output of the MVDR with Regularized Tyler Estimators

KAUST Repository

Elkhalil, Khalil; Kammoun, Abla; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

2016-01-01

case in which the receiver employs the regularized Tyler estimator in order to estimate the covariance matrix of the interference-plus-noise process using n observations of size N×1N×1. The choice for the regularized Tylor estimator (RTE) is motivated

Inverter communications using output signal

Science.gov (United States)

Chapman, Patrick L.

2017-02-07

Technologies for communicating information from an inverter configured for the conversion of direct current (DC) power generated from an alternative source to alternating current (AC) power are disclosed. The technologies include determining information to be transmitted from the inverter over a power line cable connected to the inverter and controlling the operation of an output converter of the inverter as a function of the information to be transmitted to cause the output converter to generate an output waveform having the information modulated thereon.

Performance of a procedure for yield estimation in fruit orchards

DEFF Research Database (Denmark)

Aravena Zamora, Felipe; Potin, Camila; Wulfsohn, Dvora-Laio

Early estimation of expected fruit tree yield is important for the market planning and for growers and exporters to plan for labour and boxes. Large variations in tree yield may be found, posing a challenge for accurate yield estimation. We evaluated a multilevel systematic sampling procedure...

Compairing Picture Exchange and Voice Output Communication Aids in Young Children with Autism

Science.gov (United States)

Lorah, Elizabeth R.

2012-01-01

The Center for Disease Control estimates that one in 88 births result in a diagnosis of autism (CDC, 2012). Of those individuals diagnosed with autism approximately 25-61% fail to develop vocal output capabilities (Weitxz, Dexter, & Moore, 1997). The use of Augmentative and Alternative Communication (AAC) systems, such as Picture Exchange (PE)…

Integration of TMVA Output into Jupyter notebooks

CERN Document Server

Saliji, Albulena

2016-01-01

The purpose of this report is to describe the work that I have been doing during these past eight weeks as a Summer Student at CERN. The task which was assigned to me had to do with the integration of TMVA Output into Jupyter notebooks. In order to integrate the TMVA Output into the Jupyter notebook, first, improvement of the TMVA Output in the terminal was required. Once the output was improved, it needed to be transformed into HTML output and at the end it would be possible to integrate that output into the Jupyter notebook.

Blind Deconvolution for Distributed Parameter Systems with Unbounded Input and Output and Determining Blood Alcohol Concentration from Transdermal Biosensor Data.

Science.gov (United States)

Rosen, I G; Luczak, Susan E; Weiss, Jordan

2014-03-15

We develop a blind deconvolution scheme for input-output systems described by distributed parameter systems with boundary input and output. An abstract functional analytic theory based on results for the linear quadratic control of infinite dimensional systems with unbounded input and output operators is presented. The blind deconvolution problem is then reformulated as a series of constrained linear and nonlinear optimization problems involving infinite dimensional dynamical systems. A finite dimensional approximation and convergence theory is developed. The theory is applied to the problem of estimating blood or breath alcohol concentration (respectively, BAC or BrAC) from biosensor-measured transdermal alcohol concentration (TAC) in the field. A distributed parameter model with boundary input and output is proposed for the transdermal transport of ethanol from the blood through the skin to the sensor. The problem of estimating BAC or BrAC from the TAC data is formulated as a blind deconvolution problem. A scheme to identify distinct drinking episodes in TAC data based on a Hodrick Prescott filter is discussed. Numerical results involving actual patient data are presented.

World Input-Output Network.

Directory of Open Access Journals (Sweden)

Federica Cerina

Full Text Available Production systems, traditionally analyzed as almost independent national systems, are increasingly connected on a global scale. Only recently becoming available, the World Input-Output Database (WIOD is one of the first efforts to construct the global multi-regional input-output (GMRIO tables. By viewing the world input-output system as an interdependent network where the nodes are the individual industries in different economies and the edges are the monetary goods flows between industries, we analyze respectively the global, regional, and local network properties of the so-called world input-output network (WION and document its evolution over time. At global level, we find that the industries are highly but asymmetrically connected, which implies that micro shocks can lead to macro fluctuations. At regional level, we find that the world production is still operated nationally or at most regionally as the communities detected are either individual economies or geographically well defined regions. Finally, at local level, for each industry we compare the network-based measures with the traditional methods of backward linkages. We find that the network-based measures such as PageRank centrality and community coreness measure can give valuable insights into identifying the key industries.

Methods for intraoperative, sterile pose-setting of patient-specific microstereotactic frames

Science.gov (United States)

Vollmann, Benjamin; Müller, Samuel; Kundrat, Dennis; Ortmaier, Tobias; Kahrs, Lüder A.

2015-03-01

This work proposes new methods for a microstereotactic frame based on bone cement fixation. Microstereotactic frames are under investigation for minimal invasive temporal bone surgery, e.g. cochlear implantation, or for deep brain stimulation, where products are already on the market. The correct pose of the microstereotactic frame is either adjusted outside or inside the operating room and the frame is used for e.g. drill or electrode guidance. We present a patientspecific, disposable frame that allows intraoperative, sterile pose-setting. Key idea of our approach is bone cement between two plates that cures while the plates are positioned with a mechatronics system in the desired pose. This paper includes new designs of microstereotactic frames, a system for alignment and first measurements to analyze accuracy and applicable load.

Making 2D face recognition more robust using AAMs for pose compensation

NARCIS (Netherlands)

Huisman, Peter; Munster, Ruud; Moro-Ellenberger, Stephanie; Veldhuis, Raymond N.J.; Bazen, A.M.

2006-01-01

The problem of pose in 2D face recognition is widely acknowledged. Commercial systems are limited to near frontal face images and cannot deal with pose deviations larger than 15 degrees from the frontal view. This is a problem, when using face recognition for surveillance applications in which

Integrating Worked Examples into Problem Posing in a Web-Based Learning Environment

Science.gov (United States)

Hsiao, Ju-Yuan; Hung, Chun-Ling; Lan, Yu-Feng; Jeng, Yoau-Chau

2013-01-01

Most students always lack of experience and perceive difficult regarding problem posing. The study hypothesized that worked examples may have benefits for supporting students' problem posing activities. A quasi-experiment was conducted in the context of a business mathematics course for examining the effects of integrating worked examples into…

Using GIS mapping of the extent of nearshore rocky reefs to estimate the abundance and reproductive output of important fishery species.

Directory of Open Access Journals (Sweden)

Jeremy T Claisse

Full Text Available Kelp Bass (Paralabrax clathratus and California Sheephead (Semicossyphus pulcher are economically and ecologically valuable rocky reef fishes in southern California, making them likely indicator species for evaluating resource management actions. Multiple spatial datasets, aerial and satellite photography, underwater observations and expert judgment were used to produce a comprehensive map of nearshore natural rocky reef habitat for the Santa Monica Bay region (California, USA. It was then used to examine the relative contribution of individual reefs to a regional estimate of abundance and reproductive potential of the focal species. For the reefs surveyed for fishes (i.e. 18 out of the 22 in the region, comprising 82% the natural rocky reef habitat 30% was produced from a relatively small proportion of the regional reef area (c. 10%. Natural nearshore rocky reefs make up only 11% of the area in the newly designated MPAs in this region, but results provide some optimism that regional fisheries could benefit through an increase in overall reproductive output, if adequate increases in size structure of targeted species are realized.

Parameter Estimation of Damped Compound Pendulum Differential Evolution Algorithm

Directory of Open Access Journals (Sweden)

Saad Mohd Sazli

2016-01-01

Full Text Available This paper present the parameter identification of damped compound pendulum using differential evolution algorithm. The procedure used to achieve the parameter identification of the experimental system consisted of input output data collection, ARX model order selection and parameter estimation using conventional method least square (LS and differential evolution (DE algorithm. PRBS signal is used to be input signal to regulate the motor speed. Whereas, the output signal is taken from position sensor. Both, input and output data is used to estimate the parameter of the ARX model. The residual error between the actual and predicted output responses of the models is validated using mean squares error (MSE. Analysis showed that, MSE value for LS is 0.0026 and MSE value for DE is 3.6601×10-5. Based results obtained, it was found that DE have lower MSE than the LS method.

High Output Piezo/Triboelectric Hybrid Generator

Science.gov (United States)

Jung, Woo-Suk; Kang, Min-Gyu; Moon, Hi Gyu; Baek, Seung-Hyub; Yoon, Seok-Jin; Wang, Zhong-Lin; Kim, Sang-Woo; Kang, Chong-Yun

2015-03-01

Recently, piezoelectric and triboelectric energy harvesting devices have been developed to convert mechanical energy into electrical energy. Especially, it is well known that triboelectric nanogenerators have a simple structure and a high output voltage. However, whereas nanostructures improve the output of triboelectric generators, its fabrication process is still complicated and unfavorable in term of the large scale and long-time durability of the device. Here, we demonstrate a hybrid generator which does not use nanostructure but generates much higher output power by a small mechanical force and integrates piezoelectric generator into triboelectric generator, derived from the simultaneous use of piezoelectric and triboelectric mechanisms in one press-and-release cycle. This hybrid generator combines high piezoelectric output current and triboelectric output voltage, which produces peak output voltage of ~370 V, current density of ~12 μA.cm-2, and average power density of ~4.44 mW.cm-2. The output power successfully lit up 600 LED bulbs by the application of a 0.2 N mechanical force and it charged a 10 μF capacitor to 10 V in 25 s. Beyond energy harvesting, this work will provide new opportunities for developing a small, built-in power source in self-powered electronics such as mobile electronics.

High Output Piezo/Triboelectric Hybrid Generator

Science.gov (United States)

Jung, Woo-Suk; Kang, Min-Gyu; Moon, Hi Gyu; Baek, Seung-Hyub; Yoon, Seok-Jin; Wang, Zhong-Lin; Kim, Sang-Woo; Kang, Chong-Yun

2015-01-01

Recently, piezoelectric and triboelectric energy harvesting devices have been developed to convert mechanical energy into electrical energy. Especially, it is well known that triboelectric nanogenerators have a simple structure and a high output voltage. However, whereas nanostructures improve the output of triboelectric generators, its fabrication process is still complicated and unfavorable in term of the large scale and long-time durability of the device. Here, we demonstrate a hybrid generator which does not use nanostructure but generates much higher output power by a small mechanical force and integrates piezoelectric generator into triboelectric generator, derived from the simultaneous use of piezoelectric and triboelectric mechanisms in one press-and-release cycle. This hybrid generator combines high piezoelectric output current and triboelectric output voltage, which produces peak output voltage of ~370 V, current density of ~12 μA·cm−2, and average power density of ~4.44 mW·cm−2. The output power successfully lit up 600 LED bulbs by the application of a 0.2 N mechanical force and it charged a 10 μF capacitor to 10 V in 25 s. Beyond energy harvesting, this work will provide new opportunities for developing a small, built-in power source in self-powered electronics such as mobile electronics. PMID:25791299

Impact of magnetic saturation on the input-output linearising tracking control of an induction motor

DEFF Research Database (Denmark)

Dolinar, Drago; Ljusev, Petar; Stumberger, Gorazd

2004-01-01

This paper deals with the tracking control design of an induction motor, based on input-output linearization with magnetic saturation included. Magnetic saturation is represented by the nonlinear magnetizing curve of the iron core and is used in the control design, the observer of state variables......, and in the load torque estimator. An input-output linearising control is used to achieve better tracking performances of the drive. It is based on the mixed ”stator current - rotor flux linkage” induction motor model with magnetic saturation considered in the stationary reference frame. Experimental results show...... that the proposed input-output linearising tracking control with the included saturation behaves considerably better than the one without saturation, and that it introduces smaller position and speed errors, and better motor stiffness on account of the increased computational complexity....

Rice growing farmers efficiency measurement using a slack based interval DEA model with undesirable outputs

Science.gov (United States)

Khan, Sahubar Ali Mohd. Nadhar; Ramli, Razamin; Baten, M. D. Azizul

2017-11-01

In recent years eco-efficiency which considers the effect of production process on environment in determining the efficiency of firms have gained traction and a lot of attention. Rice farming is one of such production processes which typically produces two types of outputs which are economic desirable as well as environmentally undesirable. In efficiency analysis, these undesirable outputs cannot be ignored and need to be included in the model to obtain the actual estimation of firm's efficiency. There are numerous approaches that have been used in data envelopment analysis (DEA) literature to account for undesirable outputs of which directional distance function (DDF) approach is the most widely used as it allows for simultaneous increase in desirable outputs and reduction of undesirable outputs. Additionally, slack based DDF DEA approaches considers the output shortfalls and input excess in determining efficiency. In situations when data uncertainty is present, the deterministic DEA model is not suitable to be used as the effects of uncertain data will not be considered. In this case, it has been found that interval data approach is suitable to account for data uncertainty as it is much simpler to model and need less information regarding the underlying data distribution and membership function. The proposed model uses an enhanced DEA model which is based on DDF approach and incorporates slack based measure to determine efficiency in the presence of undesirable factors and data uncertainty. Interval data approach was used to estimate the values of inputs, undesirable outputs and desirable outputs. Two separate slack based interval DEA models were constructed for optimistic and pessimistic scenarios. The developed model was used to determine rice farmers efficiency from Kepala Batas, Kedah. The obtained results were later compared to the results obtained using a deterministic DDF DEA model. The study found that 15 out of 30 farmers are efficient in all cases. It

CO{sub 2} emissions, electricity consumption and output in ASEAN

Energy Technology Data Exchange (ETDEWEB)

Lean, Hooi Hooi [Economics Program, School of Social Sciences, Universiti Sains Malaysia (Malaysia); Smyth, Russell [Department of Economics, Monash University, Clayton 3800 (Australia)

2010-06-15

This study examines the causal relationship between carbon dioxide emissions, electricity consumption and economic growth within a panel vector error correction model for five ASEAN countries over the period 1980-2006. The long-run estimates indicate that there is a statistically significant positive association between electricity consumption and emissions and a non-linear relationship between emissions and real output, consistent with the environmental Kuznets curve. The long-run estimates, however, do not indicate the direction of causality between the variables. The results from the Granger causality tests suggest that in the long-run there is unidirectional Granger causality running from electricity consumption and emissions to economic growth. The results also point to unidirectional Granger causality running from emissions to electricity consumption in the short-run. (author)

Improved pose and affinity predictions using different protocols tailored on the basis of data availability

Science.gov (United States)

Prathipati, Philip; Nagao, Chioko; Ahmad, Shandar; Mizuguchi, Kenji

2016-09-01

The D3R 2015 grand drug design challenge provided a set of blinded challenges for evaluating the applicability of our protocols for pose and affinity prediction. In the present study, we report the application of two different strategies for the two D3R protein targets HSP90 and MAP4K4. HSP90 is a well-studied target system with numerous co-crystal structures and SAR data. Furthermore the D3R HSP90 test compounds showed high structural similarity to existing HSP90 inhibitors in BindingDB. Thus, we adopted an integrated docking and scoring approach involving a combination of both pharmacophoric and heavy atom similarity alignments, local minimization and quantitative structure activity relationships modeling, resulting in the reasonable prediction of pose [with the root mean square deviation (RMSD) values of 1.75 Å for mean pose 1, 1.417 Å for the mean best pose and 1.85 Å for the mean all poses] and affinity (ROC AUC = 0.702 at 7.5 pIC50 cut-off and R = 0.45 for 180 compounds). The second protein, MAP4K4, represents a novel system with limited SAR and co-crystal structure data and little structural similarity of the D3R MAP4K4 test compounds to known MAP4K4 ligands. For this system, we implemented an exhaustive pose and affinity prediction protocol involving docking and scoring using the PLANTS software which considers side chain flexibility together with protein-ligand fingerprints analysis assisting in pose prioritization. This protocol through fares poorly in pose prediction (with the RMSD values of 4.346 Å for mean pose 1, 4.69 Å for mean best pose and 4.75 Å for mean all poses) and produced reasonable affinity prediction (AUC = 0.728 at 7.5 pIC50 cut-off and R = 0.67 for 18 compounds, ranked 1st among 80 submissions).

New hybrid multivariate analysis approach to optimize multiple response surfaces considering correlations in both inputs and outputs

OpenAIRE

Hejazi, Taha Hossein; Amirkabir University of Technology - Iran; Seyyed-Esfahani, Mirmehdi; Amirkabir University of Technology - Iran; Ramezani, Majid; Amirkabir University of Technology - Iran

2014-01-01

Quality control in industrial and service systems requires the correct setting of input factors by which the outputs result at minimum cost with desirable characteristics. There are often more than one input and output in such systems. Response surface methodology in its multiple variable forms is one of the most applied methods to estimate and improve the quality characteristics of products with respect to control factors. When there is some degree of correlation among the variables, the exi...

Aquatic concentrations of chemical analytes compared to ecotoxicity estimates

Data.gov (United States)

U.S. Environmental Protection Agency — We describe screening level estimates of potential aquatic toxicity posed by 227 chemical analytes that were measured in 25 ambient water samples collected as part...

Deflation of input-output tables from the user's point of view : a heuristic approach

NARCIS (Netherlands)

Dietzenbacher, Erik; Hoen, A.R.

This paper considers the problem of deflating an input-output table from the viewpoint of the user. In many practical cases certain margins of this table are readily available in constant prices, whereas the entire table is not. This reduces the problem to estimating the matrix of sectoral

Predicting Power Output of Upper Body using the OMNI-RES Scale.

Science.gov (United States)

Bautista, Iker J; Chirosa, Ignacio J; Tamayo, Ignacio Martín; González, Andrés; Robinson, Joseph E; Chirosa, Luis J; Robertson, Robert J

2014-12-09

The main aim of this study was to determine the optimal training zone for maximum power output. This was to be achieved through estimating mean bar velocity of the concentric phase of a bench press using a prediction equation. The values for the prediction equation would be obtained using OMNI-RES scale values of different loads of the bench press exercise. Sixty males (age 23.61 2.81 year; body height 176.29 6.73 cm; body mass 73.28 4.75 kg) voluntarily participated in the study and were tested using an incremental protocol on a Smith machine to determine one repetition maximum (1RM) in the bench press exercise. A linear regression analysis produced a strong correlation (r = -0.94) between rating of perceived exertion (RPE) and mean bar velocity (Velmean). The Pearson correlation analysis between real power output (PotReal) and estimated power (PotEst) showed a strong correlation coefficient of r = 0.77, significant at a level of p = 0.01. Therefore, the OMNI-RES scale can be used to predict Velmean in the bench press exercise to control the intensity of the exercise. The positive relationship between PotReal and PotEst allowed for the identification of a maximum power-training zone.

Toward a more robust variance-based global sensitivity analysis of model outputs

Energy Technology Data Exchange (ETDEWEB)

Tong, C

2007-10-15

Global sensitivity analysis (GSA) measures the variation of a model output as a function of the variations of the model inputs given their ranges. In this paper we consider variance-based GSA methods that do not rely on certain assumptions about the model structure such as linearity or monotonicity. These variance-based methods decompose the output variance into terms of increasing dimensionality called 'sensitivity indices', first introduced by Sobol' [25]. Sobol' developed a method of estimating these sensitivity indices using Monte Carlo simulations. McKay [13] proposed an efficient method using replicated Latin hypercube sampling to compute the 'correlation ratios' or 'main effects', which have been shown to be equivalent to Sobol's first-order sensitivity indices. Practical issues with using these variance estimators are how to choose adequate sample sizes and how to assess the accuracy of the results. This paper proposes a modified McKay main effect method featuring an adaptive procedure for accuracy assessment and improvement. We also extend our adaptive technique to the computation of second-order sensitivity indices. Details of the proposed adaptive procedure as wells as numerical results are included in this paper.

Problem-Posing in Education: Transformation of the Practice of the Health Professional.

Science.gov (United States)

Casagrande, L. D. R.; Caron-Ruffino, M.; Rodrigues, R. A. P.; Vendrusculo, D. M. S.; Takayanagui, A. M. M.; Zago, M. M. F.; Mendes, M. D.

1998-01-01

Studied the use of a problem-posing model in health education. The model based on the ideas of Paulo Freire is presented. Four innovative experiences of teaching-learning in environmental and occupational health and patient education are reported. Notes that the problem-posing model has the capability to transform health-education practice.…

Collaborative Random Faces-Guided Encoders for Pose-Invariant Face Representation Learning.

Science.gov (United States)

Shao, Ming; Zhang, Yizhe; Fu, Yun

2018-04-01

Learning discriminant face representation for pose-invariant face recognition has been identified as a critical issue in visual learning systems. The challenge lies in the drastic changes of facial appearances between the test face and the registered face. To that end, we propose a high-level feature learning framework called "collaborative random faces (RFs)-guided encoders" toward this problem. The contributions of this paper are three fold. First, we propose a novel supervised autoencoder that is able to capture the high-level identity feature despite of pose variations. Second, we enrich the identity features by replacing the target values of conventional autoencoders with random signals (RFs in this paper), which are unique for each subject under different poses. Third, we further improve the performance of the framework by incorporating deep convolutional neural network facial descriptors and linking discriminative identity features from different RFs for the augmented identity features. Finally, we conduct face identification experiments on Multi-PIE database, and face verification experiments on labeled faces in the wild and YouTube Face databases, where face recognition rate and verification accuracy with Receiver Operating Characteristic curves are rendered. In addition, discussions of model parameters and connections with the existing methods are provided. These experiments demonstrate that our learning system works fairly well on handling pose variations.

Cooperative learning neural network output feedback control of uncertain nonlinear multi-agent systems under directed topologies

Science.gov (United States)

Wang, W.; Wang, D.; Peng, Z. H.

2017-09-01

Without assuming that the communication topologies among the neural network (NN) weights are to be undirected and the states of each agent are measurable, the cooperative learning NN output feedback control is addressed for uncertain nonlinear multi-agent systems with identical structures in strict-feedback form. By establishing directed communication topologies among NN weights to share their learned knowledge, NNs with cooperative learning laws are employed to identify the uncertainties. By designing NN-based κ-filter observers to estimate the unmeasurable states, a new cooperative learning output feedback control scheme is proposed to guarantee that the system outputs can track nonidentical reference signals with bounded tracking errors. A simulation example is given to demonstrate the effectiveness of the theoretical results.

State of Charge Estimation Using the Extended Kalman Filter for Battery Management Systems Based on the ARX Battery Model

Directory of Open Access Journals (Sweden)

Hongjie Wu

2013-01-01

Full Text Available State of charge (SOC is a critical factor to guarantee that a battery system is operating in a safe and reliable manner. Many uncertainties and noises, such as fluctuating current, sensor measurement accuracy and bias, temperature effects, calibration errors or even sensor failure, etc. pose a challenge to the accurate estimation of SOC in real applications. This paper adds two contributions to the existing literature. First, the auto regressive exogenous (ARX model is proposed here to simulate the battery nonlinear dynamics. Due to its discrete form and ease of implemention, this straightforward approach could be more suitable for real applications. Second, its order selection principle and parameter identification method is illustrated in detail in this paper. The hybrid pulse power characterization (HPPC cycles are implemented on the 60AH LiFePO4 battery module for the model identification and validation. Based on the proposed ARX model, SOC estimation is pursued using the extended Kalman filter. Evaluation of the adaptability of the battery models and robustness of the SOC estimation algorithm are also verified. The results indicate that the SOC estimation method using the Kalman filter based on the ARX model shows great performance. It increases the model output voltage accuracy, thereby having the potential to be used in real applications, such as EVs and HEVs.

Generalized Hough transform based time invariant action recognition with 3D pose information

Science.gov (United States)

Muench, David; Huebner, Wolfgang; Arens, Michael

2014-10-01

Human action recognition has emerged as an important field in the computer vision community due to its large number of applications such as automatic video surveillance, content based video-search and human robot interaction. In order to cope with the challenges that this large variety of applications present, recent research has focused more on developing classifiers able to detect several actions in more natural and unconstrained video sequences. The invariance discrimination tradeoff in action recognition has been addressed by utilizing a Generalized Hough Transform. As a basis for action representation we transform 3D poses into a robust feature space, referred to as pose descriptors. For each action class a one-dimensional temporal voting space is constructed. Votes are generated from associating pose descriptors with their position in time relative to the end of an action sequence. Training data consists of manually segmented action sequences. In the detection phase valid human 3D poses are assumed as input, e.g. originating from 3D sensors or monocular pose reconstruction methods. The human 3D poses are normalized to gain view-independence and transformed into (i) relative limb-angle space to ensure independence of non-adjacent joints or (ii) geometric features. In (i) an action descriptor consists of the relative angles between limbs and their temporal derivatives. In (ii) the action descriptor consists of different geometric features. In order to circumvent the problem of time-warping we propose to use a codebook of prototypical 3D poses which is generated from sample sequences of 3D motion capture data. This idea is in accordance with the concept of equivalence classes in action space. Results of the codebook method are presented using the Kinect sensor and the CMU Motion Capture Database.

The Effects of Problem Posing on Student Mathematical Learning: A Meta-Analysis

Science.gov (United States)

Rosli, Roslinda; Capraro, Mary Margaret; Capraro, Robert M.

2014-01-01

The purpose of the study was to meta-synthesize research findings on the effectiveness of problem posing and to investigate the factors that might affect the incorporation of problem posing in the teaching and learning of mathematics. The eligibility criteria for inclusion of literature in the meta-analysis was: published between 1989 and 2011,…

Similarity Assessment of Land Surface Model Outputs in the North American Land Data Assimilation System

Science.gov (United States)

Kumar, Sujay V.; Wang, Shugong; Mocko, David M.; Peters-Lidard, Christa D.; Xia, Youlong

2017-11-01

Multimodel ensembles are often used to produce ensemble mean estimates that tend to have increased simulation skill over any individual model output. If multimodel outputs are too similar, an individual LSM would add little additional information to the multimodel ensemble, whereas if the models are too dissimilar, it may be indicative of systematic errors in their formulations or configurations. The article presents a formal similarity assessment of the North American Land Data Assimilation System (NLDAS) multimodel ensemble outputs to assess their utility to the ensemble, using a confirmatory factor analysis. Outputs from four NLDAS Phase 2 models currently running in operations at NOAA/NCEP and four new/upgraded models that are under consideration for the next phase of NLDAS are employed in this study. The results show that the runoff estimates from the LSMs were most dissimilar whereas the models showed greater similarity for root zone soil moisture, snow water equivalent, and terrestrial water storage. Generally, the NLDAS operational models showed weaker association with the common factor of the ensemble and the newer versions of the LSMs showed stronger association with the common factor, with the model similarity increasing at longer time scales. Trade-offs between the similarity metrics and accuracy measures indicated that the NLDAS operational models demonstrate a larger span in the similarity-accuracy space compared to the new LSMs. The results of the article indicate that simultaneous consideration of model similarity and accuracy at the relevant time scales is necessary in the development of multimodel ensemble.

Trotting Gait of a Quadruped Robot Based on the Time-Pose Control Method

Directory of Open Access Journals (Sweden)

Cai RunBin

2013-02-01

Full Text Available We present the Time-Pose control method for the trotting gait of a quadruped robot on flat ground and up a slope. The method, with brief control structure, real-time operation ability and high adaptability, divides quadruped robot control into gait control and pose control. Virtual leg and intuitive controllers are introduced to simplify the model and generate the trajectory of mass centre and location of supporting legs in gait control, while redundancy optimization is used for solving the inverse kinematics in pose control. The models both on flat ground and up a slope are fully analysed, and different kinds of optimization methods are compared using the manipulability measure in order to select the best option. Simulations are performed, which prove that the Time-Pose control method is realizable for these two kinds of environment.

Adaptive Neural Control for a Class of Outputs Time-Delay Nonlinear Systems

Directory of Open Access Journals (Sweden)

Ruliang Wang

2012-01-01

Full Text Available This paper considers an adaptive neural control for a class of outputs time-delay nonlinear systems with perturbed or no. Based on RBF neural networks, the radius basis function (RBF neural networks is employed to estimate the unknown continuous functions. The proposed control guarantees that all closed-loop signals remain bounded. The simulation results demonstrate the effectiveness of the proposed control scheme.

Binary classification posed as a quadratically constrained quadratic ...

Indian Academy of Sciences (India)

Binary classification is posed as a quadratically constrained quadratic problem and solved using the proposed method. Each class in the binary classification problem is modeled as a multidimensional ellipsoid to forma quadratic constraint in the problem. Particle swarms help in determining the optimal hyperplane or ...

Developing teachers' subject didactic competence through problem posing

Czech Academy of Sciences Publication Activity Database

Tichá, Marie; Hošpesová, A.

2013-01-01

Roč. 83, č. 1 (2013), s. 133-143 ISSN 0013-1954 Institutional support: RVO:67985840 Keywords : professional development * primary school teachers * problem posing Subject RIV: AM - Education Impact factor: 0.639, year: 2013 http://link.springer.com/article/10.1007%2Fs10649-012-9455-1

PARAMETER ESTIMATION OF VALVE STICTION USING ANT COLONY OPTIMIZATION

Directory of Open Access Journals (Sweden)

S. Kalaivani

2012-07-01

Full Text Available In this paper, a procedure for quantifying valve stiction in control loops based on ant colony optimization has been proposed. Pneumatic control valves are widely used in the process industry. The control valve contains non-linearities such as stiction, backlash, and deadband that in turn cause oscillations in the process output. Stiction is one of the long-standing problems and it is the most severe problem in the control valves. Thus the measurement data from an oscillating control loop can be used as a possible diagnostic signal to provide an estimate of the stiction magnitude. Quantification of control valve stiction is still a challenging issue. Prior to doing stiction detection and quantification, it is necessary to choose a suitable model structure to describe control-valve stiction. To understand the stiction phenomenon, the Stenman model is used. Ant Colony Optimization (ACO, an intelligent swarm algorithm, proves effective in various fields. The ACO algorithm is inspired from the natural trail following behaviour of ants. The parameters of the Stenman model are estimated using ant colony optimization, from the input-output data by minimizing the error between the actual stiction model output and the simulated stiction model output. Using ant colony optimization, Stenman model with known nonlinear structure and unknown parameters can be estimated.

¿Cómo transformar los modelos input-output para calcular multiplicadores netos?

Directory of Open Access Journals (Sweden)

Pereira López, Xesús

2015-11-01

Full Text Available The aim of this paper is to calculate net input-output multipliers using different adjustments on the Leontief inverse, without simply removing part of its elements. Moreover, in order to increase the accuracy of the estimation, a standardization of the inverse is offered. The empirical application is presented for the Galician economy, based on the year 2011. A comparison between the proposed extended methodology and the traditional I-O techniques is shown, throughout the results obtained in the estimation of the backward and forward sectoral linkages. With this new approach, some of the conventional key sectors will not appear as such, like the case of the construction sector.

Inertial measurement unit–based iterative pose compensation algorithm for low-cost modular manipulator

Directory of Open Access Journals (Sweden)

Yunhan Lin

2016-01-01

Full Text Available It is a necessary mean to realize the accurate motion control of the manipulator which uses end-effector pose correction method and compensation method. In this article, first, we established the kinematic model and error model of the modular manipulator (WUST-ARM, and then we discussed the measurement methods and precision of the inertial measurement unit sensor. The inertial measurement unit sensor is mounted on the end-effector of modular manipulator, to get the real-time pose of the end-effector. At last, a new inertial measurement unit–based iterative pose compensation algorithm is proposed. By applying this algorithm in the pose compensation experiment of modular manipulator which is composed of low-cost rotation joints, the results show that the inertial measurement unit can obtain a higher precision when in static state; it will accurately feedback to the control system with an accurate error compensation angle after a brief delay when the end-effector moves to the target point, and after compensation, the precision errors of roll angle, pitch angle, and yaw angle are reached at 0.05°, 0.01°, and 0.27° respectively. It proves that this low-cost method provides a new solution to improve the end-effector pose of low-cost modular manipulator.

Non-invasive cardiac output trending during exercise recovery on a bathroom-scale-based ballistocardiograph

International Nuclear Information System (INIS)

Inan, O T; Etemadi, M; Giovangrandi, L; Kovacs, G T A; Paloma, A

2009-01-01

Cardiac ejection of blood into the aorta generates a reaction force on the body that can be measured externally via the ballistocardiogram (BCG). In this study, a commercial bathroom scale was modified to measure the BCGs of nine healthy subjects recovering from treadmill exercise. During the recovery, Doppler echocardiogram signals were obtained simultaneously from the left ventricular outflow tract of the heart. The percentage changes in root-mean-square (RMS) power of the BCG were strongly correlated with the percentage changes in cardiac output measured by Doppler echocardiography (R 2 = 0.85, n = 275 data points). The correlation coefficients for individually analyzed data ranged from 0.79 to 0.96. Using Bland–Altman methods for assessing agreement, the mean bias was found to be −0.5% (±24%) in estimating the percentage changes in cardiac output. In contrast to other non-invasive methods for trending cardiac output, the unobtrusive procedure presented here uses inexpensive equipment and could be performed without the aid of a medical professional

Non-invasive cardiac output trending during exercise recovery on a bathroom-scale-based ballistocardiograph.

Science.gov (United States)

Inan, O T; Etemadi, M; Paloma, A; Giovangrandi, L; Kovacs, G T A

2009-03-01

Cardiac ejection of blood into the aorta generates a reaction force on the body that can be measured externally via the ballistocardiogram (BCG). In this study, a commercial bathroom scale was modified to measure the BCGs of nine healthy subjects recovering from treadmill exercise. During the recovery, Doppler echocardiogram signals were obtained simultaneously from the left ventricular outflow tract of the heart. The percentage changes in root-mean-square (RMS) power of the BCG were strongly correlated with the percentage changes in cardiac output measured by Doppler echocardiography (R(2) = 0.85, n = 275 data points). The correlation coefficients for individually analyzed data ranged from 0.79 to 0.96. Using Bland-Altman methods for assessing agreement, the mean bias was found to be -0.5% (+/-24%) in estimating the percentage changes in cardiac output. In contrast to other non-invasive methods for trending cardiac output, the unobtrusive procedure presented here uses inexpensive equipment and could be performed without the aid of a medical professional.

A Urinary Purine Derivatives Method for Estimating Ruminal Output of Microbial Proteins%尿嘌呤衍生物法估测瘤胃微生物蛋白质产量

Institute of Scientific and Technical Information of China (English)

马涛; 刁其玉; 邓凯东

2011-01-01

The urinary excretion of purine derivatives method is an effective approach for estimating microprotein output in the rumen. which is non-invasive and easy to operate. The method can accurately estimate the changes of microprotein output in the rumen. It has a lower residual variation and more consistent results. Two improvements are spot sampling method and dahlin method. The advantage of spot sampling method is the determination on appropriate sampling time, by which a high relevance between PD/C ( the ratio of purine derivative to creatinine) and the daily quantity of purine derivatives can be obtained; In dahlin method. inulin. a more reliable urinary marker, is used for estimating daily creatinine excretion. [ Chinese Journal of Animal Nutrition ,2011 ,23 ( 1 ) : 10-14 ]%尿嘌呤衍生物法具有非侵入性和操作方便等优点,是估测微生物蛋白质产量的一种有效方法.该方法能够准确估测瘤胃微生物蛋白质产量的变化,且其残差变异低于其他方法,估测结果的一致性较好.对其改良后的方法有点采样法和菊糖法.点采样法优点在于可以确定恰当的采样时间,保证尿嘌呤衍生物与肌酐的比例(PD/C)与尿嘌呤衍生物日排出量的高相关性;菊糖法是利用了菊糖这种可靠尿液标记物来测定肌酐日排出量.

Health Issues: Do Cell Phones Pose a Health Hazard?

Science.gov (United States)

... Procedures Home, Business, and Entertainment Products Cell Phones Health Issues Share Tweet Linkedin Pin it More sharing ... it Email Print Do cell phones pose a health hazard? Many people are concerned that cell phone ...

Oil output's changing fortunes

International Nuclear Information System (INIS)

Eldridge, D.

1994-01-01

The Petroleum Economist, previously the Petroleum Press Service, has been making annual surveys of output levels of petroleum in all the oil-producing countries since its founding in 1934. This article documents trends and changes in the major oil-producing countries output from 1934 until the present. This analysis is linked with the political and historical events accompanying these changes, notably the growth of Middle Eastern oil production, the North Sea finds and most recently, Iraq's invasion of Kuwait in 1990. (UK)

Pose Self-Measurement of Noncooperative Spacecraft Based on Solar Panel Triangle Structure

Directory of Open Access Journals (Sweden)

Jingzhou Song

2015-01-01

Full Text Available Aiming at the recognition and location of noncooperative spacecraft, this paper presents a monocular vision pose measurement method based on solar triangle structure. First of all, an autonomous recognition algorithm of feature structure based on sliding window Hough transformation (SWHT and inscribed circle of a triangle is proposed, and the image coordinates of feature points on the triangle can be obtained relying on this algorithm, combined with the P4P algorithm and the structure of spacecraft, calculating the relative pose of target expressed by rotation and translation matrix. The whole algorithm can be loaded into the prewritten onboard program, which will get the autocomplete feature structure extraction and relative pose measurement without human intervention, and this method does not need to mount any markers on the target. Then compare the measured values with the accurate value of the laser tracker, so that a conclusion can be drawn that the maximum position error is lower than 5% and the rotation error is lower than 4%, which meets the requirements of noncooperative spacecraft’s pose measurement for observations, tracking, and docking in the final rendezvous phase.

Preliminary estimate of CO2 budget discharged from Vulcano island

OpenAIRE

Inguaggiato, S.; Mazot, A.; Diliberto, I. S.; Rowet, D.; Vita, F.; Capasso, G.; Bobrowski, N.; Inguaggiato, C.; Grassa, F.

2008-01-01

Total CO2 output from fumaroles, soil gases, bubbling and water dissolved gases were estimated at Vulcano Island, Italy. The fumaroles output has been estimated from SO2 plume flux, while soil flux emission has been carried out through 730 CO2 fluxes measured on the island surface, performed by means of accumulation chamber method. Vulcano Island, located in the Aeolian Archipelago, is an active volcano that has been in state of solphataric activity, since the last eruption (1888-1890). At p...

Mining Key Skeleton Poses with Latent SVM for Action Recognition

Directory of Open Access Journals (Sweden)

Xiaoqiang Li

2017-01-01

Full Text Available Human action recognition based on 3D skeleton has become an active research field in recent years with the recently developed commodity depth sensors. Most published methods analyze an entire 3D depth data, construct mid-level part representations, or use trajectory descriptor of spatial-temporal interest point for recognizing human activities. Unlike previous work, a novel and simple action representation is proposed in this paper which models the action as a sequence of inconsecutive and discriminative skeleton poses, named as key skeleton poses. The pairwise relative positions of skeleton joints are used as feature of the skeleton poses which are mined with the aid of the latent support vector machine (latent SVM. The advantage of our method is resisting against intraclass variation such as noise and large nonlinear temporal deformation of human action. We evaluate the proposed approach on three benchmark action datasets captured by Kinect devices: MSR Action 3D dataset, UTKinect Action dataset, and Florence 3D Action dataset. The detailed experimental results demonstrate that the proposed approach achieves superior performance to the state-of-the-art skeleton-based action recognition methods.

LEVELING STUDENTS’ CREATIVE THINKING IN SOLVING AND POSING MATHEMATICAL PROBLEM

Directory of Open Access Journals (Sweden)

Tatag Yuli Eko Siswono

2010-07-01

Full Text Available Many researchers assume that people are creative, but their degree ofcreativity is different. The notion of creative thinking level has beendiscussed .by experts. The perspective of mathematics creative thinkingrefers to a combination of logical and divergent thinking which is basedon intuition but has a conscious aim. The divergent thinking is focusedon flexibility, fluency, and novelty in mathematical problem solving andproblem posing. As students have various backgrounds and differentabilities, they possess different potential in thinking patterns,imagination, fantasy and performance; therefore, students have differentlevels of creative thinking. A research study was conducted in order todevelop a framework for students’ levels of creative thinking inmathematics. This research used a qualitative approach to describe thecharacteristics of the levels of creative thinking. Task-based interviewswere conducted to collect data with ten 8thgrade junior secondary schoolstudents. The results distinguished five levels of creative thinking,namely level 0 to level 4 with different characteristics in each level.These differences are based on fluency, flexibility, and novelty inmathematical problem solving and problem posing.Keywords: student’s creative thinking, problem posing, flexibility,fluency, novelty DOI: http://dx.doi.org/10.22342/jme.1.1.794.17-40

DIST/AVC Out-Put Definition.

Science.gov (United States)

Wilkinson, Gene L.

The first stage of development of a management information system for DIST/AVC (Division of Instructional Technology/Audio-Visual Center) is the definition of out-put units. Some constraints on the definition of output units are: 1) they should reflect goals of the organization, 2) they should reflect organizational structure and procedures, and…

Pose measurement method with six parameters for microassembly based on an optical micrometer

Science.gov (United States)

Ye, Xin; Wang, Qiang; Zhang, Zhi-jing; Sun, Yuan; Zhang, Xiao-feng

2009-07-01

This paper presents a new pose measurement method of microminiature parts that is capable of transforming one dimension (1D) contour size obtained by optical micrometer to three dimension (3D) data with six parameters for microassembly. Pose measurement is one of the most important processes for microminiature parts' alignment and insertion in microassembly. During the past few years, researchers have developed their microassembly systems focusing on visual identification to obtain two or three dimension data with no more than three parameters. Scanning electronic microscope (SEM), optical microscope, and stereomicroscope are applied in their systems. However, as structures of microminiature parts become increasingly complex, six parameters to represent their position and orientation are specifically needed. Firstly, The pose measurement model is established based on the introduction of measuring objects and measuring principle of optical micrometer. The measuring objects are microminiature parts with complex 3D structure. Two groups of two dimension (2D) data are gathered at two different measurement positions. Then part pose with 6 parameters is calculated, including 3 position parameters of feature point of the part and 3 orientation parameters of the part axis. Secondly, pose measurement process for a small shaft, vertical orientation determination, and position parameters obtaining are presented. 2D data is gathered by scanning the generatrix of the part, and valid data is extracted and saved in arrays. A vertical orientation criterion is proposed to determine whether the part is parallel to the Z-axis of the coordinate. If not, 2D data will be fixed into a linear equation using least square algorithm. Then orientation parameters are calculated. Center of Part End (CPE) is selected as feature point of the part, and its position parameters are extracted form two group of 2D data. Finally, a fast pose measurement device is developed and representative

Theoretical analysis of magnetic sensor output voltage

International Nuclear Information System (INIS)

Liu Haishun; Dun Chaochao; Dou Linming; Yang Weiming

2011-01-01

The output voltage is an important parameter to determine the stress state in magnetic stress measurement, the relationship between the output voltage and the difference in the principal stresses was investigated by a comprehensive application of magnetic circuit theory, magnetization theory, stress analysis as well as the law of electromagnetic induction, and a corresponding quantitative equation was derived. It is drawn that the output voltage is proportional to the difference in the principal stresses, and related to the angle between the principal stress and the direction of the sensor. This investigation provides a theoretical basis for the principle stresses measurement by output voltage. - Research highlights: → A comprehensive investigation of magnetic stress signal. → Derived a quantitative equation about output voltage and the principal stresses. → The output voltage is proportional to the difference of the principal stresses. → Provide a theoretical basis for the principle stresses measurement.

Disturbance estimation of nuclear power plant by using reduced-order model

International Nuclear Information System (INIS)

Tashima, Shin-ichi; Wakabayashi, Jiro

1983-01-01

An estimation method is proposed of multiplex disturbances which occur in a nuclear power plant. The method is composed of two parts: (i) the identification of a simplified model of multi-input and multi-output to describe the related system response, and (ii) the design of a Kalman filter to estimate the multiplex disturbance. Concerning the simplified model, several observed signals are firstly selected as output variables which can well represent the system response caused by the disturbances. A reduced-order model is utilized for designing the disturbance estimator. This is based on the following two considerations. The first is that the disturbance is assumed to be of a quasistatic nature. The other is based on the intuition that there exist a few dominant modes between the disturbances and the selected observed signals and that most of the non-dominant modes which remain may not affect the accuracy of the disturbance estimator. The reduced-order model is furtherly transformed to a single-output model using a linear combination of the output signals, where the standard procedure of the structural identification is evaded. The parameters of the model thus transformed are calculated by the generalized least square method. As for the multiplex disturbance estimator, the Kalman filtering method is applied by compromising the following three items : (a) quick response to disturbance, (b) reduction of estimation error in the presence of observation noises, and (c) the elimination of cross-interference between the disturbances to the plant and the estimates from the Kalman filter. The effectiveness of the proposed method is verified through some computer experiments using a BWR plant simulator. (author)

Asynchronous vehicle pose correction using visual detection of ground features

International Nuclear Information System (INIS)

Harnarinesingh, Randy E S; Syan, Chanan S

2014-01-01

The inherent noise associated with odometry manifests itself as errors in localization for autonomous vehicles. Visual odometry has been previously used in order to supplement classical vehicle odometry. However, visual odometry is limited in its ability to reduce errors in localization for large travel distances that entail the cumulative summing of individual frame-to-frame image errors. In this paper, a novel machine vision approach for tiled surfaces is proposed to address this problem. Tile edges in a laboratory environment are used to define a travel trajectory for the Quansar Qbot (autonomous vehicle) built on the iRobot iRoomba platform with a forward facing camera. Tile intersections are used to enable asynchronous error recovery for vehicle position and orientation. The proposed approach employs real-time image classification and is feasible for error mitigation for large travel distances. The average position error for an 8m travel distance using classical odometry was measured to be 0.28m. However, implementation of the proposed approach resulted in an error of 0.028m. The proposed approach therefore significantly reduces pose estimation error and could be used to supplement existing modalities such as GPS and Laser-based range sensors

A model and variance reduction method for computing statistical outputs of stochastic elliptic partial differential equations

International Nuclear Information System (INIS)

Vidal-Codina, F.; Nguyen, N.C.; Giles, M.B.; Peraire, J.

2015-01-01

We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basis approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method

Perbedaan Keterampilan Pemecahan Masalah pada Pembelajaran Fisika Menggunakan Metode Problem Posing dan Problem Solving

OpenAIRE

Rahman, Adetya; Hartini, Sri; An'nur, Syubhan

2015-01-01

Teachers should be able to choose the method of learning that can help students in learning physics, namely the method of problem posing and problem solving method. The purposes of this study are : (1) describe the learning physics skills by using problem posing method, (2) describe the learning physics skills by using problem solving method, and (3) know difference between learning physics skills by using problem posing method and problem solving method in class XI of Science SMAN 6 Banjarma...

Robust Output Model Predictive Control of an Unstable Rijke Tube

Directory of Open Access Journals (Sweden)

Fabian Jarmolowitz

2012-01-01

Full Text Available This work investigates the active control of an unstable Rijke tube using robust output model predictive control (RMPC. As internal model a polytopic linear system with constraints is assumed to account for uncertainties. For guaranteed stability, a linear state feedback controller is designed using linear matrix inequalities and used within a feedback formulation of the model predictive controller. For state estimation a robust gain-scheduled observer is developed. It is shown that the proposed RMPC ensures robust stability under constraints over the considered operating range.

Scintillation camera with improved output means

International Nuclear Information System (INIS)

Lange, K.; Wiesen, E.J.; Woronowicz, E.M.

1978-01-01

In a scintillation camera system, the output pulse signals from an array of photomultiplier tubes are coupled to the inputs of individual preamplifiers. The preamplifier output signals are coupled to circuitry for computing the x and y coordinates of the scintillations. A cathode ray oscilloscope is used to form an image corresponding with the pattern in which radiation is emitted by a body. Means for improving the uniformity and resolution of the scintillations are provided. The means comprise biasing means coupled to the outputs of selected preamplifiers so that output signals below a predetermined amplitude are not suppressed and signals falling within increasing ranges of amplitudes are increasingly suppressed. In effect, the biasing means make the preamplifiers non-linear for selected signal levels

The Effect of Problem Solving and Problem Posing Models and Innate Ability to Students Achievement

Directory of Open Access Journals (Sweden)

Ratna Kartika Irawati

2015-04-01

Full Text Available Pengaruh Model Problem Solving dan Problem Posing serta Kemampuan Awal terhadap Hasil Belajar Siswa   Abstract: Chemistry concepts understanding features abstract quality and requires higher order thinking skills. Yet, the learning on chemistry has not boost the higher order thinking skills of the students. The use of the learning model of Problem Solving and Problem Posing in observing the innate ability of the student is expected to resolve the issue. This study aims to determine the learning model which is effective to improve the study of the student with different level of innate ability. This study used the quasi-experimental design. The research data used in this research is the quiz/test of the class which consist of 14 multiple choice questions and 5 essay questions. The data analysis used is ANOVA Two Ways. The results showed that Problem Posing is more effective to improve the student compared to Problem Solving, students with high level of innate ability have better outcomes in learning rather than the students with low level of innate ability after being applied with the Problem solving and Problem posing model, further, Problem Solving and Problem Posing is more suitable to be applied to the students with high level of innate ability. Key Words: problem solving, problem posing, higher order thinking skills, innate ability, learning outcomes   Abstrak: Pemahaman konsep-konsep kimia yang bersifat abstrak membutuhkan keterampilan berpikir tingkat tinggi. Pembelajaran kimia belum mendorong siswa melakukan keterampilan berpikir tingkat tinggi. Penggunaan model pembelajaran Problem Solving dan Problem Posing dengan memperhatikan kemampuan awal siswa diduga dapat mengatasi masalah tersebut. Penelitian ini bertujuan untuk mengetahui model pembelajaran yang efektif dalam meningkatkan hasil belajar dengan kemampuan awal siswa yang berbeda. Penelitian ini menggunakan rancangan eksperimen semu. Data penelitian menggunakan tes hasil belajar

Uncertainty quantification metrics for whole product life cycle cost estimates in aerospace innovation

Science.gov (United States)

Schwabe, O.; Shehab, E.; Erkoyuncu, J.

2015-08-01

The lack of defensible methods for quantifying cost estimate uncertainty over the whole product life cycle of aerospace innovations such as propulsion systems or airframes poses a significant challenge to the creation of accurate and defensible cost estimates. Based on the axiomatic definition of uncertainty as the actual prediction error of the cost estimate, this paper provides a comprehensive overview of metrics used for the uncertainty quantification of cost estimates based on a literature review, an evaluation of publicly funded projects such as part of the CORDIS or Horizon 2020 programs, and an analysis of established approaches used by organizations such NASA, the U.S. Department of Defence, the ESA, and various commercial companies. The metrics are categorized based on their foundational character (foundations), their use in practice (state-of-practice), their availability for practice (state-of-art) and those suggested for future exploration (state-of-future). Insights gained were that a variety of uncertainty quantification metrics exist whose suitability depends on the volatility of available relevant information, as defined by technical and cost readiness level, and the number of whole product life cycle phases the estimate is intended to be valid for. Information volatility and number of whole product life cycle phases can hereby be considered as defining multi-dimensional probability fields admitting various uncertainty quantification metric families with identifiable thresholds for transitioning between them. The key research gaps identified were the lacking guidance grounded in theory for the selection of uncertainty quantification metrics and lacking practical alternatives to metrics based on the Central Limit Theorem. An innovative uncertainty quantification framework consisting of; a set-theory based typology, a data library, a classification system, and a corresponding input-output model are put forward to address this research gap as the basis

Fraction Multiplication and Division Word Problems Posed by Different Years of Pre-Service Elementary Mathematics Teachers

Directory of Open Access Journals (Sweden)

Tuba Aydogdu Iskenderoglu

2018-04-01

Full Text Available It is important for pre-service teachers to know the conceptual difficulties they have experienced regarding the concepts of multiplication and division in fractions and problem posing is a way to learn these conceptual difficulties. Problem posing is a synthetic activity that fundamentally has multiple answers. The purpose of this study is to analyze the multiplication and division of fractions problems posed by pre-service elementary mathematics teachers and to investigate how the problems posed change according to the year of study the pre-service teachers are in. The study employed developmental research methods. A total of 213 pre-service teachers enrolled in different years of the Elementary Mathematics Teaching program at a state university in Turkey took part in the study. The “Problem Posing Test” was used as the data collecting tool. In this test, there are 3 multiplication and 3 division operations. The data were analyzed using qualitative descriptive analysis. The findings suggest that, regardless of the year, pre-service teachers had more conceptual difficulties in problem posing about the division of fractions than in problem posing about the multiplication of fractions.

Robust Estimation for a CSTR Using a High Order Sliding Mode Observer and an Observer-Based Estimator

Directory of Open Access Journals (Sweden)

Esteban Jiménez-Rodríguez

2016-12-01

Full Text Available This paper presents an estimation structure for a continuous stirred-tank reactor, which is comprised of a sliding mode observer-based estimator coupled with a high-order sliding-mode observer. The whole scheme allows the robust estimation of the state and some parameters, specifically the concentration of the reactive mass, the heat of reaction and the global coefficient of heat transfer, by measuring the temperature inside the reactor and the temperature inside the jacket. In order to verify the results, the convergence proof of the proposed structure is done, and numerical simulations are presented with noiseless and noisy measurements, suggesting the applicability of the posed approach.

Meanings Given to Algebraic Symbolism in Problem-Posing

Science.gov (United States)

Cañadas, María C.; Molina, Marta; del Río, Aurora

2018-01-01

Some errors in the learning of algebra suggest that students might have difficulties giving meaning to algebraic symbolism. In this paper, we use problem posing to analyze the students' capacity to assign meaning to algebraic symbolism and the difficulties that students encounter in this process, depending on the characteristics of the algebraic…

Area/latency optimized early output asynchronous full adders and relative-timed ripple carry adders.

Science.gov (United States)

Balasubramanian, P; Yamashita, S

2016-01-01

This article presents two area/latency optimized gate level asynchronous full adder designs which correspond to early output logic. The proposed full adders are constructed using the delay-insensitive dual-rail code and adhere to the four-phase return-to-zero handshaking. For an asynchronous ripple carry adder (RCA) constructed using the proposed early output full adders, the relative-timing assumption becomes necessary and the inherent advantages of the relative-timed RCA are: (1) computation with valid inputs, i.e., forward latency is data-dependent, and (2) computation with spacer inputs involves a bare minimum constant reverse latency of just one full adder delay, thus resulting in the optimal cycle time. With respect to different 32-bit RCA implementations, and in comparison with the optimized strong-indication, weak-indication, and early output full adder designs, one of the proposed early output full adders achieves respective reductions in latency by 67.8, 12.3 and 6.1 %, while the other proposed early output full adder achieves corresponding reductions in area by 32.6, 24.6 and 6.9 %, with practically no power penalty. Further, the proposed early output full adders based asynchronous RCAs enable minimum reductions in cycle time by 83.4, 15, and 8.8 % when considering carry-propagation over the entire RCA width of 32-bits, and maximum reductions in cycle time by 97.5, 27.4, and 22.4 % for the consideration of a typical carry chain length of 4 full adder stages, when compared to the least of the cycle time estimates of various strong-indication, weak-indication, and early output asynchronous RCAs of similar size. All the asynchronous full adders and RCAs were realized using standard cells in a semi-custom design fashion based on a 32/28 nm CMOS process technology.

Improvement of Frequency Domain Output Only Modal Identification from the Application of the Random Decrement Technique

DEFF Research Database (Denmark)

Rodrigues, J.; Brincker, Rune; Andersen, P.

2004-01-01

This paper explores the idea of estimating the spectral densities as the Fourier transform of the random decrement functions for the application of frequency domain output-only modal identification methods. The gains in relation to the usual procedure of computing the spectral densities directly...

Computer simulation for the effect of target angle in diagnostic x-ray tube output and half-value layer

International Nuclear Information System (INIS)

Hayami, Akimune; Fuchihata, Hajime; Yamazaki, Takeshi; Mori, Yoshinobu; Ozeki, Syuji.

1980-01-01

The change of target angle of X-ray tube plays an important role in changing both the output and the quality of X-rays. A computer simulation was made to estimate the effect of target angle on the output and the quality (half-value layer: HVL) in the central ray using Storm's semiempirical formula. The data here presented are the values of output and HVL for the target angles of 10, 15, 20 and 30 degrees and for the total filtrations of 1, 2, 3 and 4 mm Al eq., at an increment of 10 kV steps of applied voltage between 50 and 150 kV. The output values and HVL's as a function of target angle, applied voltage and total filtration are shown for a full-wave rectified diagnostic X-ray generator. As a result, changes ranging from 17 to 76% in the output and 5 to 66% in the HVL were noted by varying the target angle from 10 to 30 degrees. Therefore, the target angle of X-ray tube should be clearly stated whenever the output and the quality (HVL) of X-ray generator are discussed. (author)

WRF Model Output

Data.gov (United States)

U.S. Environmental Protection Agency — This dataset contains WRF model output. There are three months of data: July 2012, July 2013, and January 2013. For each month, several simulations were made: A...

The rarity of "unusual" [corrected] dispositions of victim bodies: staging and posing.

Science.gov (United States)

Keppel, Robert D; Weis, Joseph G

2004-11-01

The act of leaving a victim's body in an unusual position is a conscious criminal action by an offender to thwart an investigation, shock the finder and investigators of the crime scene, or give perverted pleasure to the killer. The unusual position concepts of posing and staging a murder victim have been documented thoroughly and have been accepted by the courts as a definable phenomenon. One staging case and one posing case are outlined and reveal characteristics of those homicides. From the Washington State Attorney General's Homicide Investigation and Tracking System's database on murder covering the years 1981-2000 (a total of 5,224 cases), the relative frequency of unusual body dispositions is revealed as a very rare occurrence. Only 1.3% of victims are left in an unusual position, with 0.3% being posed and 0.1% being staged. The characteristics of these types of murders also set them apart: compared to all other murders, in staged murders the victims and killers are, on average, older. All victims and offenders in the staged murders are white, with victims being disproportionately white in murders with any kind of unusual body disposition. Likewise, females stand out as victims when the body is posed, staged, or left in other unusual positions. Whereas posed bodies are more likely to include sexual assault, often in serial murders, there is no evidence of either in the staged cases. Lastly, when a body is left in an unusual position, binding is more likely, as well as the use of more "hands on" means of killing the victim, such as stabbing or cutting weapons, bludgeons, ligatures, or hands and feet.

Redesign lifts prep output 288%

Energy Technology Data Exchange (ETDEWEB)

Hamric, J

1987-02-01

This paper outlines the application of engineering creativity and how it brought output at an Ohio coal preparation plant up from 12,500 tpd to nearly four times that figure, 48,610 tpd. By streamlining the conveyor systems, removing surplus belt length and repositioning subplants the whole operation was able to run far more efficiently with a greater output. Various other alterations including the raw material supply and management and operating practices were also undertaken to provide a test for the achievements possible with such reorganization. The new developments have been in the following fields: fine coal cleaning, heavy media cyclones, feeders, bins, filter presses, dewatering equipment and settling tanks. Output is now limited only by the reduced demand by the Gavin power station nearby.

Output Information Based Fault-Tolerant Iterative Learning Control for Dual-Rate Sampling Process with Disturbances and Output Delay

Directory of Open Access Journals (Sweden)

Hongfeng Tao

2018-01-01

Full Text Available For a class of single-input single-output (SISO dual-rate sampling processes with disturbances and output delay, this paper presents a robust fault-tolerant iterative learning control algorithm based on output information. Firstly, the dual-rate sampling process with output delay is transformed into discrete system in state-space model form with slow sampling rate without time delay by using lifting technology; then output information based fault-tolerant iterative learning control scheme is designed and the control process is turned into an equivalent two-dimensional (2D repetitive process. Moreover, based on the repetitive process stability theory, the sufficient conditions for the stability of system and the design method of robust controller are given in terms of linear matrix inequalities (LMIs technique. Finally, the flow control simulations of two flow tanks in series demonstrate the feasibility and effectiveness of the proposed method.

Multi-decadal Variability of the Wind Power Output

Science.gov (United States)

Kirchner Bossi, Nicolas; García-Herrera, Ricardo; Prieto, Luis; Trigo, Ricardo M.

2014-05-01

parameters of the Weibull PDF. This allowed us to derive a linear model to estimate the annual power output from those parameters, which results especially useful when no wind power data is available.

CMAQ Model Output

Data.gov (United States)

U.S. Environmental Protection Agency — CMAQ and CMAQ-VBS model output. This dataset is not publicly accessible because: Files too large. It can be accessed through the following means: via EPA's NCC tape...

The response of a linear monostable system and its application in parameters estimation for PSK signals

International Nuclear Information System (INIS)

Duan, Chaowei; Zhan, Yafeng

2016-01-01

The output characteristics of a linear monostable system driven with a periodic signal and an additive white Gaussian noise are studied in this paper. Theoretical analysis shows that the output signal-to-noise ratio (SNR) decreases monotonously with the increasing noise intensity but the output SNR-gain is stable. Inspired by this high SNR-gain phenomenon, this paper applies the linear monostable system in the parameters estimation algorithm for phase shift keying (PSK) signals and improves the estimation performance. - Highlights: • The response of a linear monostable system driven with a periodic signal and an additive white Gaussian noise is analyzed. • The optimal parameter of this linear monostable system to maximum the output SNR-gain is obtained. • Application of this linear monostable system in parameters estimation algorithm for PSK signals obtains performance improvement.